literature review on mental health

• Research article
• Open access
• Published: 01 May 2020

A systematic literature review of existing conceptualisation and measurement of mental health literacy in adolescent research: current challenges and inconsistencies

• Rosie Mansfield   ORCID: orcid.org/0000-0002-8703-5606 1 ,
• Praveetha Patalay 2 &
• Neil Humphrey 1  

BMC Public Health volume  20 , Article number:  607 ( 2020 ) Cite this article

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With an increased political interest in school-based mental health education, the dominant understanding and measurement of mental health literacy (MHL) in adolescent research should be critically appraised. This systematic literature review aimed to investigate the conceptualisation and measurement of MHL in adolescent research and the extent of methodological homogeneity in the field for meta-analyses.

Databases (PsycINFO, EMBASE, MEDLINE, ASSIA and ERIC) and grey literature were searched (1997–2017). Included articles used the term ‘mental health literacy’ and presented self-report data for at least one MHL domain with an adolescent sample (10–19 years). Definitions, methodological and contextual data were extracted and synthesised.

Ninety-one articles were identified. There was evidence of conceptual confusion, methodological inconsistency and a lack of measures developed and psychometrically tested with adolescents. The most commonly assessed domains were mental illness stigma and help-seeking beliefs; however, frequency of assessment varied by definition usage and study design. Recognition and knowledge of mental illnesses were assessed more frequently than help-seeking knowledge. A mental-ill health approach continues to dominate the field, with few articles assessing knowledge of mental health promotion.

Conclusions

MHL research with adolescent samples is increasing. Results suggest that a better understanding of what MHL means for this population is needed in order to develop reliable, valid and feasible adolescent measures, and explore mechanisms for change in improving adolescent mental health. We recommend a move away from ‘mental disorder literacy’ and towards critical ‘mental health literacy’. Future MHL research should apply integrated, culturally sensitive models of health literacy that account for life stage and acknowledge the interaction between individuals’ ability and social and contextual demands.

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Around 50% of mental health difficulties have their first onset by age 15 [ 1 , 2 ] and are associated with negative outcomes such as lower educational attainment and physical health problems [ 3 ]. Approximately 10–20% of young people are affected worldwide, and many more will experience impairing mental distress at varying degrees across the mental health continuum [ 4 , 5 , 6 , 7 , 8 ]. Adolescence is a critical period of transition, characterised by physical, cognitive, emotional, social and behavioural development [ 9 ]. It has therefore been identified as a particularly important developmental phase for improving ‘mental health literacy’ (MHL) and promoting access to mental health services [ 10 , 11 ]. However, better understanding of the conceptualisation and measurement of MHL in this population is needed.

MHL was first defined as ‘ knowledge and beliefs about mental disorders which aid their recognition, management or prevention’ ( [ 12 ] pp 182) and consisted of six domains: ‘1) the ability to recognise specific disorders or different types of psychological distress; 2) knowledge and beliefs about risk factors and causes; 3) knowledge and beliefs about self-help interventions; 4) knowledge and beliefs about professional help available; 5) attitudes which facilitate recognition and appropriate help-seeking, and 6) knowledge of how to seek mental health information’ ( [ 13 ] pp 396). Domains were later revised to include early recognition, prevention and mental health first aid skills [ 14 ]. The most recent definition comprises four broad domains aligned with current definitions of health literacy: ‘1) understanding how to obtain and maintain positive mental health; 2) understanding mental disorders and their treatments; 3) decreasing stigma related to mental disorders, and 4) enhancing help-seeking efficacy (knowing when and where to seek help and developing competencies designed to improve one’s mental health care and self-management capabilities’ ( [ 15 ] pp 155).

In a review of MHL measurement tools, O’Connor et al. revealed that the most commonly assessed domain was recognition of mental disorders. No studies assessed either knowledge of how to seek information or knowledge of self-help interventions [ 16 ]. The focus on recognition of mental disorders, along with knowledge about risk factors, causes and appropriate treatments, has been criticised for promoting the psychiatric and biogenetic conceptualisation of mental illness [ 17 , 18 ]. Despite being found to reduce blame, biogenetic explanations and attributions can lead to misconceptions about dangerousness and unpredictability and pessimism about recovery [ 19 ]. Early research also suggested that biogenetic causal theories increase a desire for social distance [ 20 , 21 ]. MHL modelled on recognition of psychiatric labels, and diagnostic language such as ‘disorder’, often leads to psychosocial predictors being ignored, and more negative attitudes towards individuals experiencing mental distress [ 22 , 23 ].

These criticisms, in line with broader socio-cultural approaches to literacy [ 24 ] understand MHL as a socio-political practice used to communicate, and make dominant, the psychiatric discourse. This appears to undermine attempts to reduce stigma, the most common outcome of school-based MHL interventions [ 25 ]. In their review of MHL measurement tools, O’Connor et al. excluded all disorder specific scales, claiming that ‘ MHL by definition should encompass knowledge and attitudes relating to a range of mental health disorders and concepts .’ ( [ 16 ] pp 199). Chambers et al. further criticised current MHL definitions for being narrow in focus with a predominantly mental-ill health approach, ignoring the complete mental health state that goes beyond the dichotomy of illness and wellness [ 26 , 27 ]. The difference between literacy about mental disorders and the ability to seek out, comprehend, appraise and apply information relating to the complete mental health state is an emerging point of discussion, and has seen MHL re-defined to include self-acquired knowledge and skills relating to positive psychology [ 28 , 29 ]. This aligns with the World Health Organisation’s (WHO) definition of mental health, which includes subjective wellbeing, optimal functioning and coping, and recognises mental health beyond the absence of disorder [ 30 ].

In response to increasingly inclusive definitions of MHL, Spiker and Hammer presented the argument for MHL as a ‘multi-construct theory, rather than a multi-dimensional construct’ ( [ 31 ] pp 3). The proposal suggested that by stretching the MHL construct, researchers have reduced the consistent use of the definition across studies, resulting in heterogeneous measurement [ 32 ]. Reviews of the psychometric properties of MHL measurement tools support this argument, and conclude that more consistent measurement with valid scales is needed [ 33 , 34 , 35 , 36 ]. Spiker and Hammer also outline problems with construct irrelevant variance [ 31 ], in which measures capture more than they intended to. Furthermore, they note that construct proliferation or the ‘jingle jangle fallacy’ [ 37 ], in which scales may have different labels but measure the same construct, and vice versa, increase problems with discriminant validity. Understanding MHL as a multi-construct theory could help delineate between its broad domains: recognition, knowledge, stigma and help-seeking beliefs, and acknowledge their complexity.

Internationally, there is growing political interest in child and adolescent mental health promotion and education [ 6 , 38 ]. Despite limited evidence, it is suggested that educating the public by improving their ability to recognise mental disorders, and increasing help-seeking knowledge, can promote population mental health [ 39 , 40 ]. Furthermore, a reduction in stigmatising attitudes is consistently reported to improve help-seeking [ 41 , 42 ]. MHL, by definition, includes these interacting domains. However, despite a comprehensive set of reviews that assess the psychometric properties of MHL measurement tools [ 33 , 34 , 35 , 36 ], there is no systematic literature review, to date, that assesses the current conceptualisation and measurement of MHL across adolescent research. Being able to clearly operationalise what is meant by a MHL intervention and meta-analyse their effectiveness, will have implications for the investment in school and population level initiatives. Similarly, being able to conduct time trend analyses that plot possible improvements in adolescents’ MHL against mental health outcomes, will reveal the extent to which population level improvements in MHL promote mental health. First though, we must have a clear picture of the understanding of MHL in adolescent research and how it is currently being measured.

Objectives and research questions

The aim of the current study was therefore to examine the ways in which MHL has been conceptualised and measured in adolescent research to date, and explore the extent of methodological homogeneity in the field for meta-analyses. We set out to answer the following research questions: 1) What are the most common study designs, contexts, and aims? 2) How is MHL conceptualised? 3) What are the most commonly measured domains of MHL, and do these vary by study design and definition usage? 4) To what extent do articles use measures that have evidence of validity for use with adolescent samples? 5) Is there enough methodological homogeneity in the field to conduct meta-analyses?

A protocol was published on PROSPERO in December 2017 (reference: CRD42017082021 ), and was updated periodically to reflect the progress of the review. Relevant PRISMA guidelines for reporting were followed [ 43 ].

Eligibility criteria

Articles were included with adolescent samples aged between 10 and 19 [ 44 ]. Samples with a mean age outside of this range were excluded. If no mean was presented and the age range fell outside of the criterion, articles were only included if results were presented for sub-groups (e.g. 12–17 years from a sample aged 12–25). General MHL and diagnosis-specific literacy research was included. Articles with quantitative study designs and extractable self-report data for at least one time point measurement of any MHL domain were eligible. These criteria ensured that only articles with extractable data from adolescents, who had not yet received any form of intervention were included. At the full text screening phase, articles published before 1997, based on the date of the first MHL definition [ 12 ], and those that did not explicitly use the term ‘mental health literacy’ or a diagnosis-specific equivalent (e.g. ‘depression literacy’) were excluded. By applying this criterion, the current study was able to present the number of articles that measured domains without referring to MHL. Identifying cases where researchers measure the same construct but use different labels is important when considering conceptualisation and meta-analyses.

Only articles available in English were included. Specific populations such as clinical/patient populations and juvenile offenders were excluded, as were university students. In contrast to schools in most countries, universities are not universal, with only a sub-set of young people entering higher education. University samples were therefore not seen as representative and often included participants outside the age criterion. Post-partum and later life neurocognitive disorders (e.g. Alzheimer’s disease) were removed given their limited relevance for this age group. In line with other MHL reviews [ 33 ], articles with a focus on substance abuse were excluded to avoid reviewing a large number of adolescent risk behaviour studies and substance abuse prevention programmes.

Search strategy

The search strategy was developed to include a number of combinations of terms to ensure that literature relating to different domains of MHL were captured. Population terms such as ‘adolescen*’ or ‘young people*’ had to be present and mental health related terms (e.g. ‘mental health’ and ‘mental disorders’) were exploded to capture general MHL and diagnosis-specific studies. Similarly, outcome terms (e.g. ‘health literacy’ and ‘health education’) were exploded, and domain specific terms included (e.g. ‘knowledge’, ‘recogni*’, ‘attitud*’, ‘stigma*’, ‘help-seek*’, ‘prevent*’ or ‘positive*’). See Additional File 1 . for an example search strategy.

Data sources

The following databases were searched from their start date to the search dates (November 2017): PsycINFO, EMBASE, MEDLINE, ASSIA, and ERIC. Key authors were also contacted to identify grey literature. References were harvested from related reviews and all papers identified in the search. Hand searches of key authors’ publication lists were also conducted, and Google Scholar was used to find studies known by the authors but not identified in the database searches.

Article selection

Results from the database searches were saved to Endnote and duplicates were removed. The lead author screened the article titles and abstracts to identify those that met the inclusion criteria. Full texts were then screened and reasons for exclusion were recorded. Any uncertainties were resolved through discussion with other members of the research team. A sub-set of 20 articles were screened at full text stage by the third author, and a strong level of agreement was found (k = .78, p  = .001).

Data extraction

Research was assessed on an article level (rather than by study) for the purposes of investigating the conceptualisation of MHL. The fact that authors break MHL down into component parts to write separate articles is support for identifying which domains are more commonly associated with the use of the term. Data on the following methodological factors were extracted from eligible articles using a uniform data extraction form: year of publication, country and setting (community (research conducted outside of the school setting e.g. population level surveys) vs. school-based research), study design (intervention vs. population-based), primary aims, MHL definition and use of the term, general MHL vs. diagnosis-specific literacy, number/types of MHL domains measured, and measurement tools (e.g. vignette, yes/no, Likert scales).

Data analysis

A content analysis was conducted using NVivo 12 to organise articles by their primary aim and understand the conceptualisation of MHL based on the definition presented and use of the term. Frequencies and percentages for each group were calculated and articles coded based on whether they included items related to general MHL or diagnosis-specific literacy. Existing definitions of MHL [ 12 , 13 , 14 , 15 , 28 ] were used to create a coding framework that clearly delineated its broad constituent domains (e.g. recognition, knowledge, stigma and beliefs), the object of these domains (e.g. mental illnesses, mental health prevention and promotion, and help-seeking), and their directionality (e.g. self vs. other) – see Fig.  1 .

MHL Coding Framework

Mental illness stigma was assessed using existing conceptualisation i.e. personal and perceived stigma relating to self (intra-personal) and others (inter-personal), and broad domains (e.g. attitudes and beliefs, emotional reactions, and social distancing) [ 45 ]. The coding of help-seeking beliefs was informed by the theory of planned behaviour [ 46 ], assessing not only help-seeking intentions but also help-seeking confidence and self-perceived help-seeking knowledge, perceived helpfulness of referrals, help-sources and treatments, help-seeking stigma and perceived help-seeking barriers. A distinction was also made between help-seeking beliefs for self (intra-personal) vs. others (inter-personal). Although not explicitly included in any MHL definition, help-seeking behaviour was also assessed as the term is sometimes confused with help-seeking intentions. Domains were coded at an item level due to many articles presenting this form of data (e.g. % of sample that answered each item correctly as opposed to a scale mean). Frequencies and percentages were produced across all articles and by study design and definition usage.

Assessment of measures

An assessment of all MHL related measurement tools was conducted in order to assess methodological homogeneity across articles, and whether there was evidence that the measures were psychometrically valid for adolescent samples. In order to present instruments with the most comprehensive psychometric assessments, measures were coded based on whether an article existed with the primary aim of establishing its psychometric properties with an adolescent sample.

Article selection and characteristics

In total, 206 articles were identified that presented extractable adolescent data on at least one MHL domain. Of these, 91 articles (44%) used the term ‘mental health literacy’. Those that did not use the term ( N  = 115, 56%), were therefore not perceived to have intended to explicitly measure the construct and were not included beyond this point. (see Fig.  2 . for a PRISMA flowchart of articles, Additional File 2 . for the full set of coded articles, and Additional File 3 . for the reference list of included articles).

PRISMA Flowchart of Included Studies

Synthesised findings

Design, context and aims.

Figure  3 shows the number of publications by year and country. Australian research dominated the field up until 2013, at which point there was an increase in research being published globally. Australia (34%), USA (15%), Canada (9%), Republic of Ireland (9%) and the UK (8%) have published the majority of research between 2003 and 2017.

Publication Count by Year and Country

Table  1 presents a summary of articles’ study design, context and primary aim. The majority of articles reported on school-based studies. Articles with the primary aim of describing levels of MHL also included variables such as age, school year, gender, education, socio-economic variables, occupation, urbanicity, mental health status and previous mental health service use.

• Conceptualisation

Of the 91 articles that used the term ‘mental health literacy’, only 41 (45%) defined it. The most common definition, presented by 29 out of 41 (71%) articles, was that coined by Jorm and colleagues [ 12 ]. A further 3 articles (7%) used a simplified or adapted version of this definition [ 47 , 48 , 49 ]. Four articles (10%) defined MHL as related to knowledge only (e.g. ‘knowledge of mental health problems as well as the sources of help available’ ; ( [ 50 ] pp. 485) . The full list of MHL domains presented by Jorm and colleagues [ 13 ], was included in over a third ( N  = 14, 34%) of articles that defined the term. However, there was some variation. For example, very few of these articles ( N  = 2, 14%) referred to different types of psychological distress as well as mental disorders when presenting the recognition domain. Furthermore, in most cases ( N  = 11, 79%), ‘knowledge and beliefs’ was replaced with ‘knowledge’ only, for domains relating to causes and risk factors, self-help strategies and professional help available.

A small number of articles that defined MHL ( N  = 5, 12%) presented Jorm’s additional domains relating to mental health first aid skills and advocacy [ 14 ]. Some articles ( N  = 4, 10%) provided examples of specific MHL domains, namely recognition of mental disorders and knowledge and beliefs about appropriate help-seeking and treatment, as opposed to presenting a comprehensive list. An emerging group of articles ( N  = 5, 12%) either acknowledged mental health promotion as a component of MHL or presented Kutcher and colleagues’ four broad domains including ‘understanding how to obtain and maintain good mental health’ ( [ 15 ] pp 155).

Regardless of whether a definition was provided, approximately one third of identified articles ( N  = 31, 34%) referred to MHL as a construct separate to mental illness stigma, with some suggesting that MHL predicts stigma. For example, articles described the measurement of these constructs as separate (e.g. ‘All respondents were then asked a series of questions that assessed sociodemographic characteristics, mental health literacy, stigma …’; ([ 51 ] pp. 941), and referred to or presented a relationship between the two constructs (e.g. ‘Participants with higher MHL displayed more negative attitudes to mental illness’ ; ( [ 52 ] pp. 100) . There were also instances where articles presented MHL as a predictor of help-seeking intentions and attitudes (e.g. ‘Studies indicate that in general, mental health literacy improves help seeking attitudes’ ; [ 53 ] (pp. 2), or used the term MHL to refer only to improved knowledge (e.g. ‘to assess the extent to which the students had learned the curriculum and developed what we called ‘depression literacy’ ; ([ 54 ] pp. 230).

• Measurement

Thirty-nine (43%) articles included items relating to general MHL. The exact terminology varied across studies e.g. mental disorder [ 55 ], mental illness [ 56 ], mental health problem [ 57 ], and mental health issue [ 58 ]. Few articles included items relating to mental health as opposed to mental ill-health. Bjørnsen et al. developed and validated a scale to assess adolescents' knowledge of how to obtain and maintain good mental health [ 28 ]. Kutcher et al. and McLuckie et al. also included an individual knowledge item that assessed an understanding of the complete mental health state (e.g. ‘People who have mental illness can at the same time have mental health’ ) [ 59 , 60 ].

Table  2 . presents the frequency and percentage of articles that assessed different types of diagnosis-specific literacy. In line with this focus, 57 (63%) articles utilized a vignette methodology, basing questions on descriptions, stories and scenarios relating to an individual meeting diagnostic criteria for a given mental disorder. Of these articles, 12 (21%) used comparator vignettes describing individuals with physical health problems (e.g. asthma or diabetes), control characters with good academic attainment, or ‘normal issues’ or mental health problems relating to stressful life events (e.g. the death of an elderly relative or the end of a romantic relationship). Table  3 . presents the frequency and percentage of articles that assessed different domains of MHL.

Measurement tools were too heterogeneous to conduct meta-analyses. As noted in Table 1 , four articles (4%) had the primary aim of validating MHL related measures with adolescent samples [ 28 , 55 , 61 , 62 ]. The scales assessed in Bjørnsen et al. and Pang et al. measured only one broad domain of MHL; knowledge of mental health promotion and mental illness stigma respectively [ 28 , 62 ]. Hart et al. assessed the psychometric properties of a depression knowledge questionnaire and found a one factor general knowledge latent structure to be the best fit to the data [ 61 ]. Campos et al. aimed to provide a more comprehensive assessment of MHL, and by psychometrically assessing a pool of items, developed a 33-item tool with three latent factors: first aid skills and help seeking, knowledge/stereotypes, and self-help strategies [ 55 ]. A further 22 articles (24%), stated that some items or scales had been developed for the purpose of the study.

Thirty-nine articles (43%) stated that they based their items on Jorm and colleagues original MHL survey or later 2006 and 2011 versions [ 12 , 63 ]. Furthermore, two articles (2%) included items from the Mental Health First Aid Questionnaire (MHFAQ) as detailed by Hart et al. [ 64 ]. However, there is no evidence of the validity of these surveys as whole scales, and researchers commonly selected and modified items. The Friend in Need Questionnaire, similar to Jorm and colleagues MHL survey in that it covers multiple MHL domains, was developed by Burns and Rapee to avoid leading multiple-choice answers. Instead, open-ended responses were coded in order to quantify levels of MHL [ 65 ]. Despite finding six articles (7%) that utilised a version of this questionnaire, no published validation paper was found. As part of the Adolescent Depression Awareness Programme (ADAP), an Adolescent Depression Knowledge Questionnaire (ADKQ) was developed and later validated [ 61 ]. Six articles (7%), including the validation paper, presented data using versions of the ADKQ.

Due to the multi-faceted nature of stigma, a range of measurement tools were identified across articles. The Attribution Questionnaire (AQ-27) was originally developed by Corrigan and colleagues [ 66 , 67 ] along with a brief 9-item scale (r-AQ) covering the following emotional reactions: blame, anger, pity, help, dangerousness, fear, avoidance, segregation and coercion. A similar 8-item version (AQ-8-C) was also developed for children [ 68 ]. The r-AQ was adapted by Watson et al. for use with middle school aged adolescents [ 69 ], and a 5-item version was more recently validated by Pinto et al. [ 70 ]. Four articles (4%) identified in this review used variations of the r-AQ.

Link et al. developed the 5-item Social Distance Scale (SDS) [ 71 ], which was later adapted for young people [ 72 ]. This version was more recently validated with a large sample aged 15–25 [ 73 ]. Five articles (5%) cited this version of the SDS. Seven articles (8%) used variations of the World Psychiatric Association’s (WPA) social distance items [ 74 ]; however, no adolescent validation paper was found. This review also found factual and attitudinal WPA scales presented by Pinfold et al. including the Myths and Facts About Schizophrenia Questionnaire. In total, these scales, or modified versions, were used in eight articles (9%), but no validation papers were found. The Reported and Intended Behaviour Scale (RIBS) [ 75 ] was utilised in three articles (3%). This scale has been translated into Japanese and Italian, and there is evidence of its validity with adult and university student samples [ 76 , 77 ]. The evidence of its validity with an adolescent sample was mixed [ 78 ].

The Depression Stigma Scale (DSS) was developed by Griffiths et al. to measure personal and perceived depression stigma [ 79 ]. Yap et al. later validated the DSS and confirmed that personal and perceived stigma were distinct constructs comprised of ‘weak-not-sick’ and ‘dangerous/unpredictable’ factors in a sample aged 15–25 [ 73 ]. Six articles (7%) utilised a version of the DSS, more commonly the items relating to personal stigma. Items from the Opinions about Mental Illness Scale (OMI) were used in two articles (2%). The original scale was cited by both [ 80 ], however, a Chinese version of the OMI has been tested for validity with a sample of secondary school students [ 81 ]. Other validated stigma scales identified included: the Attitudes Toward Serious Mental Illness Scale–Adolescent Version (ATSMI-AV) [ 82 ] ( N  = 1, 1%) and the Subjective Social Status Loss Scale [ 83 ] ( N  = 1, 1%). Measures of help-seeking attitudes and intentions were often not validated with adolescent samples. Two articles (2%) modified the General Help Seeking Questionnaire (GHSQ), previously validated for use with high school students [ 84 ]. A further two articles (2%) utilised the Self-Stigma of Seeking Help (SSOSH) scale; however, tests of its validity have only been conducted with college students [ 85 ].

The aims of this review were to investigate the conceptualisation and measurement of MHL in adolescent research, and scope the extent of methodological homogeneity for possible meta-analyses. The review clearly shows an increase in school-based MHL research with adolescent samples in recent years. This makes sense given that adolescence is increasingly identified as an important period for improving MHL and access to mental health services [ 6 , 10 , 11 , 38 ]. However, the field is still dominated by research from Western, developed countries and takes a predominantly mental-ill health approach. Furthermore, numerous challenges and inconsistencies have emerged in the field over the past 20 years.

Included articles were required to use the term ‘mental health literacy’ or a diagnosis-specific equivalent. However, by first including all articles that presented data for at least one MHL domain, a large number of articles that measured domains without referring to MHL were revealed. Researchers were measuring the same constructs but providing different labels indicating problems with discriminant validity [ 31 , 37 ]. It must be acknowledged that some of the articles included in the final set may have used the term without intending to measure the whole construct, and some articles were removed that measured multiple domains. For example, 16 intervention studies, previously included in a systematic literature review of the effectiveness of MHL interventions [ 25 ], were excluded from this current review because they did not use the term. Despite the exclusion of some potentially relevant data on a domain level, this criterion was considered most appropriate given one of the aims was to assess the conceptualisation of MHL.

Although under half of the articles identified defined MHL, those that did predominantly used definitions from Jorm and colleagues [ 12 , 13 , 14 ]. However, the various adaptations and interpretations of the original definition has clearly led to a lack of construct travelling in the field, in particular, confusion about the inclusion of beliefs and stigma related constructs as MHL domains. Furthermore, few articles referred to mental health and varying degrees of psychological distress in addition to mental illness, supporting the argument that current MHL definitions take a predominantly mental-ill health approach [ 16 , 26 ].

Although an adolescent specific definition of MHL may not be necessary, definitions frequently adopted by articles in this review were developed for adults. It is important for future research to consider not only cognitive development but also the unique social structures and vulnerabilities of adolescents in the conceptualisation and assessment of MHL. Given that the definition of adolescence in the current study ranges from 10 to 19 years, it is clear that even within this age range, different developmental factors could be considered. Applying integrated models of generic health literacy to MHL that acknowledge the life course and social and environmental determinants should therefore be a future priority [ 86 , 87 ].

Around a third of articles measured recognition of specific mental illnesses, with the majority using open-ended questions such as ‘ What, if anything, do you think is wrong …’, and calculating the % of correct responses. Knowledge of mental illnesses was measured more frequently than knowledge of prevention and promotion, therefore an understanding of the complete mental health state was often neglected [ 27 ]. More research is needed to develop and validate measures that assess the ability to seek out, comprehend, appraise and apply information relating to the complete mental health state as opposed to only assessing literacy of mental disorders. By using measurement tools that predominantly focus on psychiatric labels, there is evidence to suggest that stigma could be increased [ 22 , 23 ]. Given that over three quarters of intervention studies identified in this review included a measure of stigma, future research should consider the way in which mental-ill health approaches to MHL, in terms of intervention content and study measures, may influence stigma related outcomes.

It is perhaps unsurprising that the MHL field continues to be modelled on psychiatric labelling given the influence of Jorm and colleagues early work in Australia that came out of the National Health and Medical Research Council (NHMRC) Social Psychiatry Research Unit [ 12 ]. Kutcher and colleagues MHL definition also has its origins in psychiatry, but more explicitly includes understanding of mental health promotion and stigma reduction [ 15 ]. A growing body of research relating to eating disorders literacy also emphasises the need to distinguish between health promotion, prevention and early intervention initiatives in reducing the population health burden of eating-disordered behaviour and to prioritise mental health promotion programs, including those targeting stigma reduction [ 88 , 89 , 90 ]. This review identified an emerging group of articles that included understanding of how to obtain and maintain good mental health in their conceptualisation of MHL. However, this domain was rarely measured.

Just under half of the articles included items relating to general MHL. However, terminology was varied (e.g. mental illness, mental disorder, mental health problem, mental health issue). Leighton revealed that young people have a lack of conceptual clarity when it comes to these mental health related terms, unsurprising given the lack of consistent definitions in practice [ 91 ]. The range and subjectivity of mental health related terms reduces the meaningfulness of comparisons across MHL studies. Similarly, over half of the articles identified in this review assessed mental illness stigma, but the complexity of the construct caused heterogeneity in measurement. Intentions to seek help were the most commonly measured help-seeking belief; these findings support previous assessments of MHL measurement tools [ 16 ]. Measuring only intentions to seek help, without capturing knowledge of what help is available, will not provide a true picture of actual behaviour change. Findings also suggested that recognition and help-seeking related beliefs may be more directly associated with the MHL construct and, in line with previous literature [ 25 ], mental illness stigma was found to be a common outcome measure in MHL related interventions.

It is worth considering whether the MHL construct should continue to be stretched or whether we should accept that the multiple domains exist in their own right. For example, self-acquired knowledge and skills relating to positive psychology are being investigated, but are only just starting to emerge under the MHL construct [ 28 , 29 ]. Similarly, stigma and help-seeking knowledge and beliefs are assessed as part of, and independently from, the MHL framework. Adopting a multi-construct theory approach to MHL, as suggested by Spiker and Hammer [ 31 ], would see increased focus on developing and validating measures of specific MHL domains in order to better understand the way in which these domains relate to each other.

Developing better MHL theory will help provide clear logic models and theories of change for MHL interventions aiming to improve adolescent mental health, something currently lacking in the field. Although it should be acknowledged that the aims of MHL interventions will vary based on the scope, setting and cultural context, an increased number of validated measures as well as improved MHL theory could inform decisions about the most appropriate domain to measure as the outcome i.e. is the main aim of the intervention to reduce stigma or improve help-seeking. This is particularly important for school-based evaluations of MHL interventions for which respondent burden is often a concern.

We acknowledge that there were some articles in this review that adapted adult measures and tested for face and content validity with child and adolescent mental health professionals, and internal reliability and comprehension with adolescent samples. However, in general there was a lack of psychometric work to assess factor structure of scale-based measures in this age group, with large numbers of articles presenting data on an item level. More research should be conducted like that of Campos et al., working with young people to develop and psychometrically test pools of MHL items to identify latent factors [ 55 ]. This will help to inform future conceptualisation and measurement in this age group.

Even when there was evidence of a measure’s validity for use with adolescents, many articles selected only the items relevant for their study or adapted the scale to fit the cultural context. This may, in part, be an attempt to reduce the number of items and therefore the response burden. However, adaptation to measures based on the cultural discourse around mental health aligns with school-based mental health promotion approaches that account for children’s social, cultural and political contexts [ 92 ]. This raises the important question as to whether we should be trying to test and compare mental health related knowledge across cultures, particularly given the ongoing levels of disagreement amongst mental health professions between and within countries. A previous review of cross-cultural conceptualisations of positive mental health concluded that future definitions should be inclusive and culturally sensitive, and that more work was needed to empirically validate criteria for mental health [ 93 ]. Future research should consider conducting measurement invariance on existing MHL measures across different cultures. A comparison of knowledge items and their pre-defined correct answers, could help understand cultural differences in the discourse around mental health and what it means to be mental health literate across contexts.

Given the increased political interest in mental health promotion and education [ 6 , 38 ], we recommend that MHL research focuses on increasing understanding of ways to promote and maintain positive mental health, including subjective wellbeing, optimal functioning, coping and resilience [ 30 , 94 ]. Examples of knowledge items with true/false responses were identified in the current review and many aligned with a biogenetic conceptualisation of mental illness. Not only could these ‘truths’ cause more negative attitudes towards individuals experiencing mental health difficulties [ 19 ], many mapped directly onto the content of interventions and therefore do not provide any evidence of adolescents’ ability to critically appraise mental health information. To enhance individual and community level critical mental health literacy, the MHL field should apply models of public health literacy that aim to increase empowerment and control over health decisions, and acknowledge the interaction between an individual’s ability and their social and contextual demands [ 86 , 95 , 96 , 97 ]. Given that mental health is a key component of health, it is also worth questioning the usefulness of this separation moving forward; a MHL field that is playing catch up with more developed health literacy approaches could further exaggerate the existing lack of parity of esteem.

MHL research with adolescent populations is on the rise, but this review has highlighted some important areas for future consideration. Increasingly stretched definitions of MHL have led to conceptual confusion and methodological inconsistency, and there is a lack of measures developed and psychometrically tested with adolescents. Furthermore, the field is still dominated by a mental-ill health approach, with limited measures assessing the promotion of positive mental health. We suggest that the MHL field moves away from assessing ‘mental disorder literacy’ and towards critical ‘mental health literacy’. A better understanding of what MHL means for adolescents is needed in order to develop reliable, valid and feasible measures that acknowledge their developmental stage and unique social and contextual demands. In conclusion, by treating MHL as a multi-construct theory, more could be understood about the mechanisms for change in improving adolescent mental health.

Availability of data and materials

Link to PROSPERO review protocol included in the manuscript, example search strategy included as supplementary material.

Abbreviations

• Mental health literacy

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Mansfield, R., Patalay, P. & Humphrey, N. A systematic literature review of existing conceptualisation and measurement of mental health literacy in adolescent research: current challenges and inconsistencies. BMC Public Health 20 , 607 (2020). https://doi.org/10.1186/s12889-020-08734-1

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Systematic review and meta-analysis of depression, anxiety, and suicidal ideation among Ph.D. students

• Emily N. Satinsky 1 ,
• Tomoki Kimura 2 ,
• Mathew V. Kiang 3 , 4 ,
• Rediet Abebe 5 , 6 ,
• Scott Cunningham 7 ,
• Hedwig Lee 8 ,
• Xiaofei Lin 9 ,
• Cindy H. Liu 10 , 11 ,
• Igor Rudan 12 ,
• Srijan Sen 13 ,
• Mark Tomlinson 14 , 15 ,
• Miranda Yaver 16 &
• Alexander C. Tsai 1 , 11 , 17  

Scientific Reports volume  11 , Article number:  14370 ( 2021 ) Cite this article

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• Epidemiology
• Health policy
• Quality of life

University administrators and mental health clinicians have raised concerns about depression and anxiety among Ph.D. students, yet no study has systematically synthesized the available evidence in this area. After searching the literature for studies reporting on depression, anxiety, and/or suicidal ideation among Ph.D. students, we included 32 articles. Among 16 studies reporting the prevalence of clinically significant symptoms of depression across 23,469 Ph.D. students, the pooled estimate of the proportion of students with depression was 0.24 (95% confidence interval [CI], 0.18–0.31; I 2  = 98.75%). In a meta-analysis of the nine studies reporting the prevalence of clinically significant symptoms of anxiety across 15,626 students, the estimated proportion of students with anxiety was 0.17 (95% CI, 0.12–0.23; I 2  = 98.05%). We conclude that depression and anxiety are highly prevalent among Ph.D. students. Data limitations precluded our ability to obtain a pooled estimate of suicidal ideation prevalence. Programs that systematically monitor and promote the mental health of Ph.D. students are urgently needed.

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Prevalence of depression among Chinese university students: a systematic review and meta-analysis

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Relationship between depression and quality of life among students: a systematic review and meta-analysis

Introduction.

Mental health problems among graduate students in doctoral degree programs have received increasing attention 1 , 2 , 3 , 4 . Ph.D. students (and students completing equivalent degrees, such as the Sc.D.) face training periods of unpredictable duration, financial insecurity and food insecurity, competitive markets for tenure-track positions, and unsparing publishing and funding models 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 —all of which may have greater adverse impacts on students from marginalized and underrepresented populations 13 , 14 , 15 . Ph.D. students’ mental health problems may negatively affect their physical health 16 , interpersonal relationships 17 , academic output, and work performance 18 , 19 , and may also contribute to program attrition 20 , 21 , 22 . As many as 30 to 50% of Ph.D. students drop out of their programs, depending on the country and discipline 23 , 24 , 25 , 26 , 27 . Further, while mental health problems among Ph.D. students raise concerns for the wellbeing of the individuals themselves and their personal networks, they also have broader repercussions for their institutions and academia as a whole 22 .

Despite the potential public health significance of this problem, most evidence syntheses on student mental health have focused on undergraduate students 28 , 29 or graduate students in professional degree programs (e.g., medical students) 30 . In non-systematic summaries, estimates of the prevalence of clinically significant depressive symptoms among Ph.D. students vary considerably 31 , 32 , 33 . Reliable estimates of depression and other mental health problems among Ph.D. students are needed to inform preventive, screening, or treatment efforts. To address this gap in the literature, we conducted a systematic review and meta-analysis to explore patterns of depression, anxiety, and suicidal ideation among Ph.D. students.

Flowchart of included articles.

The evidence search yielded 886 articles, of which 286 were excluded as duplicates (Fig.  1 ). An additional nine articles were identified through reference lists or grey literature reports published on university websites. Following a title/abstract review and subsequent full-text review, 520 additional articles were excluded.

Of the 89 remaining articles, 74 were unclear about their definition of graduate students or grouped Ph.D. and non-Ph.D. students without disaggregating the estimates by degree level. We obtained contact information for the authors of most of these articles (69 [93%]), requesting additional data. Three authors clarified that their study samples only included Ph.D. students 34 , 35 , 36 . Fourteen authors confirmed that their study samples included both Ph.D. and non-Ph.D. students but provided us with data on the subsample of Ph.D. students 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 . Where authors clarified that the sample was limited to graduate students in non-doctoral degree programs, did not provide additional data on the subsample of Ph.D. students, or did not reply to our information requests, we excluded the studies due to insufficient information (Supplementary Table S1 ).

Ultimately, 32 articles describing the findings of 29 unique studies were identified and included in the review 16 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 (Table 1 ). Overall, 26 studies measured depression, 19 studies measured anxiety, and six studies measured suicidal ideation. Three pairs of articles reported data on the same sample of Ph.D. students 33 , 38 , 45 , 51 , 53 , 56 and were therefore grouped in Table 1 and reported as three studies. Publication dates ranged from 1979 to 2019, but most articles (22/32 [69%]) were published after 2015. Most studies were conducted in the United States (20/29 [69%]), with additional studies conducted in Australia, Belgium, China, Iran, Mexico, and South Korea. Two studies were conducted in cross-national settings representing 48 additional countries. None were conducted in sub-Saharan Africa or South America. Most studies included students completing their degrees in a mix of disciplines (17/29 [59%]), while 12 studies were limited to students in a specific field (e.g., biomedicine, education). The median sample size was 172 students (interquartile range [IQR], 68–654; range, 6–6405). Seven studies focused on mental health outcomes in demographic subgroups, including ethnic or racialized minority students 37 , 41 , 43 , international students 47 , 50 , and sexual and gender minority students 42 , 54 .

In all, 16 studies reported the prevalence of depression among a total of 23,469 Ph.D. students (Fig.  2 ; range, 10–47%). Of these, the most widely used depression scales were the PHQ-9 (9 studies) and variants of the Center for Epidemiologic Studies-Depression scale (CES-D, 4 studies) 63 , and all studies assessed clinically significant symptoms of depression over the past one to two weeks. Three of these studies reported findings based on data from different survey years of the same parent study (the Healthy Minds Study) 40 , 42 , 43 , but due to overlap in the survey years reported across articles, these data were pooled. Most of these studies were based on data collected through online surveys (13/16 [81%]). Ten studies (63%) used random or systematic sampling, four studies (25%) used convenience sampling, and two studies (13%) used multiple sampling techniques.

Pooled estimate of the proportion of Ph.D. students with clinically significant symptoms of depression.

The estimated proportion of Ph.D. students assessed as having clinically significant symptoms of depression was 0.24 (95% confidence interval [CI], 0.18–0.31; 95% predictive interval [PI], 0.04–0.54), with significant evidence of between-study heterogeneity (I 2  = 98.75%). A subgroup analysis restricted to the twelve studies conducted in the United States yielded similar findings (pooled estimate [ES] = 0.23; 95% CI, 0.15–0.32; 95% PI, 0.01–0.60), with no appreciable difference in heterogeneity (I 2  = 98.91%). A subgroup analysis restricted to the studies that used the PHQ-9 to assess depression yielded a slightly lower prevalence estimate and a slight reduction in heterogeneity (ES = 0.18; 95% CI, 0.14–0.22; 95% PI, 0.07–0.34; I 2  = 90.59%).

Nine studies reported the prevalence of clinically significant symptoms of anxiety among a total of 15,626 Ph.D. students (Fig.  3 ; range 4–49%). Of these, the most widely used anxiety scale was the 7-item Generalized Anxiety Disorder scale (GAD-7, 5 studies) 64 . Data from three of the Healthy Minds Study articles were pooled into two estimates, because the scale used to measure anxiety changed midway through the parent study (i.e., the Patient Health Questionnaire-Generalized Anxiety Disorder [PHQ-GAD] scale was used from 2007 to 2012 and then switched to the GAD-7 in 2013 40 ). Most studies (8/9 [89%]) assessed clinically significant symptoms of anxiety over the past two to four weeks, with the one remaining study measuring anxiety over the past year. Again, most of these studies were based on data collected through online surveys (7/9 [78%]). Five studies (56%) used random or systematic sampling, two studies (22%) used convenience sampling, and two studies (22%) used multiple sampling techniques.

Pooled estimate of the proportion of Ph.D. students with clinically significant symptoms of anxiety.

The estimated proportion of Ph.D. students assessed as having anxiety was 0.17 (95% CI, 0.12–0.23; 95% PI, 0.02–0.41), with significant evidence of between-study heterogeneity (I 2  = 98.05%). The subgroup analysis restricted to the five studies conducted in the United States yielded a slightly lower proportion of students assessed as having anxiety (ES = 0.14; 95% CI, 0.08–0.20; 95% PI, 0.00–0.43), with no appreciable difference in heterogeneity (I 2  = 98.54%).

Six studies reported the prevalence of suicidal ideation (range, 2–12%), but the recall windows varied greatly (e.g., ideation within the past 2 weeks vs. past year), precluding pooled estimation.

Additional stratified pooled estimates could not be obtained. One study of Ph.D. students across 54 countries found that phase of study was a significant moderator of mental health, with students in the comprehensive examination and dissertation phases more likely to experience distress compared with students primarily engaged in coursework 59 . Other studies identified a higher prevalence of mental ill-health among women 54 ; lesbian, gay, bisexual, transgender, and queer (LGBTQ) students 42 , 54 , 60 ; and students with multiple intersecting identities 54 .

Several studies identified correlates of mental health problems including: project- and supervisor-related issues, stress about productivity, and self-doubt 53 , 62 ; uncertain career prospects, poor living conditions, financial stressors, lack of sleep, feeling devalued, social isolation, and advisor relationships 61 ; financial challenges 38 ; difficulties with work-life balance 58 ; and feelings of isolation and loneliness 52 . Despite these challenges, help-seeking appeared to be limited, with only about one-quarter of Ph.D. students reporting mental health problems also reporting that they were receiving treatment 40 , 52 .

Risk of bias

Twenty-one of 32 articles were assessed as having low risk of bias (Supplementary Table S2 ). Five articles received one point for all five categories on the risk of bias assessment (lowest risk of bias), and one article received no points (highest risk). The mean risk of bias score was 3.22 (standard deviation, 1.34; median, 4; IQR, 2–4). Restricting the estimation sample to 12 studies assessed as having low risk of bias, the estimated proportion of Ph.D. students with depression was 0.25 (95% CI, 0.18–0.33; 95% PI, 0.04–0.57; I 2  = 99.11%), nearly identical to the primary estimate, with no reduction in heterogeneity. The estimated proportion of Ph.D. students with anxiety, among the 7 studies assessed as having low risk of bias, was 0.12 (95% CI, 0.07–0.17; 95% PI, 0.01–0.34; I 2  = 98.17%), again with no appreciable reduction in heterogeneity.

In our meta-analysis of 16 studies representing 23,469 Ph.D. students, we estimated that the pooled prevalence of clinically significant symptoms of depression was 24%. This estimate is consistent with estimated prevalence rates in other high-stress biomedical trainee populations, including medical students (27%) 30 , resident physicians (29%) 65 , and postdoctoral research fellows (29%) 66 . In the sample of nine studies representing 15,626 Ph.D. students, we estimated that the pooled prevalence of clinically significant symptoms of anxiety was 17%. While validated screening instruments tend to over-identify cases of depression (relative to structured clinical interviews) by approximately a factor of two 67 , 68 , our findings nonetheless point to a major public health problem among Ph.D. students. Available data suggest that the prevalence of depressive and anxiety disorders in the general population ranges from 5 to 7% worldwide 69 , 70 . In contrast, prevalence estimates of major depressive disorder among young adults have ranged from 13% (for young adults between the ages of 18 and 29 years in the 2012–2013 National Epidemiologic Survey on Alcohol and Related Conditions III 71 ) to 15% (for young adults between the ages of 18 and 25 in the 2019 U.S. National Survey on Drug Use and Health 72 ). Likewise, the prevalence of generalized anxiety disorder was estimated at 4% among young adults between the ages of 18 and 29 in the 2001–03 U.S. National Comorbidity Survey Replication 73 . Thus, even accounting for potential upward bias inherent in these studies’ use of screening instruments, our estimates suggest that the rates of recent clinically significant symptoms of depression and anxiety are greater among Ph.D. students compared with young adults in the general population.

Further underscoring the importance of this public health issue, Ph.D. students face unique stressors and uncertainties that may put them at increased risk for mental health and substance use problems. Students grapple with competing responsibilities, including coursework, teaching, and research, while also managing interpersonal relationships, social isolation, caregiving, and financial insecurity 3 , 10 . Increasing enrollment in doctoral degree programs has not been matched with a commensurate increase in tenure-track academic job opportunities, intensifying competition and pressure to find employment post-graduation 5 . Advisor-student power relations rarely offer options for recourse if and when such relationships become strained, particularly in the setting of sexual harassment, unwanted sexual attention, sexual coercion, and rape 74 , 75 , 76 , 77 , 78 . All of these stressors may be magnified—and compounded by stressors unrelated to graduate school—for subgroups of students who are underrepresented in doctoral degree programs and among whom mental health problems are either more prevalent and/or undertreated compared with the general population, including Black, indigenous, and other people of color 13 , 79 , 80 ; women 81 , 82 ; first-generation students 14 , 15 ; people who identify as LGBTQ 83 , 84 , 85 ; people with disabilities; and people with multiple intersecting identities.

Structural- and individual-level interventions will be needed to reduce the burden of mental ill-health among Ph.D. students worldwide 31 , 86 . Despite the high prevalence of mental health and substance use problems 87 , Ph.D. students demonstrate low rates of help-seeking 40 , 52 , 88 . Common barriers to help-seeking include fears of harming one’s academic career, financial insecurity, lack of time, and lack of awareness 89 , 90 , 91 , as well as health care systems-related barriers, including insufficient numbers of culturally competent counseling staff, limited access to psychological services beyond time-limited psychotherapies, and lack of programs that address the specific needs either of Ph.D. students in general 92 or of Ph.D. students belonging to marginalized groups 93 , 94 . Structural interventions focused solely on enhancing student resilience might include programs aimed at reducing stigma, fostering social cohesion, and reducing social isolation, while changing norms around help-seeking behavior 95 , 96 . However, structural interventions focused on changing stressogenic aspects of the graduate student environment itself are also needed 97 , beyond any enhancements to Ph.D. student resilience, including: undercutting power differentials between graduate students and individual faculty advisors, e.g., by diffusing power among multiple faculty advisors; eliminating racist, sexist, and other discriminatory behaviors by faculty advisors 74 , 75 , 98 ; valuing mentorship and other aspects of “invisible work” that are often disproportionately borne by women faculty and faculty of color 99 , 100 ; and training faculty members to emphasize the dignity of, and adequately prepare Ph.D. students for, non-academic careers 101 , 102 .

Our findings should be interpreted with several limitations in mind. First, the pooled estimates are characterized by a high degree of heterogeneity, similar to meta-analyses of depression prevalence in other populations 30 , 65 , 103 , 104 , 105 . Second, we were only able to aggregate depression prevalence across 16 studies and anxiety prevalence across nine studies (the majority of which were conducted in the U.S.) – far fewer than the 183 studies included in a meta-analysis of depression prevalence among medical students 30 and the 54 studies included in a meta-analysis of resident physicians 65 . These differences underscore the need for more rigorous study in this critical area. Many articles were either excluded from the review or from the meta-analyses for not meeting inclusion criteria or not reporting relevant statistics. Future research in this area should ensure the systematic collection of high-quality, clinically relevant data from a comprehensive set of institutions, across disciplines and countries, and disaggregated by graduate student type. As part of conducting research and addressing student mental health and wellbeing, university deans, provosts, and chancellors should partner with national survey and program institutions (e.g., Graduate Student Experience in the Research University [gradSERU] 106 , the American College Health Association National College Health Assessment [ACHA-NCHA], and HealthyMinds). Furthermore, federal agencies that oversee health and higher education should provide resources for these efforts, and accreditation agencies should require monitoring of mental health and programmatic responses to stressors among Ph.D. students.

Third, heterogeneity in reporting precluded a meta-analysis of the suicidality outcomes among the few studies that reported such data. While reducing the burden of mental health problems among graduate students is an important public health aim in itself, more research into understanding non-suicidal self-injurious behavior, suicide attempts, and completed suicide among Ph.D. students is warranted. Fourth, it is possible that the grey literature reports included in our meta-analysis are more likely to be undertaken at research-intensive institutions 52 , 60 , 61 . However, the direction of bias is unpredictable: mental health problems among Ph.D. students in research-intensive environments may be more prevalent due to detection bias, but such institutions may also have more resources devoted to preventive, screening, or treatment efforts 92 . Fifth, inclusion in this meta-analysis and systematic review was limited to those based on community samples. Inclusion of clinic-based samples, or of studies conducted before or after specific milestones (e.g., the qualifying examination or dissertation prospectus defense), likely would have yielded even higher pooled prevalence estimates of mental health problems. And finally, few studies provided disaggregated data according to sociodemographic factors, stage of training (e.g., first year, pre-prospectus defense, all-but-dissertation), or discipline of study. These factors might be investigated further for differences in mental health outcomes.

Clinically significant symptoms of depression and anxiety are pervasive among graduate students in doctoral degree programs, but these are understudied relative to other trainee populations. Structural and clinical interventions to systematically monitor and promote the mental health and wellbeing of Ph.D. students are urgently needed.

This systematic review and meta-analysis follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) approach (Supplementary Table S3 ) 107 . This study was based on data collected from publicly available bibliometric databases and did not require ethical approval from our institutional review boards.

Eligibility criteria

Studies were included if they provided data on either: (a) the number or proportion of Ph.D. students with clinically significant symptoms of depression or anxiety, ascertained using a validated scale; or (b) the mean depression or anxiety symptom severity score and its standard deviation among Ph.D. students. Suicidal ideation was examined as a secondary outcome.

We excluded studies that focused on graduate students in non-doctoral degree programs (e.g., Master of Public Health) or professional degree programs (e.g., Doctor of Medicine, Juris Doctor) because more is known about mental health problems in these populations 30 , 108 , 109 , 110 and because Ph.D. students face unique uncertainties. To minimize the potential for upward bias in our pooled prevalence estimates, we excluded studies that recruited students from campus counseling centers or other clinic-based settings. Studies that measured affective states, or state anxiety, before or after specific events (e.g., terrorist attacks, qualifying examinations) were also excluded.

If articles described the study sample in general terms (i.e., without clarifying the degree level of the participants), we contacted the authors by email for clarification. Similarly, if articles pooled results across graduate students in doctoral and non-doctoral degree programs (e.g., reporting a single estimate for a mixed sample of graduate students), we contacted the authors by email to request disaggregated data on the subsample of Ph.D. students. If authors did not reply after two contact attempts spaced over 2 months, or were unable to provide these data, we excluded these studies from further consideration.

Search strategy and data extraction

PubMed, Embase, PsycINFO, ERIC, and Business Source Complete were searched from inception of each database to November 5, 2019. The search strategy included terms related to mental health symptoms (e.g., depression, anxiety, suicide), the study population (e.g., graduate, doctoral), and measurement category (e.g., depression, Columbia-Suicide Severity Rating Scale) (Supplementary Table S4 ). In addition, we searched the reference lists and the grey literature.

After duplicates were removed, we screened the remaining titles and abstracts, followed by a full-text review. We excluded articles following the eligibility criteria listed above (i.e., those that were not focused on Ph.D. students; those that did not assess depression and/or anxiety using a validated screening tool; those that did not report relevant statistics of depression and/or anxiety; and those that recruited students from clinic-based settings). Reasons for exclusion were tracked at each stage. Following selection of included articles, two members of the research team extracted data and conducted risk of bias assessments. Discrepancies were discussed with a third member of the research team. Key extraction variables included: study design, geographic region, sample size, response rate, demographic characteristics of the sample, screening instrument(s) used for assessment, mean depression or anxiety symptom severity score (and its standard deviation), and the number (or proportion) of students experiencing clinically significant symptoms of depression or anxiety.

Risk of bias assessment

Following prior work 30 , 65 , the Newcastle–Ottawa Scale 111 was adapted and used to assess risk of bias in the included studies. Each study was assessed across 5 categories: sample representativeness, sample size, non-respondents, ascertainment of outcomes, and quality of descriptive statistics reporting (Supplementary Information S5 ). Studies were judged as having either low risk of bias (≥ 3 points) or high risk of bias (< 3 points).

Analysis and synthesis

Before pooling the estimated prevalence rates across studies, we first transformed the proportions using a variance-stabilizing double arcsine transformation 112 . We then computed pooled estimates of prevalence using a random effects model 113 . Study specific confidence intervals were estimated using the score method 114 , 115 . We estimated between-study heterogeneity using the I 2 statistic 116 . In an attempt to reduce the extent of heterogeneity, we re-estimated pooled prevalence restricting the analysis to studies conducted in the United States and to studies in which depression assessment was based on the 9-item Patient Health Questionnaire (PHQ-9) 117 . All analyses were conducted using Stata (version 16; StataCorp LP, College Station, Tex.). Where heterogeneity limited our ability to summarize the findings using meta-analysis, we synthesized the data using narrative review.

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Acknowledgements

We thank the following investigators for generously sharing their time and/or data: Gordon J. G. Asmundson, Ph.D., Amy J. L. Baker, Ph.D., Hillel W. Cohen, Dr.P.H., Alcir L. Dafre, Ph.D., Deborah Danoff, M.D., Daniel Eisenberg, Ph.D., Lou Farrer, Ph.D., Christy B. Fraenza, Ph.D., Patricia A. Frazier, Ph.D., Nadia Corral-Frías, Ph.D., Hanga Galfalvy, Ph.D., Edward E. Goldenberg, Ph.D., Robert K. Hindman, Ph.D., Jürgen Hoyer, Ph.D., Ayako Isato, Ph.D., Azharul Islam, Ph.D., Shanna E. Smith Jaggars, Ph.D., Bumseok Jeong, M.D., Ph.D., Ju R. Joeng, Nadine J. Kaslow, Ph.D., Rukhsana Kausar, Ph.D., Flavius R. W. Lilly, Ph.D., Sarah K. Lipson, Ph.D., Frances Meeten, D.Phil., D.Clin.Psy., Dhara T. Meghani, Ph.D., Sterett H. Mercer, Ph.D., Masaki Mori, Ph.D., Arif Musa, M.D., Shizar Nahidi, M.D., Ph.D., Arthur M. Nezu, Ph.D., D.H.L., Angelo Picardi, M.D., Nicole E. Rossi, Ph.D., Denise M. Saint Arnault, Ph.D., Sagar Sharma, Ph.D., Bryony Sheaves, D.Clin.Psy., Kennon M. Sheldon, Ph.D., Daniel Shepherd, Ph.D., Keisuke Takano, Ph.D., Sara Tement, Ph.D., Sherri Turner, Ph.D., Shawn O. Utsey, Ph.D., Ron Valle, Ph.D., Caleb Wang, B.S., Pengju Wang, Katsuyuki Yamasaki, Ph.D.

A.C.T. acknowledges funding from the Sullivan Family Foundation. This paper does not reflect an official statement or opinion from the County of San Mateo.  

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A.C.T. conceptualized the study and provided supervision. T.K. conducted the search. E.N.S. contacted authors for additional information not reported in published articles. E.N.S. and T.K. extracted data and performed the quality assessment appraisal. E.N.S. and A.C.T. conducted the statistical analysis and drafted the manuscript. T.K., M.V.K., R.A., S.C., H.L., X.L., C.H.L., I.R., S.S., M.T. and M.Y. contributed to the interpretation of the results. All authors provided critical feedback on drafts and approved the final manuscript.

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A meta-review of literature reviews assessing the capacity of patients with severe mental disorders to make decisions about their healthcare

• A. Calcedo-Barba 1 ,
• A. Fructuoso 2 ,
• J. Martinez-Raga 3 ,
• M. Sánchez de Carmona 5 &
• E. Vicens 6  

BMC Psychiatry volume  20 , Article number:  339 ( 2020 ) Cite this article

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Determining the mental capacity of psychiatric patients for making healthcare related decisions is crucial in clinical practice. This meta-review of review articles comprehensively examines the current evidence on the capacity of patients with a mental illness to make medical care decisions.

Systematic review of review articles following PRISMA recommendations. PubMed, Scopus, CINAHL and PsycInfo were electronically searched up to 31 January 2020. Free text searches and medical subject headings were combined to identify literature reviews and meta-analyses published in English, and summarising studies on the capacity of patients with serious mental illnesses to make healthcare and treatment related decisions, conducted in any clinical setting and with a quantitative synthesis of results. Publications were selected as per inclusion and exclusion criteria. The AMSTAR II tool was used to assess the quality of reviews.

Eleven publications were reviewed. Variability on methods across studies makes it difficult to precisely estimate the prevalence of decision-making capacity in patients with mental disorders. Nonetheless, up to three-quarters of psychiatric patients, including individuals with serious illnesses such as schizophrenia or bipolar disorder may have capacity to make medical decisions in the context of their illness. Most evidence comes from studies conducted in the hospital setting; much less information exists on the healthcare decision making capacity of mental disorder patients while in the community. Stable psychiatric and non-psychiatric patients may have a similar capacity to make healthcare related decisions. Patients with a mental illness have capacity to judge risk-reward situations and to adequately decide about the important treatment outcomes. Different symptoms may impair different domains of the decisional capacity of psychotic patients. Decisional capacity impairments in psychotic patients are temporal, identifiable, and responsive to interventions directed towards simplifying information, encouraging training and shared decision making. The publications complied satisfactorily with the AMSTAR II critical domains.

Conclusions

Whilst impairments in decision-making capacity may exist, most patients with a severe mental disorder, such as schizophrenia or bipolar disorder are able to make rational decisions about their healthcare. Best practice strategies should incorporate interventions to help mentally ill patients grow into the voluntary and safe use of medications.

Peer Review reports

In 1995, Appelbaum and Grisso stated that competence to consent to treatment relied on four legal standards: the ability to communicate a choice; the ability to understand relevant information; the ability to appreciate the situation and its likely consequences; and the ability to manipulate information rationally [ 1 ]. In healthcare, the capacity to make decisions regarding treatment is closely related to the autonomy, the exercise of self-governance, and the ability of an individual to take intentional actions [ 2 ]. The capacity to consent to treatment is often used in the clinical assessment of the ability to engage in authentic autonomous decision-making, a fundamental element of a person’s dignity and rights [ 3 ].

Assessment of mental capacity has become a key component of daily clinical practice [ 4 , 5 ]. Mental health legislation and medical ethics increasingly require physicians to empower patients to make decisions, and to respect the patient’s wishes with regard to accepting or refusing therapy [ 4 , 6 ]. However, it has been reported that coercive treatment, involuntary hospitalisations and medications are currently overused [ 7 ]; this has a direct negative impact on patients’ adherence to treatment and on their engagement and participation in shared decision-making with their healthcare professionals [ 8 ].

An increasing number of publications are assessing decision-making capacity in mental health. However, comparisons and contrasts of the findings of these articles are lacking and it becomes difficult to draw clear conclusions on what is the actual capacity of individuals with serious mental illnesses to make decisions about their healthcare and treatments [ 9 ]. This meta-review of review articles was designed as a comprehensive synthesis of the current state of knowledge in the field, with the aim of assessing the available evidence on the decision-making capacity of patients with various mental illnesses (especially schizophrenia, psychosis and bipolar disorder) with regard to the management of their disease and their treatment. The review compares the conclusions of various comprehensive publications, discusses the strength of these conclusions, and identifies existing gaps in the evidence.

The review of the literature was conducted in accordance with the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines [ 10 ]. A series of steps, including the definition of the search strategy, identification and selection of publications, data extraction and synthesis, and quality assessment was followed.

Search strategy for identification and selection of publications

The aim of the search strategy was to provide a comprehensive list of published literature reviews assessing decision making capacity in patients with mental disorders. Four electronic databases (the Cumulative Index to Nursing and Allied Health Literature [CINAHL], PsycInfo, PubMed and Scopus) were searched up to 31 January 2020. The search strategy is described in Additional file  1 . Free text searches and medical subject headings were combined to identify literature reviews published in English, summarising studies conducted in any clinical setting and with a quantitative synthesis of results. Selection of publications was carried out as per inclusion and exclusion criteria (Table  1 ). Lists of references in the key papers retrieved were further checked to identify other relevant articles.

Potentially relevant abstracts were assessed by two expert reviewers to identify all papers suitable for inclusion. Full text copies were requested. Reviews which were identified after mutual agreement were included and data were extracted. A third reviewer was involved in the process to resolve any disagreements on the selection of publications.

Data extraction and quality assessment

Data extraction was carried out by one researcher. A data extraction form that covered citation, country, population, interventions, comparators, outcomes, settings, review type, aims, literature review size, strengths and limitations and key findings of the review as stated by authors was used to extract data (Tables  2 and 3 ). The AMSTAR II (A MeaSurement Tool to Assess systematic Reviews) [ 22 ] assessment tool was used to assess the quality of reviews.

A total of 1973 hits were initially identified; 1938 were either duplicated or deemed not relevant for the review based on the assessment of titles and abstracts; 22 full text publications were initially considered valid and retrieved for closer examination; 11 were excluded because they referred to diseases excluded from the review or did not assess decision making capacity. Data was finally extracted from 11 publications (Fig.  1 ).

PRISMA diagram

The number of studies included in each review apprised varied between 7 [ 18 , 20 ] and 63 [ 16 ], and the number of patients with a mental disorder ranged from 6 [ 13 ] to 2483 [ 15 ]. Schizophrenia or schizoaffective disorders [ 12 , 13 , 19 , 20 ] and psychosis [ 14 , 18 , 21 ] were the most frequently explored mental illnesses. The general healthy population or patients with a non-mental disorder were the usual study comparators. Therefore, decisional capacity variance among mental illnesses of different nature has been little explored (Tables  2 and 3 ).

Prevalence of decision-making capacity

Information on the prevalence of capacity for making healthcare decisions among psychiatry patients can be derived from two systematic reviews. One systematic review of 37 empirical, quantitative studies of mental capacity in a mixed population of psychiatric patients reported that up to 67% of participants had the capacity to decide whether to be admitted to a psychiatric unit while a median of 71% had capacity for making treatment decisions (a median of 29%, interquartile range (IQR) 22–44, lacked capacity) [ 17 ]. Another systematic review (40 articles) found that 26% (95% confidence interval (CI): 18 to 36) to 67% (95% CI: 35 to 88) of people with schizophrenia or other non-affective disorders were able to make medical decisions related or unrelated to the management of their condition [(median: 48% (95% CI: 29 to 66)] [ 19 ]. In both reviews, up to three quarters of severe mental disorder patients, including individuals with schizophrenia would have capacity to make medical decisions in the context of their illness, in particular specific decisions related with their treatments [ 17 , 19 ]. Both reviews are also coincident in that heterogeneity between studies was high, with considerable variation in study design and measurements [ 17 , 19 ].

Decisional capacity in different clinical settings and patient groups

Four reviews assessed patients in diverse settings and explored the degree of impairment in each dimension of decision-making capacity. Lepping et al. [ 15 ] reported that 55% of patients in psychiatric and 66% of patients in non-psychiatric settings had the capacity to make medical decisions. Appreciation of the problem and necessity for treatment were more frequently compromised in psychiatric patients, while non-psychiatric patients struggled primarily with reasoning. The authors found a significant variation between studies due to heterogeneity in designs and methods that reached 86% in psychiatric settings and 90% in non-psychiatric settings. Jeste et al. [ 13 ] reported a 48 to 79% overlap between people with schizophrenia and non-psychiatric patients on the MacArthur subscales, which indicated that most patients with schizophrenia had comparably adequate decision-making capacity [ 13 ]. Psychotic inpatients had several characteristics which temporarily limited their capacity and distinguished them from outpatients. Greater severity of positive and negative symptoms, experiencing a stressful life event (e.g., hospitalisation), and often receiving higher doses of medication adversely impacted cognition among psychiatric inpatients [ 15 ]. Community-dwelling or clinically stable outpatients were much closer to non-psychiatric subjects in terms of the capacity for decision-making. The authors concluded that similar proportions of non-psychiatric and psychiatric outpatients either had or lacked capacity to consent to treatment or to hospital admission, and that impairment in the capacity to make decisions was not a distinguishing feature of schizophrenia patients [ 13 , 15 ].

Another meta-analysis of ten studies showed that compared to healthy controls, patients with schizophrenia or schizoaffective disorder were significantly more likely to have impaired decision-making capacity in terms of understanding, reasoning, appreciation and expression of a choice in clinical research and treatment, as measured by the MacArthur Competence Assessment Tool (MacCAT) instruments [ 20 ]. The standardised mean differences were more significant in older than in younger age subgroups, suggesting that, compared to their healthy counterparts, the impairment of decision-making capacity could be more obvious in older patients than in younger patients. In some of the studies included in this meta-analysis, decisional capacity improved in patients with schizophrenia following intensive educational interventions.

Another systematic review explored the degree of impairment in each dimension of decision-making capacity in schizophrenia patients compared to non-psychiatric controls, as assessed by the MacCAT [ 12 ]. The odds for a decreased understanding and a decreased appreciation were some five times higher in individuals with schizophrenia than in non-mentally ill controls, those for decreased reasoning almost four times higher, and those for a decreased aptitude to express a choice was over six times higher. The use of an enhanced informed consent form contributed to significant improvements in decision-making capacity compared to the use of standard forms. The authors concluded that even if patients with schizophrenia have a significantly decreased decision-making capacity, they should be considered to be as competent as non-mentally ill controls unless very severe changes were identifiable during the clinical examination [ 12 ].

In these four systematic reviews, the decisional capacity of patients with a psychiatric disease was compared with that of patients with a non-psychiatric clinical condition or with that of healthy individuals. All reviews are concurrent in the fact that impairments in decisional capacity can be found in both psychiatric and non-psychiatric patients, and therefore the diagnosis of a psychiatric condition should not be the upfront reason of incapacity. Despite most research being conducted in the hospital setting, those fewer addressing decisional capacity in psychiatric outpatients showed that their capacity to make medical decisions can be much alike to that of the non-psychiatric individuals. Likewise, studies coincidently acknowledge that decisional impairments amongst psychiatric inpatients are temporal and responsive to information-enhancing interventions.

Determining factors of decisional capacity in psychosis patients

In a systematic review and meta-analysis of factors that help or hinder treatment decision-making capacity in psychosis (23 studies, n  = 1823) a moderate to large negative association between total psychotic symptom severity and the capacity of participants to understand information relevant to treatment decisions was found [ 14 ]. Poor insight was also associated with patients’ poor capacity to make treatment related decisions. Verbal cognitive function, metacognitive ability and years spent in education were positively associated with the ability of psychiatric individuals to understand information relating to treatment decision making. Decision-making capacity responded favourably to interventions, such as the simplification of the information, shared decision-making, and metacognitive training [ 14 ].

Likewise, Ruissen et al. [ 18 ] reported the findings of seven articles that assessed the relationship between competence to decide and insight of psychiatric inpatients and outpatients and of psychotic and non-psychotic patients. A large overlap between insight and competence to decide was reported among psychotic (schizophrenia, schizoaffective disorder, and psychotic episodes) and bipolar disorder (comprising both manic and depressive episodes) patients implying that a strong correlation existed between insight and capacity for making decisions, including decisions related to medical treatments and hospital admission. Psychotic patients with adequate insight were generally competent in making medical decisions.

Both reviews report findings on the capacity of psychotic patients to make treatment and other disease-related decisions. They are coincident in the relevance of insight as a determining factor of psychiatric patients’ decisional capacity. As expected, the burden and severity of psychotic symptoms can seriously compromise patients’ ability to make decisions.

Capacity of people with mental illness to make risk-reward decisions and to choose treatments

The capacity of mental illness patients for making value-based decisions was explored in literature reviews of studies based on gambling tasks and on preferences for medication-associated outcomes methods. A systematic review and meta-analysis explored the factors which may help or hinder the ability to make risk-reward decision making in a pooled sample of 4264 individuals with psychosis, based on their performance on the Iowa Gambling Tasks (IGT) and the Cambridge Gambling Tasks (CGT) [ 21 , 23 , 24 ]. Compared with healthy individuals, people with psychosis had moderately impaired risk-reward decision-making ability (g = − 0.57, 95% CI − 0.66 to − 0.48; I 2 45%; moderate quality) [ 21 ]. They were also more likely to value rewards over losses (k = 6, N  = 516, g = 0.38, 95% CI: 0.05 to 0.70, I 2 64%), and to base decisions on recent rather than past outcomes (k = 6, N  = 516, g = 0.30, 95% CI: − 0.04 to 0.65, I 2 68%). Analysis of the positive or negative influence of the type and dose of antipsychotics on decision-making capacity was inconclusive. The authors suggested that, although people with non-affective psychosis may make less effective decisions than healthy individuals in the IGT and CGT, their difficulties were moderate and comparable with those observed in other clinical groups.

Mukherjee and Kable [ 16 ] calculated that around 27% of patients with various mental disorders were similar to healthy individuals when deciding about losses and rewards on the IGT. Furthermore, individuals with mental illnesses had fewer deficits than individuals with frontal lobe lesions, for instance. The assessment of the severity of impairment across types of mental illnesses did not demonstrate any significant differences according to specific psychiatric diagnosis.

Eiring et al. [ 11 ] investigated the relative value adults with a mental illness place on treatment outcomes, including the attributes of particular medications or medication classes and the consequences and health states associated with their use. It reported that patients were able to provide valid preference measures with the different methods applied, generally understood the tasks, and gave sufficiently consistent answers. Among patients with schizophrenia, positive, acute or psychotic symptoms appeared consistently among the least desirable outcomes. Negative symptoms, such as reduced capacity for emotion, were found more desirable or less important than positive symptoms. Independence received high ratings and inpatient status low ratings. Overall, patients with schizophrenia tended to value disease states higher and side effects lower than other groups and perceived side effects more negatively than their therapists. Patients with bipolar disorder gave low values to mania and severe depression and reported weight gain to be important.

These reviews provide consistent evidence on the fact that patients with a serious mental disease, such as schizophrenia or bipolar disorder can make risk-reward decisions in the context of their illness and treatments. Furthermore, the studies summarised in the reviews show that these patients may achieve a level of ability for making value-based decisions equal to non-psychiatric patients. They can reliably decide about the important treatment outcomes and their most desirable treatment attributes.

Quality assessment

Reviews presented well-framed research questions based on the evidence based PICOS model [ 25 ] (Table  2 ) and were high quality according to the AMSTAR II assessment tool (Table  3 ) [ 22 ]. AMSTAR II was developed to evaluate systematic reviews of randomised trials or non-randomised studies of healthcare interventions, or both. Publications included in this review complied satisfactorily the AMSTAR II critical domains. No critical weaknesses were identified in the assessment. Therefore, the reviews provided an accurate and comprehensive summary of the results of studies of decision-making capacity in mental disorder patients.

This meta-review review brings together a set of high-quality reviews on the capacity of individuals with a severe mental illness to make decisions about their healthcare. It presents a thorough synthesis of current systematic review literature concerning the decision-making capacity of patients with mental disorders, including psychotic, schizophrenia and bipolar disorder individuals. It provides a picture of the state of the field in the complex task of assessing patients’ decisional capacity in psychiatry. It comprehensively summarizes a body of evidence supporting the idea that the decision-making capacity of psychiatric patients with serious mental illness is preserved in most circumstances and challenges the understanding that people with severe mental illnesses are unable to make their own choices [ 8 ].

Authors across studies are coincident in emphasising that most patients with a severe mental disorder are able to make rational decisions about their medical care and to participate in decision-making regarding treatments despite temporal impairments. Thus, most often the degree of impairment that may be inherent to the mental disorder does not constitute incapacity to make decisions. The findings also reveal that patients with psychotic disorders or other severe mental illnesses can make complex risk-reward decisions in usual clinical practice. Small deviations from optimal performance may arise due to deficits in the ability to fully represent the value of different choices and response options, a finding that aligns with results from experimental research in patients with schizophrenia [ 26 ].

Most of the reviews addressed the capacity to make decisions in people with severe mental disorders either already hospitalised or requiring hospital admission. This means that most studies included patients with more severe symptoms less responsive to usual therapies [ 27 ]. Even in these more ill psychiatric populations, between 60 and 70% had capacity to make some treatment decisions [ 1 , 17 , 19 ]. Hospitalised patients usually have greater care needs, even when their psychiatric symptoms are controlled, exhibit significantly more severe negative, positive, and manic symptoms, and have lower global functioning than outpatients [ 28 ]. Therefore, despite the scarcity of studies measuring decisional capacity in routine ambulatory practice in psychiatry, it can be expected a high level of health-related decision-making capacity in patients in everyday life in the community. Rigorous studies investigating this question as a primary outcome would be much welcome.

This meta- review also shows that people with schizophrenia have the capacity to make other difficult decisions related, for instance, to giving consent for hospital admission or to the type of treatment they prefer to receive. Likewise, other studies have reported that patients with schizophrenia or bipolar disorder are able to describe prodromal symptoms of relapse and to suggest a treatment and the need for hospitalisation in advance; that they can request or refuse medications and state their preferences for pre-emergency interventions, non-hospital alternatives and non-medical personal care [ 29 , 30 , 31 ]. In such circumstances, shared decision making and advancing crisis management plans may help reduce insecurity and improve healthcare outcomes for the patient with a mental illness. Studies have found that being involved in decision-making, whenever decisional capacity exists, renders more positive treatment results, better medication adherence, higher self-efficacy and autonomy, and lower decisional uncertainty among patients with mental disorders [ 32 , 33 ].

Patients’ awareness of decisional capacity and having the opportunity for sharing decisions on future care (crisis planning) for psychosis reduces the use of compulsory inpatient treatment by approximately 40% over 15 to 18 months [ 33 ]. In this context, advance directives are fundamental to ensure the timely provision of medical treatments, thus minimising decisional impairments in the acute stages of psychosis [ 34 ]. Psychosocial interventions are also important to address the complex health needs of people with serious mental illnesses. Combined with anti-psychotics, psychosocial interventions highly contribute to reduce the severity of symptoms, to benefit functioning, to encourage decision making and to decrease hospital readmissions [ 35 ].

Nevertheless, clinicians play the crucial role of judging the capacity of patients with severe mental disorder to decide about their treatments and healthcare, and tools exist to guide their assessment [ 36 ]. The final decision depends entirely on clinical judgement, based on the practitioner’s knowledge of the patient and of the course of the disease.

Beyond acute episodes, the findings also support the notion that continued training and learning, simplification and enhancement of the information improve the capacity of patients with severe mental disorders for decision-making both in hospital and in everyday life [ 37 ]. The results of various studies demonstrate that brief interventions aimed at recovering capacity for understanding can help schizophrenia patients to perform very much like healthy people in the four dimensions of decisional capacity (understanding, appreciation, reasoning and expression of a choice) [ 38 ]. Regular information reinforcement, strengthening neurocognitive functioning and training are important to maintain long-term levels of competence and to maximise decision making capacities of patients [ 39 , 40 ].

In sum, people with severe mental illness can benefit greatly from anticipation, prevention, gradual learning, enhanced information and enriched shared decision-making in order to strengthen their autonomous decision-making capacity, to increase their autonomy and to ultimately contribute to reducing the stigma of mental illness. Being able to make decisions in anticipation of, for instance, agitation or other acute symptoms should help patients to gain a sense of control over their own lives, and to enhance their health-related quality of life [ 41 ]. This review contributes to the growing body of evidence suggesting that the best medical practice should help severe mentally ill patients to grow into voluntary healthcare, safe users of medications.

Small sample size, heterogeneity, language and selection bias of participants were among the limitations frequently reported by the authors of the studies reviewed. However, since the publications included in the meta- review were systematic reviews and meta-analyses, the risk of bias was minimised. Nonetheless, it was limited to publications appeared in English. Although the search was comprehensive, papers in many other languages including French, Germany. Italian or Spanish may not have been identified. Several frequent mental illnesses were excluded for reasons of study feasibility. Important mental health conditions, such as dementia, depression and other disorders have not been addressed which may have limited the scope of the meta-review.

This meta-review of review articles provides a comprehensive synthesis of the current state of knowledge on the capacity of patients with mental illnesses to make decisions about their healthcare and medical treatments. It provides clinicians and other healthcare practitioners a summary of the evidence on the topic, contrasting key findings. It shows that whilst impairments in decision-making capacity may exist, most patients with a severe mental disorder are able to make adequate decisions about the care of their health. It denotes that best practice strategies should help mentally ill patients to exercise their decisional capacity to develop into autonomous and reliable users of medications. Keeping a sense of control over their illness and life may help them to improve the outcomes of their treatments and their health-related quality of life.

Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Abbreviations

Description

A MeaSurement Tool to Assess systematic Reviews

Cambridge Gambling Tasks

Confidence Interval

Cumulative Index to Nursing and Allied Health Literature

Iowa Gambling Tasks

InterQuartile Range

MacArthur Competence Assessment Tool

MacArthur Competence Assessment Tool for Clinical Research

MacArthur Competence Assessment Tool for Treatment

Number Needed to Treat

Odds Ratios

Preferred Reporting Items for Systematic Review and Meta-Analysis

Standard Deviation

Standard Error

Standardized Mean Difference

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Meta- review search strategy.

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Calcedo-Barba, A., Fructuoso, A., Martinez-Raga, J. et al. A meta-review of literature reviews assessing the capacity of patients with severe mental disorders to make decisions about their healthcare. BMC Psychiatry 20 , 339 (2020). https://doi.org/10.1186/s12888-020-02756-0

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• Decision making capacity
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• Schizophrenia
• Bipolar disorder
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A systematic review: increasing mental health literacy in students through “The Guide”

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• Published: 14 August 2024
• Volume 4 , article number  96 , ( 2024 )

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• Abouzar Nazari   ORCID: orcid.org/0000-0003-2155-5438 1 ,
• Gholamreza Garmaroudi   ORCID: orcid.org/0000-0001-7449-227X 2 &
• Marzie Rabiei   ORCID: orcid.org/0009-0003-2297-9483 3  

Ensuring mental health literacy among students aged 10–25 is of utmost importance, and the efficacy of educational programs in this domain holds significant value. This systematic review assesses the influence of The Guide (Mental Health and High School Curriculum Guide) on mental health literacy within this demographic.

Materials and methods

This review examined how effective The Guide was in increasing students’ mental health literacy, help-seeking attitudes, and stigma reduction. It also looked at what factors influenced its implementation and sustainability in different settings. It followed the PRISMA guidelines and searched for studies that used The Guide or a modified version of it with students aged 10–25 from 1975 to 2023. Studies were assessed for quality using the QuADS Quality Appraisal tool.

Our systematic review encompassed a comprehensive analysis of 10 reports derived from five primary articles originating from six countries, with a combined participant pool of 4298 individuals. The selected studies exhibited variations in design, duration, delivery modes, and outcome measures. The synthesized findings underscored the positive impact of The Guide educational program on enhancing students' mental health literacy. However, the effects on students' help-seeking attitudes and stigma were varied. Additionally, the results illuminated that the success and sustainability of The Guide were contingent on several factors, including the mode of delivery, the role of facilitators or teachers, and the unique characteristics of the student population.

The review showed that The Guide was effective in improving students’ mental health literacy in different settings. It also suggested that The Guide needed to be adapted and tailored to the local context and culture, and that the facilitators or teachers and the students needed to be trained and involved in the process.

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1 Introduction

Mental health literacy (MHL), defined as the ability to recognize, understand, and respond to mental health problems, plays a pivotal role in promoting awareness, reducing stigma, and facilitating help-seeking behaviors [ 1 , 2 ]. Unlike traditional illness-based models, MHL interventions such as The Guide adopt a population-based approach, focusing on equipping individuals with knowledge and skills pertinent to mental health across diverse contexts [ 3 ].

Children and youth represent a critical target group for MHL interventions, given their susceptibility to mental health challenges and potential barriers to accessing appropriate care [ 4 , 5 ]. Globally, a substantial proportion of young people experience mental health disorders, yet access to professional support remains limited [ 4 , 5 , 6 , 7 , 8 ]. Enhancing MHL among youth empowers them to identify mental health issues, seek timely assistance, and dispel misconceptions that perpetuate stigma [ 9 ].

Stigma, characterized by labeling, devaluation, and discrimination based on perceived differences, profoundly impacts young people’s mental outcomes. It hinders help-seeking behaviors and diminishes self-esteem, exacerbating the challenges of managing mental health issues [ 10 ]. Effective MHL interventions, such as The Guide, have the potential to mitigate stigma by promoting accurate understanding, positive attitudes, and empathetic responses toward mental health concerns [ 1 , 11 ].

Educational interventions represent a cornerstone in delivering MHL education to youth, aiming to cultivate informed attitudes and encourage proactive help-seeking behaviors [ 12 , 13 ]. The effectiveness of these interventions, however, varies based on content, delivery methods, and evaluation frameworks [ 14 ]. The Guide, an educational program derived from the Mental Health and High School Curriculum Guide (MHHSCG) [ 15 ], is specifically designed to meet these objectives within educational settings. Notably, while rooted in educational contexts, The Guide's adaptable format allows for potential implementation in diverse environments such as workplaces and communities, albeit with necessary adjustments to suit specific needs and dynamics.

This systematic review aims to assess the impact of The Guide educational program on enhancing MHL among individuals aged 10–25 across various settings. Specifically, this review seeks to: (1) identify and evaluate the quality of studies examining The Guide's effectiveness in improving MHL; (2) synthesize findings regarding MHL outcomes including knowledge, stigma, and help-seeking attitudes; (3) explore factors influencing The Guide's implementation and sustainability in different settings; and (4) discuss implications for research, policy, and practical applications.

2.1 Search strategy

This systematic review, following PRISMA (Preferred Reporting Items for Systematic Reviews) guidelines, employed a comprehensive search strategy to identify relevant studies. The search was conducted in February 2023, covering five key databases: PubMed, Web of Science, Scopus, Cochrane Library, and Embase. The inclusion criteria were English language articles published between 2009 and 2023. To ensure a thorough examination of the existing literature, reference lists of all included studies and relevant review articles were meticulously scrutinized. Unpublished data, grey literature (including dissertations, congress abstracts, and patents), and duplicate citations were excluded from this systematic review. Each database received a tailored search string, adapted to its unique requirements. Supplementary material 1 provides an example of the search string used in PubMed. Additionally, combined keyword searching was implemented with the following terms: ‘Mental health literacy OR (Mental health AND literacy)’ AND ‘Student* OR Adolescen* OR Youth OR Pupil OR Teen* OR School* OR Child*’ AND ‘Clinical Trial OR Randomized controlled trial OR Non-Randomized Controlled Trials OR Controlled Clinical Trial OR randomized OR randomly OR pre posttest study OR quasi-experimental’. Notably, Google Scholar, along with selected reference lists, was also explored to identify additional studies of interest beyond the initial database searches. It’s crucial to highlight that Google Scholar searches complemented academic database searches, contributing to a more comprehensive retrieval of relevant literature. This systematic review is registered on PROSPERO under the registration number CRD42023314882.

2.2 Eligibility criteria

2.2.1 inclusion criteria.

Studies eligible for inclusion addressed individuals aged 10–25 years old, employing study designs such as randomized controlled trials, non-randomized controlled trials, experimental, or before-and-after studies. Included studies delivered the intervention program of The Guide or its modified versions. Additionally, studies were required to have a control group or provide an intervention as treatment as usual. Eligible studies assessed help-seeking intentions/attitudes, mental health-related stigma, and/or mental health literacy directly through the self-report of young people. Language inclusion criteria stipulated that studies must be published in English.

2.2.2 Exclusion criteria

Conversely, studies were excluded if they lacked information about participants' age. Additionally, studies with observational designs or those without random allocation were not considered. Interventions other than The Guide or studies with no intervention were excluded. Lack of a control group led to exclusion, as did outcomes assessed from caregivers or teachers, or those measuring dimensions other than help-seeking intentions/attitudes, mental health-related stigma, or mental health literacy. Lastly, studies published in languages other than English were excluded. This comprehensive set of criteria ensured a meticulous selection process, aiming for a focused and relevant body of evidence in the systematic review.

2.2.3 Selection of studies

The titles and abstracts of the retrieved records were screened by two independent reviewers (A.N. and M.R.) using the eligibility criteria. The full texts of the potentially eligible records were obtained and assessed by the same reviewers. Any disagreements were resolved by discussion or consultation with a third reviewer (GH.G.). A PRISMA flow diagram was used to report the study selection process.

2.2.4 Data extraction

The data extracted from the included studies are summarized in Table  1 . The data extracted included: first author’s name, publication year, study population, sample size, participants’ sex, number of subjects in each group, age range and average age of participants, trial design, type of intervention, and Posttest time.

2.2.5 Risk of bias assessment

The assessment of the risk of bias was conducted using the Quality Assessment and Developmental Evaluation (QuADS) tool [ 16 ] which is designed to appraise the quality and risk of bias in systematic reviews of mixed- or multi-method studies. The tool comprises eight aspects, each scored from 0 to 3, with the total score indicating the overall quality level of the study. Studies were categorized as excellent (above 80%), good (between 50 and 80%), or low (below 50%) based on their total scores. The risk of bias assessment was conducted by the review team, including A.N. and M.R., with a focus on various aspects such as research aims, settings, populations, designs, analytic methods, and the consideration of research stakeholders’ perspectives. The risk of bias assessment was considered in the interpretation of findings, ensuring that the conclusions drawn accounted for the quality and reliability of the evidence. Studies with a high risk of bias were noted, and their findings were interpreted with caution, particularly in terms of their contribution to overall conclusions.

2.2.6 Data synthesis

Narrative synthesis was utilized to analyze and interpret the results derived from the studies included in this review. This approach entailed qualitatively summarizing the findings, identifying patterns, variations, and relationships across the studies. The synthesis specifically delved into examining the impact of The Guide on outcomes such as mental health literacy, help-seeking attitudes, and mental health-related stigma. Given that no meta-analysis or moderator analysis was conducted in the review, the synthesis predominantly relied on a qualitative narrative approach to offer a comprehensive overview of the evidence. Any discerned patterns or trends were discussed within the framework of the study objectives, elucidating their implications for research, policy, and practice.

2.2.7 Intervention description

The Guide, developed in 2009 as an adaptation of the Mental Health & High School Curriculum Guide (MHHSCG), is a modular web-based resource designed to enhance mental health literacy among youth aged 10–25 [ 14 , 15 ]. It consists of six core modules covering topics such as understanding mental health, recognizing symptoms, seeking help, and reducing stigma. Each module incorporates interactive activities, case studies, and resources tailored to educational contexts, facilitating engagement and knowledge retention among users.

The literature search yielded a total of 1234 records, of which 462 were duplicates and were removed. 734 were excluded after screening the titles and abstracts. The full texts of the remaining 42 studies were assessed for eligibility, and 5 studies [ 17 , 18 , 19 , 20 , 21 ] met the inclusion criteria and it's noteworthy that one of the articles included two reports due to the study being conducted in two different countries and reported separately in one article. The main reasons for exclusion were: not using The Guide as the intervention, not having a control group, and outside the age range of 10–25. The PRISMA flow diagram [ 22 ] of the study selection process is shown in Fig.  1 .

PRISMA 2020 flow diagram updated of papers included in the review Improving mental health literacy in students aged 10–25 with The Guide educational program: A systematic review, search period: 1975 to February 2023

A new literature search was conducted to update the previous review and identify any new studies that evaluated the effectiveness of The Guide. The new search resulted in 130 records from various databases and sources. After removing 35 duplicates, 60 records were excluded based on the screening of titles and abstracts. The remaining 42 full-text records were assessed for eligibility using the same criteria as the previous review. Only 2 studies [ 23 , 24 ] met all the criteria and were added to the review. The reasons for exclusion were the same as the previous review.

The characteristics, quality, and risk of bias of the included studies are summarized in Table  1 and Supplementary material 2. The studies were conducted in eight different countries: Iran, Ethiopia, Vietnam, Cambodia, Nicaragua, Canada, Germany, and Wales. The study population comprised students aged 10–25 from various educational settings, including schools, colleges, universities, and community organizations. The total sample size across all studies was 7420 participants, with a proportion of female participants ranging from 50 to 100%. The mean age of participants across studies was 15.93 years.

The study design was either randomized controlled trial (RCT), quasi-experimental design, or pre-post evaluation. The intervention was The Guide or a modified version of it. The duration of the intervention ranged from 2 to 12 weeks, with a mean of 8.14 weeks. The total time of the intervention ranged from 5 to 14 h, with a mean of 10.16 h (One of the studies reported the duration of the intervention as 1 day). The intervention was delivered either online or in-person by trained facilitators or teachers.

The outcome measures were validated instruments or scales for mental health literacy or help-seeking attitudes and stigma, such as the Mental Health Literacy Scale (MHL), the Mental Health Knowledge Schedule (MHK), the Mental Health Knowledge and Attitude Scale (MHKAS), the Attitudes Towards Seeking Professional Psychological Help Scale (ATMI), the Mental health knowledge (MHK), the Knowledge and Attitudes to Mental Health Scales (KAMHS) or the Mental Health Knowledge and Awareness Assessment (MHKAA). The Posttest time ranged from immediately after the intervention to 6 months later.

The quality and risk of bias of the included studies were assessed using the QuADS Quality Appraisal [ 16 ]. The overall quality and risk of bias of the studies were moderate to high, with some concerns in domains such as randomization, allocation concealment, blinding, attrition, measurement, reporting, and confounding. The study by Simkiss [ 23 ] in Wales had the highest quality score (97%), while the study by Zare [ 17 ] in Iran had the lowest quality score (61%). A detailed breakdown of these assessments is provided in Supplementary Material 2.

The data from the included studies were synthesized using a narrative approach. The main findings are reported below according to the research questions and hypotheses.

The Table  2 shows the mean change and standard deviation of the outcome measures for the intervention and control groups in six studies. The outcome measures were mental health knowledge, attitudes, literacy, or stigma. The intervention group received The Guide or a modified version of it, while the control group received no intervention, usual care, or another intervention. The table also shows the p-value of the difference between the intervention and control groups, which indicates the statistical significance of the difference.

3.1 Effectiveness of The Guide in improving mental health literacy

Zare [ 17 ] measured it using a self-developed questionnaire and found that the intervention group had a mean change of 54.08 (7.70), while the control group had a mean change of 1.28 (6.09). The difference was statistically significant (p < 0.001). Hassen [ 18 ] measured mental health literacy using the Mental Health Literacy Questionnaire and found that the intervention group had a mean change of 27.41 (19.55), while the control group had a mean change of 20.98 (16.54). The difference was statistically significant (p < 0.05). This result suggests that The Guide improved students’ mental health literacy more than the control group, which received no intervention or usual care.

Nguyen [ 19 ] measured it using the MHL-Knowledge scale and found that the intervention group had a mean change of 0.06 (0.11) in Vietnam and 0.04 (0.09) in Cambodia, while the control group had a mean change of 0.01 (0.07) in Vietnam and − 0.02 (0.08) in Cambodia. The difference was statistically significant in both countries (p < 0.05). Ravindran [ 20 ] measured it using the MHKAS-Knowledge scale and found that the intervention group had a mean change of 2.23 (2.84), while the control group had a mean change of − 1.43 (4.52). The difference was statistically significant (p < 0.001). Milin [ 21 ] measured it using a self-developed scale and found that the intervention group had a mean change of 0.7 (1.47), while the control group had a mean change of − 0.18 (1.48). The difference was statistically significant (p < 0.001). These results suggest that The Guide improved students’ mental health literacy compared to no intervention or usual care.

Simkiss [ 23 ] measured mental health literacy using the Knowledge and Attitudes about Mental Health Scale (KAMHS) and found that the intervention group had a mean change of 0.09 (0.09), while the control group had a mean change of − 0.01 (0.09). The difference was statistically significant (p < 0.05). This result suggests that The Guide improved students’ mental health literacy more than the control group, which received usual care. Freţian [ 24 ] conducted a quasi-experimental pre-post study in Germany with students aged 14–17. The intervention involved The Guide and the Mental Health Knowledge (MHK) scale over a single day. The intervention group displayed a statistically significant mean change in mental health knowledge (p < 0.05).

3.2 Effectiveness of The Guide in improving help-seeking attitudes and stigma

Nguyen [ 19 ] measured them using the Stigma scale and found that the intervention group had a mean change of − 0.09 (0.37) in Vietnam and − 0.66 (0.50) in Cambodia, while the control group had a mean change of − 0.03 (0.39) in Vietnam and − 0.08 (0.52) in Cambodia. The difference was not statistically significant in both countries (p > 0.05). Ravindran [ 20 ] measured them using the MHKAS-Attitudes scale and found that the intervention group had a mean change of 0.54 (1.87), while the control group had a mean change of − 0.28 (1.79). The difference was statistically significant (p < 0.001). Milin [ 21 ] measured them using the Attitudes Towards Mental Illness scale and found that the intervention group had a mean change of 1.3 (2.46), while the control group had a mean change of − 1.17 (2.63). The difference was statistically significant (p < 0.001). These results suggest that The Guide had a mixed effect on improving students’ attitudes and reducing their stigma compared to no intervention or usual care.

3.3 Factors influencing the implementation and sustainability of The Guide

Some studies reported on the factors that influenced the implementation and sustainability of The Guide in different contexts. These factors included:

Mode of delivery The Guide was delivered either online or in-person by trained facilitators or teachers. The mode of delivery affected the accessibility, engagement, and interaction of the students with the program. For example, Nguyen [ 19 ] found that online delivery was more convenient and flexible for the students, but also posed some challenges such as technical issues, low attendance, and limited feedback. Milin [ 21 ] found that online delivery was more effective than in-person delivery in improving mental health knowledge and attitudes, but also required more support and guidance from the teachers. Simkiss [ 23 ] found that online delivery was more acceptable and feasible for the students and the schools, but also needed more resources and infrastructure to ensure the quality and fidelity of the program.

Duration and frequency of the sessions The total number of sessions varied across interventions in different studies, ranging from 2 to 12 weeks (with a mean duration of 7.1 weeks) and from 1 to 14 h (with a mean of 8.9 h). The duration and frequency of the sessions affected the retention, completion, and satisfaction of the students with the program. For example, Zare [ 17 ] found that a shorter duration (6 weeks) and a longer time (9 h) of the sessions resulted in a higher retention rate (95%) and a higher completion rate (90%) than a longer duration (12 weeks) and a shorter time (6 h) of the sessions in another study. Ravindran [ 20 ] found that a longer duration (6 weeks) and a longer time (12 h) of the sessions resulted in a higher satisfaction rate (90%) than a shorter duration (5 weeks) and a shorter time (7.5 h) of the sessions in another study. Freţian [ 24 ] found that a shorter duration (2 weeks) and a shorter time (1 h) of the sessions resulted in a lower dropout rate (5%) and a higher satisfaction rate (95%) than a longer duration (6 weeks) and a longer time (6 h) of the sessions in another study.

Characteristics of the facilitators or teachers The facilitators or teachers who delivered The Guide were either trained professionals or peers who had received training on the program content and methods. The characteristics of the facilitators or teachers affected the quality, fidelity, and effectiveness of the program delivery. For example, Hassen [ 18 ] found that peer educators were more relatable, credible, and engaging for the students than professionals, but also faced some challenges such as lack of confidence, experience, and supervision. Milin [ 21 ] found that teachers who delivered The Guide had more positive attitudes towards mental health than those who did not, but also needed more training and support to deliver the program effectively. Simkiss [ 23 ] found that facilitators who delivered The Guide had more knowledge and skills in mental health than those who did not, but also required more monitoring and feedback to ensure the consistency and quality of the program.

Characteristics of the students The students who participated in The Guide were aged 10–25 from various educational settings and cultural backgrounds. The diverse characteristics of students played a significant role in shaping their engagement with the program, influencing motivation, participation, and subsequent learning outcomes. Nguyen [ 19 ] highlighted this by illustrating that students from Vietnam and Cambodia exhibited varying levels of mental health knowledge, attitudes, and stigma both before and after the program. These differences were closely tied to the distinct cultural values and beliefs surrounding mental health in each region. Milin [ 21 ] found that students who had higher levels of mental health knowledge and lower levels of stigma before the program benefited more from the program than those who had lower levels of knowledge and higher levels of stigma. Freţian [ 24 ] found that students who had lower levels of mental health knowledge and higher levels of stigma before the program showed more improvement in their knowledge and attitudes than those who had higher levels of knowledge and lower levels of stigma.

4 Discussion

The primary objective of this systematic review was to assess the effectiveness of The Guide, a school-based program aimed at enhancing mental health literacy, improving attitudes, and reducing stigma among students aged 10–25. The study followed the PRISMA guidelines and examined ten studies from eight countries, encompassing a diverse range of participants and methodologies.

The review found that The Guide had a positive impact on mental health literacy and a mixed impact on help-seeking attitudes and stigma compared to no intervention or usual care [ 25 ]. The magnitude of the impact varied from small to large, depending on the instrument or scale used and the post-test time. These findings are consistent with previous reviews that have shown that mental health literacy interventions can improve mental health knowledge, attitudes, and behaviors among young people [ 26 , 27 , 28 ]. Mental health literacy is considered a key strategy to facilitate early intervention and prevention of mental disorders, as well as to promote mental health and well-being among young people [ 9 , 29 ]. By improving mental health literacy, young people can enhance their awareness, understanding, and skills related to mental health, reduce stigma and discrimination towards people with mental disorders, and increase their help-seeking efficacy and use of appropriate services [ 9 , 29 , 30 ]. The overall impact of The Guide on mental health literacy outcomes across all studies was moderate, indicating a noticeable improvement in mental health literacy after participating in The Guide.

The review also found that The Guide had a mixed impact on help-seeking attitudes and stigma among students aged 10–25. Help-seeking attitudes, representing the willingness to seek help for mental issues, and stigma, encompassing negative stereotypes and prejudices, are interconnected. The results of this review indicate that The Guide can improve help-seeking attitudes and reduce stigma among some groups of students, but not among others [ 19 , 20 , 21 ]. The overall impact of The Guide on help-seeking attitudes and stigma outcomes across all studies was small, indicating a slight improvement in help-seeking attitudes and a slight reduction in stigma after participating in The Guide. Research exploring why these outcomes vary among students is limited but crucial. Potential factors include cultural and contextual differences influencing perceptions of mental health interventions [ 31 , 32 , 33 ], perceived barriers to seeking help such as stigma and confidentiality concerns [ 34 , 35 ], variability in program implementation quality [ 31 ], and individual differences in developmental stages and personal experiences with mental health [ 31 , 34 ]. These factors suggest the need for further qualitative exploration of students’ perspectives and experiences to optimize the effectiveness of future MHL interventions like The Guide in promoting mental health awareness and reducing stigma among youth.

However, the review also found that the impact of The Guide may vary depending on the context, culture, and characteristics of the students and the facilitators or teachers. The review identified four main factors that influenced the implementation and sustainability of The Guide in different contexts: mode of delivery, duration and frequency of the sessions, characteristics of the facilitators or teachers, and characteristics of the students [ 31 , 32 , 33 , 34 ]. These factors affected the accessibility, engagement, interaction, retention, completion, satisfaction, quality, fidelity, and effectiveness of the program delivery [ 35 ]. The review suggested that The Guide needed to be adapted and tailored to the local context and culture, and that the facilitators or teachers and the students needed to be trained and involved in the planning, delivery, and evaluation of The Guide.

4.1 Limitations

The review has some limitations that should be acknowledged. First, the quality and risk of bias of the included studies were variable, which may affect the validity and reliability of the findings. Second, the heterogeneity of the studies in terms of population, intervention, comparison, outcome, and study design limited the possibility of conducting a meta-analysis or a subgroup analysis. Third, the review only included studies published in English, which may exclude relevant studies published in other languages. Fourth, the review only focused on The Guide or a modified version of it as an intervention, which may not capture other types of mental health literacy interventions that may be effective for young people.

4.2 Implications for practice and research

The systematic review underscores several implications for both practice and research. For practice, The Guide emerges as a valuable tool for advancing mental health education and awareness among young people, while also fostering reductions in stigma and improvements in help-seeking behavior. However, successful adoption and implementation of The Guide necessitate careful consideration of potential barriers and facilitators, including resource availability, participant readiness, alignment with local cultural norms, and robust evaluation mechanisms. Moreover, adequate training and ongoing support for facilitators and teachers are crucial, alongside active engagement of students and stakeholders in all stages of planning, delivery, and evaluation. In terms of research, there is a clear need for more high-quality studies to assess the long-term effects of The Guide on mental health outcomes across diverse demographic backgrounds and settings. Furthermore, future research should explore effective strategies for integrating The Guide into existing educational curricula or policies to ensure sustainability and scalability. Methodologically, there is a call for studies that delve deeper into the mechanisms and moderators influencing The Guide's impact on various mental health outcomes, utilizing more rigorous and standardized methods and measures. Additionally, comparative research that contrasts The Guide with other mental health literacy interventions or control conditions would provide valuable insights into its unique contributions.

5 Conclusion

The systematic review of The Guide, a mental health intervention targeting young people aged 10–25, underscores its positive impact on enhancing mental health literacy and help-seeking attitudes, though effect sizes vary across studies. Factors influencing its implementation and sustainability include delivery mode, session frequency, facilitator characteristics, and student demographics. While this review contributes valuable insights, limitations such as variability in study quality, number, and data heterogeneity highlight the necessity for more robust research efforts. Implications for practice include recognizing The Guide's potential across diverse educational and cultural settings, contingent upon addressing implementation barriers and optimizing facilitator training. Future research should prioritize enhancing measurement validity, exploring long-term effects, and assessing implementation costs to advance both understanding and application of The Guide. Expanding on the potential long-term impacts of The Guide and its scalability in various educational contexts could enrich the conclusion, offering a forward-looking perspective on its sustained effectiveness and broader implications for mental health interventions among young populations.

Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. No datasets were generated or analysed during the current study.

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We are grateful to Golbarg Andaji Garmaroudi for her help in translating this manuscript into English.

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Abouzar Nazari

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Nazari, A., Garmaroudi, G. & Rabiei, M. A systematic review: increasing mental health literacy in students through “The Guide”. Discov Psychol 4 , 96 (2024). https://doi.org/10.1007/s44202-024-00219-1

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Improving mental health literacy in adolescents: systematic review of supporting intervention studies

Affiliations.

• 1 Sirindhorn College of Public Health, Khon Kaen, Thailand.
• 2 Faculty of Public Health, Mahasarakham University, Mahasarakham, Thailand.
• 3 Boromarajonani College of Nursing, Buddhachinaraj, Phitsanulok, Thailand.
• PMID: 32478983
• DOI: 10.1111/tmi.13449

Abstract in English, French

Objective: Mental health literacy (MHL) in adolescents is an important issue as it can lead to early detection and recognition of mental illness. The aim of this systematic review was to explore the effect of supporting interventions on improving MHL in adolescents.

Methods: Systematic literature review by searching the ScienceDirect, Scopus, PubMed, Crochrane and CINAHL databases. Seven of 1107 papers were included in the final review.

Results: Supporting interventions for improving MHL in adolescents could be categorised into school-based and community-based. Both types used an education stand-alone strategy or an education plus contact-based group in their programmes. To provide knowledge of mental illness to adolescents, teaching methods should be interactive and use various media such as group discussion, videos and movies.

Conclusions: School-based and community-based interventions were likely to improve MHL among adolescents. However, further research with objective tool measures is needed to confirm the findings.

Objectif: La littératie sur la santé mentale (LSM) chez les adolescents est un sujet important car elle peut conduire à la détection et à la reconnaissance précoces des maladies mentales. Le but de cette revue systématique était d'explorer l'effet du soutien des interventions sur l'amélioration de la LSM chez les adolescents. MÉTHODES: Analyse systématique de la littérature en recherchant dans les bases de données ScienceDirect, Scopus, PubMed, Crochrane et CINAHL. 7 des 1.107 articles ont été inclus dans l’analyse finale. RÉSULTATS: L’effet des interventions de soutien visant à améliorer la LSM chez les adolescents pourraient être classés en soit du milieu scolaire, soit communautaire. Les deux types ont utilisé une stratégie basée sur l’éducation seule ou sur l'éducation et des contacts dans leurs programmes. Fournir des connaissances de la maladie mentale aux adolescents, les méthodes d'enseignement devraient être interactifs et utiliser divers médias comme la discussion de groupe, des vidéos et des films.

Conclusions: Les interventions en milieu scolaire et communautaires étaient susceptibles d’améliorer la LSM chez les adolescents. Cependant, des recherches supplémentaires avec des mesures d'outils objectives sont nécessaires pour confirmer les résultats.

Keywords: adolescent; community-based intervention; connaissances sur la santé mentale; intervention; intervention communautaire; intervention en milieu scolaire; mental health literacy; revue systématique; school-based intervention; systematic review.

© 2020 John Wiley & Sons Ltd.

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Insights into the effect of light pollution on mental health: focus on affective disorders—a narrative review.

Graphical Abstract

1. Introduction

2. materials and methods, 3.1. literature search results and study description, 3.2. light pollution, sleep, and circadian disruption, 3.3. light pollution and mood disorders: depressive, hypomanic/manic symptoms, and suicidal behaviors, 3.3.1. light pollution, depressive symptoms, and suicidal behaviors, 3.3.2. light pollution and bipolar disorders, 3.4. risk perception related to the effects of light pollution on health, 3.4.1. risk perception of light pollution, sleep disturbances, and affective symptoms.

3.4.2. Factors Influencing Risk Perception of Light Pollution

4. discussion, 5. conclusions, author contributions, institutional review board statement, conflicts of interest.

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Share and Cite

Menculini, G.; Cirimbilli, F.; Raspa, V.; Scopetta, F.; Cinesi, G.; Chieppa, A.G.; Cuzzucoli, L.; Moretti, P.; Balducci, P.M.; Attademo, L.; et al. Insights into the Effect of Light Pollution on Mental Health: Focus on Affective Disorders—A Narrative Review. Brain Sci. 2024 , 14 , 802. https://doi.org/10.3390/brainsci14080802

Menculini G, Cirimbilli F, Raspa V, Scopetta F, Cinesi G, Chieppa AG, Cuzzucoli L, Moretti P, Balducci PM, Attademo L, et al. Insights into the Effect of Light Pollution on Mental Health: Focus on Affective Disorders—A Narrative Review. Brain Sciences . 2024; 14(8):802. https://doi.org/10.3390/brainsci14080802

Menculini, Giulia, Federica Cirimbilli, Veronica Raspa, Francesca Scopetta, Gianmarco Cinesi, Anastasia Grazia Chieppa, Lorenzo Cuzzucoli, Patrizia Moretti, Pierfrancesco Maria Balducci, Luigi Attademo, and et al. 2024. "Insights into the Effect of Light Pollution on Mental Health: Focus on Affective Disorders—A Narrative Review" Brain Sciences 14, no. 8: 802. https://doi.org/10.3390/brainsci14080802

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Published on 14.8.2024 in Vol 11 (2024)

Application of Positive Psychology in Digital Interventions for Children, Adolescents, and Young Adults: Systematic Review and Meta-Analysis of Controlled Trials

Authors of this article:

• Sundas Saboor 1 , MBBS, MPH   ; 
• Adrian Medina 2 , MPH, EdM   ; 
• Laura Marciano 3 , PhD  

1 Department of Health Behavior & Health Education, University of Michigan School of Public Health, Ann Arbor, MI, United States

2 Deptartment of Social & Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA, United States

3 Lee Kum Sheung Center for Health and Happiness, Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA, United States

Corresponding Author:

Laura Marciano, PhD

Lee Kum Sheung Center for Health and Happiness

Department of Social and Behavioral Sciences

Harvard T.H. Chan School of Public Health

677 Huntington Avenue

Boston, MA, 02115

United States

Phone: 1 6175828025

Email: [email protected]

Background: The rising prevalence of mental health issues in children, adolescents, and young adults has become an escalating public health issue, impacting approximately 10%-20% of young people on a global scale. Positive psychology interventions (PPIs) can act as powerful mental health promotion tools to reach wide-ranging audiences that might otherwise be challenging to access. This increased access would enable prevention of mental disorders and promotion of widespread well-being by enhancing self-efficacy, thereby supporting the achievement of tangible objectives.

Objective: We aimed to conduct a comprehensive synthesis of all randomized controlled trials and controlled trials involving children, adolescents, and young adults, encompassing both clinical and nonclinical populations, to comprehensively evaluate the effectiveness of digital PPIs in this age group.

Methods: After a literature search in 9 electronic databases until January 12, 2023, and gray literature until April 2023, we carried out a systematic review of 35 articles, of which 18 (51%) provided data for the meta-analysis. We included randomized controlled trials and controlled trials mainly based on web-based, digital, or smartphone-based interventions using a positive psychology framework as the main component. Studies included participants with a mean age of <35 years. Outcomes of PPIs were classified into indicators of well-being (compassion, life satisfaction, optimism, happiness, resilience, emotion regulation and emotion awareness, hope, mindfulness, purpose, quality of life, gratitude, empathy, forgiveness, motivation, and kindness) and ill-being (depression, anxiety, stress, loneliness, and burnout). PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines were used for the selection of studies and data extraction. Quality assessment was performed following the CONSORT (Consolidated Standards of Reporting Trials) guidelines.

Results: For well-being outcomes, meta-analytic results showed that PPIs augmented the feeling of purpose, gratitude, and hope (Hedges g =0.555), compassion (Hedges g =0.447), positive coping behaviors (Hedges g =0.421), body image–related outcomes (Hedges g =0.238), and positive mindset predisposition (Hedges g =0.304). For ill-being outcomes, PPIs reduced cognitive biases (Hedges g =–0.637), negative emotions and mood (Hedges g =–0.369), and stress levels (Hedges g =–0.342). Of note, larger effect sizes were found when a waiting list control group was considered versus a digital control group. A funnel plot showed no publication bias. Meta-regression analyses showed that PPIs tended to show a larger effect size on well-being outcomes in studies including young adults, whereas no specific effect was found for ill-being outcomes.

Conclusions: Revised evidence suggests that PPIs benefit young people’s well-being and mitigate ill-being symptoms. Digital platforms offer a unique way to address their mental health challenges, although not without limitations. Future research should explore how they work for the needs of the young population and further examine what specific PPIs or combination of interventions is most beneficial with respect to other digital control groups.

Trial Registration: PROSPERO International Prospective Register of Systematic Reviews CRD42023420092; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=420092

Introduction

Mental health problems among children, adolescents, and young adults are a growing public health concern, affecting 10% to 20% of young people worldwide [ 1 ]. According to World Mental Health Report 2022, 970 million people have mental disorders, with 3% to 7% of mental disorders among those aged <10 years, 13.5% to 14.7% among those aged 10 to 19 years, and 14.1% to 14.9% among those aged 20 to 49 years [ 2 ]. Globally, 1 in 7 (14%) people who are aged 10 to 19 years have different mental health conditions, and most of them remain untreated [ 3 ]. In addition, among three-quarters of adults, long-term mental health problems occurred before the age of 24 years [ 1 ]. According to the US Surgeon General’s Advisory Report, from 2009 to 2019, the proportion of high school students with persistent feelings of sadness or hopelessness increased by 40% [ 4 ]. In addition, the mental health conditions of young people faced unprecedented challenges during the COVID-19 pandemic, wherein the risk of depression and anxiety doubled [ 4 ], together with feelings of loneliness [ 5 , 6 ].

Considering the above statistics, enhancing youth well-being is an urgent public health need and concern today [ 7 ]. To date, the field of psychiatry and psychology have primarily addressed challenges in treating mental illness, focusing on therapy access and engagement [ 8 ] only after a symptomatology has occurred. However, there has been less attention on enhancing and protecting mental well-being [ 8 , 9 ] before the onset of mental health issues. Interventions aiming at diminishing mental health problems by using the prevailing disease model of human functioning (ie, ill-being model) largely ignore positive psychological assets such as meaning, courage, compassion, and kindness that could not only relieve ill-being states but also prevent them [ 10 ]. Positive psychology aims to provide a more comprehensive scientific knowledge of the human experience, from positive to negative, and better integrate and complement the illness framework with concepts related to positive mental health and use them at scale to solve public health issues [ 10 ].

Advocating for a more holistic approach to mental health promotion and expanding the field’s focus to include strategies for improving mental well-being are crucial to boost intervention effectiveness, prevent mental illness and relapse, and broaden our understanding of how to support individuals in flourishing and improving their overall quality of life [ 9 ]. Tomé et al [ 11 ] conducted a systematic review on 13 studies, focusing on children and adolescents aged 0 to 18 years who had been a target audience for mental health and well-being promotion interventions and suggested that preventive school-based interventions can reduce the onset and progression of clinical disorders and promote good mental health. Another systematic review and meta-analysis of 16 studies concluded that people with severe mental illness benefit from positive psychology interventions (PPIs) in terms of enhancing mental health [ 12 ]. Williams et al [ 13 ] proposed in their systematic review that social interventions to increase positive emotions for people diagnosed with mental health disorders are suitable and effective adjuncts to mental health treatment.

Hence, in this systematic review and meta-analysis, we aimed to focus on digital interventions based on positive psychology as a promising option to promote well-being and prevent mental health issues in a population (children, adolescents, and young adults) that is not at a high risk of developing such issues.

Positive Psychology Framework

According to the American Psychological Association, positive psychology is defined as “a field of psychological theory and research that focuses on the psychological states (e.g., contentment, joy), individual traits or character strengths (e.g., intimacy, integrity, altruism, wisdom), and social institutions that enhance subjective well-being and make life most worth living” [ 14 ]. It is the scientific study of optimal functioning that identifies skills and strengths so that an individual or a community can thrive [ 15 ]. Positive psychology complements and extends the ill-being framework: PPIs focus on the science of positive mental states and behavioral patterns to improve quality of life [ 16 , 17 ]. Positive psychology involves the promotion of well-being differentiated between hedonic well-being, focusing on happiness, pleasure attainment, and pain avoidance, and eudaimonic well-being, related to meaning, self-realization, and full functioning of the person [ 18 ]. By doing so, positive psychology solves problems by identifying and leveraging individual and societal strengths [ 19 ]. Also, positive psychology enhances the importance of flourishing, a construct that encompasses positive emotions and relationships, engagement, meaning, and accomplishments directly or indirectly related to different dimensions of well-being, including psychological, emotional, social, and subjective [ 20 ].

Martin EP Seligman, the father of positive psychology, introduced 5 dimensions essential for well-being known as the PERMA model: positive emotions, engagement, relationships, meaning, and accomplishment [ 21 , 22 ]. Positive emotions (eg, joy, interest, contentment, and love) serve as markers of flourishing and optimal well-being [ 23 ]. Engagement is the extent of use and a subjective experience characterized by interest, affect, and attention [ 24 ]. Positive relationships can be regarded as strong connections with family and friends, developing a sense of belonging [ 25 ]. Meaning is understood as coherence, purpose, and a sense of life’s inherent value, making it worth living [ 26 ]. Accomplishment refers to achievement, mastery, and competence [ 27 ].

Digital PPIs

On the basis of positive psychology theories and empirical research, PPIs aim to ameliorate well-being and health outcomes by increasing positive feelings, healthier lifestyle behaviors, and better cognitive functioning [ 28 ]. PPIs promote positive well-being outcomes, especially in people dealing with stress, by fostering positive daily emotions, providing people with stress-free time, mindful attention and positive cognition, and strengthening social relationships based on the Positive Pathways to Health theoretical model [ 29 - 31 ]. This theoretical model posits that PPIs promote physical and psychological well-being for people dealing with stress by elevating positive emotions experienced in their daily lives [ 30 ]. PPIs rely on elements such as optimism, spirituality, hopefulness, happiness, gratitude, creativity, meaning, and purpose [ 32 ].

From a public health perspective, PPIs can serve as effective mental health promotion tools to reach large target audiences, which would be challenging to reach otherwise. PPIs can be used as preventive and easily accessible tools that can promote well-being at scale by building self-efficacy and reinforcing the effects of meeting concrete goals [ 33 ]. Health promotion strategies can address complex mental health issues, treat preclinical and underdiagnosed cases, and prevent the recurrence of health problems to sustain health networks [ 34 ]. These strategies bolster public policies such as providing employment opportunities and antidiscriminatory laws, establishing supportive environments through interventions such as parenting programs, strengthening community action through initiatives such as media campaigns and research, and improving health services such as depression screening, all aimed at enhancing health and well-being [ 10 ].

Although mental health problems are a growing public health concern among youth, research on the impact of digital PPIs on this population remains limited. Prior reviews primarily addressed conventional interventions, such as in-person therapies within clinical settings and nonclinical settings [ 35 - 38 ]. However, considering the ongoing digitalization of health care, web-based resources and mental health applications have emerged as new avenues for young individuals to access health care services. Surprisingly, there is a notable absence of previous reviews exclusively focusing on digital PPIs for this demographic.

In previous reviews, individual meta-analyses for interventions were assessed for behavioral interventions [ 39 ] and ecological momentary interventions [ 40 ]. Other meta-analyses were performed for well-being components individually, for example, optimism [ 41 ], anxiety [ 42 , 43 ], depression [ 44 - 48 ], well-being [ 46 , 47 , 49 ], employee or work-based well-being [ 50 - 52 ], happiness [ 49 ], and school-based well-being [ 53 ]. However, previous reviews and meta-analyses excluded studies that did not mention outcome measure of well-being [ 54 ]; had no restriction on age groups [ 47 , 55 ]; or included only adults [ 56 , 57 ] or clinical population (eg, cardiovascular disease, psychiatric or somatic disorder, medical patients, schizophrenia, severe mental illness, and chronic pain) [ 12 , 42 , 58 - 61 ]. Although these reviews provide in-depth analysis of the effects of PPIs, the effects of digital PPIs on children, adolescents, and young adults have not been consistently summarized. Moreover, previous reviews mainly included traditional interventions (eg, cognitive therapy or cognitive behavioral therapy [CBT], mindfulness CBT, face-to-face group therapies and meditation, mainly among college students, young community members, or pediatric clinical settings) [ 41 , 47 , 62 ]; however, with the digitalization process, web-based resources and mental health apps are becoming the new way for youth to access health services. However, no previous reviews focused only on digital PPIs. Finally, when it comes to included studies, few reviews and meta-analyses included design such as randomized controlled trials (RCTs) and controlled trials (CTs) [ 41 , 47 , 62 ].

To overcome the abovementioned limitations, our objective was to comprehensively synthesize all RCTs and CTs conducted with young population (ie, children, adolescents, and young adults), encompassing both clinical and nonclinical populations, in order to assess the global effectiveness of digital PPIs on individuals in this age group holistically, without differentiation of prevention and treatment. In particular, we aimed to carry out a systematic review and meta-analysis including both clinical and nonclinical population to determine the efficacy of digital PPIs by considering if digital PPIs maintain health (by improving well-being constructs of compassion, life satisfaction, optimism, happiness, hope, resilience, etc or by reducing ill-being constructs of depression, anxiety, stress, loneliness, burnout, etc) and if there is any difference with respect to other (digital) control conditions.

In this study, we described study characteristics, theoretical background of the PPIs, quality assessment of the studies, the diverse range of PPIs used by the studies, the well-being and ill-being outcomes of these PPIs, and the meta-analytic results for the outcomes.

This systematic review and meta-analysis followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines [ 63 ].

Study Sources and Searches

In total, 9 electronic databases (Communication & Mass Media Complete, Psychology and Behavioral Sciences Collection, PsycINFO, CINAHL, ERIC: Education Resource Information Center, MEDLINE Proquest, ProQuest Sociology, Web of Science [ISI Web of Knowledge], and MEDLINE PubMed) were searched up to January 12, 2023 ( Textbox 1 ).

All citations were imported into Zotero reference manager (Corporation for Digital Scholarship) to automatically remove any duplicates. An additional hand search was carried out by scanning the references of relevant review articles identified along with all gray literature in Google Scholar until April 2023.

• Online* OR internet* OR digital* OR smartphone* OR social media OR EMI* OR EMA* OR in-situ OR ecological momentary assess* OR ecological momentary intervention* OR ESM* OR experience sampling* OR ambulatory assess* OR trace data OR chatbot* OR artificial intelligence* OR AI* OR conversational agent* OR chatterbot* OR virtual agent*
• positive psychology* OR positive psychotherapy* OR kindness* OR optimism* OR gratitude* OR happ* OR flourish* OR satisfaction* OR optimis* OR strength* OR forgiveness* OR positive relationship* OR savoring* OR altruism* OR gift* OR meaning* OR purpose* OR hedon* OR eudaimon* OR compassion* OR hop*
• Interven* OR treatment* OR therap* OR RCT* OR random* OR trial* OR control*

Study Selection

After duplicates were removed from the initial list of extracted publications, 2 authors independently completed title and abstract screening. For title and abstract screening, we included studies that (1) were either RCTs or CTs; (2) had the intervention that was mainly based on positive psychology (eg, gratitude, hope, optimism, etc) as the main component (for interventions, we included psychotherapies, therapy, interventions, mindfulness, training, exercise, and similar); and (3) included children, adolescents, and young adults with a mean age of <35 years. Although mental health disorders and treatment vary among this diverse age range, aggregating mental health across this range is appropriate due to similarities in mental health challenges and responses to interventions observed across different developmental stages within this age range. The proportion of individuals with the onset of any mental disorders before the ages of 14, 18, and 25 years were 34.6%, 48.4%, and 62.5%, respectively, and the peak age was 14.5 years [ 64 ]. Separation anxiety disorder, specific phobia, and social phobia have their mean onset before the age of 15 years, whereas agoraphobia, obsessive-compulsive disorder, posttraumatic stress disorder, panic disorder, and generalized anxiety disorder began, on average, between 21.1 and 34.9 years [ 65 ]. The mean age of <35 years is in line with the upper age limit of the early psychosis paradigm reporting on universal interventions or selective interventions [ 66 - 68 ]. In addition, studies needed to (4) include from both clinical and nonclinical population and (5) be carried out web-based or digital or through smartphone-based interventions. We excluded studies with face-to-face interventions and psychotherapy only of any kind, including digital or web-based or smartphone based. We also excluded studies in which positive psychology was not the main focus of the intervention (eg, when positive psychology was an additional component of a mindfulness-based intervention or CBT or other therapies). Moreover, we removed studies with no experimental design or control group and studies where the average age of the sample was >35 years or the focus was on caregivers. We further excluded conference abstracts, theses, books, or book sections. We excluded studies that were not in the English language. If at least 1 of the 2 authors decided to retain an article during the title and abstract screening process, we included it in the full-text screening. Discrepancies after full-text screening were solved through a consensus meeting with a third author.

Data Extraction

For each included study, we extracted information about the article (first author, year of publication, journal, and title); the study (country where the study was conducted, study design, sample size of experimental group, presence of control group, type of control group, sample size of control group, type of sampling, and attrition rates); and characteristics of the sample (including clinical or general population with details, ethnicity, gender distribution, and age). For intervention, we extracted information regarding the kind of positive intervention and its details, reference theory of the intervention, the type of activity and intervention, the setting of the intervention with details, the duration of the intervention, number of follow-ups and the time of the follow-ups, and data collection survey details. Outcomes included different ill-being and well-being constructs. Finally, we collected information on intervention evaluation, statistical analyses, and results to be converted into effect sizes.

Quality Assessment

In total, 2 authors independently assessed the quality of the studies according to the CONSORT (Consolidated Standards of Reporting Trials) guidelines [ 69 ], and a sum score was created, with a higher score indicating methodological quality. CONSORT guidelines are better suited for assessing the quality of study reporting for RCTs and CTs as recommended by Altman [ 70 ] and Versluis et al [ 40 ]. As a form of quality assessment, we checked whether studies explicitly mentioned (1) title and abstract; (2) introduction (including background and objectives); (3) methods (including trial design, participants, interventions, outcomes, sample size, randomization-sequence generation, randomization-sequence allocation concealment, randomization-implementation, blinding, and statistical methods); (4) results (including participants flow diagram, participant flow, recruitment, baseline data, number analyzed, outcomes and estimations, ancillary analyses, and harms); (5) discussion (including limitations, interpretations, generalizability, and registration); and (6) other information such as funding and protocol. For each paper, we rated if each criterion of the quality assessment was 0=“absent” and 1=“completely met.” Then, we calculated a sum score of all criteria. The maximum score obtainable for each study was 34.

Data Synthesis and Analysis

We conducted the meta-analysis using “meta” [ 27 ] packages in R statistical software (R Foundation for Statistical Computing). A standardized mean difference approach was used as a measure of effect size using the Hedges adjusted g , which is similar to Cohen d , but it includes an adjustment for small sample bias [ 71 ]. All the analyses were implemented using the inverse-variance method with a random effects model using the Hartung-Knapp-Sidik-Jonkman adjustment [ 55 ] to limit the effect of studies’ diversities. According to Cohen [ 72 ], a final effect falling in the ranges of 0 to 0.2, 0.3 to 0.5, and 0.6 to 0.8 was interpreted, respectively, as small, moderate, and large. Meta-analyses were run for well-being and ill-being outcomes separately, with additional specifications of the type of outcome. In particular, we further grouped well-being and ill-being outcomes in the following dimensions: body image related, cognitive bias/flexibility, compassion, coping, mindset predisposition, mood/affect/emotions, purpose/gratitude/hope, satisfaction/quality of life, stress, and 3 funny things/3 good things. A complete list of well-being and ill-being outcomes categorized in each of the abovementioned dimensions is reported in Table 1 .

The heterogeneity of the effect size was computed with the between-study variance τ 2 and the Hartung-Knapp-Sidik-Jonkman adjustment, which allows to control for errors due to diversities in the sample sizes [ 73 ]. Heterogeneity level was interpreted as low (25%), moderate (50%), and high (75%), according to Higgins et al [ 74 ]. Potential publication biases were assessed by both funnel plots and Egger regression test for funnel plot asymmetry [ 75 , 76 ]. In addition, influence analyses were conducted to test if a single study accounted for a significant part of the variance in the final effect. Additional subgroup analyses were conducted to test if the effect size differed depending on the control group (waiting list vs digital control) when possible ( k ≥2 in each subgroup). To further explore the effect of age, meta-regression analyses were performed by different age categories (ie, children, adolescents, and young adults or a combination of these categories). In contrast to what we anticipated in our study protocol registered in PROSPERO, we could not run subgroup analyses to differentiate the effect of specific interventions due to the paucity of studies using the same PPIs.

The study selection process is reported in the PRISMA flowchart ( Figure 1 ). The initial database and hand search returned 1344 publications, of which 729 (54.24%) were duplicates, which were removed. After title and abstract screening of 615 (45.76%) records, we assessed 120 full-text articles for eligibility. We then excluded 85 (70.8%) articles, resulting in a qualitative assessment of 35 (29.2%) articles and a meta-analysis of 18 studies. The reasons for exclusion include out of age range or the age was not explicitly mentioned (n=51, 60%), positive psychology was not the main focus of the intervention (n=7, 8%), the CBT was internet based (n=3, 4%), the intervention was not web based (n=2, 2%), the trials were not RCTs (n=11, 13%) or CTs (n=1, 1%), the intervention was hybrid (n=1, 1%), repetitions (n=5, 6%), and the research was still ongoing (n=4, 5%). Cohen κ was calculated as a measure on intercoder reliability, and it was excellent (κ=0.95).

Study Characteristics

The systematic review is based on 35 studies ( Multimedia Appendix 1 [ 77 - 94 , 96 - 112 ]). Overall, the analytical sample amounts to 7341 participants, of which 19 studies (54%) mentioned young adults aged 20 to 35 years of age; 8 studies (23%) were focused on children, adolescents, and young adults aged up to 20 years of age; and 3 studies (9%) mentioned children, adolescents, and adults aged up to 35 years. A total of 3 studies (9%) mentioned young adults and adult participants, while 1 (3%) study mentioned children, adolescents, and adults, and 1 study (3%) mentioned all age groups, that is, children, adolescents, young adults, and adults. Gender distribution for males and females has been mentioned separately in 28 (80%) studies, while 7 (20%) studies only mentioned the percentage of female participants [ 79 , 85 , 87 , 96 - 99 ]. A total of 27 studies (77%) mentioned the ethnicity of the participants.

A total of 13 (37%) studies were conducted in Europe (Sweden, Slovakia, London, the Netherlands, Norway, Turkey, Finland, Germany, Greece, Spain, and Austria); 11 (31%) studies were conducted in North America (both United States and Canada combined); 7 (20%) in Asia (Turkey, Singapore, India, China, Japan, and South Korea); 3 (9%) in Australia, and 1 (3%) in Africa (Tunisia). The duration of the interventions varied from 1 week to a maximum of 12 weeks. Of all the studies, 23 (66%) studies had follow-up assessments. In particular, 19 (54.3%) studies had 1 follow-up, 2 (6%) studies had 2 follow-ups, and 2 (6%) had 3 follow-ups ( Table 2 ). The duration of the follow-ups ranged from 2 to 12 weeks. The range of the interventions was 11 weeks (from 1 to 12 weeks), while the median duration was 12 weeks.

Data from the participants were collected through web-based surveys and questionnaires as well as in person. A total of 26 (74%) studies used convenience sampling techniques, and 7 (20%) studies used purposive sampling procedures. In 1 (3%) study, experience sampling was used, while in 1 (3%) study, the details of sampling were not clearly mentioned; 29 (83%) studies conducted the trial on the general population (nonclinical), while 6 (17%) studies conducted the trial on clinical population (ie, individuals who engaged in nonsuicidal self-injury, scored high on scales of depression, had anxiety and stress, had mental disorder or psychological stress, had autism spectrum disorder, were undergoing active cancer treatment). A total of 28 (80%) studies conducted the intervention in a web-based setting. In addition, 4 (11%) studies conducted the intervention through smartphone-based applications or SMS text messaging; 1 (3%) study used a hybrid setting, and 1 (3%) conducted the intervention in a telehealth setting [ 100 , 101 ]. Interestingly, 1 (3%) study conducted the intervention through Instagram, and 1 (3%) study used the Vivibot chatbot [ 89 , 102 ].

a RCT: randomized controlled trial.

b Not applicable.

c iACT: internet-based acceptance and commitment therapy.

d CFI: compassion-focused therapy-based intervention.

e REBT: rational emotive behavior therapy.

Theoretical Background

The broaden-and-build theory was the widely used theory in 5 (14%) studies [ 84 , 89 , 91 , 99 , 103 ]. The broaden-and-build theory of positive emotion states that certain discrete positive emotions, for example, joy, contentment, pride, and love, share the ability to broaden momentary thought-action repertoires of people and build their enduring personal resources, ranging from physical and intellectual resources to social and psychological resources [ 113 ]. Other studies frequently mentioned in the articles included acceptance and commitment theory [ 79 ] (oriented toward the development of psychological flexibility), affect theory [ 80 ] (emotions generating weak or strong ties to relations), attachment theory [ 80 , 92 , 100 ] (individuals born with innate behaviors function to attract proximity to attachment figures), Eisenberg’s theory of parent emotion socialization [ 104 ] (parents’ emotion socialization behaviors driving children’s emotion socialization), emotion-focused therapy theory [ 105 ] (integrating person-focused care with modern emotion theory), motivational theory of life span development (Heckausen’s theory) [ 97 ] (role of individual in lifespan development), Bandura’s self-efficacy theory [ 106 ] (belief that one can execute needed steps to achieve a goal), social mentality theory [ 92 , 100 ] (both care-seeking and caregiving mentalities are activated when one is being self-compassionate and reassuring), embodiment theory [ 87 ] (psychological processes influenced by body), self-determination theory [ 103 ] (internalizing regulation and self-regulation), theory of mindfulness [ 107 ] (being actively engaged is beneficial for a rigid and judgmental mindset), Festinger’s social comparison theory [ 102 ] (based on social comparison), stress and coping theory [ 89 ] (coping with stressful situations), and humor theory [ 90 ] (cognitive view of humor).

Among all 35 articles, the summary score of the quality assessment ranged from 12 [ 78 ] to 29 [ 77 , 102 ], with a median of 22.5 points. Among all criteria, most of the papers (31/35, 89%) did not report all important harms or unintended effects in each group and protocol of the full trial. Blinding was either not performed or not explicitly reported by 86% (n=30) of the studies. Also, most papers (26/35, 74%) lacked more detailed information about any changes to trial outcomes after the trial started with reasons, and 24 (69%) studies lacked information regarding the mechanism used to implement the random allocation sequence (such as sequentially numbered containers) and the description of any steps taken to conceal the sequence until interventions were assigned; 23 (66%) studies did not report explanation of any interim analyses and stopping guidelines, and 22 (63%) studies did not mention essential changes to methods after trial commencement (such as eligibility criteria) with reasons. Finally, 21 (60%) studies did not calculate both absolute and relative effect sizes for binary outcomes. A detailed description of each study evaluation is reported in Multimedia Appendix 2 [ 77 - 94 , 96 - 112 ].

PPIs Used in the Studies

A diverse range of PPIs were conducted among the study participants and is reported in detail in Multimedia Appendix 3 [ 77 - 94 , 96 - 112 ].

Web-Based Meditation and Mindfulness

Drabu et al [ 78 ] used web-based, self-compassion–based, guided meditation for nonsuicidal self-injury. Krifa et al [ 77 ] experimented with a web-based multicomponent intervention that included lectures, expert videos, psychoeducation, and positive psychology practices to assist Tunisian students with mental health. Kelman et al [ 82 ] compared web-based compassion mind training and CBT for perinatal and pregnant women. Beshai et al [ 81 ] used web-based psychoeducational videos, guided meditations, and exercises to reduce anxiety and depression. Halamová et al [ 105 , 108 , 109 ] studied self-compassion and self-criticism through various web-based and smartphone-assisted exercises. Pizarro-Ruiz et al [ 107 ] conducted guided mindfulness sessions via a smartphone app (Aire Fresco). Gu et al [ 92 ] experimented on Chinese students to mitigate depression and anxiety through web-based individual counseling sessions regarding mindfulness meditation (MP3 files).

Positive Psychology and Self-Compassion

Lennard et al [ 79 ] provided web-based self-compassion training for mothers. Drozd et al [ 110 ] experimented with an internet-based program, “Better Days,” which included psychoeducational exercises to increase happiness. Halamová et al [ 111 ] explored emotion-focused training and loving-kindness meditation. Galante et al [ 99 ] practiced loving-kindness meditation through web-based videos. Webb et al [ 87 ] used a web-based yoga program to improve body image satisfaction and self-compassion. Nawa and Yamagishi [ 103 ] assessed academic motivation using journal writing and web-based self-assessments, including gratitude and other daily life aspects. Brouzos et al [ 88 ] tested the “Staying Home—Feeling Positive” web-based PPI during the COVID-19 pandemic. Andersson et al [ 80 ] provided compassion mindset intervention training via smartphone app among university students. Alexiou et al [ 93 ] assessed burnout and depression among Greek health care professionals by conducting a PPI. Manicavasagar et al [ 94 ] used “Bite Back,” a multicomponent web-based positive psychology to increase well-being among young adults.

Gratitude and Acts of Kindness

Chilver and Gatt [ 96 ] explored self-compassion and acts of kindness through web-based modules. Hussong et al [ 104 ] examined parent-child gratitude conversations using web-based tools. Tagalidou et al [ 90 ] used web-based humorous diary writing techniques to address happiness and depression.

Optimism and Positive Emotion

Sergeant and Mongrain [ 85 ] analyzed optimism among participants through web-based diary writing exercises. Tay [ 106 ] assessed a web-based Hope, Optimism, and Positive Emotion intervention. Sampson et al [ 102 ] used Instagram images to assess body, facial, and smile dissatisfaction. Koydemir and Sun-Selışık [ 84 ] analyzed optimism among participants by using alternating web-based diary writing exercises. Hamm et al [ 97 ] focused on improving goal engagement and optimism among university students.

Relationship Satisfaction and Acceptance

Kappen et al [ 83 ] assessed relationship satisfaction and partner acceptance through web-based psychoeducation. Qu et al [ 101 ] analyzed sensory social routines, attention, dyadic engagement, and nonverbal communication in children with autism using synchronous group-based parent coaching sessions via telehealth.

Purpose and Well-Being

Mahalik et al [ 112 ] assessed the Father Project webpage’s intervention for fathers’ sense of purpose. Paetzold et al [ 100 ] aimed to enhance resilience through web-based ecologic momentary interventions and face-to-face sessions. Lappalainen et al [ 86 ] used ACT intervention to increase self-compassion skills and psychological flexibility during the COVID-19pandemic. Bronk et al [ 91 ] conducted the Purpose Toolkit and Gratitude Toolkit to increase a sense of purpose among participants. Greer et al [ 89 ] studied psychological well-being among patients with cancer using Vivibot, a chatbot designed to deliver positive psychological skills. Daugherty et al [ 98 ] used a smartphone app for hope and well-being.

Digital Control Versus Waitlist Control

The control groups were categorized into 2 groups: digital controls (15/35, 43%) and waitlist controls (19/35, 54%; Table 2 ). Digital controls involved some form of digital or web-based interaction but did not include the full intervention content. They had access to certain activities or features but did not receive the complete intervention that the experimental group received. For example, digital control groups included audio recording; video watching; internet-based communication [ 78 , 81 , 82 ]; psychoeducation; web-based daily registry of relationship experiences; web-based diary writing activities without positive psychology components; and digital placebo activities (writing daily events, early memories, and life events) [ 83 , 85 , 93 , 94 ]. Other control measures included elements of positive psychology that differed from the focus of the intervention (the digital control group had identical initial app assessment as the intervention group but did not receive the complete treatment or they had access to a website featuring inspirational phrases) [ 96 , 98 , 99 , 106 ]. In other cases, the control group even performed daily self-evaluations without an equivalent active task, downloaded the Lumosity smartphone app, or used neutral Instagram images of nature [ 101 - 103 , 107 ].

The waitlist controls referred to the control groups in which participants did not receive the active intervention during the initial phase of the study but were promised or scheduled to receive it at a later time. The waitlist control group participants do not receive the full intervention immediately and instead are placed on “waitlist” to receive the intervention after a specified waiting period. RCT control groups either received no treatment or were given access to full digital intervention content after the trial. Among the 35 studies, 1 (3%) study did not explicitly mention the category of the control group [ 88 ].

Outcomes of PPIs

Outcomes were related to both ill-being and well-being components ( Table 1 ). In particular, 27% (15/18) of studies focused on ill-being, among others prominently including depression (11/15, 73%), anxiety (9/15, 60%), stress (8/15, 53%), and loneliness (3/15, 20%) using measures such as the Depression, Anxiety, and Stress Scales, the Generalized Anxiety Disorder scale, the short and long forms of the Spielberger State-Trait Anxiety Inventory, and De Jong Gierveld Loneliness Scale.

Well-being outcomes included compassion (6/18, 33%), satisfaction (7/18, 39%), optimism (1/18, 6%), happiness (3/18, 17%), resilience (1/18, 6%), emotion regulation and emotion awareness (6/18, 33%), hope (3/18, 17%), mindfulness (2/18, 11%), purpose (1/18, 6%), quality of life (1/18, 6%), gratitude (1/18, 6%), empathy (1/18, 6%), forgiveness (1/18, 6%), motivation (1/18, 6%), and kindness (1/18, 6%) using the Self‐Compassion Scale (Self‐Compassion Scale‐Short Form), Satisfaction with Life Scale, Life Orientation Test-Revised, Authentic Happiness Inventory, Connor-Davidson Resilience Scale, Profile of Emotional Competence, Snyder Hope scale, The Five Facet Mindfulness Questionnaire-15, Claremont Purpose Scale, “Psychological Health” and “Social Relationships” subscales of WHO Quality of Life-Brief Version, Gratitude Questionnaire, Interpersonal Reactivity Index, Heartland Forgiveness Scale, and Chinese Compassion Scale.

Both ill-being and well-being included components of self-criticism and self-reassurance (6/18, 33%), well-being (both positive and negative; 5/18, 28%), positive and negative effect (4/18, 22%) using Forms of Self-Criticism and Reassuring Scale, Warwick-Edinburgh Mental Well-being Scale and Positive and Negative Affect Scale.

Meta-Analytic Results

Meta-analyses on well-being outcomes showed that PPIs improved purpose, gratitude, and hope with a medium-to-large effect size ( k =12; Hedges g =0.555, 95% CI 0.348-0.761; P <.001; I 2 =70%). Only 1 (%) study involved a digital control group, for which the reported effect was significantly smaller (Hedges g =0.09). In addition, PPIs augmented the levels of compassion ( k =13; Hedges g =0.447, 95% CI 0.210-0.684; P =.001; I 2 =62%), with no significant differences ( P =.34) between the waiting list ( k =11; Hedges g =0.356) and the digital control group ( k =2; g =0.670). In addition, PPIs augmented the positive coping behaviors ( k =6; Hedges g =0.421; 95% CI 0.072-0.770; P =.003; I 2 =72%) with a medium effect size. PPI interventions also improved body image–related outcomes with a medium effect ( k =7; Hedges g =0.238, 95% CI 0.090-0.388; P =.007; I 2 =0%). A small-to-medium effect was found for mindset predisposition ( k =13; Hedges g =0.304, 95% CI 0.072-0.537; P =.02; I 2 =74%), with a significant difference between the control groups ( P =.01). In particular, effect size was larger and significant when a waiting list ( k =6; Hedges g =0.534) was included as the control group when compared with the digital controls ( k =7; Hedges g =0.092). Also, a small-to-medium effect was also found for the variable 3 funny things/3 good things ( k =8; Hedges g =–0.206, 95% CI –0.328 to –0.083; P =.005; I 2 =0%) with all studies including the waiting list control groups. A nonsignificant effect was found for cognitive flexibility ( k =7; Hedges g =0.054, 95% CI –0.265 to 0.372; P =.69; I 2 =75%) and mood/affect/emotions ( k =8; Hedges g =0.364, 95% CI –0.120 to 0.849; P =.12; I 2 =81%), the latter with no difference in the control groups ( P =.40) although participants in the waiting list showed a larger effect size ( k =5; Hedges g =0.570) when compared with the digital control ( k =3; Hedges g =0.088). Also, satisfaction and quality of life ( k =7; Hedges g =0.338, 95% CI –0.119 to 0.793; P =.12; I 2 =81%) showed a nonsignificant effect, with no differences between subgroups ( P =.65; Figure 2 ).

Ill-being outcomes were less represented in the included studies ( Figure 3 ). Meta-analyses showed a large negative effect for the reduction of cognitive biases ( k =14; Hedges g =–0.637, 95% CI 1.309 to –0.036; P =.05; I 2 =94%), with no group differences between the waiting list and the digital control group ( P =.54), although once again effect sizes tended to be larger when a waiting list ( k =7; Hedges g =–0.799) was considered with respect to digital control groups ( k =5; Hedges g =–0.405). PPIs showed a medium-to-large effect on the reduction of negative emotions and mood problems ( k =30; Hedges g =–0.369, 95% CI –0.513 to –0.225; P <.001; I 2 =60%). Interestingly, subgroup differences showed that the effect size was significantly ( P =.03) larger for studies including a waiting list ( k =21; Hedges g =–0.456) when compared with studies including digital control groups ( k =9; Hedges g =–0.200). PPIs also diminished stress levels ( k =8; Hedges g =–0.342, 95% CI –0.677 to –0.007; P =.045; I 2 =81%), with no significant differences in the effect size ( P =.35) between studies including a waiting list ( k =5; Hedges g =–0.441) versus digital control groups ( k =3; Hedges g =–0.157). A very large effect was found for coping ( k =3; Hedges g =–0.939,95% CI –1.151 to –0.728; P =.003; I 2 =0%); however, interpretation of this result would be limited due to the low number of studies. While the effect sizes were not significant for body image–related outcomes ( k =4; Hedges g =–0.305, 95% CI –0.851 to –0.240; P =.17; I 2 =17%) and 3 funny things/3 good things ( k =6; Hedges g =–0.048, 95% CI –0.289 to –0.192; P =.63; I 2 =28.5%).

Funnel plots were symmetrical for the overall meta-analysis of both the well-being and ill-being outcomes ( Figures 4 and 5 ), and the regression test for funnel plot asymmetry was not significant in both cases as well, thus confirming the absence of publication biases. Influence analyses revealed that that a single study did not account for a significant part of the variance in the final effect.

Finally, meta-regression analyses showed that PPIs tended to show a larger effect size on well-being outcomes in studies including young adults (β=.322; P =.008), while no specific effect was found for ill-being outcomes. Figures S1 and S2 in Multimedia Appendices 4 and 5 report additional detailed information of each meta-analysis.

Principal Findings

In our systematic review and meta-analysis of 35 studies and 18 studies, respectively, we examined the impact of digital interventions grounded in positive psychology on the well-being and ill-being of children, adolescents, and young adults. Our results showed 4 main findings. First, when it comes to well-being outcomes, PPIs enhanced various facets of well-being, notably purpose, gratitude, and hope, with a medium-to-large effect, as well as compassion, positive coping (eg, coping with humor), and body image–related concerns with a medium effect. Smaller effects were found for mindset predisposition and 3 funny things/3 good things, while PPIs did not seem to improve mood and positive emotions, satisfaction and quality of life, and cognitive flexibility. This aligns with prior investigations of PPIs in traditional settings [ 17 ]. These interventions seem to provide robust support in enhancing aspects of well-being that involve an individual’s outlook on life and their ability to foster a sense of personal achievement and satisfaction.

Second, when we looked at ill-being outcomes, the picture was different. In particular, the larger effect was found for diminishing cognitive biases, including self-criticism and fears, followed by a decrement in negative emotions and mood problems, especially when participants of the experimental group were compared with the waiting list. Hence, PPIs can be a useful tool in reducing cognitive biases typical of, for example, mood problems, and stress levels [ 83 ]. To note, it is crucial to differentiate the control groups in the analyses. Indeed, although we could not make subgroup comparisons for all the outcomes due to the paucity of studies in each group, we showed that effects sizes tended to be consistently larger in studies including a waiting list rather than a digital control group (eg, including some sort of web-based interactions). Digital control groups, such as those engaging in nonspecific digital activities or using general health apps, could serve as valuable benchmarks. This would allow us to distinguish the specific contributions of PPIs from broader digital engagement effects. Such comparisons would shed light on the specific psychological mechanisms activated by PPIs compared with general digital exposure, helping to isolate the unique elements of PPIs that contribute to improved well-being outcomes.

Third, several studies within our review highlighted the efficacy of interventions tailored to specific settings and contexts. For example, digital interventions aimed at fostering hope and optimism were found to be particularly beneficial for college students prone to failure and those with low optimism levels [ 63 ]. Also, interventions focusing on self-compassion were found to be especially beneficial for mothers of infants, offering them a respite from the unique challenges of early parenthood [ 61 ]. By contrast, interventions that used smartphone delivery, such as the hope intervention, showcased the adaptability and accessibility of digital platforms, making well-being practices more integrated into daily routines [ 64 ]. Another noteworthy finding was the positive impact of multicomponent PPIs delivered web-based for subjective well-being of young adults [ 62 ].

Fourth, when age was considered as a moderator, studies with young adult participants showed larger effect sizes in the meta-analysis with well-being outcomes, but no differences emerged with respect to ill-being indicators. This is an important consideration since young adults might be more inclined to understand the importance of promoting well-being and thus more willing to take part in interventions and experiencing the positive effects. However, while some demographic groups appeared to benefit more from certain types of interventions, the overall evidence was not strong enough to conclusively determine that these effects were consistently replicated across different age groups, such as children, adolescents, or young adults [ 17 , 31 ].

Finally, the variability in intervention efficacy highlights the critical role of intervention design and implementation in achieving desired outcomes. This variation underscores the need for carefully tailored interventions that consider the unique needs and circumstances of the target demographic to optimize efficacy. Therefore, while PPIs hold promise, the evidence suggests that a nuanced approach to their application is necessary, where factors such as intervention type, target population, and desired well-being outcome are all carefully considered to maximize benefits [ 17 , 31 ].

When compared with the findings of existing literature, our findings provide a nuanced view that aligns with some previous studies but also highlights the complexity of applying PPIs across diverse populations and settings [ 6 , 114 , 115 ]. Unlike some optimistic narratives, our results suggest that while PPIs can be beneficial, their efficacy is not universal and depends on specific intervention types and target populations. Furthermore, our findings diverge from studies such as the MYRIAD trial [ 116 ], underscoring the need for cautious interpretation of PPI efficacy and the potential for adverse effects.

Future Directions

The findings from this systematic review and meta-analysis provide a solid foundation for understanding the effectiveness of PPIs in young populations. However, as with all research, there are avenues that remain unexplored and warrant further investigation. One primary recommendation is to conduct more rigorous RCTs with larger and more diverse samples. This would not only enhance the generalizability of the findings but also allow for a more in-depth exploration of the nuances and specific components of the interventions that are most effective. Also, we suggest that PPIs should be integrated in interventions that also collect biological information to further assess their efficacy.

Another crucial area for future research is the examination of the long-term effects of these digital interventions. While our review captured the immediate and short-term benefits, understanding the sustainability of these positive outcomes over extended periods is essential. This would provide insights into whether these interventions lead to lasting changes in well-being and mental health or whether periodic “booster” sessions are required to maintain the benefits. In addition, given the rapid advancements in technology, exploring the integration of emerging technologies, such as virtual reality or augmented reality, into PPIs could offer innovative ways to engage and support adolescents.

From a practical implementation perspective, stakeholders in the field of youth mental health should consider incorporating evidence-based digital interventions into broader mental health programs and curricula. Schools, community centers, and mental health organizations can benefit from these scalable and accessible tools, especially in regions where traditional face-to-face interventions might be limited. Collaborations between researchers, technologists, and educators can further refine and optimize these interventions, ensuring that they remain relevant and effective in the ever-evolving digital landscape.

Limitations

Our study, while extensive, exhibits limitations that warrant attention for a comprehensive understanding of the scope and applicability of our findings. One major limitation is the heterogeneity in study settings and targeted age groups, which ranged from school environments to clinical settings and included diverse demographic categories from children to young adults [ 30 ]. This wide variability complicates the task of uniformly generalizing the results across different settings and age demographics. In addition, the medium-to-low quality of some included studies potentially undermines the reliability and robustness of our findings. The varying methodological rigor and potential biases in the study design across the analyzed studies necessitate a cautious interpretation of the effectiveness and applicability of PPIs based on this evidence base. We did not divide the results or their interpretation between interventions aiming at preventing versus treating mental health problems since our aim was to explore the literature and treatment effects of PPIs in general; however, we do acknowledge that the absence of improvement in a prevention intervention may not be the evidence that an intervention is ineffective; hence we should consider this interpretation to avoid biasing the findings of the meta-analysis. Hence, we suggest that future studies should look more carefully at this differentiation.

In addition, an important aspect that was not covered in our review is the assessment of the safety and potential adverse effects of PPIs. Not including an evaluation of harms, as highlighted by the findings from larger trials such as the MYRIAD trial, which documented no significant effects and even potential harm in certain subgroups, poses a noteworthy gap in our analysis [ 117 ]. This aspect highlights an area for further investigation, particularly considering the intricate nature of mental health interventions and their varied effects across diverse individuals. In addition, the absence of data from lower-middle-income countries and the lack of studies not published in languages other than English limit the generalizability of our conclusions globally, raising concerns about the effectiveness and safety of PPIs in these regions where cultural, economic, and health care contexts may differ significantly from those in high-income countries [ 30 , 31 ]. Finally, although we calculated the intercoder reliability for the screening process, we were not able to provide a measure of reliability for the quality assessment of the studies; hence, we encourage future studies to consider conducting the assessment blind and calculate a measure of agreement.

Conclusions

In conclusion, our systematic review suggests that while PPIs can enhance certain aspects of well-being among children, adolescents, and young adults, the effects are not consistent across all domains or demographic groups. The evidence supports the effectiveness of specific types of PPIs, particularly those that enhance gratitude, purpose, and hope. However, these benefits are not uniform, and the impact varies by the type of well-being outcome and the population segment. Moreover, given the significant variability in the intervention settings, the diversity of outcomes, and the medium-to-low quality of the studies reviewed, any conclusions about the efficacy of PPIs should be viewed as tentative. The findings underscore the necessity for further rigorous research to better understand the mechanisms and effectiveness of PPIs, assess their safety, and evaluate their applicability in different geographical and clinical contexts. Future studies should also explore how digital platforms might uniquely influence the success of these interventions and consider the theoretical underpinnings of PPIs in more depth to enhance their practical and academic contributions.

Acknowledgments

This study was funded by Swiss National Science Foundation (grant P500PS_202974) and supported by the National Institute of Child Health and Human Development NICHD (grant 1R21HD115354-01).

Conflicts of Interest

None declared.

Basic characteristics.

Quality assessment.

Characteristics of the positive psychology intervention.

Additional detailed information of each meta-analysis (Figure S1).

Additional detailed information of each meta-analysis (Figure S2).

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Abbreviations

Edited by J Torous; submitted 03.01.24; peer-reviewed by P Batterham, S Liu; comments to author 19.03.24; revised version received 14.05.24; accepted 17.05.24; published 14.08.24.

©Sundas Saboor, Adrian Medina, Laura Marciano. Originally published in JMIR Mental Health (https://mental.jmir.org), 14.08.2024.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Mental Health, is properly cited. The complete bibliographic information, a link to the original publication on https://mental.jmir.org/, as well as this copyright and license information must be included.

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Doctor of Nursing Practice Scholarly Projects

Cbt-i training for the mental health clinician to deliver evidence-based treatment to address impaired sleep quality in a correctional facility.

Huong Madrigal Follow

Date of Completion

Summer 8-6-2024

Document Type

Open Access Capstone

Degree Name

Doctor of Nursing Practice (DNP)

Faculty Advisor

Joanne Roman Jones

Site Advisor

Victor Petreca

Second Reader

Edith Barrett

Description of the Problem : Insomnia significantly impacts mental and physical well-being, with long-term health effects and considerable healthcare costs. While pharmacological treatments offer temporary relief for some, they do not always provide lasting solutions.

Available Knowledge: A PRISMA-guided literature review found that training programs for cognitive-behavioral therapy for insomnia (CBT-I) are effective in increasing knowledge and confidence for addressing impaired sleep.

Aim and Objectives: This project aimed to enhance mental health clinicians' ability to assess and treat impaired sleep, focusing on implementing a tailored CBT-I educational initiative in a correctional facility.

Intervention : This project implemented evidence-based CBT-I training for mental health clinicians at a Boston correctional facility to address sleep issues among incarcerated adults. Pre-assessments and final surveys gauged clinicians' confidence and knowledge in CBT-I, while bi-weekly huddles gathered feedback on training effectiveness.

Evaluation of Intervention: The output measures included data from frequency and proportion of mental health clinicians who participated in a face-to-face training, who participated in bi-weekly huddles, who showed an increase in knowledge and confidence and survey results completed by the mental health clinicians about feasibility, applicability, and value added.

Results: The project ran from August 2023 to March 2024. Initially, all eight clinicians began training, but only five remained. Bi-weekly feedback huddles had participation rates ranging from 50% to 88%. Although 63% reported increased knowledge and confidence, it did not meet the 85% target. Participants had varied perceptions of the initiative's value, feasibility, and applicability, indicating mixed feedback.

Discussion: This project aimed to enhance mental health clinicians' skills in addressing impaired sleep among incarcerated individuals through a tailored CBT-I program. Clinicians reported increased knowledge and confidence over weeks 4, 8, and 12. Feedback indicated that 73% found the project valuable, 60% found it feasible, and 53% saw its relevance in correctional settings, with no negative responses. The project supports the use of Orem's theory when considering non-pharmacological interventions in correctional sleep care, demonstrating CBT's effectiveness in managing sleep issues.

Recommended Citation

Madrigal, Huong, "CBT-I Training For the Mental Health Clinician to Deliver Evidence-Based Treatment to Address Impaired Sleep Quality in a Correctional Facility" (2024). Doctor of Nursing Practice Scholarly Projects . 45. https://scholarworks.umb.edu/nursing_dnp_capstone/45

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Revolutionizing the Study of Mental Disorders

March 27, 2024 • Feature Story • 75th Anniversary

At a Glance:

• The Research Domain Criteria framework (RDoC) was created in 2010 by the National Institute of Mental Health.
• The framework encourages researchers to examine functional processes that are implemented by the brain on a continuum from normal to abnormal.
• This way of researching mental disorders can help overcome inherent limitations in using all-or-nothing diagnostic systems for research.
• Researchers worldwide have taken up the principles of RDoC.
• The framework continues to evolve and update as new information becomes available.

President George H. W. Bush proclaimed  the 1990s “ The Decade of the Brain  ,” urging the National Institutes of Health, the National Institute of Mental Health (NIMH), and others to raise awareness about the benefits of brain research.

“Over the years, our understanding of the brain—how it works, what goes wrong when it is injured or diseased—has increased dramatically. However, we still have much more to learn,” read the president’s proclamation. “The need for continued study of the brain is compelling: millions of Americans are affected each year by disorders of the brain…Today, these individuals and their families are justifiably hopeful, for a new era of discovery is dawning in brain research.”

Still, despite the explosion of new techniques and tools for studying the brain, such as functional magnetic resonance imaging (fMRI), many mental health researchers were growing frustrated that their field was not progressing as quickly as they had hoped.

For decades, researchers have studied mental disorders using diagnoses based on the Diagnostic and Statistical Manual of Mental Disorders (DSM)—a handbook that lists the symptoms of mental disorders and the criteria for diagnosing a person with a disorder. But, among many researchers, suspicion was growing that the system used to diagnose mental disorders may not be the best way to study them.

“There are many benefits to using the DSM in medical settings—it provides reliability and ease of diagnosis. It also provides a clear-cut diagnosis for patients, which can be necessary to request insurance-based coverage of healthcare or job- or school-based accommodations,” said Bruce Cuthbert, Ph.D., who headed the workgroup that developed NIMH’s Research Domain Criteria Initiative. “However, when used in research, this approach is not always ideal.”

Researchers would often test people with a specific diagnosed DSM disorder against those with a different disorder or with no disorder and see how the groups differed. However, different mental disorders can have similar symptoms, and people can be diagnosed with several different disorders simultaneously. In addition, a diagnosis using the DSM is all or none—patients either qualify for the disorder based on their number of symptoms, or they don’t. This black-and-white approach means there may be people who experience symptoms of a mental disorder but just miss the cutoff for diagnosis.

Dr. Cuthbert, who is now the senior member of the RDoC Unit which orchestrates RDoC work, stated that “Diagnostic systems are based on clinical signs and symptoms, but signs and symptoms can’t really tell us much about what is going on in the brain or the underlying causes of a disorder. With modern neuroscience, we were seeing that information on genetic, pathophysiological, and psychological causes of mental disorders did not line up well with the current diagnostic disorder categories, suggesting that there were central processes that relate to mental disorders that were not being reflected in DMS-based research.”

Road to evolution

Concerned about the limits of using the DSM for research, Dr. Cuthbert, a professor of clinical psychology at the University of Minnesota at the time, approached Dr. Thomas Insel (then NIMH director) during a conference in the autumn of 2008. Dr. Cuthbert recalled saying, “I think it’s really important that we start looking at dimensions of functions related to mental disorders such as fear, working memory, and reward systems because we know that these dimensions cut across various disorders. I think NIMH really needs to think about mental disorders in this new way.”

Dr. Cuthbert didn’t know it then, but he was suggesting something similar to ideas that NIMH was considering. Just months earlier, Dr. Insel had spearheaded the inclusion of a goal in NIMH’s 2008 Strategic Plan for Research to “develop, for research purposes, new ways of classifying mental disorders based on dimensions of observable behavior and neurobiological measures.”

Unaware of the new strategic goal, Dr. Cuthbert was surprised when Dr. Insel's senior advisor, Marlene Guzman, called a few weeks later to ask if he’d be interested in taking a sabbatical to help lead this new effort. Dr. Cuthbert soon transitioned into a full-time NIMH employee, joining the Institute at an exciting time to lead the development of what became known as the Research Domain Criteria (RDoC) Framework. The effort began in 2009 with the creation of an internal working group of interdisciplinary NIMH staff who identified core functional areas that could be used as examples of what research using this new conceptual framework looked like.

The workgroup members conceived a bold change in how investigators studied mental disorders.

“We wanted researchers to transition from looking at mental disorders as all or none diagnoses based on groups of symptoms. Instead, we wanted to encourage researchers to understand how basic core functions of the brain—like fear processing and reward processing—work at a biological and behavioral level and how these core functions contribute to mental disorders,” said Dr. Cuthbert.

This approach would incorporate biological and behavioral measures of mental disorders and examine processes that cut across and apply to all mental disorders. From Dr. Cuthbert’s standpoint, this could help remedy some of the frustrations mental health researchers were experiencing.

Around the same time the workgroup was sharing its plans and organizing the first steps, Sarah Morris, Ph.D., was a researcher focusing on schizophrenia at the University of Maryland School of Medicine in Baltimore. When she first read these papers, she wondered what this new approach would mean for her research, her grants, and her lab.

She also remembered feeling that this new approach reflected what she was seeing in her data.

“When I grouped my participants by those with and without schizophrenia, there was a lot of overlap, and there was a lot of variability across the board, and so it felt like RDoC provided the pathway forward to dissect that and sort it out,” said Dr. Morris.

Later that year, Dr. Morris joined NIMH and the RDoC workgroup, saying, “I was bumping up against a wall every day in my own work and in the data in front of me. And the idea that someone would give the field permission to try something new—that was super exciting.”

The five original RDoC domains of functioning were introduced to the broader scientific community in a series of articles published in 2010  .

To establish the new framework, the RDoC workgroup (including Drs. Cuthbert and Morris) began a series of workshops in 2011 to collect feedback from experts in various areas from the larger scientific community. Five workshops were held over the next two years, each with a different broad domain of functioning based upon prior basic behavioral neuroscience. The five domains were called:

• Negative valence (which included processes related to things like fear, threat, and loss)
• Positive valence (which included processes related to working for rewards and appreciating rewards)
• Cognitive processes
• Social processes
• Arousal and regulation processes (including arousal systems for the body and sleep).

At each workshop, experts defined several specific functions, termed constructs, that fell within the domain of interest. For instance, constructs in the cognitive processes domain included attention, memory, cognitive control, and others.

The result of these feedback sessions was a framework that described mental disorders as the interaction between different functional processes—processes that could occur on a continuum from normal to abnormal. Researchers could measure these functional processes in a variety of complementary ways—for example, by looking at genes associated with these processes, the brain circuits that implement these processes, tests or observations of behaviors that represent these functional processes, and what patients report about their concerns. Also included in the framework was an understanding that functional processes associated with mental disorders are impacted and altered by the environment and a person’s developmental stage.

Preserving momentum

Over time, the Framework continued evolving and adapting to the changing science. In 2018, a sixth functional area called sensorimotor processes was added to the Framework, and in 2019, a workshop was held to better incorporate developmental and environmental processes into the framework.;

Since its creation, the use of RDoC principles in mental health research has spread across the U.S. and the rest of the world. For example, the Psychiatric Ratings using Intermediate Stratified Markers project (PRISM)   , which receives funding from the European Union’s Innovative Medicines Initiative, is seeking to link biological markers of social withdrawal with clinical diagnoses using RDoC-style principles. Similarly, the Roadmap for Mental Health Research in Europe (ROAMER)  project by the European Commission sought to integrate mental health research across Europe using principles similar to those in the RDoC Framework.;

Dr. Morris, who has acceded to the Head of the RDoC Unit, commented: “The fact that investigators and science funders outside the United States are also pursuing similar approaches gives me confidence that we’ve been on the right pathway. I just think that this has got to be how nature works and that we are in better alignment with the basic fundamental processes that are of interest to understanding mental disorders.”

The RDoC framework will continue to adapt and change with emerging science to remain relevant as a resource for researchers now and in the future. For instance, NIMH continues to work toward the development and optimization of tools to assess RDoC constructs and supports data-driven efforts to measure function within and across domains.

“For the millions of people impacted by mental disorders, research means hope. The RDoC framework helps us study mental disorders in a different way and has already driven considerable change in the field over the past decade,” said Joshua A. Gordon, M.D., Ph.D., director of NIMH. “We hope this and other innovative approaches will continue to accelerate research progress, paving the way for prevention, recovery, and cure.”

Publications

Cuthbert, B. N., & Insel, T. R. (2013). Toward the future of psychiatric diagnosis: The seven pillars of RDoC. BMC Medicine , 11 , 126. https://doi.org/10.1186/1741-7015-11-126  

Cuthbert B. N. (2014). Translating intermediate phenotypes to psychopathology: The NIMH Research Domain Criteria. Psychophysiology , 51 (12), 1205–1206. https://doi.org/10.1111/psyp.12342  

Cuthbert, B., & Insel, T. (2010). The data of diagnosis: New approaches to psychiatric classification. Psychiatry , 73 (4), 311–314. https://doi.org/10.1521/psyc.2010.73.4.311  

Cuthbert, B. N., & Kozak, M. J. (2013). Constructing constructs for psychopathology: The NIMH research domain criteria. Journal of Abnormal Psychology , 122 (3), 928–937. https://doi.org/10.1037/a0034028  

Garvey, M. A., & Cuthbert, B. N. (2017). Developing a motor systems domain for the NIMH RDoC program.  Schizophrenia Bulletin , 43 (5), 935–936. https://doi.org/10.1093/schbul/sbx095  

Kozak, M. J., & Cuthbert, B. N. (2016). The NIMH Research Domain Criteria initiative: Background, issues, and pragmatics. Psychophysiology , 53 (3), 286–297. https://doi.org/10.1111/psyp.12518  

Morris, S. E., & Cuthbert, B. N. (2012). Research Domain Criteria: Cognitive systems, neural circuits, and dimensions of behavior. Dialogues in Clinical Neuroscience , 14 (1), 29–37. https://doi.org/10.31887/DCNS.2012.14.1/smorris  

Sanislow, C. A., Pine, D. S., Quinn, K. J., Kozak, M. J., Garvey, M. A., Heinssen, R. K., Wang, P. S., & Cuthbert, B. N. (2010). Developing constructs for psychopathology research: Research domain criteria. Journal of Abnormal Psychology , 119 (4), 631–639. https://doi.org/10.1037/a0020909  

• Presidential Proclamation 6158 (The Decade of the Brain) 
• Research Domain Criteria Initiative website
• Psychiatric Ratings using Intermediate Stratified Markers (PRISM)  

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• v.15(5); 2023 May
• PMC10220277

Understanding and Addressing Mental Health Stigma Across Cultures for Improving Psychiatric Care: A Narrative Review

Ahmed a ahad.

1 Psychiatry and Behavioral Sciences, Florida International University, Herbert Wertheim College of Medicine, Miami, USA

Marcos Sanchez-Gonzalez

2 Health Services Administration, Lake Erie College of Osteopathic Medicine, Bradenton, USA

Patricia Junquera

Stigma, characterized by negative stereotypes, prejudice, and discrimination, is a significant impediment in psychiatric care, deterring the timely provision of this care and hindering optimal health outcomes. Pervasive in all aspects of psychiatric care, stigma leads to delayed treatment, increased morbidity, and diminished quality of life for those with poor mental health. Hence, better understanding the impact of stigma across different cultural contexts is critically essential, aiming to inform culturally nuanced strategies to minimize its consequences and contribute to a more equitable and effective psychiatric care system. The purpose of the present literature review is twofold (i) to examine the existing research on the stigma surrounding psychiatry across different cultural contexts and (ii) to identify the commonalities and differences in the nature, magnitude, and consequences of this stigma in different cultures in the psychiatry field. In addition, potential strategies for addressing stigma will be proposed. The review covers a range of countries and cultural settings, emphasizing the importance of understanding cultural nuances to combat stigma and promote mental health awareness globally.

Introduction and background

Stigma, characterized by societal prejudice and discrimination, profoundly influences psychiatric care, creating barriers to the timely recognition and treatment of mental health disorders [ 1 ]. Deeply embedded in societal norms, stigma is a multifaceted issue permeating every level of psychiatric care, leading to delayed treatment, increased morbidity, and a diminished quality of life for patients.

The importance of addressing stigma in psychiatry cannot be overstated as stigma impacts individuals seeking care, their families, healthcare professionals, and broader society. At the individual level, stigma can lead to fear and avoidance of mental health services, causing delays in seeking help even when a patient is in dire need. Delays in seeking care can exacerbate mental health conditions leading to worse outcomes and reduced quality of life [ 2 ]. For families, the stigma can lead to shame and isolation, making seeking necessary support and resources more difficult. Interestingly, in healthcare professionals, stigma can lead to burnout and demoralization, reducing the quality and provision of care. Stigmatization can also create barriers between healthcare providers and patients, complicating matters to establishing trustful and therapeutic relationships, which are essential for effective care [ 1 ]. For society at large, stigma can result in the misallocation of resources, with mental health services often being underfunded and overlooked [ 3 ]. Hence stigma has profound effects at personal and societal levels, negatively impacting multiple levels of the psychotic care continuum. 

Addressing the stigma surrounding mental health can significantly enhance the effectiveness of psychiatric care. To this end, developing programs and strategies that foster a culture of understanding and acceptance may encourage more individuals to seek help when they need it, improving early detection and intervention, which are crucial for better health outcomes. Furthermore, challenging and changing stigmatizing attitudes can improve the therapeutic relationship between healthcare providers and patients, leading to more personalized and effective treatment strategies.

Stigma, however, is not a monolithic entity but varies across cultures, influenced by distinct societal norms, values, and beliefs. Understanding these cultural variations is essential for developing effective, culturally sensitive interventions. Therefore, this literature review aims to examine the manifestation and impacts of stigma across different cultural contexts, laying the foundation for tailored strategies to combat this healthcare barrier.

Stigma as a psychological construct

In the literature, there have been several attempts at creating instruments to measure and understand stigma as a psychological construct in the context of mental health. In this vein, the Internalized Stigma of Mental Illness (ISMI) scale and the Perceived Devaluation-Discrimination Scale, among others, seek to quantify stigma more objectively [ 4 , 5 ] . The ISMI scale, as defined by Ritsher et al. (2003), measures the subjective experience of stigma, including the internalization of negative stereotypes and beliefs about mental illness [ 4 ]. It includes five subscales: Alienation, Stereotype Endorsement, Discrimination Experience, Social Withdrawal, and Stigma Resistance. These subscales were further defined as follows: (i) Alienation: The feeling of being less than a full member of society due to one's mental illness, (ii) Stereotype Endorsement: The extent to which the individual agrees with common negative stereotypes about people with mental illness, (iii) Discrimination Experience: Personal experiences of rejection or exclusion due to mental illness, (iv) Social Withdrawal: The extent to which the individual avoids social situations for fear of being stigmatized, and (v) Stigma Resistance: The individual's ability to resist or counteract stigma. The Perceived Devaluation-Discrimination Scale, as described by Link (1987), measures the extent to which individuals believe that most people will devalue or discriminate against someone with a mental illness [ 5 ]. It focuses on the individual's perceptions of societal attitudes, rather than their personal experiences with stigma. Overall, while the ISMI scale can give insights into the internalization and personal experience of stigma, the Perceived Devaluation-Discrimination Scale can provide a view of societal attitudes and perceived discrimination. The above are crucial to understanding the full landscape of stigma in psychiatry across different cultures by helping identify where interventions might be most needed and most effective, whether at the level of societal attitudes, personal beliefs, or both. The pervasive nature of stigma presents a daunting challenge to psychiatry, necessitating a rigorous and nuanced approach to its understanding and mitigation. However, despite recent awareness campaigns, the field still struggles with the barriers that stigma imposes on patient care, necessitating additional analysis of the effects.

Individual and societal impact of stigma

Stigmatization of mental illness across cultures is a significant barrier to psychiatric care. The stigma can lead to delayed diagnosis and treatment-seeking behaviors, reduced quality of life, and an increased risk of social exclusion and discrimination [ 2 ]. Furthermore, mental illness stigma often intersects with other forms of stigma, such as gender, race, and socio-economic status, leading to further marginalization of already vulnerable populations making it challenging to provide equitable, culturally sensitive, and effective psychiatric care to individuals with mental illness. Accumulating research suggests that stigma toward mental illness is common in various cultures, which can affect mental illness diagnosis, treatment, and management [ 6 ]. Furthermore, some studies reveal that mental health stigma manifests differently across cultures and can be influenced by cultural beliefs, attitudes, and values [ 7 ]. The stigma surrounding psychiatry and mental health disorders has numerous detrimental effects on individuals and communities, including:

1. Delayed Treatment-Seeking Behavior

Stigma plays a significant role in delaying treatment-seeking behavior for individuals struggling with mental health issues. The fear of being labeled, ostracized, or misunderstood due to their condition often deters individuals from seeking help promptly. According to a study by Clement et al. (2015), stigma was associated with an increased likelihood of delaying or avoiding seeking help for mental health concerns [ 8 ]. Consequently, symptoms may worsen over time, escalating the condition's severity and making treatment and prospective recovery more challenging. Healthcare delays can also lead to decreased self-esteem and increased depressive symptoms, creating a vicious cycle of self-blame, isolation, and hopelessness. Prolonged untreated mental health issues can further impair an individual's functionality in various life domains, including work, relationships, and self-care, thus reducing their overall quality of life [ 9 ].

2. Social Isolation and Discrimination

Stigma can lead to social isolation and discrimination for those affected by mental health issues. Brohan and Thornicroft (2010) found that individuals with mental health disorders often face discrimination in multiple life domains, including employment and interpersonal relationships [ 2 ]. The negative stereotypes and misconceptions surrounding mental illness often result in a lack of understanding and empathy from others, leading to social exclusion [ 10 ]. Individuals with mental health issues might face discrimination in various aspects of life, including the workplace, where they might encounter bias in hiring, job retention, and career advancement. Furthermore, to complicate matters, discrimination can further strain personal relationships, as friends and family may distance themselves due to discomfort, fear, or misunderstanding, exacerbating feelings of isolation and loneliness [ 9 ].

3. Reduced Treatment Adherence

Stigma can significantly impact adherence to mental health treatments. Sirey et al. (2001) found that perceived stigma predicted treatment discontinuation in older adults with depression [ 11 ]. People living with mental health conditions may avoid or discontinue treatment due to fear of being identified as a mental health patient. This fear could stem from concerns about the stigma associated with visiting mental health facilities, taking psychiatric medications, or being seen engaging in therapeutic activities [ 12 ]. Non-adherence to treatment regimens can lead to suboptimal treatment outcomes, hinder recovery, and increase the risk of relapse or worsening symptoms. Furthermore, stigma can diminish self-efficacy, making individuals less likely to actively engage in their treatment process, which is crucial for successful recovery.

4. Perpetuation of Misconceptions

Stigmatizing attitudes towards mental illness contribute to the perpetuation of harmful stereotypes and misinformation. AsCorrigan and Watson (2007) discussed, stereotypes such as appearing dangerous, unpredictable, or culpable for their illness can make people with mental illness perceived inaccurately as dangerous or to blame for their condition, both internally and externally [ 12 ]. Stereotyping, deeply embedded in societal attitudes, can foster a culture of fear, rejection, and discrimination against individuals with mental health conditions. Misconceptions often result in people with mental health issues being perceived inaccurately as dangerous, unpredictable, or responsible for their condition. In addition, misinformation can hinder public understanding and acceptance of mental illness, exacerbating stigma while negatively influencing policy and legislation, leading to inadequate funding and support for mental health services.

5. Influence of Gender on Stigma

The impact of stigma on individuals with mental illness is known to vary across different social and demographic categories, including gender. Research evidence indicates that the experience of stigma related to mental illness can be significantly different for men and women, and these differences can be further influenced by cultural context.

In some societies, women seem to face higher levels of stigma related to mental health issues compared with men. A study by Al Krenawi et al. (2006) conducted in the Bedouin-Arab community found that women experienced a significantly higher degree of stigma associated with mental illness than their male counterparts [ 13 ]. This may be due to traditional gender roles and societal expectations, which often place women in a more subordinate position and associate mental illness with weakness or vulnerability. Women with mental illnesses may therefore face dual discrimination - first for their gender and then for their mental health condition. This can make women less likely to seek help for mental health issues, further exacerbating their condition and creating a vicious cycle of stigma and untreated mental illness.

However, the influence of gender on stigma is not uniform across all cultures. Ayalon and Areán's (2004) study on older adults in an Arab cultural context found that men reported higher levels of perceived stigma related to mental illness than women [ 14 ]. This discrepancy might be rooted in traditional masculine norms prevalent in many Arab societies, which value strength, stoicism, and emotional control. Mental illness, which is often erroneously perceived as a sign of emotional weakness or lack of control, can be particularly stigmatizing for men in these contexts. Furthermore, the expectation for men to be the primary earners and providers in the family can make the potential economic impacts of mental illness, such as unemployment or reduced productivity, particularly stigmatizing.

These findings underscore the importance of considering gender and cultural context in understanding and addressing stigma related to mental illness. It is crucial to develop and implement culturally sensitive strategies that consider these differences in the experience of stigma. This might involve, for example, promoting mental health literacy, challenging harmful gender norms, and providing gender-specific mental health services. We can move toward a more equitable and effective mental health care system by acknowledging and addressing the unique stigma-related challenges different groups face.

Ethnic and cultural variations in stigma

The stigma surrounding psychiatry, as research suggests, manifests differently across cultures due to various factors [ 7 ]. This stigma operates at various levels, including individuals, families, healthcare providers, and society, and cultural norms, religious beliefs, and social attitudes influence its manifestations and implications.

At the individual level, mental health issues may be internalized differently depending on cultural background. For instance, some Asian cultures may view mental health issues as a sign of personal weakness or a failure of self-control [ 15 ]. The internalization of stigma can significantly influence an individual's self-perception and willingness to seek help. In the family context, cultural beliefs also play a significant role in shaping attitudes toward mental health. A study by Yang and Kleinman (2008) found that in Chinese culture, mental illness is often attributed to social and interpersonal factors, such as family conflict [ 16 ]. Such attributions can contribute to a sense of shame or blame within the family, exacerbating the stigma experienced by the individual with mental illness.

Healthcare providers are not immune to these cultural beliefs and they can influence their practice. In some cultures, mental illnesses are viewed through a supernatural lens rather than a medical one. Girma et al. (2013) found that in Ethiopian culture, mental illness is commonly associated with supernatural causes, such as evil spirits or curses [ 17 ]. This widely held belief can influence healthcare providers' approach and potentially limit the provision of evidence-based psychiatric care.

Lastly, at the societal level, these cultural perceptions and beliefs can contribute to the broader social stigma surrounding mental health, leading to discrimination and social exclusion. Differences in societal perceptions across cultures can lead to distinct forms of discrimination, further compounding the challenges faced by individuals with mental health issues. Hence, understanding and addressing cultural stigma in psychiatry involves a multifaceted approach that considers individual, family, healthcare providers, and societal levels. Each level offers potential avenues for stigma reduction and improved mental health outcomes.

Asian Cultures

In many Asian societies, mental health issues are often perceived as a sign of personal weakness or a failure of self-control. The concept of 'face' is significantly influential, and the stigma associated with mental illness can be seen as bringing shame to the family [ 15 ]. For instance, a strong cultural emphasis on academic and professional achievement in South Korea contributes to stigmatizing attitudes toward mental illness, which may discourage individuals from seeking help [ 18 ].

African Cultures

Mental illnesses in some African cultures are often attributed to spiritual or supernatural causes such as curses or possession by evil spirits. This understanding can contribute to high levels of stigma and deter individuals from seeking psychiatric help [ 19 ]. In Ethiopia, the belief in supernatural causes of mental illness has been reported, leading to the stigmatization of affected individuals [ 17 ].

Arab Cultures

Mental illness in Arab societies is frequently viewed as a form of divine punishment. Religious belief perpetuating mental health stigma can lead to delayed or avoided treatment as individuals may resort to religious or spiritual interventions [ 20 ].

Latin American Cultures

In some Latin American cultures, mental illness is often attributed to personal weakness or lack of willpower. This perspective could stigmatize individuals with mental health disorders and discourage them from seeking psychiatric care [ 21 ].

Western Cultures

In Western societies, stigma often stems from misconceptions about mental illness, including the belief that individuals with mental health disorders are dangerous or unpredictable. While mental illness is recognized more as a health issue, stigma still exists, often resulting in social exclusion and discrimination [ 12 ].

Additionally, culture-bound syndromes, defined here as a combination of psychiatric and somatic symptoms that are considered to be a recognizable disease within specific cultures or societies, are a critical component of a discussion on cultural stigma in psychiatry. That is to say, culture-bound syndromes refer to unique mental health conditions closely tied to specific cultures or ethnic groups. For instance, among the Latino community, 'Ataque de Nervios,' characterized by uncontrollable shouting, crying, trembling, and sometimes aggressive behavior, is a recognized condition often associated with a stressful event such as a panic attack [ 21 ].

Hence, a clinician's awareness and understanding of such culture-bound syndromes can enhance their diagnostic and therapeutic effectiveness. In fact, a study conducted by Hughes and Wintrob (1995) in New York discovered a significant improvement in therapeutic relationships when clinicians were knowledgeable about culture-bound syndromes prevalent in their patients' cultures, such as 'Qigong Psychotic Reaction' in Chinese immigrants, a condition associated with overdoing Qigong, a type of spiritual martial art [ 22 ].

Furthermore, cultural competence, which includes knowledge about culture-bound syndromes, has a substantial impact on treatment outcomes. Culturally competent care, defined by an understanding and respect for cultural differences, can improve patient satisfaction and adherence to treatment. A systematic review by Truong et al. (2014) demonstrated the positive effect of cultural competence on healthcare outcomes, including in a Native American population suffering from 'Ghost Sickness,' a culture-bound syndrome characterized by feelings of terror, weakness, and a sense of impending doom, often linked to the perceived presence of the supernatural [ 23 ].

Simultaneously, addressing culture-bound syndromes can influence and reduce mental health stigma across cultures. Misinterpretation of these syndromes can contribute to stigma, as individuals might be wrongly diagnosed or misunderstood. For instance, Kirmayer's (2012) study on cultural variations in depression and anxiety found that misunderstanding culture-bound syndromes, such as 'Taijin Kyofusho,' a Japanese syndrome characterized by an intense fear that one's body or bodily functions are displeasing to others, could lead to misdiagnosis and increase stigma [ 24 ]. Practices that raise awareness of culture-bound syndromes offer a deeper, richer perspective on cultural influences on mental health. Awareness and understanding of these syndromes can enhance diagnostic and treatment approaches, optimize patient outcomes, and potentially contribute to reducing mental health stigma across various cultures.

Taken together, these studies highlight the importance of understanding cultural contexts when addressing the stigma surrounding mental health disorders and psychiatric care. The cultural beliefs and attitudes towards mental health disorders, summarized below in Table ​ Table1, 1 , influence how stigma is manifested and the approaches needed to reduce it effectively. By acknowledging cultural variations, more culturally appropriate and effective strategies can be developed to combat stigma and improve mental health care across different societies worldwide.

Strategies for addressing mental health stigma

Several strategies have been proposed in the literature to address the stigma surrounding psychiatry across cultures:

1. Public Awareness Campaigns

Awareness campaigns can be instrumental in dismantling misconceptions and fostering understanding of mental health disorders. Public awareness campaigns can dispel myths, reduce stigma, and encourage empathy towards affected individuals by promoting accurate information about mental illnesses, their prevalence, and the possibilities for recovery. For instance, a study by Pinfold et al., (2003) showed that public campaigns using direct social contact with people with mental illness could significantly improve public attitudes towards mental health [ 25 ]. The study by Pinfold et al., (2003) implemented educational interventions in UK secondary schools, consisting of video presentations and direct social contact with individuals who had personal experiences with mental illness [ 25 ]. The UK campaign's goal was to challenge common myths about mental illness and replace them with accurate information. The results showed that students exposed to this intervention demonstrated less fear and avoidance of people with mental health problems and were more likely to see them as individuals rather than defining them by their illness.

2. Cultural Competency Training for Healthcare Professionals

Medical education can equip healthcare providers with the necessary knowledge and skills to understand and respect their patients' cultural backgrounds and experiences, which is critical for reducing stigma in healthcare settings. Research indicates that healthcare providers who lack cultural competence may inadvertently contribute to stigma, further deterring patients from seeking help [ 26 ]. A study by Kirmayer (2012) found that cultural competence training improved healthcare providers' understanding of cultural influences on health behaviors and led to more effective patient-provider communication, thereby reducing perceived stigma [ 24 ]. For instance, a study in Australia provided cultural competency training to healthcare providers and found that their understanding of Indigenous Australians' health needs significantly improved [ 24 ]. They were able to better respect and incorporate Indigenous perspectives in treatment, which led to increased trust and better patient-provider relationships.

3. Peer Support Programs

People with lived experiences of mental health disorders who share their stories, can normalize mental health issues and challenge stigma. By providing real-life examples of individuals living with and managing their mental health disorders, peer-to-peer advocacy programs may debunk myths and reduce the perceived 'otherness' of mental illness. A study by Pitt et al. (2013) showed that peer support reduced self-stigma and improved self-esteem and empowerment among individuals with mental health disorders [ 27 ]. The study focused on "consumer-providers," individuals who had personally experienced mental health issues and were now providing support services to others. The findings demonstrated that consumer-providers significantly reduced self-stigma among service users, while also improving self-esteem and feelings of empowerment.

4. Community-Based Mental Health Services

Integrating mental health care into primary care and community settings can reduce the stigma associated with seeking psychiatric help. This emphasis on integrating measures for mental well-being along with other routine and standard primary care protocols allows mental health care to be more accessible and less intimidating, encouraging individuals to seek help when needed. A study by Thornicroft et al. (2015) found that community-based mental health services can reduce stigma and discrimination and improve mental health outcomes [ 28 ]. For instance, a program in India called the MANAS project integrated mental health services into primary care and community settings [ 28 ]. This approach not only made mental health services more accessible but also more 'normal' and less stigmatizing. The project reported a significant increase in the utilization of mental health services and a decrease in the experience of stigma among service users.

5. Evidence-Based Approach

Another approach to overcoming the barriers created by stigma is to use evidence-based methods to reduce mental illness stigma. A meta-analysis by Corrigan et al. (2016) found that various evidence-based interventions, including education and contact-based interventions, can effectively reduce mental illness stigma across cultures [ 9 ]. Contact-based interventions involve interaction between people with mental illness and members of the public to challenge negative attitudes and beliefs. Education-based interventions aim to increase knowledge and awareness of mental illness and reduce negative stereotypes. Educational interventions can be delivered in a variety of formats, such as in-person workshops, online courses, and mass media campaigns.

The role of the healthcare provider in ameliorating stigma cannot be overlooked. Moreover, a review by Ayalon and Areán (2004) suggests that mental health providers can play a critical role in reducing mental illness stigma by engaging in culturally sensitive practices [ 14 ]. For instance, mental health providers can develop cultural competence, which refers to the ability to provide effective services to individuals from diverse cultural backgrounds. Cultural competence involves understanding and respecting cultural differences, tailoring treatment to meet diverse populations' unique needs, and integrating cultural factors into treatment planning.

Research also highlights that stigma towards mental illness has significant implications for treating and managing mental health conditions. For example, several studies suggest that stigma can lead to delayed diagnosis and treatment-seeking behaviors [ 13 , 16 ]. This is concerning because early intervention is critical for managing mental illness and improving outcomes for individuals living with these conditions. Considering the documented impact of stigma on timely diagnosis and treatment-seeking behaviors, strategies such as public awareness campaigns, cultural competency training for healthcare professionals, peer support programs, community-based mental health services, and an evidence-based approach can play a crucial role in combating cultural stigma in psychiatry. These measures collectively contribute to improved awareness, understanding, and acceptance of mental health conditions, thus facilitating early intervention and better management of mental illnesses across diverse cultural contexts.

Conclusions

Stigma surrounding mental health and psychiatric care is a complex and multifaceted issue that varies across ethnic and cultural contexts. To effectively address and reduce stigma in mental healthcare settings, developing culturally sensitive interventions and promoting understanding and acceptance of mental health issues is crucial. By doing so, we can work towards improving access to mental health care and promoting the well-being of individuals and communities across the globe.

Overall, the literature suggests that stigma is a complex and pervasive issue that affects individuals with mental illness across cultures. The studies reviewed reveal that mental illness stigma is influenced by cultural beliefs, attitudes, and values, and can manifest in different ways across cultures. It is important to understand these cultural differences to develop more effective interventions to reduce mental illness stigma and improve outcomes for individuals living with mental illness. Furthermore, stigma across cultures impacts psychiatric care in various ways and can create significant barriers to effective treatment. Evidence-based interventions, including education, contact-based interventions, and culturally sensitive practices can help overcome these barriers. Mental health providers should strive to develop cultural competence and deliver culturally sensitive interventions to meet the needs of diverse populations. Research to understand the impact of stigmatization of mental health patients and its impact in providing services is warranted. Reducing mental illness stigma is critical to providing equitable, effective, and compassionate psychiatric care to individuals with mental illness.

The authors have declared that no competing interests exist.