research methodology about mental health of students

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http://orcid.org/0000-0002-8277-9980 David Matthew Edmonds 1 ,
Olga Zayts-Spence 1 ,
Zoë Fortune 1 , 2 ,
http://orcid.org/0000-0002-9524-5638 Angus Chan 1 ,
Jason Shang Guan Chou 1
1 School of English , The University of Hong Kong , Hong Kong , China
2 School of Social Sciences , Heriot-Watt University Dubai , Dubai , UAE
Correspondence to Dr David Matthew Edmonds; edmonds{at}hku.hk

Objectives This scoping review maps the extant literature on students’ and graduates’ mental health experiences throughout their university-to-work transitions. The current review investigates the methodological features of the studies, the main findings, and the theories that the studies draw on to conceptualise mental health and transitions.

Design This project used a scoping review methodology created and developed by Peters and colleagues and the Joanna Briggs Institute. The review searched academic databases and screened existing studies that met predetermined inclusion criteria.

Data sources Seven academic databases and Google Scholar were searched with sets of search terms.

Eligibility The included studies examined participants who were final-year university students or those who had graduated from university within a 3-year period. Studies published in English since 2000 and from any country were included. The review included studies examining the negative dimensions of mental health. The review excluded studies focusing on medical students and graduates.

Data extraction Basic information about the studies and their findings on mental health and university-to-work transitions was retrieved. The findings are presented in tables and in a qualitative thematic summary.

Results The scoping review included 12 studies. Mental health was often not explicitly defined and it’s theoretical foundations were not clearly articulated. The review identified factors, including a lack of social support and economic precarity, as sources of adverse mental health. Other protective factors in these studies—variables that guard against mental health problems—were identified, such as career preparedness and having a good job.

Conclusions Despite the methodological focus on the negative aspects of mental health, people’s mental health experiences during university-to-work transitions are not uniformly negative. Clear conceptualisations of mental health in future studies will aid in developing resources to improve well-being.

Trial registration number This scoping review adhered to a protocol previously published in this journal and that is registered on the Open Science Framework website ( https://osf.io/gw86x ).

mental health
occupational stress

Data availability statement

No data are available.

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ .

https://doi.org/10.1136/bmjopen-2023-076729

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STRENGTHS AND LIMITATIONS OF THIS STUDY

A methodological advantage of this project lies in deploying a scoping review methodology, alongside following a well-documented and thorough literature search and screening process. The scoping review’s validity and reliability was ensured by the three reviewers working together, documenting reasons for study inclusion and exclusion, and regularly talking through problems.

The comparatively small number of included studies is a strength because it allows an in-depth examination of the literature base. As such, the review can extend beyond just documenting the studies’ findings and can also investigate their theoretical underpinnings.

The scoping review’s limitations relate to the possibility of missing existing studies and work not published in English before 2000. In addition, our condensed search of Google Scholar means we may have missed relevant grey literature.

The scoping review has a restricted focus on non-medical students and graduates, and thus, this narrow focus may mean that some relevant findings have not been included.

Introduction

People’s lives consist of transition periods as they experience milestones such as marriage, divorce, and relocating to different places. Transitions have previously been defined as ‘sharp discontinuities with the previous life events’ that mark a change in our circumstances (p. 239). 1 One extensively researched transition is when graduates leave tertiary education and begin a career in the workforce—or what has been termed university-to-work transitions. This term implies a somewhat simplistic conceptualisation of transitions—as a linear move from one set of circumstances to another. 2 Research has shown that this period is complex. 2 Some people follow a straightforward transition from graduation, encountering difficulties in their new jobs, to eventually being fully enmeshed in the workplace. 3 Others may instead start their first job and then leave it for another job. 4 Still, others may begin preparing for their career before they graduate, in the form of internships. 2 Thus, university-to-work transitions involve different stages, and people may move between them. 2 4

University-to-work transitions are different according to the group of students and graduates at issue. There is evidence that graduates from some disciplines have different career search strategies. 5 Furthermore, graduates from some disciplines, such as psychology, have lower salaries in their first jobs compared with those from other disciplines. 6 Finally, graduates in medicine (and related fields) experience unique transitions compared to others, for reasons including on-the-job training as part of their education, 7 different and challenging curricula 8 , and facing the psychological demands of dealing with injured or dead patients. 9

The university-to-work transition entails shifts in aspects of students’ and graduates’ lives, including their skills, mindsets, and financial standing. 2 10 Students and graduates navigate these changes in order to succeed in their chosen careers. Transitions are complicated periods, as changing circumstances can lead to changes in one’s personality and psychological well-being. 11 12 One challenge faced by students and graduates is mental health problems. Mental health is a multifaceted term that is understood as a continuum. 13–16 At one end, there is psychological health , including facets such as ‘positive feelings and positive functioning in life’ (p. 208). 16 This review treats mental health as a negative phenomenon—the other side of the continuum—including mental ill health, psychological distress and mental illnesses. 13 17

Mental health is an important issue as it is implicated in low productivity, 18 job loss 19 , and substance abuse 20 in workplaces. Mental health is important during the university-to-work transition because this is a period of existing challenges, with people experiencing changes to their identities, finances, and abilities. 2 10 Students and graduates can face mental health problems throughout the transition. Cassidy and Wright found that around 34% of underemployed graduates could be classified as clinically distressed. 21 Being aware of these mental health issues could help us understand the psychological struggles faced by students and graduates. Such insights could enable universities to allocate their resources to help these vulnerable individuals. Prospective employers should know the mental health struggles of their new employees so that they can create a supportive workplace environment to help them thrive.

Aims and objectives

The scoping review aims to chart the existing research on the mental health outcomes and experiences of students and graduates during the university-to-work transition. The review has three objectives: (1) to examine the methodological features of the studies, (2) to identify the findings about graduates’ and students’ mental health during university-to-work transitions from the examined studies and (3) to investigate the theories used to conceptualise mental health and transitions (the third objective differs from the original published protocol due to the inclusion of an examination of the theories used to conceptualise transitions).

This scoping review strictly adhered to the steps and guidelines provided by other scholars and organisations. 11 22–24 Further methodological details can be found in the published protocol for this review. 13 A scoping review is appropriate because our cursory examination of the extant research base showed that it was small compared with literature on other topics and university-to-work transitions. 13 A systematic review would be too extensive of a methodology for such little research. 25

Stages 1 and 2: finding and choosing the studies

Two tasks constituted the preliminary work for this scoping review. The first task was to operationalise the population, context and concepts in this review. 22 The operationalisation of population refers to the participants in the sample of each included study. 22 Studies meeting the inclusion criteria focused on participants who were (1) final-year undergraduate and postgraduate university students; (2) those people who had graduated from university within the previous 3 years; (3) students from all disciplines except dentistry, nursing, and medicine and (4) those students not suffering from any form of disability. 13 Our scoping review did not include students and graduates from medical fields because of the unique nature of their education and transitions compared with other disciplines that were outlined earlier. 7–9 13 There are existing review papers focusing on medical (and related) students’ and graduates’ mental health during this period 26 27 and reviews of medical students’ mental health generally. 28 29 In relation to the studies’ contexts, those papers published in English since 2000 and from any geographical location qualified for inclusion in the review. 13

The scoping review includes two key concepts. The conceptualisation of mental health focuses on its negative dimensions—namely, mental ill health, psychological disorder, and psychological distress 13 . This definition incorporates mental illnesses, including depression, anxiety, and personality disorders, and psycho-emotional states such as stress, worry, and sadness. 13 The concept of university-to-work transitions was operationalised broadly and encompasses (1) the time period of those students who will leave university within a year; (2) the period of preparation that students and graduates undertake for moving into a career and (3) a period of 3 years postgraduation. 13 The full inclusion and exclusion criteria are outlined in the published protocol. 13

The second task was developing the scoping review’s search terms. Online supplemental file 1 summarises the scoping review’s search strategy. These search term strings were applied to seven online academic databases. Three reviewers searched the databases. The following databases and the accompanying search fields were searched: SSCI (title, abstract, keyword plus), Scopus (title, abstract, keywords), Web of Science (title, abstract, author keywords and keywords plus), CINAHL Plus (title and abstract), ERIC (title and abstract), OVID (abstract) and PSYCINFO (title, abstract and keywords). Google Scholar was also searched. However, Google Scholar has limitations as a database for scoping reviews, including an innumerable number of results, a restricted number of characters for search terms and an inability to use some search operators. 30–32 Some solutions were devised and two searches of Google Scholar were undertaken. In the first search, a condensed string of search terms was used, and each study was individually extracted from the first six pages of results (with 10 results per page) 30–32 . In the second search, some informal online advice was followed, and the software Publish or Perish was used 33 , which allows users to use the software to search Google Scholar and retrieve more studies without having to manually extract each single result. 32 33 The string of search terms used for both searches on Google Scholar can be found in online supplemental appendix 1 . All eight databases were searched in March 2023. After the studies were included in the scoping review, their reference lists were also scanned for other papers (Phase 4 in figure 1 ). Other academics and research collaborators were contacted to request any references that fit the review’s inclusion criteria. 13 Finally, instead of two reviewers initially examining a select number of studies against the inclusion criteria, the reviewers first met to discuss the inclusion and exclusion criteria before searching the databases. 13

Supplemental material

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A diagram showing the process undertaken for the scoping review. Adapted from Moher et al (2009). 35

The citations from the databases were transferred into EndNote V.20 and then into Covidence. 13 Duplicate records of studies were detected by Covidence and manually by the reviewers and then removed. Two reviewers undertook the preliminary screening and the comprehensive screening. 13 During this process, if disagreement occurred about whether a study should be included, the two reviewers discussed how to resolve the problem(s). The workflow in Covidence allowed reviewers to document the reasons why studies were excluded at each stage. A summary of the reasons for exclusion at the stage of comprehensive screening is included in figure 1 . The preliminary screening and comprehensive screening of studies in Covidence resulted in the final 12 studies included in this scoping review. The process of stages 1 and 2 of the scoping review is depicted in figure 1 .

Stage 3: retrieving the data from the studies

Twelve studies satisfied the inclusion criteria, and each of the three reviewers read through these studies and added the relevant details into the data retrieval form that was included in the published protocol. 13 The data retrieval form was developed to identify details from the studies that were relevant to the three research objectives. The details included in the data retrieval form included classificatory information (author and publication date), methodological information (study aims and sample size), mental health findings, and findings about university-to-work-transitions. 13 Thus, the data retrieval form for each study included the information identified by each reviewer. Comments were added when there were conflicting details from each reviewer, which were further resolved through discussion.

Stage 4: analysing the data from the studies

The information from the data retrieval forms formed the basis for the scoping review’s findings. Key details from the studies are shown in both table 1 and 2 of online supplemental file 2 . The latter table includes the relevant findings in relation to mental health. A qualitative thematic analysis of the studies was conducted in both inductive and deductive ways. 34 The qualitative analyses were deductive because they were guided by the research objectives and the data retrieval form, as well as being inductive because we also allowed for the possibility for findings to be generated from our examination of the data.

Patient and public involvement

Our project is not clinically focused and patients were not involved in this study. Nevertheless, this scoping review was one part of a project investigating how the COVID-19 pandemic impacted Hong Kong graduates during their university-to-work transitions. Some stakeholders in this project were involved in aspects of this scoping review. Recent graduates—part of the ‘population’ of interest in the scoping review and project—were involved in the scoping review’s design and implementation. 13 The scoping review’s findings were disseminated in events delivered to stakeholders. Finally, the findings of the scoping review may help inform resources that will be developed to provide to stakeholders to improve students’ and graduates’ mental health during these transitions.

The scoping review process is depicted in figure 1 . 341 studies were located through database searches. Seven studies were found from existing papers that we located for our wider project, and four studies were found from the reference lists of the included papers ( figure 1 ). Our findings are based on the 12 studies that were included in the scoping review. As visible from the reasons for excluding studies ( figure 1 ), 35 we focused on studies that explicitly examined university-to-work transitions. Crucially, at some point in these papers, the studies had some finding(s) related to students’ and graduates’ mental health.

Methodological features of studies

The review’s first objective was to highlight the methodological features of these studies, which are addressed in table 1 of online supplemental file 2 . Starting broadly, several studies were published at the end of the 2000s, with others published throughout the 2010–2019 period. In contrast, 50% of studies (n=6) were published in the last 3 years. Thus, there has recently been an increased interest in the matter of graduates’ mental health during university-to-work transitions. The geographical setting of the studies is limited, with 58% (n=7) of studies conducted in the USA and 33% (n=4) in Europe. Only one study was conducted in Africa, and there was an absence of studies from Asia, the Pacific, and South America. Seventy five percent (n = 9) of studies were cross-sectional designs, and 25% (n = 3) were longitudinal designs. Fifty per cent (n=6) of studies presented solely quantitative findings, and 33% (n=4) of studies presented solely qualitative findings. Seventeen per cent (n=2) of studies presented both quantitative and qualitative findings. Seven studies (58%) used survey methods alone, two studies (17%) used only interviews, two (17%) studies used both surveys and interviews, and one study used participatory research methods. Finally, the studies’ sample sizes ranged from 10 to 5264 people (median sample size of 219.5 people).

One feature evident in table 1 of online supplemental file 2 is the lack of specification in the studies—namely, the authors did not explicitly mention crucial details of some studies. Fifty per cent (n=6) of studies did not mention the timescale of their project—that is, how long it took the authors to collect their data. Forty-two per cent (n=5) of studies did not specify details about the backgrounds of their participants, such as the majors of students and the industries in which graduates worked.

The findings about mental health from each included study are provided in table 2 of online supplemental file 2 . Some studies did not explicitly state how they operationalized mental health. 4 36–40 We included these studies because they did focus on mental health in their findings, but nevertheless, they did not explicitly operationalise it as a variable. Other studies defined mental health through the scales that they used. 21 41 For instance, Yang and Gysbers (2007) operationalized the variable of ‘psychological distress’ (p. 160) as measured by the Brief Symptom Inventory, which assessed the constructs of depression and anxiety. 42 Other studies defined mental health as comprising elements of psychological distress, including negative emotions, 43 anxiety 44 and depression. 45 Finally, there was little uniformity in the scales used to assess mental health, with studies using a variety of scales from the General Health Questionnaire 21 to the State Anxiety Inventory. 44

Findings related to mental health in university-to-work transitions

The review’s second objective was to synthesise the findings in relation to students’ and graduates’ mental health during university-to-work transitions. Some sources of mental health difficulties for students and graduates during these transitions are provided in table 2 of online supplemental file 2 . The absence of social support and economic forces (eg, overqualification and a poor job market) is associated with mental health problems. 36–38 Mental health is also related to other health problems for graduates, for instance, poor mental health is also linked to excessive alcohol consumption. 45

The findings also revealed a temporal dimension to mental health—namely, that there can be different mental health experiences at different points during the transition. Arnold and Rigotti identified different ‘trajectories of mental health’ (p. 724), including one whereby people started the transition with relatively good mental health, but this deteriorated over time. 39 The studies’ findings also reveal what we call ‘prospective negativity’, which relates to students experiencing stress, anxiety, and negative emotions before they even graduate because of the uncertainty associated with the university-to-work transition. 40 42 43 Furthermore, some graduates may experience stress and other mental health problems because of issues with their jobs. 4

Although the inclusion criteria specified a focus on negative mental health, the review also revealed positive dimensions of mental health. For instance, traits and variables such as optimism and career preparedness appear to offer some protection against adverse mental health. 21 36 42 Furthermore, obtaining a desired job is associated with lower psychological distress for graduates. 21 Finally, some studies found that graduates can achieve a state of relative psychological well-being as time passes and they gain experience in their jobs. 4 21

Theoretical and epistemological foundations

The review’s third objective was to unpack the theories used to conceptualise mental health and transitions. Some studies did not specify the theories that they used to conceptualise mental health. 21 37 40 43 45 One reason for the omission of the theoretical foundations of mental health was that, in most studies, it was not the primary variable that was examined. In fact, the studies examined a range of variables, from choice in underemployment, 38 to employability, 44 to substance abuse. 45 Indeed, mental health was sometimes an ancillary focus of the analyses. Alternatively, mental health was one dimension of the theories used to explain other variables in a study. For example, Okay-Somerville and colleagues' (2022) theoretical framework of a ‘graduate identity perspective (on) employability’ (p. 545) included psycho-emotional well-being as one dimension of graduates’ employability. 44 Finally, one study developed its own theory of university-to-work transitions, which was characterised by distinct mental health outcomes at the different stages. 4

Only three studies explicitly stated how they defined transitions in a substantive way. 4 41 42 For most studies, we had to surmise from other information that was provided—such as the participant inclusion criteria—in order to arrive at a definition. Based on these ‘educated guesses’, one can infer that graduation from university indicates the transition’s beginning, which also involves a sustained period characterised by employment or job searching. Some studies acknowledge that the period prior to graduation is also important in these transitions, and thus, examined those students in their final year of undergraduate study. 21 40 44

The word transition implies a linear concept—shifting from one discrete stage of life to another. However, some studies have acknowledged that university-to-work transitions are not necessarily linear. 40 45 Indeed, Aronson et al (2015) found that the university-to-work transition is an unstable period characterised by ‘frequent job changes’ (p. 1099). 37 Glassburn (2020) found that 63% of her interviewees indicated that they had changed jobs during their transition. 4 These findings imply that there can be smaller ‘transitions’ within the wider period. In addition, Glassburn (2020) provided the only staged model of transition among the studies, specifically focusing on graduates from a Master of Social Work programme. 4 Each phase of this transition model is characterised by unique mental health profiles. For instance, in the ‘sinking or swimming’ phase (p. 148), graduates experience excessive psychological distress, and in the ‘treading water phase’ (p. 151), graduates deal with burnout. 4

Relative to mental health, it is arguably the case that there is a stronger theoretical grounding for transitions. Some studies did not mention the theories they used to conceptualise university-to-work transitions. 21 Yet, there were diverse theoretical frameworks in these studies in relation to transitions. The studies drew on human capital theory, 40 organisational socialisation theory, 37 adaptation theory, 39 conservation of resources theory 39 and existing theoretical frameworks around resilience, 36 40 adaptability 36 and employability. 44 These observations highlight the varied intellectual traditions involved in studying university-to-work transitions.

Discussion and conclusions

This scoping review mapped the research on the mental health experiences and outcomes for students and graduates during the university-to-work transition. The goal was to identify the methodological characteristics of these studies. One conclusion is that this literature is fragmented because there are only 12 studies from different disciplines. Furthermore, not all of the studies directly focused on mental health. Rather, mental health was sometimes a secondary focus. The lack of an exclusive focus on mental health in some studies is understandable, as this is a period of empirical interest for many different reasons, such as employment and the skills needed in the workplace. Nevertheless, a sustained focus on future studies on mental health would be beneficial, as it could identify the unique features of mental health outcomes during this period.

Another methodological feature of these studies was multiple absences. First, there was an absence of studies from outside the USA and Europe. It is imperative to understand this topic in the context of the Global South and other ‘peripheries’. 46 The mental health outcomes for graduates in these geographical settings may be different owing to the diverse cultural norms and stigma surrounding mental health. 47 48 Mental health may be understood and conceptualised differently across cultures, and thus, we may have an incomplete picture of the culturally specific mental health challenges for graduates during university-to-work transitions. Second, there was an absence of clear definitions of the concepts of mental health and transitions in some studies. There should be systematicity in how concepts are defined in order to allow direct comparison across studies. A ‘shared vocabulary’ would allow researchers to understand whether references to mental health in one study are equivalent in conceptual and empirical terms to other studies. Researchers should make explicit their conceptualisations of mental health and transitions, and address questions such as, does the definition of mental health incorporate emotions, how long does a university-to-work transition last, and what are some of the features of this period of life?

A second goal was to identify the findings regarding the mental health of graduates and students during these transitions. In line with our inclusion criteria, the included studies found that people experienced mental ill health during this period. Yet, some of the studies also identified graduates’ positive psycho-emotional experiences in these transitions and some of the variables that protect against mental health problems. These findings underscore that university-to-work transitions do not necessarily have negative mental health impacts on students and graduates. The positive side of mental health during these transitions provides a more complete picture and enables others to create effective resources to intervene through the identification of protective factors.

The third goal was to investigate the theoretical foundations of mental health and university-to-work transitions. The review revealed that transition is not a uniform concept that relates to a linear change from student to worker. The university-to-work transition can be complicated by socioeconomic upheavals, such as the Great Recession 37 and the COVID-19 pandemic, 43 and differential access to material and social resources. 38 44 The findings reveal the idiosyncratic nature of the trajectories during this period, 41 the varying length between each stage 4 and the unstable nature of employment. 37 Thus, university-to-work transitions are processual in nature, with the ideal type being the linear change, but the reality is more complicated. Definitions of transitions should allow for movement throughout stages and delimit when these stages begin and end. In all, the scoping review reveals the complexity of the notion of transitions. Theoretical clarity on transitions benefits an understanding of mental health by clarifying issues including the variation in mental health outcomes at different points in the transition, and identifying times when students and graduates are at higher risk of psychological distress.

Future research should better conceptualise mental health and transitions, which would benefit stakeholders. To begin with, transitions and clarifying their exact time period(s) would aid universities in better targeting resources to support students’ and graduates’ mental health. If the university-to-work transition starts in the final year of education, then universities could direct tailor support directly to those students. Clarifying this time period would be beneficial to employers as it would provide them with insights into interventions and for how long they may need to support new hires.

This scoping review has some limitations, particularly, in its scope. 13 The review was limited to research published since 2000, which was set because of the reasoning that it would provide the most up-to-date work. 13 There may well be seminal work on this topic during prior decades that was missed. The review excluded studies not published in English, which perhaps led to an absence of work from the Global South. Thus, the review arguably provides a culturally limited understanding of mental health during university-to-work transitions. The small number of studies from a diverse range of disciplines is also a limitation as it means that the conclusions are somewhat disparate. A final limitation is that we did not include studies focusing on medical (and related) students and graduates. As such, there may be certain findings that were missed as a result.

The job market is subject to the whims of the economy, which could adversely impact people’s mental health during the university-to-work transition. This review provides insights into this research base and identifies the existing findings and gaps. Understanding this issue of societal importance provides concrete avenues for universities, employers and students to develop resources to bolster psychological well-being and prepare them for successful transitions.

Ethics statements

Patient consent for publication.

Not applicable.

Ethics approval

Our scoping review did not need ethical clearance because it did not use materials from human participants. In addition, it was focused on materials that are publicly available. Nevertheless, the scoping review is part of a wider project that received ethical approval from the University of Hong Kong's Human Research Ethics Committee (ethics code: EA200104).

Acknowledgments

We thank Brandon Kong for his work on the protocol for this review. We thank Afina Nafisah Jasmine and Apple Hui Min Kwok for their assistance during the revisions. We also extend our thanks to the reviewers and editors for their valuable comments on improving this manuscript.

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Supplementary materials

Supplementary data.

This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.

Data supplement 1
Data supplement 2
Data supplement 3

Contributors OZS and ZF conceptualised the research project, decided on the scoping review topic, supervised the scoping review and drafted and edited the paper. DME, AC and JSGC conducted the scoping review and drafted the paper. OZS is the guarantor of this paper and project.

Funding The scoping review is part of a project that received funding from the Research Grants Council Collaborative Research Fund (CRF), Hong Kong (The Educational, Social and Health Impacts of the COVID-19 Pandemic on University Graduates Transitioning to the Workforce in Hong Kong; grant no. C7086-21G). We thank the Hong Kong Research Grants Council Collaborative Research Fund for their funding in making this article open access. The funders have no role in the design, undertaking or writing of this scoping review.

Competing interests None declared.

Patient and public involvement Patients and/or the public were involved in the design, or conduct, or reporting, or dissemination plans of this research. Refer to the Methods section for further details.

Provenance and peer review Not commissioned; externally peer reviewed.

Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

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Examining the mental health of university students: A quantitative and qualitative approach to identifying prevalence, associations, stressors, and interventions

Affiliations.

1 Department of Dental Public Health and Behavioural Sciences, University of Missouri-Kansas City School of Dentistry, Kansas City, MO, USA.
2 Office of Research and Graduate Programs, University of Missouri-Kansas City School of Dentistry, Kansas City, MO, USA.
PMID: 35380931
DOI: 10.1080/07448481.2022.2057192

Objective To identify the prevalence of anxiety, depression, and suicidal ideation that would place university students at risk for mental health disorders. To explore the source of stressors and possible interventions that may benefit student mental health in a university setting.

Participants: University students (n = 483) who had been learning remotely due to the COVID-19 pandemic.

Methods: A mixed-methods cross-sectional survey was administered in 2020.

Results: Students were at an increased rate of depression, anxiety and suicidal ideation as compared to the general population. Female gender, lack of social support, living alone, being a first-generation college student and COVID-19 were significantly associated with mental health disorders. Stressors were identified and categorized into themes and interventions were recognized that may improve student well-being.

Conclusion: Students enrolled in university programs appear to experience significant amounts of anxiety, depression, and suicidal ideation. Additional mental health education, resources, and support is needed.

Keywords: Anxiety; COVID-19; college students; depression; suicidal ideation.

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ORIGINAL RESEARCH article

Mental health and well-being of university students: a bibliometric mapping of the literature.

$\r\nDaniel Hernndez-Torrano*$

1 Graduate School of Education, Nazarbayev University, Nur-Sultan, Kazakhstan
2 Nazarbayev University School of Medicine, Nur-Sultan, Kazakhstan
3 Psychological Counseling Center, Nazarbayev University, Nur-Sultan, Kazakhstan

The purpose of this study is to map the literature on mental health and well-being of university students using metadata extracted from 5,561 journal articles indexed in the Web of Science database for the period 1975–2020. More specifically, this study uses bibliometric procedures to describe and visually represent the available literature on mental health and well-being in university students in terms of the growth trajectory, productivity, social structure, intellectual structure, and conceptual structure of the field over 45 years. Key findings of the study are that research on mental health and well-being in university students: (a) has experienced a steady growth over the last decades, especially since 2010; (b) is disseminated in a wide range of journals, mainly in the fields of psychology, psychiatry, and education research; (c) is published by scholars with diverse geographical background, although more than half of the publications are produced in the United States; (d) lies on a fragmented research community composed by multiple research groups with little interactions between them; (e) is relatively interdisciplinary and emerges from the convergence of research conducted in the behavioral and biomedical sciences; (f) tends to emphasize pathogenic approaches to mental health (i.e., mental illness); and (g) has mainly addressed seven research topics over the last 45 years: positive mental health, mental disorders, substance abuse, counseling, stigma, stress, and mental health measurement. The findings are discussed, and the implications for the future development of the field are highlighted.

Introduction

The entrance to the university marks a period of transition for young people. Through this transition, students face new challenges, such as making independent decisions about their lives and studies, adjusting to the academic demands of an ill-structured learning environment, and interacting with a diverse range of new people. In addition, many students must, often for the first time, leave their homes and distance themselves from their support networks ( Cleary et al., 2011 ). These challenges can affect the mental health and well-being of higher education students. Indeed, there is evidence that a strain on mental health is placed on students once they start at the university, and although it decreases throughout their studies ( Macaskill, 2013 ; Mey and Yin, 2015 ), it does not return to pre-university levels ( Cooke et al., 2006 ; Bewick et al., 2010 ). Also, the probabilities of experiencing common psychological problems, such as depression, anxiety, and stress, increase throughout adolescence and reach a peak in early adulthood around age 25 ( Kessler et al., 2007 ) which makes university students a particularly vulnerable population.

The interest in mental health and well-being in university students has grown exponentially in the last decades. This is likely due to three interrelated challenges. First, although university students report levels of mental health similar to their non-university counterparts ( Blanco et al., 2008 ), recent studies suggest an increase and severity of mental problems and help-seeking behaviors in university students around the world in the last decade ( Wong et al., 2006 ; Hunt and Eisenberg, 2010 ; Verger et al., 2010 ; Auerbach et al., 2018 ; Lipson et al., 2019 ). Some researchers refer to these trends as an emerging “mental health crisis” in higher education ( Kadison and DiGeronimo, 2004 ; Evans et al., 2018 ). Second, psychological distress in early adulthood is associated with adverse short-term outcomes, such as poor college attendance, performance, engagement, and completion (e.g., King et al., 2006 ; Antaramian, 2015 ), and others in the long term, such as dysfunctional relationship ( Kerr and Capaldi, 2011 ), recurrent mental health problems, university dropout, lower rates of employment, and reduced personal income ( Fergusson et al., 2007 ). Third, there is a widespread agreement that higher education institutions offer unique opportunities to promote the mental health and well-being of young adults as they provide a single integrated setting that encompasses academic, professional, and social activities, along with health services and other support services ( Eisenberg et al., 2009 ; Hunt and Eisenberg, 2010 ). However, the majority of university students experiencing mental health problems and low levels of well-being are not receiving treatment ( Blanco et al., 2008 ; Eisenberg et al., 2011 ; Lipson et al., 2019 ) and, while universities continue to expand, there is a growing concern that the services available to provide support to students are not developing at an equivalent rate ( Davy et al., 2012 ).

In response to the increasing volume of research on the mental health and well-being of university students, there have been several attempts to synthesize the accumulating knowledge in the field and to provide an illustration of the theoretical core and structure of the field using traditional content analysis of the literature (e.g., Kessler et al., 2007 ; Gulliver et al., 2010 ; Hunt and Eisenberg, 2010 ; Sharp and Theiler, 2018 ). This study aims to extend the understanding of mental health in university students by providing a bird’s eye view of the research conducted in this field in recent decades using a bibliometric approach. Bibliometric overviews provide an objective and systematic approach to discover knowledge flows and patterns in the structure of a field ( Van Raan, 2014 ) reveal its scientific roots, identify emerging thematic areas and gaps in the literature ( Skute et al., 2019 ) and, ultimately, contribute to moving the field forward. Accordingly, this study employs several bibliometric indicators to explore the evolution of the field based on publication and citation trends, key actors and venues contributing to the advancement of research on mental health and well-being of university students, and the structure of the field in terms of patterns of scientific collaborations, disciplines underlying the foundations of the field, and recurrent research themes explored in the literature. This is important because, despite significant advances in the field, research on mental health and well-being remains a diverse and fragmented body of knowledge ( Pellmar and Eisenberg, 2000 ; Bailey, 2012 ; Wittchen et al., 2014a ). Indeed, mental health and well-being are nebulous concepts and their history and development are quite intricate, with a multitude of perspectives and contributions emerging from various disciplines and contexts (see section “Conceptualization of Mental Health, Mental Illness, and Well-Being: An Overview”). Therefore, mapping research on mental health and well-being in university students is essential to identify contributions and challenges to the development of the field, to help guide policy, research, and practice toward areas, domains, populations, and contexts that should be further explored, and to provide better care of students at higher education institutions ( Naveed et al., 2017 ).

Conceptualization of Mental Health, Mental Illness, and Well-Being: An Overview

This section provides an overview of the different perspectives adopted in the literature to conceptualize mental health, well-being, and other relevant constructs in order to identify the glossary of key terms that will be used in the search strategy to create a comprehensive corpus of documents on mental health and well-being in university students for this bibliometric review.

Perspectives on Mental Health and Mental Illness

There is no general agreement on the definition of mental health. For a long time, the term mental health has been used as a euphemism for mental illness ( Manwell et al., 2015 ). However, mental health and mental illness are regarded as distinct constructs nowadays and two main perspectives differentiating between mental health and illness are available in the literature. The continuum approach considers that mental health and mental illness are the two opposite poles of a continuum. Thus, there are various degrees of health and illness between these poles, with most of us falling somewhere in between. The categorical approach, on the other hand, represents mental health and illness as a dichotomy. People who manifest mental illness symptoms would belong to that category and labeled correspondingly, while those absent of these symptoms can be considered as mentally healthy ( Scheid and Brown, 2010 ).

Disciplinary Approaches to the Conceptualization of Mental Health/Illness

Conceptualizations of mental health/illness are largely dependent on the theoretical and paradigmatic foundations of the disciplines from which they emerge. In this context, the field has progressively evolved through the accumulation of knowledge generated in a diverse range of disciplines in the biomedical, behavioral, and social sciences. Biomedical disciplines are grounded in the medical paradigm focused on disease and (ab)normality and often emphasize dichotomous conceptions of mental health/illness ( Scheid and Brown, 2010 ). Research on mental health and well-being in this domain has been traditionally conducted from a psychiatric perspective, which aims to understand the dysfunctionality in the brain that leads to psychiatric symptoms and to also offer a pharmacological treatment to correct neuronal dysfunctions. Consequently, psychiatrists have historically considered mental health as a disease of the brain (e.g., depression), similar to any other physical disease, caused by genetic, biological, or neurological factors ( Schwartz and Corcoran, 2010 ). While the prevalence of psychiatric approaches to mental health is currently incontestable, the development of other biomedical disciplines has tremendously contributed to the progression of the field in recent decades. For example, Insel and Wang (2010) argue that insights gained from genetics and neuroscience contribute to the reconceptualization of “the disorders of the mind as disorders of the brain and thereby transform the practice of psychiatry.” (1979). In addition to that, other disciplines such as behavioral medicine have made important contributions to the field, although it has recently argued that mental health and behavioral medicine should be as two separate fields ( Dekker et al., 2017 ).

Within the behavioral sciences, the study of mental health focuses on the distinct psychological processes and mechanisms that prompt thoughts, feelings, and behaviors ( Peterson, 2010 ). Clinical psychology has the longest tradition in the psychological study of mental health and tends to focus on the assessment and treatment of mental illness and disorders that can alleviate psychological distress or promote positive states of being ( Haslam and Lusher, 2011 ). However, significant contributions to the field have also emerged from other branches of psychology less focused on psychopathology, including personality and social psychology, psychoanalysis, humanistic psychology, and cognitive psychology ( Peterson, 2010 ). Despite the diversity of theories, principles, and methodological approaches to understanding mental health within the behavioral sciences, these disciplines acknowledge that mental health have a biological basis and reside in the social context, and tend to prioritize continuum approaches to mental health ( Scheid and Brown, 2010 ).

Perspectives from the social sciences complement the biomedical and behavioral approaches by considering the influence of social and cultural environments in mental health/illness ( Horwitz, 2010 ). For example, sociologists are interested in how social circumstances (e.g., level of support available) affect levels of mental health/illness and how social structures shape the understanding and response to mental health issues [see Compton and Shim (2015) for an overview of the social determinants of mental health]. Similarly, medical anthropologists attend to the mental health beliefs and practices that form the cultural repertory within and across populations ( Foster, 1975 ). Beyond sociology and anthropology, social researchers in the fields of business and economics, family and ethnic studies, and educational research have also played a key role in advancing research on mental health in different directions.

The Importance of the Context in Mental Health

Certainly, most notions of mental health/illness in the literature derive from prevailing psychiatric and psychological traditions developed in Western countries ( Gopalkrishnan, 2018 ). However, cultural values and traditions do shape how mental health and mental illness are conceptualized across contexts ( Vaillant, 2012 ). In this regard, Eshun and Gurung (2009) pointed out that “culture influences how individuals manifest symptoms, communicate their symptoms, cope with psychological challenges, and their willingness to seek treatment.” (4). Fernando (2019) argued that issues related to the ‘mind’ developed and are often interpreted very differently in non-Western and Low- and Middle-Income Countries (LMICs). For example, cultures explain the manifestation of certain feelings and behaviors based on a range of motives including biological, psychological, social, religious, spiritual, supernatural, and cosmic. Failure to acknowledge alternative non-Western approaches to mental health and mental illness has resulted in imbalances of knowledge exchange and the permeation of dominating Western narratives into LMICs (i.e., so-called medical imperialism) ( Timimi, 2010 ; Summerfield, 2013 ). To address this issue, scholars have advocated for a greater willingness to embrace pluralism in the conceptualization of mental health and illness, which might help people to engage with particular forms of support that they deem to be appropriate for them, and to explore how knowledge and practices developed in LMICs can benefit those living in higher-income countries (i.e., knowledge “counterflow”) (see White et al., 2014 ).

Prioritizing Positive Mental Health: The Science of Well-Being

Despite the diversity of disciplinary and contextual approaches to mental health, current definitions of mental health have two things in common. First, mental health is considered from a biopsychosocial point of view that incorporates biological, psychological, and social factors. Second, mental health implies something beyond the absence of mental illness (e.g., Bhugra et al., 2013 ; Galderisi et al., 2015 ). An example is the definition by the World Health Organization which refers to mental health as “a state of well-being in which every individual realizes his or her own potential, can cope with the normal stresses of life, can work productively and fruitfully, and is able to make a contribution to her or his community” ( World Health Organization, 2004 ). This definition contributed to substantial progress in research and practice in the field as it expanded the notion of mental health beyond the absence of mental illness and integrated the presence of positive features ( Galderisi et al., 2015 ).

Research on positive mental health is relatively new but has grown rapidly in the last decades fueled by advocates of positive medicine and psychology, who have argued for a change of paradigm from medical and psychopathological-oriented models of mental health that focus on disorders and illness toward more strength-based approaches, which pay more attention to what is right about people and positive attributes and assets ( Kobau et al., 2011 ). In this regard, the term mental well-being has been progressively incorporated into the study of mental health to account for the positive aspects of mental health beyond the absence of negative factors. While there is not a universally accepted definition of well-being, two perspectives have dominated the discourses on well-being in the literature: subjective well-being (SBW) and psychological well-being (PWB). SWB is based on hedonic perspectives of pleasure and represents “people’s beliefs and feelings that they are living a desirable and rewarding life” ( Diener, 2012 ). SBW is strongly linked with the idea of happiness and is typically understood as the personal experience of high levels of positive affect, low levels of negative affect, and high satisfaction with one’s life ( Deci and Ryan, 2008 ). PWB is grounded in Aristotelian ideas about eudaimonia, i.e., self-realization, with the ultimate aim in life being to strive to realize one’s true potential ( Ryff and Singer, 2008 ). PWB has been broadly defined as a state of positive psychological functioning and encompasses six dimensions: purpose in life (i.e., the extent to which respondents felt their lives had meaning, purpose, and direction); autonomy (i.e., whether they viewed themselves as living in accord with their own convictions); personal growth (i.e., the extent to which they were making use of their personal talents and potential); environmental mastery (i.e., how well they were managing their life situations); positive relationships (i.e., the depth of connection they had in ties with significant others); and self-acceptance (i.e., the knowledge and acceptance they had of themselves, including awareness of personal limitations) ( Ryff, 1989 ).

Integrating Mental Health, Mental Illness, and Well-Being

The contribution of positive mental health frameworks to the advancement of the field has been undeniable. However, definitions that overemphasize positive emotions and productive functioning as key indicators of mental health have been recently challenged because of the potential they have to discriminate against individuals and groups that, for example, might not be able to work productively or function within the environment because of individual physical characteristics or contextual constraints ( Galderisi et al., 2015 ). To address these issues, Keyes has successfully integrated the notions of mental illness, mental health, well-being, and other related terms in the literature into a conceptual framework that allows for a more comprehensive understanding of mental health ( Keyes, 2005 , 2007 ; Keyes and Michalec, 2010 ). The model argues that neither pathogenic approaches focusing on the negative (e.g., mental illness) nor salutogenic approaches focusing on the positive (e.g., well-being) can alone accurately describe the mental health of a person ( Keyes and Michalec, 2010 ). Instead, the model proposes that mental illness and well-being represent two correlated but differentiated latent continua in defining mental health. More specifically, mental illness and well-being lie on two separate spectra, the first going from absent to present mental illness and the second running from low to high well-being ( Slade, 2010 ). The absence of mental illness, therefore, does not necessarily imply high levels of well-being. Correspondingly, low levels of well-being do not always indicate the presence of mental illness. Further, in this model, mental health is defined as not only the absence of mental illness, not the mere presence of high well-being. Complete mental health (i.e., flourishing) is a result of experiencing low mental illness and high levels of well-being. Incomplete mental health (i.e., languishing), on the other hand, refers to the absence of mental illness symptoms and low reported levels of well-being. Two other conditions are possible within this framework. Incomplete mental illness (i.e., struggling) refers to high levels of well-being accompanied by high mental illness symptoms. Lastly, complete mental illness (i.e., floundering) accounts for low levels of well-being and high mental illness symptoms ( Keyes and Lopez, 2002 ).

The Present Study

In light of the complexity of the constructs of mental health and well-being and the multiple theoretical, disciplinary, and contextual approaches to their conceptualization, this study seeks to map out the terrain of international research and scholarship on mental health and university students for the period 1975–2020. More specifically, this study aims to provide new insights into the development and current state of mental health research in university students by mapping and visually representing the literature on mental health and well-being of university students over the last 45 years in terms of the growth trajectory, productivity, and social, intellectual, and conceptual structure of the field. First, the study describes the development of research mental health and well-being in university students examining the trends in publication and citation data between 1975 and 2020 (i.e., growth trajectory). Second, the study identifies the core journals and the research areas contributing most to the development of the field, as well as the key authors and countries leading the generation and dissemination of research on mental health and well-being in university populations (i.e., productivity). Third, the study outlines the networks of scientific collaboration between authors, and countries (i.e., social structure). Fourth, the scientific disciplines underlying the intellectual foundations of research on mental health and well-being in university settings (i.e., intellectual structure) are uncovered. Fifth, the study elucidates the topical foci (i.e., conceptual structure) of the research on the mental health and well-being of university students over the last 45 years.

Materials and Methods

A bibliometric approach was used in this study to map the literature on mental health and well-being in university students over the last 45 years using metadata extracted from four indexes of the Web of Science (WoS): The Science Citation Index-Expanded (SCI-Expanded); the Social Sciences Citation Index (SSCI); the Arts & Humanities Citation Index (A&HCI); and the Emerging Sources Citation Index (ESCI). Several reasons justified the selection of the WoS database in this study. First, the WoS remains as the standard and most widely used for bibliometric analysis ( Meho and Yang, 2007 ). Second, the WoS is a multidisciplinary database and includes publications on mental health and well-being emerging from distinctive research areas and disciplines published in more than 20,000 journals ( McVeigh, 2009 ). Using specialized databases such as PubMed would introduce biases into the search strategy favoring biomedical research disciplines. Still, it is important to note that interdisciplinary databases such as WoS and Scopus discriminate against publications in the Social Sciences and Humanities and publications in languages other than the English language ( Mongeon and Paul-Hus, 2016 ), so the picture provided by WoS is still imperfect. Third, while other databases might provide wider coverage, WoS includes publication and citation information from 1900. For example, Scopus has complete citation information only from 1996 ( Li et al., 2010 ). Moreover, Google Scholar provides results of inconsistent accuracy in terms of citations, and citation analyses in PubMed are not available ( Falagas et al., 2008 ). Fourth, WoS has demonstrated better accuracy in its journal classification system compared to Scopus database ( Wang and Waltman, 2016 ).

The methodological approach used in this study is presented in Figure 1 and further elaborated in the following paragraphs.

Figure 1. Methodological framework.

Search Strategy

To create a comprehensive corpus of documents on the mental health and well-being of university students, three parallel searches were performed, which accounted for the multiple approaches and perspectives that have been used in the field, as identified in the Section “Conceptualization of Mental Health, Mental Illness, and Well-Being: An Overview.” All the searches were conducted in the last week of January 2020. The first search aimed at capturing research on mental health broadly and included one single keyword in the topic field: [“mental health”]. The second search was implemented to capture research focusing on pathogenic approaches to mental health. Key terms used in the literature to refer to the negative side of mental health, as well as the most frequent mental health problems experienced by university students, were introduced in this search in the title field: [“mental illness,” “mental disorder ∗ ,” “mental distress,” “psychological distress,” “psychopathology,” “depression,” “anxiety,” “stress,” “suicide,” “eating disorder ∗ ,” “substance use”]. In the third search, keywords reflecting salutogenic approaches to mental health were input. These included terms related to mental health from a positive mental health perspective (i.e., well-being). These key terms were added in the title field and included the following: [“well-being,” “wellbeing,” “wellness,” “life satisfaction,” “happiness,” “positive affect,” “purpose in life,” “personal growth,” “self-determination”].

To retrieve research relevant only to higher education students, another set of keywords was imputed in all three searches in the title field. These included: [“university,” “college,” “higher education,” “tertiary education,” “post-secondary education,” “postsecondary education,” “undergrad ∗ student,” “grad ∗ student,” “master’s student,” “doctoral student,” “Ph.D. student”]. The Boolean operator OR was used between keywords in all the three searches to secure a higher number of relevant hits. Also, asterisks were used as wildcards to account for multiple variations in several keywords (e.g., disorder and disorder-s). All searches were limited to journal articles published between 1975 and 2020 (both inclusive). No restrictions on language were implemented in the search.

The search strategy retrieved a total of 6,356 hits ( n search 1 = 2782; n search 2 = 2814, n search 3 = 760). After the removal of duplicates, 5,561 research articles were finally selected and retained for the study. For each of the documents obtained in the search, the authors extracted metadata about the title of the paper, the year of publication, the journal, the number of citations, and the authors’ name, organization, and country. Also, the title, the abstract, the author’s keywords, and cited references were retrieved.

Data Analysis Procedures

The corpus of the literature was then analyzed using descriptive and bibliometric approaches to provide an overall picture of the evolution and current state of the research on mental health and wellbeing in university settings. Frequency counts of the number of publications and citations per year were obtained to describe the growth trajectory of research on the mental health and well-being of university students. Rank ordered tables were produced to describe the productivity of the field in terms of core journals and research areas, as well as leading scholars and countries contributing to the development of the field.

Bibliometric analyses in VOSViewer software were implemented to examine and visually represent the social, intellectual, and conceptual structure of the field. VOSViewer is a freely available computer software for viewing and constructing bibliometric maps 1 . In VOSViewer, the units of analysis are journals, publications, citations, authors, or countries, depending on the focus of the analysis. The units of analysis are represented in the maps as circular nodes. The size of the node accounts for volume (e.g., number of publications in the dataset by an author) and the position represents the similarity with other nodes in the map. Closer nodes are more alike than nodes far apart from each other. The lines connecting nodes represent the relationship between nodes and their thickness indicates the strength of that relationship. Finally, the color of the node denotes the cluster to which each node has been allocated. Nodes are clustered together based on relatedness ( Van Eck et al., 2010 ). The software uses a distance-based approach to constructing the bibliometric maps in three steps ( Van Eck and Waltman, 2014 ). In the first step, the software normalizes the differences between nodes. In the second step, the software builds a two-dimensional map where the distance between the nodes reflects the similarity between these nodes. In the third step, VOSViewer groups closely related nodes into clusters ( Van Eck and Waltman, 2014 ).

A series of co-authorship analyses were performed to examine the social structure of research on mental health and well-being in university students. In these analyses, the units of analysis were authors and countries/territories. Each node in the map represents an author or a country/territory and the lines connecting them reflect the relationship between nodes. Clusters represent networks of scientific collaboration, which might be interpreted as groups of authors or countries frequently publishing together (e.g., research groups in the case of authors).

Co-citation analysis of journals was implemented to explore the intellectual structure of the field. Here, the units of analysis were journals in the dataset and the map reflects co-citation relationships between journals. Two journals are co-cited if there is a third journal citing these two. The more times a pair of journals are cited by other journals, the stronger their co-citation relationship will be. Frequently co-cited journals are assumed to share theoretical and semantical grounds. Therefore, in our study, clusters of frequently co-cited journals can be interpreted as disciplines underlying the foundations of research on mental health and well-being in university students.

Finally, a co-occurrence analysis of keywords was used to uncover the conceptual structure of the field. The units of analysis, in this case, were the authors’ keywords. The more often two keywords appear in the same record, the stronger their co-occurrence relationship. Clusters of co-occurring keywords represent in this study the topical foci (i.e., knowledge base) that have been addressed in the literature in mental health and well-being in university students in the last 45 years.

Findings and Discussion

Growth trajectory: evolution of publications and citations in the field.

The developmental patterns of a particular field can be well demonstrated by trends in publications and citations. The 5,561 publications in the dataset have been cited 87,096 times, with an average of 15.6 citations per item. Figure 2 shows the growth trajectory of publication data of research on mental health and well-being in university students from 1975 to January 2020. Overall, the trends demonstrate a gradual increase in the scholarly interest in the mental health of university students over the last 45 years that can be organized in three stages: an emergence stage, in which publications rose slowly (1975–2000); a fermentation stage, with a notable increase in publications in the field (2000–2010); and a take-off stage, during which the number of records published per year in the field has almost risen 10 times (2010–2020). The steady increase of publications in the last 15 years coincides with the first calls for attention on the increase and severity of mental problems and help-seeking behaviors of college students ( Kadison and DiGeronimo, 2004 ; Evans et al., 2018 ), potentially indicating a growing interest in exploring the epidemiology of mental disorders and the role of universities in promoting the mental health and well-being of students. A similar pattern has also been observed in a recent bibliometric study examining global research on mental health both in absolute terms and as a proportion of all papers published in medicine and across disciplines, which certainly reflects an increase in the general interest in the field ( Larivière et al., 2013 ).

Figure 2. Growth of research on mental health and well-being of university students.

Productivity I: Core Journals and Research Areas

In total, 1,560 journals published the 5,561 records included in the dataset. Table 1 presents the ten core journals in the field. The Journal of American College stands out as the main publication venue in the field, accumulating around 5% of the publications in the dataset ( n = 270). Psychological Reports and Journal of College Student Development also stand out, publishing 119 and 102 studies, respectively. The Journal of Counseling Psychology ranks fourth in the list with 83 records. Despite being an interdisciplinary and relatively young journal, Plos One appears in the top five journal publishing research on mental health and well-being in university students.

Table 1. Core journals ranked by number of records.

The top research areas contributing to the publication of research on the mental health and well-being of university students are presented in Table 2 . Nearly half of the records in the dataset are published in psychology journals. Another influential research area in the field is psychiatry , which captures almost 20% of the publications. Journals on education and educational research also accumulate a considerable number of publications in the field (15%). Other relevant research areas in the field are connected with health and medicine, including public environmental occupational health , substance abuse , general internal medicine , neurosciences neurology , health care sciences services , and nursing . Finally, the field is also grounded, although to a lower extent, in the publications emerging from journals in the social sciences , family studies , and social work research.

Table 2. Top research areas ranked by number of records.

All in all, the productivity analysis for journals and research areas showed that most research on mental health and well-being in university students is disseminated in journals in the “psy disciplines”’ (i.e., psychology and psychiatry) ( McAvoy, 2014 ), which is consistent with previous research on mental health in general populations (e.g., Haslam and Lusher, 2011 ). However, our findings demonstrated that the volume of research in psychology doubles that of research emerging from psychiatric journals. This contrasts with the findings by Haslam and Lusher (2011) , who demonstrated that psychiatry journals had a greater influence on mental health research compared to clinical psychology journals and that psychiatry journals accumulate a higher volume of research and citations on mental health research. This is probably because our study includes publications emerging from all branches of psychology, unlike the study by Haslam and Lusher, which included only journals in the field of clinical psychology. Additionally, mental health services in higher education are typically provided by counseling centers led and staffed by non-medical professionals (e.g., psychologists, social workers, counselors, and family therapists) who tend to adopt developmental models of practice grounded in the behavioral sciences and focused on adjustment issues, vocational training, employment, and other personal needs rather than diagnosis and symptom reduction, more common in the biomedical sciences (i.e., psychiatry) ( LeViness et al., 2018 ; Mitchell et al., 2019 ).

Productivity II: Leading Authors and Countries/Territories

The 5,561 publications in the dataset were published by a total of 16,161 authors from 119 countries worldwide. Table 3 shows the researchers with the highest number of publications in the field. D. Eisenberg appears as the most productive researcher, followed by K. Peltzer and S. Pengpid. Authors on the list come from diverse geographical backgrounds. Five of the authors work at three different American universities (University of Michigan, Harvard Medical School, and Boston University), two researchers work at KU Leuven University (Belgium), and two other authors are affiliated to the same two universities in Thailand and South Africa. Other prolific researchers are affiliated with higher education institutions in the Netherlands, Egypt, and Germany.

Table 3. Leading authors ranked by number of records.

Countries and territories leading research on mental health and well-being of university students are presented in Table 4 . The United States is the indisputable leader in this field, publishing more than half of the records in the dataset. This is nearly 10 times the number of publications produced in China, which occupies the second position in the ranking and accounts for nearly 6% of the volume of research in the dataset. Three predominantly English speaking countries/territories complete the top five of the ranking: Canada (265 records), Australia (254), and England (243). The rest of the countries in the list are situated in Europe (Spain, Germany, Turkey), Western Asia (Iran), Africa (South Africa), and East Asia (Japan), which demonstrates that research on college students’ mental health and well-being is a matter of concern in different regions of the world, at least to some extent.

Table 4. Leading countries/territories ranked by number of records.

Overall, the productivity analysis for authors and countries indicated that the research of mental health and well-being of university students occurs in a variety of locations around the world, especially in developed countries, and in a very prominent way, in the United States. This is not surprising since it is in those countries where better infrastructures and more abundant resources for research are available ( Wong et al., 2006 ), and a more lasting tradition in the study of mental health, in general, exists ( Gopalkrishnan, 2018 ). However, Larivière et al. (2013) found that the productivity of the United States on mental health research has dropped significantly and remained stable in other two English speaking countries (the United Kingdom and Canada) since 1980. On the contrary, the number of publications from European countries and the five major emerging national economies (Brazil, Russia, India, China, and South Africa), has experienced remarkable growth, and collectively account nearly for half of the publications in the field. Still, the predominance of knowledge generated in the developed world today, which tends to be grounded on psychiatric and psychological perspectives, might be eclipsing non-traditional views on mental health and well-being that are popular in other regions of the world and, therefore, limiting the development of effective initiatives that align better with local norms, values, and needs in LMICs ( Timimi, 2010 ; Summerfield, 2013 ).

Social Structure: Networks of Scientific Collaboration

Research collaboration is regarded as an indicator of quality research and a means to improve research productivity and academic impact (i.e., citations) ( Kim, 2006 ; Abramo et al., 2009 ). In particular, international research collaboration is considered a key contributor to the social construction of science and the evolution of scientific disciplines ( Coccia and Wang, 2016 ). There is recent evidence that national and international research collaborations have been accelerating in recent years ( Gazni et al., 2012 ; Wagner et al., 2015 ), especially in applied fields such as medical and psychological disciplines ( Coccia and Bozeman, 2016 ). In this study, co-authorship analyses were performed to find out patterns in the scientific collaboration between researchers and countries/territories on the mental health and well-being of university students.

Figure 3 demonstrates collaborative ties among authors who published at least 5 articles in the dataset ( n = 179). The map shows the existence of multiple productive collaborative networks of five or more researchers contributing to the development of the field. The largest collaboration network (red cluster) represents an international research group composed of 15 scholars affiliated to universities in the United States, Belgium, and Netherlands. This cluster groups some of the leading scholars in the field, including R. P. Auerbach, R. Brauffaerts, R. C. Kressler, and P. Cuijpers. Moreover, researchers in this cluster lead The WHO World Mental Health International College Student (WMH-ICS) Initiative, a large scale international project aimed at promoting the mental health and well-being of college students around the world through generating epidemiological data of mental health issues in university students worldwide, designing web-based interventions for the prevention and promotion of mental health, and disseminating evidence-based interventions ( Cuijpers et al., 2019 ). The second biggest cluster (green) represents an intra-national research network that includes 10 researchers from eight different higher education institutions in the United States. The dark blue cluster represents an institutional collaborative network, including nine researchers from the School of Public Health, Puerto Rico. Other prominent clusters in the map represent collaborative research networks between eight (olive color) and seven researchers (turquoise, violet, orange, and mellow mauve). This contrasts, however, with the limited collaboration that exists between clusters. Only four of the clusters on the map demonstrate some kind of scientific collaboration in the field (light blue, pink, brown, and yellow).

Figure 3. Collaborative research networks between researchers. Only researchers with five or more publications were considered in the analysis ( n = 179).

Cross-country collaboration networks in mental health and well-being of university students study are presented in Figure 4 . Research collaborations between countries with 20 or more publications were considered in this analysis ( n = 45). The United States occupies the central position of the map and shares collaborative ties with all other countries/territories, forming a cluster together with China, South Korea, and Taiwan. Overall, the results suggest that international collaborations in the field are framed to a large extent by cultural, linguistic, and geographical proximity. For instance, the largest cluster (red) is formed by two European countries (Spain and Portugal) and other South American countries with whom they share historical and cultural backgrounds. Other European countries form the purple cluster. Similarly, the blue cluster clearly brings together predominantly English-speaking countries and territories, while the green cluster agglomerates a range of Asian countries.

Figure 4. Collaborative research networks between countries and territories. Only countries with 20 or more publications were considered in the analysis ( n = 45).

Collectively, the results of our study suggest that research collaboration in the field of mental health and well-being in university students remains relatively scarce and localized to date. The social structure of the field at the author level could be described as an archipelago formed by a large number of islands (research groups) of different composition and size but with few bridges connecting them, which suggests a relatively fragmented research community. Moreover, while the existence of international collaborative networks was evident in the analysis, they seem to be formed within national borders, between researchers in neighboring countries/territories, or between countries that share cultural, linguistic, and historical heritages. This may be due to the important role that cultural and traditional values play in the conceptualization of mental health and well-being across contexts ( Eshun and Gurung, 2009 ; Vaillant, 2012 ; Fernando, 2019 ). Also, language differences, divergent cross-national institutional and organizational traditions, and increased costs of extramural collaboration, have been found to complicate the formation and continuity of research partnerships in health research ( Hooper et al., 2005 ; Freshwater et al., 2006 ). Nevertheless, limited within- and between-country research collaboration arguably poses challenges to the development of a field in terms of lost opportunities to challenge assumptions taken for granted and move toward fresh perspectives, push boundaries in methods and techniques, meet diverse groups of people from differing cultures and get immersed in those cultures, share information, resources, and skills, and address common mental health problems through the pooling of resources ( Rolfe et al., 2004 ; Freshwater et al., 2006 ).

Intellectual Structure: Disciplines Underlying the Foundations of the Field

Interdisciplinarity is considered as a valuable approach to address the complex and multidimensional nature of health and well-being ( Mabry et al., 2008 ). Buckton (2015) argues that the integration of medical, psychological, and social sciences have contributed to generate “new insights into theory, practice, and research in mental health and development.” (3). To examine the disciplines underlying research on the mental health and well-being of university students, a journal co-citation analysis was performed. In this analysis, only journals with at least 50 citations were considered ( n = 593). The nodes on the map represent journals and their size reflects the number of co-citation relationships with other journals. Colors account for journal clusters, which agglutinate journals with higher co-citation relationships and stronger semantic connectedness. Clusters were interpreted and labeled accounting for the WoS categorization of the journals with the highest co-citation links within each cluster. For example, if the Journal of Personality and Social Psychology , the Journal of Counseling Psychology , and Personality and Individual Differences clustered together, this group was interpreted as the personality, social, and counseling psychology cluster.

In general, the findings of this study suggest that research on mental health and well-being in university students is interdisciplinary, to a certain extent, and mainly emerges from the convergence of research conducted in the behavioral and biomedical sciences, as it has been suggested elsewhere ( Schumann et al., 2014 ; Wittchen et al., 2014b ). More specifically, the map shows that the research in the mental health and well-being of university students is constructed through the integration of knowledge generated in five interconnected disciplines (see Figure 5 ). To the left of the map, the red cluster integrates journals on personal, social, and counseling psychology . To the right, the blue cluster represents the contribution of psychiatric journals to research to the formation and development of the field. At the top, the yellow cluster groups journals on substance abuse and issues related to alcohol consumption, addiction, and interpersonal violence. At the bottom of the map, journals covering topics on eating behaviors, sleep, and other issues related to physical health converge on the green cluster. At the center of the map is the purple cluster, which includes journals in the area of clinical psychology and behavioral therapy .

Figure 5. Map of clustered network journals based on co-citation data. Only publications with 50 or more citations were considered in the analysis ( n = 593).

More broadly, the findings suggest that biomedical sciences contribute to a large extent to the composition of the field. Psychiatric research emerged in our study as an obvious building block in the study of university students’ mental health and well-being, which is not surprising considering the historical contributions of biomedical disciplines to mental health research ( Schwartz and Corcoran, 2010 ). Within the behavioral sciences, personality and social psychology, which explores processes and mechanisms through which social phenomena influence mental health and well-being ( Sánchez Moreno and Barrón López de Roda, 2003 ), appears as a key discipline underlying the foundations of the field. Surprisingly, clinical psychology journals occupy a central position in the map and demonstrate co-citation relationships with journals from all other clusters but make up the most dispersed network and account for a considerably lower volume of co-citation relationships in the field. This suggests that clinical psychology journals are more subordinate to journals in other disciplines in terms of citations flows, and ultimately, play a less unique role in research on the mental health and well-being of university students, as suggested by Haslam and Lusher (2011) . Interestingly, research arising from the social sciences (e.g., sociology and anthropology) does not seem to make a distinctive contribution to the intellectual structure of the field, which suggests that the influence of social contexts and cultures on university students’ mental health and well-being (e.g., inequality, social norms, public policies, cultural beliefs, and values) is an underexplored research area. Still, the density of co-citation network relationships within and between clusters is particularly noteworthy, considering the lack of common language between disciplines, the absence of a shared philosophy of practice on mental health, and the tensions between medical, psychological, and social explanations of mental distress ( Bailey, 2012 ).

Conceptual Structure: Topical Foci Addressed in the Literature Over the Last 45 Years

The topical foci of research on the mental health and well-being of university students during the 1975–January 2020 period are presented in Figure 6 . The map offers a visual representation of the co-occurrence analysis of author keywords of all the publications included in the dataset. Only the most frequently occurring keywords (25+ occurrences) were considered in the analysis ( n = 84). Items that were not related to others and do not belong to the existing clusters were excluded. The size of the nodes indicates the occurrence of author keywords in the dataset and the thickness of edges represents the co-occurrence strength between pairs of keywords.

Figure 6. Topical foci in mental health and well-being of university students research. Only keywords with 25 or more occurrences were considered in the analysis ( n = 84).

The most frequent keywords in the dataset, excluding students’ descriptors (e.g., college students and university students), refer to common mental health challenges experienced by university students such as depression ( n = 612), anxiety ( n = 353), and stress ( n = 341). Salutogenic-related keywords such as well-being and life satisfaction occurred less often ( n = 138, n = 113, respectively), suggesting that pathogenic approaches to the exploration of mental health issues in higher education are more widespread. More broadly, seven general themes seem to summarize the topical foci of interest in the field of mental health and well-being of university students over the last 45 years. First, there has been a general interest in positive mental health , as denoted by frequently co-occurring key terms such as well-being, self-esteem, life satisfaction, social support, emotional intelligence, and happiness (red cluster). Second, mental disorders stand as another theme widely addressed in the literature, with a special emphasis on depression, anxiety, and to a lesser extent, suicide and suicidal ideation (green cluster). A third topical area in this field has been substance abuse , most predominantly alcohol consumption (blue cluster). The fourth theme reflects college counseling for mental health , including interventions and protective factors such as mindfulness, stress management, spirituality, and help-seeking (yellow cluster). Other topics reflected in the map are mental illness stigma (purple), stress (e.g., psychological distress and coping) (light blue), and mental health measurement (orange).

This study provides a comprehensive overview of the research on university students’ mental health and well-being in the last 45 years using bibliometric indicators. In general, the results reveal interesting trends in the evolution of the field over the last four decades and promising scientific patterns toward a better understanding of the mental health and well-being of university students internationally. First, the interest in the mental health and well-being of university students has grown in the last decades and in a very significant way during the last 10 years, indicating that this area has not still reached its maturity period and will continue developing in the future. Second, research in the field is relatively interdisciplinary and emerges from the convergence of research conducted in several disciplines within the behavioral and biomedical sciences. Third, research in this field is produced by a community of productive researchers coming from several regions around the world, most notably in the United States, which secures a generation of scholars that will continue shaping the field in the years to come. Fourth, over the last 45 years, researchers have been able to address a multitude of research topics in the field, including positive mental health, mental disorders, substance abuse, counseling, stigma, stress, and mental health measurement.

However, this study also identified some issues that could be hindering the development of the study of the mental health and well-being of university students. For example, the research available overrepresents theoretical and disciplinary approaches from the developed world. Additional studies on the field from developing economies and LMICs are needed to provide a more comprehensive picture and ensure a fair representation of the multiple perspectives available in the field. Such studies would inform administrators and practitioners on how to broaden and enrich available programs and initiatives to promote mental health and well-being in higher education contexts in order to offer alternative forms of support that university students find appropriate for their social and cultural values. Moreover, the research community contributing to the development of the field is relatively fragmented. There are multiple research groups but little research collaborations between them and, at the international level, these connections tend to be limited by geographic, cultural, and language proximity. In this context, more actions like the WMH-ICS Initiative could provide a partial solution to this problem by strengthening national and international research partnerships and facilitating knowledge exchange across regions. Also, special issues in the core journals in the field inviting cross-cultural studies on the topic could contribute to promoting research collaboration across regions and research in less represented countries. The field would also benefit from a greater volume of research from the social sciences and humanities exploring the influence of social, cultural, economic, and educational factors on the conceptualization, manifestation, and experience of mental health and well-being. Moreover, more studies emerging from disciplines such as sociology, anthropology, business, and education, would likely increase the permeability of positive mental health concepts into the field and contribute to the promotion of salutogenic approaches to the study of mental health and well-being of university students.

This study has several limitations. First, publications were retrieved only from the WoS database, which limits the generalizability of the findings. Second, WoS provides stronger coverage of Life Sciences, Biomedical Sciences, and Engineering, and includes a disproportionate number of publications in the English language ( Mongeon and Paul-Hus, 2016 ). This could partially explain the low number of publications emerging from the Social Sciences, the Arts, and the Humanities, and research conducted in non-English speaking countries in the present study. Third, only journal articles were retrieved for analysis, excluding other relevant publications in the field such as reviews, book chapters, and conference proceedings. Future studies could replicate the findings of this study using alternative databases (e.g., Scopus and PubMed) or a combination of them, as well as different filters in the search strategy, to provide an alternative coverage of research conducted in the field. Nevertheless, we believe that the bibliometric approach used in this study offers novel insights about the development and current status of the field and some of the challenges that undermine its progression.

Data Availability Statement

The datasets generated for this study are available on request to the corresponding author.

Author Contributions

DH-T and LI contributed to conception and design of the study, organized the database, and performed the statistical analysis. DH-T, LI, and JS wrote the first draft of the manuscript. NL, AC, AA, YN, and AM wrote the sections of the manuscript.

This research was funded by the Nazarbayev University Faculty-Development Competitive Research Grants Program (Reference Number 240919FD3902).

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Keywords : mental health, mental illness, well-being, psychological distress, university students, higher education, bibliometric review, VOSViewer

Citation: Hernández-Torrano D, Ibrayeva L, Sparks J, Lim N, Clementi A, Almukhambetova A, Nurtayev Y and Muratkyzy A (2020) Mental Health and Well-Being of University Students: A Bibliometric Mapping of the Literature. Front. Psychol. 11:1226. doi: 10.3389/fpsyg.2020.01226

Received: 03 March 2020; Accepted: 11 May 2020; Published: 09 June 2020.

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Copyright © 2020 Hernández-Torrano, Ibrayeva, Sparks, Lim, Clementi, Almukhambetova, Nurtayev and Muratkyzy. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Daniel Hernández-Torrano, [email protected] ; [email protected]

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Published: 20 September 2022

Factors that influence mental health of university and college students in the UK: a systematic review

Fiona Campbell 1 ,
Lindsay Blank 1 ,
Anna Cantrell 1 ,
Susan Baxter 1 ,
Christopher Blackmore 1 ,
Jan Dixon 1 &
Elizabeth Goyder 1

BMC Public Health volume 22 , Article number: 1778 ( 2022 ) Cite this article

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Worsening mental health of students in higher education is a public policy concern and the impact of measures to reduce transmission of COVID-19 has heightened awareness of this issue. Preventing poor mental health and supporting positive mental wellbeing needs to be based on an evidence informed understanding what factors influence the mental health of students.

To identify factors associated with mental health of students in higher education.

We undertook a systematic review of observational studies that measured factors associated with student mental wellbeing and poor mental health. Extensive searches were undertaken across five databases. We included studies undertaken in the UK and published within the last decade (2010–2020). Due to heterogeneity of factors, and diversity of outcomes used to measure wellbeing and poor mental health the findings were analysed and described narratively.

We included 31 studies, most of which were cross sectional in design. Those factors most strongly and consistently associated with increased risk of developing poor mental health included students with experiences of trauma in childhood, those that identify as LGBTQ and students with autism. Factors that promote wellbeing include developing strong and supportive social networks. Students who are prepared and able to adjust to the changes that moving into higher education presents also experience better mental health. Some behaviours that are associated with poor mental health include lack of engagement both with learning and leisure activities and poor mental health literacy.

Improved knowledge of factors associated with poor mental health and also those that increase mental wellbeing can provide a foundation for designing strategies and specific interventions that can prevent poor mental health and ensuring targeted support is available for students at increased risk.

Peer Review reports

Poor mental health of students in further and higher education is an increasing concern for public health and policy [ 1 , 2 , 3 , 4 ]. A 2020 Insight Network survey of students from 10 universities suggests that “1 in 5 students has a current mental health diagnosis” and that “almost half have experienced a serious psychological issue for which they felt they needed professional help”—an increase from 1 in 3 in the same survey conducted in 2018 [ 5 ]. A review of 105 Further Education (FE) colleges in England found that over a three-year period, 85% of colleges reported an increase in mental health difficulties [ 1 ]. Depression and anxiety were both prevalent and widespread in students; all colleges reported students experiencing depression and 99% reported students experiencing severe anxiety [ 5 , 6 ]. A UK cohort study found that levels of psychological distress increase on entering university [ 7 ], and recent evidence suggests that the prevalence of mental health problems among university students, including self-harm and suicide, is rising, [ 3 , 4 ] with increases in demand for services to support student mental health and reports of some universities finding a doubling of the number of students accessing support [ 8 ]. These common mental health difficulties clearly present considerable threat to the mental health and wellbeing of students but their impact also has educational, social and economic consequences such as academic underperformance and increased risk of dropping out of university [ 9 , 10 ].

Policy changes may have had an influence on the student experience, and on the levels of mental health problems seen in the student population; the biggest change has arguably been the move to widen higher education participation and to enable a more diverse demographic to access University education. The trend for widening participation has been continually rising since the late 1960s [ 11 ] but gained impetus in the 2000s through the work of the Higher Education Funding Council for England (HEFCE). Macaskill (2013) [ 12 ] suggests that the increased access to higher education will have resulted in more students attending university from minority groups and less affluent backgrounds, meaning that more students may be vulnerable to mental health problems, and these students may also experience greater challenges in making the transition to higher education.

Another significant change has been the introduction of tuition fees in 1998, which required students to self fund up to £1,000 per academic year. Since then, tuition fees have increased significantly for many students. With the abolition of maintenance grants, around 96% of government support for students now comes in the form of student loans [ 13 ]. It is estimated that in 2017, UK students were graduating with average debts of £50,000, and this figure was even higher for the poorest students [ 13 ]. There is a clear association between a student’s mental health and financial well-being [ 14 ], with “increased financial concern being consistently associated with worse health” [ 15 ].

The extent to which the increase in poor mental health is also being seen amongst non-students of a similar age is not well understood and warrants further study. However, the increase in poor mental health specifically within students in higher education highlights a need to understand what the risk factors are and what might be done within these settings to ensure young people are learning and developing and transitioning into adulthood in environments that promote mental wellbeing.

Commencing higher education represents a key transition point in a young person’s life. It is a stage often accompanied by significant change combined with high expectations of high expectations from students of what university life will be like, and also high expectations from themselves and others around their own academic performance. Relevant factors include moving away from home, learning to live independently, developing new social networks, adjusting to new ways of learning, and now also dealing with the additional greater financial burdens that students now face.

The recent global COVID-19 pandemic has had considerable impact on mental health across society, and there is concern that younger people (ages 18–25) have been particularly affected. Data from Canada [ 16 ] indicate that among survey respondents, “almost two-thirds (64%) of those aged 15 to 24 reported a negative impact on their mental health, while just over one-third (35%) of those aged 65 and older reported a negative impact on their mental health since physical distancing began” (ibid, p.4). This suggests that older adults are more prepared for the kind of social isolation which has been brought about through the response to COVID-19, whereas young adults have found this more difficult to cope with. UK data from the National Union of Students reports that for over half of UK students, their mental health is worse than before the pandemic [ 17 ]. Before COVID-19, students were already reporting increasing levels of mental health problems [ 2 ], but the COVID-19 pandemic has added a layer of “chronic and unpredictable” stress, creating the perfect conditions for a mental health crisis [ 18 ]. An example of this is the referrals (both urgent and routine) of young people with eating disorders for treatment in the NHS which almost doubled in number from 2019 to 2020 [ 19 ]. The travel restrictions enforced during the pandemic have also impacted on student mental health, particularly for international students who may have been unable to commence studies or go home to see friends and family during holidays [ 20 ].

With the increasing awareness and concern in the higher education sector and national bodies regarding student mental health has come increasing focus on how to respond. Various guidelines and best practice have been developed, e.g. ‘Degrees of Disturbance’ [ 21 ], ‘Good Practice Guide on Responding to Student Mental Health Issues: Duty of Care Responsibilities for Student Services in Higher Education’ [ 22 ] and the recent ‘The University Mental Health Charter’ [ 2 ]. Universities UK produced a Good Practice Guide in 2015 called “Student mental wellbeing in higher education” [ 23 ]. An increasing number of initiatives have emerged that are either student-led or jointly developed with students, and which reflect the increasing emphasis students and student bodies place on mental health and well-being and the increased demand for mental health support: Examples include: Nightline— www.nightline.ac.uk , Students Against Depression— www.studentsagainstdepression.org , Student Minds— www.studentminds.org.uk/student-minds-and-mental-wealth.html and The Alliance for Student-Led Wellbeing— www.alliancestudentwellbeing.weebly.com/ .

Although requests for professional support have increased substantially [ 24 ] only a third of students with mental health problems seek support from counselling services in the UK [ 12 ]. Many students encounter barriers to seeking help such as stigma or lack of awareness of services [ 25 ], and without formal support or intervention, there is a risk of deterioration. FE colleges and universities have identified the need to move beyond traditional forms of support and provide alternative, more accessible interventions aimed at improving mental health and well-being. Higher education institutions have a unique opportunity to identify, prevent, and treat mental health problems because they provide support in multiple aspects of students’ lives including academic studies, recreational activities, pastoral and counselling services, and residential accommodation.

In order to develop services that better meet the needs of students and design environments that are supportive of developing mental wellbeing it is necessary to explore and better understand the factors that lead to poor mental health in students.

Research objectives

The overall aim of this review was to identify, appraise and synthesise existing research evidence that explores the aetiology of poor mental health and mental wellbeing amongst students in tertiary level education. We aimed to gain a better understanding of the mechanisms that lead to poor mental health amongst tertiary level students and, in so doing, make evidence-based recommendations for policy, practice and future research priorities. Specific objectives in line with the project brief were to:

To co-produce with stakeholders a conceptual framework for exploring the factors associated with poorer mental health in students in tertiary settings. The factors may be both predictive, identifying students at risk, or causal, explaining why they are at risk. They may also be protective, promoting mental wellbeing.

To conduct a review drawing on qualitative studies, observational studies and surveys to explore the aetiology of poor mental health in students in university and college settings and identify factors which promote mental wellbeing amongst students.

To identify evidence-based recommendations for policy, service provision and future research that focus on prevention and early identification of poor mental health

Methodology

Identification of relevant evidence.

The following inclusion criteria were used to guide the development of the search strategy and the selection of studies.

We included students from a variety of further education settings (16 yrs + or 18 yrs + , including mature students, international students, distance learning students, students at specific transition points).

Universities and colleges in the UK. We were also interested in the context prior to the beginning of tertiary education, including factors during transition from home and secondary education or existing employment to tertiary education.

Any factor shown to be associated with mental health of students in tertiary level education. This included clinical indicators such as diagnosis and treatment and/or referral for depression and anxiety. Self-reported measures of wellbeing, happiness, stress, anxiety and depression were included. We did not include measures of academic achievement or engagement with learning as indicators of mental wellbeing.

Study design

We included cross-sectional and longitudinal studies that looked at factors associated with mental health outcomes in Table 5 .

Data extraction and quality appraisal

We extracted and tabulated key data from the included papers. Data extraction was undertaken by one reviewer, with a 10% sample checked for accuracy and consistency The quality of the included studies were evaluated using the Newcastle-Ottawa Scale [ 26 ] and the findings of the quality appraisal used in weighting the strength of associations and also identifying gaps for future high quality research.

Involvement of stakeholders

We recruited students, ex-students and parents of students to a public involvement group which met on-line three times during the process of the review and following the completion of the review. During a workshop meeting we asked for members of the group to draw on their personal experiences to suggest factors which were not mentioned in the literature.

Methods of synthesis

We undertook a narrative synthesis [ 27 ] due to the heterogeneity in the exposures and outcomes that were measured across the studies. Data showing the direction of effects and the strength of the association (correlation coefficients) were recorded and tabulated to aid comparison between studies.

Search strategy

Searches were conducted in the following electronic databases: Medline, Applied Social Sciences Index and Abstracts (ASSIA), International Bibliography of Social Sciences (IBSS), Science,PsycINFO and Science and Social Sciences Ciatation Indexes. Additional searches of grey literature, and reference lists of included studies were also undertaken.

The search strategy combined a number of terms relating to students and mental health and risk factors. The search terms included both subject (MeSH) and free-text searches. The searches were limited to papers about humans in English, published from 2010 to June 2020. The flow of studies through the review process is summarised in Fig. 1 .

Flow diagram

The full search strategy for Medline is provided in Appendix 1 .

Thirty-one quantitative, observational studies (39 papers) met the inclusion criteria. The total number of students that participated in the quantitative studies was 17,476, with studies ranging in size from 57 to 3706. Eighteen studies recruited student participants from only one university; five studies (10 publications) [ 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 ] included seven or more universities. Six studies (7 publications) [ 35 , 36 , 37 , 38 , 39 , 40 , 41 ] only recruited first year students, while the majority of studies recruited students from a range of year groups. Five studies [ 39 , 42 , 43 , 44 , 45 ] recruited only, or mainly, psychology students which may impact on the generalisability of findings. A number of studies focused on students studying particular subjects including: nursing [ 46 ] medicine [ 47 ], business [ 48 ], sports science [ 49 ]. One study [ 50 ] recruited LGBTQ (lesbian, gay, bisexual, transgender, intersex, queer/questioning) students, and one [ 51 ] recruited students who had attended hospital having self-harmed. In 27 of the studies, there were more female than male participants. The mean age of the participants ranged from 19 to 28 years. Ethnicity was not reported in 19 of the studies. Where ethnicity was reported, the proportion that were ‘white British’ ranged from 71 – 90%. See Table 1 for a summary of the characteristics of the included studies and the participants.

Design and quality appraisal of the included studies

The majority of included studies ( n = 22) were cross-sectional surveys. Nine studies (10 publications) [ 35 , 36 , 39 , 41 , 43 , 50 , 51 , 52 , 53 , 62 ] were longitudinal in design, recording survey data at different time points to explore changes in the variables being measured. The duration of time that these studies covered ranged from 19 weeks to 12 years. Most of the studies ( n = 22) only recruited participants from a single university. The use of one university setting and the large number of studies that recruited only psychology students weakens the wider applicability of the included studies.

Quantitative variables

Included studies ( n = 31) measured a wide range of variables and explored their association with poor mental health and wellbeing. These included individual level factors: age, gender, sexual orientation, ethnicity and a range of psychological variables. They also included factors that related to mental health variables (family history, personal history and mental health literacy), pre-university factors (childhood trauma and parenting behaviour. University level factors including social isolation, adjustment and engagement with learning. Their association was measured against different measures of positive mental health and poor mental health.

Measurement of association and the strength of that association has some limitations in addressing our research question. It cannot prove causality, and nor can it capture fully the complexity of the inter-relationship and compounding aspect of the variables. For example, the stress of adjustment may be manageable, until it is combined with feeling isolated and out of place. Measurement itself may also be misleading, only capturing what is measureable, and may miss variables that are important but not known. We included both qualitative and PPI input to identify missed but important variables.

The wide range of variables and different outcomes, with few studies measuring the same variable and outcomes, prevented meta-analyses of findings which are therefore described narratively.

The variables described were categorised during the analyses into the following categories:

Vulnerabilities – factors that are associated with poor mental health

Individual level factors including; age, ethnicity, gender and a range of psychological variables were all measured against different mental health outcomes including depression, anxiety, paranoia, and suicidal behaviour, self-harm, coping and emotional intelligence.

Six studies [ 40 , 42 , 47 , 50 , 60 , 63 ] examined a student’s ages and association with mental health. There was inconsistency in the study findings, with studies finding that age (21 or older) was associated with fewer depressive symptoms, lower likelihood of suicide ideation and attempt, self-harm, and positively associated with better coping skills and mental wellbeing. This finding was not however consistent across studies and the association was weak. Theoretical models that seek to explain this mechanism have suggested that older age groups may cope better due to emotion-regulation strategies improving with age [ 67 ]. However, those over 30 experienced greater financial stress than those aged 17-19 in another study [ 63 ].

Sexual orientation

Four studies [ 33 , 40 , 64 , 68 ] examined the association between poor mental health and sexual orientation status. In all of the studies LGBTQ students were at significantly greater risk of mental health problems including depression [ 40 ], anxiety [ 40 ], suicidal behaviour [ 33 , 40 , 64 ], self harm [ 33 , 40 , 64 ], use of mental health services [ 33 ] and low levels of wellbeing [ 68 ]. The risk of mental health problems in these students compared with heterosexual students, ranged from OR 1.4 to 4.5. This elevated risk may reflect the greater levels of isolation and discrimination commonly experienced by minority groups.

Nine studies [ 33 , 38 , 39 , 40 , 42 , 47 , 50 , 60 , 63 ] examined whether gender was associated mental health variables. Two studies [ 33 , 47 ] found that being female was statistically significantly associated with use of mental health services, having a current mental health problem, suicide risk, self harm [ 33 ] and depression [ 47 ]. The results were not consistent, with another study [ 60 ] finding the association was not significant. Three studies [ 39 , 40 , 42 ] that considered mediating variables such as adaptability and coping found no difference or very weak associations.

Two studies [ 47 , 60 ] examined the extent to which ethnicity was associated with mental health One study [ 47 ] reported that the risks of depression were significantly greater for those who categorised themselves as non-white (OR 8.36 p = 0.004). Non-white ethnicity was also associated with poorer mental health in another cross-sectional study [ 63 ]. There was no significant difference in the McIntyre et al. (2018) study [ 60 ]. The small number of participants from ethnic minority groups represented across the studies means that this data is very limited.

Family factors

Six studies [ 33 , 40 , 42 , 50 , 60 ] explored the association of a concept that related to a student’s experiences in childhood and before going to university. Three studies [ 40 , 50 , 60 ] explored the impact of ACEs (Adverse Childhood Experiences) assessed using the same scale by Feletti (2009) [ 69 ] and another explored the impact of abuse in childhood [ 46 ]. Two studies examined the impact of attachment anxiety and avoidance [ 42 ], and parental acceptance [ 46 , 59 ]. The studies measured different mental health outcomes including; positive and negative affect, coping, suicide risk, suicide attempt, current mental health problem, use of mental health services, psychological adjustment, depression and anxiety.

The three studies that explored the impact of ACE’s all found a significant and positive relationship with poor mental health amongst university students. O’Neill et al. (2018) [ 50 ] in a longitudinal study ( n = 739) showed that there was in increased likelihood in self-harm and suicidal behaviours in those with either moderate or high levels of childhood adversities (OR:5.5 to 8.6) [ 50 ]. McIntyre et al. (2018) [ 60 ] ( n = 1135) also explored other dimensions of adversity including childhood trauma through multiple regression analysis with other predictive variables. They found that childhood trauma was significantly positively correlated with anxiety, depression and paranoia (ß = 0.18, 0.09, 0.18) though the association was not as strong as the correlation seen for loneliness (ß = 0.40) [ 60 ]. McLafferty et al. (2019) [ 40 ] explored the compounding impact of childhood adversity and negative parenting practices (over-control, overprotection and overindulgence) on poor mental health (depression OR 1.8, anxiety OR 2.1 suicidal behaviour OR 2.3, self-harm OR 2.0).

Gaan et al.’s (2019) survey of LGBTQ students ( n = 1567) found in a multivariate analyses that sexual abuse, other abuse from violence from someone close, and being female had the highest odds ratios for poor mental health and were significantly associated with all poor mental health outcomes [ 33 ].

While childhood trauma and past abuse poses a risk to mental health for all young people it may place additional stresses for students at university. Entry to university represents life stage where there is potential exposure to new and additional stressors, and the possibility that these students may become more isolated and find it more difficult to develop a sense of belonging. Students may be separated for the first time from protective friendships. However, the mechanisms that link childhood adversities and negative psychopathology, self-harm and suicidal behaviour are not clear [ 40 ]. McLafferty et al. (2019) also measured the ability to cope and these are not always impacted by childhood adversities [ 40 ]. They suggest that some children learn to cope and build resilience that may be beneficial.

McLafferty et al. (2019) [ 40 ] also studied parenting practices. Parental over-control and over-indulgence was also related to significantly poorer coping (OR -0.075 p < 0.05) and this was related to developing poorer coping scores (OR -0.21 p < 0.001) [ 40 ]. These parenting factors only became risk factors when stress levels were high for students at university. It should be noted that these studies used self-report, and responses regarding views of parenting may be subjective and open to interpretation. Lloyd et al.’s (2014) survey found significant positive correlations between perceived parental acceptance and students’ psychological adjustment, with paternal acceptance being the stronger predictor of adjustment.

Autistic students may display social communication and interaction deficits that can have negative emotional impacts. This may be particularly true during young adulthood, a period of increased social demands and expectations. Two studies [ 56 ] found that those with autism had a low but statistically significant association with poor social problem-solving skills and depression.

Mental health history

Three studies [ 47 , 51 , 68 ] investigated mental health variables and their impact on mental health of students in higher education. These included; a family history of mental illness and a personal history of mental illness.

Students with a family history or a personal history of mental illness appear to have a significantly greater risk of developing problems with mental health at university [ 47 ]. Mahadevan et al. (2010) [ 51 ] found that university students who self-harm have a significantly greater risk (OR 5.33) of having an eating disorder than a comparison group of young adults who self-harm but are not students.

Buffers – factors that are protective of mental wellbeing

Psychological factors.

Twelve studies [ 29 , 39 , 40 , 41 , 42 , 43 , 46 , 49 , 54 , 58 , 64 ] assessed the association of a range of psychological variables and different aspects of mental wellbeing and poor mental health. We categorised these into the following two categories: firstly, psychological variables measuring an individual’s response to change and stressors including adaptability, resilience, grit and emotional regulation [ 39 , 40 , 41 , 42 , 43 , 46 , 49 , 54 , 58 ] and secondly, those that measure self-esteem and body image [ 29 , 64 ].

The evidence from the eight included quantitative studies suggests that students with psychological strengths including; optimism, self-efficacy [ 70 ], resilience, grit [ 58 ], use of positive reappraisal [ 49 ], helpful coping strategies [ 42 ] and emotional intelligence [ 41 , 46 ] are more likely to experience greater mental wellbeing (see Table 2 for a description of the psychological variables measured). The positive association between these psychological strengths and mental well-being had a positive affect with associations ranging from r = 0.2–0.5 and OR1.27 [ 41 , 43 , 46 , 49 , 54 ] (low to moderate strength of association). The negative associations with depressive symptoms are also statistically significant but with a weaker association ( r = -0.2—0.3) [ 43 , 49 , 54 ].

Denovan (2017a) [ 43 ] in a longitudinal study found that the association between psychological strengths and positive mental wellbeing was not static and that not all the strengths remained statistically significant over time. The only factors that remained significant during the transition period were self-efficacy and optimism, remaining statistically significant as they started university and 6 months later.

Parental factors

Only one study [ 59 ] explored family factors associated with the development of psychological strengths that would equip young people as they managed the challenges and stressors encountered during the transition to higher education. Lloyd et al. (2014) [ 59 ] found that perceived maternal and paternal acceptance made significant and unique contributions to students’ psychological adjustment. Their research methods are limited by their reliance on retrospective measures and self-report measures of variables, and these results could be influenced by recall bias.

Two studies [ 29 , 64 ] considered the impact of how individuals view themselves on poor mental health. One study considered the impact of self-esteem and the association with non-accidental self-injury (NSSI) and suicide attempt amongst 734 university students. As rates of suicide and NSSI are higher amongst LGBT (lesbian, gay, bisexual, transgender) students, the prevalence of low self-esteem was compared. There was a low but statistically significant association between low self-esteem and NSSI, though not for suicide attempt. A large survey, including participants from seven universities [ 42 ] compared depressive symptoms in students with marked body image concerns, reporting that the risk of depressive symptoms was greater (OR 2.93) than for those with lower levels of body image concerns.

Mental health literacy and help seeking behaviour

Two studies [ 48 , 68 ] investigated attitudes to mental illness, mental health literacy and help seeking for mental health problems.

University students who lack sufficient mental health literacy skills to be able to recognise problems or where there are attitudes that foster shame at admitting to having mental health problems can result in students not recognising problems and/or failing to seek professional help [ 48 , 68 ]. Gorcyznski et al. (2017) [ 68 ] found that women and those who had a history of previous mental health problems exhibited significantly higher levels of mental health literacy. Greater mental health literacy was associated with an increased likelihood that individuals would seek help for mental health problems. They found that many students find it hard to identify symptoms of mental health problems and that 42% of students are unaware of where to access available resources. Of those who expressed an intention to seek help for mental health problems, most expressed a preference for online resources, and seeking help from family and friends, rather than medical professionals such as GPs.

Kotera et al. (2019) [ 48 ] identified self-compassion as an explanatory variable, reducing social comparison, promoting self-acceptance and recognition that discomfort is an inevitable human experience. The study found a strong, significant correlation between self-compassion and mental health symptoms ( r = -0.6. p < 0.01).

There again appears to be a cycle of reinforcement, where poor mental health symptoms are felt to be a source of shame and become hidden, help is not sought, and further isolation ensues, leading to further deterioration in mental health. Factors that can interrupt the cycle are self-compassion, leading to more readiness to seek help (see Fig. 2 ).

Poor mental health – cycles of reinforcement

Social networks

Nine studies [ 33 , 38 , 41 , 46 , 51 , 54 , 60 , 64 , 65 ] examined the concepts of loneliness and social support and its association with mental health in university students. One study also included students at other Higher Education Institutions [ 46 ]. Eight of the studies were surveys, and one was a retrospective case control study to examine the differences between university students and age-matched young people (non-university students) who attended hospital following deliberate self-harm [ 51 ].

Included studies demonstrated considerable variation in how they measured the concepts of social isolation, loneliness, social support and a sense of belonging. There were also differences in the types of outcomes measured to assess mental wellbeing and poor mental health. Grouping the studies within a broad category of ‘social factors’ therefore represents a limitation of this review given that different aspects of the phenomena may have been being measured. The tools used to measure these variables also differed. Only one scale (The UCLA loneliness scale) was used across multiple studies [ 41 , 60 , 65 ]. Diverse mental health outcomes were measured across the studies including positive affect, flourishing, self-harm, suicide risk, depression, anxiety and paranoia.

Three studies [ 41 , 60 , 62 ] measuring loneliness, two longitudinally [ 41 , 62 ], found a consistently positive association between loneliness and poor mental health in university students. Greater loneliness was linked to greater anxiety, stress, depression, poor general mental health, paranoia, alcohol abuse and eating disorder problems. The strength of the correlations ranged from 0–3-0.4 and were all statistically significant (see Tables 3 and 4 ). Loneliness was the strongest overall predictor of mental distress, of those measured. A strong identification with university friendship groups was most protective against distress relative to other social identities [ 60 ]. Whether poor mental health is the cause, or the result of loneliness was explored further in the studies. The results suggest that for general mental health, stress, depression and anxiety, loneliness induces or exacerbates symptoms of poor mental health over time [ 60 , 62 ]. The feedback cycle is evident, with loneliness leading to poor mental health which leads to withdrawal from social contacts and further exacerbation of loneliness.

Factors associated with protecting against loneliness by fostering supportive friendships and promoting mental wellbeing were also identified. Beliefs about the value of ‘leisure coping’, and attributes of resilience and emotional intelligence had a moderate, positive and significant association with developing mental wellbeing and were explored in three studies [ 46 , 54 , 66 ].

The transition to and first year at university represent critical times when friendships are developed. Thomas et al. (2020) [ 65 ] explored the factors that predict loneliness in the first year of university. A sense of community and higher levels of ‘social capital’ were significantly associated with lower levels of loneliness. ‘Social capital’ scales measure the development of emotionally supportive friendships and the ability to adjust to the disruption of old friendships as students transition to university. Students able to form close relationships within their first year at university are less likely to experience loneliness (r-0.09, r- 0.36, r- 0.34). One study [ 38 ] investigating the relationship between student experience and being the first in the family to attend university found that these students had lower ratings for peer group interactions.

Young adults at university and in higher education are facing multiple adjustments. Their ability to cope with these is influenced by many factors. Supportive friendships and a sense of belonging are factors that strengthen coping. Nightingale et al. (2012) undertook a longitudinal study to explore what factors were associated with university adjustment in a sample of first year students ( n = 331) [ 41 ]. They found that higher skills of emotion management and emotional self-efficacy were predictive of stable adjustment. These students also reported the lowest levels of loneliness and depression. This group had the skills to recognise their emotions and cope with stressors and were confident to access support. Students with poor emotion management and low levels of emotional self-efficacy may benefit from intervention to support the development of adaptive coping strategies and seeking support.

The positive and negative feedback loops

The relationship between the variables described appeared to work in positive and negative feedback loops with high levels of social capital easing the formation of a social network which acts as a critical buffer to stressors (see Fig. 3 ). Social networks and support give further strengthening and reinforcement, stimulating positive affect, engagement and flourishing. These, in turn, widen and deepen social networks for support and enhance a sense of wellbeing. Conversely young people who enter the transition to university/higher education with less social capital are less likely to identify with and locate a social network; isolation may follow, along with loneliness, anxiety, further withdrawal from contact with social networks and learning, and depression.

Triggers – factors that may act in combination with other factors to lead to poor mental health

Stress is seen as playing a key role in the development of poor mental health for students in higher education. Theoretical models and empirical studies have suggested that increases in stress are associated with decreases in student mental health [ 12 , 43 ]. Students at university experience the well-recognised stressors associated with academic study such as exams and course work. However, perhaps less well recognised are the processes of transition, requiring adapting to a new social and academic environment (Fisher 1994 cited by Denovan 2017a) [ 43 ]. Por et al. (2011) [ 46 ] in a small ( n = 130 prospective survey found a statistically significant correlation between higher levels of emotional intelligence and lower levels of perceived stress ( r = 0.40). Higher perceived stress was also associated with negative affect in two studies [ 43 , 46 ], and strongly negatively associated with positive affect (correlation -0.62) [ 54 ].

University variables

Eleven studies [ 35 , 39 , 47 , 51 , 52 , 54 , 60 , 63 , 65 , 83 , 84 ] explored university variables, and their association with mental health outcomes. The range of factors and their impact on mental health variables is limited, and there is little overlap. Knowledge gaps are shown by factors highlighted by our PPI group as potentially important but not identified in the literature (see Table 5 ). It should be noted that these may reflect the focus of our review, and our exclusion of intervention studies which may evaluate university factors.

High levels of perceived stress caused by exam and course work pressure was positively associated with poor mental health and lack of wellbeing [ 51 , 52 , 54 ]. Other potential stressors including financial anxieties and accommodation factors appeared to be less consistently associated with mental health outcomes [ 35 , 38 , 47 , 51 , 60 , 62 ]. Important mediators and buffers to these stressors are coping strategies and supportive networks (see conceptual model Appendix 2 ). One impact of financial pressures was that students who worked longer hours had less interaction with their peers, limiting the opportunities for these students to benefit from the protective effects of social support.

Red flags – behaviours associated with poor mental health and/or wellbeing

Engagement with learning and leisure activities.

Engagement with learning activities was strongly and positively associated with characteristics of adaptability [ 39 ] and also happiness and wellbeing [ 52 ] (see Fig. 4 ). Boulton et al. (2019) [ 52 ] undertook a longitudinal survey of undergraduate students at a campus-based university. They found that engagement and wellbeing varied during the term but were strongly correlated.

Engagement and wellbeing

Engagement occurred in a wide range of activities and behaviours. The authors suggest that the strong correlation between all forms of engagement with learning has possible instrumental value for the design of systems to monitor student engagement. Monitoring engagement might be used to identify changes in the behaviour of individuals to assist tutors in providing support and pastoral care. Students also were found to benefit from good induction activities provided by the university. Greater induction satisfaction was positively and strongly associated with a sense of community at university and with lower levels of loneliness [ 65 ].

The inte r- related nature of these variables is depicted in Fig. 4 . Greater adaptability is strongly associated with more positive engagement in learning and university life. More engagement is associated with higher mental wellbeing.

Denovan et al. (2017b) [ 54 ] explored leisure coping, its psychosocial functions and its relationship with mental wellbeing. An individual’s beliefs about the benefits of leisure activities to manage stress, facilitate the development of companionship and enhance mood were positively associated with flourishing and were negatively associated with perceived stress. Resilience was also measured. Resilience was strongly and positively associated with leisure coping beliefs and with indicators of mental wellbeing. The authors conclude that resilient individuals are more likely to use constructive means of coping (such as leisure coping) to proactively cultivate positive emotions which counteract the experience of stress and promote wellbeing. Leisure coping is predictive of positive affect which provides a strategy to reduce stress and sustain coping. The belief that friendships acquired through leisure provide social support is an example of leisure coping belief. Strong emotionally attached friendships that develop through participation in shared leisure pursuits are predictive of higher levels of well-being. Friendship bonds formed with fellow students at university are particularly important for maintaining mental health, and opportunities need to be developed and supported to ensure that meaningful social connections are made.

The ‘broaden-and-build theory’ (Fredickson 2004 [ 85 ] cited by [ 54 ]) may offer an explanation for the association seen between resilience, leisure coping and psychological wellbeing. The theory is based upon the role that positive and negative emotions have in shaping human adaptation. Positive emotions broaden thinking, enabling the individual to consider a range of ways of dealing with and adapting to their environment. Conversely, negative emotions narrow thinking and limit options for adapting. The former facilitates flourishing, facilitating future wellbeing. Resilient individuals are more likely to use constructive means of coping which generate positive emotion (Tugade & Fredrickson 2004 [ 86 ], cited by [ 54 ]). Positive emotions therefore lead to growth in coping resources, leading to greater well-being.

Health behaviours at university

Seven studies [ 29 , 31 , 38 , 45 , 51 , 54 , 66 ] examined how lifestyle behaviours might be linked with mental health outcomes. The studies looked at leisure activities [ 63 , 80 ], diet [ 29 ], alcohol use [ 29 , 31 , 38 , 51 ] and sleep [ 45 ].

Depressive symptoms were independently associated with problem drinking and possible alcohol dependence for both genders but were not associated with frequency of drinking and heavy episodic drinking. Students with higher levels of depressive symptoms reported significantly more problem drinking and possible alcohol dependence [ 31 ]. Mahadevan et al. (2010) [ 51 ] compared students and non-students seen in hospital for self-harm and found no difference in harmful use of alcohol and illicit drugs.

Poor sleep quality and increased consumption of unhealthy foods were also positively associated with depressive symptoms and perceived stress [ 29 ]. The correlation with dietary behaviours and poor mental health outcomes was low, but also confirmed by the negative correlation between less perceived stress and depressive symptoms and consumption of a healthier diet.

Physical activity and participation in leisure pursuits were both strongly correlated with mental wellbeing ( r = 0.4) [ 54 ], and negatively correlated with depressive symptoms and anxiety ( r = -0.6, -0.7) [ 66 ].

Thirty studies measuring the association between a wide range of factors and poor mental health and mental wellbeing in university and college students were identified and included in this review. Our purpose was to identify the factors that contribute to the growing prevalence of poor mental health amongst students in tertiary level education within the UK. We also aimed to identify factors that promote mental wellbeing and protect against deteriorating poor mental health.

Loneliness and social isolation were strongly associated with poor mental health and a sense of belonging and a strong support network were strongly associated with mental wellbeing and happiness. These associations were strongly positive in the eight studies that explored them and are consistent with other meta-analyses exploring the link between social support and mental health [ 87 ].

Another factor that appeared to be protective was older age when starting university. A wide range of personal traits and characteristics were also explored. Those associated with resilience, ability to adjust and better coping led to improved mental wellbeing. Better engagement appeared as an important mediator to potentially explain the relationship between these two variables. Engagement led to students being able to then tap into those features that are protective and promoting of mental wellbeing.

Other important risk factors for poor mental wellbeing that emerged were those students with existing or previous mental illness. Students on the autism spectrum and those with poor social problem-solving also were more likely to suffer from poor mental health. Negative self-image was also associated with poor mental health at university. Eating disorders were strongly associated with poor mental wellbeing and were found to be far more of a risk in students at university than in a comparative group of young people not in higher education. Other studies of university students also found that pre-existing poor mental health was a strong predictor of poor mental health in university students [ 88 ].

At a family level, the experience of childhood trauma and adverse experiences including, for example, neglect, household dysfunction or abuse, were strongly associated with poor mental health in young people at university. Students with a greater number of ‘adverse childhood experiences’ were at significantly greater risk of poor mental health than those students without experience of childhood trauma. This was also identified in a review of factors associated with depression and suicide related outcomes amongst university undergraduate students [ 88 ].

Our findings, in contrast to findings from other studies of university students, did not find that female gender associated with poor mental health and wellbeing, and it also found that being a mature student was protective of mental wellbeing.

Exam and course work pressure was associated with perceived stress and poor mental health. A lack of engagement with learning activities was also associated with poor mental health. A number of variables were not consistently shown to be associated with poor mental health including financial concerns and accommodation factors. Very little evidence related to university organisation or support structures was assessed in the evidence. One study found that a good induction programme had benefits for student mental wellbeing and may be a factor that enables students to become a part of a social network positive reinforcement cycle. Involvement in leisure activities was also found to be associated with improved coping strategies and better mental wellbeing. Students with poorer mental health tended to also eat in a less healthy manner, consume more harmful levels of alcohol, and experience poorer sleep.

This evidence review of the factors that influence mental health and wellbeing indicate areas where universities and higher education settings could develop and evaluate innovations in practice. These include:

Interventions before university to improve preparation of young people and their families for the transition to university.

Exploratory work to identify the acceptability and feasibility of identifying students at risk or who many be exhibiting indications of deteriorating mental health

Interventions that set out to foster a sense of belonging and identify

Creating environments that are helpful for building social networks

Improving mental health literacy and access to high quality support services

This review has a number of limitations. Most of the included studies were cross-sectional in design, with a small number being longitudinal ( n = 7), following students over a period of time to observe changes in the outcomes being measured. Two limitations of these sources of data is that they help to understand associations but do not reveal causality; secondly, we can only report the findings for those variables that were measured, and we therefore have to support causation in assuming these are the only factors that are related to mental health.

Furthermore, our approach has segregated and categorised variables in order to better understand the extent to which they impact mental health. This approach does not sufficiently explore or reveal the extent to which variables may compound one another, for example, feeling the stress of new ways of learning may not be a factor that influences mental health until it is combined with a sense of loneliness, anxiety about financial debt and a lack of parental support. We have used our PPI group and the development of vignettes of their experiences to seek to illustrate the compounding nature of the variables identified.

We limited our inclusion criteria to studies undertaken in the UK and published within the last decade (2009–2020), again meaning we may have limited our inclusion of relevant data. We also undertook single data extraction of data which may increase the risk of error in our data.

Understanding factors that influence students’ mental health and wellbeing offers the potential to find ways to identify strategies that enhance the students’ abilities to cope with the challenges of higher education. This review revealed a wide range of variables and the mechanisms that may explain how they impact upon mental wellbeing and increase the risk of poor mental health amongst students. It also identified a need for interventions that are implemented before young people make the transition to higher education. We both identified young people who are particularly vulnerable and the factors that arise that exacerbate poor mental health. We highlight that a sense of belonging and supportive networks are important buffers and that there are indicators including lack of engagement that may enable early intervention to provide targeted and appropriate support.

Availability of data and materials

Further details of the study and the findings can be provided on request to the lead author ([email protected]).

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Acknowledgements

We acknowledge the input from our public advisory group which included current and former students, and family members of students who have struggled with their mental health. The group gave us their extremely valuable insights to assist our understanding of the evidence.

This project was supported by funding from the National Institute for Health Research as part of the NIHR Public Health Research Programme (fuding reference 127659 Public Health Review Team). The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care.

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All of the included authors designed the project methods and prepared a protocol. A.C. designed the search strategy. F.C, L.B and C.B screened the identified citations and undertook data extraction. S.B. led the PPI involvement. JD participated as a member of the PPI group. F.C and L.B undertook the analysis. F.C. and L.B wrote the main manuscript text. All authors reviewed the manuscript. F.C designed Figs. 2 , 3 and 4 . The author(s) read and approved the final manuscript.

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Campbell, F., Blank, L., Cantrell, A. et al. Factors that influence mental health of university and college students in the UK: a systematic review. BMC Public Health 22 , 1778 (2022). https://doi.org/10.1186/s12889-022-13943-x

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The mental health of university students during the COVID-19 pandemic: An online survey in the UK

Roles Conceptualization, Data curation, Formal analysis, Methodology, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliation Department of Computer Science, School of Computing and Engineering, University of Huddersfield, Huddersfield, West Yorkshire, United Kingdom

Roles Methodology, Writing – review & editing

Affiliation Centre for Applied Research in Health, School of Human and Health Sciences, University of Huddersfield, Huddersfield, West Yorkshire, United Kingdom

Tianhua Chen,
Mike Lucock

Published: January 12, 2022
https://doi.org/10.1371/journal.pone.0262562
Reader Comments

Higher education students’ mental health has been a growing concern in recent years even before the COVID-19 pandemic. The stresses and restrictions associated with the pandemic have put university students at greater risk of developing mental health issues, which may significantly impair their academic success, social interactions and their future career and personal opportunities. This paper aimed to understand the mental health status of University students at an early stage in the pandemic and to investigate factors associated with higher levels of distress. An online survey including demographics, lifestyle/living situations, brief mental well-being history, questions relating to COVID-19 and standardised measures of depression, anxiety, resilience and quality of life was completed by 1173 students at one University in the North of England. We found high levels of anxiety and depression, with more than 50% experiencing levels above the clinical cut offs, and females scoring significantly higher than males. The survey also suggested relatively low levels of resilience which we attribute to restrictions and isolation which reduced the opportunities to engage in helpful coping strategies and activities rather than enduring personality characteristics. Higher levels of distress were associated with lower levels of exercising, higher levels of tobacco use, and a number of life events associated with the pandemic and lockdown, such as cancelled events, worsening in personal relationships and financial concerns. We discuss the importance of longer-term monitoring and mental health support for university students.

Citation: Chen T, Lucock M (2022) The mental health of university students during the COVID-19 pandemic: An online survey in the UK. PLoS ONE 17(1): e0262562. https://doi.org/10.1371/journal.pone.0262562

Editor: Prabhat Mittal, Satyawati College (Eve.), University of Delhi, INDIA

Received: October 15, 2021; Accepted: December 30, 2021; Published: January 12, 2022

Copyright: © 2022 Chen, Lucock. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: Data cannot be shared publicly because of confidential nature of university student information. Data are available from the University of Huddersfield, School of Computing and Engineering Institutional Data Access / Ethics Committee (contact via [email protected] ) for researchers who meet the criteria for access to confidential data.

Funding: The authors received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

Introduction

The mental well-being of higher education students was a growing concern even before the COVID-19 pandemic, with increasing numbers of students experiencing mental health problems as reported by UK Parliament Briefing Paper [ 1 ]. Community surveys suggest that common mental health problems, anxiety and depression, generally affect one in six people in a given week in England [ 2 ], and concerns were expressed early in the pandemic about the mental health impact of the pandemic on the general population [ 3 ], at least in the short term. For higher education students, the pandemic presented a number of specific challenges, such as the transfer of more learning and support services online, which many students found difficult to engage effectively [ 4 ], leading to increased anxiety and concerns about their academic performances and long-term employment [ 5 , 6 ]. Other impacts include the closure of student halls, cancellation of exchange studies and graduation ceremonies, loss of part-time jobs, and increased uncertainties regarding career options. The lockdown and social distancing measures also led to limited opportunities for socialising and establishing relationships, with greater reliance on social media, and possible chronic loneliness brought by social isolation [ 7 ].

A number of studies have explored the impact of the pandemic on the mental health of university students and factors associated with higher levels of distress. For example, a US interview survey of 195 undergraduate students from one university [ 8 ] reported negative impacts of the COVID-19 pandemic and the urgent need to develop interventions and preventive strategies. Another US survey of 162 undergraduates [ 9 ] found high levels of mental health distress, with depression being associated with difficulties focusing on academic work and loss of employment and higher levels of anxiety more likely in students who spent more than an hour per day looking for information on COVID-19. An online survey of 255 students at a university in Hong Kong in July 2020 also found high levels of depression with perceived available peer support being negatively associated with depressive symptoms [ 10 ]. Another cross-sectional web-based study of 324 college students in India between November and December 2020 [ 11 ] suggested that 68.8% had high fear of COVID-19, 28.7% had moderate to severe depression, and 51.5% had mild to severe anxiety, with having a family member who was infected with COVID-19 being significantly associated with anxiety and depression. Studies have also provided evidence of a worsening of common mental health problems and wellbeing during the pandemic. For example, a survey of undergraduate students by the Higher Education Policy Institute in the UK found that 58% reported a worsening in their mental health because of the pandemic, 14% said it was better and the remaining 28% said it was the same [ 12 ]. Also in the UK, a survey of students in higher and further education conducted by the National Union of Students, found that 52% described their current mental health and well-being as worse, 35% described it as the same and 8% as better, compared with their life before the pandemic [ 13 ]. The Student Covid Insight Survey (SCIS), conducted in November 2020, found 57% of students reported that their well-being and mental health had become slightly or much worse since the start of the autumn term [ 14 ], with lower levels of life satisfaction and happiness, and higher levels of anxiety, compared with the general population.

Longitudinal studies comparing mental health before and during the pandemic are rare but a study of 254 undergraduates at one UK university [ 15 ], found a significant increase in depression and reduction in wellbeing during the first lockdown (April/May 2020) compared with before the pandemic (autumn 2019) and that over a third of the sample could be classed as clinically depressed at lockdown, an increase from 15% before the pandemic. The increase in depression was highly correlated with a worse sleep quality. A longitudinal survey of 66 students in a Chinese college also concluded that sleep quality was a key factor in the emotional impact on students, and that daily physical activity and good sleep may mitigate mental health problems [ 16 ]. Interestingly, they also found reductions in people’s aggressiveness, which they suggested was due to people realizing the fragility and preciousness of life.

These studies have contributed to our understanding of the impact of the pandemic and lock-down on students’ mental health, but they have tended to involve relatively small sample sizes of undergraduates and have not looked at positive factors associated with better mental health, such as resilience. This paper describes a relatively large survey of undergraduate and postgraduate students which investigates different aspects of mental health and coping, including anxiety, depression, the resilience to cope with difficulties, quality of life and general health, and a range of questions on demographics, lifestyle/ living situation and COVID-19 related factors. Conducted at a university in the UK, this study aimed to identify: 1) The impact of the COVID-19 pandemic on University students; 2) Levels of mental health and quality of life in University students during the COVID-19 pandemic; 3) Predictors of mental health and quality of life.

Materials and methods

Design and setting.

This was a cross-sectional on-line survey at a large university in the North of England, UK. Almost 20,000 students attend the University each year. The study was approved by a University ethics committee. The data collection was conducted in the period between 26.06.2020 and 30.07.2020. To put this in context with the lockdown in England, it entered the first national lockdown on 23.03.20 and lockdown measures were eased on 01.06.20.

Participants

Students, including both undergraduates and postgraduates across all seven schools at the university were eligible and sent an invitation by local school administrators through their mailing-list.

A link to the survey that was deployed in Google Forms was delivered to students via e-mail. The anonymous survey questionnaire took up to 10 minutes to complete, once participants agree to take part. Students completing the survey were entered into a prize draw for £650 worth of gift vouchers, distributed in varying amounts to 36 prize winners.

The following set of demographic information and measures are used to identify the students’ mental health, wellbeing and resilience.

Demographics.

The first part of survey included demographic information including age, gender, ethnicity, current educational level, and relationship status.

Patient health questionnaire (PHQ-9) [ 17 ].

The PHQ-9 is a self-administered screening questionnaire, validated for use in primary care and community settings, to measure the severity of depression. Nine questions cover different aspects of depression on a four-point scale—“0” (not at all), “1” (several days), “2” (more than half the days), “3” (nearly every day). Scores can be categorised as 0-4 none, 5-9 mild, 10-14 moderate, 15-19 moderately severe, 20-27 severe. The total score was used as the dependent variable with the aim to conduct statistical significance test for alternative independent variables.

Generalised anxiety disorder questionnaire (GAD-7) [ 18 ].

The GAD-7 is also a self-administered screening questionnaire, which measures the severity of generalised anxiety disorder (GAD). Seven questions are rated on the same four-point scale as the PHQ-9. Scores of 5, 10, and 15 are taken as the cut-off points for mild, moderate and severe anxiety, respectively. In this study the total score was be used as the dependent variable to conduct statistical significance test.

Lifestyle / Living situation under COVID-19.

This set of questions explored the lifestyle, living situation, behaviours and experiences of individuals. These included experiences of adversities (e.g., worsen personal relations/financial situation/live conditions, loss of employment/families etc.), and the frequency of conducting exercise/ communicating with friends/relatives and the 122 consumption of alcohol/tobaccos during the lockdown period. The values of these variables were dichotomised to 0 (Never, Rarely, Sometimes) and 1 (Often, Always) for 124 analysis [ 9 ].

Brief resilience scale (BRS) [ 19 ].

The BRS aims to measure the ability to bounce back or recover from stress. It has a 5-point Likert response scale, for six items, ranging from 1 = strongly disagree to 5 = strongly agree, with three items positively phrased and three negatively phrased. The BRS is scored by reverse coding items 2, 4, and 6, and then calculating the mean of the six items. An averaged score of 1.00 to 2.99 suggests low resilience, 3.00 to 4.30 normal resilience and 4.31 to 5.00 high resilience. Similar to PHQ-9 and GAD-7, the overall averaged score was used as the dependent variable to conduct statistical significance test.

Brief mental wellbeing history.

Three questions asked about the students’ history of treatment and support for a mental health issue, including therapy and medication.

The EQ-5D-5L instrument [ 20 ] is a self-assessed, health related, quality of life questionnaire. The descriptive system comprises five dimensions: mobility, self-care, usual activities, pain/discomfort and anxiety/depression. Each dimension has 5 levels: no problems, slight problems, moderate problems, severe problems and extreme problems. Responses are coded as single-digit numbers expressing the severity level selected in each dimension. The overall score will be used as a dependent variable, with the best health state (11111) being a score of 5 and the worst health state (55555) being a score of 25. Additionally, the EQ-VAS was also used for students to provide a broad self assessment of their health, on a visual analogue scale ranging between 100 (best imaginable health) and 0 (worst imaginable health).

COVID-19 related questions.

A set of five questions were asked in relation to COVID-19 pandemic. These included: how often the person practised the recommended social distancing on a 5-point scale (‘1’ is never and ‘5’ is always); the severity of the risk group the subject assumes they belong to; whether the subject is cohabiting with anyone falling with the risk groups; how likely the subject feels at the risk of contracting COVID-19 (on a 5-point scale where ‘1’ is definitely not and ‘5’ is certain); the extent to which the subject had felt needing extra support during lockdown (where ‘0’ was no need for extra support and ‘100’ indicated immediate support required).

Data analysis

All analysis below used the SciPy (Scientific Python) [ 21 ], which is a free and open-source Python library extensively used for scientific and technical computations for data science. Descriptive analyses examined the distribution of all variables/questions of interest, with the summarised information presented in Tables 1 – 5 . A bivariate analysis was then conducted to examine the associations between each of the independent variables against each of the six decision variables that had been previously introduced, including PHQ9 depression, GAD 7 Anxiety, BRS6 Resilience, EQ-5D-5L life quality, self-rated health score and support needs. Specifically, paired two tail t-tests were used to examine the significance of the associations. The findings are presented in Tables 6 – 9 , where the significance levels are represented as ns ( p > 0.05), *( p ≤ 0.05);**( p ≤ 0.01);***( p ≤ 0.001) on the basis of the associated p values. Furthermore, a multivariate linear regression was utilised to evaluate the predictive capabilities of the independent variables that have achieved statistical significance (i.e., p < 0.05) with respect to the corresponding decision variable.

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A total of 1173 valid responses were collected without any missing values (each of the 48 asked questions was required to fill in before the survey could be submitted).

Descriptive analysis

Table 1 presents the descriptive analysis for demographic related variables. The mean of age was 25.65 (standard deviation = 8.89), with a median value of 22 and 70% of participates were females. Approximately one third of the students were living in the University town, with 23% living in nearby cities and 43% living in various other places. Nearly one third of the students were from non-white ethnic backgrounds and there were slightly more (53%) post graduates than undergraduates. 45% were single and 54% in a relationship.

Table 2 summarises the descriptive statistics regarding the life style/living situation, including the experience of an adverse life event during the pandemic. Regarding adversity, 979 out of the 1173 (86.6%) participants reported at least one adverse effect of the pandemic, with an average of 2.3 adverse effects per student. The three most prevalent adverse effects were the cancellation of an important event (56.1%), worse personal relations (40.2%) and worse financial situation (39.6%). Over 13% of students also reported the death of a partner, close relative or friend. Approximately 30% of students were exercising frequently despite lockdown, 18% reported often or always using alcohol and 12% often or always using tobacco. 72% reported that their relationships with friends or families had been impacted and 60% had often or always been communicating with friends and family remotely.

Table 3 shows high levels of use of mental health and talking therapies, with approximately 40% of students having been referred to or participated in talking therapies for a mental health issue in the past (not just at the current time), 27.7% reported currently or previously taking medications for a mental health issue and about a third had accessed or attempted to access healthcare services personally or for a family member during the pandemic period. Table 4 shows that over 90% of the students reported practicing the recommended social distancing often/always, 15% believed they were in high or increased risk groups for pre-existing health conditions or needing special medical care, with 30% living with another person in the high risk groups, while 16.5% of students felt they were likely or extremely likely to contract COVID-19 virus.

Table 5 shows the descriptive analysis on decision variables. The mean value of PHQ9 (depression) was in the moderate range and the mean GAD7 score (anxiety) was in the mild range; the BRS6 measure of resilience was very slightly above the lower boundary of the range [3.00 to 4.30], just within the average level of normal resilience. The EQ-5D-5L mean of 7.9 is relatively close to the best possible value of 5, suggesting good quality of life for the sample as a whole. The mean self-rated health score, which is part of the EQ-5D-5L instrument, was 69.51, but with a large standard deviation suggesting a wide variation across the sample. The perceived support needs value of 29.9 suggests relatively low levels of urgent support was required during lockdown across the sample.

Table 10 shows distribution of PHQ9, GAD7 and BRS6 scores across the severity levels and table VII shows the numbers and percentages of students who scored above and below the clinical cut-offs on the PHQ9 and GAD7, as a whole sample and by gender. Table 11 shows 53.4% of students scored in the clinical range for depression on the PHQ9 (suggestive of clinically significant depression), with females being more likely (56.8%) than males (43.3%) to be above the cut-off. 51.5% of the students scored above the anxiety cut off (suggestive of clinically significant anxiety) on the GAD7 and again the percentage was higher for females (54.8%) than for males (43.2%). The BRS6 scores suggest 26% were in the low resilience category, with no significant gender difference. No students were in the high resilience category.

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Bivariate associations analysis with decision variables

Bivariate associations between demographic characteristics and mental health variables are presented in Table 6 . With respect to gender, female students had significantly higher levels of anxiety and depression and poorer overall self-rated health. Comparing scores for undergraduates and post-graduates, a statistically significant difference was found for the PHQ-9 (depression) only, with undergraduates showing a higher level of depression. This is also reflected in a higher percentage of undergraduates scoring above the clinical cut off on the PHQ9 (56.4%) compared to post-graduates (51%), shown in Table 12 . No significant differences were found in relation to any decision variable when comparing those who were single or in a relationship.

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Bivariate associations between lifestyle/living situations and mental health burden variables are presented in Table 7 . Regarding adverse life experiences during the pandemic, there were no statistically significant differences in depression, anxiety or quality of life between those reporting a negative impact of the pandemic on their life compared to those without any. Interestingly, students reporting at least one impact showed higher level of resilience and self-rated health scores but lower support needs. Regarding exercising, those who always or very often exercised showed lower levels of depression and anxiety, better quality of life, higher self-rated health score and lower support needs, compared to those who occasionally or never exercised.

Regarding the consumption of alcohol and tobacco, most students reported using either substance less often during the pandemic. Alcohol use was not related to any of the decision variables but tobacco use was significantly related to five decision variables, with those using tobacco showing higher anxiety and depression, lower life quality of life and self-reported health, and higher support needs.

Those students reporting an impact of the pandemic on their relationships tended to report higher scores of depression and anxiety, significant enough to put the affected cohort in one level up in terms of severity for both depression and anxiety. This also applied to students reporting scarce communication with friends and family. Those whose relationships had not been impacted or who had maintained good communication with family and friends tended to have better quality of life and self-reported health and lower support needs.

The bivariate analysis of the students’ mental wellbeing history against the set of decision variables are presented in Table 8 . Students who had been referred to or participated in talking therapies for a mental health issue in the past (not just at the current time), tended to report higher scores of depression and anxiety, significant enough to put the affected cohort in one level up in terms of severity for both depression and anxiety. Students who reported currently or previously taking medications for a mental health issue, or had accessed or attempted to access healthcare services personally or for a family member during the pandemic period, also tended to experience higher levels of depression and anxiety with lower life quality and self-rated health score and more support needs.

The bivariate analysis on COVID-19 related questions against the set of decision variables are presented in Table 9 . A large majority of participants, 93.4%, reported always or very often practising social distancing and this factor was not related to any of the decision variables (possibly due to the highly skewed distribution on this factor). About 15% of the students were in high or increased risk due to pre-existing medical conditions or needing special care and the higher risk group showed higher scores of depression and lower health scores, yet they had lower support needs and better index for quality of life. Furthermore, approximately 30% of the students reported living with someone in a high or increased risk group and these tended to showed higher levels of depression and anxiety, poorer quality of life and lower self-rated health scores, while having more support needs. Finally, 16.5% of the participants reported feeling likely or extremely likely to contract the virus, and these showed an increased level of anxiety, worse health score and higher support needs.

Multivariate linear regression analysis

A multivariate linear regression was conducted for each of the dependent variables, with results presented in Tables 13 and 14 , with each regression analysis using a different subset of independent variables, those which were found to be statistically significantly related from the bivariate analysis as shown in Tables 6 – 9 .

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Apart from the regression model for the BRS6 Resilience variable, which achieves the statistical significance at the level of p < 0.01 (with R 2 only being 0.014), the remaining regression models all achieve statistical significance with p < 0.001, indicating the selection of underlying variables are meaningful in associating with the level of the corresponding decision variable.

Ten out of eleven variables included for the analysis of the PHQ9 show statistical significance. Exercise was the predictor with biggest coefficient, closely followed by communication, and then the history of accessing a talking therapy and impact on relationships. The values of these coefficients within 95% of the data, (the confidence interval, CI), or within two standard deviations, are also listed accordingly. For the regression analysis for the GAD7, ten variables were included with only the contract risk not showing a statistical significance contribution. The level of communication with families/friends was the most significant predictor for anxiety, followed by accessing a talking therapy and impact on relationships. There were also significant gender differences, with female students showing higher levels of anxiety and depression, and lower self-rated health scores. For BRS6, only three independent variables were included, with ethnicity and the adversity question (which asked whether the student had experienced any adverse events) showing statistical significance.

Nine predictors were included for the analysis of EQ5D5L quality of life measure, with the three most significant predictors being a history of talking therapy, taking medication for a mental health issue and access or attempt to access healthcare service personally or for a family member during the pandemic.

Twelve predictors were included for the analysis of self-rated health score, with seven showing a statistically significant correlation. Exercise, accessing talking therapy and communication were the top three predictors.

Eight out of twelve variables were significant predictors for the support needs dependent variable, with healthcare service, medication and communication being top three predictors.

This survey set out to investigate the mental health and wellbeing of higher education students during the COVID19 pandemic and predictive factors. Perhaps the most striking finding was the high levels of depression and anxiety, with scores above the clinical cut off for over half the students. This suggests they are likely to have been experiencing clinically significant levels of depression and/or anxiety at the time of the survey. Measures such as the PHQ9 and GAD7 are screening instruments which highlight individuals likely to have significant problems and requiring further assessment and support. Although these measures are not diagnostic, they have been favourably compared to diagnostic interviews [ 22 ]. Previous community surveys suggest about one in six people report experiencing a common mental health problem (anxiety or depression) in a given week in England [ 2 ] so our survey suggests the incidence of common mental health problems was much higher than usual in this student group during the pandemic. The survey took place over one month, about three to four months after the first lockdown in the UK began (and after exam time for undergraduates), so it is likely to be due to the pandemic rather than other factors but we do not know how the levels of anxiety and depression changed over time. A recent study [ 23 ] identified different trajectories of depression and anxiety symptoms over time for subgroups in a large community sample in England during the pandemic. For example, they found young, female and more sociable people, and essential workers, experienced severe anxiety at the start of the lockdown which quickly decreased whilst younger people with lower incomes and previous mental health problems experienced increasing levels of symptoms over time. Other surveys have also showed increases in common mental health problems during the pandemic. For example, an Office for National Statistics (ONS) survey in early 2021 reported about 1 in 5 (21%) adults experienced depression in early 2021, more than double that found before the COVID-19 pandemic (10%). This ONS survey also reported that younger adults and women were more likely to experience some form of depression, with 43% of women and 26% of men in the 16 to 29 year age range found to be experiencing depressive symptoms. This higher level of depressive symptoms in women and younger adults is consistent with our survey and we also found higher levels of anxiety symptoms. Other studies have also reported higher levels psychological distress in younger people, with higher levels in females compared to males, during the pandemic [ 24 ]. The high percentages of students reporting current or past referral to or receiving talking therapy (40%) and/or medication for mental health problems (28%) suggest this may have been a sample with relatively high levels of pre-existing mental health difficulties but this is speculative. The high levels of anxiety and depression contrast to some extent with the quality of life scores, which might suggest that the experience of low mood and anxiety were due to the current circumstances of the pandemic (and therefore transient for many people), rather than longer term mental health difficulties that had impacted on quality of life. However, we do not how, as the pandemic and restrictions persisted, quality of life was affected in the longer term. It was interesting that the 15% of the students who were in high or increased risk due to pre-existing medical conditions or needing special care showed higher scores of depression and lower health scores, yet they had lower support needs and better index for quality of life. It is possible that this was due to them having better support systems in place before the pandemic, which they continued to access.

The study also set out to investigate levels and predictors of resilience and most students scored in the normal range with 26% in low resilience category and none in the high category. This is reflected in the overall mean of 3.1 which is lower than that reported in the original validation study [ 19 ] which reported on four samples (including two student samples), with means ranging from 3.53 to 3.98 and lower scores in the younger age groups. An interpretation of the resilience scores is that the pandemic not only led to increases in anxiety and depression but also undermined personal resilience. For example, the restrictions of lockdown were likely to have deprived students of outlets and activities important to their wellbeing. Also, low mood may have contributed to a negative appraisal of personal resilience at the time. It is therefore possible that the low resilience is due to the adverse circumstances of the pandemic and lockdown, not stable characteristics of the individuals. We suggest our findings should be interpreted in terms of attributing the distress and coping as consequence of the situation the students found themselves in, ‘what happened to them’ during the pandemic, rather than ‘what is wrong with’ them [ 25 , 26 ].

The survey also suggested a number of factors that may have contributed to the high levels of common mental health problems (in addition to gender), such as cancellation of an important event (56%), worse personal relations (40%) and worse financial situation (40%). Students with higher levels of depression tended to exercise less, communicated less with friends/family, and experienced greater impacts on their relationships, as well as (not surprisingly) having more history of accessing a talking therapy. Those with higher anxiety levels also tended to communicate less with friends/family, experience greater impacts on their relationships, and had more history of accessing a talking therapy. We cannot attribute causal effects and in some cases the relationships between these variables are likely to work both ways. For example, low mood may lead to worse personal relationships which would adversely affect mood.

The relationship between exercise and mental health in our survey is consistent with evidence that physical activity has a role in preventing depression [ 27 ] and a physical activity programme is recommended for people with mild to moderate depression [ 28 ]. The finding that tobacco use was significantly related to higher anxiety and depression, lower life quality of life and self-reported health, and higher support needs is consistent with reports that as the severity of mental health problems increase, the prevalence of smoking is higher [ 29 ]. For example, Public Health England reports that whilst the prevalence of smoking for all adults in England was 16.4% in 2014 to 2015, the prevalence was 28% for people with anxiety or depression, and 40.5% for those with serious mental illness. There is also good evidence that smoking cessation is associated with reductions in anxiety and depression, and with improvements in mood and quality of life, and that this applies to those with mental health problems [ 30 ].

There are a number of limitations of this study. Firstly, this was a one off, cross sectional survey over one month, four months into the pandemic so we are not able to report on changes over time, and crucially, whether the high levels of anxiety and depression were transitory or longer term. Secondly, the survey was carried out at only one University in England so it is possible findings will differ in other localities. Having said that, there was diversity in our sample, which included students from all over the UK with a higher proportion of non-white students (32%) than in the general population in England, enabling comparisons to be made between white and non-white students. Thirdly, it is possible that there was a bias in our sample, in that those experiencing mental health difficulties at the time of the survey were more likely to be attracted by the advert for the survey and to complete it. It may not therefore be representative of the larger population of students but the high levels of anxiety and depression and gender difference are nevertheless significant findings. Finally, although the study identifies levels and predictors of mental health distress, it does not identify how the pandemic impacted on individuals, and how they coped with the challenges. This would require more in depth, qualitative research and we recommend this to complement surveys.

Despite these limitations, this study identifies high levels of anxiety and depression in undergraduate and postgraduate students early in Covid-19 pandemic in England and relatively low levels of resilience which are likely to reflect the impact of restrictions and isolation which reduced the opportunities to engage in helpful coping strategies and activities. These high levels of psycho logical distress are therefore likely to be a combination of pandemic-related stresses and limited access to positive coping behaviours, such as socialising. Mental health distress was associated with lower levels of exercising, higher levels of tobacco use, and a number of life events likely to be associated with the pandemic and lockdown, such as cancelled events, worsening in personal relationships and financial concerns. We can assume that some of the students would have been experiencing high levels of depression and anxiety for the first time, whilst others would have experienced a worsening of pre-existing difficulties. This study highlights how these mainly younger adult students may be particularly prone to experiencing high levels of anxiety and low mood during a pandemic, and the importance of providing support to reduce the likelihood of longer-term problems. Given the global context for these increased levels of psychological distress, it is important to see this as an understandable reaction to an adverse situation which may be transitory, rather than necessarily the start of continued and long-term problems but this will only be achieved with support. Some will find adequate support within their social networks, coping strategies and activities, but it is likely a significant number would be at risk of longer term and more severe difficulties and might therefore benefit from professional support including psychological therapy and counselling.

Acknowledgments

The authors highly appreciate Altif Ali’s general technical support in this research.

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Expert Commentary

Improving college student mental health: Research on promising campus interventions

Hiring more counselors isn’t enough to improve college student mental health, scholars warn. We look at research on programs and policies schools have tried, with varying results.

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This work is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License .

by Denise-Marie Ordway, The Journalist's Resource September 13, 2023

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If you’re a journalist covering higher education in the U.S., you’ll likely be reporting this fall on what many healthcare professionals and researchers are calling a college student mental health crisis.

An estimated 49% of college students have symptoms of depression or anxiety disorder and 14% seriously considered committing suicide during the past year, according to a national survey of college students conducted during the 2022-23 school year. Nearly one-third of the 76,406 students who participated said they had intentionally injured themselves in recent months.

In December, U.S. Surgeon General Vivek Murthy issued a rare public health advisory calling attention to the rising number of youth attempting suicide , noting the COVID-19 pandemic has “exacerbated the unprecedented stresses young people already faced.”

Meanwhile, colleges and universities of all sizes are struggling to meet the need for mental health care among undergraduate and graduate students. Many schools have hired more counselors and expanded services but continue to fall short.

Hundreds of University of Houston students held a protest earlier this year , demanding the administration increase the number of counselors and make other changes after two students died by suicide during the spring semester, the online publication Chron reported.

In an essay in the student-run newspaper , The Cougar, last week, student journalist Malachi Key blasts the university for having one mental health counselor for every 2,122 students, a ratio higher than recommended by the International Accreditation of Counseling Services , which accredits higher education counseling services.

But adding staff to a campus counseling center won’t be enough to improve college student mental health and well-being, scholars and health care practitioners warn.

“Counseling centers cannot and should not be expected to solve these problems alone, given that the factors and forces affecting student well-being go well beyond the purview and resources that counseling centers can bring to bear,” a committee of the National Academies of Sciences, Engineering, and Medicine writes in a 2021 report examining the issue.

Advice from prominent scholars

The report is the culmination of an 18-month investigation the National Academies launched in 2019, at the request of the federal government, to better understand how campus culture affects college student mental health and well-being. Committee members examined data, studied research articles and met with higher education leaders, mental health practitioners, researchers and students.

The committee’s key recommendation: that schools take a more comprehensive approach to student mental health, implementing a wide range of policies and programs aimed at preventing mental health problems and improving the well-being of all students — in addition to providing services and treatment for students in distress and those with diagnosed mental illnesses.

Everyone on campus, including faculty and staff across departments, needs to pitch in to establish a new campus culture, the committee asserts.

“An ‘all hands’ approach, one that emphasizes shared responsibility and a holistic understanding of what it means in practice to support students, is needed if institutions of higher education are to intervene from anything more than a reactive standpoint,” committee members write. “Creating this systemic change requires that institutions examine the entire culture and environment of the institution and accept more responsibility for creating learning environments where a changing student population can thrive.”

In a more recent analysis , three leading scholars in the field also stress the need for a broader plan of action.

Sara Abelson , a research assistant professor at Temple University’s medical school; Sarah Lipson , an associate professor at the Boston University School of Public Health; and Daniel Eisenberg , a professor of health policy and management at the University of California, Los Angeles’ School of Public Health, have been studying college student mental health for years.

Lipson and Eisenberg also are principal investigators for the Healthy Minds Network , which administers the Healthy Minds Study , a national survey of U.S college students conducted annually to gather information about their mental health, whether and how they receive mental health care and related issues.

Abelson, Lipson and Eisenberg review the research to date on mental health interventions for college students in the 2022 edition of Higher Education: Handbook of Theory and Research . They note that while the evidence indicates a multi-pronged approach is best, it’s unclear which specific strategies are most effective.

Much more research needed

Abelson, Lipson and Eisenberg stress the need for more research. Many interventions in place at colleges and universities today — for instance, schoolwide initiatives aimed at reducing mental health stigma and encouraging students to seek help when in duress – should be evaluated to gauge their effectiveness, they write in their chapter, “ Mental Health in College Populations: A Multidisciplinary Review of What Works, Evidence Gaps, and Paths Forward .”

They add that researchers and higher education leaders also need to look at how campus operations, including hiring practices and budgetary decisions, affect college student mental health. It would be helpful to know, for example, how students are impacted by limits on the number of campus counseling sessions they can have during a given period, Abelson, Lipson and Eisenberg suggest.

Likewise, it would be useful to know whether students are more likely to seek counseling when they must pay for their sessions or when their school charges every member of the student body a mandatory health fee that provides free counseling for all students.

“These financially-based considerations likely influence help-seeking and treatment receipt, but they have not been evaluated within higher education,” they write.

Interventions that show promise

The report from the National Academies of Sciences, Engineering, and Medicine and the chapter by Abelson, Lipson and Eisenberg both spotlight programs and policies shown to prevent mental health problems or improve the mental health and well-being of young people. However, many intervention studies focus on high school students, specific groups of college students or specific institutions. Because of this, it can be tough to predict how well they would work across the higher education landscape.

Scientific evaluations of these types of interventions indicate they are effective:

Building students’ behavior management skills and having them practice new skills under expert supervision . An example: A class that teaches students how to use mindfulness to improve their mental and physical health that includes instructor-led meditation exercises.
Training some students to offer support to others , including sharing information and organizing peer counseling groups. “Peers may be ‘the single most potent source of influence’ on student affective and cognitive growth and development during college,” Abelson, Lipson and Eisenberg write.
Reducing students’ access to things they can use to harm themselves , including guns and lethal doses of over-the-counter medication.
Creating feelings of belonging through activities that connect students with similar interests or backgrounds.
Making campuses more inclusive for racial and ethnic minorities, LGBTQ+ students and students who are the first in their families to go to college. One way to do that is by hiring mental health professionals trained to recognize, support and treat students from different backgrounds. “Research has shown that the presentation of [mental health] symptoms can differ based on racial and ethnic backgrounds, as can engaging in help-seeking behaviors that differ from those of cisgender, heteronormative white men,” explain members of National Academies of Sciences, Engineering, and Medicine committee.

Helping journalists sift through the evidence

We encourage journalists to read the full committee report and aforementioned chapter in Higher Education: Handbook of Theory and Research . We realize, though, that many journalists won’t have time to pour over the combined 304 pages of text to better understand this issue and the wide array of interventions colleges and universities have tried, with varying success.

To help, we’ve gathered and summarized meta-analyses that investigate some of the more common interventions. Researchers conduct meta-analyses — a top-tier form of scientific evidence — to systematically analyze all the numerical data that appear in academic studies on a given topic. The findings of a meta-analysis are statistically stronger than those reached in a single study, partly because pooling data from multiple, similar studies creates a larger sample to examine.

Keep reading to learn more. And please check back here occasionally because we’ll add to this list as new research on college student mental health is published.

Peer-led programs

Stigma and Peer-Led Interventions: A Systematic Review and Meta-Analysis Jing Sun; et al. Frontiers in Psychiatry, July 2022.

When people diagnosed with a mental illness received social or emotional support from peers with similar mental health conditions, they experienced less stress about the public stigma of mental illness, this analysis suggests.

The intervention worked for people from various age groups, including college students and middle-aged adults, researchers learned after analyzing seven studies on peer-led mental health programs written or published between 1975 and 2021.

Researchers found that participants also became less likely to identify with negative stereotypes associated with mental illness.

All seven studies they examined are randomized controlled trials conducted in the U.S., Germany or Switzerland. Together, the findings represent the experiences of a total of 763 people, 193 of whom were students at universities in the U.S.

Researchers focused on interventions designed for small groups of people, with the goal of reducing self-stigma and stress associated with the public stigma of mental illness. One or two trained peer counselors led each group for activities spanning three to 10 weeks.

Five of the seven studies tested the Honest, Open, Proud program, which features role-playing exercises, self-reflection and group discussion. It encourages participants to consider disclosing their mental health issues, instead of keeping them a secret, in hopes that will help them feel more confident and empowered. The two other programs studied are PhotoVoice , based in the United Kingdom, and

“By sharing their own experiences or recovery stories, peer moderators may bring a closer relationship, reduce stereotypes, and form a positive sense of identity and group identity, thereby reducing self-stigma,” the authors of the analysis write.

Expert-led instruction

The Effects of Meditation, Yoga, and Mindfulness on Depression, Anxiety, and Stress in Tertiary Education Students: A Meta-Analysis Josefien Breedvelt; et al. Frontiers in Psychiatry, April 2019.

Meditation-based programs help reduce symptoms of depression, anxiety and stress among college students, researchers find after analyzing the results of 24 research studies conducted in various parts of North America, Asia and Europe.

Reductions were “moderate,” researchers write. They warn, however, that the results of their meta-analysis should be interpreted with caution considering studies varied in quality.

A total of 1,373 college students participated in the 24 studies. Students practiced meditation, yoga or mindfulness an average of 153 minutes a week for about seven weeks. Most programs were provided in a group setting.

Although the researchers do not specify which types of mindfulness, yoga or meditation training students received, they note that the most commonly offered mindfulness program is Mindfulness-Based Stress Reduction and that a frequently practiced form of yoga is Hatha Yoga .

Meta-Analytic Evaluation of Stress Reduction Interventions for Undergraduate and Graduate Students Miryam Yusufov; et al. International Journal of Stress Management, May 2019.

After examining six types of stress-reduction programs common on college campuses, researchers determined all were effective at reducing stress or anxiety among students — and some helped with both stress and anxiety.

Programs focusing on cognitive-behavioral therapy , coping skills and building social support networks were more effective in reducing stress. Meanwhile, relaxation training, mindfulness-based stress reduction and psychoeducation were more effective in reducing anxiety.

The authors find that all six program types were equally effective for undergraduate and graduate students.

The findings are based on an analysis of 43 studies dated from 1980 to 2015, 30 of which were conducted in the U.S. The rest were conducted in Australia, China, India, Iran, Japan, Jordan, Kora, Malaysia or Thailand. A total of 4,400 students participated.

Building an inclusive environment

Cultural Adaptations and Therapist Multicultural Competence: Two Meta-Analytic Reviews Alberto Soto; et al. Journal of Clinical Psychology, August 2018.

If racial and ethnic minorities believe their therapist understands their background and culture, their treatment tends to be more successful, this analysis suggests.

“The more a treatment is tailored to match the precise characteristics of a client, the more likely that client will engage in treatment, remain in treatment, and experience improvement as a result of treatment,” the authors write.

Researchers analyzed the results of 15 journal articles and doctoral dissertations that examine therapists’ cultural competence . Nearly three-fourths of those studies were written or published in 2010 or later. Together, the findings represent the experiences of 2,640 therapy clients, many of whom were college students. Just over 40% of participants were African American and 32% were Hispanic or Latino.

The researchers note that they find no link between therapists’ ratings of their own level of cultural competence and client outcomes.

Internet-based interventions

Internet Interventions for Mental Health in University Students: A Systematic Review and Meta-Analysis Mathias Harrer; et al. International Journal of Methods in Psychiatric Research, June 2019.

Internet-based mental health programs can help reduce stress and symptoms of anxiety, depression and eating disorders among college students, according to an analysis of 48 research studies published or written before April 30, 2018 on the topic.

All 48 studies were randomized, controlled trials of mental health interventions that used the internet to engage with students across various platforms and devices, including mobile phones and apps. In total, 10,583 students participated in the trials.

“We found small effects on depression, anxiety, and stress symptoms, as well as moderate‐sized effects on eating disorder symptoms and students’ social and academic functioning,” write the authors, who conducted the meta-analysis as part of the World Mental Health International College Student Initiative .

The analysis indicates programs that focus on cognitive behavioral therapy “were superior to other types of interventions.” Also, programs “of moderate length” — one to two months – were more effective.

The researchers note that studies of programs targeting depression showed better results when students were not compensated for their participation, compared to studies in which no compensation was provided. The researchers do not offer possible explanations for the difference in results or details about the types of compensation offered to students.

About The Author

Denise-Marie Ordway

Student mental health is in crisis. Campuses are rethinking their approach

Amid massive increases in demand for care, psychologists are helping colleges and universities embrace a broader culture of well-being and better equipping faculty to support students in need

Vol. 53 No. 7 Print version: page 60

Mental Health

college student looking distressed while clutching textbooks

By nearly every metric, student mental health is worsening. During the 2020–2021 school year, more than 60% of college students met the criteria for at least one mental health problem, according to the Healthy Minds Study, which collects data from 373 campuses nationwide ( Lipson, S. K., et al., Journal of Affective Disorders , Vol. 306, 2022 ). In another national survey, almost three quarters of students reported moderate or severe psychological distress ( National College Health Assessment , American College Health Association, 2021).

Even before the pandemic, schools were facing a surge in demand for care that far outpaced capacity, and it has become increasingly clear that the traditional counseling center model is ill-equipped to solve the problem.

“Counseling centers have seen extraordinary increases in demand over the past decade,” said Michael Gerard Mason, PhD, associate dean of African American Affairs at the University of Virginia (UVA) and a longtime college counselor. “[At UVA], our counseling staff has almost tripled in size, but even if we continue hiring, I don’t think we could ever staff our way out of this challenge.”

Some of the reasons for that increase are positive. Compared with past generations, more students on campus today have accessed mental health treatment before college, suggesting that higher education is now an option for a larger segment of society, said Micky Sharma, PsyD, who directs student life’s counseling and consultation service at The Ohio State University (OSU). Stigma around mental health issues also continues to drop, leading more people to seek help instead of suffering in silence.

But college students today are also juggling a dizzying array of challenges, from coursework, relationships, and adjustment to campus life to economic strain, social injustice, mass violence, and various forms of loss related to Covid -19.

As a result, school leaders are starting to think outside the box about how to help. Institutions across the country are embracing approaches such as group therapy, peer counseling, and telehealth. They’re also better equipping faculty and staff to spot—and support—students in distress, and rethinking how to respond when a crisis occurs. And many schools are finding ways to incorporate a broader culture of wellness into their policies, systems, and day-to-day campus life.

“This increase in demand has challenged institutions to think holistically and take a multifaceted approach to supporting students,” said Kevin Shollenberger, the vice provost for student health and well-being at Johns Hopkins University. “It really has to be everyone’s responsibility at the university to create a culture of well-being.”

Higher caseloads, creative solutions

The number of students seeking help at campus counseling centers increased almost 40% between 2009 and 2015 and continued to rise until the pandemic began, according to data from Penn State University’s Center for Collegiate Mental Health (CCMH), a research-practice network of more than 700 college and university counseling centers ( CCMH Annual Report , 2015 ).

That rising demand hasn’t been matched by a corresponding rise in funding, which has led to higher caseloads. Nationwide, the average annual caseload for a typical full-time college counselor is about 120 students, with some centers averaging more than 300 students per counselor ( CCMH Annual Report , 2021 ).

“We find that high-caseload centers tend to provide less care to students experiencing a wide range of problems, including those with safety concerns and critical issues—such as suicidality and trauma—that are often prioritized by institutions,” said psychologist Brett Scofield, PhD, executive director of CCMH.

To minimize students slipping through the cracks, schools are dedicating more resources to rapid access and assessment, where students can walk in for a same-day intake or single counseling session, rather than languishing on a waitlist for weeks or months. Following an evaluation, many schools employ a stepped-care model, where the students who are most in need receive the most intensive care.

Given the wide range of concerns students are facing, experts say this approach makes more sense than offering traditional therapy to everyone.

“Early on, it was just about more, more, more clinicians,” said counseling psychologist Carla McCowan, PhD, director of the counseling center at the University of Illinois at Urbana-Champaign. “In the past few years, more centers are thinking creatively about how to meet the demand. Not every student needs individual therapy, but many need opportunities to increase their resilience, build new skills, and connect with one another.”

Students who are struggling with academic demands, for instance, may benefit from workshops on stress, sleep, time management, and goal-setting. Those who are mourning the loss of a typical college experience because of the pandemic—or facing adjustment issues such as loneliness, low self-esteem, or interpersonal conflict—are good candidates for peer counseling. Meanwhile, students with more acute concerns, including disordered eating, trauma following a sexual assault, or depression, can still access one-on-one sessions with professional counselors.

As they move away from a sole reliance on individual therapy, schools are also working to shift the narrative about what mental health care on campus looks like. Scofield said it’s crucial to manage expectations among students and their families, ideally shortly after (or even before) enrollment. For example, most counseling centers won’t be able to offer unlimited weekly sessions throughout a student’s college career—and those who require that level of support will likely be better served with a referral to a community provider.

“We really want to encourage institutions to be transparent about the services they can realistically provide based on the current staffing levels at a counseling center,” Scofield said.

The first line of defense

Faculty may be hired to teach, but schools are also starting to rely on them as “first responders” who can help identify students in distress, said psychologist Hideko Sera, PsyD, director of the Office of Equity, Inclusion, and Belonging at Morehouse College, a historically Black men’s college in Atlanta. During the pandemic, that trend accelerated.

“Throughout the remote learning phase of the pandemic, faculty really became students’ main points of contact with the university,” said Bridgette Hard, PhD, an associate professor and director of undergraduate studies in psychology and neuroscience at Duke University. “It became more important than ever for faculty to be able to detect when a student might be struggling.”

Many felt ill-equipped to do so, though, with some wondering if it was even in their scope of practice to approach students about their mental health without specialized training, Mason said.

Schools are using several approaches to clarify expectations of faculty and give them tools to help. About 900 faculty and staff at the University of North Carolina have received training in Mental Health First Aid , which provides basic skills for supporting people with mental health and substance use issues. Other institutions are offering workshops and materials that teach faculty to “recognize, respond, and refer,” including Penn State’s Red Folder campaign .

Faculty are taught that a sudden change in behavior—including a drop in attendance, failure to submit assignments, or a disheveled appearance—may indicate that a student is struggling. Staff across campus, including athletic coaches and academic advisers, can also monitor students for signs of distress. (At Penn State, eating disorder referrals can even come from staff working in food service, said counseling psychologist Natalie Hernandez DePalma, PhD, senior director of the school’s counseling and psychological services.) Responding can be as simple as reaching out and asking if everything is going OK.

Referral options vary but may include directing a student to a wellness seminar or calling the counseling center to make an appointment, which can help students access services that they may be less likely to seek on their own, Hernandez DePalma said. Many schools also offer reporting systems, such as DukeReach at Duke University , that allow anyone on campus to express concern about a student if they are unsure how to respond. Trained care providers can then follow up with a welfare check or offer other forms of support.

“Faculty aren’t expected to be counselors, just to show a sense of care that they notice something might be going on, and to know where to refer students,” Shollenberger said.

At Johns Hopkins, he and his team have also worked with faculty on ways to discuss difficult world events during class after hearing from students that it felt jarring when major incidents such as George Floyd’s murder or the war in Ukraine went unacknowledged during class.

Many schools also support faculty by embedding counselors within academic units, where they are more visible to students and can develop cultural expertise (the needs of students studying engineering may differ somewhat from those in fine arts, for instance).

When it comes to course policy, even small changes can make a big difference for students, said Diana Brecher, PhD, a clinical psychologist and scholar-in-residence for positive psychology at Toronto Metropolitan University (TMU), formerly Ryerson University. For example, instructors might allow students a 7-day window to submit assignments, giving them agency to coordinate with other coursework and obligations. Setting deadlines in the late afternoon or early evening, as opposed to at midnight, can also help promote student wellness.

At Moraine Valley Community College (MVCC) near Chicago, Shelita Shaw, an assistant professor of communications, devised new class policies and assignments when she noticed students struggling with mental health and motivation. Those included mental health days, mindful journaling, and a trip with family and friends to a Chicago landmark, such as Millennium Park or Navy Pier—where many MVCC students had never been.

Faculty in the psychology department may have a unique opportunity to leverage insights from their own discipline to improve student well-being. Hard, who teaches introductory psychology at Duke, weaves in messages about how students can apply research insights on emotion regulation, learning and memory, and a positive “stress mindset” to their lives ( Crum, A. J., et al., Anxiety, Stress, & Coping , Vol. 30, No. 4, 2017 ).

Along with her colleague Deena Kara Shaffer, PhD, Brecher cocreated TMU’s Thriving in Action curriculum, which is delivered through a 10-week in-person workshop series and via a for-credit elective course. The material is also freely available for students to explore online . The for-credit course includes lectures on gratitude, attention, healthy habits, and other topics informed by psychological research that are intended to set students up for success in studying, relationships, and campus life.

“We try to embed a healthy approach to studying in the way we teach the class,” Brecher said. “For example, we shift activities every 20 minutes or so to help students sustain attention and stamina throughout the lesson.”

Creative approaches to support

Given the crucial role of social connection in maintaining and restoring mental health, many schools have invested in group therapy. Groups can help students work through challenges such as social anxiety, eating disorders, sexual assault, racial trauma, grief and loss, chronic illness, and more—with the support of professional counselors and peers. Some cater to specific populations, including those who tend to engage less with traditional counseling services. At Florida Gulf Coast University (FGCU), for example, the “Bold Eagles” support group welcomes men who are exploring their emotions and gender roles.

The widespread popularity of group therapy highlights the decrease in stigma around mental health services on college campuses, said Jon Brunner, PhD, the senior director of counseling and wellness services at FGCU. At smaller schools, creating peer support groups that feel anonymous may be more challenging, but providing clear guidelines about group participation, including confidentiality, can help put students at ease, Brunner said.

Less formal groups, sometimes called “counselor chats,” meet in public spaces around campus and can be especially helpful for reaching underserved groups—such as international students, first-generation college students, and students of color—who may be less likely to seek services at a counseling center. At Johns Hopkins, a thriving international student support group holds weekly meetings in a café next to the library. Counselors typically facilitate such meetings, often through partnerships with campus centers or groups that support specific populations, such as LGBTQ students or student athletes.

“It’s important for students to see counselors out and about, engaging with the campus community,” McCowan said. “Otherwise, you’re only seeing the students who are comfortable coming in the door.”

Peer counseling is another means of leveraging social connectedness to help students stay well. At UVA, Mason and his colleagues found that about 75% of students reached out to a peer first when they were in distress, while only about 11% contacted faculty, staff, or administrators.

“What we started to understand was that in many ways, the people who had the least capacity to provide a professional level of help were the ones most likely to provide it,” he said.

Project Rise , a peer counseling service created by and for Black students at UVA, was one antidote to this. Mason also helped launch a two-part course, “Hoos Helping Hoos,” (a nod to UVA’s unofficial nickname, the Wahoos) to train students across the university on empathy, mentoring, and active listening skills.

At Washington University in St. Louis, Uncle Joe’s Peer Counseling and Resource Center offers confidential one-on-one sessions, in person and over the phone, to help fellow students manage anxiety, depression, academic stress, and other campus-life issues. Their peer counselors each receive more than 100 hours of training, including everything from basic counseling skills to handling suicidality.

Uncle Joe’s codirectors, Colleen Avila and Ruchika Kamojjala, say the service is popular because it’s run by students and doesn’t require a long-term investment the way traditional psychotherapy does.

“We can form a connection, but it doesn’t have to feel like a commitment,” said Avila, a senior studying studio art and philosophy-neuroscience-psychology. “It’s completely anonymous, one time per issue, and it’s there whenever you feel like you need it.”

As part of the shift toward rapid access, many schools also offer “Let’s Talk” programs , which allow students to drop in for an informal one-on-one session with a counselor. Some also contract with telehealth platforms, such as WellTrack and SilverCloud, to ensure that services are available whenever students need them. A range of additional resources—including sleep seminars, stress management workshops, wellness coaching, and free subscriptions to Calm, Headspace, and other apps—are also becoming increasingly available to students.

Those approaches can address many student concerns, but institutions also need to be prepared to aid students during a mental health crisis, and some are rethinking how best to do so. Penn State offers a crisis line, available anytime, staffed with counselors ready to talk or deploy on an active rescue. Johns Hopkins is piloting a behavioral health crisis support program, similar to one used by the New York City Police Department, that dispatches trained crisis clinicians alongside public safety officers to conduct wellness checks.

A culture of wellness

With mental health resources no longer confined to the counseling center, schools need a way to connect students to a range of available services. At OSU, Sharma was part of a group of students, staff, and administrators who visited Apple Park in Cupertino, California, to develop the Ohio State: Wellness App .

Students can use the app to create their own “wellness plan” and access timely content, such as advice for managing stress during final exams. They can also connect with friends to share articles and set goals—for instance, challenging a friend to attend two yoga classes every week for a month. OSU’s apps had more than 240,000 users last year.

At Johns Hopkins, administrators are exploring how to adapt school policies and procedures to better support student wellness, Shollenberger said. For example, they adapted their leave policy—including how refunds, grades, and health insurance are handled—so that students can take time off with fewer barriers. The university also launched an educational campaign this fall to help international students navigate student health insurance plans after noticing below average use by that group.

Students are a key part of the effort to improve mental health care, including at the systemic level. At Morehouse College, Sera serves as the adviser for Chill , a student-led advocacy and allyship organization that includes members from Spelman College and Clark Atlanta University, two other HBCUs in the area. The group, which received training on federal advocacy from APA’s Advocacy Office earlier this year, aims to lobby public officials—including U.S. Senator Raphael Warnock, a Morehouse College alumnus—to increase mental health resources for students of color.

“This work is very aligned with the spirit of HBCUs, which are often the ones raising voices at the national level to advocate for the betterment of Black and Brown communities,” Sera said.

Despite the creative approaches that students, faculty, staff, and administrators are employing, students continue to struggle, and most of those doing this work agree that more support is still urgently needed.

“The work we do is important, but it can also be exhausting,” said Kamojjala, of Uncle Joe’s peer counseling, which operates on a volunteer basis. “Students just need more support, and this work won’t be sustainable in the long run if that doesn’t arrive.”

Contact APA

Supporting mental health and wellbeing of university and college students: A systematic review of review-level evidence of interventions

Joanne deborah worsley.

1 Department of Primary Care and Mental Health, University of Liverpool, Liverpool, United Kingdom

Andy Pennington

2 Department of Public Health and Policy, University of Liverpool, Liverpool, United Kingdom

Rhiannon Corcoran

Associated data.

The authors have provided detailed information regarding their search strategy and the articles that were found. The information necessary to replicate the study is in the Supporting information files.

The review of reviews had three aims: (i) to synthesize the available evidence on interventions to improve college and university students’ mental health and wellbeing; (ii) to identify the effectiveness of interventions, and (iii) to highlight gaps in the evidence base for future study.

Electronic database searches were conducted to identify reviews in English from high-income OECD countries published between 1999 and 2020. All review-level empirical studies involving post-secondary students attending colleges of further education or universities that examined interventions to improve general mental health and wellbeing were included. Articles were critically appraised using an amended version of the AMSTAR 2 tool. Evidence from the included reviews were narratively synthesized and organised by intervention types.

Twenty-seven reviews met the review of reviews inclusion criteria. The quality of the included reviews varied considerably. Intervention types identified included: mindfulness-based interventions, psychological interventions, psychoeducation interventions, recreation programmes, relaxation interventions, setting-based interventions, and stress management/reduction interventions. There was evidence that mindfulness-based interventions, cognitive behavioural therapy (CBT), and interventions delivered via technology were effective when compared to a passive control. Some evidence suggested that the effects of CBT-related interventions are sustained over time. Psychoeducation interventions do not appear to be as effective as other forms of intervention, with its effects not enduring over time.

Conclusions

The review of reviews located a sizeable body of evidence on specific interventions such as mindfulness and cognitive-behavioural interventions. The evidence suggests that these interventions can effectively reduce common mental health difficulties in the higher education student body. Gaps and limitations in the reviews and the underlying body of evidence have been identified. These include a notable gap in the existing body of review-level evidence on setting-based interventions, acceptance and commitment training, and interventions for students attending colleges in UK settings.

Introduction

Poor mental health of further and higher education students is a growing public policy concern [ 1 , 2 ]. Recent research indicates that levels of common mental health difficulties, self-harm, and suicide are increasing among young people, especially young women [ 3 – 5 ]. There have been particular concerns about university students, with research and official figures suggesting that there has been an increase in the number of students experiencing mental health problems over recent years. Data on young people aged 16 to 24 years from three UK National Psychiatric Morbidity Surveys (2000, 2007, and 2014) highlighted that the prevalence of common mental health problems, suicide attempts, and self-harm was similar in students and non-students [ 6 ]. Between 2007 and 2014, however, the prevalence of common mental health problems increased in female students but not in female non-students. Although the prevalence of non-suicidal self-harm increased between 2000 and 2014 in both students and non-students, a smaller proportion of students than non-students reported suicide attempts [ 6 ]. US college students are also increasingly reporting common mental health problems and suicidality [ 7 ]. It is, therefore, important for educational institutions to offer accessible and effective interventions for their students.

Research suggests that young people’s mental health is poorer during university study than before entry. In a UK study, anxiety and depression were found to be higher at mid-course compared to one-month pre-entry into university [ 8 ]. Similarly, a UK cohort study found that levels of psychological distress increase on entering university and levels of distress did not return to pre-registration levels [ 9 ]. Other studies have also demonstrated that students’ mental health is poorer during their first year of study compared to pre-entry into university [ 10 ].

Concern around students’ mental health has prompted recent focus on mental health provision [ 11 ]. Services offered within educational institutions typically include either individual or group counselling. Although these services are well-positioned to provide mental health care, many college counselling centres across the US are under-resourced and operate at full capacity during much of the year [ 12 ]. According to an online survey of UK student counselling services, there was an increase in demand for support services over a three-year period in further education sectors [ 13 ]. Similarly, there has been an increase in the number of students seeking support from university counselling services [ 14 ]. Despite this increase, the capacity of professional services to offer 1 to 1 support to large numbers of students is limited [ 2 ]. Although requests for professional support have increased substantially [ 15 ], only a third of higher education students with mental health problems seek support from counselling services in the UK [ 16 ]. Many students do not seek help due to barriers such as stigma or lack of awareness of services [ 17 – 19 ]. Without formal support or intervention, there is a risk of further deterioration.

Given the increase in mental health problems among students and the surge in demand for formal support [ 1 , 20 , 21 ], reactive services alone cannot effectively support student mental health and wellbeing [ 11 ]. Educational institutions have recognised the need to move beyond traditional forms of support and provide alternative, more accessible interventions aimed at improving mental health and wellbeing. Such institutions have unique opportunities to identify, prevent, and treat mental health problems because they support multiple aspects of students’ lives. Although interventions exist to improve general mental health and wellbeing of students, research on the effectiveness of the various interventions has not been effectively synthesised to date. To address this, we conducted a review of review-level evidence to capture the largest body of existing research on general mental health and wellbeing interventions for college and university students. As there was a substantial body of reviews to be synthesised, the purpose of our review of review-level evidence was to summarise and synthesise this evidence and identify remaining gaps and limitations in the evidence base. This review of reviews aimed to: (i) synthesize the available evidence on interventions to improve college and university students’ mental health and wellbeing; (ii) identify the effectiveness of interventions, and (iii) highlight gaps for future study. The review of reviews explored two questions:

What is the current evidence on interventions to improve the general mental health and wellbeing of college and university students?
What does the evidence tell us about the effectiveness of current interventions and what interventions are likely to be the most effective?

Study identification

Search strategy.

We conducted a search of English language peer-reviewed literature of MEDLINE and MEDLINE In Process and other Non-Indexed Citations (via OVID) ; PsycINFO (via EBSCOhost) ; Social Science Citation Index (via Web of Science) ; and CINAHL Plus (via EBSCOhost) , from 1999 (01/01/1999) to 2020 (31/12/2020), which reflects review-level evidence of interventions before the global COVID-19 pandemic. Reference lists of all eligible reviews were hand-searched in order to identify additional relevant reviews (citation ‘snowballing’). Examples of each search strategy can be found in S1 File .

Inclusion and exclusion criteria

We included all review-level empirical studies (reviews of Randomised Controlled Trials [RCTs] and/or Non-Randomised Studies of Interventions [NRSIs]) involving post-secondary students attending colleges of further education or universities that examined interventions to improve general mental health and wellbeing. Both universal and indicated interventions aimed at improving mental health were included. Universal interventions are aimed at students without any pre-existing mental health problems, whilst indicated interventions are aimed at students who meet criteria for mild to moderate levels of mental health problems or have acknowledged an existing mental health problem, such as depression or anxiety. Thus, studies were included involving both general student populations and students with mental health problems. Studies were excluded if they examined interventions to address specific, pre-existing neurodevelopmental conditions (e.g., attention deficit hyperactivity disorder) or focused on non-health or wellbeing outcomes (e.g., educational performance outcomes). The search was limited to English language literature. Only peer-reviewed reviews published from year 1999 onwards from high-income countries of the Organisation for Economic Co-operation and Development (OECD) were included.

Titles and abstracts of publications were independently screened by two reviewers (JW and AP). Full-text copies of relevant reviews were obtained and assessed independently for inclusion by two reviewers (JW and AP). Any queries or disagreements were resolved by discussion or by recourse to a third reviewer (RC).

Assessment of methodological quality

All reviews that met the inclusion criteria were critically appraised using an amended version of the AMSTAR 2 tool [ 22 ]. The tool was amended to make it sensitive enough to differentiate between the various methodological standards of this particular body of evidence (see S2 File ). The reviews were quality assessed independently by two reviewers. Based on the results of the critical appraisal, reviews were then categorised as: (i) higher methodological quality (score 10 or above); (ii) moderate methodological quality (score 6 to 9); or (iii) lower methodological quality (score 0 to 5). This is a rating/categorisation of relative methodological quality across this body of evidence.

Data extraction and synthesis

The following data was extracted by the first author and checked for accuracy by the second author: aims, primary study design, setting/country, type of intervention, comparator (if any), population, outcomes reported, main findings in relation to the review questions, limitations, and conclusions specified by authors. Key findings from the reviews were tabulated and narratively synthesised [ 23 ]. Findings were grouped by intervention category, with evidence from higher methodological quality reviews reported first and in greater detail [following 24 , 25 ].

The search generated 4,006 records. Title and abstract screening resulted in 44 articles that met the study inclusion criteria. Full-text screening resulted in the inclusion of 27 reviews. Seventeen reviews were excluded as not meeting inclusion criteria (see S3 File ). A summary of our study selection process is presented in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Flow Diagram ( Fig 1 ).

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Characteristics of the included reviews

The characteristics of included reviews are summarised within Table 1 . Information on setting (country) should be provided within Table 1 ; however, very few reviews specified the country in which interventions took place.



Amanvermez et al. (2020)	College students (undergraduate or graduate)	54	Stress management interventions	Anxiety
				Depression
				Psychological distress/stress
Breedvelt et al. (2019)	Tertiary education students (university, college or other postsecondary higher education)	24	Meditation, yoga, and mindfulness	Anxiety
				Depression
				Stress
Davies et al. (2014)	Higher education students (undergraduate and postgraduate students)	17	Computer-delivered and web-based interventions	Anxiety
				Depression
				Psychological distress
				Stress
Dawson et al. (2020)	University students	51	Mindfulness-based interventions	Anxiety
				Depression
				Mindfulness
				Rumination
				Wellbeing
Guo et al. (2020)	College students	14	Exercise interventions	Depression
Halladay et al. (2019)	Post-secondary students including undergraduate, graduate, college and health professional students	49	Mindfulness-based interventions	Anxiety
				Depression
				Perceived stress
Harrer et al. (2018)	Tertiary education students (studying at university, college, or comparable post-secondary higher education)	48	Interventions delivered via technology (a specific delivery method)	Anxiety
				Depression
				Stress
				Wellbeing
Huang et al. (2018)	University or college students	51	Interventions for common mental health problems such as cognitive-behavioural interventions, mindfulness-based interventions, art, exercise, and peer support.	Anxiety
				Depression
Ma et al. (2019)	University students	25	Mindfulness-based interventions	Depressive symptoms
Winzer et al. (2018)	Students in university settings	26	Mental health promoting and mental ill health preventing interventions including CBT, mind-body interventions, and psychoeducation.	Positive mental health
				Mental ill health


Bamber and Morpeth (2019)	College students including undergraduate and postgraduate students	25	Mindfulness-based interventions (MBIs)	Anxiety
Conley et al. (2015)	Higher education students (students receiving postsecondary education in 2- or 4-year colleges and universities, trade and vocational schools, or various graduate and professional programs such as medical or law school).	90	Universal mental health prevention programs: psychoeducational interventions, cognitive-behavioral interventions, relaxation interventions, mindfulness interventions, meditation, social skills and other (e.g., psychodrama, behavioural contracting)	Anxiety
				Depression
				Stress
				General psychological distress
Conley et al. (2016)	Higher education students (college, graduate, professional)	41	Technology-delivered interventions such as cognitive behavioural interventions, mindfulness interventions, psychoeducational interventions, social skills interventions, relaxation interventions, online support group interventions, and other interventions (such as concreteness training intervention, an emotion perception training intervention, and an interactive gaming intervention).	Anxiety
				Depression
				Stress
				General psychological distress
				Health
Conley et al. (2017)	Higher education students (college, university, graduate, postgraduate and professional students)	60	Cognitive-behavioral interventions, relaxation interventions, social skills training, general behavioural interventions, social support interventions, mindfulness interventions, psychoeducational interventions, acceptance and commitment therapy interventions, interpersonal psychotherapy programs, other interventions (resilience training intervention and forgiveness training intervention).	Anxiety
				Depression
				General psychological distress
Cuijpers et al. (2016)	College students	15	Psychological therapy	Depression
Farrer et al. (2013)	Students attending a tertiary institution such as university, college, or a technical and further education (TAFE) institution	28	Technology-based interventions	Anxiety
				Depression
				Stress
Fenton et al. (2018)	Students attending postsecondary institutions	21	Recreation programs such as relaxation (mindfulness or meditation), stress management (yoga or Tai Chi), exercise (pilates), and relationships (animal therapy and expressive writing)	Anxiety
				Depression
				Stress
				Mood
Fernandez et al. (2016)	University students and staff	19	Structural and/or organizational strategies to promote mental health	Global measures of mental wellbeing, mental health, wellness or mental health related quality of life. Condition-specific outcome measures (such as depression or anxiety)
Lattie et al. (2019)	College students	89	Digital mental health interventions	Anxiety
				Depression
				Psychological wellbeing
Rith-Najarian et al. (2019)	University students	62	Prevention programmes	Anxiety
				Depression
				Stress


Bamber and Schneider (2016)	College students including graduates and undergraduates.	57	Mindfulness-based interventions (MBIs)	Anxiety
				Stress
				Mindfulness
Conley (2013)	Higher education students (students receiving postsecondary education in 2- or 4-year colleges and universities, trade and vocational schools, or various graduate and professional programs such as medical or law school).	74	Universal mental health promotion and prevention programs: psychoeducational interventions, cognitive-behavioral interventions, relaxation interventions, mindfulness interventions, meditation, and others (e.g., psychodrama, behavioural contracting, expressive writing and social skills)	Emotional distress (depression, anxiety, stress, general psychological distress or wellbeing)
Howell and Passmore (2018)	University students	5	Acceptance and Commitment Training, a positive psychological intervention	Anxiety
				Depression
				Stress
				Wellbeing
Miller and Chung (2009)	College students	4	Cognitive therapy and education intervention	Depression
Reavley and Jorm (2010)	Higher education student population	Not reported	Prevention and early interventions (e.g., cognitive behavioural interventions, online support group interventions, educational/personalized feedback interventions, social marketing interventions)	Anxiety
				Depression
Regehr (2013)	Undergraduate, graduate, and professional students	24	Cognitive, behavioural and/or mindfulness-based techniques	Anxiety
				Depression
				Psychological stress
Yusufov et al. (2019)	Undergraduate and graduate students	43	Stress reduction interventions (including CBT, coping skills training, MBSR, relaxation training, psychoeducation, and social support)	Anxiety
				Perceived stress

Overview of quality of included reviews

As shown in Table 1 , the methodological quality of the reviews varied. Using the AMSTAR 2 quality assessment tool, eleven reviews were categorised as higher methodological quality, ten reviews were categorised as moderate methodological quality, and seven reviews were categorised as lower methodological quality.

Findings of included reviews

1. mindfulness-based interventions.

A systematic review and meta-analysis of RCTs (rated as higher methodological quality) of different interventions for common mental health problems in 3396 university and college students found that MBIs were effective in reducing both depression and generalized anxiety disorder in the short term but were not durable [ 26 ]. In their meta-analysis, the authors found evidence that MBIs led to statistically significant reductions in depression (pooled effect size: -0.52, 95% CI: -0.88 to -0.16). Art, exercise and peer support interventions (-0.76, 95% CI: -1.19 to -0.32), and cognitive-behavioural related interventions (-0.59, 95% CI: -0.72 to -0.45) led, however, to greater reductions. They found no evidence that the effects of MBIs on depression were sustained over time. They also found evidence that MBIs significantly reduced anxiety (-0.49, 95% CI: -0.84 to -0.15) but, again, other interventions such as peer support and music (-0.84, 95% CI: -1.19 to -0.49) and CBT related interventions (-0.39, 95% CI: -0.55 to -0.22) led to greater reductions.

Another systematic review and meta-analysis of RCTs, which was graded as higher quality, examined the effectiveness of MBIs for mental health outcomes in 4211 post-secondary students [ 27 ]. Halladay and colleagues found evidence that MBIs significantly reduced symptoms of depression (Standardised Mean Difference [SMD] -0.49, 95% CI: -0.68 to -0.30), anxiety (SMD -0.53, 95% CI: -0.78 to -0.29), and perceived stress (SMD -0.39, 95% CI: -0.50 to -0.27) when compared to a passive control group (receiving no intervention/on waiting list). There was, however, no significant difference between the MBI intervention group in levels of depression, anxiety or perceived stress when compared to an active control group receiving health education, relaxation, physical activity, or other approaches including CBT.

Halladay et al. [ 27 ] also analysed the impacts of different lengths of intervention. They found that there was no significant difference in effects, for depressive symptoms, anxiety and stress, between brief and longer interventions. They also analysed the impact of traditional compared to adapted interventions (i.e., Mindfulness-Based Stress Reduction [MBSR] versus Mindfulness-Based Cognitive Therapy [MBCT] versus other or adapted MBIs), and found that MBCT (SMD: -1.21, 95% CI: -1.76 to -0.66) was more effective than both MBSR (SMD = -0.44, 95% CI: -0.72 to -0.16, p = 0.01) and other MBIs (SMD = -0.29, 95% CI: -0.45 to -0.12, p<0.01). When compared to no intervention, MBCT was found to be the most effective type of MBI.

Studies examining whether effects were sustained over time (follow-up studies) were split by type of intervention. Halladay et al. [ 27 ] found that MBCT interventions demonstrated sustained reductions in depression one month after (post-) intervention in two studies with a total of 64 participants (Mean Difference [MD] on the Beck Depression Inventory -5.06, 95% CI: -6.52 to -3.59). Other MBIs did not demonstrate sustained reductions in depression at one month or 2–3 months post-intervention in three studies (with a total of 374 participants), although reductions in depression were found at 4–5 months post-intervention in two studies (with a total of 191 participants; SMD -0.43, 95% CI: -0.72 to -0.14). MBCT interventions also demonstrated sustained reductions in anxiety symptoms at both 1-month in two studies (with a total of 66 participants; MD on Beck Anxiety Inventory [BAI] -7.12, 95% CI: -8.23 to -5.97) and 6 months in two studies post-intervention (a total of 65 participants; MD on BAI -5.95, 95% CI: -10.78 to -1.13). Other MBIs demonstrated significant reductions 1-month post-intervention in one study using a different measure (with a total of 33 participants; MD Hamilton Anxiety Scale -9.50, CI: -17.27 to -1.73).

A systematic review and meta-analysis of RCTs (rated as higher methodological quality) of MBIs for mental and physical health in university students found that MBIs were effective in reducing distress, depression and state anxiety when compared to passive controls [ 28 ]. In their meta-analysis, the authors found evidence that MBIs led to significantly significant reductions in distress (SMD -0.47, 95% CI: -0.60 to -0.34), depression (SMD -0.40, 95% CI -0.57 to -0.24), and state anxiety (MD -3.18, 95% CI -5.51 to -0.85) when compared to a passive control (receiving no intervention/waiting list). MBIs led to improvements in wellbeing (SMD 0.35, 95% CI 0.21 to 0.50) when compared to a passive control. Effects of MBIs lasted beyond three months for distress (SMD -0.32, 95% CI -0.50 to -0.13). When compared with active control groups, MBIs significantly reduced distress (SMD -0.37, 95% CI -0.56 to -0.18) and state anxiety (MD -5.95, 95% CI -9.49 to -2.41), but not depression (SMD -0.19, 95% CI -0.43 to 0.05) and wellbeing (SMD -0.08, 95% CI -0.43 to 0.27).

Ma and colleagues conducted a meta-analytic review of RCTs (rated as higher methodological quality) of MBIs [ 29 ]. They found that MBIs were effective in reducing depressive symptoms in university students (effect size: 0.52, 95% CI 0.39 to 0.65). The authors found evidence that universal MBIs (effect size: 0.41, 95% CI 0.28 to 0.55), selective MBIs (effect size: 0.44, 95% CI 0.18 to 0.70), and indicated MBIs (effect size: 0.88, 95% CI 0.64 to 1.11) led to significant reductions in depressive symptoms.

Bamber and Morpeth’s [ 30 ] review, graded as moderate quality, included a meta-analysis of evidence on the effects of MBIs on anxiety in 1492 college students. A number of primary study designs were included: studies with two-group comparisons (e.g., MBI versus control) and studies with pre-test and post-test analysis of MBI (one-group MBI). They found MBIs significantly reduced anxiety, compared to no-treatment controls (ES 0.56, 95% CI: 0.42 to 0.70, p<0.001). MBI groups’ pre and post intervention comparisons showed large significant reductions in anxiety. There was, however, a small but significant reduction in control group anxiety pre/post comparisons. They also found that higher numbers of sessions (number not specified) increased the effects of MBIs (p = 0.01), with more sessions leading to greater reductions in anxiety.

Fenton et al. [ 31 ] conducted a moderate quality systematic review of evidence on the impacts of different recreation programmes, including MBIs, on mental health outcomes in post-secondary students in North America. Randomised controlled trials, non-randomised with control, and non-randomised no control studies were all included. They found that mindfulness interventions reduced depression, anxiety, stress, and negative mood.

Conley et al. [ 32 ] conducted a moderate quality review and meta-analysis of evidence on the impact of universal mental health prevention programmes including MBIs for higher education students. The review included two study designs: quasi-experimental and random designs. They found that skill-training programmes with supervised practice were significantly more effective than both skill-training programmes without supervised practice and psychoeducation in reducing depression, anxiety, stress, and general psychological distress. Conley and colleagues found that relaxation interventions demonstrated the most overall benefit in terms of effectiveness, followed by mindfulness interventions and cognitive-behavioural interventions that did not differ from each other.

Regehr et al. [ 33 ] conducted a review and meta-analysis (rated as lower methodological quality) of evidence on the effectiveness of preventative interventions in reducing mental health outcomes in 1431 university students, including randomised and parallel cohort designs. Regehr and colleagues found that mindfulness-based interventions focussing on stress reduction significantly reduced symptoms of anxiety and depression. In their meta-analysis, mindfulness-based interventions were assessed for their impact on anxiety. They found that mindfulness-based interventions led to significant improvements, compared to control groups (SMD -0.73, 95% CI: -1.00 to -0.45).

Conley et al. [ 34 ] reviewed evidence on the effectiveness of 83 (controlled) universal promotion and prevention interventions (rated as lower methodological quality). These authors explored whether skill-orientated interventions were more effective with or without supervised skills practice. The authors also examined the effectiveness of different strategies employed in skill-oriented interventions such as cognitive-behavioural interventions, mindfulness interventions, relaxation interventions, and meditation in quasi-experimental and random designs. They found that skill-oriented interventions were more effective with supervised practice, and that supervised skills practice interventions reduced depression, anxiety, and stress. They found mindfulness interventions to be the most effective form among the skill-oriented programmes containing supervised practice. Mindfulness interventions were significantly more effective in comparison to other interventions (the proportion of all significant post-intervention outcomes combined was 78.8% for mindfulness, in comparison to psychoeducation [12.5%], cognitive behavioural [43.4%], relaxation [27.1%], meditation [13%], and other interventions [21.9%]).

Bamber and Schneider [ 35 ] explored the effects of MBIs such as Mindfulness Based Stress Reduction (MBSR) and Mindfulness Meditation (MM) on mental health outcomes including anxiety and stress in college students (rated as lower methodological quality). Both MBSR and MM were found to significantly reduce symptoms of anxiety and stress.

2. Psychological interventions (e.g., cognitive-behavioural interventions)

Huang et al. [ 26 ] conducted a systematic review and meta-analysis of RCT evidence (rated as higher methodological quality) on the effectiveness of interventions for common mental health difficulties in 3396 university and college students. They found that cognitive behavioural therapy (CBT) had significant positive effects on depression and generalized anxiety disorder. Meta-analysis results showed that cognitive-behavioural-related interventions led to greater reductions in depression (-0.59, 95% CI: -0.72 to -0.45) than mindfulness-based interventions (-0.52, 95% CI: -0.88 to -0.16) and attention/perception modification (-0.46, 95% CI: -1.06 to 0.13). Other interventions (art, exercise, and peer support) led to a greater reduction in depression (-0.76, 95% CI: -1.19 to -0.32). The follow-up (pooled) effect size of cognitive-behavioural related interventions (-0.75, 95% CI: -0.95 to -0.54) had a greater significant effect (the follow-up ranged from 2 weeks to 7 months post intervention).

CBT related interventions were associated with significant (pooled) reductions in anxiety (-0.39, 95% CI: -0.55 to -0.22). The pooled effect of other interventions (peer support and music; -0.84, 95% CI: -1.19 to -0.49) and mindfulness (-0.49, 95% CI: -0.84 to -0.15) for generalised anxiety disorder were associated with greater reductions in anxiety compared to CBT.

Winzer et al. [ 36 ] conducted a systematic review and meta-analysis (rated as higher methodological quality) to assess whether the effects of mental health promotion and mental ill-health prevention interventions were sustained over time. They found that CBT-related interventions led to significant (pooled) effects for 3–6 month and 13–18 month follow-ups in sub-group analyses for combined mental ill-health outcomes (-0.40, 95% CI-0.64 to 0.16; -0.30, 95% CI: -0.51 to 0.08, respectively). They also analysed impacts on combined positive mental health and academic performance at 3–6 months, and found that the interventions had significant effects (pooled effect size: 0.52, 95% CI: 0.06 to 0.98).

Cuijpers et al. [ 37 ] carried out a meta-analysis of evidence (rated as moderate methodological quality) that examined the effectiveness of different forms of psychological treatment, such as CBT and behavioural activation therapy (BAT), for addressing symptoms of depression in 997 college students. The review found a large overall (pooled) effect of the therapies versus controls (g = 0.89, 95% CI: 0.66 to 1.11). It also found that individual therapy was significantly more effective than group therapy (p = 0.003) but that type of treatment (CBT, BAT, or other) was not significantly associated with the size of effect.

In their review and meta-analysis (rated as moderate methodological quality) of the impact of universal mental health prevention programmes for higher education students, Conley et al. [ 32 ] found that skill-training programmes with supervised practice such as cognitive-behavioural interventions, mindfulness interventions, relaxation interventions, and meditation significantly reduced depression, anxiety, stress, and general psychological distress. Programmes without supervised practice were significantly less effective. Comparing the effectiveness of different interventions overall, they also found that relaxation interventions were the most effective (mean effect size: 0.55, 95% CI: 0.41 to 0.68), followed by CBT interventions (0.49, CI: 0.40 to 0.58), MBIs (0.34, CI: 0.19 to 0.49), meditation (0.25, CI: 0.02 to 0.53), and then psychoeducational interventions (0.13: CI: 0.06 to 0.21).

In their review and meta-analysis of evidence (rated as lower methodological quality) on the effectiveness of preventative interventions in reducing mental health outcomes in university students, Regehr et al. [ 33 ] found that cognitive and behavioural interventions focusing on stress reduction significantly reduced symptoms of anxiety and depression. In their meta-analysis, cognitive-behavioural interventions were assessed for their impact on anxiety. They found that cognitive-behavioural interventions (SDM -0.77, 95% CI: -0.97 to -0.57) led to significant improvement, compared to control groups.

Howell and Passmore [ 38 ] conducted a review and (‘initial’) meta-analysis (rated as lower methodological quality) on the impacts of ACT interventions for university student wellbeing (N = 585), including randomized controlled experimental designs. Their meta-analysis showed a small significant (pooled) effect on wellbeing (d = 0.29, 95% CI: 0.11 to 0.47, p = 0.008) when assessed with the Wellbeing Manifestations Measure Scale. ACT interventions were also found to reduce depression, anxiety, and stress.

Conley et al. [ 34 ] examined the effectiveness of different strategies employed in skill-oriented interventions such as cognitive-behavioural interventions, mindfulness interventions, relaxation interventions, and meditation (rated as lower methodological quality). Conley and colleagues found that interventions with supervised skills practice reduced depression, anxiety, and stress. Mindfulness interventions were found to be the most effective (78.8%) form of intervention among the skill-oriented programmes containing supervised practice, followed by cognitive-behavioural interventions (55.8%) which performed significantly better than relaxation (28.9%, OR = 3.11, p<0.01) and meditation (19.4%, OR = 5.26, p<0.001) interventions.

One review graded as lower quality reviewed evidence on the prevention and early intervention for mental health problems in higher education students found that CBT approaches are effective for prevention and early intervention [ 39 ]. The authors also reported that these approaches are effective for at least some months following the CBT intervention. The authors did not report the primary study designs they included.

In a literature review of studies of depression and treatment outcomes among US college students, graded as lower quality, brief individual cognitive therapy was found to be effective at reducing mild to moderate depressive symptoms [ 40 ]. This finding was based on only one RCT, however.

3. Psychoeducational interventions

In their review of RCTs (graded as higher methodological quality), Winzer et al. [ 36 ] explored whether the effects of mental health interventions (e.g., psychoeducational interventions) for students in higher education were sustainable over time. They did not find significant (pooled) effects on combined mental ill health outcomes at 3–6 months, 7–12 months, or 13–18 month follow-ups. They reported no superior effect of psychoeducational intervention. The 3–6 month and 13–18 month follow-up were, however, both only based on one study.

When Conley et al. [ 32 ] reviewed evidence on the impact of universal prevention programmes for higher education students, they found that skill-training programmes with supervised practice (0.45, CI: 0.39 to 0.52) were significantly more effective than both psychoeducation (information only) interventions (0.13, CI: 0.06 to 0.21) and skill-training programmes without supervised practice (0.11, CI: -0.01 to 0.22) in reducing depression, anxiety, stress, and general psychological distress (rated as moderate methodological quality). Psychoeducational interventions yielded significant effects for several mental health related outcomes including anxiety, stress, and general psychological distress (ESs>0.13). However, these interventions did not yield significant effects for depression, social and emotional skills, or interpersonal relationships. Psychoeducational interventions were found to be less effective than relaxation interventions, cognitive-behavioural interventions, mindfulness interventions, and meditation. Although interventions with supervised skills practice produced a significant positive effect averaged across all types of outcomes at follow-up (0.28, CI: 0.16 to 0.40), psychoeducational interventions did not.

In their 2013 review (graded as lower methodological quality), Conley et al. [ 34 ] explored whether skill-oriented interventions that included supervised skills were more effective than psychoeducational programmes. They found that psychoeducational programmes were not as effective as preventive interventions for higher education students.

3a. Educational/personalised feedback interventions

In their review (rated as lower methodological quality) of prevention and early intervention for mental health issues in higher education students, Reavely and Jorm [ 39 ] reported mixed findings on the effectiveness of educational/personalised feedback interventions.

Miller and Chung [ 40 ] explored treatment for depression and found that an intervention using personalised mailed feedback was effective at reducing symptoms of depression (rated as lower methodological quality). This finding was only based on one study, however.

4. Recreation programmes

In their review of RCTs (rated as higher methodological quality) on the effectiveness of interventions for common mental health difficulties, Huang et al. [ 26 ] found that recreational interventions including exercise, art and peer support were effective treatments for depression and anxiety. Although both CBT and MBIs were found to be effective, other interventions (i.e., art, exercise, and peer support) showed larger effects for both depression and generalized anxiety disorder.

When exploring the combined effects of yoga, meditation, and mindfulness on depression, anxiety, and stress in 1373 tertiary education students, Breedvelt et al. [ 41 ] found moderate positive effects for yoga, meditation, and mindfulness on symptoms of depression, anxiety, and stress (rated as higher methodological quality). They found no significant differences in subgroup analysis when they compared the effectiveness of yoga, mindfulness meditation, and MBSR. A small number of the included studies (N = 6) provided long-term follow-up data which ranged from 1 to 24 months. The (pooled) effect at follow-up was found to be small to medium (g = 0.39, 95% CI: 0.17 to 0.61).

A network of meta-analysis of RCTs (rated as higher methodological quality) of exercise interventions for depression in 2010 college students found that exercise interventions were effective in reducing depression [ 42 ]. When compared with usual care, Tai Chi (SMD = -11, 95% CI -16 to -6), yoga (SMD = -9.1, 95% CI -14 to -4), dance (SMD = -5.5, 95% CI -11 to -0.39) and running (-6, 95% CI -10 to -1.6) interventions were effective in reducing depressive symptoms. The authors found Tai Chi to be the most effective exercise intervention followed by yoga.

Fenton et al. [ 31 ] reviewed evidence on the impacts of recreation programmes such as mindfulness, meditation, Tai Chi, yoga, exercise, and animal therapy on mental health outcomes in post-secondary students in North America (rated as moderate methodological quality). They included a number of different primary study designs: non-randomised with control, non-randomised no control, and RCTs. They found that mindfulness, yoga, meditation, exercise, and animal therapy all reduced depression, anxiety, stress, and negative mood.

The review of evidence (rated as moderate methodological quality) on the impact of universal mental health prevention programmes by Conley et al. [ 32 ] found that meditation interventions were more effective than psychoeducational interventions but less effective than relaxation, cognitive-behavioural and mindfulness interventions.

The review (rated as lower methodological quality) by Conley et al. [ 34 ] also examined the relative effectiveness of different approaches used in skill-oriented interventions, including cognitive-behavioural, mindfulness, relaxation, and meditation. They reported that mindfulness interventions were more effective than cognitive-behavioural interventions, relaxation interventions, and meditation; and found that cognitive-behavioural interventions were more effective than both meditation and relaxation interventions which did not differ significantly from each other.

5. Relaxation interventions

In their review of universal mental health prevention programmes for higher education students (rated as moderate methodological quality), Conley et al. [ 32 ] found relaxation interventions to be the most effective. In contrast, Conley et al [ 34 ] examined the relative effectiveness of different strategies used in skill-oriented interventions including cognitive-behavioural, mindfulness, relaxation and meditation, and found that mindfulness interventions and cognitive-behavioural interventions were more effective than relaxation interventions, and that meditation and relaxation interventions did not differ significantly from each other (rated as lower methodological quality).

6. Setting-based interventions

Fernandez et al. [ 43 ] conducted a systematic review of evidence (rated as moderate methodological quality) on the mental wellbeing impacts of setting-based interventions for university students. They included experimental (e.g., RCT) and observational (e.g., controlled trial without randomisation, pre-post/before and after, and time series) study designs. Academic-based interventions, to enhance learning and teaching, were found to significantly improve mental wellbeing.

7. Stress management/reduction interventions

A systematic review and meta-analysis (rated as higher methodological quality) of stress management interventions for college students found that stress reduction interventions were effective in reducing distress [ 44 ]. In their meta-analysis, the authors found evidence that stress management interventions were effective in reducing stress (g = 0.61, 95% CI 0.30 to 0.93), anxiety (g = 0.52, 95% CI 0.25 to 0.78), and depression (g = 0.46, 95% CI 0.16 to 0.77) for students with high stress levels. The authors found evidence that the effects of stress management interventions were sustained over time. The effect of stress management programmes for students with high stress levels remained up to the 12-month follow-up (g = 0.40, 95% CI 0.21 to 0.60). Stress management interventions were also found to be effective in reducing depression (g = 0.36, 95% CI 0.21 to 0.51), anxiety (g = 0.52, 95% CI 0.36 to 0.68), and stress (g = 0.58, 95% CI 0.44 to 0.73) in an unselected college student population.

Yusufov et al. [ 45 ] conducted a meta-analysis (rated as lower methodological quality) of evidence on the impacts of stress reduction interventions. In their meta-analysis of stress reduction interventions, the authors found that stress reduction interventions were effective in reducing anxiety and stress.

Interventions delivered via technology

Different categories of interventions (e.g., CBT) can be delivered through different means. Harrer et al. [ 46 ] systematically reviewed and performed a meta-analysis of evidence (rated as higher methodological quality) on the impacts of internet interventions on symptoms of common mental health problems, wellbeing and functional outcomes among university students. Small effects from internet interventions were found on depression ( g = 0.18, 95% CI: 0.08 to 0.27), anxiety ( g = 0.27, 95% CI: 0.13 to 0.40), and stress ( g = 0.20, 95% CI: 0.02 to 0.38). There were, however, no significant effects on wellbeing. The effects were higher for interventions that were based on CBT principles.

Similarly, Davies et al. [ 47 ] reviewed evidence on the effectiveness of computer-delivered and web-based interventions in improving depression, anxiety, and psychological wellbeing in 1795 higher education students (rated as higher methodological quality). When compared to an inactive control group (receiving no-treatment or on a waiting list), sensitivity meta-analyses showed that interventions significantly improved anxiety (Pooled SMD −0.56; 95% CI: −0.77 to −0.35, p <0.001), depression (SMD −0.43; 95% CI: −0.63 to −0.22, p <0.001), and stress (SMD −0.73; 95% CI: −1.27 to −0.19, p = 0.008). The sensitivity analyses showed no significant effects for anxiety or depression, however, when compared to the active control group (in which participants received materials designed to mimic the time and attention received in the intervention group). Sensitivity analyses also showed no significant difference between the computer and web-based intervention for anxiety or depression when compared to comparison interventions that included a face-to-face version of the intervention, a web-based stress management intervention, another computer-based CBT program, and an online support group.

Lattie et al. [ 48 ] conducted a systematic review of evidence (rated as moderate methodological quality) on the effectiveness of digital mental health interventions on mental health outcomes in college students. All study designs were included. They found that digital mental health interventions can be effective for improving depression, anxiety, and psychological wellbeing among college students.

Conley et al. [ 49 ] conducted a meta-analytic review of evidence on the impact of universal and indicated technology-delivered interventions (TDIs) targeting mental health outcomes in 4763 higher education students, including randomized and quasi-experimental study designs (rated as moderate methodological quality). Universal interventions are aimed at students without any pre-existing mental health problems whereas indicated interventions are aimed at students who meet criteria for mild to moderate levels of mental health problems or have acknowledged an existing mental health problem such as depression or anxiety. They found that both universal and indicated TDIs were significantly effective in reducing symptoms of depression, anxiety, and stress. Indicated interventions produced higher overall (mean) improvements (0.37, CI: 0.27 to 0.47, p<0.001) than universal interventions (0.19, CI: 0.11 to 0.28, p<0.001). Both universal (0.21, CI: 0.11 to 0.31, p<0.001) and indicated (0.39, CI: 0.29 to 0.50, p<0.001) skill-training interventions led to significant improvements. Interventions without skill training were, however, only significant among indicated interventions (0.25, CI: 0.01 to 0.49, p = 0.042). Three of the 22 universal interventions, and eight of the 26 indicated interventions, assessed outcomes at follow-up (ranging between 13 to 52 weeks, and 2 to 26 weeks, respectively). Both universal and indicated interventions sustained significant positive effects on mental health outcomes at follow up (0.30, CI: 0.06 to 0.54, p = 0.015; 0.49, CI: 0.31 to 0.67, p<0.001, respectively).

Farrer et al. [ 50 ] systematically reviewed evidence on the effectiveness of technology-based interventions for mental health outcomes in tertiary students (rated as moderate methodological quality). They included both randomized controlled trials and randomized trials (equivalence trials). In interventions targeting both depression and anxiety, they found that technology-based CBT was effective in reducing anxiety and depression, although to a lesser degree than traditional therapy with human contact.

Other evidence

Conley et al. [ 51 ] conducted a meta-analysis of evidence (rated as moderate methodological quality) on the impacts of indicated prevention programmes for various forms of early-identified mental health problems such as sub-threshold depression and anxiety symptoms. Although they report significant effects, they provided insufficient information on the type of interventions to be categorised.

Rith-Najarian et al. [ 52 ] conducted a systematic review of evidence (rated as moderate methodological quality) on the effectiveness of preventative interventions in reducing depression, anxiety, and stress in university students. Rith-Najarian and colleagues found that prevention programmes reduced symptoms. The average effect sizes for preventative programmes were moderate (g = 0.65, 95% CI 0.57 to 0.73) regardless of delivery format or prevention level. According to delivery format, the effect sizes were similar for group (g = 0.69, 95% CI 0.58 to 0.81), self-administered (g = 0.65, 95% CI 0.50 to 0.81), and online/computer-delivered (0.52, 95% CI 0.41 to 0.63). According to prevention level, effect sizes differed for universal (0.69, 95% CI 0.55 to 0.83), selective (0.73, 95% CI 0.59 to 0.87), and indicated (0.53, 95% CI 0.44 to 0.63).

This review of reviews identified a range of interventions for student mental health and wellbeing, including mindfulness-based interventions (MBIs), psychological interventions (e.g., cognitive-behavioural therapy; CBT), psychoeducation interventions, recreation programmes, relaxation interventions, and setting-based interventions (e.g., academic and curriculum-based strategies). There was evidence that MBIs, CBT, and interventions delivered via technology were effective when compared to a passive control. There is some evidence to suggest that the effects of CBT-related interventions are sustained over time. The effects of interventions delivered via technology were found to be higher for interventions that were based on CBT principles in one higher quality review. Although technology-based CBT was effective in reducing depression and anxiety, traditional therapy with human contact was found to be more effective.

Moving beyond CBT, recreation programmes were also found to be effective. In fact, while both CBT and MBIs were found to be effective, other interventions (i.e., art, exercise, and peer support) were found to be more effective in one higher quality review. The review-level evidence suggests that psychoeducation interventions are not as effective as other interventions such as MBIs, cognitive-behavioural interventions, relaxation interventions, and meditation. The effects of psychoeducation interventions do not appear to sustain over time.

The review of reviews only located single reviews of evidence on acceptance and commitment training interventions [ 38 ] and setting-based interventions such as developing curricula to support wellbeing [ 43 ]. Although these interventions were shown to be effective, it should be noted that some of these reviews only included a small number of studies with small sample sizes [e.g., 38 ], and their findings should be viewed with some caution.

Limitations in the review of reviews

This is the first review of reviews to synthesise evidence on interventions to improve college and university students’ mental health and wellbeing. Despite every effort to gather the best evidence available, the review had several limitations. First, as our searches were limited to English language literature, we did not include evidence from studies reported in other languages. Identification and synthesis of evidence published in other languages is therefore desirable, although this would require sophisticated, technical, multilingual skills during study identification, appraisal and synthesis. Second, the searches were limited to a 21-year date range (1999 to 2020). Although this date range was deemed appropriate as we aimed to identify interventions that are most relevant to modern student populations and contexts, it should be noted that this review of review-level evidence reflects the time period before the global COVID-19 pandemic. Last, scarcity of high quality evidence syntheses on interventions to improve student mental health and wellbeing led to our decision to analyse data from all 27 reviews. This decision impacts on the quality of evidence synthesised. Despite limitations in the methodological strength of some evidence, the search identified a substantial group of higher methodological quality reviews and a large number of systematic reviews and meta-analyses. It should, therefore, be used to inform policies and practice alongside other considerations.

Gaps and limitations in the body of evidence

Although there was a large body of evidence on specific interventions such as mindfulness and cognitive-behavioural interventions, review-level evidence was limited in relation to other interventions such as setting-based interventions and acceptance and commitment training. Therefore, further primary studies examining the efficacy of setting-based interventions and acceptance and commitment training for students are required. Also, as there was a notable gap in the existing body of review-level evidence on interventions for students attending colleges in UK settings, a systematic review should be conducted in this area to identify primary level studies.

There are several limitations in the body of evidence. First, a number of the included reviews did not specify country and setting of the underlying evidence. It is likely that a substantial portion of the evidence is from US institutions, as this is typical for most evidence on health and wellbeing interventions. Another important limitation was that the included reviews only reported findings on beneficial effects of interventions. The underlying primary studies may have only attempted to assess efficacy and not the potential broader impacts of interventions. This is an important omission in the primary literature or the reviews. Interventions aiming for beneficial outcomes can often lead to unintended, adverse impacts for some participants. Primary and secondary research (including reviews) should attempt to identify adverse impacts so they can be eliminated or ameliorated, in accordance with the ‘first do no harm’ principle. A further limitation was that many of the included reviews did not consider the distribution of impacts from interventions across different population subgroups such as socio-economic status, age, gender, disability, and sexuality. As it is entirely possible that some interventions may work better for some students than for others, an evidence base that is more nuanced in terms of individual differences and differential impacts could underpin the tailoring of interventions to suit particular student characteristics leading, in time, to more suitable and effective interventions associated with nuanced, evidence-based delivery strategies. In addition to this, some of the included studies were lacking in detail on the nature of control groups. Greater detail on the nature of control groups should be provided in future studies. Last, few studies examined duration of effects over time. Future studies should routinely assess the duration of effects over time.

Implications

In light of the above, future primary and review-level research should carefully consider the distribution of impacts of interventions by population sub-groups, including socioeconomic, gender, ethnic, age, sexuality, and disability groups [ 53 ]. Intersectionalities between these population characteristics should also be considered. Cultural and faith backgrounds may also be important factors to consider. Future research should also explore latency and durability of effects overtime as some interventions, such as CBT, showed promise of effects sustained post intervention. This could include exploring further and longer pre and post intervention studies and studies exploring the impacts of top-up sessions. Moving beyond CBT, there are wider social determinant interventions which may be particularly important in this context such as debt or financial management, quality of student accommodation and housing, the competitive versus cooperative ethos of the learning environment, and sense of belonging to the student body and to the institution [ 54 ]. With the increasing prevalence of student mental health issues pointing to the influence of these wider determinants, it is clear that primary research in this area that takes note of the distribution of impacts is needed.

The review-of-reviews located a large body of evidence on specific interventions such as mindfulness and cognitive-behavioural interventions. The evidence suggests that these interventions can effectively reduce the common mental health difficulties of students. Evidence on other interventions was, however, limited. For example, although some work has begun developing curricula to support wellbeing, review-level evidence on organisational and structural interventions was limited. Thus, it is not currently possible to determine and rank which interventions work best, where and for whom, as this would require a larger body of evidence on certain intervention types, and comparative studies or reviews. Most of the included reviews did not consider the distribution of the intervention impacts (inequalities) for population subgroups such as age, gender, ethnicity, and socio-economic status. Noting the gaps and limitations in the review-level evidence previously identified, universities should select interventions based on the best available evidence, taking into consideration: the methodological strength of the underlying evidence, and the evidence on effectiveness. A good quality primary evidence-base examining these areas needs to be developed and then systematically reviewed before confident conclusions can be drawn about what works best to sustain positive mental health and wellbeing in today’s diverse and growing post-secondary student population. The need for effective support in this area can only have grown following the global COVID-19 pandemic and the associated disruption to teaching, learning, and university and college life. Following the disruption to teaching and learning, together with other stressors placed on young people from the COVID-19 pandemic, there is an imperative need to support students’ mental health and wellbeing. Future research in this area should elucidate the unique challenges that COVID-19 has presented for students to inform and tailor interventions for this generation and future cohorts facing disruptions to their teaching and learning experience.

Supporting information

S1 checklist, acknowledgments.

We would like to thank the review advisory group for their support and the What Works Centre for Wellbeing.

Funding Statement

The What Works Centre for Wellbeing Communities of Place evidence programme is funded by the Economic and Social Research Council (ESRC) and partners. The funders had no role in data collection and analysis, decision to publish, or preparation of the manuscript.

Data Availability

Surviving Medical School During a Pandemic: Experiences of New York Medical Students During the Height of SARS-CoV-2

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Background The COVID-19 pandemic dramatically altered the landscape of medical education. While patients overwhelmed hospital systems, lockdowns and social distancing recommendations took priority, and medical education was pushed online. Early in 2020, New York State (NYS) was hit especially hard by COVID-19.

Objective This study sought to understand the effect of the COVID-19 pandemic on medical students well-being and education.

Methods NYS medical students responded to a six-question survey during April and May 2020. Questions assessed self-reported changes in stress levels, academic performance, and board preparation efforts. Open-ended data was analyzed using a modified grounded theory approach.

Results 488 responses across 11 medical schools were included (response rate of 5.8%). Major themes included: standardized test-related stressors (23%), study-related changes (19%), education and training concerns (17%), financial stressors (12%), and additional family obligations (12%).

Second year students reported more stress/anxiety than students in other years (95.9%, p -value< 0.00001). Reported stress/anxiety, effects on exam preparation, and anticipated academic effect varied by geographics.

Conclusions While all NYS medical students reported being greatly affected, those closest to the NY City pandemic epi-center and closest to taking the Step 1 exam were the most distressed. Lack of flexibility of the medical education system during this public health emergency contributed to worsened student well-being. It is time to make plans for supporting the long-term mental health needs of these physicians-in-training and to examine ways the academic medical community can better adapt to the needs of students affected by a large public health emergency in the future.

Competing Interest Statement

The authors have declared no competing interest.

Statements and Declarations:

Funding: No funding was received for conducting this study.

Competing Interests: The authors have no relevant financial or non-financial interests to disclose.

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Improving Health

Mental Health in Schools

Mental health in schools, where we stand.

NAMI believes that public policies and practices should promote greater awareness and early identification of mental health conditions. NAMI supports public policies and laws that enable all schools, public and private, to increase access to appropriate mental health services.

Why We Care

One in six U.S. youth aged 6-17 experience a mental health disorder each year, and half of all mental health conditions begin by age 14. Attention-deficit/hyperactivity disorder (ADHD), behavior problems, anxiety, and depression are the most commonly diagnosed mental disorders in children. Yet, about half of youth with mental health conditions received any kind of treatment in the past year.

Undiagnosed, untreated or inadequately treated mental illnesses can significantly interfere with a student’s ability to learn, grow and develop. Since children spend much of their productive time in educational settings, schools offer a unique opportunity for early identification, prevention, and interventions that serve students where they already are. Youth are almost as likely to receive mental health services in an education setting as they are to receive treatment from a specialty mental health provider — in 2019, 15% of adolescents aged 12-17 reported receiving mental health services at school, compared to 17% who saw a specialty provider.

School-based mental health services are delivered by trained mental health professionals who are employed by schools, such as school psychologists, school counselors, school social workers, and school nurses. By removing barriers such as transportation, scheduling conflicts and stigma, school-based mental health services can help students access needed services during the school-day. Children and youth with more serious mental health needs may require school-linked mental health services that connect youth and families to more intensive resources in the community.

Early identification and effective treatment for children and their families can make a difference in the lives of children with mental health conditions. We must take steps that enable all schools to increase access to appropriate mental health services. Policies should also consider reducing barriers to delivering mental health services in schools including difficulty with reimbursement, scaling effective treatments, and equitable access.

How We Talk About It

Many mental health conditions first appear in youth and young adults, with 50% of all conditions beginning by age 14 and 75% by age 24.
One in six youth have a mental health condition, like anxiety or depression, but only half receive any mental health services.
Early treatment is effective and can help young people stay in school and on track to achieving their life goals. In fact, the earlier the treatment, the better the outcomes and lower the costs.
Unfortunately, far too often, there are long delays before they children and youth get the help they need.
Delays in treatment lead to worsened conditions that are harder — and costlier — to treat.
For people between the ages of 15-40 years experiencing symptoms of psychosis, there is an average delay of 74 weeks (nearly 1.5 years) before getting treatment.
Untreated or inadequately treated mental illness can lead to high rates of school dropout, unemployment, substance use, arrest, incarceration and early death.
In fact, suicide is the second leading cause of death for youth ages 10-34.
Schools can play an important role in helping children and youth get help early. School staff — and students — can learn to identify the warning signs of an emerging mental health condition and how to connect someone to care.
Schools also play a vital role in providing or connecting children, youth, and families to services. School-based mental health services bring trained mental health professionals into schools and school-linked mental health services connect youth and families to more intensive resources in the community.
School-based and school-linked mental health services reduce barriers to youth and families getting needed treatment and supports, especially for communities of color and other underserved communities.
When we invest in children’s mental health to make sure they can get the right care at the right time, we improve the lives of children, youth and families — and our communities.

What We’ve Done

NAMI letter of support for the Mental Health Services for Students Act (H.R. 1109), introduced by Reps. Napolitano and Katko
NAMI letter of support for Mental Health Services for Students Act of 2019 (S. 1122) introduced by Senator Tina Smith
NAMI Ending the Silence Presentation Program

Know the warning signs of mental illness

Learn more about common mental health conditions

NAMI HelpLine is available M-F, 10 a.m. – 10 p.m. ET. Call 800-950-6264 , text “helpline” to 62640 , or chat online. In a crisis, call or text 988 (24/7).

Student Resources

Student mental health: Creating a supportive academic environment

Why is mental health important for students?

June 21, 2024 •

6 min reading

Mental health is an increasingly prevalent topic of conversation these days, with higher rates of anxiety, depression, and distress reported by Gen Zers than any other age group and the social stigma around it lifting. For young people in their study years in particular, mental health and well-being is critical at a potentially stressful time of life

However, people remember their university years as the best days of their life. Did they forget about all the hours spent studying? Didn’t they ever wake up from a nightmare in which they missed a deadline? And what about the stress before every single exam?

It is a well-known psychological phenomenon that humans tend to remember positive experiences more vividly than negative ones. This selective memory helps maintain mental well-being, allowing individuals to view their past through a nostalgic lens.

That said, the importance of well-being during university years cannot be overstated , as this is a crucial period of personal development.

How universities can support students

Ensuring the well-being of students involves addressing three key factors in priority:

Academic support,
Mental health,
Balanced lifestyle.

Universities must provide resources such as counseling, stress management workshops, social activities, and opportunities for physical activity to help students cope with the pressures of their studies.

Additionally, fostering a supportive community where students feel connected and valued can signiﬁcantly enhance their overall experience. By taking these factors into account, institutions can create an environment where students not only thrive academically but also enjoy a healthy and fulﬁlling life.

What is the healthy campus program?

The Healthy Campus by FISU (Fédération Internationale des Sports Universitaires) program certiﬁes universities that focus efforts on increasing their community’s well-being and demonstrate a comprehensive commitment to the quality of life of their community.

It is the perfect way to compare the eﬀorts deployed with an evidence-based framework, allowing encouragement for cross-cutting collaborations and gradually involving more departments and resources in the project.

Launched in May 2020, this program evaluates institutions based on an extensive set of criteria to ensure a holistic approach to health and wellness. The certiﬁcation process involves meeting over 100 speciﬁc criteria across several key areas:

1. Mental health support

Evaluates the availability and eﬀectiveness of mental health services, such as counseling centers, stress management programs, and mental health awareness initiatives.

2. Physical activity

Assesses the quality and accessibility of sports facilities, the variety of physical activities oﬀered, and programs designed to encourage regular exercise.

3. Nutrition

Looks at the availability of healthy food options, nutrition education programs, and initiatives to promote balanced eating habits on campus.

4. Social integration

Considers efforts to foster an inclusive and supportive campus environment, including social activities, community-building events, and support networks for students.

5. Health services

Examines the comprehensiveness of healthcare services provided, including medical care, preventive health programs, and collaborations with external health providers.

6. Environmental sustainability

Reviews initiatives aimed at creating a sustainable and eco-friendly campus, promoting practices that reduce environmental impact.

7. Personal development

Evaluates programs and resources that support the personal growth and development of students, such as workshops, career counseling, and life skills training.

EHL Hospitality Business School, FISU accredited

By meeting these extensive criteria, universities awarded the Healthy Campus label showcase their dedication to creating a supportive, healthy, and enriching environment for their students, staﬀ, and the broader campus community.

At EHL, discussion to undertake the Healthy Campus process began at the end of year 2021, after the COVID-19 pandemic started showing sure sign of waning. Priorities being retrieving balance and investing the new campus, the process was then delayed for around a year to make sure it was embarked upon at an appropriate time to ensure impactful outcomes.

After an internal review, as well as the gathering of all the documentation and evidence, EHL Hospitality Business School is now the ﬁrst hospitality school to receive the FISU Healthy Campus label. Indeed, six months into the process, the highest level of certiﬁcation granted by the Healthy Campus scale has already been reached and EHL therefore joins the 29 “elite” universities that have obtained this level of validation.

Holistic health at EHL

EHL's commitment to student well-being is further evidenced by its comprehensive approach to health and wellness .

The many research articles that can be found on the EHL Insight blog on the link between hospitality and well-being has extended the understanding of the topic and underlines the growing interest in the domain. Shedding light on the value the new generation gives to nurturing well-being shows that prioritizing care and self-care is at a peak of urgency in the EHL community’s agenda.

Prevention is better than cure

After renovating and innovating a new health center with advanced quality services, a major shift towards prevention and health promotion was undertaken. This allowed cross-departmental collaborations.

Through the Healthy Campus process, it was now assessed that the new programs put in place for the promotion of mental health support and the eased access to a large panel of diﬀerent external partners help students get the right support when needed and ensure regular medical care such as general medicine check-ups or STD screenings are undertaken on time.

You are what you eat

Nutrition is another focus area where excellence has been emphasized, with a goal of oﬀering nutritional counseling by one of the internal nurses currently ﬁnishing her nutrition degree. In the meantime, a collaboration with the HES School of Nutrition students offers online consultations.

A transversal and cross-departmental project on healthy and sustainable internal F&B oﬀerings has started, and another initiative was recently completed to make sure vending machines on campus provide healthy options.

EHL also prioritizes physical activity by providing a variety of sports programs and state-of-the-art facilities that encourage active lifestyles on and oﬀ the campus.

The free registrations to many local and regional competitions, as well as the wide range of team and individual sports in which students and staﬀ can participate, deﬁnitely encourage physical activity.

The recent achievement of the Qualicert accreditation further strengthens the quality of service, facilities, and oﬀerings of the sports services and continues the extension of the oﬀer to become attractive for external clients.

Get involved

Get in EHL's commitment to well-being aligns with several of the United Nations Sustainable Development Goals (SDGs), particularly SDG 3 Good Health and Well-being. By promoting mental health, physical activity, and nutritious eating habits, EHL ensures long-term health benefits for its community.

Social integration and personal development are actively promoted through a variety of activities and workshops, as well as taking on roles in one of the many committees. The Alaya by Benevity platform helps promote this dedication to social responsibility.

The Healthy Campus Label is one way to make sure the initiatives at EHL align with the general goal of putting words to action, and explicitly improve quality of life on campus during academic years.

EHL's holistic approach to student well-being not only enhances individual health and happiness but also fosters a sustainable community lifestyle. It ensures that the community has the right environment to excel, embodying our mission to empower growth by nurturing excellence in human experiences.

Health & Wellness Coordinator at EHL

Keep reading

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Jun 19, 2024

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May 13, 2024

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DOI: 10.36330/kmj.v20i1.13900
Corpus ID: 270543758

Impact of Internet and Social Media on Academic Performance, Social Interaction, and Mental Health among a Sample of Iraqi University Students

Taqi Mohammed Jwad Taher , Diana Mazlum Ali
Published in Kufa Medical Journal 15 June 2024
Education, Psychology

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STRENGTHS AND LIMITATIONS OF THIS STUDY

Introduction

Aims and objectives

Stages 1 and 2: finding and choosing the studies

Supplemental material

Stage 3: retrieving the data from the studies

Stage 4: analysing the data from the studies

Patient and public involvement

Methodological features of studies

Findings related to mental health in university-to-work transitions

Theoretical and epistemological foundations

Discussion and conclusions

Ethics statements

Ethics approval

Acknowledgments

Supplementary materials

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Examining the mental health of university students: A quantitative and qualitative approach to identifying prevalence, associations, stressors, and interventions

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ORIGINAL RESEARCH article

Introduction

Conceptualization of Mental Health, Mental Illness, and Well-Being: An Overview

Perspectives on Mental Health and Mental Illness

Disciplinary Approaches to the Conceptualization of Mental Health/Illness

The Importance of the Context in Mental Health

Prioritizing Positive Mental Health: The Science of Well-Being

Integrating Mental Health, Mental Illness, and Well-Being

The Present Study

Materials and Methods

Search Strategy

Data Analysis Procedures

Findings and Discussion

Productivity I: Core Journals and Research Areas

Productivity II: Leading Authors and Countries/Territories

Social Structure: Networks of Scientific Collaboration

Intellectual Structure: Disciplines Underlying the Foundations of the Field

Conceptual Structure: Topical Foci Addressed in the Literature Over the Last 45 Years

Data Availability Statement

Author Contributions

Conflict of Interest

Factors that influence mental health of university and college students in the UK: a systematic review

Research objectives

Methodology

Study design

Data extraction and quality appraisal

Involvement of stakeholders

Methods of synthesis

Search strategy

Design and quality appraisal of the included studies

Quantitative variables

Vulnerabilities – factors that are associated with poor mental health

Sexual orientation

Family factors

Mental health history

Buffers – factors that are protective of mental wellbeing

Parental factors

Mental health literacy and help seeking behaviour

Social networks

Triggers – factors that may act in combination with other factors to lead to poor mental health

University variables

Red flags – behaviours associated with poor mental health and/or wellbeing

Health behaviours at university

Availability of data and materials

Acknowledgements

Author information

Contributions

Corresponding author

Ethics declarations

Consent for publication

Competing interests

Additional information

Supplementary Information

About this article