A Meta-analysis of Universal Mental Health Prevention Programs for Higher Education Students

Abstract

This meta-analysis investigated the effectiveness of universal mental health prevention programs for higher education students on a range of adjustment outcomes. A systematic literature search identified 103 controlled published and unpublished interventions involving college, graduate, or professional students. As hypothesized, skill-training programs that included a supervised practice component were significantly more effective overall (mean effect size = 0.45, confidence interval (CI) = 0.39 to 0.52) compared to skill-training programs without supervised practice (0.11, CI = -0.01 to 0.22) and psychoeducational (information-only) programs (0.13, CI = 0.06 to 0.21). When comparisons on specific outcomes were possible, skill-training programs including supervised practice were significantly more effective than the other two groups of programs in reducing symptoms of depression, anxiety, stress, and general psychological distress, and in improving social-emotional skills, self-perceptions, and academic behaviors and performance. The magnitude of effects achieved in several outcome areas is comparable to or higher than that reported in other reviews of universal programs, suggesting that skill-training programs for higher education students that incorporate supervised practice now join the ranks of other effective preventive mental health interventions. This review offers several recommendations to improve the experimental rigor of future research.

A pragmatic clinical trial examining the impact of a resilience program on college student mental health

“…Effect sizes for the current intervention at semester‐end were similar to that found for previous interventions with college populations (Conley et al, ). The group who received resilience programming had average depression scores approximately three T scores lower than the comparison group.…”

“…According to Conley et al (), the average effect size of intervention programs previously implemented in college populations is d = 0.29. We assessed (a) required sample size for 80% power and (b) achieved power for N = 126 per group, given the intracluster correlations (ICC) observed for PROMIS Depression, Anxiety, and CD‐RISC (0.62–0.70).…”

Understanding Students’ Experiences of Well-Being in Learning Environments

“…There have been a multitude of articles exploring the impacts of interventions which embed mental health and well-being topics or skills training within curriculum (Conley et al, 2015;Seligman et al, 2009), but fewer articles have explored how the design and delivery of learning experiences themselves can support well-being. Some articles have outlined the impacts of learning experiences on particular aspects of well-being such as social connection or resilience (Ewert & Yoshino, 2011;Rowe & Stewart, 2011), while others have explored the benefits of specific teaching practices such as facilitation techniques, on student well-being (Adriansen & Madsen, 2013).…”

“…The Charter emphasizes the importance of incorporating well-being within the core mandate of higher education, and suggests that learning environments are an important setting for creating health. Although there are many studies exploring how health interventions can be embedded within educational settings (Seligman, Ernst, Gillham, Reivich, & Linkins, 2009;Conley, Durlak, & Kirsch, 2015), there is very little research on how higher education class structure and curriculum can be intentionally designed to create conditions for well-being. This study uses a qualitative methodology to explore students' own experiences of well-being in learning environments, and provides insight into how future learning experiences in higher education may be designed to enhance well-being and learning.…”

Mental Health Literacy and Peer‐to‐Peer Counseling Referrals Among Community College Students

“…Conley, Durlak, and Kirsch (2015) and Kalkbrenner (2016) identified a number of MHL‐related topics (e.g., recognizing warning signs of mental health concerns, referral and communication strategies, prevention and intervention methods) and mental health support training (e.g., supervised skills trainings) that have implications for programming. College counselors might promote students’ engagement with peer‐to‐peer mental health support by facilitating supervised skills trainings for students, as these trainings are significantly more effective at promoting college students’ mental health when compared with traditional psychoeducation sessions (Conley et al, 2015). As just one example, the REDFLAGS model (see Figure 1) provides an empirically supported model for use with community college students (Kalkbrenner et al, 2019) that college counselors might find useful for framing the content of supervised skills trainings.…”