The EFA showed no problems with the measurement instruments: the extracted five factors explained 67.05% of the variance, and each one was composed of the expected items with good factor loadings (minimum factor loading, 0.53). Harman single factor test, which forced the extraction of a single factor, demonstrated the absence of common method bias because the extracted single factor explained only 29.37% of the variance. After these preliminary analyses, we continued with the data analysis. Although we decided to test our research model using structural equations, following Hair et al, 60 we assessed the measurement model through CFAs. In particular, to exclude the absence of a common latent factor and assess the independence of the five measures, we conducted two CFAs, comparing a one-factor model grouping all the study items with a five-factor model in which each item saturated in its expected factor. The results showed that the one-factor model had a very poor fit ( χ 2 = 25,401.97; df = 104; P < 0.001; CFI = 0.56; TLI = 0.50; RMSEA = 0.15; Standardized Root Mean Squared Residual (SRMR) = 0.11). On the other hand, the fit of the five-factor model ( χ 2 = 2831.54; df = 94; P < 0.001; CFI = 0.95; TLI = 0.94; RMSEA = 0.05; SRMR = 0.04) was satisfying, implying structural validity of the model measures. For this model, all items reported saturation values in their factor higher than 0.50.
The minimum AVE score for the five scales was 0.46. Each value was greater than the corresponding MSV score (the highest MSV was 0.35). Furthermore, the square root of each AVE value was higher than the correlations between each considered variable and the other latent constructs, indicating discriminant validity. 59 All the CR values were over the 0.70 cutoff 60 and in the range 0.72 to 0.83, suggesting good reliability of the measures. Finally, according to Fornell and Larcker, 59 although AVE values were slightly lower than the 0.50 cutoff for three of the five study variables (AVE WFC = 0.46, AVE WENG = 0.49, and AVE W-BEING = 0.49), since CR was in every case higher than 0.60 (and 0.70), the convergent validity of the constructs has been considered adequate.
Cronbach alphas for the five scales of the model showed values all above the threshold of 0.70, confirming excellent reliability of the model scales again. Together with means, standard deviations, and correlations, such values are reported in Table 2 .
Variables | Mean | SD | 1 | 2 | 3 | 4 | 5 |
---|---|---|---|---|---|---|---|
1. Workload | 3.56 | 1.74 | (0.78) | ||||
2. Work-family conflict | 2.60 | 0.90 | 0.37** | (0.72) | |||
3. Sleeping problems | 2.18 | 1.00 | 0.17** | 0.35** | (0.79) | ||
4. Work engagement | 4.00 | 0.69 | −0.03* | −0.15** | −0.24** | (0.73) | |
5. Mental well-being | 4.59 | 0.86 | −0.09** | −0.28** | −0.40** | 0.44** | (0.83) |
6. Frequency of telework | 1.49 | 0.50 | −0.10** | −0.03* | 0.02 | 0.05** | −0.01 |
The average workload reported by homeworkers tended toward high values (mean, 3.56; SD, 1.74), suggesting that homeworkers reported working with moderately tight deadlines and at a high pace. Homeworkers reported having experienced limited level of work-family conflict (mean, 2.60; SD, 0.90) and limited sleeping problems (mean, 2.18; SD, 1.00). On the other side, homeworkers were in many cases engaged with their work (mean, 4.00; SD, 0.67) and in a condition of mental well-being (mean, 4.59; SD, 0.96).
Focusing on the correlations, Table 2 shows that workload was positively correlated with work-family conflict ( r = 0.37, P < 0.001) and sleeping problems ( r = 0.17, P < 0.001), but negatively correlated with mental well-being ( r = −0.03, P = 0.003). Work-family conflict was positively correlated with sleeping problems ( r = 0.35, P < 0.001) and negatively correlated with mental well-being ( r = −0.28, P < 0.001). Sleeping problems had a significant negative association with work engagement ( r = −0.24, P < 0.001) and mental well-being ( r = −0.40, P < 0.001), whereas work engagement had a positive correlation with mental well-being ( r = 0.44, P < 0.001).
The hypothesized model was tested using SEM. In this model, the control variable of the frequency of homeworking was tested on the mediational variables of work-family conflict and work engagement, since no significant correlations were instead obtained between this control variable and, respectively, sleeping problems and mental well-being.
The model as a whole, with the errors of the variables work-family conflict and sleeping problems correlated to improve the closeness of the model to the reality described by data, reported an adequate fit ( χ 2 = 3022.73; df = 107; P < 0.001; CFI = 0.95; TLI = 0.94; RMSEA = 0.05; SRMR = 0.04). In addition, all the measured items reported saturation values greater than 0.50 in their latent factors, confirming the CFA results and the good validity of the measures. Figure 2 depicts the model results.
According to the model results, the relationship between homeworkers’ workload and mental well-being was small but positive ( β = 0.04, P = 0.001; confidence interval [CI], 0.02 to 0.06). Thus, H1 was not verified, since the hypothesized relationship is significant but, contrary to expectations, positive.
Workload significantly and positively influenced work-family conflict ( β = 0.50, P < 0.001; CI, 0.49 to 0.52; hypotheses H2a supported). In turn, work-family conflict negatively affected work engagement ( β = −0.15; P < 0.001; CI, −0.18 to −0.13) and mental well-being ( β = −0.13, P < 0.001; CI, −0.16 to −0.11). Thus, H2b and H2c were fully supported. Even H2d was supported, and Table 3 shows the indirect effect of homeworkers’ workload on mental well-being via work-family conflict ( β = −0.07; P < 0.001; CI, −0.08 to −0.05).
Indirect Effects | |
---|---|
WLD → WFC → MWB | −0.07* |
WLD → SP → MWB | −0.06* |
WLD → WE → MWB | 0.04* |
WLD → WFC → WE → MWB | −0.04* |
WLD → SP → WE → MWB | −0.03* |
Total indirect effect of WLD on MWB | −0.16* |
Regarding the hypotheses about sleeping problems, H3a was supported because homeworkers’ workload was positively related to sleeping problems ( β = 0.23; P < 0.001; CI, 0.21 to 0.25). Sleeping problems was negatively related to work engagement ( β = −0.30; P < 0.001; CI, −0.32 to −0.28) and mental well-being ( β = −0.28; P < 0.001; CI, −0.30 to −0.26), supporting also H3b and H3c. Furthermore, the indirect effect of homeworkers’ workload on mental well-being via sleeping problems was also significant ( β = −0.06; P < 0.001; CI, −0.07 to −0.06), supporting hypothesis H3d ( Table 3 ).
Finally, an unexpected result was observed between homeworkers’ workload and work engagement. Workload was positively, rather than negatively, related to work engagement ( β = 0.09, P < 0.001; CI, 0.07 to 0.11). Hence, hypothesis H4a was not supported, although the relationship is significant and opposite to the hypothesis. However, as expected, homeworkers’ work engagement significantly and positively affected mental well-being ( β = 0.47, P < 0.001; CI, 0.45 to 0.49), supporting hypothesis H4b. Homeworkers’ workload showed also an indirect effect on mental well-being via work engagement ( β = 0.04; P < 0.001; CI, 0.03 to 0.05) ( Table 3 ), supporting hypothesis H4c.
Indirect effects were then observed even in the two serial mediations. The mediations between workload and mental well-being via work-family conflict and work engagement ( β = −0.04; P < 0.001; CI, −0.04 to −0.03), and also that one via sleeping problems and work engagement ( β = −0.03; P < 0.001; CI, −0.04 to −0.03) were significant, thus supporting H4d and H4e.
Finally, the total indirect effect of workload on mental well-being, through the multiple mediators, as shown in Table 3 , was negative and significant ( β = −0.16; P < 0.001; CI, −0.17 to −0.14). Hence, the negative indirect effects of workload on mental well-being are higher than the positive direct effect of these two variables; as a result, the total effect of the relationship between workload and mental well-being, calculated as the sum of direct and indirect effects, is therefore negative ( β = −0.12; P < 0.001; CI, −0.14 to −0.10).
Lastly, the control variable of frequency of homeworking revealed significant relationships with the tested variables. Positive, although small, effects were found between frequency of homeworking and, respectively, work-family conflict ( β = 0.06 P < 0.001; CI, 0.05 to 0.08) and work engagement ( β = 0.06 P < 0.001; CI, 0.04 to 0.07).
This study used the COR theory as theoretical background to investigate the relationship between homeworkers’ workload and mental well-being and the mediating effect of work-family conflict, sleeping problems, and work engagement. In light of this approach, we expected that employees’ workload at home was positively related to work-family conflict and sleeping problems and negatively related to work engagement. Furthermore, we expected that work engagement was, in turn, negatively related to work-family conflict and sleeping problems and positively related to mental well-being.
Most of our study hypotheses were supported. Homeworkers’ workload positively affected work-family conflict, sleeping problems, and, surprisingly, work engagement and had a total negative effect on mental well-being.
The positive effect of the workload on work-family conflicts and sleeping problems was also observed in previous studies reporting the positive effect of workload on work-family conflict 30 and sleeping problems 15,23,61 in employees working at official sites of their organization. Our result extends findings observed in the official workplace to the field of homework and confirms the applicability of COR theory to homeworking. Investing time and energy resources to cope with an increased workload may result in the depletion of energy resources needed to balance work and family life and have a good quality of sleep, consequently affecting mental well-being resulting from the stress experienced from the loss of resources.
However, study findings also reveal an unexpected result by reporting a positive relationship between workload on work engagement. This unexpected finding, although small ( β = 0.09; P < 0.001; CI, 0.07 to 0.11), is contrary to the one found by Ladyshewsky and Taplin, 62 who reported that workload negatively affects work engagement. Although this result was unexpected, other studies support the evidence reported in this research, suggesting that workload may not always be harmful but, in some cases, may have a positive effect on work engagement. 43–45,63 In other words, the workload may not always have a detrimental effect on work engagement. Instead, the relationship between these two variables could be curvilinear in the homeworking context, as already observed in the usual workplace. 45
Considering that workload was positively related to work-family conflict, sleeping problems, and, at the same time, also positively related to work engagement, our findings support previous studies that identified workload both as a hindrance and a challenge stressor 44,63 that increases employees’ work engagement to completing their challenging work, while also impacting work-family conflict and sleeping problems that diminish employees’ energy. 43
Focusing on the relationship between workload and well-being, we point out that, although the direct relationship was small but positive ( β = 0.04; P = 0.001; CI, 0.01 to 05), the total effect of workload on mental well-being, as mentioned above, was instead significant and negative ( β = −0.12; P < 0.001; CI, −0.14 to −0.10), thus suggesting that the three mediators in our model contribute to establishing that too much workload is negative for homeworkers. Therefore, this suggests that intervening in those factors (work-family conflict, work engagement, and sleeping problems) could reduce the negative effect of the workload on homeworkers’ well-being.
The importance of those three mediators is also confirmed by the simple direct relationships they have with mental well-being. This study shows that work-family conflict is negatively related to work engagement and mental well-being, thus supporting prior studies on work engagement 28,32,34 and employees’ well-being 33,64 and extending those findings to homeworkers. Although other studies used different theoretical approaches, our results are also coherent with the spiral loss of resources of the COR theory. Sleeping problems experienced by homeworkers had a significant adverse effect on work engagement and well-being, consistently with previous studies conducted in other contexts. 36–39 Based on the COR theory’s desperation principle, homeworkers may be less inclined to invest more resources into their work task (work engagement) when their self-regulatory resources have not been fully replenished due to sleeping problems. 37 The loss of this resource, in turn, may explain the loss of the other resource, which is well-being. Thus, our study sheds light on the potential mechanism that the resource loss of time and energy due to high workload compromises sleep quality, leading to the loss of other resources such as well-being.
Finally, despite the frequency of homeworking was marginally related to work-family conflict and work engagement, this variable was not related to mental well-being * . However, we believe that this latter result is also an interesting research finding because it suggests that workers’ mental well-being is not related to the mere frequency of homeworking, but to characteristics of the task and the context in which homeworking is carried out. Nevertheless, we believe these results should be read with caution and also interpreted considering other studies that suggest a curvilinear relationship between frequency of homeworking and some worker satisfaction outcomes. 56,57
In this study, we contributed to the literature on the relationship between workload and well-being in the context of homework by simultaneously exploring the mediational variables of work-family conflict, sleeping problems, and work engagement.
From a theoretical point of view, since research on the effect of workload on homeworkers’ well-being is limited, 15,16 we believe our findings, framed in the COR theory, 22 contribute to homeworking literature by showing that homeworkers’ workload has, on the whole, a negative impact on mental well-being and that workload contributes to increased work-family conflict, sleeping problems, and also work engagement that, in turn, affect mental well-being. This result is coherent with the resource caravans’ principle of the COR theory, which suggests that resources, or threats of resources, do not exist individually but travel in packs. 22 Thus, workload threatens mental well-being because it affects, at least, other two aspects that can become potential stressors, such as sleep and family relations.
Our results also show that workload is positively related to work engagement and positively related to mental well-being. Considering the second principle of the COR theory, which states that individuals invest resources to protect against resource loss, it seems that employees dedicate time, energy, and mental resources to work (in other words, become more engaged in their work) to compensate the adverse effects of the workload. Hobfoll et al 22 suggest that individuals, over time, learn how to adapt to stressors and how to use their resources effectively. Thus, a possible explanation of this result is that employees know that workload negatively impacts individual and family resources and, to mitigate such effects, they increase their work engagement to manage their work tasks, complete them quickly and effectively, and dedicate the remaining time to family duties or free time.
On the other side, our study also confirms that workload as a challenging or a hindrance stressor. 43–45 According to our results, the workload is related to both negative (increased work-family conflict and sleeping problems) and positive outcomes (work engagement), which confirms a complex relationship between workload and employees’ well-being that depends on the mediators included in the studies. Our findings suggest that workload is not only a threatening stressor but also a resource that enhances, through work engagement, employees’ mental well-being. Montani et al 45 observed that the relationships between workload and work engagement may be curvilinear. Thus, future studies should investigate under which conditions the positive sides of homework workload are observed and how positive and negative effects of workload coexist.
From a practical point of view, this research provides some insights that may help organizations and managers coordinate employees’ work. High amounts of workload are associated with work-family conflict and sleep problems, and these threaten the mental well-being of their employees, potentially affecting their effectiveness at work. On the other hand, we guess that a moderate extent of workload, compared with too low or too high, might enhance employees’ engagement with their work, leading them to feel better and, potentially, work better. Therefore, organizations should pay attention to employees’ workload and identify and avoid to assign tasks, with a too high or low workload to favor employees’ well-being and maximize their efforts.
Our study points out that offering homeworking alone may not be enough. Organizations implementing homeworking should also implement strategies to contain work-family conflict (eg, by considering employees’ childcare needs) and sleeping problems (eg, by promoting proper sleep-wake rhythms, including working on the proper use and correct timing of homework), as well as interventions aimed at fostering work engagement. Such organizational interventions seem promising directions to ensure that workload does not affect the mental well-being of homeworkers.
This study has different limitations. In particular, it used a cross-sectional research design, which limits the causal inferences between study variables. In addition, the cross-sectional mediational analysis may show mediational effects that exaggerate indirect effects among study variables that are different from effects observed using longitudinal studies or multiwave design. 65 To lessen this limitation, we used a large sample size to diminish biases in regression estimates because of measurement errors. 66 Furthermore, we point out that the study design does not exclude the possibility of reverse mediations between the investigated variables. For these reasons, future research may use a longitudinal design approach to more appropriately support the evidence found here.
Furthermore, another major limitation of the study is that data were collected before the COVID-19 pandemic. Although there are no rational reasons to think about changes in the tested relationships, future studies should verify if, in a postpandemic scenario, the conclusions drawn may still be applicable. Finally, we point out that this study used self-reported measures. Thus, they may lead to exaggeration or understatement on the part of the participants opening up to the tendency of common method bias, which may compromise the study's validity. Therefore, future studies using multirater measures should address this issue.
The present study sheds light on the underlying mechanisms of workload affecting employees’ mental well-being. Findings suggest that the workload experienced by homeworkers is related to work-family conflict, sleeping problems, and work engagement, which, in turn, affect mental well-being. This study contributes to the literature by providing new evidence on the relationship between workload and well-being, offering insights for academic research and organizational interventions on the complex relationship between workload and well-being in homeworkers. We conclude that organizations just offering homeworking without considering needs and duties when working at home are not enough to improve the well-being of homeworkers. Further work on appropriate home working conditions (eg, workload) may represent a good step forward to achieve the purpose of homeworking and improve homeworkers’ well-being. Hence, the present study offered significant knowledge and empirical evidence to help organizational policymakers and managers on the need to pay critical attention to employees’ workload during homeworking.
* Note: Although not included in our hypotheses, following the suggestion of a reviewer, we tested “frequency of homeworking” using a multigroup approach to highlight potential differences in the model in low- or high-frequency homeworking conditions. The results of this multigroup analysis are not included in this article because they confirmed that all relationships in the research model were significant and, in the same direction, in the low- and high-frequency homeworking conditions. These results are anyway available upon request to the corresponding author.
homework; workload; work-family conflict; sleeping problems; work engagement; mental well-being
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Education scholar Denise Pope has found that too much homework has negative effects on student well-being and behavioral engagement. (Image credit: L.A. Cicero)
A Stanford researcher found that too much homework can negatively affect kids, especially their lives away from school, where family, friends and activities matter.
“Our findings on the effects of homework challenge the traditional assumption that homework is inherently good,” wrote Denise Pope , a senior lecturer at the Stanford Graduate School of Education and a co-author of a study published in the Journal of Experimental Education .
The researchers used survey data to examine perceptions about homework, student well-being and behavioral engagement in a sample of 4,317 students from 10 high-performing high schools in upper-middle-class California communities. Along with the survey data, Pope and her colleagues used open-ended answers to explore the students’ views on homework.
Median household income exceeded $90,000 in these communities, and 93 percent of the students went on to college, either two-year or four-year.
Students in these schools average about 3.1 hours of homework each night.
“The findings address how current homework practices in privileged, high-performing schools sustain students’ advantage in competitive climates yet hinder learning, full engagement and well-being,” Pope wrote.
Pope and her colleagues found that too much homework can diminish its effectiveness and even be counterproductive. They cite prior research indicating that homework benefits plateau at about two hours per night, and that 90 minutes to two and a half hours is optimal for high school.
Their study found that too much homework is associated with:
* Greater stress: 56 percent of the students considered homework a primary source of stress, according to the survey data. Forty-three percent viewed tests as a primary stressor, while 33 percent put the pressure to get good grades in that category. Less than 1 percent of the students said homework was not a stressor.
* Reductions in health: In their open-ended answers, many students said their homework load led to sleep deprivation and other health problems. The researchers asked students whether they experienced health issues such as headaches, exhaustion, sleep deprivation, weight loss and stomach problems.
* Less time for friends, family and extracurricular pursuits: Both the survey data and student responses indicate that spending too much time on homework meant that students were “not meeting their developmental needs or cultivating other critical life skills,” according to the researchers. Students were more likely to drop activities, not see friends or family, and not pursue hobbies they enjoy.
The results offer empirical evidence that many students struggle to find balance between homework, extracurricular activities and social time, the researchers said. Many students felt forced or obligated to choose homework over developing other talents or skills.
Also, there was no relationship between the time spent on homework and how much the student enjoyed it. The research quoted students as saying they often do homework they see as “pointless” or “mindless” in order to keep their grades up.
“This kind of busy work, by its very nature, discourages learning and instead promotes doing homework simply to get points,” Pope said.
She said the research calls into question the value of assigning large amounts of homework in high-performing schools. Homework should not be simply assigned as a routine practice, she said.
“Rather, any homework assigned should have a purpose and benefit, and it should be designed to cultivate learning and development,” wrote Pope.
In places where students attend high-performing schools, too much homework can reduce their time to foster skills in the area of personal responsibility, the researchers concluded. “Young people are spending more time alone,” they wrote, “which means less time for family and fewer opportunities to engage in their communities.”
The researchers say that while their open-ended or “self-reporting” methodology to gauge student concerns about homework may have limitations – some might regard it as an opportunity for “typical adolescent complaining” – it was important to learn firsthand what the students believe.
The paper was co-authored by Mollie Galloway from Lewis and Clark College and Jerusha Conner from Villanova University.
Denise Pope, Stanford Graduate School of Education: (650) 725-7412, [email protected] Clifton B. Parker, Stanford News Service: (650) 725-0224, [email protected]
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Students who are chronically absent from school are much more likely to struggle with mental health challenges, with pre-teen boys and teen girls reporting some of the highest signs of distress.
When students need help, availability of mental health support often depends on the income of families. “As household income increased, so did the availability of mental health services” in children’s schools, University of Southern California researchers found in a survey of 2,500 households nationwide.
Their findings are part of an in-depth report on the continuing national school absenteeism crisis in which 25% of students, or about 12 million children, across 42 states and Washington, D.C., were chronically absent in the 2022-23 school year. That rate remains higher than the pre-pandemic national rate of 15%.
This in-depth report on chronic absenteeism is part of an EdSource partnership with the Associated Press and Stanford Professor Thomas Dee.
For earlier coverage, go to EdSource’s Getting Students Back to School .
— Rose Ciotta, investigations and projects editor
While California saw a decrease of 5 percentage points in chronic absenteeism during the same school year, to 24.9%, districts statewide are still struggling to get all students back to school .
“Chronic absenteeism in California is still twice what it was prior to the pandemic, and roughly 1 in 4 kids in public schools are chronically absent. That is just really striking and is a serious barrier to achieving academic recovery for this generation of students who were so harmed by the pandemic,” said Thomas Dee, a Stanford University education professor and economist who gathered nationwide data in collaboration with The Associated Press and the release of the USC research.
Emotional and behavioral problems also have kept kids home from school. University of Southern California research shared exclusively with AP found strong relationships between absenteeism and poor mental health.
For example, in the USC study, almost a quarter of chronically absent kids had high levels of emotional or behavioral problems, according to a parent questionnaire, compared with just 7% of kids with good attendance. Emotional symptoms among teen girls were especially linked with missing lots of school.
Families with the lowest incomes reported a much higher rate of using mental health services if they were offered to their children in school — more than five times higher than those with the highest incomes. And, crucially, the researchers also found that 1 in 5 respondents would have used mental health services if they were made available at their school, with higher rates among Black and Hispanic families who were surveyed.
“There is tremendous opportunity here for schools to increase the offerings but also, if they have the offerings, to increase the outreach to the kids and the families that need it because there is clearly an unmet need,” said Amie Rapaport , who co-authored the report and is the co-director of Center for Economic and Social Research at USC.
If Jennifer Hwang’s son made it to his first grade classroom, it was rarely without a fight.
He struggled with severe attention deficit hyperactivity disorder (ADHD), and Hwang says his teacher’s habit of discarding art work in front of him would spike his anxiety, leading to violent outbursts and refusing to even get in the car or walk onto campus.
“I thought I would have a good year in first grade, but I didn’t,” said her son, 8, whose name Hwang declined to share to protect his privacy. “I had a very bad year.”
The absences began piling up during the second semester of that 2022-23 school year; he started missing two to three days most weeks. He soon became chronically absent, meaning he missed at least 40 days total. That classified him as chronically absent because he had missed at least 10% or more days in one school year. He began to see a therapist outside the L.A. Unified district.
Addressing chronic absenteeism.
Join EdSource on Aug. 28 at 2 p.m. for a roundtable discussion on the impact of chronic absenteeism on schools and families, and hear about the latest in research, data and solutions.
Panelists include Thomas Dee, professor of education at Stanford University, who has collaborated with the Associated Press to collect attendance data from states nationwide, and Amie Rapaport, a research scientist at USC and co-author of a research report on school absenteeism.
Hwang tried getting her son an individualized education program (IEP), which would grant him access to school-based counseling services given his ADHD diagnosis. But because her son’s academic performance was up to par, the school said he didn’t need it.
She also inquired about him seeing a child psychologist who went to his Riverside Drive Charter campus in Sherman Oaks once or twice a week — but the waitlists were too long. Because he was already seeing a therapist outside of school, Hwang gave up on pressing for school resources.
The USC report published Thursday highlights that pre-teen boys, which includes children ages 5 to 12, are struggling significantly with symptoms of hyperactivity and conduct problems, while teen girls, ages 13 to 17, are struggling most with emotional symptoms, such as depression and anxiety.
Morgan Polikoff, a co-author of the USC report, said they cannot confirm there is “a cause and effect here,” noting that the correlation between chronic absenteeism and mental health challenges could “go both directions.”
“In reality, it’s probably both ways. There’s probably some kids for whom increasing anxiety is leading them to stay home, and there’s probably kids who are missing a lot of school and that’s increasing their anxiety. So it probably is bi-directional or multi-directional,” Rapaport agreed.
Both the USC researchers and Dee advocated for more research to better understand the causes of persistently high chronic absenteeism rates.
Last year, for second grade, everything changed, Hwang said, largely thanks to a teacher who adapted assignments to suit her son’s social-emotional needs and incorporated “brain breaks” into the school day, which Hwang’s son said helped him concentrate.
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“She understood him. She knew that he was bright and he felt things much more deeply, and he saw things differently and with a very different perspective,” Hwang said. “She allowed him to feel heard.”
“One day (his teacher told me), ‘Oh, my goodness, your son just gave me a hug!’ Hwang said. “That doesn’t come cheap because he does not give out hugs very often. So that he actually hugged the teacher … that says a lot.”
Hwang and her family aren’t sure what third grade will bring, but they were able to at least secure a 504, a type of plan that helps level the playing field for students with disabilities, so her son could have access to a special chair and space to doodle.
LAUSD, the second-largest school district in the nation, has struggled with high rates of chronic absenteeism since the onset of the pandemic. Nearly 33% of their over 400,000 students were chronically absent during the 2022-23 school year , down from about 40% the previous year.
Most recently, in 2023-24, preliminary data shows their rate is hovering at 32.3%, a spokesperson said.
LAUSD has increased its staffing of social workers and pupil attendance workers, but staffers say it’s just not enough.
“We have what we can afford at this point — more than ever before — but still not at an appropriate ratio that I think this board, or myself, would feel comfortable,” Superintendent Alberto Carvalho said at a news conference Monday.
Carvalho described the district’s staffing as “an unprecedented network” but did not specify how much staffing had increased.
Ofelia Sofia Ryan is one of LAUSD’s roughly 400 pupil services and attendance counselors who are on the front lines helping get chronically absent students connected with mental health resources and Medi-Cal so they can get back to school.
This year, the 20-year district veteran works in five elementary schools, including Orchard Academies in the city of Bell.
“Poverty is the No. 1 issue. Financial issues are … second — the inability of a parent to monitor because they are having two jobs, which also relates to the poverty issue,” Ryan said. “Mental health, I would say that will be maybe next.”
Darlene Rivas, one of the district’s 800 psychiatric social workers (PSWs), is assigned to two East Los Angeles elementary schools: William R. Anton and Lorena Street.
“We have to be team players because it can’t just be one person,” Rivas said. “I think that’s why you see a lot of exhaustion within PSW professionals.”
There is a long waitlist for students in need of therapy, she said. If a parent can’t make it to an initial appointment, it can take months to reschedule.
Adding staffing can come from school funding, but there are competing demands.
This year Ryan said she started on an LAUSD campus two days a week. At the last minute, “boom,” they dropped a day, she said.
“That’s very unfair, because (the district tells) you, on one hand, mental health matters, attendance matters. You’re working your butt off to get attendance improved. I improved attendance in all my schools. Everything was done by the book, and then (the school) just took the money away,” said Ryan. “You cannot do anything. You are powerless.”
Carvalho regularly touts the district’s iAttend program, where he, among others, visits the homes of chronically absent students to coax them back to school. The district made more than 34,000 home visits last school year, contributing to a more than 4 percentage point decrease in chronic absenteeism, according to the district.
What the public doesn’t know is how much work it takes after the house visit to get the child back in school, Ryan said.
Researchers like Dee offer advice for lowering chronic absenteeism rates: “Be acutely aware of the problem” and “look to the really local barriers.”
That advice appears to be playing out successfully farther north, in Placer County, where more and more of Roseville City School District’s 12,000 students are attending school regularly each year.
Placer’s 2023-24 absenteeism rate is expected to be about 11% — nearly double what it was pre-pandemic. But that is down from 20% in 2022-23 and 26% in 2021-22.
School staff have found the two main reasons for the absences are “misinformation and a lot of struggle,” said Jessica Hull, the district’s executive director of communication and community engagement. They zeroed in on these top reasons by closely tracking absenteeism over several years with their attendance system plus a notification system managed by a third-party team, SchoolStatus , that they hired specifically to address chronic absences.
The misinformation largely centers on families being unsure of whether to send a child to school when they are sick, not knowing they can rely on independent study if the family is going on a lengthy vacation, or not understanding the importance of enrolling in pre-kindergarten known as TK.
This misinformation is part of what Dee and other researchers are calling “norm erosion.”
“The learning experiences of families and students during the pandemic, in particular the experience of remote schooling, may have reduced the perceived value of regular school attendance among students and parents,” said Dee.
He cautioned against blaming parents for the erosion, saying that “we’re in a crisis now that merits immediate attention and perhaps a little less finger-pointing.”
The struggles that Hull, from Roseville, said families face are often mental health challenges, particularly with middle schoolers, or families with unmet basic needs, such as unstable housing.
One of their solutions to both barriers has been constant check-ins with those chronically absent students in order to offer resources, such as access to mental health specialists, gas cards to families facing transportation issues, and offering families bags of food from the local food bank.
Another help is clearly explaining the notices behind their child being absent . “Schools are all about the acronym and all about words that no one else understands, so we start sending letters home and talking about truancy and chronically truant and excused absence and unexcused absence — all of that’s a mess,” Hull said.
Instead, parents can expect to see at schools half-sheets of card stock paper explaining the terms and printed in five languages from English to Ukrainian to Pashto.
“It’s really trying to remove that language barrier when we are talking jargon, and they’re just saying, ‘my kid needs help, we need help figuring out how to get them to school,’” Hull said.
In Oakland, districtwide efforts include creating a sense of belonging. Oakland’s African American Male Achievement project , for example, pairs Black students with Black teachers who offer support.
Kids who identify with their educators are more likely to attend school, said Michael Gottfried, a University of Pennsylvania professor. According to one study led by Gottfried, California students felt “it’s important for me to see someone who’s like me early on, first thing in the day,” he said.
The Associated Press contributed to this story.
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We absolutely need more mental health resources in schools, and for all kids of all income levels. In rural areas, there are very few providers, and to take your child to a provider is going to involve missing multiple hours of school. For a typical once a week cadence of appointments, this is a big problem for both the parent and for the student's progress in school. Providers really only have 5 after school appointments a … Read More
We absolutely need more mental health resources in schools, and for all kids of all income levels.
In rural areas, there are very few providers, and to take your child to a provider is going to involve missing multiple hours of school. For a typical once a week cadence of appointments, this is a big problem for both the parent and for the student’s progress in school. Providers really only have 5 after school appointments a week, right?
Those few providers prioritize the most acute cases… which means the other kids do not get services, or they don’t get services until they are in crisis.
Having space in school means kids aren’t wasting their valuable time in transit, it means parents can focus on their work and not take on the additional stress of trying to arrange midday transportation, and it just makes the whole process easier. And if those professionals have a few free hours, there are plenty of things for them to do in a school that include working with small groups or even just getting the chance to observe the kids they are working with directly in the classroom or playground.
It’s clear to me that the number one reason kids don’t come to school is because they won’t be comfortable there. That could be because they’re sick with a virus, but all the pressures from social interactions or expectations are a factor too, creating additional patterns of anxiety on top of any other existing issues. Helping students with strategies to deal with those pressures is critical to academic and life success, and a teacher with 30 kids in the classroom has neither the bandwidth nor the training to really address those issues.
The observation that kids miss due to anxiety and then have anxiety due to missing school is also very on point. I’d urge all educators to be thoughtful about ensuring that they are not adding to that in their interactions with students on the first day they return.
In California, 1 in 4 students are chronically absent putting them academically behind. A new USC study finds links between absenteeism and mental health struggles.
Data gathered from over 40 states shows absenteeism improved slightly but remains above pre-pandemic levels. School leaders are trying various strategies to get students back to school.
A 2010 law sponsored by then-District Attorney Kamala Harris, allows for the arrest of parents of chronically absent students.
California’s community colleges are barred by state law from offering bachelor’s degrees in fields like education and nursing, even in remote areas without a four-year university. That’s not the case in Washington.
Stay ahead of the latest developments on education in California and nationally from early childhood to college and beyond. Sign up for EdSource’s no-cost daily email.
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Aidan bodner.
1 Faculty of Health Sciences, Simon Fraser University, Burnaby, BC V5A 1S6, Canada
Shayna skakoon-sparling.
2 Department of Psychology, Toronto Metropolitan University (Formerly Ryerson), Toronto, ON M5B 2K3, Canada
3 Institute for Social Connection, Victoria, BC V8P 5C2, Canada
Data used in the study analysis is stored and available on the OSF Repository ( https://osf.io/87vgs/ , accessed on 3 August 2022).
The COVID-19 pandemic has seen a considerable expansion in the way work settings are structured, with a continuum emerging between working fully in-person and from home. The pandemic has also exacerbated many risk factors for poor mental health in the workplace, especially in public-facing jobs. Therefore, we sought to test the potential relationship between work setting and self-rated mental health. To do so, we modeled the association of work setting (only working from home, only in-person, hybrid) on self-rated mental health (Excellent/Very Good/Good vs. Fair/Poor) in an online survey of Canadian workers during the third wave of COVID-19. The mediating effects of vaccination, masking, and distancing were explored due to the potential effect of COVID-19-related stress on mental health among those working in-person. Among 1576 workers, most reported hybrid work (77.2%). Most also reported good self-rated mental health (80.7%). Exclusive work from home (aOR: 2.79, 95%CI: 1.90, 4.07) and exclusive in-person work (aOR: 2.79, 95%CI: 1.83, 4.26) were associated with poorer self-rated mental health than hybrid work. Vaccine status mediated only a small proportion of this relationship (7%), while masking and physical distancing were not mediators. We conclude that hybrid work arrangements were associated with positive self-rated mental health. Compliance with vaccination, masking, and distancing recommendations did not meaningfully mediate this relationship.
The COVID-19 pandemic has exacerbated many risk factors for poor mental health in the workplace. As this pandemic has intensified, with rising cases and deaths globally, so too have feelings of worry and fear in response to ongoing COVID-19 community transmission [ 1 , 2 ]. Studies from across the world have demonstrated that many workers are afraid of contracting and transmitting COVID-19 while at work [ 3 , 4 , 5 , 6 ]. Fear is an adaptive defense mechanism for humans when confronted with a risk or danger, however chronic fear can lead to adverse mental health outcomes and behaviours. In the COVID-19 pandemic, fear of COVID-19 has been associated with depression, anxiety, and even impaired job performance [ 5 ]. A Canadian study from May 2020 reported that mental health has worsened since the onset of the COVID-19 pandemic, due in large part to economic uncertainty and fear of illness [ 7 ]. Notably, these negative mental health effects have largely been observed in work settings that are predominantly public-facing and more exposed to viral transmission [ 3 , 4 , 5 , 8 , 9 , 10 , 11 , 12 ].
Alongside healthcare workers, many low-wage service workers have been deemed essential workers in Canada, and like other front-facing workers at the start of the pandemic, these workers have not always had access to safe working environments [ 3 , 13 ]. At several points in the pandemic, many workers had to attend in-person positions without widespread availability of COVID-19 vaccines or public health mandates, effectively exposing them to anxiety-provoking environments. The pandemic has also heightened burdens that impact mental health among essential workers, including: adopting caretaking roles of vulnerable family members; choosing between working through illness or taking time off and facing financial losses when sick; lower job security; reduced income; greater risk of contracting COVID-19; and slashed work hours [ 10 , 14 , 15 , 16 , 17 ]. These burdens intersect with other socio-demographic factors. For example, ethnic minorities and recent immigrants in Canada are more likely to work in low-wage, public-facing positions, which highlights health equity concerns given the increased risk for COVID-19 transmission and accompanying mental health disorders in this population [ 18 , 19 ].
While mental health risks are well-known among public-facing workers, it is less clear what the mental health impacts are on workers who have been able to transition to working from home. Workers at home may experience a more complex impact of their work settings on their mental health, despite having a generally lower risk situation [ 20 , 21 , 22 ]. Although much of the research studying teleworks impacts on workers mental health during the pandemic is ongoing, several studies have already shed light on this relationship. For example, some research has shown that workers who were more afraid of COVID-19 were more productive when working from home [ 23 ]. When faced with going back to in-person work, many workers anticipate negative impacts specifically due to concerns about COVID-19 safety [ 24 ]. Conversely, telework during the pandemic has also been associated with increases in social isolation and work stress [ 23 , 25 ], family conflict [ 22 , 23 ], distractions [ 22 , 23 ], as well as food and alcohol consumption [ 22 , 26 ]—which can all negatively impact the mental health of workers [ 22 ]. A recent study from Portugal has shown that employees working from home felt like they needed to appear online and in touch with their colleagues more often, correlating depression, anxiety and stress [ 25 ].
The literature exploring differences in mental health outcomes between workers in public-facing occupations and those working from home in Canada has been sparse [ 13 , 27 ]. One study conducted in the first half of 2020 measured anxiety and depression symptoms through Generalized Anxiety Disorder 2-item (GAD-2) and Patient Health Questionaire-2 (PHQ-2) screeners. These objective measures of mental health contribute only to a narrow understanding of mental health in relation to overall wellbeing. Similarly, most of the current research has examined telework during the first waves of COVID-19. Although useful, this work may not fully capture the impact that novel interventions such as vaccines and mask mandates have on the mental health of workers. Unlike during the first waves of the pandemic, Canadians now have access to free vaccines and masks; and other risk mitigation approaches (e.g., physical distancing, ventilation) are better understood by the public. These measures may, therefore, mitigate the fear of COVID-19 and its associated stress for people working in public, front-facing jobs [ 3 ]. Conversely, we have also experienced a slow relaxation of public health orders which enforced COVID-19 protection behaviours, such as social distancing, vaccine, and mask mandates, which may increase feelings of fear or anxiety about returning to work. Thus, there is a need to explore this area further.
Furthermore, the first doses of the vaccine rollout for the general population in Canada were underway during the third wave of the pandemic in 2021, bringing about another layer of nuance to consider when assessing mental health of [ 28 ]. This development added complexity in both negative and positive directions via the potential for increased apprehension and vaccine hesitancy, as well as the potential for reduced mental distress as a result of the sense of protection offered by the vaccine [ 29 , 30 ]. Reduced mental distress due to the availability of COVID-19 vaccines may have also been more likely due to the mentally taxing events of the first and second waves which saw an overwhelmed healthcare system, deaths in long-term care facilities, and socially isolating lockdown measures [ 31 , 32 , 33 ].
Presently, at the end of the sixth wave of the COVID-19 pandemic has seen jurisdictions move further away from public health orders, following roll-outs of third doses for the majority of working age adults in response to the Omicron variant [ 34 , 35 ]. It remains unclear how the ongoing need for vaccine uptake and the turbulent nature of the pandemic will impact mental health. Moreover, as many companies and organizations transitioned large numbers of staff to working from home or a hybrid of working from home and in-person work during earlier waves of the pandemic, this work will be relevant for both employers and policy makers respectively to assess the costs and benefits of different arrangements as workplaces largely return to in-person work. Determining the extent of any differences in mental health related to work-from-home status has clear health equity implications for employers and policy makers to ensure best practices throughout the ongoing COVID-19 pandemic, as well as for future public health crises. As COVID-19 risks continue to the present day—particularly with risks such as long-COVID and unmitigated Omicron infection—it has become important to understand mental health differences according to where participants are working.
This study used survey data collected during the third wave of the COVID-19 pandemic in Canada [ 36 ] to examine whether there were any differences in self-rated mental health based on work setting and if so, what contributes to these differences? The dataset provided a unique opportunity to explore the nuances of self-rated mental health, and thus, bivariable and multivariable logistic regression models were used to test the hypothesis that mental health status is poorer among individuals who are not working from home. Additionally, physical distancing and mask wearing, which have been common practice since the onset of the pandemic, will be tested as mediators due to their potential for combating pandemic-related stressors related to concerns about COVID-19 transmission [ 37 ]. A mediation analysis tested whether COVID-19 vaccination, physical distancing, and mask adherence—due to their effectiveness as COVID-19 mitigation measures—had significant and protective effects on self-rated mental health. In conducting these analyses, we hypothesized that people working from home or engaging in hybrid work arrangements had better self-rated mental health than those working exclusively in-person. We further hypothesized that the exposure to COVID-19, as reflected in lack of compliance with public safety COVID-19 prevention guidelines, would partially mediate the association between working from home and worse self-rated mental health.
2.1. study data.
The study utilized the Canadian Social Connection Survey (CSCS) dataset, which collected data from 21 April to 1 June 2021. The survey was circulated on the internet using paid advertising on Facebook, Twitter, Instagram, and Google. Participants were eligible if they were Canadian residents and 16 years of age or older. Ethics approval was granted by the University of Victoria Research Ethics Board (Ethics Protocol Number 21-0115) [ 36 ]. All participants provided informed consent and were able to complete the questionnaire in English or French. Given the need to determine mental health effects in various work settings, the dataset allows for a comprehensive exploration. Inclusion for the current study was conditional on whether a respondent indicated that they were working during the COVID-19 pandemic.
A total of 2286 eligible participants completed the survey. Of these, 1917 were working during the COVID-19 pandemic. We excluded participants with missing observations on the primary outcome (i.e., self-rated mental health) and primary exposure variable (i.e., amount of work from home during COVID-19); thus, the analytic sample size for this analysis was 1576.
2.2.1. outcome variable.
Respondents’ self-rated mental health was the primary outcome variable for the study. This variable has previously shown a positive correlation to other mental health morbidity measures [ 38 ], but should not be conflated with other more specific diagnostic categories such as depression or anxiety [ 39 , 40 ]. Indeed, as a more global and subjective measure, many authors consider self-rated mental health as a more holistic measure of mental health outcomes which allows for a broad range of mental health issues to be captured [ 38 , 41 ], including mental health problems that are developing but which are not captured by more clinical mental health indicators [ 40 ]. Participants evaluated their current mental health on a Likert scale (At the present time, would you say your MENTAL HEALTH is: “Poor”, “Fair”, “Good”, “Very good”, or “Excellent”) (see Supplementary Materials File S1 ). The variable was dichotomized to “Negative Self-Rated Mental Health” (“Poor” and “Fair”) and “Positive Self-Rated Mental Health” (“Good”, “Very good”, and “Excellent”). This was deemed to be an acceptable (if not conservative) approach to capture a general sense of mental health status based on precedent from previous studies using self-rated mental health [ 38 ]—allowing us to explicitly identify factors associated with sub-optimal (i.e., fair or poor) mental health.
Work setting (listed as work_from_home in the dataset) was the primary explanatory variable for the study. The variable measured how often participants worked from home (“Not Working During COVID”, “Not at all”, “Very little of the time”, “Some of the time”, “Most of the time”, and “All of the time”). The levels “Very little of the time”, “Some of the time”, and “Most of the time” were collapsed into a single level—“Hybrid”. “Not at all” was recoded as “Do Not Work from Home” and “All of the time” was recoded as “Work from Home Only”. These levels allowed for a continuum of working from home to be represented. Participants who reported not working during COVID-19 were removed from analyses as our goal was to explore the effects among Canadian workers who were currently employed.
Other explanatory variables related to employment, adherence to COVID-19 mitigation measures, income, and identity were controlled for in multivariable analysis. This allowed us to isolate the effects of demographic and socio-economic factors which may otherwise play an important role in self-rated mental health while also being correlated with work setting. The included variables were household income (originally collected in increments of CAD 10,000, but binned into four groups capturing low, lower-middle, middle, and upper income groups: Less than CAD 30,000, CAD 30,000 to CAD 59,999, CAD 60,000 to CAD 89,999, CAD 90,000 or more), age (18 to 29 years-old, 30 to 39 years-old, 40 to 49 years-old, 50 to 59 years old, 60 years and older), gender (Male, Non-binary, Woman), ethnicity (White; African, Caribbean, or Black; Asian; Indigenous; Middle Eastern; Other), educational attainment (High School Diploma or Lower, Bachelor’s Degree or Higher, Some College), hours worked per week (participant-reported numeric value), national occupation class (Art, culture, recreation and sport; Business; Education, law and social, community, and government services; Health; Management; Manufacturing and utilities; Natural and applied sciences; Natural resources and agriculture; Sales and service; Trades, transport and equipment operators).
In addition to these conventional confounding variables, several additional variables were selected based on their potential to mediate the relationship between self-reported mental health and work setting. COVID-19 vaccine status and adherence to mask and/or physical distancing recommendations were identified as particularly important factors with mediation potential. These concepts were measured by asking to what extent participants wore masks in public (“Not at all”, “Somewhat”, “Very Closely”), to what extent participants practice physical distancing in public (“Not at all”, “Somewhat”, “Very Closely”), and whether participants were vaccinated (“No”, “Yes, one dose”, “Yes, two doses”).
All statistical analyses were performed using R Statistical Software version 4.1.1 (R Foundation for Statistical Computing, Vienna, Austria) [ 42 ]; DescTools and regclass packages were used to assist in model assessment and fitting [ 43 , 44 ]; the mice package was used for multiple imputations of missing observations [ 45 ]; and the mediation package was used for mediation analysis [ 46 ]. Missing observations on the remaining variables were imputed using multiple imputation in the mice package [ 45 ].
An initial multivariable binary logistic regression model ( Supplementary Materials File S1 ), with the outcome variable of self-rated mental health and primary explanatory variable of work setting, was constructed with 30 confounding variables. The final multivariable model was developed by running a backwards selection process favouring the model with lowest Akaike Information Criterion [ 47 ]. This process was balanced by supplementing the model with variables critical to understanding the relationship between work-setting and self-rated mental health that the backwards selection process had excluded. McFadden’s Pseudo R 2 and variance inflation factor were assessed for reasonability of model fit and collinearity, with variables exhibiting collinearity removed to arrive at a final multivariable model. Bivariable logistic regression models were constructed from the newly developed study sample between all explanatory variables and the outcome variable.
Mediation analysis was followed firstly via Baron and Kenney’s (1986) steps for determining mediation via logistic regression models and secondly by utilizing the mediate package in R with bootstrapping enabled [ 48 , 49 ]. The mediate package explicitly allows for handling of binary and logistic measures outside of a linear framework, while Baron and Kenney’s (1986) steps provide a process for reviewing bivariable and multivariable models, which has helped us to evaluate the associations between our primary exposure and outcome, primary exposure and mediator, mediator and outcome, and primary exposure while controlling for the mediator and outcome. The mediate function was then used for more rigorous tests of indirect (mediation) effects on the outcome variable [ 49 ].
2286 respondents were initially included. However, 370 indicated they were not currently employed and of the remaining 1916 employed respondents, 340 were missing data on our primary measures. This resulted in 1576 participants eligible for analysis. Descriptive statistics, stratified by self-rated mental health, are presented in Table 1 . The study sample predominantly reported positive self-rated mental health (80.7%) with the majority of participants in both outcome groups responding that they work both from home and in person (hybrid); however, a greater proportion (46%) of those not working from home reported negative self-rated mental health compared to those in other work setting configurations ( Figure 1 ). In terms of demographics, 41.8% were 18 to 29 years-old; 49.9% identified as a man; 65.5% were White; 36.0% earned between CAD 30,000 and CAD 59,000 in 2020; and 51.0% had a Bachelor’s degree or higher. The average number of reported hours worked per week was 23.87; 19.9% worked in sales and service; 53.7% indicated they very closely practice physically distancing 2 metres from others; 72.8% reported very closely adhering to wearing masks in public; and 56.8% had received one dose of a COVID-19 vaccine.
Work Setting and Self-Rated Mental Health.
Sample Characteristics Stratified by Self-Rated Mental Health.
Overall | Positive Self-Rated Mental Health | Negative Self-Rated Mental Health | -Value | |
---|---|---|---|---|
1576 (100) | 1272 (80.7) | 304 (19.3) | ||
18 to 29 years-old | 658 (41.8) | 572 (45.0) | 86 (28.3) | <0.001 |
30 to 39 years-old | 543 (34.5) | 460 (36.2) | 83 (27.3) | |
40 to 49 years-old | 169 (10.7) | 115 (9.0) | 54 (17.8) | |
50 to 59 years-old | 119 (7.6) | 71 (5.6) | 48 (15.8) | |
60 years and older | 87 (5.5) | 54 (4.2) | 33 (10.9) | |
<0.001 | ||||
Man | 787 (49.9) | 666 (52.4) | 121 (39.8) | |
Non-binary | 41 (2.6) | 26 (2.0) | 15 (4.9) | |
Woman | 748 (47.5) | 580 (45.6) | 168 (55.3) | |
0.0024 | ||||
White | 1033 (65.5) | 824 (64.8) | 209 (68.8) | |
African, Caribbean, or Black | 158 (10.0) | 141 (11.1) | 17 (5.6) | |
Asian | 132 (8.4) | 105 (8.3) | 27 (8.9) | |
Indigenous | 103 (6.5) | 92 (7.2) | 11 (3.6) | |
Middle Eastern | 45 (2.9) | 34 (2.7) | 11 (3.6) | |
Other | 105 (6.7) | 76 (6.0) | 29 (9.5) | |
0.8181 | ||||
Less than CAD 30,000 | 474 (30.1) | 382 (30.0) | 92 (30.3) | |
CAD 30,000 to CAD 59,999 | 567 (36.0) | 461 (36.2) | 106 (34.9) | |
CAD 60,000 to CAD 89,999 | 376 (23.9) | 305 (24.0) | 71 (23.4) | |
CAD 90,000 or more | 159 (10.1) | 124 (9.7) | 35 (11.5) | |
0.013 | ||||
High School Diploma or Lower | 187 (11.9) | 136 (10.7) | 51 (16.8) | |
Bachelor’s Degree or Higher | 804 (51.0) | 657 (51.7) | 147 (48.4) | |
Some College | 585 (37.1) | 479 (37.7) | 106 (34.9) | |
23.87 (16.8) | 22.48 (16.54) | 29.70 (16.74) | <0.0001 | |
<0.0001 | ||||
Sales and Service | 313 (19.9) | 234 (18.4) | 79 (26.0) | |
Art, Culture, Recreation and sport | 102 (6.5) | 82 (6.4) | 20 (6.6) | |
Business | 228 (14.5) | 195 (15.3) | 33 (10.9) | |
Education, Law and Social, Community, and Government Services | 272 (17.3) | 195 (15.3) | 77 (25.3) | |
Health | 180 (11.4) | 152 (11.9) | 28 (9.2) | |
Management | 193 (12.2) | 168 (13.2) | 25 (8.2) | |
Manufacturing and utilities | 47 (3.0) | 37 (2.9) | 10 (3.3) | |
Natural and applied sciences | 103 (6.5) | 93 (7.3) | 10 (3.3) | |
Natural resources and agriculture | 48 (3.0) | 37 (2.9) | 11 (3.6) | |
Trades, transport and equipment operators | 90 (5.7) | 79 (6.2) | 11 (3.6) | |
<0.0001 | ||||
Hybrid | 1216 (77.2) | 1059 (83.3) | 157 (51.6) | |
Do Not Work from Home | 155 (9.8) | 84 (6.6) | 71 (23.4) | |
Work from Home Only | 205 (13.0) | 129 (10.1) | 76 (25.0) | |
0.6947 | ||||
Not at all | 89 (5.6) | 74 (5.8) | 15 (4.9) | |
Somewhat | 641 (40.7) | 521 (41.0) | 120 (39.5) | |
Very Closely | 846 (53.7) | 677 (53.2) | 169 (55.6) | |
0.0067 | ||||
Not at all | 60 (3.8) | 50 (3.9) | 10 (3.3) | |
Somewhat | 369 (23.4) | 318 (25.0) | 51 (16.8) | |
Very Closely | 1147 (72.8) | 904 (71.1) | 243 (79.9) | |
<0.0001 | ||||
No | 286 (18.1) | 204 (16.0) | 82 (27.0) | |
Yes, one dose | 895 (56.8) | 725 (57.0) | 170 (55.9) | |
Yes, two doses | 395 (25.1) | 343 (27.0) | 52 (17.1) |
Bivariable associations were investigated between all explanatory variables and self-rated mental health ( Table 2 ). Associations between self-rated mental health and work setting were significant among people not working from home as well as those exclusively working from home. These groups had respectively 5.70 (95% Confidence Interval [95% CI]: 3.98, 8.15) and 3.97 (95% CI: 2.85, 5.52) greater odds of negative self-rated mental health as compared to people working in hybrid arrangements. Other significant bivariable associations with negative self-rated mental health were age (all ages over 40 years-old versus those 18 to 29 years-old) and being non-binary or a woman (vs. a man). Positive self-rated mental health was significantly associated with African, Caribbean, or Black ethnicity (vs. White) and Indigenous ethnicity (vs. White); having some college education or a Bachelor’s degree or higher (vs. high school diploma or lower); employment in business, health, management, natural and applied sciences, or trades, transport and equipment operations (vs. sales and services); and having one or two doses of a COVID-19 vaccine (vs. not having received a COVID-19 vaccine).
Bivariable and Multivariable Logistic Regression Models.
Bivariable | Multivariable | |||||
---|---|---|---|---|---|---|
95% CI | 95% CI | |||||
OR | Lower | Upper | aOR | Lower | Upper | |
Do Not Work from Home | ||||||
Work from Home Only | ||||||
1.03 | 1.02 | 1.03 | ||||
CAD 30,000 to CAD 59,999 | 0.95 | 0.70 | 1.30 | 0.77 | 0.53 | 1.10 |
CAD 60,000 to CAD 89,999 | 0.97 | 0.68 | 1.36 | 0.78 | 0.53 | 1.16 |
CAD 90,000 or more | 1.17 | 0.75 | 1.80 | 0.93 | 0.56 | 1.52 |
30 to 39 years-old | 1.20 | 0.87 | 1.66 | 1.19 | 0.83 | 1.71 |
40 to 49 years-old | ||||||
50 to 59 years-old | ||||||
60 years and older | ||||||
Non-binary | ||||||
Woman | 1.15 | 0.86 | 1.56 | |||
African, Caribbean, or Black | 0.79 | 0.43 | 1.38 | |||
Asian | 1.01 | 0.64 | 1.57 | 1.11 | 0.66 | 1.82 |
Indigenous | 0.84 | 0.40 | 1.61 | |||
Middle Eastern | 1.28 | 0.61 | 2.48 | |||
Other | 1.50 | 0.94 | 2.34 | |||
Bachelor’s Degree or Higher | 0.70 | 0.45 | 1.10 | |||
Some College | 0.76 | 0.49 | 1.20 | |||
Art, Culture, Recreation and sport | 0.72 | 0.41 | 1.23 | 0.82 | 0.44 | 1.49 |
Business | ||||||
Education, Law and Social, Community, and Government Services | 1.17 | 0.81 | 1.69 | 0.86 | 0.55 | 1.34 |
Health | ||||||
Management | ||||||
Manufacturing and utilities | 0.80 | 0.36 | 1.63 | 0.78 | 0.33 | 1.71 |
Natural and applied sciences | ||||||
Natural resources and agriculture | 0.88 | 0.41 | 1.76 | 0.74 | 0.31 | 1.66 |
Trades, transport and equipment operators | ||||||
Somewhat | 0.80 | 0.40 | 1.77 | 1.02 | 0.45 | 2.46 |
Very Closely | 1.34 | 0.70 | 2.85 | 1.58 | 0.71 | 3.79 |
Somewhat | 1.14 | 0.65 | 2.12 | 1.32 | 0.66 | 2.78 |
Very Closely | 1.23 | 0.71 | 2.28 | 1.02 | 0.51 | 2.20 |
Yes, one dose | 0.71 | 0.50 | 1.02 | |||
Yes, two doses |
Numeric bolding: Indicates statistical significance.
In the multivariable model, after controlling for potential confounders, negative self-rated mental health retained the association with not working from home (Adjusted Odds Ratio [aOR]: 2.79, 95% CI: 1.83, 4.26) and working from home exclusively (aOR: 2.79, 95% CI: 1.90, 4.07) versus hybrid work. Furthermore, negative self-rated mental health was significantly associated with increasing hours worked per week, being 40 years or older (vs. 18 to 29 years-old), identifying as non-binary (vs. man), Middle Eastern or Other ethnicity (vs. White), Conversely, positive self-rated mental health was associated with employment in business, health, management, natural and applied sciences, or trades, transport and equipment operations (vs. sales and services); and having two doses of a COVID-19 vaccine (vs. not having received any).
Table 3 illustrates the results of the mediation analyses for each of the three COVID-19 prevention factors. Vaccination status was found to be a statistically significant mediator ( p = 0.02), mediating approximately 7% of the relationship between work setting and self-rated mental health; mask wearing ( p = 0.76) and physical distancing ( p = 0.20) were not found to significantly mediate the relationship. In the mediation analyses for vaccination status, the first part of the pathway between work setting and self-rated mental health, when adjusting for having received a COVID-19 vaccine, shows not working from home is significantly associated with negative self-rated mental health (aOR: 3.91, 95% CI: 2.74, 5.56). The next part of the pathway between work setting and having received a COVID-19 vaccine indicates people not working from home had lower odds of having at least one dose of a COVID-19 vaccine (OR: 0.52, 95% CI: 0.39, 0.70). The last part of the pathway shows a significant association between having received a COVID-19 vaccine and positive self-rated mental health (OR: 0.30, 95% CI: 0.21, 0.43).
Relationship between Work Setting (Ref = At least some of the time (Hybrid/Work from home only)), Mediators (Vaccination Status (Ref = No), Adherence to Mask Wearing Recommendations (Ref = Not at all), and Adherence to Physical Distancing Recommendations (Ref = Not at all)), and Self-Rated Mental Health (Ref = Positive).
Vaccination Status | Mask Wearing | Physical Distancing | |
---|---|---|---|
WS → Vaccination | |||
Vaccination → SRMH | |||
WS → SRMH | |||
Proportion Mediated (Average) | |||
WS → Masks | 0.82 (0.40, 2.00) | ||
Masks → SRMH | 1.20 (0.63, 2.54) | ||
WS → SRMH | 4.32 (3.05, 6.10) | ||
Proportion Mediated (Average) | −0.002 | ||
WS → Distancing | 0.47 (0.27, 0.86) | ||
Distancing → SRMH | 1.19 (0.69, 2.18) | ||
WS → SRMH | 4.40 (3.10, 6.22) | ||
Proportion Mediated (Average) | −0.01 |
1 OR = Odds Ratio (95% Confidence Interval); 2 aOR = Adjusted Odds Ratio (95% Confidence Interval); * p ≤ 0.05; Numeric bolding: Indicates statistical significance; WS = Work setting; SRMH = Self-rated mental health.
Primary findings.
This study represents a preliminary assessment of the relationship between work setting and self-rated mental health, controlling for relevant demographic factors, and providing several preliminary insights into the ways in which COVID-19 stressors and protections shape these relationships. In doing so, our findings show that mental health is adversely impacted for those either working exclusively from home or in person. This is in agreement with existing literature showing poor mental health among workers in public-facing workspaces across numerous international contexts [ 8 , 9 , 10 , 11 , 12 , 13 , 14 ]. Similarly, although findings of studies examining mental health effects of working from home prior to the COVID-19 pandemic have been inconsistent [ 21 ], studies exploring this increasingly normalized work setting during the pandemic have generally found working from home associated with poorer mental health outcomes [ 26 ]. This is often attributed to difficulties in establishing a work-life balance and due to feelings of isolation [ 22 , 23 , 50 , 51 ]. However, the current findings are unique in that only a handful of studies investigating the link between workplace and mental health during COVID-19 to-date have directly examined varying degrees of working from home [ 8 , 9 , 13 , 27 ] and none to our knowledge have investigated these associations during the later phases of the COVID-19 pandemic, when vaccines were made widely available. Furthermore, the majority of studies have explored the mental health of healthcare workers [ 2 , 11 , 12 , 52 ] or those in public-facing positions [ 10 ]. As such, the present study makes a valuable contribution in terms of the timing within the COVID-19 pandemic, its focus on a broad range of labour sectors, and its use of holistic self-rated mental health measures.
As such, these findings help to further research into the mental health outcomes of the Canadian workforce during the later phases of ongoing COVID-19 pandemic and beyond. One Canadian study exploring the relationship between working from home and self-rated mental health (although not of primary interest) during the first wave of the pandemic found that workers who transitioned to working from home did not differ or have affected mental health when compared to those who remained working in-person. Conversely, another Canadian study from the first wave of the pandemic found lower prevalence of depression and anxiety among respondents working from home or those working in person whose employers met all of their infection control needs [ 27 ]. These findings differ from what this study has found during the third wave, namely: both not working from home and working exclusively from home are significantly associated with negative self-rated mental health. Turning to international evidence (again from the first wave), both Gómez-Salgado et al. (2020) and Mazza et al. (2020) found poorer mental health was associated with not working from home, when compared to working from home, and not working at all, respectively. The range of evidence adds credence to our findings indicating negative mental health outcomes at either end of the work from home continuum—where workers are exclusively working from one location.
The mediation analysis found that, of the three variables tested, COVID-19 vaccination status was the only significant mediator of the effect of work setting on self-rated mental health. However, this variable mediated only approximately 7% of the effect of work setting on self-rated mental health. Both the lack of significance and the low impact of the mediation among the variables tested suggests that the prominent source of psychological stress may not arise from fear of COVID-19 infection. Although it is likely that these prevention measures may do less to mediate mental health among workers who are not continually facing risk of viral exposure, it is less clear why this would also be the case for public-facing workers. One possibility could be that, by the later phases of the COVID-19 pandemic, workplaces already tended to have high levels of COVID-19 control measures in place [ 53 ], likely reducing the contribution of the environment to stress related to concerns about viral exposure. Secondly, views on the severity of COVID-19 symptoms or susceptibility to it may have an impact on the extent that the COVID-19 prevention measures mediate mental health [ 54 ]. Lastly, uncertainty related to the unpredictable trajectory of the pandemic, such as economic concerns may present as greater stressors when compared to fears of COVID-19 infection [ 55 ].
This study also highlighted poor negative mental health among several groups. Though we did not specifically explore groups that are more likely to work from home, concerns have been raised about the well-being of ethnic minority groups who disproportionately work in public-facing occupations [ 56 ]. These sectors have experienced numerous disruptions in their capacity to operate throughout the COVID-19 pandemic [ 19 ]. This has had severe effects on members of ethnic minorities. For instance, in mid-2020, 44% and 40% of people of Arabic and West Asian ethnicity respectively, reported that the COVID-19 pandemic had moderate to strong impacts on their financial stability [ 57 ].
The identity groups associated with negative self-rated mental health—non-binary individuals and people over 40 years—are less clear in terms of contextualizing within work setting. For non-binary individuals, it is unclear whether they are more likely to work from home; however, it does appear that the pre-pandemic stressors have been compounded by COVID-19 for members of sexual and gender minorities [ 58 ]. As for middle-and-older age workers, the association with negative self-rated mental health corresponds to a general trend that mental health has worsened for all age groups in Canada since the onset of the pandemic [ 59 ]; however, it is unclear what this finding may mean in the context of other studies, indicating better mental health among older adults during the pandemic [ 60 , 61 ].
Despite COVID-19 prevention measures not emerging as a primary influencer of self-rated mental health, Canadian provinces such as British Columbia have routinely made it a priority to vaccinate frontline workers, a category of worker who cannot typically work from home [ 62 ]. Moreover, in examining other sources of economic-related stress, initial pandemic responses did see the Canadian federal government initiating supports for unemployed workers such as the Canada Emergency Response Benefit (CERB) in conjunction with provincial eviction bans, and to a lesser extent, rent freezes [ 63 ]. Though CERB provided support for workers financially impacted by the pandemic, workers who continued to be employed did not enjoy these benefits, despite facing the possibility of reduced work hours. Moreover, rent freezes that were widely enacted by provincial governments were largely discontinued after December 2020 [ 63 ]. Thus, despite a relatively rapid implementation of social protections in response to the arrival of COVID-19 in Canada [ 64 ], the lack of continuity of these measures coupled with pandemic uncertainty may feed into stressors affecting Canadian workers.
This exploratory study has limitations but provides rationale for more rigorous investigations of the potential benefits of hybrid work. Limitations include our use of secondary data that likely does not fully capture the nuanced associations between work setting and self-rated mental health. These relationships are further simplified by our analytic choices to collapse work setting to three levels and self-rated mental health to two levels. Future studies should explore more comprehensive measures of mental health, including using specific measures of anxiety and depression. Such analyses might be feasible in large surveys, such as ours, through the use of short scales developed for large surveys, such as the PHQ-2 and GAD-2. It is possible that these more specific measures would allow for greater granularity in understanding how working conditions during an ongoing public health crisis is related to mental health and well-being—particularly in terms of the mediating effects of COVID-19 prevention on anxiety and stress (vs. depression). Qualitative research could also be used to better understand specific pathways of poor mental health for those working exclusively from home or in-person. Given limitations in measurement, the results of the current study must be interpreted with caution when considering specific psychological disorders. As well, the dataset over-represented (77.2%) individuals who work in hybrid arrangements, compared to the other two groups (exclusively working from home and exclusively working in-person). Caution should therefore be taken in interpretation, as this drastically departs from the range of Canadian workers working the majority of their hours from home—40.5% in April 2020 to 26.5% in June 2021 [ 65 ]. Lastly, as the CSCS did not include questions assessing individuals’ worry about COVID-19 exposure at work, nor how well their workplace implemented protection protocols, we were not able to account for the nuance of psychological distress related to COVID-19 infection. The measures we use to assess compliance are global and not work specific. As such, our mediation models should be interpreted as preliminary. Likewise, some measures need refined assessment in future studies. For example, to measure income, participants’ household incomes were collected in increments of $10,000 CAD. Bins of $30,000 CAD were selected with consideration of classifying individuals according to approximate thresholds for low- (e.g., Approx. $30,000 per households) and median income (approx. $90,000 per household) in Canada. As household size and cost-of living values varied, a more nuanced measure of income would have been preferred by was not available in this secondary data analysis. Personal income, adjusted for cost of living, could provide a more nuanced insight into working condition and types of work engaged in, as these parameters are undoubtedly important for understanding worker health.
Recognizing these limitations, as well as several opportunities to establish new lines of inquiry, we recommend that future research on the COVID-19 pandemic and future communicable disease epidemics should aim to sample a more representative group of people working from home; determine interactions between ethnic, sexual and gender minorities, and older populations; and incorporate measures of self-assessed psychological distress around workplace safety. Furthermore, as noted above, the present study did not account for important and salient factors such as living conditions, household composition, sources of material, social, and emotional support, non-work-related labor, and other undoubtedly important factors. Future research will explore these factors in relation to working arrangements. Such analyses are critical for understanding the gendered dynamics of work from home. We hypothesize that this would be a critical moderator for exploration in future research. As well, family composition and income are critical moderators for understanding how people can best be supported in distance work environments. Therefore, future research should conduct more narrow analyses or improve measurements of these key factors so that a more nuanced profile of working conditions (e.g., income, class, status, hierarchy) can be assessed in relation to our research questions. Finally, it is critical for longitudinal within person studies to continue examining the effect of work from home on individual health and wellbeing.
Given the few studies that are available assessing the effect of work setting on mental health, this study provides important data demonstrating potential hazards to mental health associated with exclusively in-person or home-based work. Hybrid models of work may therefore provide promising opportunities to improve the mental health of workers. Of course, replication will further advance our understanding of telecommuting and in-person work, particularly in the context of an ongoing public health crisis that has disproportionately impacted low-wage and marginalized people.
The authors would like to thank the 2021 Social Connection Survey Participants for their contributions of time and attention in completing our survey.
The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijerph191811588/s1 , File S1: Independent Variables Included in Initial Multivariable Binary Regression Model.
Funding for the Canadian Social Connection Survey was received from a Canadian Institutes for Health Research (CIHR) Project Grant (#480066) and a Genwell Project Research Catalyst Grant (#2021-001). KGC is funded by a Michael Smith Health Research BC Scholar Award (#1547).
Conceptualization, A.B., K.G.C., A.S., and E.B.; Data curation, K.G.C.; Formal analysis, A.B.; Funding acquisition, K.G.C.; Methodology, A.B. and K.G.C.; Supervision, K.G.C.; Writing—original draft, A.B.; Writing—review & editing, A.B., L.R., E.B., A.S., S.S.-S. and K.G.C. All authors have read and agreed to the published version of the manuscript.
The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Institutional Review Board (or Ethics Committee) of University of Victoria (protocol code 21-0115; 9 April 2021).
Informed consent was obtained from all subjects involved in the study.
Conflicts of interest.
The authors declare no conflict of interest.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.
BMC Psychology volume 11 , Article number: 188 ( 2023 ) Cite this article
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As of March 2020, the UK public were instructed to work from home where possible and as a result, nearly half of those in employment did so during the following month. Pre-pandemic, around 5% of workers chose to work from home; it was often seen as advantageous, for example due to eliminating commuting time and increasing flexibility. However, homeworking also had negative connotations, for example, blurred boundaries between work and home life due to a sense of constant connectivity to the workplace. Understanding the psychological impact of working from home in an enforced and prolonged manner due to the COVID-19 pandemic is important. Therefore, this review sought to establish the relationship between working from home, mental health, and productivity.
In January 2022, literature searches were conducted across four electronic databases: Medline, Embase, PsycInfo and Web of Science. In February 2022 grey literature searches were conducted using Google Advanced Search, NHS Evidence; Gov.uk Publications and the British Library directory of online doctoral theses. Published and unpublished literature which collected data after March 2020, included participants who experienced working from home for at least some of their working hours, and detailed the association in terms of mental health or productivity were included.
In total 6,906 citations were screened and 25 papers from electronic databases were included. Grey literature searching resulted in two additional papers. Therefore, 27 studies were included in this review. Findings suggest the association between homeworking and both, mental health and productivity varies considerably, suggesting a complex relationship, with many factors (e.g., demographics, occupation) having an influence on the relationship.
We found that there was no clear consensus as to the association between working from home and mental health or productivity. However, there are indications that those who start homeworking for the first time during a pandemic are at risk of poor productivity, as are those who experience poor mental health. Suggestions for future research are suggested.
Peer Review reports
Within the UK, the COVID-19 pandemic led to several behavioural interventions being implemented by the government with the aim to reduce transmission of the virus. As of March 2020, the public were instructed to work from home and as a result, nearly half of those in employment did so during April 2020 [ 1 ]. As of January 2022, 36% of workers still reported homeworking at least once in the last seven days [ 2 ]. Pre-pandemic, only around 5% of workers chose to work from home [ 3 ] and findings on the impact of doing so is inconsistent. For some, homeworking was seen as a positive way of overcoming issues (e.g., decreasing commuting time [ 4 ]). However, homeworking also had negative connotations, for example, blurred boundaries between work and home life due to a sense of constant connectivity to the workplace [ 5 ]. Considering the potential disadvantages of homeworking pre-pandemic, understanding the psychological effect of enforced and prolonged working from home due to the COVID-19 pandemic is important.
Unsurprisingly, since the onset of the pandemic, the association between working from home and various aspects of health have been the subject of much research. Literature reviews, including papers from pre-pandemic, have reported mixed findings. For example, a rapid review conducted by Oakman (2020), contained 23 studies published between 2008 and 2020, explored the link between working from home and mental and physical health. For mental health specifically, the relationship was reported to be complex with many conflicting findings (e.g., increased stress and increased well-being; [ 6 ]). Varied findings have also been reported by a systematic review conducted by Lunde (2022) which sought to establish the relationship between working from home and employee health (examined outcomes included: general health, pain, well-being, stress, exhaustion and burnout, satisfaction, life and leisure) using studies published between 2010 to 2020 [ 7 ].
A scoping review focused on more current pandemic related research was conducted by Elbaz (2022) and aimed to establish the association between telework (i.e., a working arrangement that allows individuals to engage in work activities through information and communication technologies from outside the main work location [ 8 ]) and work-life balance using studies published between January 2020 and December 2021. 42 papers were included, and the review concluded that teleworking resulted in a mixed relationship. However, the link between teleworking and psychological health was typically more negative than positive [ 8 ].
Thus, the purpose of this review is to establish if there is an association between working from home and both, mental health, and productivity; specifically, for those who experienced working from home during the COVID-19 pandemic. This systematic review seeks to, first, contribute to the evidence base by being the first review to collate findings from published and grey literature research originating from economically developed countries (as indicated by membership of the Organisation for Economic Co-operation and Development; OECD) into the link between working from home and both, mental health, and productivity during the COVID-19 pandemic. Second, to establish risk or resilience (as defined as positive adaptation in response to adversity [ 9 ]) factors that make an individual more likely to adapt well to homeworking during a pandemic. Third, to provide findings and conclusions that can be used to establish implications and future research suggestions for improving the experience of homeworking for those doing so during a future public health emergency.
This systematic review is designed in concordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [ 10 ]. This results in the method section describing and explaining the process of criteria selection, use of information sources, the search strategy, study selection, data collection, quality assessment and the analytical method used during the review.
The development of inclusion and exclusion criteria for the current review was iterative and developed alongside literature familiarisation, preliminary database searches, and research team meetings. The final inclusion and exclusion criteria for the current systematic review can be found in Table 1 .
Electronic database searches.
Search terms were created in relation to population/context, intervention, and outcome of the research question, as recommended by Cochrane’s Handbook for Systematic Reviews [ 11 ]. Terms were developed a priori from current literature and developed iteratively by the research team using preliminary searches to ensure a manageable and focused scope of investigation.
The final search was conducted on the 25 th of January 2022 across the following databases:
Ovid®SP MEDLINE.® 1946 to January 18, 2022
Ovid.®SP Embase 1974 to 2022 January 14
Ovid.®SP APA PsycINFO 1806 to January Week 2 2022
Web of Science™ Core Collection
The final search involved two strings of terms: firstly, those relating to homeworking, and secondly, psychological terms encompassing mental health, resilience, and productivity. Where possible, databased controlled vocabulary was used. Free text terms remained consistent across all four searches, only differing on database specific truncation and use of punctuation. Free text terms were searched within titles and abstracts on Medline, Embase and APA PsychINFO. Free text terms were searched within title, abstract, author keywords and Keywords Plus in Web of Science Core Collection. All searches were limited to 2020 – current, to only capture data related to working from home during the COVID-19 pandemic. Full search strategies for all databases, including filters and limits used can be found in Supplemental Table 1 .
The following sources were searched on the 1 st of February 2022: Google Advanced Search, NHS Evidence; Gov.uk Publications; and the British Library directory of online doctoral theses (EThOS).
The following search was used for the Google Advanced Search, NHS evidence, and EthOS. For the Google Advanced Search, the results were ordered by most relevant, and the first 20 pages (totalling 200 hits) were screened. The NHS search was limited to primary research only.
(“work from home” OR “telework” OR “homework”)
(“mental health” OR “productivity” OR “resilience”)
The remaining searches were kept relatively simple due to small numbers of papers available shown during preliminary searches. Gov.uk Publication searches were limited to: ‘research’ or ‘statistics’ or ‘policy papers and consultations’, including the terms “homework”, “telework”, or “work from home”. Office for National Statistics searches were “homework”, “telework” or “work from home”. Full search strategies for all registers and websites, including filters and limits used can be found in Supplemental Table 2 .
Results of the literature searches were downloaded to EndNote X9 reference management software (Thomson Reuters, New York, United States (US)). Initial screening was carried out for all titles and abstracts against the inclusion and exclusion criteria by one author (CEH). Each study was categorised into one of the following groups: “include”, “exclude” or “unsure”. A 10% check of excluded papers (~ 400 records) was carried out by a second reviewer (LD), any papers marked as potentially relevant by LD were then rescreened by CEH. Both of the “include” and “unsure” categories then were subject to full text screening. To provide robustness to the review process, 10% of the papers were also full text screened by a second reviewer (LD). When there were disagreements between reviewers (i.e., on 3/12 papers), a third reviewer (SKB) was used, and the majority decision taken. Articles were then categorised into “include” or “exclude”. A PRIMSA flowchart of the screening process is presented in Fig. 1 .
PRISMA flow diagram
Data was extracted using a data extraction spreadsheet by one author (CEH). Article data and information extracted included: authors; title; type of document (e.g., publication, governmental report); publication year; publication origin; aims and hypotheses; size of sample; sample demographics and characteristics; variables of interest examined, outcome measures; key findings, limitations, and recommendations. Extraction of this data allowed for study characteristics (e.g., date of publication, country of origin, sample characteristics, outcome measures) to be reported alongside key findings, whilst considering reported study limitations and recommendations/implications suggested by the authors. A 20% check of extracted data relating to key findings was carried out by LD, no discrepancies found between reviewers. Narrative synthesis was used to collate findings from the retained papers [ 12 ]. Research findings were firstly grouped by variables examined (e.g., productivity or mental health focused), and a narrative was synthesised.
The Mixed Methods Appraisal tool [ 13 ] was used to appraise the quality of included studies based on the information provided in the papers. This tool was chosen due to its ability to appraise both qualitative and quantitative studies whilst also accounting for the differences between types of study. Many reviews have used this tool for quality assessment, for example [ 14 , 15 , 16 ]. Papers were checked for suitability using the following screening questions: “Are there clear research questions?”; “Do the collected data allow to address the research questions?”. Each study was then assessed using five questions relevant to the methodological approach used within the paper [ 13 ]. One author carried out the quality appraisal (CEH).
In total 6,906 search results were extracted from electronic databases. Post duplication screening, 4,233 papers remained for title and abstract screening. 119 papers were sought for retrieval, one paper [ 17 ] was deemed potentially relevant to the review, but after exhausting all means of accessing the full text the paper had to be excluded from the review. Following title and abstract screening, 118 full texts were screened, and 25 studies were retained as they aligned with the inclusion criteria. Two additional studies were included as a result of grey literature searches. Therefore, 27 studies were included in this review (refer to Fig. 1 for flow diagram).
Date of publication.
No papers included in this review were published prior to 2020, as per the exclusion criteria. Only one paper was published in 2020 [ 18 ], 25 papers were published in 2021 [ 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 ], and one paper was published in 2022 [ 44 ].
Data extracted relating to the location of the first authors institution at the time of publication was extracted to display geographical spread of the papers retained within this review. As per the inclusion criterion, all paper origins are from OECD countries. The location of papers is relatively varied, with four papers originating from each of the USA [ 21 , 28 , 30 , 43 ], the UK [ 19 , 39 , 40 , 42 ] and Japan [ 32 , 33 , 34 , 38 ]. Three papers originated from Turkey [ 26 , 27 , 37 ], and Italy [ 18 , 22 , 24 ]. Two papers originated from Columbia [ 23 , 35 ]. The remaining papers originated from Canada [ 31 ], Germany [ 44 ], Luxembourg [ 36 ], the Netherlands [ 41 ], Portugal [ 20 ], Spain [ 25 ] and Sweden [ 29 ].
The majority of the retained papers used similar methodological approaches to collect data; 24 out of 27 of the papers used online surveys [ 18 , 20 , 21 , 22 , 23 , 24 , 25 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 ]. It is necessary to note that, three of these papers used additional qualitative elements in their surveys [ 39 , 40 , 42 ], and four surveys collected data at multiple time points [ 36 , 38 , 41 , 44 ]. Of the remaining three papers, two used secondary data analysis [ 26 , 44 ], and one paper [ 19 ] used semi-structed interviews to collect data.
Of the 27 papers, 13 focused specifically on mental health outcomes [ 22 , 24 , 25 , 26 , 28 , 29 , 33 , 34 , 36 , 37 , 41 , 42 , 43 ], six on productivity outcomes [ 20 , 21 , 23 , 27 , 31 , 32 ], and eight included both mental health and productivity outcomes [ 18 , 19 , 30 , 35 , 38 , 39 , 40 , 44 ]. All measures used varied across studies with many being unvalidated. Table 2 shows more in-depth details about variable measures.
There was substantial variation in the sample characteristics across the included papers. Sample size varied highly between papers, ranging from n = 32 [ 19 ] to n = 20,395 [ 34 ]. In relation to job role, many papers included participants from difference sectors and occupations within their study [ 19 , 21 , 22 , 23 , 25 , 27 , 28 , 31 , 32 , 33 , 37 , 38 , 39 , 41 , 43 , 44 ], two included a representative participant group [ 26 , 36 ], some targeted specific occupations or groups (e.g., Alumni from the Portuguese AESE Business School [ 20 ]; Italian professionals [ 24 ]; university staff [ 29 , 42 ]; behaviour analysists [ 30 ]; administrative workers [ 18 ]) and, some did not provide information on job role but focused on home working populations [ 34 , 35 , 40 ]. Table 3 displays extracted data in relation to sample size and characteristics including location and job role details.
Overall quality of papers varied across the 27 that were retained, with an average score of 62%. The MMAT quality scores as a percentage can be found in Table 2 . The included papers within this systematic review varied in quality. Many were cross-sectional, quantitative in methodology, and recruited participants using snowball or opportunistic sampling. This resulted in some unclear sample characteristics (e.g., not knowing where a percentage of participants were from), and uncertainty as to how often the sample were working from home. Only three of the retained papers within this review used qualitative research elements, and there was no common method for measuring mental health, or productivity across homeworking research.
To allow comparisons across and between research, findings relating to mental health and productivity will be separated and reported on separately in the following section.
This following section details outcomes relating to mental health and synthesises the following outcomes from 21 papers: ‘depression’ [ 20 , 22 , 33 , 37 , 42 ]; ‘anxiety’ [ 20 , 22 , 33 , 37 , 42 ]; ‘stress’ (including work stress) [ 18 , 22 , 28 , 29 , 35 , 37 , 38 ]; ‘psychological distress’ [ 24 , 34 , 41 ]; wellbeing [ 36 ] (including ‘subjective wellbeing’ [ 24 ], ‘psychological wellbeing’ [ 25 ]; ‘mental wellbeing’ [ 26 , 42 , 43 ]); ‘health’ [ 29 ]; ‘burnout’ [ 28 , 30 , 44 ]; and general ‘mental health’ [ 39 , 40 ]. Table 2 provides additional information on how these outcomes are measured, and it is necessary to note that there are overlap in how outcomes are described (i.e., ‘mental wellbeing’, ‘psychological wellbeing’, ‘health’, and ‘psychological distress’ were all measured using the same questionnaire).
The findings in relation to mental health varied across the retained papers. Many of the papers reported a negative relationship between homeworking and mental health and wellbeing [ 19 , 24 , 25 , 26 , 29 , 30 , 33 , 36 , 37 , 38 , 39 , 40 , 41 , 43 , 44 ]. For example, one paper established that the transition to homeworking during the pandemic increased psychological strain due to increased work intensification, poor adaptation to new ways of working, and online presenteeism [ 19 ]. Another paper reported that out of those who continued to work during the COVID-19 pandemic (i.e., not furloughed, or unemployed), teleworkers experienced less self-perceived wellbeing than those who continued working at their pre-COVID-19 workplace [ 25 ].
Some of the retained papers concluded a mixed findings in relation to home working and mental health. For example, despite a main finding that working from home during the COVID-19 pandemic results in lower levels of well-being, Schifano et al., also concluded that when the sample only includes those who switched to homeworking from office working, there is a small fall in anxiety levels when moving to working from home [ 36 ]. Additionally, Taylor et al., reports that around 40 per cent believe that their mental health had worsened either a lot or a little since working from home, compared to around 30 per cent that believed their mental health had improved [ 39 ]. Similarly, Moretti et al., reports that around 40 per cent of participants declared a reduced stress level since they have worked remotely, around 30 per cent reported an unchanged level, and one-third of participants experienced increased stress [ 18 ].
Homeworking was found to have no association with burnout by one retained paper [ 30 ]. Shimura et al., provides evidence that remote work does decrease psychological and physical stress responses when controlling for confounding factors such as job stressors, social support, and sleep status [ 38 ]. Working from home was also considered to be better for wellbeing in comparison to being furloughed or unemployed [ 25 , 36 ].
Demographics.
When considering age, findings were mixed. One paper reported being older [ 36 ] resulted in poorer mental health outcomes. Additionally, another paper focused on stress and burnout specifically reported that being a young male [ 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 ], an older male (55 +) or a middle aged or older woman (45 +) resulted in increased stress, and being a middle-aged man [ 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 ] increased burnout [ 28 ].
Being female was reported to result in increases of depression, anxiety, and stress [ 37 ]. Females were also reported to experience two or more new physical or mental health issues were provided in comparison to male workers [ 43 ]. In this study, nine types of physical issues were assessed, these included, but are not limited to, musculoskeletal discomfort or injury, headaches or migraines, cardiovascular issues. Eight types of mental health issues were assessed, these included, but are not limited to, anxiety or nervousness, mental stress, rumination or worry, depression, sadness, or feeling blue [ 43 ].
Those considered better-educated were reported to have worsened mental health outcomes [ 36 ]. Those working in the field of “education and research” judged their telework experience to be much worse than participants working in other fields (e.g., ‘IT and telecommunication’, ‘Public administration and law enforcement agencies’, ‘Health and social services’ and ‘Legal and administrative services’) and were less willing to replicate the telework experience, there were also higher levels of stress and anxiety apparent [ 22 ].
Living and working in a home which is considered crowded or confined resulted in poorer mental health [ 33 , 36 ]. Having a larger house and living with a partner, or with one or two housemates, was also found to be protective of mental health [ 22 ].
Results are mixed in relation to working in a household that includes children. On one hand, having young children in the home was considered to have a negative link to wellbeing, supposedly related to increased demands [ 36 ]. Whereas other research reported having infants (less than two years old) or toddlers (two to five years of age) at home as protective of wellbeing but were also associated with more mental health issues [ 43 ]. These conflicting findings were reasoned to be due to working parents being able to spend more time at home with their children, resulting in better mental wellbeing. However, due to work-life strain caused by increased demands and lack of support (i.e., from babysitters) during working hours there is an increase in new physical and mental issues apparent [ 43 ].
Spending more time remote working was considered to increase perceptions of isolation, and isolation and psychological distress were reported to mutually affect each other over time [ 41 ]. Additionally, having frequent contacts with work colleagues was considered protective factors of mental health [ 22 ].
Workers who preferred to work from home experienced less psychological distress with increasing telecommuting frequency, while those who preferred not to telecommute experienced more psychological distress with increasing telecommuting frequency [ 34 ].
The association between working from home and mental health and wellbeing was found to differ depending on frequency and length of time home working [ 26 , 29 , 33 , 44 ].
One paper found working from home for a short duration was considered no different on mental well-being in comparison to those always working at the employer’s premises [ 26 ]. Niu et al., found that there was initially no difference in the mental health between workers who continued working in the office and those who switched to telework, but participants who teleworked for a longer period showed more severe anxiety and depression in comparison to those who teleworked for a short period. [ 33 ]. Similarly, those working from home for a high percentage of their weekly hours reported more negative psychological symptoms than employees who work from home for less hours [ 44 ], and higher ratings of stress were also reported in those working from home several times per week in comparison to those who worked from home less than once per month [ 29 ].
This following section details outcomes relating to productivity and synthesises the following outcomes from 14 papers: ‘productivity’[ 18 , 21 , 27 , 30 , 31 , 32 , 35 , 40 ], ‘performance’ [ 23 , 39 ], ‘percieved productivity’ [ 20 ], ‘level of work ability’ [ 44 ], ‘presenteeism’ [ 38 ]. Table 2 provides additional information on how these outcomes are measured.
The findings in relation to productivity varied across the retained papers. Some of the retained papers concluded a negative relationship between home working and productivity [ 19 , 30 , 32 , 40 ]. For example, Adisa (2021) found that the transition to home working from office-based work caused increased work intensification, online presenteeism and employment insecurity – which resulted in psychological strain and poor levels of work engagement [ 19 ]. Similarly, increased work intensity (e.g., receiving more information from teams and engaging in more planning activities) due to working from home also resulted in decreased worker productivity [ 30 ]. Morikawa et al., concludes that productivity whilst working from home was about 60–70% of the productivity at business premises, and was especially low for employees and firms that started homeworking after the onset of the COVID pandemic [ 32 ]. A UK-wide survey of office workers (including telecom, local government, financial services and civil service staff) who were working from home during the COVID-19 pandemic reported that since the onset of homeworking, 30% reported of workers that it is now more difficult to meet targets, and they had concerns of underperforming [ 39 ].
Some studies concluded that working from home was in fact no different in comparison to office working in terms of productivity [ 23 ]. This was reported for those who worked at home pre-COVID-19 and tended to practice working from home frequently [ 32 ]. Additionally, other research concluded that 90% of new teleworkers reported being at least as productive (i.e., accomplishing at least as much work per hour at home) as they were previously in their usual place of work [ 31 ].
Moretti et al., reported that working at home resulted in productivity decreasing in 39.2% and an increasing in 29.4% of participants [ 18 ]. However, Guler et al., established that participants who worked from home were more relaxed, more efficient, and they produced better quality work [ 27 ]. Despite reported increased or no change to levels of productivity, some research studies did find that those working from home were reporting longer working hours [ 21 , 27 ].
Two papers reported that males were less productive than females when working from home [ 20 , 21 ]. Those who are older and have higher levels of income are also more likely to be productive when homeworking [ 21 ], as were those who are unmarried with no children [ 31 ]. Those who are highly educated, high wage employees, long distance commuters, tended to exhibit a relatively small reduction in productivity [ 32 ]. Having an appropiate workspace was also associated with higher levels of productivity [ 21 ].
In terms of occupation, “scientists” were most likely to have the highest level of productivity, in comparison to “engineering and architecture,” “computer sciences and mathematics” and “healthcare and social services.” [ 21 ]. Other research also supported that those who work in in information and communications industry only displayed a relatively small reduction in productivity [ 32 ]. Higher levels of productivity in were also apparent in public administration (41%) as well as in health care and social assistance (45%). In contrast, the corresponding percentage was lower in goods-producing industries (31%) and educational services (25%) [ 31 ].
A few of the retained studies looked at the interaction between mental health and productivity whilst homeworking [ 21 , 27 , 35 ]. In a sample of staff that had been working from home for more than 6 months, it was reported that they were less stressed, more efficient, and had better quality of work during working from home period according to self-report data [ 27 ]. Other research reported that having an appropiate workspace, and better mental health was also associated with higher levels of productivity [ 21 ]. Stress was also found to lessen the positive association between working remotely on productivity and engagement [ 35 ].
This systematic literature review sought to 1) explore the association between working from home and both, mental health, and productivity, and 2) establish potential risk factors. Literature searches encompassed both peer previewed published literature and grey literature, 27 papers were retained post screening and included within this review. The results established that relationship between homeworking and both, mental health and productivity varies considerably, suggesting a complex association with many mediating and moderating factors.
Prior to the COVID-19 pandemic and the introduction of enforced and prolonged homeworking, working from home was often considered advantageous. Research often concluded that homeworking had multiple advantages [ 4 , 45 , 46 , 47 ]. There were also potential concerns reported with homeworking [ 45 , 48 ], for example in relation constant connectivity to the workplace [ 5 ], but these were not considered to outweigh the benefits [ 48 ]. This review revealed conflicting findings, with the majority of the research suggesting a negative or mixed link to mental health, which is supported by current literature [ 6 ].
This suggests that homeworking as a choice is considered largely beneficial (i.e., as shown by research prior to the pandemic), but when homeworking is instead mandatory there is potential that it may have a more negative association for certain individuals and occupations over others.
The relationship between working from home and productivity was also mixed, in that some papers found that home workers could be more productive, whereas others found the opposite. However, most studies reviewed show that homeworking for both new starters (e.g., has only worked from home) and those transitioning to homeworking for the first time, were particularly likely to report low levels of productivity along with concerns about meeting targets. There was also consistency amongst reviewed papers that homeworkers who reported better mental health (e.g., were less stressed) were more productive which is consistent with previous research showing an inverse relationship between stress levels and productivity [ 49 , 50 ]. Taken together, findings from the current review suggest that prolonged homeworking can negatively affect mental health, and in turn, lower levels of mental health can negatively affect productivity. Therefore, there should be a focus on maintaining and mitigating workers mental health when they are asked to work from home for a prolonged period.
Feelings of isolation or loneliness in homeworkers were also considered to have a consistent link to poorer mental health. This finding is well supported as the negative association isolation and loneliness have on mental health is widely reported across research (e.g., [ 51 , 52 ], and as demonstrated in an overview of systematic reviews [ 53 ]). The ability to create a shared sense of social identity with colleagues, which is protective of workplace stress [ 54 ] and burnout [ 55 ], may be hindered by homeworking [ 56 ] which can result in feelings of isolation or loneliness. This finding suggests that opportunities for social integration should be promoted by managers and team leaders. For example, through team meetings, in person events, or where possible, office working days.
As the findings relating to both mental health and productivity were varied, examination of factors which have potential to affect this relationship were explored. Personal and practical factors such as, being female, older in age, living and working in a crowded or confined home, or having young children at home were consistently associated with worsened mental health. Literature also concludes, being female, older in age, a highly educated high wage earner, being unmarried with no children, or someone with an active advantage towards homeworking (e.g., long distance commuters), and an appropiate workspace were associated with higher levels of productivity. These findings highlight the importance of considering practical factors that could be targeted by potential interventions (e.g., exploring how to manage work and having children at home, having an appropriately sized workspace, and managing overcrowded housing situations) as well as tailoring interventions to suit the target demographic (e.g., by considering gender, age, and occupation).
Limitations for the current review these can be split into retained paper limitations and review process limitations. In terms of retained paper limitations, quality screening established that the retained papers varied in quality. Many were cross-sectional (only four studies within the current review collected data from multiple time points), quantitative in methodology, and recruited participants using snowball or opportunistic sampling. This resulted in some unclear sample characteristics (e.g., not knowing where a percentage of participants were from), and uncertainty as to how often the sample were working from home. These elements limit the generalisability of the findings, and this should be considered when conclusions are drawn from this data.
For this review specifically there are a number of limitations to consider. Firstly, limiting the search to English only may have resulted in the exclusion of potentially relevant papers. Secondly, this review did not seek to collate findings from studies which only directly compared those who had to work from home during the pandemic vs. those who could not, or did not, work from home, which could have potentially provided clearer results. However, where papers provided comparisons (e.g., [ 25 , 36 ]) they were extracted and presented in the results. Thirdly, current literature has established that working throughout the pandemic can be negatively related to mental health [ 57 , 58 , 59 ], which makes it difficult to disentangle the impact of working from home specifically. However, in the current review, three papers indicated that homeworking has potential to be negatively linked to mental health when carried out, or continued, for a long period of time (in comparison to hybrid working or working from home for a short period). This could possibly be due to the previously reported benefits of homeworking (e.g., flexibility, eradicating commuting time, and work life balance) no longer feeling advantageous when constantly working from home. This is an area that requires more research and is discussed in more detail in the following section.
The current review found that working from home is neither positively or negative related to mental health or productivity, suggesting that a one size fits all approach to tackling the mitigation and management of workers mental health and productivity whilst they work from home is not suitable nor fit for purpose. However, there are indications that those who start homeworking for the first time during a pandemic are at risk of poor productivity, as are those who experience poor mental health. This suggests that employers should aim to help those who are new to home working, for example through training or mentoring programs. Additionally, those at risk of having poor mental health should be more closely monitored and provided with early support to ensure productivity.
The varied nature of the findings also calls for more in-depth research into why homeworking has such wide-ranging effect on individuals, and what factors have potential to mitigate and moderate this relationship. Due to the wide-ranging findings, it may be sensible to focus on specific occupational contexts and qualitatively explore barriers and facilitators to working from home to provide in depth rich data. Such work is currently underway as a PhD project focused on response organisations that worked from home during the COVID-19 pandemic conducted by the first author of the current review.
Considering the impact of working from home for different durations is also important, as the current review establishes that three papers indicated that homeworking has potential to be negatively associated with mental health when carried out, or continued, for a long period of time. Further empirical research is needed to provide more detail into, this finding along with examination into the factors that could impact this relationship (e.g., isolation, pre-existing mental health concerns). Resilience factors and characteristics associated with growth and flourishing whilst working from home should also be the subject of future research.
Methodologically, future research should seek to employ qualitative or mixed method designs to collect more in-depth and complete data in relation to the psychological effect of homeworking. Additionally, there should be a focus on using similar research measures when adding to the homeworking evidence base, as this would allow for research finding to be accurately compared. Similar suggestions were reported in a recent rapid review [ 60 ].
The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.
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Charlotte E. Hall, Samantha K. Brooks & Neil Greenberg
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CEH, DW, SKB and NG conceptualised the review, created aims and established inclusion criteria. CEH, LD and SKB conducted the database searches and all screening in accordance with the inclusion criteria. CEH conducted quality appraisal of included papers. CEH carried out the analysis, and CEH drafted the initial manuscript; all authors provided critical revision of intellectual content. All authors reviewed and approved the final manuscript.
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Supplemental Table 1. Search Strategy. Supplemental Information Table 2. Grey literature Searches.
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A study of Dutch twins has uncovered a slight association between higher intelligence and a reduced risk of psychopathology, primarily driven by common genetic factors. This means that the same genetic influences that contribute to higher intelligence also appear to protect against the development of certain mental health issues. Notably, the heritability of anxiety and negative affect—traits associated with mood disorders like depression—was found to be greatest in individuals with below-average intelligence. This study was published in the journal Behavior Genetics .
Intelligence, the ability to learn, understand, and apply knowledge to solve problems, encompasses various cognitive functions such as reasoning, memory, and decision-making. It manifests in many different areas of life and in many different forms. Intelligence is not limited to academic knowledge but also includes the capacity to adapt to new situations and environments across all domains of life.
Previous studies have consistently shown a negative association between intelligence and psychopathology. This means that individuals with lower intelligence scores are generally at a higher risk of developing various mental health issues, including anxiety, depression, and behavioral disorders. Despite this well-documented correlation, the reasons behind it remain a subject of ongoing research. Scientists have been particularly interested in understanding whether this relationship is driven by genetic factors, environmental influences, or a combination of both.
To explore this relationship further, study author Susanne Bruins and her colleagues examined the link between intelligence, as assessed by psychological tests, and five aspects of psychopathology in 7-year-old twins. The five aspects of psychopathology they focused on were: negative affect (including depressive symptoms and withdrawn behavior), anxiety (encompassing anxiety- and phobia-related symptoms), oppositional defiant disorder (which involves disobedient and defiant behavior), autism (referring to problems with communication, affect, and flexibility), and attention-deficit hyperactivity disorder (ADHD), which includes attention problems, hyperactivity, and impulsive behavior.
The researchers utilized data from the Young Netherlands Twin Register, a long-term study that recruits twins at birth and follows them throughout their lives. Parents of the twins regularly complete surveys about their children’s development and behavior. This register, which was initiated in 1986, provided the researchers with a valuable source of longitudinal data.
For this study, the researchers focused on a subgroup of 1,089 twins from the register, specifically those for whom both intelligence test scores and detailed psychopathology data were available. This subgroup included 543 complete twin pairs, with 262 pairs of monozygotic (identical) twins and 281 pairs of dizygotic (fraternal) twins. Monozygotic twins share 100% of their genetic material, while dizygotic twins share about 50%, similar to non-twin siblings. This difference in genetic similarity allowed the researchers to make inferences about the relative contributions of genetic and environmental factors to both intelligence and psychopathology.
The intelligence of the twins was measured using a range of age-appropriate IQ tests, including the Revised Amsterdam Child Intelligence Test, the Wechsler Adult Intelligence Scale (WAIS), and the Wechsler Intelligence Scale for Children (WISC), depending on the age of the child at the time of testing. Psychopathology was assessed using the Child Behavior Checklist (CBCL), a widely used tool that identifies symptoms of various mental health conditions in children. The CBCL is designed to be sensitive across a wide range of intellectual abilities, making it a suitable instrument for this study.
The study revealed that all five groups of psychopathology symptoms analyzed—negative affect, anxiety, oppositional defiant disorder, autism, and ADHD—were slightly less common in participants with higher intelligence. Although the association was statistically significant, it was very slight, indicating that intelligence alone is not a strong predictor of mental health outcomes.
One of the most interesting findings was that the association between intelligence and symptoms of anxiety, ADHD, and autism was primarily driven by common genetic factors. This suggests that the same genetic influences that contribute to higher intelligence also reduce the risk of developing these mental health issues. However, the relationship between intelligence and anxiety or oppositional defiant disorder did not appear to be driven solely by genetic factors, indicating that other environmental or developmental influences might be at play.
The study also found that the heritability of anxiety and negative affect varied depending on the level of intelligence. Specifically, the heritability of both anxiety and negative affect was highest in participants with below-average intelligence. This means that genetic factors contributing to these conditions are more pronounced in children with lower intelligence scores. In contrast, environmental factors appeared to play a more significant role in children with higher intelligence, particularly in the development of anxiety.
“We found that intelligence correlated negatively with negative affect, anxiety, ODD, ADHD, and autism. These correlations in part reflected common genetic effects, with genetic factors that increase intelligence decrease psychopathology. Genetic and environmental effects on negative affect and anxiety (respectively) were moderated by intelligence, such that the heritability of both anxiety and negative affect was greatest in children with lower IQ [intelligence quotient],” the study authors concluded.
The study sheds light on the factors behind the link between psychopathology and intelligence. However, it should be noted that the association between intelligence and psychopathology was very low, practically negligible, and that the study was conducted on a selected group of twins—those who had all the necessary data in the register. Given these very weak associations, it is possible that the findings might not be present if the study were conducted on a less selected sample of twins.
The paper, “ Are Genetic and Environmental Risk Factors for Psychopathology Amplified in Children with Below‑Average Intelligence? A Population‑Based Twin Study, ” was authored by Susanne Bruins, Elsje van Bergen, Maurits W. Masselink, Stefania A. Barzeva, Catharina A. Hartman, Roy Otten, Nanda N. J. Rommelse, Conor V. Dolan, and Dorret I. Boomsma.
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Stress is your body's response to a challenging or demanding situation. When you feel stressed, your body releases certain hormones. Your hormones are chemical signals your body uses to tell your body systems what to do. The hormones your body releases when you're stressed get you ready to meet the challenge or demand in your environment. During the stress response, your body gets ready to flee or fight by increasing your heart rate, breathing rate, and blood pressure.
Not all stress is bad. In small doses, stress can help you accomplish tasks or prevent you from getting hurt. For example, stress is what makes you slam on the brakes to avoid hitting a suddenly stopped car in front of you. That's a good thing.
But people handle stressful situations differently. What stresses you out may be of little concern to someone else.
Stress can be a short-term response to something that happens once or only a few times or a long-term response to something that keeps happening. Our bodies can usually handle short-term stress without long-term effects. But long-term or chronic stress can make you sick, both mentally and physically.
The first step to managing your stress is to know the symptoms. But recognizing stress symptoms may be harder than you think. Many of us are so used to feeling stressed that we may not know it until we get sick. Read on to learn more about the various symptoms you may have when you're stressed.
Difference between stress and distress
Stress is a normal reaction to challenges in your physical environment or in your perceptions of what's happening around you. Experts consider distress to be stress that is severe, prolonged, or both. Distress is when you feel you’re under more stress than you can handle.
Mental symptoms of emotional stress include:
Symptoms of stress that you might feel in your body include:
Respiratory distress
This is when you aren't getting enough oxygen or are having to work really hard to breathe. If you or a loved one has symptoms of respiratory distress, you need to call 911 and get to the ER as soon as possible. Signs include:
Symptoms of stress that affect your mental performance include:
Symptoms of behavioral stress include:
Chronic stress is when you experience stress over an extended time. This can have negative effects on your body and your mental state, and it can increase your risk of cardiovascular disease, anxiety, and depression.
In general, the symptoms of chronic stress are the same as those for shorter-term stress. You may not have all these symptoms, but if you have more than three symptoms and they last for a few weeks, you may have chronic stress. Potential symptoms to look for include:
You may be dealing with something more serious than day-to-day stress if you have symptoms over a period of time even though you've tried to cope using healthy mechanisms. Long-term stress is linked to number of mental health disorders, such as:
It may be time to visit your doctor if you're struggling to cope with the stress in your life or you have mental health problems from long-term stress. They can help you figure out ways of coping in a healthy way or refer you to a mental health professional who can help you.
Posttraumatic stress disorder (PTSD) is mental health condition that you may have after you have or witness a traumatic event, such as a natural disaster, accident, or violence. PTSD overwhelms your ability to cope with new stress. PTSD can lead to symptoms such as intrusive memories, avoidance behaviors, and hyperarousal.
These symptoms can cause significant problems in your work or relationships. T alk to your doctor or a mental health professional if you've had or witnessed a traumatic event and have disturbing thoughts and feelings about it for more than a month, if your thoughts and feelings are severe, or if you feel like you're having trouble getting your life back on track.
Ongoing, chronic stress can trigger or worsen many serious health problems, including:
Stress is a part of life. What matters most is how you handle it. The best thing you can do to prevent stress overload and the health consequences that come with it is to know your stress symptoms.
If you or a loved one is feeling overwhelmed by stress, talk to your doctor. Many symptoms of stress can also be signs of other health problems. Your doctor can evaluate your symptoms and rule out other conditions. If stress is to blame, your doctor can recommend a therapist or counselor to help you better handle your stress.
Stress is your body's response to a challenging or demanding situation. It can affect you physically, mentally, and behaviorally, especially when you have chronic stress. Chronic stress is when you are stressed for an extended time. Chronic stress can make it more likely for you to develop other mental health disorders, such as anxiety or depression. It can also affect your heart health and digestive health. If you're stressed and having trouble coping, it may be time for you to see your doctor or a mental health professional.
What can extreme stress cause?
Extreme stress, especially if it's prolonged, can cause emotional distress. And stress from a traumatic event, which is usually extreme, can cause posttraumatic stress disorder (PTSD). These are more serious cases of stress that overwhelm your ability to manage on your own. You may need to get a professional's help to get back on track. If you feel like you're having trouble managing your emotions, talk to your doctor. They can help you or direct you to someone who can help you.
Can stress make you throw up?
Yes, stress can make you throw up. Your digestive system is one of the many systems that stress can affect. In fact, you may have a whole range of other digestive symptoms, such as nausea, pain, and constipation or diarrhea. Not everyone has stress nausea or vomiting, but you may be more prone to it if you have a gastrointestinal condition, such as irritable bowel syndrome (IBS), or you have anxiety or depression.
You may be able to tell if you're stress vomiting if your episode passes when the stress goes away. If it doesn't, then your episode may be caused by something else. It's time to get checked out by your doctor if you have more than a couple of episodes or you can't figure out what's causing them.
Chu, B. Physiology, Stress Reaction , StatPearls Publishing, 2024.
American Psychological Association: "Stress effects on the body."
MedlinePlus: "Stress."
Mayo Clinic: "Stress management," "Emotional exhaustion: When your feelings feel overwhelming," "Post-traumatic stress disorder (PTSD)."
Cleveland Clinic: "Emotional Stress: Warning Signs, Management, When to Get Help," "Stress Nausea: Why It Happens and How To Deal. "
Johns Hopkins Medicine: "Signs of Respiratory Distress."
Helpguide.org: "Stress Symptoms, Signs, and Causes," "Understanding Stress."
Yale Medicine: "Chronic Stress."
Department of Health and Human Services: "Stress and Your Health."
American Institute of Stress: "Effects of Stress."
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Recent Student Voice data from Inside Higher Ed and Generation Lab finds two in five college students say stress or mental health is impacting their academics a great deal, and they want help from their institutions to take the pressure off.
By Ashley Mowreader
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College students say juggling their responsibilities outside of college in addition to their academics is one of their greatest stressors, according to recent Student Voice data.
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To be a college student in 2024 is to be surrounded by stressful events , ranging from personal matters—juggling work, family responsibilities and financial obligations—to unprecedented global phenomena, political turmoil and a constant stream of digital information.
“We’re living in an age of anxiety,” says Melissa Saunders, assistant director of clinical services at the University of North Carolina at Chapel Hill’s Counseling and Psychological Services (CAPS). “There are major life stressors going on all across the world— climate change , terrible wars , toxic political discourse —that students have no control over and are completely bombarded with all the time. That is an awful lot to handle at age 18, 19, 20.”
Laura Erickson-Schroth, chief medical officer for The Jed Foundation, works as a clinician with 18- to 25-year-olds, and when clients discuss their stressors, many times they talk about societal issues such as climate change , movements for racial justice , reproductive rights , protests on campus and anti-LGBTQ+ legislation .
“Young people are dealing with a completely different world than we were when we were younger … Young people are thinking about world events in a way that wasn’t true always in previous generations,” Erickson-Schroth explains.
The latest Student Voice survey from Inside Higher Ed , conducted by Generation Lab, found two in five (43 percent) of students say stress is impacting their ability to focus, learn and perform well academically “a great deal.” An additional 42 percent say stress is impacting them at least “some.”
The survey’s findings point to the changing nature of being a young adult, the needs of today’s increasingly diverse college students and how mental health and stress can impact learners in and outside the classroom.
Inside Higher Ed ’s annual Student Voice survey was fielded in May in partnership with Generation Lab and had 5,025 total student respondents.
The sample includes over 3,500 four-year students and 1,400 two-year students. Over one-third of respondents were post-traditional (attending a two-year institution or 25 or older in age), 16 percent are exclusively online learners, and 40 percent are first-generation students. Over half (52 percent) of respondents are white, 15 percent are Hispanic, 14 percent are Asian American or Pacific Islanders, 11 percent are Black, and 8 percent are another race (international student or two or more races).
The complete data set, with interactive visualizations, is available here . In addition to questions about health and wellness, the survey asked students about their academics , college experience and preparation for life after college.
Across all student respondents, fewer than half (42 percent) rate their mental health as excellent or good. Twenty-eight percent rate their mental health as fair or poor.
Mental health, as a term, has evolved from what was previously known as mental illness to be used more broadly to refer to mental and emotional discomfort due to the ordinary stressors of life, Saunders explains. This makes understanding a growing mental health crisis hard to define.
“We need to start using mental health in the appropriate context,” argues Doug Everhart, the University of California, Irvine’s director of well-being. “Because mental health, like physical health, is something we strive for. It’s something we want to enhance. When I talk about mental health, it’s about health promotion, right? How do we help students increase, enhance [and] improve their mental health through actions that they take?”
Students are more likely to rate their physical health (51 percent) or ability to care for themselves (56 percent) as good or excellent. Only half of respondents say they had good or excellent overall well-being.
Some demographic groups are more likely to rate their mental health as poor. That includes low-income learners (15 percent)—those with a household income of less than $50,000—as well as Black or African American students (12 percent), first-generation students (11 percent), and online learners (11 percent). Among nonbinary students—who made up around 100 of the 5,000 respondents—26 percent rate their mental health as poor, 14 percent say their physical health is poor and 22 percent rate their stress management abilities as poor.
Adult learners, inversely, have higher ratings for their health and wellness across categories compared to their traditional-aged peers, with almost half rating their mental health and physical health as good or excellent. Two-year students of any age are also more likely to rate their ability to care for themselves as excellent (26 percent) or good (38 percent).
Across groups, 41 percent of students say they have good or excellent stress management skills, while 27 percent rate their stress management as poor or fair.
As one first-year student shared in the survey, “One could have two out of the three: good social, academic or physical health but not three from the level of meaningless work assigned. I typically prioritize good academics and social [life] to keep my head above water and [find] motivation through friends.”
When asked what their top stressors are while in college, Student Voice respondents rank balancing their academics with personal, family or financial responsibilities as the most stressful (47 percent). This was most true for adult learners (60 percent), students at two-year institutions (54 percent) and first-generation students (53 percent).
These results weren’t surprising to Trace Terrell, a current undergraduate student at Johns Hopkins University.
“I have had so many friends and so many of my peers be in situations where they just felt so overwhelmed by everything that they have on their plate,” says Terrell, who also served as a policy intern for Active Minds. “It makes a lot of sense.”
As student demographics have grown more diverse, their needs and characteristics have changed, with more students working part- or full-time jobs, acting as caregivers , or balancing severe health conditions, which in turn impacts their college experiences.
“Students, they bring their academic lives into their dorm rooms or into their clubs, and back home when they visit home. And then, vice versa, they bring their homes with them and their family,” says James Raper, vice president for health, well-being, access and prevention at Emory University.
Experts who reviewed Student Voice findings commented on how college affordability and the rising cost of living can directly relate to student mental health , as well. One-third of survey respondents name paying for college as a top stressor, and an additional 26 percent say paying for personal expenses is a high source of stress.
“We [CAPS] see big gaps between students that don’t have to work to pay for help pay for their college or their spending money, and those that do,” says Saunders of UNC. “I think the stress levels are much higher on those that are juggling outside jobs, or even work-study jobs , that eat up a significant amount of time, than they are on the students who had the good fortune not to have to work. That seems to have gotten worse as the country has had a bigger economic divide.”
Fewer than one-third of students say acute academic stress (32 percent), job or internship searches (30 percent), or chronic academic stress (22 percent) are their greatest stressors.
Institution type and student age reveal differing pressures. Students at private universities, for example, are more likely to point to job and internship searches (50 percent) as a stressor, followed by academic stress (43 percent) before their competing responsibilities.
Emory’s Raper says this could be due to the privileges afforded to many private school students who don’t have to pay for college on their own, but it could also point to students who need jobs to help support their lives during college. “That data may reflect that some students are stressed out because they can’t think about internships, they don’t feel like they have access to them, because they don’t have enough time to do both.”
Students at public institutions (36 percent) or who are taking classes exclusively online (37 percent) are more likely to indicate paying for college is a stressor.
Around one in 10 students say being on their own and caring for themselves is a top stressor, which mirrors the 13 percent of students who rate their ability to care for themselves as poor or fair.
In terms of chronic stress specifically, 41 percent of nonbinary students say this type of personal stress impacts them, compared to 18 percent of all respondents.
Choosing a major or course planning was a top stressor for about 10 percent of all students, but that number grows to 17 percent among learners at two-year institutions.
In the “other” category, which made up 2 percent of responses, three students wrote “all of the above,” and one indicated “everything” is stressing them out.
Just as the pressures that impact students’ mental well-being are complicated, identifying how to alleviate students’ stress is just as complicated.
“It’s not necessarily about the world becoming easier for me to navigate, but 'What kind of skills do I need?' and 'What kind of work do I need to put in to make the world seem easier?'” says Everhart of UCI.
When asked which three of 11 institutional actions would most benefit their overall well-being, students overwhelmingly believe that institutions rethinking high-stakes exams would be most helpful (48 percent). The second-largest number of students identified adding mental health days to the academic calendar (37 percent), followed by encouraging faculty members to build in flexibility with course deadlines (35 percent).
The results highlighted to Raper that students are looking for areas to exercise autonomy over their schedules and assessment, he says. “We experience things that are in our control and out of our control, and to be an 18- or 20-year-old in 2024, there’s a lot that we’re aware of that is just happening to us. And so, rightly so, we’re getting better and better at looking at, ‘Well, where could I leverage some control?’”
College students also value food services as a health priority. Twenty percent of students believe their institutions making campus meal plans or food prices more affordable would positively impact their well-being (this was especially true for students at four-year institutions), and 14 percent say improved quality, variety and access to campus food services would make a difference in their health.
Private school students identified more wellness facilities and services (23 percent) and improved quality of food services (22 percent) as helpful actions for improving campus health, compared to the average student respondent (19 percent naming more health and wellness and 15 percent naming better food services).
One in five students would like institutions to encourage faculty members to build student mental health day policies into their syllabi or for additional investment in wellness facilities or services to promote overall wellness. When asked how students rank the quality of their current campus health and wellness services, the largest share of students (37 percent) rank their campus at average, while 44 percent say it is good or excellent.
Across the country, institutions have begun to integrate excused absences for mental health and mental health days into the academic calendar, which each serve a different purpose, explains Active Minds’ Terrell.
An excused absence allows a young person to take, for any mental health–related reason, a day off and not be expected to make up activities.
General mental health days emphasize that everyone has mental health, “and so we should all have a break to be able to care for that,” Terrell says. Similar to the excused absence, the intention behind a day off is that students can take a step back from their academic responsibilities.
Historically, mental health days in higher education have been more reactive and, in turn, have become a catch-up day for students to work, Emory’s Raper says. Instead, mental health days should be a time for students to practice wellness in an intentional way.
Some institutions, in their faculty manuals, prohibit or highly discourage instructors from assigning any instruction, exams, essays or projects that could extend into the break period, “to really allow young people to take time for themselves,” Terrell adds.
UNC introduced institutionwide mental health breaks in fall 2020 to give students a pause from classes to focus on their health and wellness and added them as a permanent feature in 2021.
Now, the academic term starts one week earlier, with five mental health days spread throughout the year. The breaks fall at the start or end of the workweek, giving students longer weekends to unplug, Saunders says. “They’re not using it to stay here and study or catch up on their academic work; they’re mostly going home or going out of town or doing something that gets them away from the stress, which I think has been really helpful.”
Eighteen percent of Student Voice respondents say increasing the length of school breaks would support their well-being.
Rethinking exam schedules is not a policy solution Active Minds advocates for but is “something that makes a lot of sense,” Terrell says. “When we talk about common-sense solutions to the mental health crisis on college and university campuses, one of the easiest ways is just to reimagine how we are actually giving instruction and formatting tests.”
Alexa Silverman, EAB’s senior director of student experience and well-being research, says institution-level considerations around finals and their impact on student wellness has conversation that’s been slow to build, mostly because it will require an entire college or university to change.
Rather than placing all the burden on faculty members to decrease students’ exam stress, Silverman believes more frequent opportunities for self-assessment or incremental assessment can help students feel confident in their learning and prepared for testing.
Similarly, when students ask for flexibility with deadlines , Silverman wonders, is that the only thing students know how to ask for? “If we don’t show students the whole range of tools and resources we have to support them, then that’s where they’ll go.”
This is another opportunity for faculty members to create earlier and more frequent opportunities for students to evaluate their progress, such as intermediate check-ins before a large research paper is due, to limit the amount of last-minute work students are completing. Similarly, long tests can be divided into more regular quizzes to help students benchmark progress throughout the term rather than one heavily weighed assignment.
“We want to shift the conversation from ‘ Can we be flexible about this ?’ to ‘How can we create check marks to make sure that students don’t fall behind?’” Silverman says.
Professors can also prioritize student wellness with deadlines in practical ways. “Let’s stop the practice of having due dates at midnight ," Raper says. "It helps with sleep, it reinforces that we’re being very intentional—that’s a very easy change."
While such actions are individual solutions colleges and universities can evaluate, Raper sees a greater thread for administrators to reprioritize systems and organization to focus on student wellness, rather than responding at each concern.
“If we do not get organized, all we’re going to do is what we’ve been doing for the last 10 years; we just react and fund a lot of downstream things,” Raper says. “Which is not bad, it’s just not the only thing you can do, and [you] can’t expect things are going to change in terms of moving the needle around student well-being if we don’t move upstream.”
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In 2009, only about half of teens said they used social media every day. By 2022, 95% of teens said they used some social media — and about a third say they use it constantly, a poll from Pew Research Center found . Daniel de la Hoz/Getty Images hide caption
In 2009, only about half of teens said they used social media every day. By 2022, 95% of teens said they used some social media — and about a third say they use it constantly, a poll from Pew Research Center found .
Rates of depression and anxiety have risen among teens over the last decade. Amid this ongoing mental health crisis, the American Psychological Association issued guidelines for parents to increase protection for teens online last year.
In this encore episode, NPR science correspondent Michaeleen Doucleff looks into the data on how that change has impacted the mental health of teenagers. In her reporting, she found that the seismic shift of smartphones and social media has re-defined how teens socialize, communicate and even sleep.
In 2009, about half of teens said they were using social media daily, reported psychologist Jean Twenge . And by 2022 , 95% of teens said they used some social media, and about a third said they use it constantly.
We want to hear the science questions that keep you up at night. Send us an email at [email protected] .
Listen to Short Wave on Spotify and Apple Podcasts .
This episode was produced by Jane Greenhalgh with Liz Metzger. It was edited by Jane Greenhalgh and our managing producer, Rebecca Ramirez. Michaeleen Doucleff checked the facts. Our audio engineers were Neisha Heinis and Hans Copeland.
Strategies for managing financial stress, how many americans suffer from financial stress, what is money dysmorphia, what is chrometophobia, the bottom line.
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Financial stress is a reality for many people, but when it goes unchecked, it can become an underlying cause of mental and physical health issues. For young adults, developing a healthy relationship with money and mastering personal finance concepts can help them avoid financial strain and improve their overall well-being.
Through education and personal effort, financial well-being is attainable, and it’s not about earning a huge salary or owning expensive things. Rather, it's about taking control over your everyday finances, putting protections in place so you have financial security, and working toward larger financial goals while you enjoy life.
If you recently graduated from college or are just starting your career, here's what you should know about how money impacts your mental health and strategies you can implement to help achieve financial well-being.
What is financial stress.
Financial stress is feelings of worry and anxiety related to money. It could be day-to-day concerns like not having enough money to cover basic needs, or a general sense of not being able to manage debt or achieve personal goals like buying a home or affording a car because of fund shortages.
For young adults who are early in their careers and perhaps facing down major financial responsibilities for the first time, financial stress can be overwhelming.
“Money is one of the biggest stressors in life,” says Carolyn McClanahan , M.D., CFP, founder of Life Planning Partners. “And when you're stressed over anything, that creates physical issues within your body, like those stress hormones that make you not sleep or bring down your sense of well being overall.”
People may have different types of financial stress depending on their life stage. So while someone in their 50s might be concerned about not being able to retire, people in their 20s are more likely thinking about the here and now, says McClanahan. “How do you meet daily expenses without going into credit card debt ? It's day-to-day things that they think about and because we do such a bad job of teaching financial literacy, many younger people just don't know how to handle it,” says McClanahan.
Navigating young adult life can be challenging regardless of financial stability since there are so many major changes in a relatively short period of time, agrees Curtis Pope , CFP CFT-I, founder of Pope Wealth Planning.
“There are a lot of unknowns. This stage of life can mean new living situations, new cities, a new job, full independence for the first time in many cases, etc.,” he says. “If personal finances feel unstable during this time, it's another layer of new challenges during an already tricky time of navigation.”
On top of that, a good portion of young adults are also grappling with student loan bills . According to The College Board’s Trends in College Pricing 2023 report, more than half (51%) of 2021-22 bachelor’s degree recipients graduated with debt, and the average debt among borrowers was $29,400.
According to a Harvard study, more than half (56%) of young adults ages 18-25 report that financial worries negatively influence their mental health. “How we take care of our physical and mental health all goes together. And if we're having basic things like money stress or poor relationship issues, then that can start a cascade of poor mental health and physical health,” says McClanahan.
As a financial therapist , Pope shared a list of some of the most common effects that he’s seen result from financial stress:
Anxiety and depression: Constant worrying about finances can manifest into increased feelings of anxiety and depression, affecting overall mental well-being.
Sleep disturbance and insomnia: Ever lie awake at night doing calculations in your head to try to figure out how you’ll pay for new brakes for your car, or if you can afford a quick road trip with friends? In a study by the American Academy of Sleep Medicine, 87% of people cited finances as a worry that has caused them to lose sleep; one-fifth of those respondents said they “almost or almost always” lost sleep worrying about money.
Physical health problems : Long term chronic stress can manifest into physical health issues such as headaches, digestive problems, and a weakened immune system. The American Psychological Association points out that stress can actually impact every body system, causing long-term problems for your heart, gut health, nervous system, and more.
Relationship strain: Among Gen Z, 29% of people say money is their greatest relationship challenge. And that’s no surprise given the pressure that financial strain can put on relationships with partners, friends, and family. It could be from disagreements over money or lifestyle choices, but also, money worries can cause people to feel irritable and lash out at others.
Reduced work performance : Financial stress can lead to decreased productivity and focus at work, affecting overall job performance. In fact, nearly 3 in 4 employees (71%) say that financial stress negatively affects both their work and personal lives, according to a study conducted by Morgan Stanley at Work.
Avoiding social interactions : People under financial stress may withdraw from social activities due to lack of funds or embarrassment. One study found 72% of respondents skipped events with family, friends, and co-workers because they couldn't afford to attend.
Negative impact on self-esteem: Because money is so tied to value and worth, financial difficulties can lead to some people feeling like they are failures, impacting self-confidence.
For anyone dealing with financial stress , the good news is that turning things around is within your power. “It's all about learning the tools of how to take care of yourself financially,” says McClanahan. This includes learning budgeting, saving, and understanding basic financial concepts like how your 401(k) works, understanding how to use your health insurance, etc.
“All those concepts are building blocks to maintaining good financial health so that you can hopefully reduce the effects of money on your mental health,” adds McClanahan.
Here’s a step-by-step plan for coping with financial stress and healing your relationship with money:
Before you can get into budgeting or creating savings goals, you should do a deep dive into your finances to see where you stand.
“I'm not talking about monitoring your avocado toast intake,” says Pope. “Either create a spreadsheet or simply write down the numbers.” To get the figures you need, ask yourself these questions, and analyze your bills and banking and credit card statements to find the answers:
This exercise could be eye-opening if you have never stopped to look at where your money was going.
Once you have your numbers, you can get to work on your actual budget .
“If there's $1,000 left at the end of each month, you'll want to set aside a certain dollar amount for savings and then spend the remainder on lifestyle,” says Pope. By lifestyle, he means the flexible spending that you do each day such as groceries, carry out, shopping, entertainment, etc.
If you find yourself without enough of a leftover cushion to live, then you’ll need to go back to your bills to do some trimming, or look for ways to increase your income.
For example, you might realize that there are streaming services you really don’t use but still pay for, or you might be able to carpool with friends to save on tolls/parking costs. You might also need to set some restrictions on spending when it comes to eating out or buying new clothes.
Consider using apps to track your spending moving forward to keep yourself accountable and stick to your budget.
Did you notice that Pope suggested that savings is the first item that you should take care of with your leftover funds? There’s an important reason why. “Having an emergency fund will provide a lot more peace of mind,” he says, and therefore, reduce your overall financial stress.
Start off by automating a set deposit amount into a separate account with every paycheck. Contribute what you can, adjusting as needed based on the budget your created and your income over time. Ultimately, you want to grow your account so that you have enough to cover at least three months worth of your fixed bills, says Pope.
A high-yield savings account is a good choice for an emergency fund since it will help you earn interest on top of what you save.
Though it can take some time to fully fund your emergency savings, even knowing you have a few hundred dollars set aside in the meantime to cover an unexpected expense—rather than having to rely on borrowing—can be empowering and offer some peace of mind.
In most cases, people work a steady job and over time as they gain experience, their income increases. But if you can also find a way to introduce extra income streams, you may be able to fast track your financial goals and give yourself some budget wiggle room.
For example, you might be able to take on some freelance or gig work in your spare time. Or, if you are good at something like swimming or playing an instrument, see if there is an opportunity to teach lessons on that skill.
People tend to stress more when something is unknown or unclear to them, and that can certainly be true when it comes to financial matters. But once you gain knowledge and demystify things that once seemed so complicated, you can feel less intimidated.
Here are some of Pope’s and McClanahan’s financial literacy resource recommendations:
Self-education:
Depending on your money goals and current situation, there could be times when you may need to reach out to a professional for some guidance. Here are a few financial service providers to consider:
Financial therapists : “Financial therapists live and work in the overlapping Venn diagram between traditional financial planning and conventional (mental health) therapists,” says Pope. Financial therapy goes deeper into the psychology of money, helping you to think critically about your finances and begin to take positive action toward your goals.
Certified Financial Planner : A professional can help you with your long-term financial planning and investing goals. Starting to plan and save for retirement while you're young can help you reap the benefits of compound interest.
Credit counselor : If you find yourself struggling with debt or trouble creating a budget, you can seek help from a non-profit credit counseling agency like the National Foundation for Credit Counseling (NFCC) . You can typically get a free consultation, but then services may have a low cost fee thereafter.
Certified Public Accountant (CPA) : If your finances are fairly simple, you may not need an accountant just yet. However, it can be a good idea if you decide to start your own small business or do a lot of freelance work since a CPA can help guide you from a tax savings perspective.
Though research varies, a large majority of Americans do feel financial stress from time to time. A 2024 survey by Thrive Global found 9 out of 10 people saying that money has an impact on their stress levels.
Money dysmorphia is a flawed perception of finances, or feeling insecure about one’s financial status regardless of one’s financial reality. This distorted view can cause people to make unwise financial decisions, such as feeling like you’re not rich enough to invest money for your future.
Chrometophobia is an irrational fear of spending money that goes beyond just being frugal. Serious cases could lead to someone avoiding any situation where they would have to pay for something, even for important things like healthcare.
Financial well-being is an important component for your overall mental health. By taking the steps to address your financial situation, you can take charge of your money and make it work for you – rather than just working to pay your bills. Once you flip the script, you can stress less about money matters and improve your financial mindset.
The College Board. " Trends in College Pricing and Student Aid 2023 ." Page 4.
Harvard Graduate School of Education. " On Edge: Understanding and Preventing Young Adults’ Mental Health Challenges ." Page 6.
American Academy of Sleep Medicine. " Financial and Health-Related Worries Keeping Americans Up at Night, Survey Shows ."
American Psychological Association. " Stress Effects on the Body ."
Fidelity. " 2024 Couples & Money Study ." Page 2.
Morgan Stanley at Work. " State of the Workplace II ." Page 22.
Brightplan. " 2023 Wellness Barometer Survey ." Page 10.
Financial Industry Regulatory Authority. " Start an Emergency Fund ."
National Foundation for Credit Counseling. " What Do NFCC Members Charge for Counseling Services? "
Thriving Wallet. " 2020 Research Insights Report/White Paper ." Page 7.
CPD Online College Limited. " What is Chrometophobia? "
Article updated on August 7, 2024 at 6:30 AM PDT
Mental health apps are the perfect supplement to your wellness journey. The best one can help boost your mood, lower anxiety and more.
CNET’s expert staff reviews and rates dozens of new products and services each month, building on more than a quarter century of expertise.
What to consider
Mental health apps vary by feature, from meditation to guided sleep sessions to online therapy. Determining your goal will help you narrow down your top choice.
App credentials
Depending on your goal, you may need an app with licensed therapists or clinical research backing it up.
Many of the best mental health apps operate on a subscription model. Establishing your budget will help you narrow down your options.
User reviews
Reading app reviews before you download will give you a better idea of what the app does well and any potential pain points.
It’s always best to seek professional help when you’re struggling with your mental health. However, there are supplemental apps that can be a big help in stress reduction, anxiety management, mood elevation and more. Research has shown that some of the best mental health apps out there can be a great way to improve your well-being and record the progress you make on your mental health journey.
There's a lot to love about mental health apps: the variety, the affordability and the features. They also bring mental health resources to people who otherwise couldn't get help due to finances, disabilities or location. While they're not a one-size-fits-all, they can provide general mental health support. Just note that not all mental health apps are backed by research or clinical insights. With between 10,000 and 20,000 wellness apps out there, it can be difficult to find the best option. That's why we did the research for you. Below, you'll find my picks for the best mental health apps you can start using today to elevate your happiness.
Read more: Best Online Therapy Services
Talkspace takes our top spot for the best therapy mental health app because of its 24/7 access to medical professionals. It's an affordable online therapy option that gives you more than just helpful guides and videos to watch. You have access to a licensed therapist wherever and whenever you need them. Talkspace is a great option for someone who is not comfortable going into an office or would rather have therapy appointments online .
A 2020 study found that messaging a therapist through Talkspace reduced feelings of anxiety and depression . A different study said that using Talkspace's voice, video and text features also reduced symptoms of post-traumatic stress disorder , or PTSD. Note that the researchers of the studies had connections to Talkspace.
Within this mental health app, you have access to video, text and audio chat to communicate with your therapist. However, users note there is a 5-minute cap on audio messages. Talkspace is significantly more expensive than other mental health apps on the list. However, if you're looking for an app that allows you to talk to a therapist directly, it may be worth the price.
Calm is one of the most well-known mental health apps in the wellness space, with over 100 million downloads . We consider Calm one of the best meditation apps because of its comprehensive offerings, including breathing techniques and calming exercises.
The Calm app is pretty easy to navigate and organized well. When you open the app, you are prompted to take a few deep breaths. Then you select what your main goals are so that your recommendations are tailored to your needs. You also can track statistics within the app, such as how long you have been using the app or how many sessions you've completed.
The free version of Calm is limited, but there is a 7-day trial that helps you decide if it's right for you. After the trial, you have to pay the premium to access the 100 guided meditations, sleep library and masterclasses, which is $14.99/month or $69.99/year. If you are ready to commit to Calm, it's good to go with the full-year option since it comes out to just under $6/month instead of the full $15. Or you can always stay with the limited free version.
The Moodfit app has a lot to offer, and you can choose how to use this best mental health app. You can track sleep, nutrition, exercise and more during your wellness journey. Moodfit uses tools and sessions that help you assess your feelings, recognize negative thinking and change it.
The Moodfit app has pretty standard navigation. The "notices" tab at the bottom is what I would consider the educational section. There is a lot of good information available, like how your thoughts influence your behavior and feelings, but you will have to take the time to actually read it. Other mental health apps have a more interactive experience with imagery, videos and readouts.
Where I think Moodfit really shines is its analytics. With the easy-to-interpret charts, you can spot patterns in your mood and your activities. You also can track your mood down to the hour -- analytic views available are monthly, weekly, daily and hourly. Many apps do have analytics, but Moodfit puts a lot of intention behind helping you find patterns in your behavior and moods.
Moodfit's home page features your progress and goals.
Sanvello is the best mental health app for stress relief thanks to its full meditation library , guided journeys, health tracking and cognitive behavioral therapy tools. I was pleasantly surprised when using Sanvello . For me, it was a lesser-known option on the list, and it did not disappoint. You can choose what goals you want to target — reduce anxiety , feel happier, build confidence, etc. — and you can select as many goals as you want.
One of my favorite parts of the Sanvello app was how connected it felt when using it. Like other mental health apps, there is an education section. What's different is how it is presented. Sanvello uses text, videos and audio for a multimedia experience that is much easier to follow and digest. This comes down to preference, as some people prefer to read at their cadence.
The basic version of Sanvello is free. However, there are additional features that the app offers — like coaching and guided journeys — that are not available on the free version. There is a premium option of $8.99/month and a premium plus coaching option for $50/month which offers a coach with live connection capabilities.
The Sanvello app allows you to select which goals you want to target.
Happify is a free mental health app that focuses entirely on your mood and helps relieve anxiety. Developed by mental health professionals, Happify's strategies are derived from cognitive behavioral therapy that helps you learn how to recognize and reorient negative thinking.
Happify had the most thorough questionnaire when signing up. I was asked about relationships, employment and medical conditions to help personalize the service. As the name suggests, Happify focuses on positivity and tries to make your journey fun with engaging games. With the relaxation and mindfulness techniques Happify offers, you can boost your mood and relieve anxiety.
The app has a different navigation setup than other apps. Instead of having the navigation bar at the bottom, there's a three-bar dropdown you have to tap to bring up the menu at the top left, making it just a little more difficult to find things.
Various tracks are available from Happify.
MindShift is a free mental health app specifically designed to target anxiety. Categories within the app are broken down into general worry, social anxiety, perfectionism, panic and phobias. This allows the user to personalize which type of anxiety they want to work through.
As the name suggests, MindShift targets your mindset, meaning that it helps you identify what is making you anxious and helps you redirect your thinking to positivity. When you open the app, you're prompted to rate your daily anxiety score to track over time. The app is pretty easy to use and easier to navigate than other options simply because there is less available. One tool that stood out was the "thought journal" that helps you work through what you're worried about and how to overcome negative thoughts. "Coping cards" are also available to help you ease anxiety in the moment .
MindShift is much more interactive than other apps, as it relies on you to add anxiety scores and type responses to get the best experience. Other apps are mainly reading-based. If you want the best out of MindShift, you need to interact with the app.
The unique experiences of people of color are often excluded from traditional mental health resources. The wellness app industry is traditionally not inclusive and mainly focuses on experiences that white people encounter. Only one in three Black Americans get the mental health care they need. That's why Shine is the pick for the best mental health app for people of color.
It's specially designed to target the needs and struggles of people of color, making mental health resources more accessible and inclusive. Shine offers meditations, self-care courses led by experts and monthly virtual workshops. You are also prompted to add a wellness check-in each day and are greeted with motivational messages.
Selection of choices for Shine app.
If you’re looking for an app you can use daily to boost your wellness passively, you’ll like Soaak. Soaak is a clinically proven sound therapy app that offers frequency compositions for things like stress relief, mental clarity, better sleep, focus and mood boost. Sound therapy may seem hard to believe, but there is research behind sound stimulation . For example, a 2020 review found that sound therapy can disrupt agitated brain waves and move them into calmer waves.
The Soaak app is easy to use, and I enjoyed how I could turn it on while doing other things. My favorite compositions to use were Energy, Sleep Well and Focus. You can listen to the sound frequencies in three forms: original, nature or music. If you’re new to sound frequency, I recommend first trying the nature or music versions. For example, the energy/high vibration frequency has rain sounds over the sound compositions.
You can use the Soaak app by playing the sound frequencies or dive deeper into what the app offers with 21-day programs or custom wellness plans. However, the personalized wellness services are significantly more expensive, starting at $750.
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For older students, Kang says, homework benefits plateau at about two hours per night. "Most students, especially at these high achieving schools, they're doing a minimum of three hours, and it's ...
Emmy Kang, mental health counselor at Humantold, says studies have shown heavy workloads can be "detrimental" for students and cause a "big impact on their mental, physical and emotional health ...
Pope and her colleagues found that too much homework can diminish its effectiveness and even be counterproductive. They cite prior research indicating that homework benefits plateau at about two hours per night, and that 90 minutes to two and a half hours is optimal for high school. • Greater stress: 56 percent of the students considered ...
Beyond that point, kids don't absorb much useful information, Cooper says. In fact, too much homework can do more harm than good. Researchers have cited drawbacks, including boredom and burnout toward academic material, less time for family and extracurricular activities, lack of sleep and increased stress.
Less than 1 percent of the students said homework was not a stressor. The researchers asked students whether they experienced physical symptoms of stress, such as headaches, exhaustion, sleep ...
In this comprehensive guide, we will delve into the research surrounding homework and its effects on students' stress levels and mental health. We will explore the link between homework and stress, examine the impact of excessive homework on students' well-being, and, for those seeking relief, offer practical strategies to manage homework ...
ADHD, autism spectrum disorder, social anxiety, generalized anxiety, panic disorder, depression, dysregulation, and a range of other neurodevelopmental and mental health challenges cause numerous ...
Keywords: homework, stress, mental health The outcomes of adolescent mental health is a threat to students' health and wellbeing, more so than it ever has been in the modern era. As of 2019, the CDC reported a nearly 40. percent increase in feelings of sadness or hopelessness over the last ten years, and similar.
Homework as a Mental Health Concern. It's time for an in depth discussion about homework as a major concern for those pursuing mental health in schools. So many problems between kids and their families, the home and school, and students and teachers arise from conflicts over homework. The topic is a long standing concern for mental health ...
Introduction. Homework, or between-session practice of skills learned during therapy, is one of the most integral, yet underutilized components of high-quality, evidence-based mental health care (Kazantzis & Deane, 1999).Homework activities (e.g., self-monitoring, relaxation, exposure, parent behavior management) are assigned by providers in-session and completed by patients between sessions ...
Lack of sleep. One of the most prevalent adverse effects of schoolwork is lack of sleep. The average student only gets about 5 hours of sleep per night since they stay up late to complete their homework, even though the body needs at least 7 hours of sleep every day. Lack of sleep has an impact on both mental and physical health.
There is a non-linear relationship between homework time and adolescent mental health. Homework negatively impacts adolescent mental health, but only when exceeding about 1 h and 15 min. Teacher support, particularly emotional support, can mitigate the adverse mental health effects of excessive homework time. Abstract.
While we have shown a link between time spent on homework/studying and depression symptoms, the potential clinical implications are unclear. Additional studies are needed to evaluate the relative impact of homework/studying on sleep habits and mental health in pediatric populations with depression or anxiety.
A 2013 study conducted at Stanford University found that students in top-performing school districts who spend too much time on homework experience more stress, physical health problems, a lack of balance in their lives and alienation from society.
Homework's Potential Impact on Mental Health and Well-being. Homework-induced stress on students can involve both psychological and physiological side effects. 1. Potential Psychological Effects of Homework-Induced Stress: • Anxiety: The pressure to perform well academically and meet homework expectations can lead to heightened levels of ...
The purpose of this study is to assess whether mental health factors in a sample of secondary school students across Canada are associated with course grades and education behaviors: truancy, days missed due to health issues, and incomplete homework frequency, and secondly, whether the associations between mental health outcomes and course ...
Conclusion. In conclusion, it is clear that the amount of homework assigned to students can have a significant impact on their mental health. Too much homework can lead to increased stress levels, anxiety, depression, and decreased self-esteem. It is therefore important to ensure that students are not overloaded with homework and are given the ...
Methods A sample of 11,501 homeworkers was drawn from the sixth wave of the European Working Condition Survey data set. Results Unlike the expected, the higher the workload, the higher the mental well-being of employees. However, as expected, high workload was correlated with lower well-being when indirect effects through work-family conflict, sleep problems, and work engagement were ...
* Reductions in health: In their open-ended answers, many students said their homework load led to sleep deprivation and other health problems. The researchers asked students whether they ...
University of Southern California research shared exclusively with AP found strong relationships between absenteeism and poor mental health. For example, in the USC study, almost a quarter of chronically absent kids had high levels of emotional or behavioral problems, according to a parent questionnaire, compared with just 7% of kids with good ...
Inpatient hospital admissions of children and adolescents for mental health reasons increased substantially across Canada between ... print media, homework, religious services, working at a paid job) correlated positively with ... Although population-based studies suggest a link between social media use and mental distress among youth, the ...
The literature exploring differences in mental health outcomes between workers in public-facing occupations and those working from home in Canada has been sparse [13,27]. One study conducted in the first half of 2020 measured anxiety and depression symptoms through Generalized Anxiety Disorder 2-item (GAD-2) and Patient Health Questionaire-2 ...
For example, a rapid review conducted by Oakman (2020), contained 23 studies published between 2008 and 2020, explored the link between working from home and mental and physical health. For mental health specifically, the relationship was reported to be complex with many conflicting findings (e.g., increased stress and increased well-being; ).
A study of Dutch twins has uncovered a slight association between higher intelligence and a reduced risk of psychopathology, primarily driven by common genetic factors. This means that the same genetic influences that contribute to higher intelligence also appear to protect against the development of certain mental health issues.
Mental health problems, such as depression, anxiety, and personality disorders; Cardiovascular disease, including heart disease, high blood pressure, abnormal heart rhythms, heart attacks, and ...
Recent Student Voice data from Inside Higher Ed and Generation Lab finds two in five college students say stress or mental health is impacting their academics a great deal, and they want help from their institutions to take the pressure off. To be a college student in 2024 is to be surrounded by stressful events, ranging from personal matters—juggling work, family responsibilities and ...
Here are some benefits that will help you kindle the link between nature and mental health: #1 Reduction in stress level. Nature is the best stress reliever, empowering us to be rejuvenated ...
Troubling ties between teens, social media and mental health : ... RSS link; Why we need to talk about teens, social media and mental health. August 5, 2024 3:00 AM ET. By .
Effects of Financial Stress on Your Health . According to a Harvard study, more than half (56%) of young adults ages 18-25 report that financial worries negatively influence their mental health.
For those facing mental and/or substance use disorders, you can contact the Substance Abuse and Mental Health Services Administration (SAMHSA) at 1-800-662-HELP (4357) for referrals to local ...