Passive Psychoeducation
Key information
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Impact on mental health
Mixed impact
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Impact on student outcomes
More evidence needed
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Strength of evidence
Emerging evidence
All Student Mental Health Evidence Toolkit
What is it? Passive psychoeducation refers to information, guidance and toolkits that students can access independently to help manage mental health difficulties.
Evidence? Our evidence review found only two medium/high-quality causal studies from the UK, but a large international evidence base on the impact of passive psychoeducation on student mental health. Considering the variety of ways this intervention can be implemented by HE providers, more research is needed in a UK context.
What is the intervention?
Passive psychoeducation refers to information, guidance and toolkits aimed at raising awareness, signposting and providing essential information for managing mental health difficulties. As students can access these resources independently, this intervention does not require a trained professional to actively guide students. These resources can vary widely in their theme and content, ranging from tips to help with general wellbeing to developing skills that help people to manage anxiety, sleep or other specific difficulties. Passive psychoeducation materials can be devised by a variety of practitioners, ranging from those working in a mental health context to those supporting a student’s academic development.
They are often preventative resources that provide students with some initial or additional support. This intervention can be made accessible in multiple media forms, for example, online, in print, or on video. As they are a self-service resource, they hold the benefit of being accessed independently and privately, on a student’s own terms, though some can be programmes which can be accessed for a certain number of hours, days or weeks.
How effective is it?
Our review found that the evidence for the effectiveness of passive psychoeducation on student mental health is mixed. Though there are a large number of causal studies, such as randomised controlled trials (RCTs), most have small sample sizes, and show conflicting impact on outcomes. This means that some interventions appear to reduce mental health difficulties such as depression and anxiety with small to medium effect sizes, whereas others have limited or no effect on these outcomes. Other individual studies measure a variety of additional outcomes and demonstrate improvements in some but not all of them. The majority of the sources come from outside of the UK, namely the US. Passive psychoeducation can target a range of areas, including alcohol use, eating behaviours, stress, and general coping resources and problem solving, each of which have a different evidence base, discussed below.
Interventions teaching coping and problem-solving strategies
Many passive psychoeducation interventions seek to teach students coping and problem-solving strategies to combat mental health difficulties such as depressive symptoms. We have identified five studies that evaluate interventions teaching coping and problem-solving strategies, and demonstrate effectiveness in reducing symptoms of depression, anxiety and stress, mainly in the short-term, with small to medium effect sizes.
Geisner, Neighbors and Larimer (2006) evaluated the effectiveness of a brief intervention teaching coping strategies to students at risk of depression. Participants demonstrating moderate depressive symptoms were recruited via the psychology department at a large USA university (177 in total, majority female). Students were randomised to the intervention group, who received personalised feedback on their depressive symptoms and a brochure listing strategies for coping, or a control condition, who received a ‘thank you’ letter. Two measures of depression, as well as hopelessness, were taken pre-intervention and at one-month follow-up. Although depressive symptoms improved for all from pre- to post-intervention, there was significantly more improvement in the intervention group, with a small to medium effect size. Interestingly, the intervention was associated with significant improvement on one measure of depression but not on the other; the intervention was particularly effective for targeting concentration/memory problems and fatigue, categorised as ‘milder’ symptoms, but less effective for improving symptoms of loss of pleasure or interest (more severe symptoms). Hopelessness also improved significantly in the intervention condition, with a small to medium effect size.
Bruhns et al. (2021) also targeted students with depressive symptoms, testing the effectiveness of a psychoeducation app providing both information and guidance on cognitive strategies, positive activities, communication, mindfulness, and metacognitive training. Taking place at a university in Germany, over 400 students were randomised to use the app for four weeks or to have access after the study (a waitlist control design). Over 75% of the sample used the app at least once a week and for those that used it regularly the intervention had a small but significant effect on reducing depressive symptoms, and a small to medium effect on self-esteem.
Other interventions utilise online platforms with self-guided modules which appear to have small positive effects on anxiety, depression, and relationship issues (Ellis et al., 2011). Psychology and Health Sciences students attending a university in Australia and suffering from low to moderate levels of psychological distress were randomised to either use ‘MoodGym’, ‘MoodGarden’ or a control condition. MoodGym has modules that cover reducing dysfunctional thinking, overcoming negative feelings of anxiety and depression, identifying stress and relaxation, and strategies for problem solving and enhancing relationships. MoodGarden is an online community with a message board providing the opportunity for individuals to share experiences and receive support and encouragement in coping with their problems. Psychological distress, depression, anxiety and stress were measured pre- and post-intervention; both interventions caused positive directional changes in all measures, but only anxiety scores were significantly different from the control group. Participants gave more positive qualitative feedback on MoodGarden, suggesting the community element was important.
Braithwaite and Fincham (2009) found online modules on effective communication techniques and problem-solving skills to positively impact self-reported anxiety, depression, communication patterns, and relationship satisfaction in a USA student sample currently in romantic relationships. Interestingly this was only seen at ten-month follow-up, with intervention participants seemingly getting worse before they got better. This demonstrates the importance of capturing longer-term outcome measures.
One UK study evaluated a less common problem-solving intervention involving a computer simulation programme (Gaffney et al., 2014). Nearly 50 students attending the University of Manchester were randomised to two different computer simulation programmes – one programmed to deliver self-help techniques covering themes such as anger avoidance, cognitive dissonance, conflict, control, and perceptions, and the other (the control condition) programmed to encourage the participants to talk about their problems but without offering self-help strategies. Both programmes elicited significant reductions in distress, depression, anxiety and stress and there was no difference between the two groups in outcomes. As the control condition still involved a computer programme that enabled students to discuss their problems, the interventions should ideally be further tested against a true control (no intervention).
Interventions promoting resilience
Resilience can be defined as the knowledge, skills, and abilities that enable a person to bounce back after experiencing significant stress (Connor and Davidson, 2003). Given that many students experience stress, some psychoeducation interventions aim to teach students the skills to better cope with their environment. We have identified two studies which evaluate passive psychoeducation interventions teaching resilience, showing both small and large positive impact, however, the studies involve specific sub-groups of students, limiting generalisability.
Anderson, Vaughan and Mills (2017) conducted an RCT of a self-paced online resilience training programme to support Canadian students training to be paramedics. The course covered definitions of resilience, identifying the emotional and physical risks of paramedicine work, recognising symptoms of stress, post-traumatic stress disorder, and building resilience skills. Resilience was measured before and after, and the intervention group scored significantly better in resilience than the control group, with small effect sizes.
Kanekar, Sharma and Atri (2010) tested an internet-based intervention to enhance social support, resilience and acculturation (adapting to a new culture) among students of Asian-Indian origin at a large USA university. The intervention group were offered online instruction through access to a platform over two-months, and showed significant improvement in all mental health variables when compared to a control, with large effect sizes.
Interventions promoting positive psychology and emotion
Positive psychology interventions focus on promoting positive emotion, positive reappraisal of situations, and gratitude. We have identified three studies which have evaluated positive psychology interventions, demonstrating they can reduce symptoms of depression, anxiety and stress in students, with small to medium effect sizes.
Sarniak (2009) randomised nearly 100 students on a psychology course at a USA university to an intervention or control group. Those in the intervention group were given a writing assignment once every three days for five weeks requiring a description of three positive experiences that they’d had in the past two days and the role they played in the experience. The assignment was submitted on a webpage each time. Those in the control group completed daily e-diaries with no instruction. Participants in the intervention group reported significantly fewer depressive and anxiety symptoms at post-test when compared to the participants in the control group.
Another study in the US, again conducted on psychology students, evaluated an intervention which encouraged ‘savouring the moment’ (Hurley and Kwon, 2012). Intervention participants listened to a 20-minute audio recording created by one of the authors and followed along with provided written materials that included psychoeducation about the positive psychology movement, and descriptions of ways of savouring accompanied by an example that was relevant to university students (e.g., congratulating themselves after receiving a good grade on a test). Similar to the previous study, participants then had to recall three positive events that happened to them during the past week and to list possible ways they could have savoured these events while they occurred. The intervention significantly reduced symptoms of depression and negative affect (negative emotions such as anger and sadness) with small to medium effect sizes.
Krifa et al. (2022) conducted a study to evaluate an online self-guided positive psychology course during the COVID-19 pandemic. Nearly 400 healthcare students (majority female) at a university in Tunisia were randomised to either an eight-week online course (videos, information and brief exercises covering character strengths, positive aspects of life, self-compassion, meaning in life, gratitude and relationships), or a control group. Stress, anxiety, depression, emotional regulation, optimism and hope were all significantly improved in the intervention group compared to the control, and this was maintained at three-month follow-up with small to medium effect sizes.
Stress management interventions
We have identified two studies from the USA which have sought to evaluate stress management passive psychoeducational interventions; these are more tailored to the predictors of poor mental health in students, typically focusing on time management and problem-based learning, cognitive reappraisal of potential stressors, and stress management strategies to promote more effective coping.
Frazier et al. (2015) evaluated online stress management modules which contained videos of an expert talking about stress and perceived control (aiming to teach students to distinguish between what they can and can’t control and to focus on those things they can), other students talking about their stressors and coping, and online exercises. Nearly 200 students enrolled in psychology courses at a community college in the USA received course credit for their participation and were randomised to the intervention or a ‘stress-information only’ control (information about common college student stressors and their effects only). Participants in the intervention group reported significant increases in present control (focusing on what they can control in the present rather than ruminating about the past or worrying about the future), and significant decreases in perceived stress, stress symptoms, depression and anxiety from baseline to post-intervention and follow-up, with small to medium effect sizes.
Another study found no differences in mental health outcomes between a group of students who had access to an online stress management information intervention and a control group, though intervention participants were more likely to increase weekly physical activity, use specific stress management methods, and exhibit decreased family problems (Chiauzzi et al., 2008).
Increasing awareness and knowledge only
Most psychoeducation interventions, as the name suggests, seek to educate students on various issues related to mental health. However, they generally also teach strategies for combating mental health difficulties and thus evaluations will measure impact on mental health outcomes. One UK study evaluated an intervention which sought to increase awareness and knowledge of depression only. Merritt et al. (2007) conducted a cluster RCT on the impact of postcards containing brief information on depression including frequency among students, symptoms, possible treatments, and where to go for help. Nearly 30 University of Oxford colleges were randomised to either receive the intervention or to be in the control group, resulting in over 5,000 students in each condition. Half of the students in each condition were sent a questionnaire pre-intervention, and the other half were sent it post-intervention. The questionnaire measured knowledge of symptoms and treatments of depression, with the authors particularly interested in whether participants responded positively to the question ‘can depression be effectively treated?’ The intervention did not appear to have influenced how likely students were to think that depression can be treated effectively. However, of the seven depressive symptoms presented in the postcards, five were statistically significantly better recognised in participants who’d received the intervention, compared to the control. The intervention also increased participants’ awareness that antidepressants are not addictive. The intervention therefore didn’t appear to change beliefs about treatability but did improve recognition of symptoms and change beliefs about addictiveness.
Interventions targeting alcohol use
Most of the evidence on interventions targeting alcohol use comes from North America, targeting drinking behaviours before the legal age of 21 or when students celebrate their 21st birthdays. Consequently, there is limited generalisability to the UK HE context, and these studies do not measure mental health outcomes in addition to drinking behaviour (Neal and Carey, 2004, Lewis et al., 2008, Ichiyama et al., 2009, Turrisi et al., 2009, Neighbors et al., 2009). One study that did measure mental health outcomes evaluated a brief web-based intervention for USA university students who had both moderate to high drinking behaviours and moderate depressive symptoms (Geisner et al., 2015). Participants were randomly assigned to an ‘alcohol only’ intervention (presented with feedback on their drinking behaviour relative to other students and the link between alcohol and depression), a ‘depressed mood only’ intervention (gave information on the prevalence of depressed mood and feedback on participant’s own depression symptoms), an integrated intervention (the first two interventions combined), or a control condition. Depressive symptoms, drinking behaviours, and alcohol-related consequences (events, such as missing work/study due to drinking, over the past month) were measured at baseline and one month follow-up. The intervention had no impact on depression or alcohol outcome variables. However, those with below-average levels of baseline depression in the ‘alcohol only’ or integrated condition had significantly lower alcohol-related consequences at follow-up compared to control, suggesting the intervention may partially address milder symptoms.
How secure is the evidence?
The current evidence base for passive psychoeducation is emerging. There are a sizeable number of medium/high-quality RCTs that have been conducted with student populations which provide causal evidence on these interventions, through comparison of a treatment group that receives the intervention and a control group that does not (or does so only after a set time period – a waitlist control). However, we have only identified two which have been conducted in the UK; we need more robust evidence from the UK to draw reliable conclusions that are accurate for UK HE providers.
The majority of the studies referenced recruited students through poster and email campaigns, which results in an overrepresentation of white females in the evidence because these students are more likely to seek help and to use mental health services than males and those from marginalised ethnic backgrounds (Eisenberg, Golberstein, and Gollust, 2007). This makes the evidence for passive psychoeducation interventions less secure for different student groups. A large number of studies recruit students from psychology courses and often students are encouraged to participate in exchange for course credits. Not only should this evidence be treated with caution as it is unlikely to be generalisable to students on different courses, it may also be masking issues related to engagement with interventions, as it is probable that students who receive course credit are more likely to engage with and complete intervention programmes.
Much of the evidence captures mental health outcomes immediately or soon after the intervention has been received, so further research is needed to ascertain whether effects can be sustained in the long-term. In addition, there are no causal studies which focus on student outcomes, such as attainment and continuation, as well as mental health outcomes. It is important to understand whether interventions improve student mental health but also that they contribute to success on-course.
The use of self-report measures is also a limitation of the evidence cited above, particularly as for many interventions here students will have been acutely aware of the approach being tested, leading to a strong risk of students reporting better mental health outcomes because they think they are expected to. It should also be noted that some of the studies have small samples and/or there is insufficient detail in the paper to understand if the sample is big enough for the purpose of the analysis.
How do I evaluate this intervention?
RCTs are one of the most robust ways to measure interventions as they allow comparison of two groups that have either received or haven’t received the intervention, whilst controlling for observable and unobservable differences between the two groups. These trials should take place outside of lab settings to test whether, and how, interventions translate and perform in the ‘real world’. There are many examples in the literature on using a wait-list control design (see, for example, Bruhns et al., 2021); the key benefit of this design is that the control group is still able to receive the intervention, just at a later date once outcomes have been measured in both groups.
Outcomes should be measured using validated scales before and after the intervention has been received. As the evidence on the longer-term effects of interventions is inconsistent, measuring outcomes at multiple time points (e.g. three-, six- and 12-month follow-ups) is important, rather than only immediately after. A limitation of the existing studies is that too many outcomes are being measured, which increases the chances of (falsely) finding a statistically significant result for at least one of them. This limits the validity of findings. Outcomes measures should be chosen carefully based on what the intervention is trying to address, which should be mapped out in a Theory of Change.
There is a lack of evidence on the impact of passive psychoeducation interventions on student outcomes such as attainment, retention and progression and HE providers should seek to embed these into evaluation plans.
One further limitation of the current literature is that interventions can be outlined in insufficient detail to allow accurate replication. This is particularly important given psychoeducation interventions can address a range of different skills and knowledge, from resilience to positive psychology. HE providers should therefore include thorough intervention descriptions in their evaluations to allow others to build on their work.
See our evaluation guidance for more support.
Where can I find more information and guidance?
For guidance from the Mental Health Charter, please follow the links below:
Most passive psychoeducation interventions fall under the following themes:
Where does the evidence come from?
The evidence in the toolkit was gathered via an evidence review undertaken as part of the Student Mental Health Project. For full details of this review, please see our Methodology document.
It is important to note that our review, and therefore this Toolkit, only relates to student mental health. The review did not cover other populations (e.g. school children, other adult populations) or non-HE settings. The review was also subject to other inclusion/exclusion criteria, outlined in the Methodology document. However, we have flagged some additional links to the wider literature where appropriate and included them under ‘other references’ below.
Please also note that this toolkit page only includes Type 3 (causal) studies which have been rated as providing medium/high-quality evidence according to our evidence strength ratings. These studies are outlined in the page above and referenced below. A full list of studies collated via our evidence review, including Type 1/Type 2 studies, and those rated as providing weak/emerging evidence, can be found in our Evidence Review Spreadsheet. A breakdown of these studies by type and strength of evidence is available to download.
Main references
Anderson, G. S., Vaughan, A. D., & Mills, S. (2017). Building personal resilience in paramedic students. Journal of Community Safety and Well-Being, 2(2), 51–54. doi:10.35502/jcswb.44
Braithwaite, S.R. and Fincham, F.D. (2009). A randomized clinical trial of a computer based preventive intervention: Replication and extension of ePREP. Journal of Family Psychology, 23(1), pp.32–38. doi:10.1037/a0014061
Bruhns, A., Lüdtke, T., Moritz, S. and Bücker, L. (2021). A mobile-based intervention to increase self-esteem in students with depressive symptoms: Randomized controlled trial. JMIR mHealth and uHealth, 9(7), p.e26498. doi:10.2196/26497
Chiauzzi, E., Brevard, J., Thurn, C., Decembrele, S. and Lord, S. (2008) MyStudentBody–Stress: An online stress management intervention for college students. Journal of health communication, 13(6), 555-572. doi:10.1080/10810730802281668
Ellis, L.A., Campbell, A.J., Sethi, S. and O’Dea, B.M. (2011) Comparative randomized trial of an online cognitive-behavioral therapy program and an online support group for depression and anxiety. Journal of Cyber Therapy and Rehabilitation, 4(4), 461-467. Available at: https://interactivemediainstitute.com/wp-content/uploads/2019/04/JCR-44.pdf
Frazier, P., Meredith, L., Greer, C., Paulsen, J.A., Howard, K., Dietz, L.R. and Qin, K. (2015) Randomized controlled trial evaluating the effectiveness of a web-based stress management program among community college students. Anxiety, Stress, & Coping, 28(5), 576-586. doi:10.1080/10615806.2014.987666
Geisner, I.M., Neighbors, C. and Larimer, M.E. (2006) A randomized clinical trial of a brief, mailed intervention for symptoms of depression. Journal of Consulting and Clinical Psychology, 74(2), p.393. doi:10.1016/j.addbeh.2014.10.030
Hurley, D.B. and Kwon, P. (2012) Results of a study to increase savoring the moment: Differential impact on positive and negative outcomes. Journal of Happiness Studies, 13, pp.579-588. doi:10.1007/s10902-011-9280-8
Ichiyama, M.A., Fairlie, A.M., Wood, M.D., Turrisi, R., Francis, D.P., Ray, A.E. and Stanger, L.A. (2009) A randomized trial of a parent-based intervention on drinking behavior among incoming college freshmen. Journal of Studies on Alcohol and Drugs, Supplement, (16), 67-76. doi:10.15288/jsads.2009.s16.67
Kattelmann, K.K., Bredbenner, C.B., White, A.A., Greene, G.W., Hoerr, S.L., Kidd, T., Colby, S., Horacek, T.M., Phillips, B.W., Koenings, M.M. and Brown, O.N. (2014) The effects of Young Adults Eating and Active for Health (YEAH): a theory-based Web-delivered intervention. Journal of nutrition education and behavior, 46(6), pp.S27-S41. doi:10.1016/j.jneb.2014.08.007
Kanekar A, Sharma M and Atri A. (2010) Enhancing Social Support, Hardiness, and Acculturation to Improve Mental Health among Asian Indian International Students. International Quarterly of Community Health Education. 30 (1), 55-68. doi:10.2190/IQ.30.1.e
Krifa, I., Hallez, Q., van Zyl, L.E., Braham, A., Sahli, J., Ben Nasr, S. and Shankland, R. (2022). Effectiveness of an online positive psychology intervention among Tunisian healthcare students on mental health and study engagement during the Covid‐19 pandemic. Applied Psychology: Health and Well‐Being, 14(4), pp.1228-1254. doi:10.1111/aphw.12332
Lewis, M.A., Neighbors, C., Lee, C.M. and Oster-Aaland, L. (2008) 21st birthday celebratory drinking: evaluation of a personalized normative feedback card intervention. Psychology of Addictive Behaviors, 22(2), p.176. doi:10.1037/0893-164x.22.2.176
Merritt, R.K., Price, J.R., Mollison, J. and Geddes, J.R. (2007) A cluster randomized controlled trial to assess the effectiveness of an intervention to educate students about depression. Psychological Medicine, 37(3), 363-372. doi:10.1017/s0033291706009056
Neal, D.J. and Carey, K.B. (2004) Developing discrepancy within self-regulation theory: Use of personalized normative feedback and personal strivings with heavy-drinking college students. Addictive behaviors, 29(2), 281-297. doi:10.1016/j.addbeh.2003.08.004
Neighbors, C., Lee, C.M., Lewis, M.A., Fossos, N. and Walter, T. (2009) Internet-based personalized feedback to reduce 21st-birthday drinking: a randomized controlled trial of an event-specific prevention intervention. Journal of consulting and clinical psychology, 77(1), p.51. doi:10.1037/a0014386
Sarniak, R.H. (2009) The effects of an online intervention designed to cultivate positive emotions on emotional and health outcomes in college students (Doctoral dissertation, The University of North Carolina at Chapel Hill). Available at: https://cdr.lib.unc.edu/downloads/9593tv255?locale=en
Turrisi, R., Larimer, M.E., Mallett, K.A., Kilmer, J.R., Ray, A.E., Mastroleo, N.R., Geisner, I.M., Grossbard, J., Tollison, S., Lostutter, T.W. and Montoya, H. (2009) A randomized clinical trial evaluating a combined alcohol intervention for high-risk college students. Journal of studies on alcohol and drugs, 70(4), 555-567. doi:10.15288/jsad.2009.70.555
Other references
Connor, K. M., & Davidson, J. R. T. (2003). Development of a new resilience scale: The Connor-Davidson resilience scale (CD-RISC). Depression and Anxiety, 18(2), 76–82. doi:10.1002/da.10113
Eisenberg, D., Golberstein, E. and Gollust, S.E., (2007). Help-seeking and access to mental health care in a university student population. Medical care, pp.594-601. doi:10.1097/MLR.0b013e31803bb4c1