how to write a research question social work

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Matthew DeCarlo

Chapter Outline

• Empirical vs. ethical questions (4 minute read)
• Characteristics of a good research question (4 minute read)
• Quantitative research questions (7 minute read)
• Qualitative research questions (3 minute read)
• Evaluating and updating your research questions (4 minute read)

Content warning: examples in this chapter include references to sexual violence, sexism, substance use disorders, homelessness, domestic violence, the child welfare system, cissexism and heterosexism, and truancy and school discipline.

9.1 Empirical vs. ethical questions

Learning objectives.

Learners will be able to…

• Define empirical questions and provide an example
• Define ethical questions and provide an example

Writing a good research question is an art and a science. It is a science because you have to make sure it is clear, concise, and well-developed. It is an art because often your language needs “wordsmithing” to perfect and clarify the meaning. This is an exciting part of the research process; however, it can also be one of the most stressful.

Creating a good research question begins by identifying a topic you are interested in studying. At this point, you already have a working question. You’ve been applying it to the exercises in each chapter, and after reading more about your topic in the scholarly literature, you’ve probably gone back and revised your working question a few times. We’re going to continue that process in more detail in this chapter. Keep in mind that writing research questions is an iterative process, with revisions happening week after week until you are ready to start your project.

Empirical vs. ethical questions

When it comes to research questions, social science is best equipped to answer empirical questions —those that can be answered by real experience in the real world—as opposed to  ethical questions —questions about which people have moral opinions and that may not be answerable in reference to the real world. While social workers have explicit ethical obligations (e.g., service, social justice), research projects ask empirical questions to help actualize and support the work of upholding those ethical principles.

In order to help you better understand the difference between ethical and empirical questions, let’s consider a topic about which people have moral opinions. How about SpongeBob SquarePants? [1] In early 2005, members of the conservative Christian group Focus on the Family (2005) [2] denounced this seemingly innocuous cartoon character as “morally offensive” because they perceived his character to be one that promotes a “pro-gay agenda.” Focus on the Family supported their claim that SpongeBob is immoral by citing his appearance in a children’s video designed to promote tolerance of all family forms (BBC News, 2005). [3] They also cited SpongeBob’s regular hand-holding with his male sidekick Patrick as further evidence of his immorality.

So, can we now conclude that SpongeBob SquarePants is immoral? Not so fast. While your mother or a newspaper or television reporter may provide an answer, a social science researcher cannot. Questions of morality are ethical, not empirical. Of course, this doesn’t mean that social science researchers cannot study opinions about or social meanings surrounding SpongeBob SquarePants (Carter, 2010). [4] We study humans after all, and as you will discover in the following chapters of this textbook, we are trained to utilize a variety of scientific data-collection techniques to understand patterns of human beliefs and behaviors. Using these techniques, we could find out how many people in the United States find SpongeBob morally reprehensible, but we could never learn, empirically, whether SpongeBob is in fact morally reprehensible.

Let’s consider an example from a recent MSW research class I taught. A student group wanted to research the penalties for sexual assault. Their original research question was: “How can prison sentences for sexual assault be so much lower than the penalty for drug possession?” Outside of the research context, that is a darn good question! It speaks to how the War on Drugs and the patriarchy have distorted the criminal justice system towards policing of drug crimes over gender-based violence.

Unfortunately, it is an ethical question, not an empirical one. To answer that question, you would have to draw on philosophy and morality, answering what it is about human nature and society that allows such unjust outcomes. However, you could not answer that question by gathering data about people in the real world. If I asked people that question, they would likely give me their opinions about drugs, gender-based violence, and the criminal justice system. But I wouldn’t get the real answer about why our society tolerates such an imbalance in punishment.

As the students worked on the project through the semester, they continued to focus on the topic of sexual assault in the criminal justice system. Their research question became more empirical because they read more empirical articles about their topic. One option that they considered was to evaluate intervention programs for perpetrators of sexual assault to see if they reduced the likelihood of committing sexual assault again. Another option they considered was seeing if counties or states with higher than average jail sentences for sexual assault perpetrators had lower rates of re-offense for sexual assault. These projects addressed the ethical question of punishing perpetrators of sexual violence but did so in a way that gathered and analyzed empirical real-world data. Our job as social work researchers is to gather social facts about social work issues, not to judge or determine morality.

Key Takeaways

• Empirical questions are distinct from ethical questions.
• There are usually a number of ethical questions and a number of empirical questions that could be asked about any single topic.
• While social workers may research topics about which people have moral opinions, a researcher’s job is to gather and analyze empirical data.
• Take a look at your working question. Make sure you have an empirical question, not an ethical one. To perform this check, describe how you could find an answer to your question by conducting a study, like a survey or focus group, with real people.

9.2 Characteristics of a good research question

• Identify and explain the key features of a good research question
• Explain why it is important for social workers to be focused and clear with the language they use in their research questions

Now that you’ve made sure your working question is empirical, you need to revise that working question into a formal research question. So, what makes a good research question? First, it is generally written in the form of a question. To say that your research question is “the opioid epidemic” or “animal assisted therapy” or “oppression” would not be correct. You need to frame your topic as a question, not a statement. A good research question is also one that is well-focused. A well-focused question helps you tune out irrelevant information and not try to answer everything about the world all at once. You could be the most eloquent writer in your class, or even in the world, but if the research question about which you are writing is unclear, your work will ultimately lack direction.

In addition to being written in the form of a question and being well-focused, a good research question is one that cannot be answered with a simple yes or no. For example, if your interest is in gender norms, you could ask, “Does gender affect a person’s performance of household tasks?” but you will have nothing left to say once you discover your yes or no answer. Instead, why not ask, about the relationship between gender and household tasks. Alternatively, maybe we are interested in how or to what extent gender affects a person’s contributions to housework in a marriage? By tweaking your question in this small way, you suddenly have a much more fascinating question and more to say as you attempt to answer it.

A good research question should also have more than one plausible answer. In the example above, the student who studied the relationship between gender and household tasks had a specific interest in the impact of gender, but she also knew that preferences might be impacted by other factors. For example, she knew from her own experience that her more traditional and socially conservative friends were more likely to see household tasks as part of the female domain, and were less likely to expect their male partners to contribute to those tasks. Thinking through the possible relationships between gender, culture, and household tasks led that student to realize that there were many plausible answers to her questions about how  gender affects a person’s contribution to household tasks. Because gender doesn’t exist in a vacuum, she wisely felt that she needed to consider other characteristics that work together with gender to shape people’s behaviors, likes, and dislikes. By doing this, the student considered the third feature of a good research question–she thought about relationships between several concepts. While she began with an interest in a single concept—household tasks—by asking herself what other concepts (such as gender or political orientation) might be related to her original interest, she was able to form a question that considered the relationships  among  those concepts.

This student had one final component to consider. Social work research questions must contain a target population. Her study would be very different if she were to conduct it on older adults or immigrants who just arrived in a new country. The target population is the group of people whose needs your study addresses. Maybe the student noticed issues with household tasks as part of her social work practice with first-generation immigrants, and so she made it her target population. Maybe she wants to address the needs of another community. Whatever the case, the target population should be chosen while keeping in mind social work’s responsibility to work on behalf of marginalized and oppressed groups.

In sum, a good research question generally has the following features:

• It is written in the form of a question
• It is clearly written
• It cannot be answered with “yes” or “no”
• It has more than one plausible answer
• It considers relationships among multiple variables
• It is specific and clear about the concepts it addresses
• It includes a target population
• A poorly focused research question can lead to the demise of an otherwise well-executed study.
• Research questions should be clearly worded, consider relationships between multiple variables, have more than one plausible answer, and address the needs of a target population.

Okay, it’s time to write out your first draft of a research question.

• Once you’ve done so, take a look at the checklist in this chapter and see if your research question meets the criteria to be a good one.

Brainstorm whether your research question might be better suited to quantitative or qualitative methods.

• Describe why your question fits better with quantitative or qualitative methods.
• Provide an alternative research question that fits with the other type of research method.

9.3 Quantitative research questions

• Describe how research questions for exploratory, descriptive, and explanatory quantitative questions differ and how to phrase them
• Identify the differences between and provide examples of strong and weak explanatory research questions

Quantitative descriptive questions

The type of research you are conducting will impact the research question that you ask. Probably the easiest questions to think of are quantitative descriptive questions. For example, “What is the average student debt load of MSW students?” is a descriptive question—and an important one. We aren’t trying to build a causal relationship here. We’re simply trying to describe how much debt MSW students carry. Quantitative descriptive questions like this one are helpful in social work practice as part of community scans, in which human service agencies survey the various needs of the community they serve. If the scan reveals that the community requires more services related to housing, child care, or day treatment for people with disabilities, a nonprofit office can use the community scan to create new programs that meet a defined community need.

Quantitative descriptive questions will often ask for percentage, count the number of instances of a phenomenon, or determine an average. Descriptive questions may only include one variable, such as ours about student debt load, or they may include multiple variables. Because these are descriptive questions, our purpose is not to investigate causal relationships between variables. To do that, we need to use a quantitative explanatory question.

Quantitative explanatory questions

Most studies you read in the academic literature will be quantitative and explanatory. Why is that? If you recall from Chapter 2 , explanatory research tries to build nomothetic causal relationships. They are generalizable across space and time, so they are applicable to a wide audience. The editorial board of a journal wants to make sure their content will be useful to as many people as possible, so it’s not surprising that quantitative research dominates the academic literature.

Structurally, quantitative explanatory questions must contain an independent variable and dependent variable. Questions should ask about the relationship between these variables. The standard format I was taught in graduate school for an explanatory quantitative research question is: “What is the relationship between [independent variable] and [dependent variable] for [target population]?” You should play with the wording for your research question, revising that standard format to match what you really want to know about your topic.

Let’s take a look at a few more examples of possible research questions and consider the relative strengths and weaknesses of each. Table 9.1 does just that. While reading the table, keep in mind that I have only noted what I view to be the most relevant strengths and weaknesses of each question. Certainly each question may have additional strengths and weaknesses not noted in the table. Each of these questions is drawn from student projects in my research methods classes and reflects the work of many students on their research question over many weeks.

Making it more specific

A good research question should also be specific and clear about the concepts it addresses. A student investigating gender and household tasks knows what they mean by “household tasks.” You likely also have an impression of what “household tasks” means. But are your definition and the student’s definition the same? A participant in their study may think that managing finances and performing home maintenance are household tasks, but the researcher may be interested in other tasks like childcare or cleaning. The only way to ensure your study stays focused and clear is to be specific about what you mean by a concept. The student in our example could pick a specific household task that was interesting to them or that the literature indicated was important—for example, childcare. Or, the student could have a broader view of household tasks, one that encompasses childcare, food preparation, financial management, home repair, and care for relatives. Any option is probably okay, as long as the researcher is clear on what they mean by “household tasks.” Clarifying these distinctions is important as we look ahead to specifying how your variables will be measured in Chapter 11 .

Table 9.2 contains some “watch words” that indicate you may need to be more specific about the concepts in your research question.

It can be challenging to be this specific in social work research, particularly when you are just starting out your project and still reading the literature. If you’ve only read one or two articles on your topic, it can be hard to know what you are interested in studying. Broad questions like “What are the causes of chronic homelessness, and what can be done to prevent it?” are common at the beginning stages of a research project as working questions. However, moving from working questions to research questions in your research proposal requires that you examine the literature on the topic and refine your question over time to be more specific and clear. Perhaps you want to study the effect of a specific anti-homelessness program that you found in the literature. Maybe there is a particular model to fighting homelessness, like Housing First or transitional housing, that you want to investigate further. You may want to focus on a potential cause of homelessness such as LGBTQ+ discrimination that you find interesting or relevant to your practice. As you can see, the possibilities for making your question more specific are almost infinite.

Quantitative exploratory questions

In exploratory research, the researcher doesn’t quite know the lay of the land yet. If someone is proposing to conduct an exploratory quantitative project, the watch words highlighted in Table 9.2 are not problematic at all. In fact, questions such as “What factors influence the removal of children in child welfare cases?” are good because they will explore a variety of factors or causes. In this question, the independent variable is less clearly written, but the dependent variable, family preservation outcomes, is quite clearly written. The inverse can also be true. If we were to ask, “What outcomes are associated with family preservation services in child welfare?”, we would have a clear independent variable, family preservation services, but an unclear dependent variable, outcomes. Because we are only conducting exploratory research on a topic, we may not have an idea of what concepts may comprise our “outcomes” or “factors.” Only after interacting with our participants will we be able to understand which concepts are important.

Remember that exploratory research is appropriate only when the researcher does not know much about topic because there is very little scholarly research. In our examples above, there is extensive literature on the outcomes in family reunification programs and risk factors for child removal in child welfare. Make sure you’ve done a thorough literature review to ensure there is little relevant research to guide you towards a more explanatory question.

• Descriptive quantitative research questions are helpful for community scans but cannot investigate causal relationships between variables.
• Explanatory quantitative research questions must include an independent and dependent variable.
• Exploratory quantitative research questions should only be considered when there is very little previous research on your topic.
• Identify the type of research you are engaged in (descriptive, explanatory, or exploratory).
• Create a quantitative research question for your project that matches with the type of research you are engaged in.

Preferably, you should be creating an explanatory research question for quantitative research.

9.4 Qualitative research questions

• List the key terms associated with qualitative research questions
• Distinguish between qualitative and quantitative research questions

Qualitative research questions differ from quantitative research questions. Because qualitative research questions seek to explore or describe phenomena, not provide a neat nomothetic explanation, they are often more general and openly worded. They may include only one concept, though many include more than one. Instead of asking how one variable causes changes in another, we are instead trying to understand the experiences ,  understandings , and  meanings that people have about the concepts in our research question. These keywords often make an appearance in qualitative research questions.

Let’s work through an example from our last section. In Table 9.1, a student asked, “What is the relationship between sexual orientation or gender identity and homelessness for late adolescents in foster care?” In this question, it is pretty clear that the student believes that adolescents in foster care who identify as LGBTQ+ may be at greater risk for homelessness. This is a nomothetic causal relationship—LGBTQ+ status causes changes in homelessness.

However, what if the student were less interested in  predicting  homelessness based on LGBTQ+ status and more interested in  understanding  the stories of foster care youth who identify as LGBTQ+ and may be at risk for homelessness? In that case, the researcher would be building an idiographic causal explanation . The youths whom the researcher interviews may share stories of how their foster families, caseworkers, and others treated them. They may share stories about how they thought of their own sexuality or gender identity and how it changed over time. They may have different ideas about what it means to transition out of foster care.

Because qualitative questions usually center on idiographic causal relationships, they look different than quantitative questions. Table 9.3 below takes the final research questions from Table 9.1 and adapts them for qualitative research. The guidelines for research questions previously described in this chapter still apply, but there are some new elements to qualitative research questions that are not present in quantitative questions.

• Qualitative research questions often ask about lived experience, personal experience, understanding, meaning, and stories.
• Qualitative research questions may be more general and less specific.
• Qualitative research questions may also contain only one variable, rather than asking about relationships between multiple variables.

Qualitative research questions have one final feature that distinguishes them from quantitative research questions: they can change over the course of a study. Qualitative research is a reflexive process, one in which the researcher adapts their approach based on what participants say and do. The researcher must constantly evaluate whether their question is important and relevant to the participants. As the researcher gains information from participants, it is normal for the focus of the inquiry to shift.

For example, a qualitative researcher may want to study how a new truancy rule impacts youth at risk of expulsion. However, after interviewing some of the youth in their community, a researcher might find that the rule is actually irrelevant to their behavior and thoughts. Instead, their participants will direct the discussion to their frustration with the school administrators or the lack of job opportunities in the area. This is a natural part of qualitative research, and it is normal for research questions and hypothesis to evolve based on information gleaned from participants.

However, this reflexivity and openness unacceptable in quantitative research for good reasons. Researchers using quantitative methods are testing a hypothesis, and if they could revise that hypothesis to match what they found, they could never be wrong! Indeed, an important component of open science and reproducability is the preregistration of a researcher’s hypotheses and data analysis plan in a central repository that can be verified and replicated by reviewers and other researchers. This interactive graphic from 538 shows how an unscrupulous research could come up with a hypothesis and theoretical explanation  after collecting data by hunting for a combination of factors that results in a statistically significant relationship. This is an excellent example of how the positivist assumptions behind quantitative research and intepretivist assumptions behind qualitative research result in different approaches to social science.

• Qualitative research questions often contain words or phrases like “lived experience,” “personal experience,” “understanding,” “meaning,” and “stories.”
• Qualitative research questions can change and evolve over the course of the study.
• Using the guidance in this chapter, write a qualitative research question. You may want to use some of the keywords mentioned above.

9.5 Evaluating and updating your research questions

• Evaluate the feasibility and importance of your research questions
• Begin to match your research questions to specific designs that determine what the participants in your study will do

Feasibility and importance

As you are getting ready to finalize your research question and move into designing your research study, it is important to check whether your research question is feasible for you to answer and what importance your results will have in the community, among your participants, and in the scientific literature

Key questions to consider when evaluating your question’s feasibility include:

• Do you have access to the data you need?
• Will you be able to get consent from stakeholders, gatekeepers, and others?
• Does your project pose risk to individuals through direct harm, dual relationships, or breaches in confidentiality? (see Chapter 6 for more ethical considerations)
• Are you competent enough to complete the study?
• Do you have the resources and time needed to carry out the project?

Key questions to consider when evaluating the importance of your question include:

• Can we answer your research question simply by looking at the literature on your topic?
• How does your question add something new to the scholarly literature? (raises a new issue, addresses a controversy, studies a new population, etc.)
• How will your target population benefit, once you answer your research question?
• How will the community, social work practice, and the broader social world benefit, once you answer your research question?
• Using the questions above, check whether you think your project is feasible for you to complete, given the constrains that student projects face.
• Realistically, explore the potential impact of your project on the community and in the scientific literature. Make sure your question cannot be answered by simply reading more about your topic.

Matching your research question and study design

This chapter described how to create a good quantitative and qualitative research question. In Parts 3 and 4 of this textbook, we will detail some of the basic designs like surveys and interviews that social scientists use to answer their research questions. But which design should you choose?

As with most things, it all depends on your research question. If your research question involves, for example, testing a new intervention, you will likely want to use an experimental design. On the other hand, if you want to know the lived experience of people in a public housing building, you probably want to use an interview or focus group design.

We will learn more about each one of these designs in the remainder of this textbook. We will also learn about using data that already exists, studying an individual client inside clinical practice, and evaluating programs, which are other examples of designs. Below is a list of designs we will cover in this textbook:

• Surveys: online, phone, mail, in-person
• Experiments: classic, pre-experiments, quasi-experiments
• Interviews: in-person or via phone or videoconference
• Focus groups: in-person or via videoconference
• Content analysis of existing data
• Secondary data analysis of another researcher’s data
• Program evaluation

The design of your research study determines what you and your participants will do. In an experiment, for example, the researcher will introduce a stimulus or treatment to participants and measure their responses. In contrast, a content analysis may not have participants at all, and the researcher may simply read the marketing materials for a corporation or look at a politician’s speeches to conduct the data analysis for the study.

I imagine that a content analysis probably seems easier to accomplish than an experiment. However, as a researcher, you have to choose a research design that makes sense for your question and that is feasible to complete with the resources you have. All research projects require some resources to accomplish. Make sure your design is one you can carry out with the resources (time, money, staff, etc.) that you have.

There are so many different designs that exist in the social science literature that it would be impossible to include them all in this textbook. The purpose of the subsequent chapters is to help you understand the basic designs upon which these more advanced designs are built. As you learn more about research design, you will likely find yourself revising your research question to make sure it fits with the design. At the same time, your research question as it exists now should influence the design you end up choosing. There is no set order in which these should happen. Instead, your research project should be guided by whether you can feasibly carry it out and contribute new and important knowledge to the world.

• Research questions must be feasible and important.
• Research questions must match study design.
• Based on what you know about designs like surveys, experiments, and interviews, describe how you might use one of them to answer your research question.
• You may want to refer back to Chapter 2 which discusses how to get raw data about your topic and the common designs used in student research projects.
• Not familiar with SpongeBob SquarePants? You can learn more about him on Nickelodeon’s site dedicated to all things SpongeBob:  http://www.nick.com/spongebob-squarepants/ ↵
• Focus on the Family. (2005, January 26). Focus on SpongeBob.  Christianity Today . Retrieved from  http://www.christianitytoday.com/ct/2005/januaryweb-only/34.0c.html ↵
• BBC News. (2005, January 20). US right attacks SpongeBob video. Retrieved from:  http://news.bbc.co.uk/2/hi/americas/4190699.stm ↵
• In fact, an MA thesis examines representations of gender and relationships in the cartoon: Carter, A. C. (2010).  Constructing gender and   relationships in “SpongeBob SquarePants”: Who lives in a pineapple under the sea . MA thesis, Department of Communication, University of South Alabama, Mobile, AL. ↵
• Writing from an outline (10 minute read plus an 8 minute video, and then a 15 minute video)
• Writing your literature review (30 minute read)

Content warning: TBA

6.1: Writing from an outline

Learners will be able to...

• Integrate facts from the literature into scholarly writing
• Experiment with different approaches to integrating information that do not involve direct quotations from other authors

Congratulations! By now, you should have discovered, retrieved, evaluated, synthesized, and organized the information you need for your literature review. It’s now time to turn that stack of articles, papers, and notes into a literature review–it’s time to start writing!

The first step in research writing is outlining. In Chapter 4, we reviewed how to build a topical outline using quotations and facts from other authors. Use that outline (or one you write now) as a way to organize your thoughts.

Watch this video from Nicholas Cifuentes-Goodbody on Outlining . As he highlights, outlining is like building a mise en place before a meal--arranging your ingredients in an orderly way so you can create your masterpiece.

From quotations to original writing

Much like combining ingredients on a kitchen countertop, you will need to mix your ingredients together. That means you will not be relying extensively on quotations from other authors in your literature review. In moving from an outline to a literature review, the key intellectual move is relying on your own ideas about the literature, rather than quoting extensively from other sources.

Integrating ideas from other authors

Watch this video from Nicholas Cifuentes-Goodbody on using quotations in academic writing . In the video, he reviews a few different techniques to integrate quotations or ideas from other authors into your writing. All literature reviews use the ideas from other authors, but it's important not to overuse others' words. Your literature review is evaluated by your professor based on how well it shows  you are able to make connections between different facts in the scientific literature. The examples in this section should highlight how to get other people's words out of the way of your own. Use these strategies to diversify your writing and show your readers how your sources contributed to your work.

1. Make a claim without a quote

Claim ( Citation )

Some view cities as the storehouse of culture and creativity, and propose that urbanization is a consequence of the attractiveness of these social benefits ( Mumford, 1961 ).

More information

Oftentimes you do not need to directly quote a source to convey its conclusions or arguments – and some disciplines discourage quoting directly! Rather you can paraphrase the main point of a paper in your own words and provide an in-text citation. A benefit of using this strategy is that you can offer support for a claim without using a whole paragraph to introduce and frame a quote. You should make sure that you fully understand the paper's argument and that you are following university citation guidelines before attempting to paraphrase something from a paper.

2. Make a claim that is supported by two or more sources:

Claim ( Citation 1 ; Citation 2 ).

Reviews of this literature concede difficulty in making direct comparisons of emission levels across different sets of analysis ( Bader and Bleischwitz, 2009 ; Kennedy et al., 2009 ; Ramaswami et al., 2012 ).

Sometimes multiple sources support your claim, or there are two major publications that deserve credit for providing evidence on a topic. This is a perfect time to use multiple citations. You can cite two, three, or more sources in a single sentence!

Make a claim that has been supported in multiple contexts:

Context 1 ( Citation ), Context 2 ( Citation ), Context 3 ( Citation ).

These results are supported by more recent research on transportation energy consumption ( Liddle, 2014 ), electricity consumption in buildings ( Lariviere and Lafrance, 1999 ), and overall urban GHG emissions ( Marcotullio et al., 2013b ).

More information:

Use this citation strategy when you want to show that a body of research has found support for some claim across several different contexts. This can show the robustness of an effect or phenomenon and can give your claim some added validity

3. Quote important or unique terms

Claim " Term " ( Citation ).

The spatial implications of this thinking are manifest in the " concentric ring model " of urban expansion and its variants ( Harris and Ullman, 1945 ).

While block or even whole-sentence citations are rare in most research papers in the science and social science disciplines, there is often a need to quote specific terms or phrases that were first coined by a certain source or that were well-explained in a specific paper.

4. Quoting definitions

Contextualize quote , " important word or phrase ."

Role conflict is defined as "A situation in which contradictory, competing, or incompatible expectations are placed on an individual by two or more roles held at the same time" (Open Sociology Dictionary, 2023); whereas, role strain is defined as "a situation caused by higher-than-expected demands placed on an individual performing a specific role that leads to difficulty or stress" (Open Sociology Dictionary, 2023). In our study, we hypothesize that caregivers who reenter higher education experience role conflict between school work, paid work, and care work. Further, we hypothesize that this conflict is greater in individuals who had experienced role strain in employment or caregiving prior to entering college.

A direct quotation can bring attention to specific language in your source. When someone puts something perfectly, you can use a quotation to convey the identical meaning in your work. Definitions are an excellent example of when to use a quotation. In other cases, there may be quotations from important thinkers, clients or community members, and others whose specific wording is important.

I encourage you to use few, if any, direct quotations in your literature review. Personally, I think most students are scared of looking stupid and would rather use a good quotation than risk not getting it right. If you are a student who considers themselves a strong writer, this may not sound relevant to you. However, I'm willing to bet that there are many of your peers for whom this describes a particular bit of research anxiety.

When using quotations, make sure to only include the parts of the quotation that are necessary. You do not need to use quotation marks for statistics you use. And I encourage you to find ways to put others' statistics in  your sentences.

Why share information from other sources?

Now that you know some different sentence structures using APA citations, let's examine the purpose behind why you are sharing information from another source. Cited evidence can serve a wide range of purposes in academic papers. These examples will give you an idea of the different ways that you can use citations in your paper.

1. Summarize your source

The studies of Newman and Kenworthy ( 1989, 1999 ) demonstrate a negative relationship between population density and transportation fuel use .

You will help your reader understand your points better if you summarize the key points of a study. Describe the strengths or weaknesses a specific source that has been pivotal in your field. Describe the source's specific methodology, theory, or approach. Be sure to still include a citation. If you mention the name of the author in your text, you still need to provide the date of the study in a parenthetical citation.

2. Cite a method

Despite the popularity of the WUP indicators , they have been routinely criticized because the methodology relies on local- and country-specific definitions of bounding urban areas, resulting in of ten incomparable and widely divergent definitions of the population, density thresholds, or administrative/political units designated ( Satterthwaite, 2007 ).

This is an easy way to give credit to a source that has provided some evidence for the validity of a method or questionnaire. Readers can reference your citation if they are interested in knowing more about the method and its standing in the current literature.

3. Compare sources

Some evidence for this scaling relationship suggests that urban areas with larger population sizes have proportionally smaller energy infrastructures than smaller cities ( Bettencourt et al., 2007 ; Fragkias et al., 2013 ). Other evidence suggests that GHG emissions may increase more than proportionally to population size, such that larger cities exhibit proportionally higher energy demand as they grow than do smaller cities ( Marcotullio et al., 2013 ).

This is one of the most important techniques for creating an effective literature review. This allows you and your readers to consider controversies and discrepancies among the current literature, revealing gaps in the literature or points of contention for further study.

The examples in this guide come from:

Marcotullio, P. J., Hughes, S., Sarzynski, A., Pincetl, S., Sanchez Peña, L., Romero-Lankao, P., Runfola, D. and Seto, K. C. (2014), Urbanization and the carbon cycle: Contributions from social science. Earth's Future, 2: 496–514. doi:10.1002/2014EF000257

Avoiding plagiarism

The most difficult thing about avoiding plagiarism is that reading so much of other people's ideas can make them seem like your own after a while. We recommend you work through this interactive activity on determining how and when to cite other authors.

• Research writing requires outlining, which helps you arrange your facts neatly before writing. It's similar to arranging all of your ingredients before you start cooking.
• Eliminate quotations from your writing as much as possible. Your literature review needs to be your analysis of the literature, not just a summary of other people's good ideas.
• Experiment with the prompts in this chapter as you begin to write your research question. 

6.2 Writing your literature review

• Describe the components of a literature review
• Begin to write your literature review
• Identify the purpose of a problem statement
• Apply the components of a formal argument to your topic
• Use elements of formal writing style, including signposting and transitions
• Recognize commons errors in literature reviews

Writing about research is different than other types of writing. Research writing is not like a journal entry or opinion paper. The goal here is not to apply your research question to your life or growth as a practitioner. Research writing is about the provision and interpretation of facts. The tone should be objective and unbiased, and personal experiences and opinions are excluded. Particularly for students who are used to writing case notes, research writing can be a challenge. That's why its important to normalize getting help! If your professor has not built in peer review, consider setting up a peer review group among your peers. You should also reach out to your academic advisor to see if there are writing services on your campus available to graduate students. No one should feel bad for needing help with something they haven't done before, haven't done in a while, or were never taught how to do. 

If you’ve followed the steps in this chapter, you likely have an outline, summary table, and concept map from which you can begin the writing process. But what do you need to include in your literature review? We’ve mentioned it before, but to summarize, a literature review should:

• Introduce the topic and define its key terms.
• Establish the importance of the topic.
• Provide an overview of the important literature related to the concepts found in the research question.
• Identify gaps or controversies in the literature.
• Point out consistent findings across studies.
• Synthesize that which is known about a topic, rather than just provide a summary of the articles you read.
• Discuss possible implications and directions for future research.

Do you have enough facts and sources to accomplish these tasks? It’s a good time to consult your outlines and notes on each article you plan to include in your literature review. You may also want to consult with your professor on what is expected of you. If there is something you are missing, you may want to jump back to section 2.3 where we discussed how to search for literature. While you can always fill in material, there is the danger that you will start writing without really knowing what you are talking about or what you want to say. For example, if you don’t have a solid definition of your key concepts or a sense of how the literature has developed over time, it will be difficult to make coherent scholarly claims about your topic.

There is no magical point at which one is ready to write. As you consider whether you are ready, it may be useful to ask yourself these questions:

• How will my literature review be organized?
• What section headings will I be using?
• How do the various studies relate to each other?
• What contributions do they make to the field?
• Where are the gaps or limitations in existing research?
• And finally, but most importantly, how does my own research fit into what has already been done?

The problem statement

Scholarly works often begin with a problem statement, which serves two functions. First, it establishes why your topic is a social problem worth studying. Second, it pulls your reader into the literature review. Who would want to read about something unimportant?

A problem statement generally answers the following questions, though these are far from exhaustive:

• Why is this an important problem to study?
• How many people are affected by this problem?
• How does this problem impact other social issues relevant to social work?
• Why is your target population an important one to study?

A strong problem statement, like the rest of your literature review, should be filled with empirical results, theory, and arguments based on the extant literature. A research proposal differs significantly from other more reflective essays you’ve likely completed during your social work studies. If your topic were domestic violence in rural Appalachia, I’m sure you could come up with answers to the above questions without looking at a single source. However, the purpose of the literature review is not to test your intuition, personal experience, or empathy. Instead, research methods are about gaining specific and articulable knowledge to inform action. With a problem statement, you can take a “boring” topic like the color of rooms used in an inpatient psychiatric facility, transportation patterns in major cities, or the materials used to manufacture baby bottles, and help others see the topic as you see it—an important part of the social world that impacts social work practice.

The structure of a literature review

In general, the problem statement belongs at the beginning of the literature review. We usually advise students to spend no more than a paragraph or two for a problem statement. For the rest of your literature review, there is no set formula by which it needs to be organized. However, a literature review generally follows the format of any other essay—Introduction, Body, and Conclusion.

The introduction to the literature review contains a statement or statements about the overall topic. At a minimum, the introduction should define or identify the general topic, issue, or area of concern. You might consider presenting historical background, mentioning the results of a seminal study, and providing definitions of important terms. The introduction may also point to overall trends in what has been previously published on the topic or on conflicts in theory, methodology, evidence, conclusions, or gaps in research and scholarship. We also suggest putting in a few sentences that walk the reader through the rest of the literature review. Highlight your main arguments from the body of the literature review and preview your conclusion. An introduction should let the reader know what to expect from the rest of your review.

The body of your literature review is where you demonstrate your synthesis and analysis of the literature. Again, do not just summarize the literature. We would also caution against organizing your literature review by source—that is, one paragraph for source A, one paragraph for source B, etc. That structure will likely provide an adequate summary of the literature you’ve found, but it would give you almost no synthesis of the literature. That approach doesn’t tell your reader how to put those facts together, it doesn't highlight points of agreement or contention, or how each study builds on the work of others. In short, it does not demonstrate critical thinking.

Organize your review by argument

Instead, use your outlines and notes as a guide what you have to say about the important topics you need to cover. Literature reviews are written from the perspective of an expert in that field. After an exhaustive literature review, you should feel as though you are able to make strong claims about what is true—so make them! There is no need to hide behind “I believe” or “I think.” Put your voice out in front, loud and proud! But make sure you have facts and sources that back up your claims.

I’ve used the term “ argument ” here in a specific way. An argument in writing means more than simply disagreeing with what someone else said, as this classic Monty Python sketch demonstrates. Toulman, Rieke, and Janik (1984) identify six elements of an argument:

• Claim: the thesis statement—what you are trying to prove
• Grounds: theoretical or empirical evidence that supports your claim
• Warrant: your reasoning (rule or principle) connecting the claim and its grounds
• Backing: further facts used to support or legitimize the warrant
• Qualifier: acknowledging that the argument may not be true for all cases
• Rebuttal: considering both sides (as cited in Burnette, 2012) [1]

Let’s walk through an example. If I were writing a literature review on a negative income tax, a policy in which people in poverty receive an unconditional cash stipend from the government each month equal to the federal poverty level, I would want to lay out the following:

• Claim: the negative income tax is superior to other forms of anti-poverty assistance.
• Grounds: data comparing negative income tax recipients to people receiving anti-poverty assistance in existing programs, theory supporting a negative income tax, data from evaluations of existing anti-poverty programs, etc.
• Warrant: cash-based programs like the negative income tax are superior to existing anti-poverty programs because they allow the recipient greater self-determination over how to spend their money.
• Backing: data demonstrating the beneficial effects of self-determination on people in poverty.
• Qualifier: the negative income tax does not provide taxpayers and voters with enough control to make sure people in poverty are not wasting financial assistance on frivolous items.
• Rebuttal: policy should be about empowering the oppressed, not protecting the taxpayer, and there are ways of addressing taxpayer spending concerns through policy design.

Like any effective argument, your literature review must have some kind of structure. For example, it might begin by describing a phenomenon in a general way along with several studies that provide some detail, then describing two or more competing theories of the phenomenon, and finally presenting a hypothesis to test one or more of the theories. Or, it might describe one phenomenon, then describe another that seems inconsistent with the first, then propose a theory that resolves the inconsistency, and finally present a hypothesis to test that theory. In applied research, it might describe a phenomenon or theory, then describe how that phenomenon or theory applies to some important real-world situation, and finally, may suggest a way to test whether it does, in fact, apply to that situation.

Use signposts

Another important issue is  signposting . It may not be a term you are familiar with, but you are likely familiar with the concept. Signposting refers to the words used to identify the organization and structure of your literature review to your reader. The most basic form of signposting is using a topic sentence at the beginning of each paragraph. A topic sentence introduces the argument you plan to make in that paragraph. For example, you might start a paragraph stating, “There is strong disagreement in the literature as to whether psychedelic drugs cause people to develop psychotic disorders, or whether psychotic disorders cause people to use psychedelic drugs.” Within that paragraph, your reader would likely assume you will present evidence for both arguments. The concluding sentence of your paragraph should address the topic sentence, discussing how the facts and arguments from the paragraph you've written support a specific conclusion. To continue with our example, I might say, “There is likely a reciprocal effect in which both the use of psychedelic drugs worsens pre-psychotic symptoms and worsening psychosis increases the desire to use psychedelic drugs.”

Signposting also involves using headings and subheadings. Your literature review will use APA formatting, which means you need to follow their rules for bolding, capitalization, italicization, and indentation of headings. Headings help your reader understand the structure of your literature review. They can also help if the reader gets lost and needs to re-orient themselves within the document. We often tell our students to assume we know nothing (they don’t mind) and need to be shown exactly where they are addressing each part of the literature review. It’s like walking a small child around, telling them “First we’ll do this, then we’ll do that, and when we’re done, we’ll know this!”

Another way to use signposting is to open each paragraph with a sentence that links the topic of the paragraph with the one before it. Alternatively, one could end each paragraph with a sentence that links it with the next paragraph. For example, imagine we wanted to link a paragraph about barriers to accessing healthcare with one about the relationship between the patient and physician. We could use a transition sentence like this: “Even if patients overcome these barriers to accessing care, the physician-patient relationship can create new barriers to positive health outcomes.” A transition sentence like this builds a connection between two distinct topics. Transition sentences are also useful within paragraphs. They tell the reader how to consider one piece of information in light of previous information. Even simple transitional words like 'however' and 'similarly' can help demonstrate critical thinking and link each building block of your argument together.

Many beginning researchers have difficulty incorporating transitions into their writing. Let’s look at an example. Instead of beginning a sentence or paragraph by launching into a description of a study, such as “Williams (2004) found that…,” it is better to start by indicating something about why you are describing this particular study. Here are some simple examples:

• Another example of this phenomenon comes from the work of Williams (2004)...
• Williams (2004) offers one explanation of this phenomenon...
• An alternative perspective has been provided by Williams (2004)...

Now that we know to use signposts, the natural question is “What goes on the signposts?” First, it is important to start with an outline of the main points that you want to make, organized in the order you want to make them. The basic structure of your argument should then be apparent from the outline itself. Unfortunately, there is no formula we can give you that will work for everyone, but we can provide some general pointers on structuring your literature review.

The literature review tends to move from general to more specific ideas. You can build a review by identifying areas of consensus and areas of disagreement. You may choose to present historical studies—preferably seminal studies that are of significant importance—and close with the most recent research. Another approach is to start with the most distantly related facts and literature and then report on those most closely related to your research question. You could also compare and contrast valid approaches, features, characteristics, theories – that is, one approach, then a second approach, followed by a third approach.

Here are some additional tips for writing the body of your literature review:

• Start broad and then narrow down to more specific information.
• When appropriate, cite two or more sources for a single point, but avoid long strings of references for a single idea.
• Use quotes sparingly. Quotations for definitions are okay, but reserve quotes for when something is said so well you couldn’t possible phrase it differently. Never use quotes for statistics.
• Paraphrase when you need to relay the specific details within an article
• Include only the aspects of the study that are relevant to your literature review. Don’t insert extra facts about a study just to take up space.
• Avoid reflective, personal writing. It is traditional to avoid using first-person language (I, we, us, etc.).
• Avoid informal language like contractions, idioms, and rhetorical questions.
• Note any sections of your review that lack citations from the literature. Your arguments need to be based in empirical or theoretical facts. Do not approach this like a reflective journal entry.
• Point out consistent findings and emphasize stronger studies over weaker ones.
• Point out important strengths and weaknesses of research studies, as well as contradictions and inconsistent findings.
• Implications and suggestions for further research (where there are gaps in the current literature) should be specific.

The conclusion should summarize your literature review, discuss implications, and create a space for further research needed in this area. Your conclusion, like the rest of your literature review, should make a point. What are the important implications of your literature review? How do they inform the question you are trying to answer?

You should consult with your professor and the course syllabus about the final structure your literature review should take. Here is an example of one possible structure:

• Establish the importance of the topic
• Number and type of people affected
• Seriousness of the impact
• Physical, psychological, economic, social, or spiritual consequences of the problem
• Definitions of key terms
• Supporting evidence
• Common findings across studies, gaps in the literature
• Research question(s) and hypothesis(es)

Editing your literature review

Literature reviews are more than a summary of the publications you find on a topic. As you have seen in this brief introduction, literature reviews represent a very specific type of research, analysis, and writing. We will explore these topics further in upcoming chapters. As you begin your literature review, here are some common errors to avoid:

• Accepting a researcher’s finding as valid without evaluating methodology and data
• Ignoring contrary findings and alternative interpretations
• Using findings that are not clearly related to your own study or using findings that are too general
• Dedicating insufficient time to literature searching
• Reporting statistical results from a single study, rather than synthesizing the results of multiple studies to provide a comprehensive view of the literature on a topic
• Relying too heavily on secondary sources
• Overusing quotations
• Not justifying arguments using specific facts or theories from the literature

For your literature review, remember that your goal is to construct an argument for the importance of your research question. As you start editing your literature review, make sure it is balanced. Accurately report common findings, areas where studies contradict each other, new theories or perspectives, and how studies cause us to reaffirm or challenge our understanding of your topic.

It is acceptable to argue that the balance of the research supports the existence of a phenomenon or is consistent with a theory (and that is usually the best that researchers in social work can hope for), but it is not acceptable to ignore contradictory evidence. A large part of what makes a research question interesting is uncertainty about its answer (University of Minnesota, 2016). [2]

In addition to subjectivity and bias, writer's block can obstruct the completion of your literature review. Often times, writer’s block can stem from confusing the creating and editing parts of the writing process. Many writers often start by simply trying to type out what they want to say, regardless of how good it is. Author Anne Lamott (1995) [3] terms these “shitty first drafts,” and we all write them. They are a natural and important part of the writing process.

Even if you have a detailed outline from which to work, the words are not going to fall into place perfectly the first time you start writing. You should consider turning off the editing and critiquing part of your brain for a while and allow your thoughts to flow. Don’t worry about putting a correctly formatted internal citation (as long as  you know which source you used there) when you first write. Just get the information out. Only after you’ve reached a natural stopping point might you go back and edit your draft for grammar, APA style, organization, flow, and more. Divorcing the writing and editing process can go a long way to addressing writer’s block—as can picking a topic about which you have something to say!

As you are editing, keep in mind these questions adapted from Green (2012): [4]

• Content: Have I clearly stated the main idea or purpose of the paper? Is the thesis or focus clearly presented and appropriate for the reader?
• Organization: How well is it structured? Is the organization spelled out and easy to follow for the reader ?
• Flow: Is there a logical flow from section to section, paragraph to paragraph, sentence to sentence? Are there transitions between and within paragraphs that link ideas together?
• Development: Have I validated the main idea with supporting material? Are supporting data sufficient? Does the conclusion match the introduction?
• Form: Are there any APA style issues, redundancy, problematic wording and terminology (always know the definition of any word you use!), flawed sentence constructions and selection, spelling, and punctuation?

Social workers use the APA style guide to format and structure their literature reviews. Most students know APA style only as it relates to internal and external citations. If you are confused about them, consult this amazing APA style guide from the University of Texas-Arlington library. Your university's library likely has resources they created to help you with APA style, and you can meet with a librarian or your professor to talk about formatting questions you have. Make sure you budget in a few hours at the end of each project to build a correctly formatted references page and check your internal citations. The highest quality online source of information on APA style is the APA style blog, where you can search questions and answers from the

Of course, APA style is about much more than knowing there is a period after "et al." or citing the location a book was published. APA style is also about what the profession considers to be good writing. If you haven't picked up an APA publication manual because you use citation generators, know that I did the same thing when I was in school. Purchasing the APA manual can help you with a common problem we hear about from students. Every professor (and every website about APA style) seems to have their own peculiar idea of "correct" APA style that you can, if needed, demonstrate is not accurate.

• A literature review is not a book report. Do not organize it by article, with one paragraph for each source in your references. Instead, organize it based on the key ideas and arguments.
• The problem statement draws the reader into your topic by highlighting the importance of the topic to social work and to society overall.
• Signposting is an important component of academic writing that helps your reader follow the structure of your argument and of your literature review.
• Transitions demonstrate critical thinking and help guide your reader through your arguments.
• Editing and writing are separate processes.
• Consult with an APA style guide or a librarian to help you format your paper.

Look at your professor's prompt for the literature review component of your research proposal (or if you don't have one, use the example question provided in this section).

• Write 2-3 facts you would use to address each question or component in the prompt.
• Reflect on which questions you have a lot of information about and which you need to gather more information about in order to answer adequately.

Outline the structure of your literature review using your concept map from Section 5.2 as a guide.

• Identify the key arguments you will make and how they are related to each other.
• Reflect on topic sentences and concluding sentences you would use for each argument.
• Human subjects research (19 minute read)
• Specific ethical issues to consider (12 minute read)
• Benefits and harms of research across the ecosystem (7 minute read)
• Being an ethical researcher (8 minute read)

Content warning: examples in this chapter contain references to numerous incidents of unethical medical experimentation (e.g. intentionally injecting diseases into unknowing participants, withholding proven treatments), social experimentation under extreme conditions (e.g. being directed to deliver electric shocks to test obedience), violations of privacy, gender and racial inequality, research with people who are incarcerated or on parole, experimentation on animals, abuse of people with Autism, community interactions with law enforcement, WWII, the Holocaust, and Nazi activities (especially related to research on humans).

With your literature review underway, you are ready to begin thinking in more concrete terms about your research topic. Recall our discussion in Chapter 2 on practical and ethical considerations that emerge as part of the research process. In this chapter, we will expand on the ethical boundaries that social scientists must abide by when conducting human subjects research. As a result of reading this chapter, you should have a better sense of what is possible and ethical for the research project you create.

6.1 Human subjects research

• Understand what we mean by ethical research and why it is important
• Understand some of the egregious ethical violations that have occurred throughout history

While all research comes with its own set of ethical concerns, those associated with research conducted on human subjects vary dramatically from those of research conducted on nonliving entities. The US Department of Health and Human Services (USDHHS) defines a human subject as “a living individual about whom an investigator (whether professional or student) conducting research obtains (1) data through intervention or interaction with the individual, or (2) identifiable private information” (USDHHS, 1993, para. 1). [5] Some researchers prefer the term "participants" to "subjects'" as it acknowledges the agency of people who participate in the study. For our purposes, we will use the two terms interchangeably.

In some states, human subjects also include deceased individuals and human fetal materials. Nonhuman research subjects, on the other hand, are objects or entities that investigators manipulate or analyze in the process of conducting research. Nonhuman research subjects typically include sources such as newspapers, historical documents, pieces of clothing, television shows, buildings, and even garbage (to name just a few), that are analyzed for unobtrusive research projects. Unsurprisingly, research on human subjects is regulated much more heavily than research on nonhuman subjects. This is why many student research projects use data that is publicly available, rather than recruiting their own study participants. However, there are ethical considerations that all researchers must take into account, regardless of their research subject. We’ll discuss those considerations in addition to concerns that are unique to human subject research.

Why do research participants need protection?

First and foremost, we are professionally bound to engage in the ethical practice of research. This chapter discusses ethical research and will show you how to engage in research that is consistent with the NASW Code of Ethics as well as national and international ethical standards all researchers are accountable to. Before we begin, we need to understand the historical occurrences that were the catalyst for the formation of the current ethical standards . This chapter will enable you to view ethics from a micro, mezzo, and macro perspective.

The research process has led to many life-changing discoveries; these have improved life expectancy, improved living conditions, and helped us understand what contributes to certain social problems. That said, not all research has been conducted in respectful, responsible, or humane ways. Unfortunately, some research projects have dramatically marginalized, oppressed, and harmed participants and whole communities.

Would you believe that the following actions have been carried out in the name of research? I realize there was a content warning at the beginning of the chapter, but it is worth mentioning that the list below of research atrocities may be particularly upsetting or triggering.

• intentionally froze healthy body parts of prisoners to see if they could develop a treatment for freezing [6]
• scaled the body parts of prisoners to how best to treat soldiers who had injuries from being exposed to high temperatures [7]
• intentionally infected healthy individuals to see if they could design effective methods of treatment for infections [8]
• gave healthy people TB to see if they could treat it [9]
• attempted to transplant limbs, bones, and muscles to another person to see if this was possible [10]
• castrated and irradiated genitals to see if they could develop a faster method of sterilization [11]
• starved people and only allowed them to drink seawater to see if they could make saline water drinkable [12]
• artificially inseminated women with animal sperm to see what would happen [13]
• gassed living people to document how they would die [14]
• conducted cruel experiments on people and if they did not die, would kill them so they could undergo an autopsy [15]
• refused to treat syphilis in African American men (when treatment was available) because they wanted to track the progression of the illness [16]
• vivisected humans without anesthesia to see how illnesses that researches gave prisoners impacted their bodies [17]
• intentionally tried to infect prisoners with the Bubonic Plague [18]
• intentionally infected prisoners, prostitutes, soldiers, and children with syphilis to study the disease's progression [19]
• performed gynecological experiments on female slaves without anesthesia to investigate new surgical methods [20]

The sad fact is that not only did all of these occur, in many instances, these travesties continued for years until exposed and halted. Additionally, these examples have contributed to the formation of a legacy of distrust toward research. Specifically, many underrepresented groups have a deep distrust of agencies that implement research and are often skeptical of research findings. This has made it difficult for groups to support and have confidence in medical treatments, advances in social service programs, and evidence-informed policy changes. While the aforementioned unethical examples may have ended, this deep and painful wound on the public's trust remains. Consequently, we must be vigilant in our commitment to ethical research.

Many of the situations described may seem like extreme historical cases of misuse of power as researchers. However, ethical problems in research don't just happen in these extreme occurrences. None of us are immune to making unethical choices and the ethical practice of research requires conscientious mindful attention to what we are asking of our research participants. A few examples of less noticeable ethical issues might include: failing to fully explain to someone in advance what their participation might involve because you are in a rush to recruit a large enough sample; or only presenting findings that support your ideas to help secure a grant that is relevant to your research area. Remember, any time research is conducted with human beings, there is the chance that ethical violations may occur that pose social, emotional, and even physical risks for groups, and this is especially true when vulnerable or oppressed groups are involved.

A brief history of unethical social science research

Research on humans hasn’t always been regulated in the way it is today. The earliest documented cases of research using human subjects are of medical vaccination trials (Rothman, 1987). [21] One such case took place in the late 1700s, when scientist Edward Jenner exposed an 8-year-old boy to smallpox in order to identify a vaccine for the devastating disease. Medical research on human subjects continued without much law or policy intervention until the mid-1900s when, at the end of World War II, a number of Nazi doctors and scientists were put on trial for conducting human experimentation during the course of which they tortured and murdered many concentration camp inmates (Faden & Beauchamp, 1986). [22] The trials, conducted in Nuremberg, Germany, resulted in the creation of the Nuremberg Code , a 10-point set of research principles designed to guide doctors and scientists who conduct research on human subjects. Today, the Nuremberg Code guides medical and other research conducted on human subjects, including social scientific research.

Medical scientists are not the only researchers who have conducted questionable research on humans. In the 1960s, psychologist Stanley Milgram (1974) [23] conducted a series of experiments designed to understand obedience to authority in which he tricked subjects into believing they were administering an electric shock to other subjects. In fact, the shocks weren’t real at all, but some, though not many, of Milgram’s research participants experienced extreme emotional distress after the experiment (Ogden, 2008). [24] A reaction of emotional distress is understandable. The realization that one is willing to administer painful shocks to another human being just because someone who looks authoritative has told you to do so might indeed be traumatizing—even if you later learn that the shocks weren’t real.

Around the same time that Milgram conducted his experiments, sociology graduate student Laud Humphreys (1970) [25] was collecting data for his dissertation on the tearoom trade, which was the practice of men engaging in anonymous sexual encounters in public restrooms. Humphreys wished to understand who these men were and why they participated in the trade. To conduct his research, Humphreys offered to serve as a “watch queen,” in a local park restroom where the tearoom trade was known to occur. His role would be to keep an eye out for police while also getting the benefit of being able to watch the sexual encounters. What Humphreys did not do was identify himself as a researcher to his research subjects. Instead, he watched his subjects for several months, getting to know several of them, learning more about the tearoom trade practice and, without the knowledge of his research subjects, jotting down their license plate numbers as they pulled into or out of the parking lot near the restroom.

Sometime after participating as a watch queen, with the help of several insiders who had access to motor vehicle registration information, Humphreys used those license plate numbers to obtain the names and home addresses of his research subjects. Then, disguised as a public health researcher, Humphreys visited his subjects in their homes and interviewed them about their lives and their health. Humphreys’ research dispelled a good number of myths and stereotypes about the tearoom trade and its participants. He learned, for example, that over half of his subjects were married to women and many of them did not identify as gay or bisexual. [26]

Once Humphreys’ work became public, there was some major controversy at his home university (e.g., the chancellor tried to have his degree revoked), among scientists in general, and among members of the public, as it raised public concerns about the purpose and conduct of social science research. In addition, the Washington   Post  journalist Nicholas von Hoffman wrote the following warning about “sociological snoopers”:

We’re so preoccupied with defending our privacy against insurance investigators, dope sleuths, counterespionage men, divorce detectives and credit checkers, that we overlook the social scientists behind the hunting blinds who’re also peeping into what we thought were our most private and secret lives. But they are there, studying us, taking notes, getting to know us, as indifferent as everybody else to the feeling that to be a complete human involves having an aspect of ourselves that’s unknown (von Hoffman, 1970). [27]

In the original version of his report, Humphreys defended the ethics of his actions. In 2008 [28] , years after Humphreys’ death, his book was reprinted with the addition of a retrospect on the ethical implications of his work. In his written reflections on his research and the fallout from it, Humphreys maintained that his tearoom observations constituted ethical research on the grounds that those interactions occurred in public places. But Humphreys added that he would conduct the second part of his research differently. Rather than trace license numbers and interview unwitting tearoom participants in their homes under the guise of public health research, Humphreys instead would spend more time in the field and work to cultivate a pool of informants. Those informants would know that he was a researcher and would be able to fully consent to being interviewed. In the end, Humphreys concluded “there is no reason to believe that any research subjects have suffered because of my efforts, or that the resultant demystification of impersonal sex has harmed society” (Humphreys, 2008, p. 231). [29]

Today, given increasing regulation of social scientific research, chances are slim that a researcher would be allowed to conduct a project similar to Humphreys’. Some argue that Humphreys’ research was deceptive, put his subjects at risk of losing their families and their positions in society, and was therefore unethical (Warwick, 1973; Warwick, 1982). [30] Others suggest that Humphreys’ research “did not violate any premise of either beneficence or the sociological interest in social justice” and that the benefits of Humphreys’ research, namely the dissolution of myths about the tearoom trade specifically and human sexual practice more generally, outweigh the potential risks associated with the work (Lenza, 2004, p. 23). [31] What do you think, and why?

These and other studies (Reverby, 2009) [32] led to increasing public awareness of and concern about research on human subjects. In 1974, the US Congress enacted the National Research Act , which created the National Commission for the Protection of Human Subjects in Biomedical and Behavioral Research. The commission produced  The Belmont Report , a document outlining basic ethical principles for research on human subjects (National Commission for the Protection of Human Subjects in Biomedical and Behavioral Research, 1979). [33] The National Research Act (1974) [34] also required that all institutions receiving federal support establish institutional review boards (IRBs) to protect the rights of human research subjects. Since that time, many organizations that do not receive federal support but where research is conducted have also established review boards to evaluate the ethics of the research that they conduct. IRBs are overseen by the federal Office of Human Research Protections .

The Belmont Report

As mentioned above, The Belmont Report is a federal document that outlines the foundational principles that guide the ethical practice of research in the United States. These ethical principles include: respect for persons, beneficence, and justice. Each of these terms has specific implications as they are applied to the practice of research. These three principles arose as a response to many of the mistreatment and abuses that have been previously discussed and provide important guidance as researchers consider how they will construct and conduct their research studies. As you are crafting your research proposal, makes sure you are mindful of these important ethical guidelines.

Respect for Persons

As social workers, our professional code of ethics requires that we recognize and respect the "inherent dignity and worth of the person." [35] This is very similar to the ethical research principle of r espect for persons . According to this principle, as researchers, we need to treat all research participants with respect, dignity and inherent autonomy. This is reflected by ensuring that participants have self-determination to make informed decisions about their participation in research, that they have a clear understanding of what they will be asked to do and any risks involved, and that their participation is voluntary and can be stopped at any time. Furthermore, for those persons who may have diminished autonomy (e.g. children, people who are incarcerated), extra protections must be built in to these research studies to ensure that respect for persons continues to be demonstrated towards these groups, as they may be especially vulnerable to exploitation and coercion through the research process. A critical tool in establishing respect for persons in your research is the informed consent process, which will be discussed in more detail below.

Beneficence

You may not be familiar with this word yet, but the concept is pretty straightforward. The main idea with beneficence is that the intent of research is to do good. As researchers, to accomplish this, we seek to maximize benefits and minimize risks. Benefits may be something good or advantageous directly received by the research participant, or they may represent a broader good to a wider group of people or the scientific community at large (such as increasing knowledge about the topic or social problem that you are studying). Risks are potential physical, social, or emotional harm that may come about as a response to participation in a study. These risks may be more immediate (e.g. risk of identifying information about a participant being shared, or a participant being upset or triggered by a particular question), or long-term (e.g. some aspect about the person could be shared that could lead to long-term stigmatization). As researchers, we need to think about risk that might be experienced by the individual, but also risks that might be directed towards the community or population(s) the individual may represent. For instance, if our study is specifically focused on surveying single parents, we need to consider how the sharing of our findings might impact this group and how they are perceived. It is a very rare study in which there is no risk to participants. However, a well-designed and ethically sound study will seek to minimize these risks, provide resources to anticipate and address them, and maximize the benefits that are gained through the study.

The final ethical principle we need to cover is justice. While you likely have some idea what justice is, for the purposes of research, justice is the idea that the benefits and the burdens of research are distributed fairly across populations and groups. To help illustrate the concept of justice in research, research in the area of mental health and psychology has historically been critiqued as failing to adequately represent women and people of diverse racial and ethnic groups in their samples (Cundiff, 2012). [36] This has created a body of knowledge that is overly representative of the white male experience, further reinforcing systems of power and privilege. In addition, consider the influence of language as it relates to research justice. If we create studies that only recruit participants fluent in English, which many studies do, we are often failing to satisfy the ethical principle of justice as it applies to people who don't speak English. It is unrealistic to think that we can represent all people in all studies. However, we do need to thoughtfully acknowledge voices that might not be reflected in our samples and attempt to recruit diverse and representative samples whenever possible.

These three principles provide the foundation for the oversight work that is carried out by Institutional Review Boards, our next topic.

Institutional review boards

Institutional review boards, or IRBs, are tasked with ensuring that the rights and welfare of human research subjects will be protected at all institutions, including universities, hospitals, nonprofit research institutions, and other organizations, that receive federal support for research. IRBs typically consist of members from a variety of disciplines, such as sociology, economics, education, social work, and communications (to name a few). Most IRBs also include representatives from the community in which they reside. For example, representatives from nearby prisons, hospitals, or treatment centers might sit on the IRBs of university campuses near them. The diversity of membership helps to ensure that the many and complex ethical issues that may arise from human subjects research will be considered fully and by a knowledgeable and experienced panel. Investigators conducting research on human subjects are required to submit proposals outlining their research plans to IRBs for review and approval prior to beginning their research. Even students who conduct research on human subjects must have their proposed work reviewed and approved by the IRB before beginning any research (though, on some campuses, exceptions are made for student projects that will not be shared outside of the classroom).

The IRB has three levels of review, defined in statute by the USDHHS.

Exempt review is the lowest level of review. Studies that are considered exempt expose participants to the least potential for harm and often involve little participation by human subjects. In social work, exempt studies often examine data that is publicly available or secondary data from another researcher that has been de-identified by the person who collected it.

Expedited review is the middle level of review. Studies considered under expedited review do not have to go before the full IRB board because they expose participants to minimal risk. However, the studies must be thoroughly reviewed by a member of the IRB committee. While there are many types of studies that qualify for expedited review, the most relevant to social workers include the use of existing medical records, recordings (such as interviews) gathered for research purposes, and research on individual group characteristics or behavior.

Finally, the highest level of review is called a  full board review . A full board review will involve multiple members of the IRB evaluating your proposal. When researchers submit a proposal under full board review, the full IRB board will meet, discuss any questions or concerns with the study, invite the researcher to answer questions and defend their proposal, and vote to approve the study or send it back for revision. Full board proposals pose greater than minimal risk to participants. They may also involve the participation of  vulnerable populations , or people who need additional protection from the IRB. Vulnerable populations include prisoners, children, people with cognitive impairments, people with physical disabilities, employees, and students. While some of these populations can fall under expedited review in some cases, they will often require the full IRB to approve their study.

It may surprise you to hear that IRBs are not always popular or appreciated by researchers. Who wouldn’t want to conduct ethical research, you ask? In some cases, the concern is that IRBs are most well-versed in reviewing biomedical and experimental research, neither of which is particularly common within social work. Much social work research, especially qualitative research, is open-ended in nature, a fact that can be problematic for IRBs. The members of IRBs often want to know in advance exactly who will be observed, where, when, and for how long, whether and how they will be approached, exactly what questions they will be asked, and what predictions the researcher has for their findings. Providing this level of detail for a year-long participant observation within an activist group of 200-plus members, for example, would be extraordinarily frustrating for the researcher in the best case and most likely would prove to be impossible. Of course, IRBs do not intend to have researchers avoid studying controversial topics or avoid using certain methodologically sound data collection techniques, but unfortunately, that is sometimes the result. The solution is not to eradicate review boards, which serve a necessary and important function, but instead to help educate IRB members about the variety of social scientific research methods and topics covered by social workers and other social scientists.

What we have provided here is only a short summary of federal regulations and international agreements that provide the boundaries between ethical and unethical research.

Here are a few more detailed guides for continued learning about research ethics and human research protections.

• University of California, San Francisco: Levels of IRB Review
• United States Department of Health and Human Services: The Belmont Report
• NIH, National Institute of Environmental Health Sciences: What is Ethics in Research & Why is it important 
• NIH: Guiding Principles for Ethical Research
• Council on Social Work Education: National Statement on Research Integrity in Social Work
• Butler, I. (2002). A code of ethics for social work and social care research.  British Journal of Social Work ,  32 (2), 239-248
• Research on human subjects presents a unique set of challenges and opportunities when it comes to conducting ethical research.
• Research on human subjects has not always been regulated to the extent that it is today.
• All institutions receiving federal support for research must have an IRB. Organizations that do not receive federal support but where research is conducted also often include IRBs as part of their organizational structure.
• Researchers submit studies for IRB review at one of three different levels, depending on the level of harm the study may cause.
• Recall whether your project will gather data from human subjects and sketch out what the data collection process might look like.
• Identify which level of IRB review is most appropriate for your project.
• For many students, your professors may have existing agreements with your university's IRB that allow students to conduct research projects outside the supervision of the IRB. Make sure that your project falls squarely within those parameters. If you feel you may be outside of such an agreement, consult with your professor to see if you will need to submit your study for IRB review before starting your project.

6.2 Specific ethical issues to consider

• Define informed consent, and describe how it works
• Identify the unique concerns related to the study of vulnerable populations
• Differentiate between anonymity and confidentiality
• Explain the ethical responsibilities of social workers conducting research

As should be clear by now, conducting research on humans presents a number of unique ethical considerations. Human research subjects must be given the opportunity to consent to their participation in research, and be fully informed of the study’s risks, benefits, and purpose. Further, subjects’ identities and the information they share should be protected by researchers. Of course, how consent and identity protection are defined may vary by individual researcher, institution, or academic discipline. In this section, we’ll take a look at a few specific topics that individual researchers must consider before embarking on research with human subjects.

Informed consent

An expectation of voluntary participation is presumed in all social work research projects. In other words, we cannot force anyone to participate in our research without that person’s knowledge or consent. Researchers must therefore design procedures to obtain subjects’ informed consent to participate in their research. This specifically relates back to the ethical principle of respect for persons outlined in The Belmont Report . Informed consent  is defined as a subject’s voluntary agreement to participate in research based on a full understanding of the research and of the possible risks and benefits involved. Although it sounds simple, ensuring that one has actually obtained informed consent is a much more complex process than you might initially presume.

The first requirement is that, in giving their informed consent, subjects may neither waive nor even  appear  to waive any of their legal rights. Subjects also cannot release a researcher, her sponsor, or institution from any legal liability should something go wrong during the course of their participation in the research (USDHHS,2009). [37] Because social work research does not typically involve asking subjects to place themselves at risk of physical harm by, for example, taking untested drugs or consenting to new medical procedures, social work researchers do not often worry about potential liability associated with their research projects. However, their research may involve other types of risks.

For example, what if a social work researcher fails to sufficiently conceal the identity of a subject who admits to participating in a local swinger’s club? In this case, a violation of confidentiality may negatively affect the participant’s social standing, marriage, custody rights, or employment. Social work research may also involve asking about intimately personal topics that may be difficult for participants to discuss, such as trauma or suicide. Participants may re-experience traumatic events and symptoms when they participate in your study. Even if you are careful to fully inform your participants of all risks before they consent to the research process, I’m sure you can empathize with thinking you could bear talking about a difficult topic and then finding it too overwhelming once you start. In cases like these, it is important for a social work researcher to have a plan to provide supports. This may mean providing referrals to counseling supports in the community or even calling the police if the participant is an imminent danger to himself or others.

It is vital that social work researchers explain their mandatory reporting duties in the consent form and ensure participants understand them before they participate. Researchers should also emphasize to participants that they can stop the research process at any time or decide to withdraw from the research study for any reason. Importantly, it is not the job of the social work researcher to act as a clinician to the participant. While a supportive role is certainly appropriate for someone experiencing a mental health crisis, social workers must ethically avoid dual roles. Referring a participant in crisis to other mental health professionals who may be better able to help them is the expectation.

Beyond the legal issues, most IRBs require researchers to share some details about the purpose of the research, possible benefits of participation, and, most importantly, possible risks associated with participating in that research with their subjects. In addition, researchers must describe how they will protect subjects’ identities, how, where, and for how long any data collected will be stored, how findings may be shared, and whom to contact for additional information about the study or about subjects’ rights. All this information is typically shared in an informed consent form that researchers provide to subjects. In some cases, subjects are asked to sign the consent form indicating that they have read it and fully understand its contents. In other cases, subjects are simply provided a copy of the consent form and researchers are responsible for making sure that subjects have read and understand the form before proceeding with any kind of data collection. Your IRB will often provide guidance or even templates for what they expect to see included in an informed consent form. This is a document that they will inspect very closely. Table 6.1 outlines elements to include in your informed consent. While these offer a guideline for you, you should always visit your schools, IRB website to see what guidance they offer. They often provide a template that they prefer researchers to use. Using these templates ensures that you are using the language that the IRB reviewers expect to see and this can also save you time.

One last point to consider when preparing to obtain informed consent is that not all potential research subjects are considered equally competent or legally allowed to consent to participate in research. Subjects from vulnerable populations may be at risk of experiencing undue influence or coercion (USDHHS, 2009). [38] The rules for consent are more stringent for vulnerable populations. For example, minors must have the consent of a legal guardian in order to participate in research. In some cases, the minors themselves are also asked to participate in the consent process by signing special, age-appropriate assent forms designed specifically for them. Prisoners and parolees also qualify as vulnerable populations. Concern about the vulnerability of these subjects comes from the very real possibility that prisoners and parolees could perceive that they will receive some highly desired reward, such as early release, if they participate in research or that there could be punitive consequences if they choose not to participate. When a participant faces undue or excess pressure to participate by either favorable or unfavorable means, this is known as coercion and must be avoided by researchers.

Another potential concern regarding vulnerable populations is that they may be underrepresented or left out of research opportunities, specifically because of concerns about their ability to consent. So, on the one hand, researchers must take extra care to ensure that their procedures for obtaining consent from vulnerable populations are not coercive. The procedures for receiving approval to conduct research with these groups may be more rigorous than that for non-vulnerable populations. On the other hand, researchers must work to avoid excluding members of vulnerable populations from participation simply on the grounds that they are vulnerable or that obtaining their consent may be more complex. While there is no easy solution to this ethical research dilemma, an awareness of the potential concerns associated with research on vulnerable populations is important for identifying whatever solution is most appropriate for a specific case.

Protection of identities

As mentioned earlier, the informed consent process includes the requirement that researchers outline how they will protect the identities of subjects. This aspect of the research process, however, is one of the most commonly misunderstood. Furthermore, failing to protect identities is one of the greatest risks to participants in social work research studies.

In protecting subjects’ identities, researchers typically promise to maintain either the anonymity or confidentiality of their research subjects. These are two distinctly different terms and they are NOT interchangeable. Anonymity is the more stringent of the two and is very hard to guarantee in most research studies. When a researcher promises anonymity to participants, not even the researcher is able to link participants’ data with their identities. Anonymity may be impossible for some social work researchers to promise due to the modes of data collection many social workers employ. Face-to-face interviewing means that subjects will be visible to researchers and will hold a conversation, making anonymity impossible. In other cases, the researcher may have a signed consent form or obtain personal information on a survey and will therefore know the identities of their research participants. In these cases, a researcher should be able to at least promise confidentiality to participants.

Offering  confidentiality means that some identifying information is known at some time by the research team, but only the research team has access to this identifying information and this information will not be linked with their data in any publicly accessible way. Confidentiality in research is quite similar to confidentiality in clinical practice. You know who your clients are, but others do not. You agree to keep their information and identity private. As you can see under the “Risks” section of the consent form in Figure 5.1, sometimes it is not even possible to promise that a subject’s confidentiality will be maintained. This is the case if data are collected in public or in the presence of other research participants in the course of a focus group, for example. Participants who social work researchers deem to be of imminent danger to self or others or those that disclose abuse of children and other vulnerable populations fall under a social worker’s duty to report. Researchers must then violate confidentiality to fulfill their legal obligations.

There are a number of steps that researchers can take to protect the identities of research participants. These include, but are not limited to:

• Collecting data in private spaces
• Not requesting information that will uniquely identify or "out" that person as a participant
• Assigning study identification codes or pseudonyms
• Keeping signed informed consent forms separate from other data provided by the participant
• Making sure that physical data is kept in a locked and secured location, and the virtual data is encrypted or password-protected
• Reporting data in aggregate (only discussing the data collectively, not by individual responses)

Protecting research participants’ identities is not always a simple prospect, especially for those conducting research on stigmatized groups or illegal behaviors. Sociologist Scott DeMuth learned that all too well when conducting his dissertation research on a group of animal rights activists. As a participant observer, DeMuth knew the identities of his research subjects. So when some of his research subjects vandalized facilities and removed animals from several research labs at the University of Iowa, a grand jury called on Mr. DeMuth to reveal the identities of the participants in the raid. When DeMuth refused to do so, he was jailed briefly and then charged with conspiracy to commit animal enterprise terrorism and cause damage to the animal enterprise (Jaschik, 2009). [39]

Publicly, DeMuth’s case raised many of the same questions as Laud Humphreys’ work 40 years earlier. What do social scientists owe the public? Is DeMuth, by protecting his research subjects, harming those whose labs were vandalized? Is he harming the taxpayers who funded those labs? Or is it more important that DeMuth emphasize what he owes his research subjects, who were told their identities would be protected? DeMuth’s case also sparked controversy among academics, some of whom thought that as an academic himself, DeMuth should have been more sympathetic to the plight of the faculty and students who lost years of research as a result of the attack on their labs. Many others stood by DeMuth, arguing that the personal and academic freedom of scholars must be protected whether we support their research topics and subjects or not. DeMuth’s academic adviser even created a new group, Scholars for Academic Justice , to support DeMuth and other academics who face persecution or prosecution as a result of the research they conduct. What do you think? Should DeMuth have revealed the identities of his research subjects? Why or why not?

Discipline-specific considerations

Often times, specific disciplines will provide their own set of guidelines for protecting research subjects and, more generally, for conducting ethical research. For social workers, the National Association of Social Workers (NASW) Code of Ethics section 5.02 describes the responsibilities of social workers in conducting research. Summarized below, these responsibilities are framed as part of a social worker’s responsibility to the profession. As representative of the social work profession, it is your responsibility to conduct and use research in an ethical manner.

A social worker should:

• Monitor and evaluate policies, programs, and practice interventions
• Contribute to the development of knowledge through research
• Keep current with the best available research evidence to inform practice
• Ensure voluntary and fully informed consent of all participants
• Not engage in any deception in the research process
• Allow participants to withdraw from the study at any time
• Provide access to appropriate supportive services for participants
• Protect research participants from harm
• Maintain confidentiality
• Report findings accurately
• Disclose any conflicts of interest
• Researchers must obtain the informed consent of research participants.
• Social workers must take steps to minimize the harms that could arise during the research process.
• If anonymity is promised, individual participants cannot be linked with their data.
• If confidentiality is promised, the identities of research participants cannot be revealed, even if individual participants can be linked with their data.
• The NASW Code of Ethics includes specific responsibilities for social work researchers.
• Talk with your professor to see if an informed consent form is required for your research project. If documentation is required, customize the template provided by your professor or the IRB at your school, using the details of your study. If documentation on consent is not required, for example if consent is given verbally, use the templates as guides to create a guide for what you will say to participants regarding informed consent.
• Identify whether your data will be confidential or anonymous. Describe the measures you will take to protect the identities of individuals in your study. How will you store the data? How will you ensure that no one can identify participants based on what you report in papers and presentations? Be sure to think carefully. People can be identified by characteristics such as age, gender, disability status, location, etc.

6.3 Benefits and harms of research across the ecosystem

• Identify and distinguish between micro-, mezzo-, and macro-level considerations with respect to the ethical conduct of social scientific research

This chapter began with a long list of harmful acts that researchers engaged in while conducting studies on human subjects. Indeed, even the last section on informed consent and protection of confidential information can be seen in light of minimizing harm and maximizing benefits. The benefits of your study should be greater than the harms. But who benefits from your research study, and who might be harmed? The first person who benefits is, most clearly, you as the researcher. You need a project to complete, be it for a grade, a grant, an academic responsibility, etc. However you need to make sure that your benefit does not come at the expense of harming others. Furthermore, research requires resources, including resources from the communities we work with. Part of being good stewards of these resources as social work researchers means that we need to engage in research that benefits the people we serve in meaningful and relevant ways. We need to consider how others are impacted by our research.

Micro-, mezzo-, and macro-level concerns

One useful way to think about the breadth of ethical questions that might arise out of any research project is to think about potential issues from the perspective of different analytical levels that are familiar to us as social workers. In Chapter 1 , you learned about the micro-, mezzo-, and macro-levels of inquiry and how a researcher’s specific point of focus might vary depending on her level of inquiry. Here we’ll apply this ecological framework to a discussion of research ethics. Within most research projects, there are specific questions that arise for researchers at each of these three levels.

At the micro-level, researchers must consider their own conduct and the impact on individual research participants. For example, did Stanley Milgram behave ethically when he allowed research participants to think that they were administering electric shocks to fellow participants? Did Laud Humphreys behave ethically when he deceived his research subjects about his own identity? Were the rights of individuals in these studies protected? How did these participants benefit themselves from the research that was conducted? While not social workers by trade, would the actions of these two researchers hold up against our professional NASW Code of Ethics? The questions posed here are the sort that you will want to ask yourself as a researcher when considering ethics at the micro-level.

At the mezzo-level, researchers should think about their duty to the community. How will the results of your study impact your target population? Ideally, your results will benefit your target population by identifying important areas for social workers to intervene and to better understand the experiences of the communities they serve. However, it is possible that your study may perpetuate negative stereotypes about your target population or damage its reputation. Indigenous people in particular have highlighted how historically social science has furthered marginalization of indigenous peoples (Smith, 2013). [40] Mezzo-level concerns should also address other groups or organizations that are connected to your target population. This may include the human service agencies with whom you've partnered for your study as well as the communities and peoples they serve. If your study reflected negatively on a particular housing project in your area, for example, will community members seek to remove it from their community? Or might it draw increased law enforcement presence that is unwanted by participants or community members? Research is a powerful tool and can be used for many purposes, not all of them altruistic. In addition, research findings can have many implications, intended and unintended. As responsible researchers, we need to do our best to thoughtfully anticipate these consequences.

Finally, at the macro-level, a researcher should consider duty to, and the expectations of, society. Perhaps the most high-profile case involving macro-level questions of research ethics comes from debates over whether to use data gathered by, or cite published studies based on data gathered from, the Nazis in the course of their unethical and horrendous experiments on humans during World War II (Moe, 1984). [41] Some argue that because the data were gathered in such an unquestionably unethical manner, they should never be used. The data, say these people, are neither valid nor reliable and should therefore not be used in any current scientific investigation (Berger, 1990). [42]

On the other hand, some people argue that data themselves are neutral; that “information gathered is independent of the ethics of the methods and that the two are not linked together” (Pozos, 1992, p. 104). [43] Others point out that not using the data could inadvertently strengthen the claims of those who deny that the Holocaust ever happened. In his striking statement in support of publishing the data, medical ethics professor Velvl Greene (1992) says,

Instead of banning the Nazi data or assigning it to some archivist or custodial committee, I maintain that it be exhumed, printed, and disseminated to every medical school in the world along with the details of methodology and the names of the doctors who did it, whether or not they were indicted, acquitted, or hanged.…Let the students and the residents and the young doctors know that this was not ancient history or an episode from a horror movie where the actors get up after filming and prepare for another role. It was real. It happened yesterday (p. 169–170). [44]

While debates about the use of data collected by the Nazis are typically centered on medical scientists’ use of them, there are conceivable circumstances under which these data might be used by social scientists. Perhaps, for example, a social scientist might wish to examine contemporary reactions to the experiments. Or perhaps the data could be used in a study of the sociology of science. What do you think? Should data gathered by the Nazis be used or cited today? What arguments can you make in support of your position, and how would you respond to those who disagree?

Additionally at the macro-level, you must also consider your responsibilities to the profession of social work. When you engage in social work research, you stand on the reputation the profession has built for over a century. Since research is public-facing, meaning that research findings are intended to be shared publicly, you are an ambassador for the profession. How you conduct yourself as a social work researcher has potential implications for how the public perceives both social work and research. As a social worker, you have a responsibility to work towards greater social, environmental, and economic justice and human rights. Your research should reflect this responsibility. Attending to research ethics helps to fulfill your responsibilities to the profession, in addition to your target population.

Table 6.2 summarizes the key questions that researchers might ask themselves about the ethics of their research at each level of inquiry.

• At the micro-level, researchers should consider their own conduct and the rights of individual research participants.
• At the mezzo-level, researchers should consider the expectations of their profession, any organizations that may have funded their research, and the communities affected by their research.
• At the macro-level, researchers should consider their duty to and the expectations of society with respect to social science research.
• Summarize the benefits and harms at the micro-, mezzo-, and macro-level of inquiry. At which level of inquiry is your research project?
• In a few sentences, identify whether the benefits of your study outweigh the potential harms.

6.4 Being an ethical researcher

• Identify why researchers must provide a detailed description of methodology
• Describe what it means to use science in an ethical way

Research ethics has to do with both how research is conducted and how findings from that research are used. In this section, we’ll consider research ethics from both angles.

Doing science the ethical way

As you should now be aware, researchers must consider their own personal ethical principles in addition to following those of their institution, their discipline, and their community. We’ve already considered many of the ways that social workers strive to ensure the ethical practice of research, such as informing and protecting subjects. But the practice of ethical research doesn’t end once subjects have been identified and data have been collected. Social workers must also fully disclose their research procedures and findings. This means being honest about how research subjects were identified and recruited, how exactly data were collected and analyzed, and ultimately, what findings were reached.

If researchers fully disclose how they conducted their research, then those who use their work to build research projects, create social policies, or make treatment decisions can have greater confidence in the work. By sharing how research was conducted, a researcher helps assure readers they have conducted legitimate research and didn’t simply come to whatever conclusions they wanted   to find. A description or presentation of research findings that is not accompanied by information about research methodology is missing relevant information. Sometimes methodological details are left out because there isn’t time or space to share them. This is often the case with news reports of research findings. Other times, there may be a more insidious reason that important information is missing. This may be the case if sharing methodological details would call the legitimacy of a study into question. As researchers, it is our ethical responsibility to fully disclose our research procedures. As consumers of research, it is our ethical responsibility to pay attention to such details. We’ll discuss this more in the next section.

There’s a New Yorker cartoon that depicts a set of filing cabinets that aptly demonstrates what we don’t want to see happen with research. Each filing cabinet drawer in the cartoon is labeled differently. The labels include such headings as, “Our Facts,” “Their Facts,” “Neutral Facts,” “Disputable Facts,” “Absolute Facts,” “Bare Facts,” “Unsubstantiated Facts,” and “Indisputable Facts.” The implication of this cartoon is that one might just choose to open the file drawer of her choice and pick whichever facts one likes best. While this may occur if we use some of the unscientific ways of knowing described in Chapter 1 , it is fortunately not how the discovery of knowledge in social work, or in any other science for that matter, takes place. There actually is a method to this madness we call research. At its best, research reflects a systematic, transparent, informative process.

Honesty in research is facilitated by the scientific principle of replication . Ideally, this means that one scientist could repeat another’s study with relative ease. By replicating a study, we may become more (or less) confident in the original study’s findings. Replication is far more difficult (perhaps impossible) to achieve in the case of many qualitative studies, as our purpose is often a deep understanding of very specific circumstances, rather than the broad, generalizable knowledge we traditionally seek in quantitative studies. Nevertheless, transparency in the research process is an important standard for all social scientific researchers—that we provide as much detail as possible about the processes by which we reach our conclusions. This allows the quality of our research to be evaluated. Along with replication, peer review is another important principle of the scientific process. Peer review involves other knowledgeable researchers in our field of study to evaluate our research and to determine if it is of sufficient quality to share with the public. There are valid critiques of the peer review process: that it is biased towards studies with positive findings, that it may reinforce systemic barriers to oppressed groups accessing and leveraging knowledge, that it is far more subjective and/or unreliable than it claims to be. Despite these critiques, peer review remains a foundational concept for how scientific knowledge is generated.

Full disclosure also includes the need to be honest about a study’s strengths and weaknesses, both with oneself and with others. Being aware of the strengths and weaknesses of your own work can help a researcher make reasonable recommendations about the next steps other researchers might consider taking in their inquiries. Awareness and disclosure of a study’s strengths and weaknesses can also help highlight the theoretical or policy implications of one’s work. In addition, openness about strengths and weaknesses helps those reading the research better evaluate the work and decide for themselves how or whether to rely on its findings. Finally, openness about a study’s sponsors is crucial. How can we effectively evaluate research without knowing who paid the bills? This allows us to assess for potential conflicts of interest that may compromise the integrity of the research.

The standard of replicability, the peer-review process, and openness about a study’s strengths, weaknesses, and funding sources enables those who read the research to evaluate it fairly and completely. Knowledge of funding sources is often raised as an issue in medical research. Understandably, independent studies of new drugs may be more compelling to the Food and Drug Administration (FDA) than studies touting the virtues of a new drug that happen to have been funded by the company who created that drug. But medical researchers aren’t the only ones who need to be honest about their funding. If we know, for example, that a political think tank with ties to a particular party has funded some research, we can take that knowledge into consideration when reviewing the study’s findings and stated policy implications. Lastly, and related to this point, we must consider how, by whom, and for what purpose research may be used.

Using science the ethical way

Science has many uses. By “use” I mean the ways that science is understood and applied (as opposed to the way it is conducted). Some use science to create laws and social policies; others use it to understand themselves and those around them. Some people rely on science to improve their life conditions or those of other people, while still others use it to improve their businesses or other undertakings. In each case, the most ethical way for us to use science is to educate ourselves about the design and purpose of any studies we may wish to use. This helps us to more adequately critique the value of this research, to recognize its strengths and limitations.

As part of my research course, students are asked to critique a research article. I often find in this assignment that students often have very lofty expectations for everything that 'should' be included in the journal article they are reviewing. While I appreciate the high standards, I often give them feedback that it is perhaps unrealistic (even unattainable) for a research study to be perfectly designed and described for public consumption. All research has limitations; this may be a consequence of limited resources, issues related to feasibility, and unanticipated roadblocks or problems as we are carrying out our research. Furthermore, the ways we disseminate or share our research often has restrictions on what and how we can share our findings. This doesn't mean that a study with limitations has no value—every study has limitations! However, as we are reviewing research, we should look for an open discussion about methodology , strengths, and weaknesses of the study that helps us to interpret what took place and in what ways it may be important.

For instance, this can be especially important to think about in terms of a study's sample. It can be challenging to recruit a diverse and representative sample for your study (however, that doesn't mean we shouldn't try!). The next time you are reading research studies that were used to help establish an evidence based practice (EBP), make sure to look at the description of the sample. We cannot assume that what works for one group of people will uniformly work with all groups of people with very different life experiences; however, historically much of our intervention repertoire has been both created by and evaluated on white men. If research studies don't obtain a diverse sample, for whatever reason, we would expect that the authors would identify this as a limitation and an area requiring further study. We need to challenge our profession to provide practices, strategies, models, interventions, and policies that have been evaluated and tested for their efficacy with the diverse range of people that we work with as social workers.

Social scientists who conduct research on behalf of organizations and agencies may face additional ethical questions about the use of their research, particularly when the organization for which a study is conducted controls the final report and the publicity it receives. There is a potential conflict of interest for evaluation researchers who are employees of the agency being evaluated. A similar conflict of interest might exist between independent researchers whose work is being funded by some government agency or private foundation.

So who decides what constitutes ethical conduct or use of research? Perhaps we all do. What qualifies as ethical research may shift over time and across cultures as individual researchers, disciplinary organizations, members of society, and regulatory entities, such as institutional review boards, courts, and lawmakers, all work to define the boundaries between ethical and unethical research.

• Conducting research ethically requires that researchers be ethical not only in their data collection procedures but also in reporting their methods and findings.
• The ethical use of research requires an effort to understand research, an awareness of your own limitations in terms of knowledge and understanding, and the honest application of research findings.
• Think about your research hypothesis at this point. What would happen if your results revealed information that could harm the population you are studying? What are your ethical responsibilities as far as reporting about your research?
• Ultimately, we cannot control how others will use the results of our research. What are the implications of this for how you report on your research?
• Reading the results of empirical studies (16 minute read)
• Annotating empirical journal articles (15 minute read)
• Generalizability and transferability of empirical results (15 minute read)

Content warning: examples in this chapter contain references to domestic violence and details on types of abuse, drug use, poverty, mental health, sexual harassment and details on harassing behaviors, children’s mental health, LGBTQ+ oppression and suicide, obesity, anti-poverty stigma, and psychotic disorders.

5.1 Reading the results of empirical studies

• Describe how statistical significance and confidence intervals demonstrate which results are most important
• Differentiate between qualitative and quantitative results in an empirical journal article

If you recall from section 3.1 , empirical journal articles are those that report the results of quantitative or qualitative data analyzed by the author. They follow a set structure—introduction, methods, results, discussion/conclusions. This section is about reading the most challenging section: results.

I want to normalize not understanding statistics terms and symbols. However, a basic understanding of a results section goes a very long way to understanding the key results in an article. This will take you beyond the two or three sentences in the abstract that summarize the study's results and into the nitty-gritty of what they found for each concept they studied.

Read beyond the abstract

At this point, I have read hundreds of literature reviews written by students. One of the challenges I have noted is that students will report the results as summarized in the abstract, rather than the detailed findings laid out in the results section of the article. This poses a problem when you are writing a literature review because you need to provide specific and clear facts that support your reading of the literature. The abstract may say something like: “we found that poverty is associated with mental health status.” For your literature review, you want the details, not the summary. In the results section of the article, you may find a sentence that states: “children living in households experiencing poverty are three times more likely to have a mental health diagnosis.” This more specific statistical information provides a stronger basis on which to build the arguments in your literature review.

Using the summarized results in an abstract is an understandable mistake to make. The results section often contains figures and tables that may be challenging to understand. Often, without having completed more advanced coursework on statistical or qualitative analysis, some of the terminology, symbols, or diagrams may be difficult to comprehend. This section is all about how to read and interpret the results of an empirical (quantitative or qualitative) journal article. Our discussion here will be basic, and in parts three and four of the textbook, you will learn more about how to interpret results from statistical tests and qualitative data analysis.

Remember, this section only addresses empirical articles. Non-empirical articles (e.g., theoretical articles, literature reviews) don't have results. They cite the analysis of raw data completed by other authors, not the person writing the journal article who is merely summarizing others' work.

Quantitative results

Quantitative articles often contain tables, and scanning them is a good way to begin reading the results. A table usually provides a quick, condensed summary of the report’s key findings. Tables are a concise way to report large amounts of data. Some tables present descriptive information about a researcher’s sample (often the first table in a results section). These tables will likely contain frequencies (N) and percentages (%). For example, if gender happened to be an important variable for the researcher’s analysis, a descriptive table would show how many and what percent of all study participants are of a particular gender. Frequencies or “how many” will probably be listed as N, while the percent symbol (%) might be used to indicate percentages.

In a table presenting a causal relationship, two sets of variables are represented. The independent variable , or cause, and the dependent variable , the effect. We will discuss these further when we review quantitative conceptualization and measurement. Independent variable attributes are typically presented in the table’s columns, while dependent variable attributes are presented in rows. This allows the reader to scan a table’s rows to see how values on the dependent variable change as the independent variable values change (i.e., changes in the dependent variable depend on changes in the independent variable). Tables displaying results of quantitative analysis will also likely include some information about which relationships are significant or not. We will discuss the details of significance and p-values later in this section.

Let’s look at a specific example: Table 5.1. It presents the causal relationship between gender and experiencing harassing behaviors at work. In this example, gender is the independent variable (the cause) and the harassing behaviors listed are the dependent variables (the effects). [46] Therefore, we place gender in the table’s columns and harassing behaviors in the table’s rows.

Reading across the table’s top row, we see that 2.9% of women in the sample reported experiencing subtle or obvious threats to their safety at work, while 4.7% of men in the sample reported the same. We can read across each of the rows of the table in this way. Reading across the bottom row, we see that 9.4% of women in the sample reported experiencing staring or invasion of their personal space at work while just 2.3% of men in the sample reported having the same experience. We’ll discuss  p values later in this section.

While you can certainly scan tables for key results, they are often difficult to understand without reading the text of the article. The article and table were meant to complement each other, and the text should provide information on how the authors interpret their findings. The table is not redundant with the text of the results section. Additionally, the first table in most results sections is a summary of the study's sample, which provides more background information on the study than information about hypotheses and findings. It is also a good idea to look back at the methods section of the article as the data analysis plan the authors outline should walk you through the steps they took to analyze their data which will inform how they report them in the results section.

Statistical significance

The statistics reported in Table 5.1 represent what the researchers found in their sample. The purpose of statistical analysis is usually to generalize from a the small number of people in a study's sample to a larger population of people. Thus, the researchers intend to make causal arguments about harassing behaviors at workplaces beyond those covered in the sample.

Generalizing is key to understanding statistical significance . According to Cassidy and colleagues, (2019) [47] 89% of research methods textbooks in psychology define statistical significance incorrectly. This includes an early draft of this textbook which defined statistical significance as "the likelihood that the relationships we observe could be caused by something other than chance." If you have previously had a research methods class, this might sound familiar to you. It certainly did to me!

But statistical significance is less about "random chance" than more about the null hypothesis . Basically, at the beginning of a study a researcher develops a hypothesis about what they expect to find, usually that there is a statistical relationship between two or more variables . The null hypothesis is the opposite. It is the hypothesis that there is no relationship between the variables in a research study. Researchers then can hopefully reject the null hypothesis because they find a relationship between the variables.

For example, in Table 5.1 researchers were examining whether gender impacts harassment. Of course, researchers assumed that women were more likely to experience harassment than men. The null hypothesis, then, would be that gender has no impact on harassment. Once we conduct the study, our results will hopefully lead us to reject the null hypothesis because we find that gender impacts harassment. We would then generalize from our study's sample to the larger population of people in the workplace.

Statistical significance is calculated using a p-value which is obtained by comparing the statistical results with a hypothetical set of results if the researchers re-ran their study a large number of times. Keeping with our example, imagine we re-ran our study with different men and women from different workplaces hundreds and hundred of times and we assume that the null hypothesis is true that gender has no impact on harassment. If results like ours come up pretty often when the null hypothesis is true, our results probably don't mean much. "The smaller the p-value, the greater the statistical incompatibility with the null hypothesis" (Wasserstein & Lazar, 2016, p. 131). [48] Generally, researchers in the social sciences have used 0.05 as the value at which a result is significant (p is less than 0.05) or not significant (p is greater than 0.05). The p-value 0.05 refers to if 5% of those hypothetical results from re-running our study show the same or more extreme relationships when the null hypothesis is true. Researchers, however, may choose a stricter standard such as 0.01 in which only 1% of those hypothetical results are more extreme or a more lenient standard like 0.1 in which 10% of those hypothetical results are more extreme than what was found in the study.

Let's look back at Table 5.1. Which one of the relationships between gender and harassing behaviors is statistically significant? It's the last one in the table, "staring or invasion of personal space," whose p-value is 0.039 (under the p<0.05 standard to establish statistical significance). Again, this indicates that if we re-ran our study over and over again and gender did not  impact staring/invasion of space (i.e., the null hypothesis was true), only 3.9% of the time would we find similar or more extreme differences between men and women than what we observed in our study. Thus, we conclude that for staring or invasion of space only , there is a statistically significant relationship.

For contrast, let's look at "being pushed, hit, or grabbed" and run through the same analysis to see if it is statistically significant. If we re-ran our study over and over again and the null hypothesis was true, 48% of the time (p=.48) we would find similar or more extreme differences between men and women. That means these results are not statistically significant.

This discussion should also highlight a point we discussed previously: that it is important to read the full results section, rather than simply relying on the summary in the abstract. If the abstract stated that most tests revealed no statistically significant relationships between gender and harassment, you would have missed the detail on which behaviors were and were not associated with gender. Read the full results section! And don't be afraid to ask for help from a professor in understanding what you are reading, as results sections are often not written to be easily understood.

Statistical significance and p-values have been critiqued recently for a number of reasons, including that they are misused and misinterpreted (Wasserstein & Lazar, 2016) [49] , that researchers deliberately manipulate their analyses to have significant results (Head et al., 2015) [50] , and factor into the difficulty scientists have today in reproducing many of the results of previous social science studies (Peng, 2015). [51] For this reason, we share these principles, adapted from those put forth by the American Statistical Association, [52]  for understanding and using p-values in social science:

• P-values provide evidence against a null hypothesis.
• P-values do not indicate whether the results were produced by random chance alone or if the researcher's hypothesis is true, though both are common misconceptions.
• Statistical significance can be detected in minuscule differences that have very little effect on the real world.
• Nuance is needed to interpret scientific findings, as a conclusion does not become true or false when the p-value passes from p=0.051 to p=0.049.
• Real-world decision-making must use more than reported p-values. It's easy to run analyses of large datasets and only report the significant findings.
• Greater confidence can be placed in studies that pre-register their hypotheses and share their data and methods openly with the public.
• "By itself, a p-value does not provide a good measure of evidence regarding a model or hypothesis. For example, a p-value near 0.05 taken by itself offers only weak evidence against the null hypothesis. Likewise, a relatively large p-value does not imply evidence in favor of the null hypothesis; many other hypotheses may be equally or more consistent with the observed data" (Wasserstein & Lazar, 2016, p. 132).

Confidence intervals

Because of the limitations of p-values, scientists can use other methods to determine whether their models of the world are true. One common approach is to use a confidence interval , or a range of values in which the true value is likely to be found. Confidence intervals are helpful because, as principal #5 above points out, p-values do not measure the size of an effect (Greenland et al., 2016). [53] Remember, something that has very little impact on the world can be statistically significant, and the values in a confidence interval would be helpful. In our example from Table 5.1, imagine our analysis produced a confidence interval that women are 1.2-3.4x more likely to experience "staring or invasion of personal space" than men. As with p-values, calculation for a confidence interval compares what was found in one study with a hypothetical set of results if we repeated the study over and over again. If we calculated 95% confidence intervals for all of the hypothetical set of hundreds and hundreds of studies, that would be our confidence interval. 

Confidence intervals are pretty intuitive. As of this writing, my wife and are expecting our second child. The doctor told us our due date was December 11th. But the doctor also told us that December 11th was only their best estimate. They were actually 95% sure our baby might be born any time in the 30-day period between November 27th and December 25th. Confidence intervals are often listed with a percentage, like 90% or 95%, and a range of values, such as between November 27th and December 25th. You can read that as: "we are 95% sure your baby will be born between November 27th and December 25th because we've studied hundreds of thousands of fetuses and mothers, and we're 95% sure your baby will be within these two dates."

Notice that we're hedging our bets here by using words like "best estimate." When testing hypotheses, social scientists generally phrase their findings in a tentative way, talking about what results "indicate" or "support," rather than making bold statements about what their results "prove." Social scientists have humility because they understand the limitations of their knowledge. In a literature review, using a single study or fact to "prove" an argument right or wrong is often a signal to the person reading your literature review (usually your professor) that you may not have appreciated the limitations of that study or its place in the broader literature on the topic. Strong arguments in a literature review include multiple facts and ideas that span across multiple studies.

You can learn more about creating tables, reading tables, and tests of statistical significance in a class focused exclusively on statistical analysis. We provide links to many free and openly licensed resources on statistics in Chapter 16 . For now, we hope this brief introduction to reading tables will improve your confidence in reading and understanding the results sections in quantitative empirical articles.

Qualitative results

Quantitative articles will contain a lot of numbers and the results of statistical tests demonstrating associations between those numbers. Qualitative articles, on the other hand, will consist mostly of quotations from participants. For most qualitative articles, the authors want to put their results in the words of their participants, as they are the experts. Articles that lack quotations make it difficult to assess whether the researcher interpreted the data in a trustworthy, unbiased manner. These types of articles may also indicate how often particular themes or ideas came up in the data, potentially reflective of how important they were to participants.

Authors often organize qualitative results by themes and subthemes. For example, see this snippet from the results section in Bonanno and Veselak (2019) [54] discussion parents' attitudes towards child mental health information sources.

Data analysis revealed four themes related to participants’ abilities to access mental health help and information for their children, and parents’ levels of trust in these sources. These themes are: others’ firsthand experiences family and friends with professional experience, protecting privacy, and uncertainty about schools as information sources. Trust emerged as an overarching and unifying concept for all of these themes. Others’ firsthand experiences. Several participants reported seeking information from other parents who had experienced mental health struggles similar to their own children. They often referenced friends or family members who had been or would be good sources of information due to their own personal experiences. The following quote from Adrienne demonstrates the importance of firsthand experience: [I would only feel comfortable sharing concerns or asking for advice] if I knew that they had been in the same situation. (Adrienne) Similarly, Michelle said: And I talked to a friend of mine who has kids who have IEPs in the district to see, kind of, how did she go about it. (Michelle) ... Friends/family with professional experience . Several respondents referred to friends or family members who had professional experience with or knowledge of child mental health and suggested that these individuals would be good sources of information. For example, Hannah said: Well, what happened with me was I have an uncle who’s a psychiatrist. Sometimes if he’s up in (a city to the north), he’s retired, I can call him sometimes and get information. (Hannah) Michelle, who was in nursing school, echoed this sentiment: At this point, [if my child’s behavioral difficulties continued], I would probably call one of my [nursing] professors. That’s what I’ve done in the past when I’ve needed help with certain things...I have a professor who I would probably consider a friend who I would probably talk to first. She has a big adolescent practice. (Michelle) (p. 402-403)

The terms in bold above refer to the key themes (i.e., qualitative results) that were present in the data. Researchers will state the process by which they interpret each theme, providing a definition and usually some quotations from research participants. Researchers will also draw connections between themes, note consensus or conflict over themes, and situate the themes within the study context.

Qualitative results are specific to the time, place, and culture in which they arise, so you will have to use your best judgment to determine whether these results are relevant to your study. For example, students in my class at Radford University in Southwest Virginia may be studying rural populations. Would a study on group homes in a large urban city transfer well to group homes in a rural area?

Maybe. But even if you were using data from a qualitative study in another rural area, are all rural areas the same? How is the client population and sociocultural context in the article similar or different to the one in your study? Qualitative studies have tremendous depth, but researchers must be intentional about drawing conclusions about one context based on a study in another context. To make conclusions about how a study applies in another context, researchers need to examine each component of an empirical journal article--they need to annotate!

• The results section of empirical articles are often the most difficult to understand.
• To understand a quantitative results section, look for results that were statistically significant and examine the confidence interval, if provided.
• To understand a qualitative results section, look for definitions of themes or codes and use the quotations provided to understand the participants’ perspective.

Select a quantitative empirical article related to your topic.

• Write down the results the authors identify as statistically significant in the results section.
• How do the authors interpret their results in the discussion section?
• Do the authors provide enough information in the introduction for you to understand their results?

Select a qualitative empirical article relevant to your topic.

• Write down the key themes the authors identify and how they were defined by the participants.

5.2 Annotating empirical journal articles

• Define annotation and describe how to use it to identify, extract, and reflect on the information you need from an article

Annotation refers to the process of writing notes on an article. There are many ways to do this. The most basic technique is to print out the article and build a binder related to your topic. Raul Pacheco-Vega's excellent blog has a post on his approach to taking physical notes. Honestly, while you are there, browse around that website. It is full of amazing tips for students conducting a literature review and graduate research projects. I see a lot of benefits to the paper, pen, and highlighter approach to annotating articles. Personally though, I prefer to use a computer to write notes on an article because my handwriting is terrible and typing notes allows me search for keywords. For other students, electronic notes work best because they cannot afford to print every article that they will use in their paper. No matter what you use, the point is that you need to write notes when you're reading. Reading is research!

There are a number of free software tools you can use to help you annotate a journal article. Most PDF readers like Adobe Acrobat have a commenting and highlighting feature, though the PDF readers included with internet browsers like Google Chrome, Microsoft Edge, and Safari do not have this feature. The best approach may be to use a citation manager like Zotero. Using a citation manager, you can build a library of articles, save your annotations, and link annotations across PDFs using keywords. They also provide integration with word processing programs to help with citations in a reference list

Of course, I don't follow this advice because I have a system that works well for me. I have a PDF open in one computer window and a Word document open in a window next to it. I type notes and copy quotes, listing the page number for each note I take. It's a bit low-tech, but it does make my notes searchable. This way, when I am looking for a concept or quote, I can simply search my notes using the Find feature in Word and get to the information I need.

Annotation and reviewing literature does not have to be a solo project. If are working in a group, you can use the Hypothes.is web browser extension to annotate articles collaboratively. You can also use Google Docs to collaboratively annotate a shared PDF using the commenting feature and write collaborative notes in a shared document. By sharing your highlights and comments, you can split the work of getting the most out of each article you read and build off one another's ideas.

Common annotations

In this section, we present common annotations people make when reading journal articles. These annotations are adapted from Craig Whippo and Raul Pacheco-Vega . If you are annotating on paper, I suggest using different color highlighters for each type of annotation listed below. If you are annotating electronically, you can use the names below as tags to easily find information later. For example, if you are searching for definitions of key concepts, you can either click on the tag for [definitions] in your PDF reader or thumb through a printed copy of article for whatever color or tag you used to indicate definitions of key terms. Most of all, you want to avoid reading through all of your sources again just to find that one thing you know you read somewhere . Time is a graduate student's most valuable resource, so our goal here is to help you spend your time reading the literature wisely.

Personal reflections

Personal reflections are all about you. What do you think? Are there any areas you are confused about? Any new ideas or reflections come to mind while you're reading? Treat these annotations as a means of capturing your first reflections about an article. Write down any questions or thoughts that come to mind as you read. If you think the author says something inaccurate or unsubstantiated, write that down. If you don't understand something, make a note about it and ask your professor. Don't feel bad! Journal articles are hard to understand sometimes, even for professors. Your goal is to critically read the literature, so write down what you think while reading! Table 4.2 contains some questions that might stimulate your thoughts.

Definitions

Note definitions of key terms for your topic. At minimum, you should include a scholarly definition for the concepts represented in your working question. If your working question asks about the process of leaving a relationship with domestic violence, your research proposal will have to explain how you define domestic violence, as well as how you define "leaving" an abusive relationship. While you may already know what you mean by domestic violence, the person reading your research proposal does not.

Annotating definitions also helps you engage with the scholarly debate around your topic. Definitions are often contested among scholars. Some definitions of domestic violence will be more comprehensive, including things such economic abuse or forcing the victim to problematically use substances. Other definitions will be less comprehensive, covering only physical, verbal, and sexual abuse. Often, how someone defines something conceptually is highly related to how they measure it in their study. Since you will have to do both of these things, find a definition that feels right to you or create your own, noting the ways in which it is similar or different from those in the literature.

Definitions are also an important way of dealing with jargon. Becoming familiar with a new content area involves learning the jargon experts use. For example, in the last paragraph I used the term economic abuse, but that's probably not a term you've heard before. If you were conducting a literature review on domestic violence, you would want to search for keywords like economic abuse if they are relevant to your working question. You will also want to know what they mean so you can use them appropriately in designing your study and writing your literature review.

Theoretical perspective

Noting the theoretical perspective of the article can help you interpret the data in the same manner as the author. For example, articles on supervised injection facilities for people who use intravenous drugs most likely come from a harm reduction perspective, and understanding the theory behind harm reduction is important to make sense of empirical results. Articles should be grounded in a theoretical perspective that helps the author conceptualize and understand the data. As we discussed in Chapter 3 , some journal articles are entirely theoretical and help you understand the theories or conceptual models related to your topic. We will help you determine a theoretical perspective for your project in Chapter 7 . For now, it's a good idea to note what theories authors mention when talking about your topic area. Some articles are better about this than others, and many authors make it a bit challenging to find theory (if mentioned at all). In other articles, it may help to note which social work theories are missing  from the literature. For example, a study's findings might address issues of oppression and discrimination, but the authors may not use critical theory to make sense of what happened.

Background knowledge

It's a good idea to note any relevant information the author relies on for background. When an author cites facts or opinions from others, you are subsequently able to get information from multiple articles simultaneously. For example, if we were looking at this meta-analysis about domestic violence , in the introduction section, the authors provide facts from many other sources. These facts will likely be relevant to your inquiry on domestic violence, as well.

As you are looking at background information, you should also note any subtopics or concepts about which there is controversy or consensus. The author may present one viewpoint and then an opposing viewpoint, something you may do in your literature review as well. Similarly, they may present facts that scholars in the field have come to consensus on and describe the ways in which different sources support these conclusions.

Sources of interest

Note any relevant sources the author cites. If there is any background information you plan to use, note the original source of that information. When you write your literature review, cite the original source of a piece of information you are using, which may not be where you initially read it . Remember that you should read and refer to the primary source . If you are reading Article A and the author cites a fact from Article B, you should note Article B in your annotations and use Article B when you cite the fact in your paper. You should also make sure Article A interpreted Article B correctly and scan Article B for any other useful facts.

Research question/Purpose

Authors should be clear about the purpose of their article. Charitable authors will give you a sentence that starts with something like this:

• "The purpose of this research project was..."
• "Our research question was..."
• "The research project was designed to test the following hypothesis..."

Unfortunately, not all authors are so clear, and you may to hunt around for the research question or hypothesis. Generally, in an empirical article, the research question or hypothesis is at the end of the introduction. In non-empirical articles, the author will likely discuss the purpose of the article in the abstract or introduction.

We will discuss in greater detail how to read the results of empirical articles in Chapter 5 . For now, just know that you should highlight any of the key findings of an article. They will be described very briefly in the abstract, and in much more detail in the article itself. In an empirical article, you should look at both the 'Results' and 'Discussion' sections. For a non-empirical article, the key findings will likely be in the conclusion. You can also find them in the topic or concluding sentences in a paragraph within the body of the article.

How do researchers know something when they see it? Found in the 'Methods' section of empirical articles, the measures section is where researchers spell out the tools, or measures, they used to gather data. For quantitative studies, you will want to get familiar with the questions researchers typically use to measure key variables. For example, to measure domestic violence, researchers often use the Conflict Tactics Scale . The more frequently used and cited a measure is, the more we know about how well it works (or not). Qualitative studies will often provide at least some of the interview or focus group questions they used with research participants. They will also include information about how their inquiry and hypotheses may have evolved over time. Keep in mind however, sometimes important information is cut out of an article during editing. If you need more information, consider reaching out to the author directly. Before you do so, check if the author provided an appendix with the information you need or if the article links to a their data and measures as part open data sharing practices.

Who exactly were the study participants and how were they recruited? In quantitative studies, you will want to pay attention to the sample size. Generally, the larger the sample, the greater the study's explanatory power. Additionally, randomly drawn samples are desirable because they leave any variation up to chance. Samples that are conducted out of convenience can be biased and non-representative of the larger population. In qualitative studies, non-random sampling is appropriate but consider this: how well does what we find for this group of people transfer to the people who will be in your study? For qualitative studies and quantitative studies, look for how well the sample is described and whether there are important characteristics missing from the article that you would need to determine the quality of the sample.

Limitations

Honest authors will include these at the end of each article. But you should also note any additional limitations you find with their work as well.

Your annotations

These are just a few suggested annotations, but you can come up with your own. For example, maybe there are annotations you would use for different assignments or for the problem statement in your research proposal. If you have an argument or idea that keeps coming to mind when you read, consider creating an annotation for it so you can remember which part of each article supports your ideas. Whatever works for you. The goal with annotation is to extract as much information from each article while reading, so you don't have to go back through everything again. It's useless to read an article and forget most of what you read. Annotate!

• Begin your search by reading thorough and cohesive literature reviews. Review articles are great sources of information to get a broad perspective of your topic.
• Don’t read an article just to say you’ve read it. Annotate and take notes so you don’t have to re-read it later.
• Use software or paper-and-pencil approaches to write notes on articles.
• Annotation is best used when closely reading an empirical study highly similar to your research project.
• Select an empirical article highly related to the study you would like to conduct.
• Annotate the article using the aforementioned annotations and create some of your own.
• Create the first draft of a summary table with key information from this empirical study that you would like to compare to other empirical studies you closely read.

5.3 Generalizability and transferability of empirical results

• Define generalizability and transferability.
• Assess the generalizability and transferability to how researchers use the results from empirical research studies to make arguments about what is objectively true.
• Relate both concepts to the hierarchy of evidence and the types of articles in the scholarly literature

Now that you have read an empirical article in detail, it's important to put its results in conversation with the broader literature on your topic. In this chapter we discuss two important concepts-- generalizability and   transferability --and the interrelationship between the two. We also explain how these two properties of empirical data impact your literature review and evidence-based practice.

Generalizability

The figure below provides a common approach to assessing empirical evidence. As you move up the pyramid below, you can be more sure that the data contained in those studies generalizes to all people who experience the issue.

As we reviewed in Chapter 1, objective truth is true for everyone, regardless of context. In other words, objective truths generalize beyond the sample of people from whom data were collected to the larger population of people who experience the issue under examination. You can be much more sure that information from a systematic review or meta-analysis will generalize than something from a case study of a single person, pilot projects, and other studies that do not seek to establish generalizability.

The type of article listed here is also related to the types of research methods the authors used. While we cover many of these approaches in this textbook, some of them (like cohort studies) are somewhat less common in social work. Additionally, there is one important research method, survey design, that does not appear in this diagram. Finally, social work research uses many different types of qualitative research--some of which generates more generalizable data than others.

For a refresher on the different types of evidence available in each type of article, refer back to section 4.1. You'll recall the hierarchy of evidence as described by McNeese & Thyer (2004) [55]

• Systematic reviews and meta-analyses
• Randomized controlled trials
• Quasi-experimental studies
• Case-control and cohort studies
• Pre-experimental (or non-experimental) group studies
• Qualitative studies

Because there is further variation in the types of studies used by social work researchers, I expanded the hierarchy of evidence to cover a greater breadth of research methods in Figure 5.3.

Refined information from multiple sources

The top of the hierarchy represents refined scientific information or meta-research . Meta-research uses the scientific method to analyze and improve the scientific production of knowledge. For example, meta-analyses pull together samples of people from all high-quality studies on a given topic area creating a super-study with far more people than any single researcher could feasibly collect data from. Because scientists (and clinical experts) refine data across multiple studies, these represent the most generalizable research findings.

Of course, not all meta-analyses or systematic reviews are of good quality. As a peer reviewer for a scholarly journal, I have seen poor quality systematic reviews that make methodological mistakes—like not including relevant keywords—that lead to incorrect conclusions. Unfortunately, not all errors are caught in the peer review process, and not all limitations are acknowledged by the authors. Just because you are looking at a systematic review does not mean you are looking at THE OBJECTIVE TRUTH. Nevertheless, you can be pretty sure that results from these studies are generalizable to the population in the study’s research question.

A good way to visualize the process of sampling is by examining the procedure used for systematic reviews and meta-analyses to scientifically search for articles. In Figure 5.4 below, you can see how researchers conducting a systematic review identified a large pool of potentially relevant articles, downloaded and analyzed them for relevance, and in the end, analyzed only 71 articles in their systematic review out of a total of 1,589 potentially relevant articles. Because systematic reviews or meta-analyses are intended to make strong, generalizable conclusions, they often exclude studies that still contain good information.

In the process of selecting articles for a meta-analysis and systematic review, researchers may exclude articles with important information for a number of good reasons. No study is perfect, and all research methods decisions come with limitations--including meta-research. Authors conducting a meta-analysis cannot include a study unless researchers provide data for the authors to include in their meta-analysis, and many empirical journal articles do not make their data available. Additionally, a study’s intervention or measures may be a bit different than what researchers want to make conclusions about. This is a key truth applicable across all articles you read—who or what gets selected for analysis in a research project determines how well the project’s results generalize to everyone.

We will talk about this in future chapters as sampling, and in those chapters, we will learn which sampling approaches are intended to support generalizability and which are used for other purposes. For example, availability or convenience sampling is often used to get quick information while random sampling approaches are intended to support generalizability. It is impossible to know everything about your article right now, but by the end of this course, you will have the information you need to critically examine the generalizability of a sample.

Primary sources (empirical studies)

Because refined sources like systematic reviews exclude good studies, they are only a first step in getting to know a topic area. You will need to examine primary sources--the reports of researchers who conducted empirical studies--to make evidence-based conclusions about your topic. Figure 5.3 describes three different types of data and ranks them vertically based on how well you can be sure the information generalizes.

As we will discuss further in our chapter on causal explanations, a key factor in scientifically assessing what happened first. Researchers conducting intervention studies are causing change by providing therapy, housing, or whatever the intervention is and measuring the outcomes of that intervention after they happen. This is unlike survey researchers, who do not introduce an intervention but ask people to self-report information on a questionnaire. Longitudinal surveys are particularly helpful because they can provide a clearer picture of whether the cause came before the effect in a causal relationship, but because they are expensive and time-consuming to conduct, longitudinal studies are relatively rare in the literature and most surveys measure people at only one point in time. Thus, because researchers cannot tightly control the causal variable (an intervention, an experience of abuse, etc.) we can be somewhat less certain of the conclusions of surveys than experiments. At the same time, because surveys measure people in their naturalistic environment rather than in a laboratory or artificial setting, they may do a better job at reducing the potential for the researcher to influence the data a participant provides. Surveys also provide descriptive information--like the number of people with a diagnosis or risk factor--that experiments cannot provide.

Surveys and experiments are commonly used in social work, and we will describe the methods they use in future chapters. When assessing the generalizability of a given survey or experiment, you are looking at whether the methods used by the researchers improve generalizability (or, at least that those methods are intended to improve generalizability). Specifically, there are sampling, measurement, and design decisions that researchers make that can improve generalizability. And once the study is conducted, whether those methods worked as intended also impact generalizability.

We address sampling, measurement, and design in the coming chapters, and you will need more in-depth knowledge of research methods to assess the generalizability of the results you are reading. In the meantime, Figure 5.3 is organized by design, and this is a good starting point for your inquiry since it only requires you to identify the design in each empirical article--which should be included in the abstract and described in detail in the methods section. For more information on how to conduct sampling, measurement, and design in a way that maximizes generalizability, read Part 2 of this textbook.

When searching for design of a study, look for specific keywords that indicate the researcher used methods that do not generalize well like pilot study, pre-experiment, non-experiment, convenience sample, availability sample, and exploratory study. When researchers are seeking to perform a pilot study, they are optimizing for time, not generalizability. Their results may still be useful to you! But, you should not generalize from their study to all people with the issue under analysis without a lot of caution and additional supporting evidence. Instead, you should see whether the lessons from this study might transfer to the context in which you are researching--our next topic.

Qualitative studies use sampling, measures, and designs that do not try to optimize generalizability. Thus, if the results of a qualitative study indicate 10 out of 50 students who participated in the focus group found the mandatory training on harassment to be unhelpful, does that mean 20% of all college students at this university find it unhelpful? Because focus groups and interviews (and other qualitative methods we will discuss) use qualitative methods, they are not concerned with generalizability. It would not make sense to generalize from focus groups to all people in a population. Instead, focus groups methods optimize for trustworthy and authentic research projects that make sure, for example, all themes and quotes in the researcher's report are traceable to quotes from focus group participants. Instead of providing what is generally true, qualitative research provides a thick description of people's experiences so you can understand them. S ubjective inquiry is less generalizable but provides greater depth in understanding people's feelings, beliefs, and decision-making processes within their context. 

In Figure 5.3, you will note that some qualitative studies are ranked higher than others in terms of generalizability. Meta-syntheses are ranked highest because they are meta-research, pooling together the themes and raw data from multiple qualitative studies into a super-study. A meta-synthesis is the qualitative equivalent of a meta-analysis, which analyzes quantitative data. Because the researchers conducting the meta-syntheses aim to make more broad generalizations across research studies, even though generalizability is not strictly the goal. In a similar way, grounded theory studies (a type of qualitative design) aim to produce a testable hypothesis that could generalize. At the bottom of the hierarchy are individual case studies, which report what happens with a single person, organization, or event. It's best not to think too long about the generalizability of qualitative results. When examining qualitative articles, you should be examining their transferability, our topic for the next subsection.

Transferability

Generalizability asks one question: How well does the sample of people in this study represent everyone with this issue? If you read in a study that 50% of people in the sample experienced depression, does that mean 50% of everyone experiences depression? We previewed future discussions in this textbook that will discuss the specific quantitative research methods used to optimize the generalizability of results. By adhering strictly to best practices in sampling, measurement, and design, researchers can provide you with good evidence for the generalizability of their study's results.

Of course, generalizability is not the only question worth asking. Just because a study's sample represents a broader population does not mean it is helpful for making conclusions about your working question. In assessing a study's transferability, you are making a weaker but compelling argument that the conclusions of one study can be applied to understanding the people in your working question and research project. Generalizable results may be applicable because they are broadly transferable across situations, and you can be confident in that when they follow the best practices in this textbook for improving generalizability. However, there may be aspects of a study that make its results difficult to transfer to your topic area.

When evaluating the transferability of a research result to your working question, consider the sample, measures, and design. That is, how data was collected from individuals, who those individuals are, and what researchers did with them. You may find that the samples in generalizable studies do not talk about the specific ethnic, cultural, or geographic group that is in your working question. Similarly, studies that measure the outcomes of substance use treatment by measuring sobriety may not match your working question on moderation, medication adherence, or substitution as an outcome in substance use treatment. Evaluating the transferability of designs may help you identify whether the methods the authors used would be similar to those you might use if you were to conduct a study gathering and collecting your own raw data.

Assessing transferability is more subjective. You are using your knowledge of your topic area and research methods (which are always improving!) to make a reasonable argument about why a given piece of evidence from a primary source helps you understand something. Look back at Table 5.2, your annotations, and the researchers' sampling, data analysis, results, and design. Using your critical thinking (and the knowledge you can in Part 2 and Part 3 of this textbook) you will need to make a reasonable argument that these results transfer to the people, places, and culture that you are talking about in your working question.

In the final chapter of Part 1, we will discuss how to assemble the facts you have taken from journal articles into a literature review that represents what  you think about the topic.

• Developing your theoretical framework
• Conceptual definitions
• Inductive & deductive reasoning

Nomothetic causal explanations

Content warning: examples in this chapter include references to sexual harassment, domestic violence, gender-based violence, the child welfare system, substance use disorders, neonatal abstinence syndrome, child abuse, racism, and sexism.

11.1 Developing your theoretical framework

• Differentiate between theories that explain specific parts of the social world versus those that are more broad and sweeping in their conclusions
• Identify the theoretical perspectives that are relevant to your project and inform your thinking about it
• Define key concepts in your working question and develop a theoretical framework for how you understand your topic.

Theories provide a way of looking at the world and of understanding human interaction. Paradigms are grounded in big assumptions about the world—what is real, how do we create knowledge—whereas theories describe more specific phenomena. Well, we are still oversimplifying a bit. Some theories try to explain the whole world, while others only try to explain a small part. Some theories can be grouped together based on common ideas but retain their own individual and unique features. Our goal is to help you find a theoretical framework that helps you understand your topic more deeply and answer your working question.

Theories: Big and small

In your human behavior and the social environment (HBSE) class, you were introduced to the major theoretical perspectives that are commonly used in social work. These are what we like to call big-T 'T'heories. When you read about systems theory, you are actually reading a synthesis of decades of distinct, overlapping, and conflicting theories that can be broadly classified within systems theory. For example, within systems theory, some approaches focus more on family systems while others focus on environmental systems, though the core concepts remain similar.

Different theorists define concepts in their own way, and as a result, their theories may explore different relationships with those concepts. For example, Deci and Ryan's (1985) [56] self-determination theory discusses motivation and establishes that it is contingent on meeting one's needs for autonomy, competency, and relatedness. By contrast, ecological self-determination theory, as written by Abery & Stancliffe (1996), [57] argues that self-determination is the amount of control exercised by an individual over aspects of their lives they deem important across the micro, meso, and macro levels. If self-determination were an important concept in your study, you would need to figure out which of the many theories related to self-determination helps you address your working question.

Theories can provide a broad perspective on the key concepts and relationships in the world or more specific and applied concepts and perspectives. Table 7.2 summarizes two commonly used lists of big-T Theoretical perspectives in social work. See if you can locate some of the theories that might inform your project.

Competing theoretical explanations

Within each area of specialization in social work, there are many other theories that aim to explain more specific types of interactions. For example, within the study of sexual harassment, different theories posit different explanations for why harassment occurs.

One theory, first developed by criminologists, is called routine activities theory. It posits that sexual harassment is most likely to occur when a workplace lacks unified groups and when potentially vulnerable targets and motivated offenders are both present (DeCoster, Estes, & Mueller, 1999). [60]

Other theories of sexual harassment, called relational theories, suggest that one's existing relationships are the key to understanding why and how workplace sexual harassment occurs and how people will respond when it does occur (Morgan, 1999). [61] Relational theories focus on the power that different social relationships provide (e.g., married people who have supportive partners at home might be more likely than those who lack support at home to report sexual harassment when it occurs).

Finally, feminist theories of sexual harassment take a different stance. These theories posit that the organization of our current gender system, wherein those who are the most masculine have the most power, best explains the occurrence of workplace sexual harassment (MacKinnon, 1979). [62] As you might imagine, which theory a researcher uses to examine the topic of sexual harassment will shape the questions asked about harassment. It will also shape the explanations the researcher provides for why harassment occurs.

For a graduate student beginning their study of a new topic, it may be intimidating to learn that there are so many theories beyond what you’ve learned in your theory classes. What’s worse is that there is no central database of theories on your topic. However, as you review the literature in your area, you will learn more about the theories scientists have created to explain how your topic works in the real world. There are other good sources for theories, in addition to journal articles. Books often contain works of theoretical and philosophical importance that are beyond the scope of an academic journal. Do a search in your university library for books on your topic, and you are likely to find theorists talking about how to make sense of your topic. You don't necessarily have to agree with the prevailing theories about your topic, but you do need to be aware of them so you can apply theoretical ideas to your project.

Applying big-T theories to your topic

The key to applying theories to your topic is learning the key concepts associated with that theory and the relationships between those concepts, or propositions . Again, your HBSE class should have prepared you with some of the most important concepts from the theoretical perspectives listed in Table 7.2. For example, the conflict perspective sees the world as divided into dominant and oppressed groups who engage in conflict over resources. If you were applying these theoretical ideas to your project, you would need to identify which groups in your project are considered dominant or oppressed groups, and which resources they were struggling over. This is a very general example. Challenge yourself to find small-t theories about your topic that will help you understand it in much greater detail and specificity. If you have chosen a topic that is relevant to your life and future practice, you will be doing valuable work shaping your ideas towards social work practice.

Integrating theory into your project can be easy, or it can take a bit more effort. Some people have a strong and explicit theoretical perspective that they carry with them at all times. For me, you'll probably see my work drawing from exchange and choice, social constructionist, and critical theory. Maybe you have theoretical perspectives you naturally employ, like Afrocentric theory or person-centered practice. If so, that's a great place to start since you might already be using that theory (even subconsciously) to inform your understanding of your topic. But if you aren't aware of whether you are using a theoretical perspective when you think about your topic, try writing a paragraph off the top of your head or talking with a friend explaining what you think about that topic. Try matching it with some of the ideas from the broad theoretical perspectives from Table 7.2. This can ground you as you search for more specific theories. Some studies are designed to test whether theories apply the real world while others are designed to create new theories or variations on existing theories. Consider which feels more appropriate for your project and what you want to know.

Another way to easily identify the theories associated with your topic is to look at the concepts in your working question. Are these concepts commonly found in any of the theoretical perspectives in Table 7.2? Take a look at the Payne and Hutchison texts and see if any of those look like the concepts and relationships in your working question or if any of them match with how you think about your topic. Even if they don't possess the exact same wording, similar theories can help serve as a starting point to finding other theories that can inform your project. Remember, HBSE textbooks will give you not only the broad statements of theories but also sources from specific theorists and sub-theories that might be more applicable to your topic. Skim the references and suggestions for further reading once you find something that applies well.

Choose a theoretical perspective from Hutchison, Payne, or another theory textbook that is relevant to your project. Using their textbooks or other reputable sources, identify :

• At least five important concepts from the theory
• What relationships the theory establishes between these important concepts (e.g., as x increases, the y decreases)
• How you can use this theory to better understand the concepts and variables in your project?

Developing your own theoretical framework

Hutchison's and Payne's frameworks are helpful for surveying the whole body of literature relevant to social work, which is why they are so widely used. They are one framework, or way of thinking, about all of the theories social workers will encounter that are relevant to practice. Social work researchers should delve further and develop a theoretical or conceptual framework of their own based on their reading of the literature. In Chapter 8 , we will develop your theoretical framework further, identifying the cause-and-effect relationships that answer your working question. Developing a theoretical framework is also instructive for revising and clarifying your working question and identifying concepts that serve as keywords for additional literature searching. The greater clarity you have with your theoretical perspective, the easier each subsequent step in the research process will be.

Getting acquainted with the important theoretical concepts in a new area can be challenging. While social work education provides a broad overview of social theory, you will find much greater fulfillment out of reading about the theories related to your topic area. We discussed some strategies for finding theoretical information in Chapter 3 as part of literature searching. To extend that conversation a bit, some strategies for searching for theories in the literature include:

• Consider searching for these keywords in the title or abstract, specifically
• Looking at the references and cited by links within theoretical articles and textbooks
• Looking at books, edited volumes, and textbooks that discuss theory
• Talking with a scholar on your topic, or asking a professor if they can help connect you to someone
• Nice authors are clear about how they use theory to inform their research project, usually in the introduction and discussion section.
• For example, from the broad umbrella of systems theory, you might pick out family systems theory if you want to understand the effectiveness of a family counseling program.

It's important to remember that knowledge arises within disciplines, and that disciplines have different theoretical frameworks for explaining the same topic. While it is certainly important for the social work perspective to be a part of your analysis, social workers benefit from searching across disciplines to come to a more comprehensive understanding of the topic. Reaching across disciplines can provide uncommon insights during conceptualization, and once the study is completed, a multidisciplinary researcher will be able to share results in a way that speaks to a variety of audiences. A study by An and colleagues (2015) [63] uses game theory from the discipline of economics to understand problems in the Temporary Assistance for Needy Families (TANF) program. In order to receive TANF benefits, mothers must cooperate with paternity and child support requirements unless they have "good cause," as in cases of domestic violence, in which providing that information would put the mother at greater risk of violence. Game theory can help us understand how TANF recipients and caseworkers respond to the incentives in their environment, and highlight why the design of the "good cause" waiver program may not achieve its intended outcome of increasing access to benefits for survivors of family abuse.

Of course, there are natural limits on the depth with which student researchers can and should engage in a search for theory about their topic. At minimum, you should be able to draw connections across studies and be able to assess the relative importance of each theory within the literature. Just because you found one article applying your theory (like game theory, in our example above) does not mean it is important or often used in the domestic violence literature. Indeed, it would be much more common in the family violence literature to find psychological theories of trauma, feminist theories of power and control, and similar theoretical perspectives used to inform research projects rather than game theory, which is equally applicable to survivors of family violence as workers and bosses at a corporation. Consider using the Cited By feature to identify articles, books, and other sources of theoretical information that are seminal or well-cited in the literature. Similarly, by using the name of a theory in the keywords of a search query (along with keywords related to your topic), you can get a sense of how often the theory is used in your topic area. You should have a sense of what theories are commonly used to analyze your topic, even if you end up choosing a different one to inform your project.

Theories that are not cited or used as often are still immensely valuable. As we saw before with TANF and "good cause" waivers, using theories from other disciplines can produce uncommon insights and help you make a new contribution to the social work literature. Given the privileged position that the social work curriculum places on theories developed by white men, students may want to explore Afrocentricity as a social work practice theory (Pellebon, 2007) [64] or abolitionist social work (Jacobs et al., 2021) [65] when deciding on a theoretical framework for their research project that addresses concepts of racial justice. Start with your working question, and explain how each theory helps you answer your question. Some explanations are going to feel right, and some concepts will feel more salient to you than others. Keep in mind that this is an iterative process. Your theoretical framework will likely change as you continue to conceptualize your research project, revise your research question, and design your study.

By trying on many different theoretical explanations for your topic area, you can better clarify your own theoretical framework. Some of you may be fortunate enough to find theories that match perfectly with how you think about your topic, are used often in the literature, and are therefore relatively straightforward to apply. However, many of you may find that a combination of theoretical perspectives is most helpful for you to investigate your project. For example, maybe the group counseling program for which you are evaluating client outcomes draws from both motivational interviewing and cognitive behavioral therapy. In order to understand the change happening in the client population, you would need to know each theory separately as well as how they work in tandem with one another. Because theoretical explanations and even the definitions of concepts are debated by scientists, it may be helpful to find a specific social scientist or group of scientists whose perspective on the topic you find matches with your understanding of the topic. Of course, it is also perfectly acceptable to develop your own theoretical framework, though you should be able to articulate how your framework fills a gap within the literature.

If you are adapting theoretical perspectives in your study, it is important to clarify the original authors' definitions of each concept. Jabareen (2009) [66] offers that conceptual frameworks are not merely collections of concepts but, rather, constructs in which each concept plays an integral role. [67] A conceptual framework is a network of linked concepts that together provide a comprehensive understanding of a phenomenon. Each concept in a conceptual framework plays an ontological or epistemological role in the framework, and it is important to assess whether the concepts and relationships in your framework make sense together. As your framework takes shape, you will find yourself integrating and grouping together concepts, thinking about the most important or least important concepts, and how each concept is causally related to others.

Much like paradigm, theory plays a supporting role for the conceptualization of your research project. Recall the ice float from Figure 7.1. Theoretical explanations support the design and methods you use to answer your research question. In student projects that lack a theoretical framework, I often see the biases and errors in reasoning that we discussed in Chapter 1 that get in the way of good social science. That's because theories mark which concepts are important, provide a framework for understanding them, and measure their interrelationships. If you are missing this foundation, you will operate on informal observation, messages from authority, and other forms of unsystematic and unscientific thinking we reviewed in Chapter 1 .

Theory-informed inquiry is incredibly helpful for identifying key concepts and how to measure them in your research project, but there is a risk in aligning research too closely with theory. The theory-ladenness of facts and observations produced by social science research means that we may be making our ideas real through research. This is a potential source of confirmation bias in social science. Moreover, as Tan (2016) [68] demonstrates, social science often proceeds by adopting as true the perspective of Western and Global North countries, and cross-cultural research is often when ethnocentric and biased ideas are most visible . In her example, a researcher from the West studying teacher-centric classrooms in China that rely partially on rote memorization may view them as less advanced than student-centered classrooms developed in a Western country simply because of Western philosophical assumptions about the importance of individualism and self-determination. Developing a clear theoretical framework is a way to guard against biased research, and it will establish a firm foundation on which you will develop the design and methods for your study.

• Just as empirical evidence is important for conceptualizing a research project, so too are the key concepts and relationships identified by social work theory.
• Using theory your theory textbook will provide you with a sense of the broad theoretical perspectives in social work that might be relevant to your project.
• Try to find small-t theories that are more specific to your topic area and relevant to your working question.
• In Chapter 2 , you developed a concept map for your proposal. Take a moment to revisit your concept map now as your theoretical framework is taking shape. Make any updates to the key concepts and relationships in your concept map. . If you need a refresher, we have embedded a short how-to video from the University of Guelph Library (CC-BY-NC-SA 4.0) that we also used in Chapter 2 .

11.2 Conceptual definitions

• Define measurement and conceptualization
• Apply Kaplan’s three categories to determine the complexity of measuring a given variable
• Identify the role previous research and theory play in defining concepts
• Distinguish between unidimensional and multidimensional concepts
• Critically apply reification to how you conceptualize the key variables in your research project

In social science, when we use the term  measurement , we mean the process by which we describe and ascribe meaning to the key facts, concepts, or other phenomena that we are investigating. At its core, measurement is about defining one’s terms in as clear and precise a way as possible. Of course, measurement in social science isn’t quite as simple as using a measuring cup or spoon, but there are some basic tenets on which most social scientists agree when it comes to measurement. We’ll explore those, as well as some of the ways that measurement might vary depending on your unique approach to the study of your topic.

An important point here is that measurement does not require any particular instruments or procedures. What it does require is a systematic procedure for assigning scores, meanings, and descriptions to individuals or objects so that those scores represent the characteristic of interest. You can measure phenomena in many different ways, but you must be sure that how you choose to measure gives you information and data that lets you answer your research question. If you're looking for information about a person's income, but your main points of measurement have to do with the money they have in the bank, you're not really going to find the information you're looking for!

The question of what social scientists measure can be answered by asking yourself what social scientists study. Think about the topics you’ve learned about in other social work classes you’ve taken or the topics you’ve considered investigating yourself. Let’s consider Melissa Milkie and Catharine Warner’s study (2011) [69] of first graders’ mental health. In order to conduct that study, Milkie and Warner needed to have some idea about how they were going to measure mental health. What does mental health mean, exactly? And how do we know when we’re observing someone whose mental health is good and when we see someone whose mental health is compromised? Understanding how measurement works in research methods helps us answer these sorts of questions.

As you might have guessed, social scientists will measure just about anything that they have an interest in investigating. For example, those who are interested in learning something about the correlation between social class and levels of happiness must develop some way to measure both social class and happiness. Those who wish to understand how well immigrants cope in their new locations must measure immigrant status and coping. Those who wish to understand how a person’s gender shapes their workplace experiences must measure gender and workplace experiences (and get more specific about which experiences are under examination). You get the idea. Social scientists can and do measure just about anything you can imagine observing or wanting to study. Of course, some things are easier to observe or measure than others.

Observing your variables

In 1964, philosopher Abraham Kaplan (1964) [70] wrote The   Conduct of Inquiry,  which has since become a classic work in research methodology (Babbie, 2010). [71] In his text, Kaplan describes different categories of things that behavioral scientists observe. One of those categories, which Kaplan called “observational terms,” is probably the simplest to measure in social science. Observational terms are the sorts of things that we can see with the naked eye simply by looking at them. Kaplan roughly defines them as conditions that are easy to identify and verify through direct observation. If, for example, we wanted to know how the conditions of playgrounds differ across different neighborhoods, we could directly observe the variety, amount, and condition of equipment at various playgrounds.

Indirect observables , on the other hand, are less straightforward to assess. In Kaplan's framework, they are conditions that are subtle and complex that we must use existing knowledge and intuition to define. If we conducted a study for which we wished to know a person’s income, we’d probably have to ask them their income, perhaps in an interview or a survey. Thus, we have observed income, even if it has only been observed indirectly. Birthplace might be another indirect observable. We can ask study participants where they were born, but chances are good we won’t have directly observed any of those people being born in the locations they report.

Sometimes the measures that we are interested in are more complex and more abstract than observational terms or indirect observables. Think about some of the concepts you’ve learned about in other social work classes—for example, ethnocentrism. What is ethnocentrism? Well, from completing an introduction to social work class you might know that it has something to do with the way a person judges another’s culture. But how would you  measure  it? Here’s another construct: bureaucracy. We know this term has something to do with organizations and how they operate but measuring such a construct is trickier than measuring something like a person’s income. The theoretical concepts of ethnocentrism and bureaucracy represent ideas whose meanings we have come to agree on. Though we may not be able to observe these abstractions directly, we can observe their components.

Kaplan referred to these more abstract things that behavioral scientists measure as constructs.  Constructs  are “not observational either directly or indirectly” (Kaplan, 1964, p. 55), [72] but they can be defined based on observables. For example, the construct of bureaucracy could be measured by counting the number of supervisors that need to approve routine spending by public administrators. The greater the number of administrators that must sign off on routine matters, the greater the degree of bureaucracy. Similarly, we might be able to ask a person the degree to which they trust people from different cultures around the world and then assess the ethnocentrism inherent in their answers. We can measure constructs like bureaucracy and ethnocentrism by defining them in terms of what we can observe. [73]

The idea of coming up with your own measurement tool might sound pretty intimidating at this point. The good news is that if you find something in the literature that works for you, you can use it (with proper attribution, of course). If there are only pieces of it that you like, you can reuse those pieces (with proper attribution and describing/justifying any changes). You don't always have to start from scratch!

Look at the variables in your research question.

• Classify them as direct observables, indirect observables, or constructs.
• Do you think measuring them will be easy or hard?
• What are your first thoughts about how to measure each variable? No wrong answers here, just write down a thought about each variable.

Measurement starts with conceptualization

In order to measure the concepts in your research question, we first have to understand what we think about them. As an aside, the word concept  has come up quite a bit, and it is important to be sure we have a shared understanding of that term. A  concept is the notion or image that we conjure up when we think of some cluster of related observations or ideas. For example, masculinity is a concept. What do you think of when you hear that word? Presumably, you imagine some set of behaviors and perhaps even a particular style of self-presentation. Of course, we can’t necessarily assume that everyone conjures up the same set of ideas or images when they hear the word  masculinity . While there are many possible ways to define the term and some may be more common or have more support than others, there is no universal definition of masculinity. What counts as masculine may shift over time, from culture to culture, and even from individual to individual (Kimmel, 2008). This is why defining our concepts is so important.\

Not all researchers clearly explain their theoretical or conceptual framework for their study, but they should! Without understanding how a researcher has defined their key concepts, it would be nearly impossible to understand the meaning of that researcher’s findings and conclusions. Back in Chapter 7 , you developed a theoretical framework for your study based on a survey of the theoretical literature in your topic area. If you haven't done that yet, consider flipping back to that section to familiarize yourself with some of the techniques for finding and using theories relevant to your research question. Continuing with our example on masculinity, we would need to survey the literature on theories of masculinity. After a few queries on masculinity, I found a wonderful article by Wong (2010) [74] that analyzed eight years of the journal Psychology of Men & Masculinity and analyzed how often different theories of masculinity were used . Not only can I get a sense of which theories are more accepted and which are more marginal in the social science on masculinity, I am able to identify a range of options from which I can find the theory or theories that will inform my project. 

Identify a specific theory (or more than one theory) and how it helps you understand...

• Your independent variable(s).
• Your dependent variable(s).
• The relationship between your independent and dependent variables.

Rather than completing this exercise from scratch, build from your theoretical or conceptual framework developed in previous chapters.

In quantitative methods, conceptualization involves writing out clear, concise definitions for our key concepts. These are the kind of definitions you are used to, like the ones in a dictionary. A conceptual definition involves defining a concept in terms of other concepts, usually by making reference to how other social scientists and theorists have defined those concepts in the past. Of course, new conceptual definitions are created all the time because our conceptual understanding of the world is always evolving.

Conceptualization is deceptively challenging—spelling out exactly what the concepts in your research question mean to you. Following along with our example, think about what comes to mind when you read the term masculinity. How do you know masculinity when you see it? Does it have something to do with men or with social norms? If so, perhaps we could define masculinity as the social norms that men are expected to follow. That seems like a reasonable start, and at this early stage of conceptualization, brainstorming about the images conjured up by concepts and playing around with possible definitions is appropriate. However, this is just the first step. At this point, you should be beyond brainstorming for your key variables because you have read a good amount of research about them

In addition, we should consult previous research and theory to understand the definitions that other scholars have already given for the concepts we are interested in. This doesn’t mean we must use their definitions, but understanding how concepts have been defined in the past will help us to compare our conceptualizations with how other scholars define and relate concepts. Understanding prior definitions of our key concepts will also help us decide whether we plan to challenge those conceptualizations or rely on them for our own work. Finally, working on conceptualization is likely to help in the process of refining your research question to one that is specific and clear in what it asks. Conceptualization and operationalization (next section) are where "the rubber meets the road," so to speak, and you have to specify what you mean by the question you are asking. As your conceptualization deepens, you will often find that your research question becomes more specific and clear.

If we turn to the literature on masculinity, we will surely come across work by Michael Kimmel , one of the preeminent masculinity scholars in the United States. After consulting Kimmel’s prior work (2000; 2008), [75] we might tweak our initial definition of masculinity. Rather than defining masculinity as “the social norms that men are expected to follow,” perhaps instead we’ll define it as “the social roles, behaviors, and meanings prescribed for men in any given society at any one time” (Kimmel & Aronson, 2004, p. 503). [76] Our revised definition is more precise and complex because it goes beyond addressing one aspect of men’s lives (norms), and addresses three aspects: roles, behaviors, and meanings. It also implies that roles, behaviors, and meanings may vary across societies and over time. Using definitions developed by theorists and scholars is a good idea, though you may find that you want to define things your own way.

As you can see, conceptualization isn’t as simple as applying any random definition that we come up with to a term. Defining our terms may involve some brainstorming at the very beginning. But conceptualization must go beyond that, to engage with or critique existing definitions and conceptualizations in the literature. Once we’ve brainstormed about the images associated with a particular word, we should also consult prior work to understand how others define the term in question. After we’ve identified a clear definition that we’re happy with, we should make sure that every term used in our definition will make sense to others. Are there terms used within our definition that also need to be defined? If so, our conceptualization is not yet complete. Our definition includes the concept of "social roles," so we should have a definition for what those mean and become familiar with role theory to help us with our conceptualization. If we don't know what roles are, how can we study them?

Let's say we do all of that. We have a clear definition of the term masculinity with reference to previous literature and we also have a good understanding of the terms in our conceptual definition...then we're done, right? Not so fast. You’ve likely met more than one man in your life, and you’ve probably noticed that they are not the same, even if they live in the same society during the same historical time period. This could mean there are dimensions of masculinity. In terms of social scientific measurement, concepts can be said to have multiple dimensions  when there are multiple elements that make up a single concept. With respect to the term  masculinity , dimensions could based on gender identity, gender performance, sexual orientation, etc.. In any of these cases, the concept of masculinity would be considered to have multiple dimensions.

While you do not need to spell out every possible dimension of the concepts you wish to measure, it is important to identify whether your concepts are unidimensional (and therefore relatively easy to define and measure) or multidimensional (and therefore require multi-part definitions and measures). In this way, how you conceptualize your variables determines how you will measure them in your study. Unidimensional concepts are those that are expected to have a single underlying dimension. These concepts can be measured using a single measure or test. Examples include simple concepts such as a person’s weight, time spent sleeping, and so forth. 

One frustrating this is that there is no clear demarcation between concepts that are inherently unidimensional or multidimensional. Even something as simple as age could be broken down into multiple dimensions including mental age and chronological age, so where does conceptualization stop? How far down the dimensional rabbit hole do we have to go? Researchers should consider two things. First, how important is this variable in your study? If age is not important in your study (maybe it is a control variable), it seems like a waste of time to do a lot of work drawing from developmental theory to conceptualize this variable. A unidimensional measure from zero to dead is all the detail we need. On the other hand, if we were measuring the impact of age on masculinity, conceptualizing our independent variable (age) as multidimensional may provide a richer understanding of its impact on masculinity. Finally, your conceptualization will lead directly to your operationalization of the variable, and once your operationalization is complete, make sure someone reading your study could follow how your conceptual definitions informed the measures you chose for your variables. 

Write a conceptual definition for your independent and dependent variables.

• Cite and attribute definitions to other scholars, if you use their words.
• Describe how your definitions are informed by your theoretical framework.
• Place your definition in conversation with other theories and conceptual definitions commonly used in the literature.
• Are there multiple dimensions of your variables?
• Are any of these dimensions important for you to measure?

Do researchers actually know what we're talking about?

Conceptualization proceeds differently in qualitative research compared to quantitative research. Since qualitative researchers are interested in the understandings and experiences of their participants, it is less important for them to find one fixed definition for a concept before starting to interview or interact with participants. The researcher’s job is to accurately and completely represent how their participants understand a concept, not to test their own definition of that concept.

If you were conducting qualitative research on masculinity, you would likely consult previous literature like Kimmel’s work mentioned above. From your literature review, you may come up with a  working definition  for the terms you plan to use in your study, which can change over the course of the investigation. However, the definition that matters is the definition that your participants share during data collection. A working definition is merely a place to start, and researchers should take care not to think it is the only or best definition out there.

In qualitative inquiry, your participants are the experts (sound familiar, social workers?) on the concepts that arise during the research study. Your job as the researcher is to accurately and reliably collect and interpret their understanding of the concepts they describe while answering your questions. Conceptualization of concepts is likely to change over the course of qualitative inquiry, as you learn more information from your participants. Indeed, getting participants to comment on, extend, or challenge the definitions and understandings of other participants is a hallmark of qualitative research. This is the opposite of quantitative research, in which definitions must be completely set in stone before the inquiry can begin.

The contrast between qualitative and quantitative conceptualization is instructive for understanding how quantitative methods (and positivist research in general) privilege the knowledge of the researcher over the knowledge of study participants and community members. Positivism holds that the researcher is the "expert," and can define concepts based on their expert knowledge of the scientific literature. This knowledge is in contrast to the lived experience that participants possess from experiencing the topic under examination day-in, day-out. For this reason, it would be wise to remind ourselves not to take our definitions too seriously and be critical about the limitations of our knowledge.

Conceptualization must be open to revisions, even radical revisions, as scientific knowledge progresses. While I’ve suggested consulting prior scholarly definitions of our concepts, you should not assume that prior, scholarly definitions are more real than the definitions we create. Likewise, we should not think that our own made-up definitions are any more real than any other definition. It would also be wrong to assume that just because definitions exist for some concept that the concept itself exists beyond some abstract idea in our heads. Building on the paradigmatic ideas behind interpretivism and the critical paradigm, researchers call the assumption that our abstract concepts exist in some concrete, tangible way is known as reification . It explores the power dynamics behind how we can create reality by how we define it.

Returning again to our example of masculinity. Think about our how our notions of masculinity have developed over the past few decades, and how different and yet so similar they are to patriarchal definitions throughout history. Conceptual definitions become more or less popular based on the power arrangements inside of social science the broader world. Western knowledge systems are privileged, while others are viewed as unscientific and marginal. The historical domination of social science by white men from WEIRD countries meant that definitions of masculinity were imbued their cultural biases and were designed explicitly and implicitly to preserve their power. This has inspired movements for cognitive justice as we seek to use social science to achieve global development.

• Measurement is the process by which we describe and ascribe meaning to the key facts, concepts, or other phenomena that we are investigating.
• Kaplan identified three categories of things that social scientists measure including observational terms, indirect observables, and constructs.
• Some concepts have multiple elements or dimensions.
• Researchers often use measures previously developed and studied by other researchers.
• Conceptualization is a process that involves coming up with clear, concise definitions.
• Conceptual definitions are based on the theoretical framework you are using for your study (and the paradigmatic assumptions underlying those theories).
• Whether your conceptual definitions come from your own ideas or the literature, you should be able to situate them in terms of other commonly used conceptual definitions.
• Researchers should acknowledge the limited explanatory power of their definitions for concepts and how oppression can shape what explanations are considered true or scientific.

Think historically about the variables in your research question.

• How has our conceptual definition of your topic changed over time?
• What scholars or social forces were responsible for this change?

Take a critical look at your conceptual definitions.

• How participants might define terms for themselves differently, in terms of their daily experience?
• On what cultural assumptions are your conceptual definitions based?
• Are your conceptual definitions applicable across all cultures that will be represented in your sample?

11.3 Inductive and deductive reasoning

• Describe inductive and deductive reasoning and provide examples of each
• Identify how inductive and deductive reasoning are complementary

Congratulations! You survived the chapter on theories and paradigms. My experience has been that many students have a difficult time thinking about theories and paradigms because they perceive them as "intangible" and thereby hard to connect to social work research. I even had one student who said she got frustrated just reading the word "philosophy."

Rest assured, you do not need to become a theorist or philosopher to be an effective social worker or researcher. However, you should have a good sense of what theory or theories will be relevant to your project, as well as how this theory, along with your working question, fit within the three broad research paradigms we reviewed. If you don't have a good idea about those at this point, it may be a good opportunity to pause and read more about the theories related to your topic area.

Theories structure and inform social work research. The converse is also true: research can structure and inform theory. The reciprocal relationship between theory and research often becomes evident to students when they consider the relationships between theory and research in inductive and deductive approaches to research. In both cases, theory is crucial. But the relationship between theory and research differs for each approach.

While inductive and deductive approaches to research are quite different, they can also be complementary. Let’s start by looking at each one and how they differ from one another. Then we’ll move on to thinking about how they complement one another.

Inductive reasoning

A researcher using inductive reasoning begins by collecting data that is relevant to their topic of interest. Once a substantial amount of data have been collected, the researcher will then step back from data collection to get a bird’s eye view of their data. At this stage, the researcher looks for patterns in the data, working to develop a theory that could explain those patterns. Thus, when researchers take an inductive approach, they start with a particular set of observations and move to a more general set of propositions about those experiences. In other words, they move from data to theory, or from the specific to the general. Figure 8.1 outlines the steps involved with an inductive approach to research.

There are many good examples of inductive research, but we’ll look at just a few here. One fascinating study in which the researchers took an inductive approach is Katherine Allen, Christine Kaestle, and Abbie Goldberg’s (2011) [77] study of how boys and young men learn about menstruation. To understand this process, Allen and her colleagues analyzed the written narratives of 23 young cisgender men in which the men described how they learned about menstruation, what they thought of it when they first learned about it, and what they think of it now. By looking for patterns across all 23 cisgender men’s narratives, the researchers were able to develop a general theory of how boys and young men learn about this aspect of girls’ and women’s biology. They conclude that sisters play an important role in boys’ early understanding of menstruation, that menstruation makes boys feel somewhat separated from girls, and that as they enter young adulthood and form romantic relationships, young men develop more mature attitudes about menstruation. Note how this study began with the data—men’s narratives of learning about menstruation—and worked to develop a theory.

In another inductive study, Kristin Ferguson and colleagues (Ferguson, Kim, & McCoy, 2011) [78] analyzed empirical data to better understand how to meet the needs of young people who are homeless. The authors analyzed focus group data from 20 youth at a homeless shelter. From these data they developed a set of recommendations for those interested in applied interventions that serve homeless youth. The researchers also developed hypotheses for others who might wish to conduct further investigation of the topic. Though Ferguson and her colleagues did not test their hypotheses, their study ends where most deductive investigations begin: with a theory and a hypothesis derived from that theory. Section 8.4 discusses the use of mixed methods research as a way for researchers to test hypotheses created in a previous component of the same research project.

You will notice from both of these examples that inductive reasoning is most commonly found in studies using qualitative methods, such as focus groups and interviews. Because inductive reasoning involves the creation of a new theory, researchers need very nuanced data on how the key concepts in their working question operate in the real world. Qualitative data is often drawn from lengthy interactions and observations with the individuals and phenomena under examination. For this reason, inductive reasoning is most often associated with qualitative methods, though it is used in both quantitative and qualitative research.

Deductive reasoning

If inductive reasoning is about creating theories from raw data, deductive reasoning is about testing theories using data. Researchers using deductive reasoning take the steps described earlier for inductive research and reverse their order. They start with a compelling social theory, create a hypothesis about how the world should work, collect raw data, and analyze whether their hypothesis was confirmed or not. That is, deductive approaches move from a more general level (theory) to a more specific (data); whereas inductive approaches move from the specific (data) to general (theory).

A deductive approach to research is the one that people typically associate with scientific investigation. Students in English-dominant countries that may be confused by inductive vs. deductive research can rest part of the blame on Sir Arthur Conan Doyle, creator of the Sherlock Holmes character. As Craig Vasey points out in his breezy introduction to logic book chapter , Sherlock Holmes more often used inductive rather than deductive reasoning (despite claiming to use the powers of deduction to solve crimes). By noticing subtle details in how people act, behave, and dress, Holmes finds patterns that others miss. Using those patterns, he creates a theory of how the crime occurred, dramatically revealed to the authorities just in time to arrest the suspect. Indeed, it is these flashes of insight into the patterns of data that make Holmes such a keen inductive reasoner. In social work practice, rather than detective work, inductive reasoning is supported by the intuitions and practice wisdom of social workers, just as Holmes' reasoning is sharpened by his experience as a detective.

So, if deductive reasoning isn't Sherlock Holmes' observation and pattern-finding, how does it work? It starts with what you have already done in Chapters 3 and 4, reading and evaluating what others have done to study your topic. It continued with Chapter 5, discovering what theories already try to explain how the concepts in your working question operate in the real world. Tapping into this foundation of knowledge on their topic, the researcher studies what others have done, reads existing theories of whatever phenomenon they are studying, and then tests hypotheses that emerge from those theories. Figure 8.2 outlines the steps involved with a deductive approach to research.

While not all researchers follow a deductive approach, many do. We’ll now take a look at a couple excellent recent examples of deductive research. 

In a study of US law enforcement responses to hate crimes, Ryan King and colleagues (King, Messner, & Baller, 2009) [79] hypothesized that law enforcement’s response would be less vigorous in areas of the country that had a stronger history of racial violence. The authors developed their hypothesis from prior research and theories on the topic. They tested the hypothesis by analyzing data on states’ lynching histories and hate crime responses. Overall, the authors found support for their hypothesis and illustrated an important application of critical race theory.

In another recent deductive study, Melissa Milkie and Catharine Warner (2011) [80] studied the effects of different classroom environments on first graders’ mental health. Based on prior research and theory, Milkie and Warner hypothesized that negative classroom features, such as a lack of basic supplies and heat, would be associated with emotional and behavioral problems in children. One might associate this research with Maslow's hierarchy of needs or systems theory. The researchers found support for their hypothesis, demonstrating that policymakers should be paying more attention to the mental health outcomes of children’s school experiences, just as they track academic outcomes (American Sociological Association, 2011). [81]

Complementary approaches

While inductive and deductive approaches to research seem quite different, they can actually be rather complementary. In some cases, researchers will plan for their study to include multiple components, one inductive and the other deductive. In other cases, a researcher might begin a study with the plan to conduct either inductive or deductive research, but then discovers along the way that the other approach is needed to help illuminate findings. Here is an example of each such case.

Dr. Amy Blackstone (n.d.), author of Principles of sociological inquiry: Qualitative and quantitative methods , relates a story about her mixed methods research on sexual harassment.

We began the study knowing that we would like to take both a deductive and an inductive approach in our work. We therefore administered a quantitative survey, the responses to which we could analyze in order to test hypotheses, and also conducted qualitative interviews with a number of the survey participants. The survey data were well suited to a deductive approach; we could analyze those data to test hypotheses that were generated based on theories of harassment. The interview data were well suited to an inductive approach; we looked for patterns across the interviews and then tried to make sense of those patterns by theorizing about them. For one paper (Uggen & Blackstone, 2004) [82] , we began with a prominent feminist theory of the sexual harassment of adult women and developed a set of hypotheses outlining how we expected the theory to apply in the case of younger women’s and men’s harassment experiences. We then tested our hypotheses by analyzing the survey data. In general, we found support for the theory that posited that the current gender system, in which heteronormative men wield the most power in the workplace, explained workplace sexual harassment—not just of adult women but of younger women and men as well. In a more recent paper (Blackstone, Houle, & Uggen, 2006), [83] we did not hypothesize about what we might find but instead inductively analyzed interview data, looking for patterns that might tell us something about how or whether workers’ perceptions of harassment change as they age and gain workplace experience. From this analysis, we determined that workers’ perceptions of harassment did indeed shift as they gained experience and that their later definitions of harassment were more stringent than those they held during adolescence. Overall, our desire to understand young workers’ harassment experiences fully—in terms of their objective workplace experiences, their perceptions of those experiences, and their stories of their experiences—led us to adopt both deductive and inductive approaches in the work. (Blackstone, n.d., p. 21) [84]

Researchers may not always set out to employ both approaches in their work but sometimes find that their use of one approach leads them to the other. One such example is described eloquently in Russell Schutt’s  Investigating the Social World (2006). [85] As Schutt describes, researchers Sherman and Berk (1984) [86] conducted an experiment to test two competing theories of the effects of punishment on deterring deviance (in this case, domestic violence).Specifically, Sherman and Berk hypothesized that deterrence   theory (see Williams, 2005 [87] for more information on that theory) would provide a better explanation of the effects of arresting accused batterers than labeling theory . Deterrence theory predicts that arresting an accused spouse batterer will  reduce  future incidents of violence. Conversely, labeling theory predicts that arresting accused spouse batterers will  increase  future incidents (see Policastro & Payne, 2013 [88] for more information on that theory). Figure 8.3 summarizes the two competing theories and the hypotheses Sherman and Berk set out to test.

Research from these follow-up studies were mixed. In some cases, arrest deterred future incidents of violence. In other cases, it did not. This left the researchers with new data that they needed to explain. The researchers therefore took an inductive approach in an effort to make sense of their latest empirical observations. The new studies revealed that arrest seemed to have a deterrent effect for those who were married and employed, but that it led to increased offenses for those who were unmarried and unemployed. Researchers thus turned to control theory, which posits that having some stake in conformity through the social ties provided by marriage and employment, as the better explanation (see Davis et al., 2000 [90] for more information on this theory).

What the original Sherman and Berk study, along with the follow-up studies, show us is that we might start with a deductive approach to research, but then, if confronted by new data we must make sense of, we may move to an inductive approach. We will expand on these possibilities in section 8.4 when we discuss mixed methods research.

Ethical and critical considerations

Deductive and inductive reasoning, just like other components of the research process comes with ethical and cultural considerations for researchers. Specifically, deductive research is limited by existing theory. Because scientific inquiry has been shaped by oppressive forces such as sexism, racism, and colonialism, what is considered theory is largely based in Western, white-male-dominant culture. Thus, researchers doing deductive research may artificially limit themselves to ideas that were derived from this context. Non-Western researchers, international social workers, and practitioners working with non-dominant groups may find deductive reasoning of limited help if theories do not adequately describe other cultures.

While these flaws in deductive research may make inductive reasoning seem more appealing, on closer inspection you'll find similar issues apply. A researcher using inductive reasoning applies their intuition and lived experience when analyzing participant data. They will take note of particular themes, conceptualize their definition, and frame the project using their unique psychology. Since everyone's internal world is shaped by their cultural and environmental context, inductive reasoning conducted by Western researchers may unintentionally reinforcing lines of inquiry that derive from cultural oppression.

Inductive reasoning is also shaped by those invited to provide the data to be analyzed. For example, I recently worked with a student who wanted to understand the impact of child welfare supervision on children born dependent on opiates and methamphetamine. Due to the potential harm that could come from interviewing families and children who are in foster care or under child welfare supervision, the researcher decided to use inductive reasoning and to only interview child welfare workers.

Talking to practitioners is a good idea for feasibility, as they are less vulnerable than clients. However, any theory that emerges out of these observations will be substantially limited, as it would be devoid of the perspectives of parents, children, and other community members who could provide a more comprehensive picture of the impact of child welfare involvement on children. Notice that each of these groups has less power than child welfare workers in the service relationship. Attending to which groups were used to inform the creation of a theory and the power of those groups is an important critical consideration for social work researchers.

As you can see, when researchers apply theory to research they must wrestle with the history and hierarchy around knowledge creation in that area. In deductive studies, the researcher is positioned as the expert, similar to the positivist paradigm presented in Chapter 5. We've discussed a few of the limitations on the knowledge of researchers in this subsection, but the position of the "researcher as expert" is inherently problematic. However, it should also not be taken to an extreme. A researcher who approaches inductive inquiry as a naïve learner is also inherently problematic. Just as competence in social work practice requires a baseline of knowledge prior to entering practice, so does competence in social work research. Because a truly naïve intellectual position is impossible—we all have preexisting ways we view the world and are not fully aware of how they may impact our thoughts—researchers should be well-read in the topic area of their research study but humble enough to know that there is always much more to learn.

• Inductive reasoning begins with a set of empirical observations, seeking patterns in those observations, and then theorizing about those patterns.
• Deductive reasoning begins with a theory, developing hypotheses from that theory, and then collecting and analyzing data to test the truth of those hypotheses.
• Inductive and deductive reasoning can be employed together for a more complete understanding of the research topic.
• Though researchers don’t always set out to use both inductive and deductive reasoning in their work, they sometimes find that new questions arise in the course of an investigation that can best be answered by employing both approaches.
• Identify one theory and how it helps you understand your topic and working question.

I encourage you to find a specific theory from your topic area, rather than relying only on the broad theoretical perspectives like systems theory or the strengths perspective. Those broad theoretical perspectives are okay...but I promise that searching for theories about your topic will help you conceptualize and design your research project.

• Using the theory you identified, describe what you expect the answer to be to your working question.
• Define and provide an example of idiographic causal relationships
• Describe the role of causality in quantitative research as compared to qualitative research
• Identify, define, and describe each of the main criteria for nomothetic causal relationships
• Describe the difference between and provide examples of independent, dependent, and control variables
• Define hypothesis, state a clear hypothesis, and discuss the respective roles of quantitative and qualitative research when it comes to hypotheses

Causality  refers to the idea that one event, behavior, or belief will result in the occurrence of another, subsequent event, behavior, or belief. In other words, it is about cause and effect. It seems simple, but you may be surprised to learn there is more than one way to explain how one thing causes another. How can that be? How could there be many ways to understand causality?

Think back to our discussion in Section 5.3 on paradigms [insert chapter link plus link to section 1.2]. You’ll remember the positivist paradigm as the one that believes in objectivity. Positivists look for causal explanations that are universally true for everyone, everywhere  because they seek objective truth. Interpretivists, on the other hand, look for causal explanations that are true for individuals or groups in a specific time and place because they seek subjective truths. Remember that for interpretivists, there is not one singular truth that is true for everyone, but many truths created and shared by others.

"Are you trying to generalize or nah?"

One of my favorite classroom moments occurred in the early days of my teaching career. Students were providing peer feedback on their working questions. I overheard one group who was helping someone rephrase their research question. A student asked, “Are you trying to generalize or nah?” Teaching is full of fun moments like that one. Answering that one question can help you understand how to conceptualize and design your research project.

Nomothetic causal explanations are incredibly powerful. They allow scientists to make predictions about what will happen in the future, with a certain margin of error. Moreover, they allow scientists to generalize —that is, make claims about a large population based on a smaller sample of people or items. Generalizing is important. We clearly do not have time to ask everyone their opinion on a topic or test a new intervention on every person. We need a type of causal explanation that helps us predict and estimate truth in all situations.

Generally, nomothetic causal relationships work best for explanatory research projects [INSERT SECTION LINK]. They also tend to use quantitative research: by boiling things down to numbers, one can use the universal language of mathematics to use statistics to explore those relationships. On the other hand, descriptive and exploratory projects often fit better with idiographic causality. These projects do not usually try to generalize, but instead investigate what is true for individuals, small groups, or communities at a specific point in time. You will learn about this type of causality in the next section. Here, we will assume you have an explanatory working question. For example, you may want to know about the risk and protective factors for a specific diagnosis or how a specific therapy impacts client outcomes.

What do nomothetic causal explanations look like?

Nomothetic causal explanations express relationships between variables . The term variable has a scientific definition. This one from Gillespie & Wagner (2018) "a logical grouping of attributes that can be observed and measured and is expected to vary from person to person in a population" (p. 9). [91] More practically, variables are the key concepts in your working question. You know, the things you plan to observe when you actually do your research project, conduct your surveys, complete your interviews, etc. These things have two key properties. First, they vary , as in they do not remain constant. "Age" varies by number. "Gender" varies by category. But they both vary. Second, they have attributes . So the variable "health professions" has attributes or categories, such as social worker, nurse, counselor, etc.

It's also worth reviewing what is  not a variable. Well, things that don't change (or vary) aren't variables. If you planned to do a study on how gender impacts earnings but your study only contained women, that concept would not vary . Instead, it would be a constant . Another common mistake I see in students' explanatory questions is mistaking an attribute for a variable. "Men" is not a variable. "Gender" is a variable. "Virginia" is not a variable. The variable is the "state or territory" in which someone or something is physically located.

When one variable causes another, we have what researchers call independent and dependent variables. For example, in a study investigating the impact of spanking on aggressive behavior, spanking would be the independent variable and aggressive behavior would be the dependent variable. An independent variable is the cause, and a  dependent variable  is the effect. Why are they called that? Dependent variables  depend on independent variables. If all of that gets confusing, just remember the graphical relationship in Figure 8.5.

Write out your working question, as it exists now. As we said previously in the subsection, we assume you have an explanatory research question for learning this section.

• Write out a diagram similar to Figure 8.5.
• Put your independent variable on the left and the dependent variable on the right.
• Can your variables vary?
• Do they have different attributes or categories that vary from person to person?
• How does the theory you identified in section 8.1 help you understand this causal relationship?

If the theory you've identified isn't much help to you or seems unrelated, it's a good indication that you need to read more literature about the theories related to your topic.

For some students, your working question may not be specific enough to list an independent or dependent variable clearly. You may have "risk factors" in place of an independent variable, for example. Or "effects" as a dependent variable. If that applies to your research question, get specific for a minute even if you have to revise this later. Think about which specific risk factors or effects you are interested in. Consider a few options for your independent and dependent variable and create diagrams similar to Figure 8.5.

Finally, you are likely to revisit your working question so you may have to come back to this exercise to clarify the causal relationship you want to investigate.

For a ten-cent word like "nomothetic," these causal relationships should look pretty basic to you. They should look like "x causes y." Indeed, you may be looking at your causal explanation and thinking, "wow, there are so many other things I'm missing in here." In fact, maybe my dependent variable sometimes causes changes in my independent variable! For example, a working question asking about poverty and education might ask how poverty makes it more difficult to graduate college or how high college debt impacts income inequality after graduation. Nomothetic causal relationships are slices of reality. They boil things down to two (or often more) key variables and assert a one-way causal explanation between them. This is by design, as they are trying to generalize across all people to all situations. The more complicated, circular, and often contradictory causal explanations are idiographic, which we will cover in the next section of this chapter.

Developing a hypothesis

A hypothesis   is a statement describing a researcher’s expectation regarding what they anticipate finding. Hypotheses in quantitative research are a nomothetic causal relationship that the researcher expects to determine is true or false. A hypothesis is written to describe the expected relationship between the independent and dependent variables. In other words, write the answer to your working question using your variables. That's your hypothesis! Make sure you haven't introduced new variables into your hypothesis that are not in your research question. If you have, write out your hypothesis as in Figure 8.5.

A good hypothesis should be testable using social science research methods. That is, you can use a social science research project (like a survey or experiment) to test whether it is true or not. A good hypothesis is also  specific about the relationship it explores. For example, a student project that hypothesizes, "families involved with child welfare agencies will benefit from Early Intervention programs," is not specific about what benefits it plans to investigate. For this student, I advised her to take a look at the empirical literature and theory about Early Intervention and see what outcomes are associated with these programs. This way, she could  more clearly state the dependent variable in her hypothesis, perhaps looking at reunification, attachment, or developmental milestone achievement in children and families under child welfare supervision.

Your hypothesis should be an informed prediction based on a theory or model of the social world. For example, you may hypothesize that treating mental health clients with warmth and positive regard is likely to help them achieve their therapeutic goals. That hypothesis would be based on the humanistic practice models of Carl Rogers. Using previous theories to generate hypotheses is an example of deductive research. If Rogers’ theory of unconditional positive regard is accurate, a study comparing clinicians who used it versus those who did not would show more favorable treatment outcomes for clients receiving unconditional positive regard.

Let’s consider a couple of examples. In research on sexual harassment (Uggen & Blackstone, 2004), [92] one might hypothesize, based on feminist theories of sexual harassment, that more females than males will experience specific sexually harassing behaviors. What is the causal relationship being predicted here? Which is the independent and which is the dependent variable? In this case, researchers hypothesized that a person’s sex (independent variable) would predict their likelihood to experience sexual harassment (dependent variable).

Sometimes researchers will hypothesize that a relationship will take a specific direction. As a result, an increase or decrease in one area might be said to cause an increase or decrease in another. For example, you might choose to study the relationship between age and support for legalization of marijuana. Perhaps you’ve taken a sociology class and, based on the theories you’ve read, you hypothesize that age is negatively related to support for marijuana legalization. [93] What have you just hypothesized?

You have hypothesized that as people get older, the likelihood of their supporting marijuana legalization decreases. Thus, as age (your independent variable) moves in one direction (up), support for marijuana legalization (your dependent variable) moves in another direction (down). So, a direct relationship (or positive correlation) involve two variables going in the same direction and an inverse relationship (or negative correlation) involve two variables going in opposite directions. If writing hypotheses feels tricky, it is sometimes helpful to draw them out and depict each of the two hypotheses we have just discussed.

It’s important to note that once a study starts, it is unethical to change your hypothesis to match the data you find. For example, what happens if you conduct a study to test the hypothesis from Figure 8.7 on support for marijuana legalization, but you find no relationship between age and support for legalization? It means that your hypothesis was incorrect, but that’s still valuable information. It would challenge what the existing literature says on your topic, demonstrating that more research needs to be done to figure out the factors that impact support for marijuana legalization. Don’t be embarrassed by negative results, and definitely don’t change your hypothesis to make it appear correct all along!

Criteria for establishing a nomothetic causal relationship

Let’s say you conduct your study and you find evidence that supports your hypothesis, as age increases, support for marijuana legalization decreases. Success! Causal explanation complete, right? Not quite.

You’ve only established one of the criteria for causality. The criteria for causality must include all of the following: covariation, plausibility, temporality, and nonspuriousness. In our example from Figure 8.7, we have established only one criteria—covariation. When variables covary , they vary together. Both age and support for marijuana legalization vary in our study. Our sample contains people of varying ages and varying levels of support for marijuana legalization. If, for example, we only included 16-year-olds in our study, age would be a  constant , not a variable.

Just because there might be some correlation between two variables does not mean that a causal relationship between the two is really plausible. Plausibility means that in order to make the claim that one event, behavior, or belief causes another, the claim has to make sense. It makes sense that people from previous generations would have different attitudes towards marijuana than younger generations. People who grew up in the time of Reefer Madness or the hippies may hold different views than those raised in an era of legalized medicinal and recreational use of marijuana. Plausibility is of course helped by basing your causal explanation in existing theoretical and empirical findings.

Once we’ve established that there is a plausible relationship between the two variables, we also need to establish whether the cause occurred before the effect, the criterion of temporality . A person’s age is a quality that appears long before any opinions on drug policy, so temporally the cause comes before the effect. It wouldn’t make any sense to say that support for marijuana legalization makes a person’s age increase. Even if you could predict someone’s age based on their support for marijuana legalization, you couldn’t say someone’s age was caused by their support for legalization of marijuana.

Finally, scientists must establish nonspuriousness. A spurious relationship is one in which an association between two variables appears to be causal but can in fact be explained by some third variable. This third variable is often called a confound or confounding variable because it clouds and confuses the relationship between your independent and dependent variable, making it difficult to discern the true causal relationship is.

Continuing with our example, we could point to the fact that older adults are less likely to have used marijuana recreationally. Maybe it is actually recreational use of marijuana that leads people to be more open to legalization, not their age. In this case, our confounding variable would be recreational marijuana use. Perhaps the relationship between age and attitudes towards legalization is a spurious relationship that is accounted for by previous use. This is also referred to as the third variable problem , where a seemingly true causal relationship is actually caused by a third variable not in the hypothesis. In this example, the relationship between age and support for legalization could be more about having tried marijuana than the age of the person.

Quantitative researchers are sensitive to the effects of potentially spurious relationships. As a result, they will often measure these third variables in their study, so they can control for their effects in their statistical analysis. These are called  control variables , and they refer to potentially confounding variables whose effects are controlled for mathematically in the data analysis process. Control variables can be a bit confusing, and we will discuss them more in Chapter 10, but think about it as an argument between you, the researcher, and a critic.

Researcher: “The older a person is, the less likely they are to support marijuana legalization.” Critic: “Actually, it’s more about whether a person has used marijuana before. That is what truly determines whether someone supports marijuana legalization.” Researcher: “Well, I measured previous marijuana use in my study and mathematically controlled for its effects in my analysis. Age explains most of the variation in attitudes towards marijuana legalization.”

Let’s consider a few additional, real-world examples of spuriousness. Did you know, for example, that high rates of ice cream sales have been shown to cause drowning? Of course, that’s not really true, but there is a positive relationship between the two. In this case, the third variable that causes both high ice cream sales and increased deaths by drowning is time of year, as the summer season sees increases in both (Babbie, 2010). [94]

Here’s another good one: it is true that as the salaries of Presbyterian ministers in Massachusetts rise, so too does the price of rum in Havana, Cuba. Well, duh, you might be saying to yourself. Everyone knows how much ministers in Massachusetts love their rum, right? Not so fast. Both salaries and rum prices have increased, true, but so has the price of just about everything else (Huff & Geis, 1993). [95]

Finally, research shows that the more firefighters present at a fire, the more damage is done at the scene. What this statement leaves out, of course, is that as the size of a fire increases so too does the amount of damage caused as does the number of firefighters called on to help (Frankfort-Nachmias & Leon-Guerrero, 2011). [96] In each of these examples, it is the presence of a confounding variable that explains the apparent relationship between the two original variables.

In sum, the following criteria must be met for a nomothetic causal relationship:

• The two variables must vary together.
• The relationship must be plausible.
• The cause must precede the effect in time.
• The relationship must be nonspurious (not due to a confounding variable).

The hypothetico-dedutive method

The primary way that researchers in the positivist paradigm use theories is sometimes called the hypothetico-deductive method (although this term is much more likely to be used by philosophers of science than by scientists themselves). Researchers choose an existing theory. Then, they make a prediction about some new phenomenon that should be observed if the theory is correct. Again, this prediction is called a hypothesis. The researchers then conduct an empirical study to test the hypothesis. Finally, they reevaluate the theory in light of the new results and revise it if necessary.

This process is usually conceptualized as a cycle because the researchers can then derive a new hypothesis from the revised theory, conduct a new empirical study to test the hypothesis, and so on. As Figure 8.8 shows, this approach meshes nicely with the process of conducting a research project—creating a more detailed model of “theoretically motivated” or “theory-driven” research. Together, they form a model of theoretically motivated research. 

Keep in mind the hypothetico-deductive method is only one way of using social theory to inform social science research. It starts with describing one or more existing theories, deriving a hypothesis from one of those theories, testing your hypothesis in a new study, and finally reevaluating the theory based on the results data analyses. This format works well when there is an existing theory that addresses the research question—especially if the resulting hypothesis is surprising or conflicts with a hypothesis derived from a different theory.

But what if your research question is more interpretive? What if it is less about theory-testing and more about theory-building? This is what our next chapters will cover: the process of inductively deriving theory from people's stories and experiences. This process looks different than that depicted in Figure 8.8. It still starts with your research question and answering that question by conducting a research study. But instead of testing a hypothesis you created based on a theory, you will create a theory of your own that explain the data you collected. This format works well for qualitative research questions and for research questions that existing theories do not address.

• In positivist and quantitative studies, the goal is often to understand the more general causes of some phenomenon rather than the idiosyncrasies of one particular instance, as in an idiographic causal relationship.
• Nomothetic causal explanations focus on objectivity, prediction, and generalization.
• Criteria for nomothetic causal relationships require the relationship be plausible and nonspurious; and that the cause must precede the effect in time.
• In a nomothetic causal relationship, the independent variable causes changes in the dependent variable.
• Hypotheses are statements, drawn from theory, which describe a researcher’s expectation about a relationship between two or more variables.
• Write out your working question and hypothesis.
• Defend your hypothesis in a short paragraph, using arguments based on the theory you identified in section 8.1.
• Review the criteria for a nomothetic causal relationship. Critique your short paragraph about your hypothesis using these criteria.
• Are there potentially confounding variables, issues with time order, or other problems you can identify in your reasoning?

Inductive & deductive (deductive focus)

9. Writing your research question Copyright © 2020 by Matthew DeCarlo is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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Social Work Research Guide

• Getting Started
• Finding Articles
• Finding Books
• Citing Sources - APA
• Developing a Research Question
• Literature Review Assignment
• Annotated Bibliography Assignment

From Topic to Question

• What makes a good research question?
• QuickSearch
• Using Google

In chapter 2 of  Research Methods for Social Workers: An Introduction , the authors describe the criteria for determining whether you have a good research question. There are four elements to consider when evaluating your research question:

Researchable

• Ethical and culturally sensitive

A relevant research question is one whose answers will have an impact on policies, theories, or practices related to the social work profession. Other factors determining the relevance include the organization who funds the research, the program that houses it, and the research team that undertakes it.

Generally, questions that involve moral or faith-based decisions are outside of the realm of research. A researchable question is appropriate for scientific inquiry, where it is possible to collect viable and reliable data to answer the question.

Feasibility

What are the resources available to you to conduct this research? The scope of the research study might be limited because of your resources, or lack thereof. Could you practically do what you have planned?

Ethical and Cultural Acceptability

The way your research question is phrased as well as the way the study is eventually conducted have the potential to cause harm. As you begin your research for the literature review, you will become more aware of what came before on a similar topic, including anything that study missed. 

If you are struggling to develop a good research question talk to your professor or contact me! 

QuickSearch is a tool that searches across many of the resources available to you at SHU Library. With one search box, you can search keywords for your topic and the results will include books, eBooks, peer-reviewed articles, as well as newspapers, magazines and other media (like streaming video).

QuickSearch is a good place to start your research for your topic. With the results you get a general idea of what is available about the topic and you have the ability to start reading through the research. 

You can use the search box below to test it out.

• What am I searching?

For more information about using QuickSearch, watch the video below. 

Google is a natural place to start for all of use when looking for information. It's easy to use and generally gives you the answers you want or need. 

When it comes to academic research though, it might not be the best option. Typing in "palliative care" gives you more than 26 million results with no easy way to narrow them down or to know what is reputable, scholarly and peer-reviewed. Don't get me wrong, you could probably figure all that out with a Google search, but how much time would you end up spending to do so?

A better option is to do a search in Google Scholar. This will search through scholarly books, research articles, open access and subscription journals. So it narrows down to the resources you need to consult (are required to consult) in research in the Social Work field.

The biggest drawback is that you might not get full-text access to all of the citations, articles and books available in a Google Scholar search. Check out the Research Tools at SHU page in this guide to find out about Citation Linker and Journal Finder, which can help connect you to the resources you find in a Google Scholar search.

The pitfalls of Google

Google dominates our lives in so many ways. They are the most used search engine (about 65% of the market). Doesn't everyone use Chrome and have a Gmail account? Google knows a lot about us, but we don't know everything about them.

How does Google decide on the search results and the order they display? 

Many factors influence this:

• Your search history
• Your location
• What other people are searching
• Money: ads and sponsored content

It is important to be aware of these issues, not only when searching for an assignment, but even when you need some information for your personal life. These factors can sway your search results.

Sometimes this is okay. If you are looking for information about a place to eat lunch, you want to get results that are closest to you, not in a totally different state.  

Here is a very informative and complex infographic about this issue:  http://www.seobook.com/learn-seo/infographics/how-search-works.php 

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Module 2 Chapter 1: The Nature of Social Work Research Questions

The search for empirical evidence typically begins with a question or hypothesis. The nature of the questions asked determine many features of the studies that lead to answers: the study approach, design, measurement, participant selection, data collection, data analysis, and reporting of results. Not just any type of question will do, however:

“When the question is poorly formulated, the design, analysis, sample size calculations, and presentation of results may not be optimal. The gap between research and clinical practice could be bridged by a clear, complete, and informative research question” (Mayo, Asano, & Barbic, 2013, 513).

The topic concerning the nature of social work research questions has two parts: what constitutes a research question, and what makes it a social work question. We begin this chapter by examining a general model for understanding where different types of questions fit into the larger picture of knowledge building explored in Module 1. We then look at research questions and social work questions separately. Finally, we reassemble them to identify strong social work research questions.

In this chapter, you will learn:

• 4 types of social work research for knowledge building,
• characteristics of research questions,
• characteristics of social work research questions.

Translational Science

The concept of translational science addresses the application of basic science discoveries and knowledge to routine professional practice. In medicine, the concept is sometimes described as “bench to trench,” meaning that it takes what is learned at the laboratory “bench” to practitioners’ work in the real-world, or “in the trenches.” This way of thinking is about applied science—research aimed at eventual applications to create or support change. Figure 1-1 assembles the various pieces of the translational science knowledge building enterprise:

Figure 1-1. Overview of translational science elements

Basic Research .   Federal policy defines basic research  as systematic study that is directed toward understanding the fundamental aspects of phenomena without specific applications in mind (adapted from 32 CFR 272.3). Basic research efforts are those designed to describe something or answer questions about its nature. Basic research in social and behavioral science addresses questions of at least two major types: epidemiology  and  etiology  questions.

Epidemiology questions. Questions about the nature of a population, problem, or social phenomenon are often answered through epidemiological methods. Epidemiology is the branch of science (common in public health) for understanding how a problem or phenomenon is distributed in a population. Epidemiologists also ask and address questions related to the nature of relationships between problems or phenomena—such as the relationship between opioid misuse and infectious disease epidemics (NAS, 2018). One feature offered by epidemiological research is a picture of trends over time. Consider, for example, epidemiology data from the Centers for Disease Control and Prevention (the CDC) regarding trends in suicide rates in the state of Ohio over a four-year period (see Figure 1-2, created from data presented by CDC WONDER database).

Figure 1-2. Graph reflecting Ohio trend in suicide rate, 2012-2016

Since the upward trend is of concern, social workers might pursue additional questions to examine possible causes of the observed increases, as well as what the increase might mean to the expanded need for supportive services to families and friends of these individuals. The epidemiological data can help tease out some of these more nuanced answers. For example, epidemiology also tells us that firearms were the recorded cause in 46.9% of known suicide deaths among individuals aged 15-24 years across the nation during 2016 (CDC, WONDER database). Not only do we now know the numbers of suicide deaths in this age group, we know something about a relevant factor that might be addressed through preventive intervention and policy responses.

Epidemiology also addresses questions about the size and characteristics of a population being impacted by a problem or the scope of a problem. For example, a social worker might have a question about the “shape” of a problem defined as sexual violence victimization. Data from the United States’ 2010-2012 National Intimate Partner and Sexual Violence Survey (NISVS) indicated that over 36% of woman (1 in 3) and 17% of men (1 in 6) have experienced sexual violence involving physical contact at some point in their lives; the numbers vary by state, from 29.5% to 47.5% for women and 10.4% to 29.3% for men (Smith et al., 2017).

In developing informed responses to a problem, it helps to know for whom it is a problem. Practitioners, program administrators, and policy decision makers may not be aware that the problem of sexual violence is so prevalent, or that men are victimized at worrisome rates, as well as women. It is also helpful to know how the problem of interest might interface with other problems. For example, the interface between perpetrating sexual assault and alcohol use was examined in a study of college men (Testa & Cleveland, 2017). The study investigators determined that frequently attending parties and bars was associated with a greater probability of perpetrating sexual assault. Thus, epidemiological research helps answer questions about the scope and magnitude of a problem, as well as how it relates to other issues or factors, which can then inform next steps in research to address the problem.

Etiology questions.  Etiology research tests theories and hypotheses about the origins and natural course of a problem or phenomenon. This includes answering questions about factors that influence the appearance or course of a problem—these may be factors that mediate or moderate the phenomenon’s development or progression (e.g., demographic characteristics, co-occurring problems, or other environmental processes). To continue with our intimate partner violence example, multiple theories are presented in the literature concerning the etiology of intimate partner violence perpetration—theories also exist concerning the etiology of being the target of intimate partner violence (Begun, 2003). Perpetration theories include:

• personality/character traits
• biological/hereditary/genetic predisposition
• social learning/behavior modeling
• social skills
• self-esteem
• cultural norms (Begun, 2003, p. 642).

Evidence supporting each of these theories exists, to some degree; each theory leads to the development of a different type of prevention or intervention response. The “best” interventions will be informed by theories with the strongest evidence or will integrate elements from multiple evidence-supported theories.

Etiology research is often about understanding the mechanisms underlying the phenomena of interest. The questions are “how” questions—how does this happen (or not)? For example, scientists asked the question: how do opioid medications (used to manage pain) act on neurons compared to opioids that naturally occur in the brain (Stoeber et al., 2018)? They discovered that opioid medications used to treat pain bind to receptors  inside n erve cells, which is a quite different mechanism than the conventional wisdom that they behave the same way that naturally occurring (endogenous) opioids do—binding only on the surface  of nerve cells. Understanding this mechanism opens new options for developing pain relievers that are less- or non-addicting than current opioid medicines like morphine and oxycodone. Once these mechanisms of change are understood, interventions can be developed, then tested through intervention research approaches.

Intervention Research.  Interventions are designed around identified needs: epidemiology research helps to support intervention design by identify the needs. Epidemiology research also helps identify theories concerning the causes and factors affecting social work problems. Intervention development is further supported by later theory-testing and etiology research. However, developing an intervention is not sufficient: interventions need to be tested and evaluated to ensure that they are (1) safe, (2) effective, and (3) cost-efficient to deliver. This is where  intervention research  comes into play. Consider the example of Motivational Interviewing (MI) approaches to addressing client ambivalence about engaging in a behavior change effort. Early research concerning MI addressed questions about its effectiveness. For example, a meta-analytic review reported that “MI should be considered as a treatment for adolescent substance abuse” because the evidence demonstrated small, but significant effect sizes, and that the treatment gains were retained over time (Jensen et al., 2011). Subsequently, when its safety and effectiveness were consistently demonstrated through this kind of evidence, investigators assessed MI as cost-efficient or cost-effective. For example, MI combined with providing feedback was demonstrated to be cost-effective in reducing drinking among college students who engaged in heavy drinking behavior (Cowell et al., 2012).

Intervention research not only is concerned with the outcomes of delivering an intervention, but may also address the mechanisms of change  through which an intervention has its effects—not only what changes happen, but how  they happen. For example, investigators are exploring  how  psychotherapy works, moving beyond demonstrating that  it works (Ardito & Rabellino, 2011; Kazdin, 2007; Wampold, 2015). One mechanism that has garnered attention is the role of therapeutic alliance—the relationships, bonds, and interactions that occur in the context of treatment—on treatment outcomes.

Therapeutic alliance is one common factor identified across numerous types of effective psychotherapeutic approaches (Wampold, 2015). Authors summarizing a number of studies about therapeutic alliance and its positive relationship to treatment outcomes concluded that the quality of therapeutic alliance may be a more powerful predictor of positive outcome than is the nature or type of intervention delivered (Ardito & Rabellino, 2011). However, it is important to determine the extent to which (a) therapeutic alliance enhances clients’ symptom improvement, (b) gradual improvements in symptoms lead to enhanced therapeutic alliance, or (c) the relationship between therapeutic alliance and symptom improvement are iterative—they go back and forth, influencing each other over time (Kazdin, 2007).

Implementation Science . Social work and other disciplines have produced a great deal of evidence about “what works” for intervening around a great number of social work problems. Unfortunately, many best practices with this kind of evidence support are slow to become common practices.  Implementation science  is about understanding facilitators and barriers to these evidence-supported interventions becoming adopted into routine practice: characteristics of the interventions themselves, conditions and processes operating in the organizations where interventions are implemented, and factors external to these organizations all influence practitioners’ adoption of evidence supported interventions.

Even under optimal internal organizational conditions, implementation can be undermined by changes in organizations’ external environments, such as fluctuations in funding, adjustments in contracting practices, new technology, new legislation, changes in clinical practice guidelines and recommendations, or other environmental shifts” (Birken, et al, 2017).

Research for/about Research . In addition, social work investigators engage in research that is specifically about scientific methodology. This is where advances in measurement, participant recruitment and retention, and data analysis emerge. The results of these kinds of research studies are used to improve the research in basic, intervention, and implementation research. Later in the course you will see some of these products in action as we learn about best practices in research and evaluation methodology. Here are a few examples related to measurement methods:

• Concept mapping to assess community needs of sexual minority youth (Davis, Saltzburg, & Locke, 2010)
• Field methodologies for measuring college student drinking in natural environments (Clapp et al., 2007)
• Intergenerational contact measurement (Jarrott, Weaver, Bowen, & Wang, 2018)
• Perceived Social Competence Scale-II (Anderson-Butcher et al., 2016)
• Safe-At-Home Instrument to measure readiness to change intimate partner violence behavior (Begun et al., 2003; 2008; Sielski, Begun, & Hamel, 2015)
• Teamwork Scale for Youth (Lower, Newman, & Anderson-Butcher, 2016)

And, here are a few examples related to involving participants in research studies:

• Conducting safe research with at risk populations (Kyriakakis, Waller, Kagotho, & Edmond, 2015)
• Recruitment strategies for non-treatment samples in addiction studies (Subbaraman et al., 2015)
• Variations in recruitment results across Internet platforms (Shao et al., 2015)

Take a moment to complete the following activity.

Research Questions

In this section, we take a closer look at research questions and their relationship to the types of research conducted by investigators. It may be easier to understand research questions by first ruling out what are not research questions. In that spirit, let’s begin with examples of questions where applying research methods will not help to find answers:

• Trauma informed education. The first issue with this example is obvious: it is not worded as a question. The second is critically important: this is a general topic, it is not a research question. This topic is too vague and broad making it impossible to determine what answers would look like or how to approach finding answers.
• How is my client feeling about what just happened? This type of question about an individual is best answered by asking clinical questions of that individual, within the context of the therapeutic relationship, not by consulting research literature or conducting a systematic research study.
• Will my community come together in protest of a police-involved shooting incident? This type of question may best be answered by waiting to see what the future brings. Research might offer a guess based on data from how other communities behaved in the past but cannot predict how groups in individual situations will behave. A better research question might be: What factors predict community protest in response to police-involved shooting incidents?
• Should I order salad or soup to go with my sandwich? This type of question is not of general interest, making it a poor choice as a research question. The question might be reframed as a general interest question: Is it healthier to provide salad or soup along with a sandwich? The answer to that researchable question might inform a personal decision.
• Why divorce is bad for children. There are two problems with this example. First, it is a statement, not a question, despite starting with the word “why.” Second, this question starts out with a biased assumption—that divorce is bad for children. Research questions should support unbiased investigation, leading to evidence and answers representative of what exists rather than what someone sets out wanting to prove is the case. A better research question might be: How does divorce affect children?

Tuning back to our first example of what is not a research question, consider several possible school social work research questions related to that general topic:

• To what extent do elementary school personnel feel prepared to engage in trauma informed education with their students?
• What are the barriers and facilitators of integrating trauma informed education in middle school?
• Does integrating trauma informed education result in lower rates of suicidal ideation among high school students?

Is there a relationship between parent satisfaction and the implementation of trauma informed education in their children’s schools?

Does implementing trauma informed education in middle schools affect the rate of student discipline referrals?

What is the difference between these research questions and the earlier “not research” questions? First, research questions are specific. This is an important distinction between identifying a topic of interest (e.g., trauma informed education) and asking a researchable question. For example, the question “How does divorce affect children?” is not a good research question because it remains too broad. Instead, investigators might focus their research questions on one or two specific effects of interest, such as emotional or mental health, academic performance, sibling relationships, aggression, gender role, or dating relationship outcomes.

Related to a question being “researchable” is its feasibility for study. Being able to research a question requires that appropriate data can be collected with integrity. For example, it may not be feasible to study what would happen if every child was raised by two parents, because (a) it is impossible to study every child and (2) this reality cannot ethically be manipulated to systematically explore it. No one can ethically conduct a study whereby children are randomly assigned by study investigators to the compared conditions of being raised by two parents versus being raised by one or no parents. Instead, we settle for observing what has occurred naturally in different families.

Second, “good” research questions are relevant to knowledge building. For this reason, the question about what to eat was not a good research question—it is not relevant to others’ knowledge development. Relevance is in the “eye of the beholder,” however. A social work researcher may not see the relevance of using a 4-item stimulus array versus a 6-item stimulus array in testing children’s memory, but this may be an important research question for a cognitive psychology researcher. It may, eventually, have implications for assessment measures used in social work practice.

Third, is the issue of bias built into research questions. Remembering that investigators are a product of their own developmental and social contexts, what they choose to study and how they choose to study it are socially constructed. An important aspect at the heart of social work research relates to a question’s cultural appropriateness and acceptability. To demonstrate this point, consider an era (during the 1950s to early 1970s) when research questions were asked about the negative effects on child development of single-parent, black family households compared to two-parent, white family households in America. This “majority comparison” frame of reference is not culturally appropriate or culturally competent. Today, in social work, we adopt a strengths perspective, and avoid making comparisons of groups against a majority model. For example, we might ask questions like: What are the facilitators and barriers of children’s positive development as identified by single parents of diverse racial/ethnic backgrounds? What strengths do African American parents bring to the experience of single-parenting and how does it shape their children’s development? What are the similar and different experiences of single-parenting experienced by families of different racial/ethnic composition?

Research Questions versus Research Hypotheses . You have now seen examples of “good” research questions. Take, for example, the last one we listed about trauma informed education:

Based on a review of literature, practice experience, previous research efforts, and the school’s interests, an investigator may be prepared to be even more specific about the research question (see Figure 1-3). Assume that these sources led the investigator to believe that implementing the trauma informed education approach will have the effect of reducing the rate of disciplinary referrals. The investigator may then propose to test the following hypothesis:

Implementing trauma informed education in middle schools will result in a reduction in the number of student discipline referrals.

The research hypothesis  is a clear statement that can be tested with quantitative data and will either be rejected or not, depending on the evidence. Research hypotheses are predictions about study results—what the investigator expects the results will show. The prediction, or hypothesis, is based on theory and/or other evidence. A study hypothesis is, by definition, quantifiable—the answer lies in numerical data, which is why we do not generally see hypotheses in qualitative, descriptive research reports.

Hypotheses are also specific to one question at a time. Thus, an investigator would need to state and test a second hypothesis to answer the question:

The stated hypothesis might be:

Parent satisfaction is higher in middle schools where trauma informed education is implemented.

Figure 1-3. Increasing specificity from research topic to question to hypothesis

Social Work Questions

It is difficult to find a simple way to characterize social work research. The National Institutes of Health (NIH) described social work research in the following way:

Historically, social work research has focused on studies of the individual, family, group, community, policy and/or organizational level, focusing across the lifespan on prevention, intervention, treatment, aftercare and rehabilitation of acute and chronic conditions, including the effects of policy on social work practice (OBSSR, 2003, p. 5) .

For all the breadth expressed in this statement, it reflects only how social work research relates to the health arena—it does not indicate many other domains and service delivery systems of social work influence:

• physical, mental, and behavioral health
• substance misuse/addiction and other addictive behaviors
• income/poverty
• criminal justice
• child and family welfare
• housing and food security/insecurity
• environmental social work
• intimate partner, family, and community violence
• and others.

In addition to breadth of topic, social work research is characterized by its biopsychosocial nature. This means that social work researchers not only pursue questions relating to biological, psychological, and social context factors, but also questions relating to their intersections and interactions. Related to this observation is that social work not only addresses questions related to the multiple social system levels, social work also addresses the ways multiple levels intersect and interact (i.e., those levels represented in the NIH statement about individuals, families, groups, communities, organizations, and policy).

It is worth noting that research need not be conducted by social workers to be relevant to social work–many disciplines and professions contribute to the knowledge base which informs social work practice (medicine, nursing, education, occupational therapy, psychology, sociology, criminal justice, political science, economics, and more). Authors of one social work research textbook summarize the relevance issue in the following statement:

“To social workers, a relevant research question is one whose answers will have an impact on policies, theories, or practices related to the social work profession” (Grinnell & Unrau, 2014, p. 46).

Social Work Research Questions and Specific Aims

The kinds of questions that help inform social work practice and policy are relevant to understanding social work problems, diverse populations, social phenomena, or interventions. Most social work research questions can be divided into two general categories: background questions  and foreground questions . The major distinction between these two categories relates to the specific aims that emerge in relation to the research questions.

Background Questions.  This type of question is answerable with a fact or set of facts. Background questions are generally simple in structure, and they direct a straightforward search for evidence. This type of question can usually be formulated using the classic 5 question words: who, what, when, where, or why. Here are a few examples of social work background questions related to the topic of fetal alcohol exposure:

• Who is at greatest risk of fetal alcohol exposure?
• What are the developmental consequences of fetal alcohol exposure?
• When in gestation is the risk of fetal alcohol exposure greatest?
• Where do women get information about the hazards of drinking during pregnancy?
• Why is fetal alcohol exposure (FAE) presented as a spectrum disorder, different from fetal alcohol syndrome (FAS)?

These kinds of questions direct a social worker to review literature about human development, human behavior, the distribution of the problem across populations, and factors that determine the nature of a specific social work problem like fetal exposure to alcohol. Where the necessary knowledge is lacking, investigators aim to explore or describe the phenomenon of interest. Many background questions can be answered by epidemiology or etiology evidence.

Foreground Questions.  This type of question is more complex than the typical background question. Foreground questions typically are concerned with making specific choices by comparing or evaluating options. These types of questions required more specialized evidence and may lead to searching different types of resources than would be helpful for answering background questions. Foreground questions are dealt with in greater detail in our second course, SWK 3402 which is about understanding social work interventions. A quick foreground question example related to the fetal exposure to alcohol topic might be:

Which is the best tool for screening pregnant women for alcohol use with the aim of reducing fetal exposure, the T-ACE, TWEAK, or AUDIT?

This type of question leads the social worker to search for evidence that compares different approaches. These kinds of evidence are usually found in comparative reviews, or require the practitioner to conduct a review of literature, locating individual efficacy and effectiveness studies. Where knowledge is found to be lacking, investigators aim to experiment with different approaches or interventions.

Three Question Types and Their Associated Research Aims

Important distinctions exist related to different types of background questions. Consider three general categories of questions that social workers might ask about populations, problems, and social phenomena: exploratory, descriptive, and explanatory. The different types of questions matter because the nature of the research questions determines the specific aims and most appropriate research approaches investigators apply in answering them.

Exploratory Research Questions. Social workers may find themselves facing a new, emerging problem where there is little previously developed knowledge available—so little, in fact, that it is premature to begin asking any more complex questions about causes or developing testable theories. Exploratory research questions open the door to beginning understanding and are basic; answers would help build the foundation of knowledge for asking more complex descriptive and explanatory questions. For example, in the early days of recognition that HIV/AIDS was emerging as a significant public health problem, it was premature to jump to questions about how to treat or prevent the problem. Not enough was known about the nature and scope of the problem, for whom it was a problem, how the problem was transmitted, factors associated with risk for exposure, what factors influenced the transition from HIV exposure to AIDS as a disease state, and what issues or problems might co-occur along with either HIV exposure or AIDS. In terms of a knowledge evolution process, a certain degree of exploration had to occur before intervention strategies for prevention and treatment could be developed, tested, and implemented.

In 1981, medical providers, public health officials, and the Centers for Disease Control and Prevention (CDC) began to circulate and publish observations about a disproportionate, unexpectedly high incidence rate of an unusual pneumonia and Kaposi’s sarcoma appearing in New York City and San Francisco/California among homosexual men (Curran, & Jaffe, 2011). As a result, a task force was formed and charged with conducting an epidemiologic investigation of this outbreak; “Within 6 months, it was clear that a new, highly concentrated epidemic of life threatening illness was occurring in the United States” (Curran & Jaffe, 2011, p. 65). The newly recognized disease was named for its symptoms: acquired immune deficiency syndrome, or AIDS. Exploratory research into the social networks of 90 living patients in 10 different cities indicated that 40 had a sexual contact link with another member of the 90-patient group (Auerbach, Darrow, Jaffe, & Curran, 1984). Additionally, cases were identified among persons who had received blood products related to their having hemophilia, persons engaged in needle sharing during substance use, women who had sexual contact with a patient, and infants born to exposed women. Combined, these pieces of information led to an understanding that the causal infectious factor (eventually named the human immunodeficiency virus, HIV) was transmitted by sexual contact, blood, and placental connection. This, in turn, led to knowledge building activities to develop both preventive and treatment strategies which could be implemented and studied. Social justice concerns relate to the slow rate at which sufficient resources were committed for evolving to the point of effective solutions for saving lives among those at risk or already affected by a heavily stigmatized problem.

The exploratory research approaches utilized in the early HIV/AIDS studies were both qualitative and quantitative in nature. Qualitative studies included in-depth interviews with identified patients—anthropological and public health interviews about many aspects of their living, work, and recreational environments, as well as many types of behavior. Quantitative studies included comparisons between homosexually active men with and without the diseases of concern. In addition, social network study methods combined qualitative and quantitative approaches. These examples of early exploratory research supported next steps in knowledge building to get us to where we are today. “Today, someone diagnosed with HIV and treated before the disease is far advanced can live nearly as long as someone who does not have HIV” (hiv.gov). While HIV infection cannot (yet) be “cured,” it can be controlled and managed as a chronic condition.

Descriptive Research Questions.  Social workers often ask for descriptions about specific populations, problems, processes, or phenomena. Descriptive research questions  might be expressed in terms of searching to create a profile of a group or population, create categories or types (typology) to describe elements of a population, document facts that confirm or contradict existing beliefs about a topic or issue, describe a process, or identify steps/stages in a sequential process (Grinnell & Unrau, 2014). Investigators may elect to approach the descriptive question using qualitative methods that result in a rich, deep description of certain individuals’ experiences or perceptions (Yegidis, Weinbach, & Meyers, 2018). Or, the descriptive question might lead investigators to apply quantitative methods, assigning numeric values, measuring variables that describe a population, process, or situation of interest. In descriptive research, investigators do not manipulate or experiment with the variables; investigators seek to describe what naturally occurs (Yegidis, Weinbach, & Meyers, 2018). As a result of studies answering descriptive questions, tentative theories and hypotheses may be generated.

Here are several examples of descriptive questions.

• How do incarcerated women feel about the option of medication-assisted treatment for substance use disorders?
• What barriers to engaging in substance misuse treatment do previously incarcerated persons experience during community reentry?
• How often do emerging adults engage in binge drinking in different drinking contexts (e.g., bars, parties, sporting events, at home)?
• What percent of incarcerated adults experience a substance use disorder?
• What is the magnitude of racial/ethnic disparities in access to treatment for substance use disorders?
• Who provides supervision or coordination of services for aging adults with intellectual or other developmental disabilities?
• What is the nature of the debt load among students in doctoral social work programs?

An example of descriptive research, derived from a descriptive question, is represented in an article where investigators addressed the question: How is the topic of media violence and aggression reported in print media (Martins et al., 2013)? This question led the investigators to conduct a qualitative content analysis, resulting in a description showing a shift in tone where earlier articles (prior to 2000) emphasized the link as a point of concern and later articles (since 2000) assumed a more neutral stance.

Correlational Research Questions.  One important type of descriptive question asks about relationships that might exist between variables—looking to see if variable x  and variable y  are associated or correlated with each other. This is an example of a correlational research question; it does not indicate whether “x” causes “y” or “y” causes “x”, only whether these two are related. Consider again the topic of exposure to violence in the media and its relationship to aggression. A descriptive question asked about the existence of a relationship between exposure to media violence ( variable x ) and children’s expression of aggression ( variable y ). Investigators reported one study of school-aged children, examining the relationship between exposure to three types of media violence (television, video games, and movies/videos) and three types of aggression (verbal, relational, and physical; Gentile, Coyne, & Walsh, 2011). The study investigators reported that media violence exposure was, indeed, correlated with all three types of aggressive behavior (and less prosocial behavior, too).

For a positive correlation (the blue line), as the value of the “x” variable increases, so does the value of the “y” variable (see Figure 1-4 for a general demonstration). An example might be as age or grade in school increases (“x”), so does the number of preadolescent, adolescent, and emerging adults who have used alcohol (“y”). For a negative correlation (the orange line), as the value of the “x” variable increases, the value of the “y” variable decreases. An example might be as the number of weeks individuals are in treatment for depression symptoms (“x”), the reported depression symptoms decreases (“y”). The neutral of non-correlation line (grey) means that the two variables, “x” and “y” do not have an association with each other. For example, number of years of teachers’ education (“x”) might be unrelated to the number of students dropping out of high school (“y”).

Figure 1-4. Depicting positive, negative, and neutral correlation lines

Descriptive correlational studies are sometimes called comparison studies because the descriptive question is answered by comparing groups that differ on one of the variables (low versus high media violence exposure) to see how they might differ on the other variable (aggressive behavior).

Explanatory Research Questions. To inform the design of evidence-informed interventions, social workers need answers to questions about the nature of the relationships between potentially influential factors or variables. An explanatory research question  might be mapped as: Does variable x  cause, lead to or prevent changes in variable y  (Grinnell & Unrau, 2014)? These types of questions often test theory related to etiology.

Comparative research might provide information about a relationship between variables. For example, the difference in outcomes between persons experiencing a substance use disorder and have been incarcerated compared to others with the same problem but have not been incarcerated may be related to their employability and ability to generate a living-wage income for themselves and their families. However, to develop evidence-informed interventions, social workers need to know that variables are not only related, but that one variable actually plays a causal role in relation to the other. Imagine, for example, that evidence demonstrated a significant relationship between adolescent self-esteem and school performance. Social workers might spend a great deal of effort developing interventions to boost self-esteem in hopes of having a positive impact on school performance. However, what if self-esteem comes from strong school performance? The self-esteem intervention efforts will not likely have the desired effect on school performance. Just because research demonstrates a significant relationship between two variables does not mean that the research has demonstrated a  causal relationship between those variables. Investigators need to be cautious about the extent to which their study designs can support drawing conclusions about causality; anyone reviewing research reports also needs to be alert to where causal conclusions are properly and improperly drawn.

The questions that drive intervention and evaluation research studies are explanatory in nature: does the intervention ( x ) have a significant impact on outcomes of interest ( y )? Another type of explanatory question related to intervention research concerns the mechanisms of change. In other words, not only might social workers be interested to find out  what  outcomes or changes can be attributed to an intervention, they may also be interested to learn how  the intervention causes those changes or outcomes.

Chapter Summary

In this chapter, you learned about different aspects of the knowledge building process and where different types of research questions might fit into the big picture. No single research study covers the entire spectrum; each study contributes a piece of the puzzle as a whole. Research questions come in many different forms and several different types. What is important to recall as we move through the remainder of the course is that the decisions investigators make about research approaches, designs, and procedures all start with the nature of the question being asked. And, the questions being asked are influenced by multiple factors, including what is previously known and remains unknown, the culture and context of the questioners, and what theories they have about what is to be studied. That leads us to the next chapter.

Social Work 3401 Coursebook Copyright © by Dr. Audrey Begun is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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• Writing Strong Research Questions | Criteria & Examples

Writing Strong Research Questions | Criteria & Examples

Published on October 26, 2022 by Shona McCombes . Revised on November 21, 2023.

A research question pinpoints exactly what you want to find out in your work. A good research question is essential to guide your research paper , dissertation , or thesis .

All research questions should be:

• Focused on a single problem or issue
• Researchable using primary and/or secondary sources
• Feasible to answer within the timeframe and practical constraints
• Specific enough to answer thoroughly
• Complex enough to develop the answer over the space of a paper or thesis
• Relevant to your field of study and/or society more broadly

Table of contents

How to write a research question, what makes a strong research question, using sub-questions to strengthen your main research question, research questions quiz, other interesting articles, frequently asked questions about research questions.

You can follow these steps to develop a strong research question:

• Choose your topic
• Do some preliminary reading about the current state of the field
• Narrow your focus to a specific niche
• Identify the research problem that you will address

The way you frame your question depends on what your research aims to achieve. The table below shows some examples of how you might formulate questions for different purposes.

Using your research problem to develop your research question

Note that while most research questions can be answered with various types of research , the way you frame your question should help determine your choices.

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Research questions anchor your whole project, so it’s important to spend some time refining them. The criteria below can help you evaluate the strength of your research question.

Focused and researchable

Feasible and specific

Complex and arguable

Relevant and original

Chances are that your main research question likely can’t be answered all at once. That’s why sub-questions are important: they allow you to answer your main question in a step-by-step manner.

Good sub-questions should be:

• Less complex than the main question
• Focused only on 1 type of research
• Presented in a logical order

Here are a few examples of descriptive and framing questions:

• Descriptive: According to current government arguments, how should a European bank tax be implemented?
• Descriptive: Which countries have a bank tax/levy on financial transactions?
• Framing: How should a bank tax/levy on financial transactions look at a European level?

Keep in mind that sub-questions are by no means mandatory. They should only be asked if you need the findings to answer your main question. If your main question is simple enough to stand on its own, it’s okay to skip the sub-question part. As a rule of thumb, the more complex your subject, the more sub-questions you’ll need.

Try to limit yourself to 4 or 5 sub-questions, maximum. If you feel you need more than this, it may be indication that your main research question is not sufficiently specific. In this case, it’s is better to revisit your problem statement and try to tighten your main question up.

If you want to know more about the research process , methodology , research bias , or statistics , make sure to check out some of our other articles with explanations and examples.

Methodology

• Sampling methods
• Simple random sampling
• Stratified sampling
• Cluster sampling
• Likert scales
• Reproducibility

 Statistics

• Null hypothesis
• Statistical power
• Probability distribution
• Effect size
• Poisson distribution

Research bias

• Optimism bias
• Cognitive bias
• Implicit bias
• Hawthorne effect
• Anchoring bias
• Explicit bias

The way you present your research problem in your introduction varies depending on the nature of your research paper . A research paper that presents a sustained argument will usually encapsulate this argument in a thesis statement .

A research paper designed to present the results of empirical research tends to present a research question that it seeks to answer. It may also include a hypothesis —a prediction that will be confirmed or disproved by your research.

As you cannot possibly read every source related to your topic, it’s important to evaluate sources to assess their relevance. Use preliminary evaluation to determine whether a source is worth examining in more depth.

This involves:

• Reading abstracts , prefaces, introductions , and conclusions
• Looking at the table of contents to determine the scope of the work
• Consulting the index for key terms or the names of important scholars

A research hypothesis is your proposed answer to your research question. The research hypothesis usually includes an explanation (“ x affects y because …”).

A statistical hypothesis, on the other hand, is a mathematical statement about a population parameter. Statistical hypotheses always come in pairs: the null and alternative hypotheses . In a well-designed study , the statistical hypotheses correspond logically to the research hypothesis.

Formulating a main research question can be a difficult task. Overall, your question should contribute to solving the problem that you have defined in your problem statement .

However, it should also fulfill criteria in three main areas:

• Researchability
• Feasibility and specificity
• Relevance and originality

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Social Work Research

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Getting Started with Social Work Research

• Video Tutorials
• Understanding the Libraries "Basic" Search
• The Research Process
• What is a literature review?
• What is a Research Question?
• Turn a topic into a Search Strategy
• Keyword Brainstorming
• Search Tips

The search box on the library homepage provides a basic search across library holdings.  See the guide below for an explanation of how to effectively use the basic search:

• Library Search Help

As you work toward completing your research projects, remember that the research process is NOT linear. It's usually more of a circular process and there may be many times where you jump back and forth between the stages of your research. While not everyone's research process will look exactly the same, the following model can give you a better idea of how the research process often works.

Think of scholarly papers like a conversation. A paper takes a look at what people are saying on a particular topic and then adds something new to the conversation based on their own research. A literature review is how scholars get caught up on the conversation so they will know what to say or ask next.

A literature review can be just a simple summary of the sources, but it usually has an organizational pattern and combines both summary and synthesis.

A summary is a recap of the important information of the source, but a synthesis is a re-organization, or a reshuffling, of that information. It might give a new interpretation of old material or combine new with old interpretations. Or it might trace the intellectual progression of the field, including major debates.

• APA Literature Review Template Note: not yet updated for APA 7th edition

A research question is what forms and guides your literature review. It is the question that you want the literature to answer for you. A research question should be specific, focused, and concise.

To develop a research question, start with a general topic of interest to you. You'll want to do some preliminary and background research on this topic to think through what specific questions you might have.

Sample Topic: impact of social media on adolescent physical activity

Sample Research Question: Can social media serve as an effective tool for increasing physical activity among adolescents?

Need more guidance on developing your topic into a research question? Check out  this video  from the library at Northern Kentucky University.

In order to search most effectively for articles that pertain to your research topic, take a little time at the beginning of your project to plan out your search strategy.

1. Break up your topic/research question into it's primary concepts

• i.e. What impact does tobacco use have on the lung health of teenagers?
• Population - teenagers
• Problem - tobacco use
• Outcome - lung health

2. Brainstorm synonyms for your terms (see more in next tab)

• i.e. teenagers, teens, adolescents, youth, young adults, juvenile

3. Add quotation marks around exact phrases and be sure to include both singular and plural

• i.e. "young adults", "young adult"

4. Search one concept at a time using ORs to include all of your synonyms and then combine your searches with AND

• Search 1: teenagers OR teens OR adolescents OR youth OR "young adults" OR "young adult" OR juveniles
• Search 2:  tobacco OR smoking OR vaping OR cigarettes OR nicotine
• Search 3:  lung health OR "respiratory health" OR "respiratory distress" OR dyspnea OR asthma OR "pulmonary disorder" OR "pulmonary disorders" OR "pulmonary disease" OR "pulmonary diseases"

1. Save time, prepare to research!

• Break your research question into key concepts (you'll connect these in your paper to make an original argument)
• For each of these concepts, brainstorm multiple  keywords

• Try this   keyword tool  to brainstorm online and send the results to yourself.

2. Combine keywords using  AND  and  OR :

• Too many  results? Try using quotation marks around an exact phrase. Ex: "students with disabilities"
• Still too many  results? Narrow using  AND . Ex:  "students with disabilities" AND "assistive technology"
• Too few  results? Broaden using  OR . Ex: "students with disabilities" AND (campus OR college OR university OR higher education)
• Put  parentheses  around synonyms.
• The  asterisk  finds multiple endings from a root word. Ex: wom* will bring back women, woman's, wombat, etc.

3. Brush up on the  search tools  available:

• Here are  search tips for Google .
• Databases often include their own search tips. Tip: Look for a help link or a gear symbol.

Interfaces and search options vary across databases, but best practices for searching are relatively consistent across interfaces. No matter which database you choose, remember these important tips...

1) Don't search wth your topic as a single phrase!  Determine the key concepts of your topic. Then place each concept in its own search bar.  For example...

2) Use ORs to string together synonyms or related terms for core concepts...

3) Use truncation, when appropriate. Adding an * to the end of a word will catch all forms of that word. For example, teach* will return teach, teachers, teaching , etc.

4) Use proximity searches to force a relationship between two terms. This isn't always needed, but is sometimes super helpful. Completion is a common word that may come up in many context. The search below means that the word complete or completion must appear within two words of college in the article title and abstracts.

5) Look for the "peer reviewed" limit in each database. You can set this limit on the main search screen (before you search) or narrow your results after you've started your search.

6) Set date limits  as appropriate for your topic..

Writing a Research Paper

• Steps for Writing a Research Paper Step by Step instructions on how to write a research paper by the University Writing Center

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Social Work Research Topics & Tips on Finding and Distinguishing Good Ones

Updated 01 Jul 2024

Social work research is the systematic investigation of problems pertaining to the social work field. Alternatively, it can be defined as the application of research methods for addressing/solving problems confronted by social workers in their practice.

Major research areas include studying concepts, theories, principles, underlying methods, employees’ skills and their interaction with individuals and groups as well as internal processes, functioning principles within social entities. For a more specific selection of social work research topics, go to the appropriate section within this article.

Social work is ultimately focused on practical application, hence, the ultimate goal of social work research is understanding the efficacy of various intervention methods aimed at alleviating the conditions of people suffering from social deprivation – this highlights the importance presented by both the field and its associated research. For such difficult topics, you may ask yourself "can I pay someone to write my research paper " - and our professional team is here to help you.

Signs of Good Research Topics

Of all social work research questions, how could one distinguish the ones holding the greatest value or potential? Considering these signs could increase the chances of picking higher quality or more productive social work topics:

• Chosen topics are backed up by one or more published studies by research teams from the US or from abroad with solid article-related citation metrics, typically published in prestigious peer-reviewed academic journals (journals with high impact factor).
• Social work research topics in question are related to practice – theoretical research is very important, but nothing beats practical knowledge and efficient practical intervention methods and strategies. However, this aspect might depend on other circumstances as well (for students, for instance, theoretical topics are fairly acceptable). To ensure a successful research proposal in the field of social work, consider utilizing research proposal writing services .
• Social work research topics are breaking certain stereotypes. People are inclined towards topics that break preconceived notions – such topics naturally receive greater attention. If they bring solid evidence and reasonable arguments while providing/promising real benefits, such topics can simply revolutionize the field.
• Chosen social work research topics match current trends. Don’t understand us wrong – not everything that is trendy deserves attention (many things are overhyped). However, trends do have a sound reason for emerging (there is normally value behind the forces driving them). Moreover, delving into a field/topic that has only been recently established often gives significant advantages (career-wise). So watch out for trends in your research field closely, but always scrutinize them for what they are worth.

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Where Can You Find Perfect Topics?

When exploring education research topics or searching for social worker research topics, it might prove useful to follow a few proven strategies (which are equally valid for many other occasions):

• Skim through your study literature (e.g. handbooks, course notes) – this is material you already studied, but going through it might help you to systematically visualize all studied topics or subtopics (these can suggest new ideas).
• Brainstorming. Access your knowledge base – chances are you have a few interesting topics stored in mind that you’d like to explore in greater detail.
• Browse through published article titles in social work journals or, even better, study newsletters/highlights on journal websites. Alternatively, one could search on platforms aggregating field-related news from multiple journals.– while some articles/topics might be overly complicated or specific, these still offer an immense choice.
• Browse online for ready research topics for a custom research paper from our  research paper writing service  – skimming through such lists would bombard you with topics of appropriate complexity and scope /broadness or would inspire new related ideas (e.g. by combining elements from different topics).

Yet another way to pick a good topic is to get research paper writing help from our professional writers – they would manage all aspects, including that of choosing an original and solid topic (obviously, you might be willing to confirm it, before proceeding with your writing project).

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100 Social Work Research Topics

Below is a comprehensive social work research topics list to help get you started with your project.

50 Controversial Research Topics

• Group therapy vs individual therapy for increasing autistic children adaptability
• Impact on parents having children with autism spectrum disorder.
• Role play vs group discussion efficiency in increasing knowledge regarding drug abuse among high-school students.
• Addressing the stigma associated with depression.
• Measures to counteract condemning stereotypes with regard to depression (explaining and highlighting the biological mechanisms underlying it)
• Identifying individuals with suicide predisposition serving in military units.
• Life events role in PTSD onset in veterans.
• Strategies to prevent PTSD onset in US army veterans.
• Social inclusion measures for war veterans.
• Most efficient strategies for suicide prevention in academic setting.
• Categories are most vulnerable to drug abuse.
• Most efficient educational measures to prevent future drug abuse in children
• Myths about substance abuse among adolescents.
• Family support importance for alcohol addicts rehabilitation.
• Workaholics – new type of addicts. Impact on personal and family lives.
• Mental retardation in Alzheimer’s disease – how to cope with it as a family member?
• Promoting integration for children with Down syndrome.
• General considerations for working with children with developmental disabilities.
• Educating society with regard to dyslexic children (all target groups could be considered: parents, classmates, teachers, etc.)
• Dyslexia cases combined with ADHD – how to approach it?
• Dismounting common myths about dyslexia.
• Counteracting bullying aimed at dyslexic children.
• Early intervention benefits to address language difficulties in case of dyslexic children.
• What role should educators, parents, schools, mental health centers, private practice have in addressing dyslexia?
• Key prerequisites for building resilience to adverse life events in children
• Strategies for building resilience in welfare workers.
• Who is responsible for developing resilience in social workers?
• Self-help guidelines for social workers to become resilient.
• Most common problems encountered by LGBT youth in US schools.
• Arming LGBT individuals with coping strategies to face discrimination.
• The situation with juvenile delinquents across various US states.
• Rationale behind separating juvenile delinquents from adult delinquents.
• Factors contributing to high youth incarceration rate in certain US states (Wyoming, Nebraska, South Dakota).
• Most efficient reeducation strategies for juvenile delinquents.
• Society inclusion measures for people that served in prison.
• Coping with the stigma of having served in prison.
• Attitudes of welfare workers towards incarcerated individuals.
• Attitudes of correctional officers towards mental health of incarcerated individuals.
• Gender differences relevance when working with incarcerated people.
• Factors increasing the risk of recidivism in released prisoners.
• Incarceration impacts on parent-child relationships.
• Incarceration effects on mental health.
• Social inclusion role and family support in preventing recidivism by former prisoners.
• Circumstances associated with the highest risk of becoming a human trafficking victim.
• Ethical rules important when working with human trafficking victims.
• Trauma characteristic depiction for human trafficking victims.
• What is considered neglecting a child in child welfare?
• Prerequisites of a safe childhood and a functional family.
• Dealing with child abuse in orphanages.
• Types of child maltreatment/abuse.

50 Hot Research Topics for Social Work Students

• Difference in approaching children vs adolescents suffering from domestic violence.
• Success stories in preventing child abuse in certain regions/states.
• Strategies to encourage women to report domestic violence cases.
• Damage to families with ongoing domestic violence.
• Healing steps for victims of domestic violence.
• Effects of child neglect on later academic performance and career.
• Removing a child from a setting – when is it justified?
• Guidelines on providing testimony in court as a social worker
• Peculiarities of social work in health care assistance.
• Grief counseling for families that lost a loved one.
• Understanding the symptoms of grief.
• Risk factors for dangerous grief.
• Conduct/communication rules with persons in grief.
• Types of elder abuse. Which are the most common ones?
• Predictors of elder abuse (related to relationships within families, financial, status).
• The integrative concept of human services.
• The utility of mentoring programs in social care.
• Work with elders experiencing cognitive impairment.
• Peculiarities of working with immigrants in social care.
• Considerations for working with HIV positive people.
• Social research topics about homeless people.
• Primary factors contributing to homelessness.
• Challenges faced by social care assistants in working with sexually exploited clients belonging to the opposite gender.
• Meeting unique needs of sexually exploited children.
• Compassion fatigue experienced by welfare worker.
• Challenges experienced by single parents and support strategies
• Problem of getting medical help when belonging to vulnerable categories
• Is there place for spirituality in welfare worker?
• Religious beliefs obstructing welfare worker.
• Support strategies for low-income families having children with impaired development.
• Retrospective views and youth opinions on foster care facilities they have gone through.
• Key wishes/demands expressed by foster care facility residents
• Strategies employed by welfare worker to avoid burnout.
• Importance of building emotional intelligence as welfare worker.
• Discussing sexual health with mentally ill or retarded clients.
• Spirituality and faith as an essential element in many addiction rehabilitation programs.
• Attitude towards older people among welfare workers.
• Factors responsible for reluctance to benefit from mental health services among certain population groups.
• Differences in working with adolescent and adult drug abusers.
• Factors affecting foster youth that impact their higher education retention rate.
• Language barrier as an obstructing factor for minorities in benefiting from mental health services.
• Cultural competence as social work research topic
• Pre and post birth assistance to surrogate mothers. Evaluating impact on mental health.
• Challenges and issues arising in families with adoptive children.
• Play therapy interventions effectiveness in school-based counseling.
• Mental health in hemodialysis patients and corresponding support strategies.
• Importance presented by recreational activities for patients with Alzheimer’s.
• Intimacy impact on the outcome of group therapy practices for alcohol addiction.
• Mental health care outcomes in pedophilia victims.
• Alternative practices in social work.

Read also: Get excellent grades with the help of online research paper maker. 

Found Topic But No Time For Writing?

We truly hope that by providing this list of social work topics for research papers we’ve addressed an important challenge many students encounter. Nevertheless, choosing suitable social work research topics is not the only challenge when having to write a paper.

Fortunately, Edubirdie website has a number of other tools like a thesis statement generator, a citation tool, a plagiarism checker, etc. to help with related aspects of writing a research paper. Besides, you can directly hire our professional paper writers to assist you with writing the paper according to instructions, creating a detailed outline, an annotated bibliography, but also with editing, proofreading, creating slides for presentation, etc.

Clients can choose their preferred writers freely by evaluating their ranking and performance on the platform. Later, they can communicate with these writers as their projects progress, being able to request intermediary results and providing feedback, additional guiding. If results are not satisfying and don’t match provided instructions, you can request unlimited revisions – all for free. In the unlikely situation in which revision attempts fail, you are guaranteed to get your money back. Given these low risks and guaranteed outcome, you should definitely give it a try!

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Think Like a Researcher: Instruction Resources: #6 Developing Successful Research Questions

• Guide Organization
• Overall Summary
• #1 Think Like a Researcher!
• #2 How to Read a Scholarly Article
• #3 Reading for Keywords (CREDO)
• #4 Using Google for Academic Research
• #4 Using Google for Academic Research (Alternate)
• #5 Integrating Sources
• Research Question Discussion
• #7 Avoiding Researcher Bias
• #8 Understanding the Information Cycle
• #9 Exploring Databases
• #10 Library Session
• #11 Post Library Session Activities
• Summary - Readings
• Summary - Research Journal Prompts
• Summary - Key Assignments
• Jigsaw Readings
• Permission Form

Course Learning Outcome:   Develop ability to synthesize and express complex ideas; demonstrate information literacy and be able to work with evidence

Goal:  Develop students’ ability to recognize and create successful research questions

Specifically, students will be able to

• identify the components of a successful research question.
• create a viable research question.

What Makes a Good Research Topic Handout

These handouts are intended to be used as a discussion generator that will help students develop a solid research topic or question. Many students start with topics that are poorly articulated, too broad, unarguable, or are socially insignificant. Each of these problems may result in a topic that is virtually un-researchable. Starting with a researchable topic is critical to writing an effective paper.

Research shows that students are much more invested in writing when they are able to choose their own topics. However, there is also research to support the notion that students are completely overwhelmed and frustrated when they are given complete freedom to write about whatever they choose. Providing some structure or topic themes that allow students to make bounded choices may be a way mitigate these competing realities.

These handouts can be modified or edited for your purposes.  One can be used as a handout for students while the other can serve as a sample answer key.  The document is best used as part of a process.  For instance, perhaps starting with discussing the issues and potential research questions, moving on to problems and social significance but returning to proposals/solutions at a later date.

• Research Questions - Handout Key (2 pgs) This document is a condensed version of "What Makes a Good Research Topic". It serves as a key.
• Research Questions - Handout for Students (2 pgs) This document could be used with a class to discuss sample research questions (are they suitable?) and to have them start thinking about problems, social significance, and solutions for additional sample research questions.
• Research Question Discussion This tab includes materials for introduction students to research question criteria for a problem/solution essay.

Additional Resources

These documents have similarities to those above.  They represent original documents and conversations about research questions from previous TRAIL trainings.

• What Makes a Good Research Topic? - Original Handout (4 pgs)
• What Makes a Good Research Topic? Revised Jan. 2016 (4 pgs)
• What Makes a Good Research Topic? Revised Jan 2016 with comments

Topic Selection (NCSU Libraries)

Howard, Rebecca Moore, Tricia Serviss, and Tanya K. Rodrigues. " Writing from sources, writing from sentences ." Writing & Pedagogy 2.2 (2010): 177-192.

Research Journal

Assign after students have participated in the Developing Successful Research Topics/Questions Lesson OR have drafted a Research Proposal.

Think about your potential research question.

• What is the problem that underlies your question?
• Is the problem of social significance? Explain.
• Is your proposed solution to the problem feasible? Explain.
• Do you think there is evidence to support your solution?

Keys for Writers - Additional Resource

Keys for Writers (Raimes and Miller-Cochran) includes a section to guide students in the formation of an arguable claim (thesis).  The authors advise students to avoid the following since they are not debatable. 

• "a neutral statement, which gives no hint of the writer's position"
• "an announcement of the paper's broad subject"
• "a fact, which is not arguable"
• "a truism (statement that is obviously true)"
• "a personal or religious conviction that cannot be logically debated"
• "an opinion based only on your feelings"
• "a sweeping generalization" (Section 4C, pg. 52)

The book also provides examples and key points (pg. 53) for a good working thesis.

• << Previous: #5 Integrating Sources
• Next: Research Question Discussion >>
• Last Updated: Apr 26, 2024 10:23 AM
• URL: https://libguides.ucmerced.edu/think_like_a_researcher

Want to create or adapt books like this? Learn more about how Pressbooks supports open publishing practices.

Book Title: Guidebook for Social Work Literature Reviews and Research Questions

Authors: Rebecca L. Mauldin and Matthew DeCarlo

Download this book

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• Pressbooks XML
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Book Description: This short guidebook provides information about selecting a research topic and research questions, searching for literature, reading and understanding scholarly writing, and writing a literature review to synthesize what is known and what remains to be learned about a social problem. For students who appreciate the availability of resources on the internet, it also provides links to additional materials. It can be used with its companion textbook, Foundations of Social Work Research by Rebecca L. Mauldin and Matthew DeCarlo, or as a stand-alone guide.

Book Information

Book description.

As an introductory textbook for social work students studying research methods, this book guides students through the process of writing a literature review and determining research questions for a research project. Students will learn how to discover a researchable topic that is interesting to them, examine scholarly literature, and write a literature review. The guidebook is aligned with the Council on Social Work Education’s 2015 Educational Policy and Accreditation Standards. Students and faculty can download copies of this guidebook using the links provided in the front matter. As an open textbook, users are free to retain copies, redistribute copies (non-commercially), revise the contents, remix it with other works, and reuse for any purpose.

Guidebook for Social Work Literature Reviews and Research Questions Copyright © 2020 by Rebecca Mauldin and Matthew DeCarlo is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

Research methods: general

This open textbook is based on the open textbook Scientific Inquiry in Social Work by Matthew DeCarlo.

Social Work Research Methods That Drive the Practice

Social workers advocate for the well-being of individuals, families and communities. But how do social workers know what interventions are needed to help an individual? How do they assess whether a treatment plan is working? What do social workers use to write evidence-based policy?

Social work involves research-informed practice and practice-informed research. At every level, social workers need to know objective facts about the populations they serve, the efficacy of their interventions and the likelihood that their policies will improve lives. A variety of social work research methods make that possible.

Data-Driven Work

Data is a collection of facts used for reference and analysis. In a field as broad as social work, data comes in many forms.

Quantitative vs. Qualitative

As with any research, social work research involves both quantitative and qualitative studies.

Quantitative Research

Answers to questions like these can help social workers know about the populations they serve — or hope to serve in the future.

• How many students currently receive reduced-price school lunches in the local school district?
• How many hours per week does a specific individual consume digital media?
• How frequently did community members access a specific medical service last year?

Quantitative data — facts that can be measured and expressed numerically — are crucial for social work.

Quantitative research has advantages for social scientists. Such research can be more generalizable to large populations, as it uses specific sampling methods and lends itself to large datasets. It can provide important descriptive statistics about a specific population. Furthermore, by operationalizing variables, it can help social workers easily compare similar datasets with one another.

Qualitative Research

Qualitative data — facts that cannot be measured or expressed in terms of mere numbers or counts — offer rich insights into individuals, groups and societies. It can be collected via interviews and observations.

• What attitudes do students have toward the reduced-price school lunch program?
• What strategies do individuals use to moderate their weekly digital media consumption?
• What factors made community members more or less likely to access a specific medical service last year?

Qualitative research can thereby provide a textured view of social contexts and systems that may not have been possible with quantitative methods. Plus, it may even suggest new lines of inquiry for social work research.

Mixed Methods Research

Combining quantitative and qualitative methods into a single study is known as mixed methods research. This form of research has gained popularity in the study of social sciences, according to a 2019 report in the academic journal Theory and Society. Since quantitative and qualitative methods answer different questions, merging them into a single study can balance the limitations of each and potentially produce more in-depth findings.

However, mixed methods research is not without its drawbacks. Combining research methods increases the complexity of a study and generally requires a higher level of expertise to collect, analyze and interpret the data. It also requires a greater level of effort, time and often money.

The Importance of Research Design

Data-driven practice plays an essential role in social work. Unlike philanthropists and altruistic volunteers, social workers are obligated to operate from a scientific knowledge base.

To know whether their programs are effective, social workers must conduct research to determine results, aggregate those results into comprehensible data, analyze and interpret their findings, and use evidence to justify next steps.

Employing the proper design ensures that any evidence obtained during research enables social workers to reliably answer their research questions.

Research Methods in Social Work

The various social work research methods have specific benefits and limitations determined by context. Common research methods include surveys, program evaluations, needs assessments, randomized controlled trials, descriptive studies and single-system designs.

Surveys involve a hypothesis and a series of questions in order to test that hypothesis. Social work researchers will send out a survey, receive responses, aggregate the results, analyze the data, and form conclusions based on trends.

Surveys are one of the most common research methods social workers use — and for good reason. They tend to be relatively simple and are usually affordable. However, surveys generally require large participant groups, and self-reports from survey respondents are not always reliable.

Program Evaluations

Social workers ally with all sorts of programs: after-school programs, government initiatives, nonprofit projects and private programs, for example.

Crucially, social workers must evaluate a program’s effectiveness in order to determine whether the program is meeting its goals and what improvements can be made to better serve the program’s target population.

Evidence-based programming helps everyone save money and time, and comparing programs with one another can help social workers make decisions about how to structure new initiatives. Evaluating programs becomes complicated, however, when programs have multiple goal metrics, some of which may be vague or difficult to assess (e.g., “we aim to promote the well-being of our community”).

Needs Assessments

Social workers use needs assessments to identify services and necessities that a population lacks access to.

Common social work populations that researchers may perform needs assessments on include:

• People in a specific income group
• Everyone in a specific geographic region
• A specific ethnic group
• People in a specific age group

In the field, a social worker may use a combination of methods (e.g., surveys and descriptive studies) to learn more about a specific population or program. Social workers look for gaps between the actual context and a population’s or individual’s “wants” or desires.

For example, a social worker could conduct a needs assessment with an individual with cancer trying to navigate the complex medical-industrial system. The social worker may ask the client questions about the number of hours they spend scheduling doctor’s appointments, commuting and managing their many medications. After learning more about the specific client needs, the social worker can identify opportunities for improvements in an updated care plan.

In policy and program development, social workers conduct needs assessments to determine where and how to effect change on a much larger scale. Integral to social work at all levels, needs assessments reveal crucial information about a population’s needs to researchers, policymakers and other stakeholders. Needs assessments may fall short, however, in revealing the root causes of those needs (e.g., structural racism).

Randomized Controlled Trials

Randomized controlled trials are studies in which a randomly selected group is subjected to a variable (e.g., a specific stimulus or treatment) and a control group is not. Social workers then measure and compare the results of the randomized group with the control group in order to glean insights about the effectiveness of a particular intervention or treatment.

Randomized controlled trials are easily reproducible and highly measurable. They’re useful when results are easily quantifiable. However, this method is less helpful when results are not easily quantifiable (i.e., when rich data such as narratives and on-the-ground observations are needed).

Descriptive Studies

Descriptive studies immerse the researcher in another context or culture to study specific participant practices or ways of living. Descriptive studies, including descriptive ethnographic studies, may overlap with and include other research methods:

• Informant interviews
• Census data
• Observation

By using descriptive studies, researchers may glean a richer, deeper understanding of a nuanced culture or group on-site. The main limitations of this research method are that it tends to be time-consuming and expensive.

Single-System Designs

Unlike most medical studies, which involve testing a drug or treatment on two groups — an experimental group that receives the drug/treatment and a control group that does not — single-system designs allow researchers to study just one group (e.g., an individual or family).

Single-system designs typically entail studying a single group over a long period of time and may involve assessing the group’s response to multiple variables.

For example, consider a study on how media consumption affects a person’s mood. One way to test a hypothesis that consuming media correlates with low mood would be to observe two groups: a control group (no media) and an experimental group (two hours of media per day). When employing a single-system design, however, researchers would observe a single participant as they watch two hours of media per day for one week and then four hours per day of media the next week.

These designs allow researchers to test multiple variables over a longer period of time. However, similar to descriptive studies, single-system designs can be fairly time-consuming and costly.

Learn More About Social Work Research Methods

Social workers have the opportunity to improve the social environment by advocating for the vulnerable — including children, older adults and people with disabilities — and facilitating and developing resources and programs.

Learn more about how you can earn your  Master of Social Work online at Virginia Commonwealth University . The highest-ranking school of social work in Virginia, VCU has a wide range of courses online. That means students can earn their degrees with the flexibility of learning at home. Learn more about how you can take your career in social work further with VCU.

From M.S.W. to LCSW: Understanding Your Career Path as a Social Worker

How Palliative Care Social Workers Support Patients With Terminal Illnesses

How to Become a Social Worker in Health Care

Gov.uk, Mixed Methods Study

MVS Open Press, Foundations of Social Work Research

Open Social Work Education, Scientific Inquiry in Social Work

Open Social Work, Graduate Research Methods in Social Work: A Project-Based Approach

Routledge, Research for Social Workers: An Introduction to Methods

SAGE Publications, Research Methods for Social Work: A Problem-Based Approach

Theory and Society, Mixed Methods Research: What It Is and What It Could Be

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The link between social work research and practice

When thinking about social work, some may consider the field to solely focus on clinical interventions with individuals or groups.

There may be a mistaken impression that research is not a part of the social work profession. This is completely false. Rather, the two have been and will continue to need to be intertwined.

This guide covers why social workers should care about research, how both social work practice and social work research influence and guide each other, how to build research skills both as a student and as a professional working in the field, and the benefits of being a social worker with strong research skills. 

A selection of social work research jobs are also discussed.  

• Social workers and research
• Evidence-based practice
• Practice and research
• Research and practice
• Build research skills
• Social worker as researcher
• Benefits of research skills
• Research jobs

Why should social workers care about research?

Sometimes it may seem as though social work practice and social work research are two separate tracks running parallel to each other – they both seek to improve the lives of clients, families and communities, but they don’t interact. This is not the way it is supposed to work.

Research and practice should be intertwined, with each affecting the other and improving processes on both ends, so that it leads to better outcomes for the population we’re serving.

Section 5 of the NASW Social Work Code of Ethics is focused on social workers’ ethical responsibilities to the social work profession. There are two areas in which research is mentioned in upholding our ethical obligations: for the integrity of the profession (section 5.01) and for evaluation and research (section 5.02). 

Some of the specific guidance provided around research and social work include:

• 5.01(b): …Social workers should protect, enhance, and improve the integrity of the profession through appropriate study and research, active discussion, and responsible criticism of the profession.
• 5.01(d): Social workers should contribute to the knowledge base of social work and share with colleagues their knowledge related to practice, research, and ethics…
• 5.02(a) Social workers should monitor and evaluate policies, the implementation of programs, and practice interventions.
• 5.02(b) Social workers should promote and facilitate evaluation and research to contribute to the development of knowledge.
• 5.02(c) Social workers should critically examine and keep current with emerging knowledge relevant to social work and fully use evaluation and research evidence in their professional practice.
• 5.02(q) Social workers should educate themselves, their students, and their colleagues about responsible research practices.

Evidence-based practice and evidence-based treatment

In order to strengthen the profession and determine that the interventions we are providing are, in fact, effective, we must conduct research. When research and practice are intertwined, this leads practitioners to develop evidence-based practice (EBP) and evidence-based treatment (EBT).

Evidence-based practice is, according to The National Association of Social Workers (NASW) , a process involving creating an answerable question based on a client or organizational need, locating the best available evidence to answer the question, evaluating the quality of the evidence as well as its applicability, applying the evidence, and evaluating the effectiveness and efficiency of the solution. 

Evidence-based treatment is any practice that has been established as effective through scientific research according to a set of explicit criteria (Drake et al., 2001). These are interventions that, when applied consistently, routinely produce improved client outcomes. 

For example, Cognitive Behavioral Therapy (CBT) was one of a variety of interventions for those with anxiety disorders. Researchers wondered if CBT was better than other intervention options in producing positive, consistent results for clients.

So research was conducted comparing multiple types of interventions, and the evidence (research results) demonstrated that CBT was the best intervention.

The anecdotal evidence from practice combined with research evidence determined that CBT should become the standard treatment for those diagnosed with anxiety. Now more social workers are getting trained in CBT methods in order to offer this as a treatment option to their clients.

How does social work practice affect research?

Social work practice provides the context and content for research. For example, agency staff was concerned about the lack of nutritional food in their service area, and heard from clients that it was too hard to get to a grocery store with a variety of foods, because they didn’t have transportation, or public transit took too long. 

So the agency applied for and received a grant to start a farmer’s market in their community, an urban area that was considered a food desert. This program accepted their state’s version of food stamps as a payment option for the items sold at the farmer’s market.

The agency used their passenger van to provide free transportation to and from the farmer’s market for those living more than four blocks from the market location.

The local university also had a booth each week at the market with nursing and medical students checking blood pressure and providing referrals to community agencies that could assist with medical needs. The agency was excited to improve the health of its clients by offering this program.

But how does the granting foundation know if this was a good use of their money? This is where research and evaluation comes in. Research could gather data to answer a number of questions. Here is but a small sample:

• How many community members visited each week and purchased fruits and vegetables? 
• How many took advantage of the transportation provided, and how many walked to the market? 
• How many took advantage of the blood pressure checks? Were improvements seen in those numbers for those having repeat blood pressure readings throughout the market season? 
• How much did the self-reported fruit and vegetable intake increase for customers? 
• What barriers did community members report in visiting and buying food from the market (prices too high? Inconvenient hours?)
• Do community members want the program to continue next year?
• Was the program cost-effective, or did it waste money by paying for a driver and for gasoline to offer free transportation that wasn’t utilized? What are areas where money could be saved without compromising the quality of the program?
• What else needs to be included in this program to help improve the health of community members?

How does research affect social work practice?

Research can guide practice to implement proven strategies. It can also ask the ‘what if’ or ‘how about’ questions that can open doors for new, innovative interventions to be developed (and then research the effectiveness of those interventions).

Engel and Schutt (2017) describe four categories of research used in social work:

• Descriptive research is research in which social phenomena are defined and described. A descriptive research question would be ‘How many homeless women with substance use disorder live in the metro area?’
• Exploratory research seeks to find out how people get along in the setting under question, what meanings they give to their actions, and what issues concern them. An example research question would be ‘What are the barriers to homeless women with substance use disorder receiving treatment services?’
• Explanatory research seeks to identify causes and effects of social phenomena. It can be used to rule out other explanations for findings and show how two events are related to each other.  An explanatory research question would be ‘Why do women with substance use disorder become homeless?’
• Evaluation research describes or identifies the impact of social programs and policies. This type of research question could be ‘How effective was XYZ treatment-first program that combined housing and required drug/alcohol abstinence in keeping women with substance use disorder in stable housing 2 years after the program ended?’

Each of the above types of research can answer important questions about the population, setting or intervention being provided. This can help practitioners determine which option is most effective or cost-efficient or that clients are most likely to adhere to. In turn, this data allows social workers to make informed choices on what to keep in their practice, and what needs changing. 

How to build research skills while in school

There are a number of ways to build research skills while a student.  BSW and MSW programs require a research course, but there are other ways to develop these skills beyond a single class:

• Volunteer to help a professor working in an area of interest. Professors are often excited to share their knowledge and receive extra assistance from students with similar interests.
• Participate in student research projects where you’re the subject. These are most often found in psychology departments. You can learn a lot about the informed consent process and how data is collected by volunteering as a research participant.  Many of these studies also pay a small amount, so it’s an easy way to earn a bit of extra money while you’re on campus. 
• Create an independent study research project as an elective and work with a professor who is an expert in an area you’re interested in.  You’d design a research study, collect the data, analyze it, and write a report or possibly even an article you can submit to an academic journal.
• Some practicum programs will have you complete a small evaluation project or assist with a larger research project as part of your field education hours. 
• In MSW programs, some professors hire students to conduct interviews or enter data on their funded research projects. This could be a good part time job while in school.
• Research assistant positions are more common in MSW programs, and these pay for some or all your tuition in exchange for working a set number of hours per week on a funded research project.

How to build research skills while working as a social worker

Social service agencies are often understaffed, with more projects to complete than there are people to complete them.

Taking the initiative to volunteer to survey clients about what they want and need, conduct an evaluation on a program, or seeing if there is data that has been previously collected but not analyzed and review that data and write up a report can help you stand out from your peers, be appreciated by management and other staff, and may even lead to a raise, a promotion, or even new job opportunities because of the skills you’ve developed.

Benefits of being a social worker with strong research skills

Social workers with strong research skills can have the opportunity to work on various projects, and at higher levels of responsibility. 

Many can be promoted into administration level positions after demonstrating they understand how to conduct, interpret and report research findings and apply those findings to improving the agency and their programs.

There’s also a level of confidence knowing you’re implementing proven strategies with your clients. 

Social work research jobs

There are a number of ways in which you can blend interests in social work and research. A quick search on Glassdoor.com and Indeed.com retrieved the following positions related to social work research:

• Research Coordinator on a clinical trial offering psychosocial supportive interventions and non-addictive pain treatments to minimize opioid use for pain.
• Senior Research Associate leading and overseeing research on a suite of projects offered in housing, mental health and corrections.
• Research Fellow in a school of social work
• Project Policy Analyst for large health organization
• Health Educator/Research Specialist to implement and evaluate cancer prevention and screening programs for a health department
• Research Interventionist providing Cognitive Behavioral Therapy for insomnia patients participating in a clinical trial
• Research Associate for Child Care and Early Education
• Social Services Data Researcher for an organization serving adults with disabilities.
• Director of Community Health Equity Research Programs evaluating health disparities.

No matter your population or area of interest, you’d likely be able to find a position that integrated research and social work. 

Social work practice and research are and should remain intertwined. This is the only way we can know what questions to ask about the programs and services we are providing, and ensure our interventions are effective. 

There are many opportunities to develop research skills while in school and while working in the field, and these skills can lead to some interesting positions that can make a real difference to clients, families and communities. 

Drake, R. E., Goldman, H., Leff, H. S., Lehman, A. F., Dixon, L., Mueser, K. T., et al. (2001). Implementing evidence-based practices in routine mental health service settings. Psychiatric Services, 52(2), 179-182. 

Engel, R.J., & Schutt, R.K. (2017). The Practice of Research in Social Work. Sage.

National Association of Social Workers. (n.d). Evidence Based Practice. Retrieved from: https://www.socialworkers.org/News/Research-Data/Social-Work-Policy-Research/Evidence-Based-Practice

Educational resources and simple solutions for your research journey

How to Craft a Strong Research Question (With Research Question Examples)

A sound and effective research question is a key element that must be identified and pinned down before researchers can even begin their research study or work. A strong research question lays the foundation for your entire study, guiding your investigation and shaping your findings. Hence, it is critical that researchers spend considerable time assessing and refining the research question based on in-depth reading and comprehensive literature review. In this article, we will discuss how to write a strong research question and provide you with some good examples of research questions across various disciplines.

Table of Contents

The importance of a research question

A research question plays a crucial role in driving scientific inquiry, setting the direction and purpose of your study, and guiding your entire research process. By formulating a clear and focused research question, you lay the foundation for your investigation, ensuring that your research remains on track and aligned with your objectives so you can make meaningful contribution to the existing body of knowledge. A well-crafted research question also helps you define the scope of your study and identify the appropriate methodologies and data collection techniques to employ.

Key components of a strong research question

A good research question possesses several key components that contribute to the quality and impact of your study. Apart from providing a clear framework to generate meaningful results, a well-defined research question allows other researchers to understand the purpose and significance of your work. So, when working on your research question, incorporate the following elements:

• Specificity : A strong research question should be specific about the main focus of your study, enabling you to gather precise data and draw accurate conclusions. It clearly defines the variables, participants, and context involved, leaving no room for ambiguity.
• Clarity : A good research question is clear and easily understood, so articulate the purpose and intent of your study concisely without being generic or vague. Ensuring clarity in your research question helps both you and your readers grasp the research objective.
• Feasibility : While crafting a research question, consider the practicality of conducting the research and availability of necessary data or access to participants. Think whether your study is realistic and achievable within the constraints of time, resources, and ethical considerations.

How to craft a well-defined research question

A first step that will help save time and effort is knowing what your aims are and thinking about a few problem statements on the area or aspect one wants to study or do research on. Contemplating these statements as one undertakes more progressive reading can help the researcher in reassessing and fine-tuning the research question. This can be done over time as they read and learn more about the research topic, along with a broad literature review and parallel discussions with peer researchers and supervisors. In some cases, a researcher can have more than one research question if the research being undertaken is a PhD thesis or dissertation, but try not to cover multiple concerns on a topic.

A strong research question must be researchable, original, complex, and relevant. Here are five simple steps that can make the entire process easier.

• Identify a broad topic from your areas of interest, something that is relevant, and you are passionate about since you’ll be spending a lot of time conducting your research.
• Do a thorough literature review to weed out potential gaps in research and stay updated on what’s currently being done in your chosen topic and subject area.
• Shortlist possible research questions based on the research gaps or see how you can build on or refute previously published ideas and concepts.
• Assess your chosen research question using the FINER criteria that helps you evaluate whether the research is Feasible, Interesting, Novel, Ethical, and Relevant. 1
• Formulate the final research question, while ensuring it is clear, well-written, and addresses all the key elements of a strong research question.

Examples of research questions

Remember to adapt your research question to suit your purpose, whether it’s exploratory, descriptive, comparative, experimental, qualitative, or quantitative. Embrace the iterative nature of the research process, continually evaluating and refining your question as you progress. Here are some good examples of research questions across various disciplines.

Exploratory research question examples

• How does social media impact interpersonal relationships among teenagers?
• What are the potential benefits of incorporating mindfulness practices in the workplace?

Descriptive research question examples

• What factors influence customer loyalty in the e-commerce industry?
• Is there a relationship between socioeconomic status and academic performance among elementary school students?

Comparative research question examples

• How does the effectiveness of traditional teaching methods compare to online learning platforms in mathematics education?
• What is the impact of different healthcare policies on patient outcomes in various countries?

Experimental research question examples

• What are the effects of a new drug on reducing symptoms of a specific medical condition?
• Does a dietary intervention have an impact on weight loss among individuals with obesity?

Qualitative research question examples

• What are the lived experiences of immigrants adapting to a new culture?
• What factors influence job satisfaction among healthcare professionals?

Quantitative research question examples

• Is there a relationship between sleep duration and academic performance among college students?
• How effective is a specific intervention in reducing anxiety levels among individuals with phobias?

With these simple guidelines and inspiring examples of research questions, you are equipped to embark on your research journey with confidence and purpose. Here’s wishing you all the best for your future endeavors!

References:

• How to write a research question: Steps and examples. Indeed Career Guide. Available online at https://www.indeed.com/career-advice/career-development/how-to-write-research-questions

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Research the White Paper

Researching the white paper:.

The process of researching and composing a white paper shares some similarities with the kind of research and writing one does for a high school or college research paper. What’s important for writers of white papers to grasp, however, is how much this genre differs from a research paper.  First, the author of a white paper already recognizes that there is a problem to be solved, a decision to be made, and the job of the author is to provide readers with substantive information to help them make some kind of decision--which may include a decision to do more research because major gaps remain. 

Thus, a white paper author would not “brainstorm” a topic. Instead, the white paper author would get busy figuring out how the problem is defined by those who are experiencing it as a problem. Typically that research begins in popular culture--social media, surveys, interviews, newspapers. Once the author has a handle on how the problem is being defined and experienced, its history and its impact, what people in the trenches believe might be the best or worst ways of addressing it, the author then will turn to academic scholarship as well as “grey” literature (more about that later).  Unlike a school research paper, the author does not set out to argue for or against a particular position, and then devote the majority of effort to finding sources to support the selected position.  Instead, the author sets out in good faith to do as much fact-finding as possible, and thus research is likely to present multiple, conflicting, and overlapping perspectives. When people research out of a genuine desire to understand and solve a problem, they listen to every source that may offer helpful information. They will thus have to do much more analysis, synthesis, and sorting of that information, which will often not fall neatly into a “pro” or “con” camp:  Solution A may, for example, solve one part of the problem but exacerbate another part of the problem. Solution C may sound like what everyone wants, but what if it’s built on a set of data that have been criticized by another reliable source?  And so it goes. 

For example, if you are trying to write a white paper on the opioid crisis, you may focus on the value of  providing free, sterilized needles--which do indeed reduce disease, and also provide an opportunity for the health care provider distributing them to offer addiction treatment to the user. However, the free needles are sometimes discarded on the ground, posing a danger to others; or they may be shared; or they may encourage more drug usage. All of those things can be true at once; a reader will want to know about all of these considerations in order to make an informed decision. That is the challenging job of the white paper author.     
 The research you do for your white paper will require that you identify a specific problem, seek popular culture sources to help define the problem, its history, its significance and impact for people affected by it.  You will then delve into academic and grey literature to learn about the way scholars and others with professional expertise answer these same questions. In this way, you will create creating a layered, complex portrait that provides readers with a substantive exploration useful for deliberating and decision-making. You will also likely need to find or create images, including tables, figures, illustrations or photographs, and you will document all of your sources. 

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