Stress management interventions for university students in low-and middle-income countries: a systematic review and...

Stress is one of major issues among university students which can lead to negative academic performance and poor quality of life. Stress-management interventions (SMIs) have been proved as being effective in helping university students cope with stress. However, most of prior studies focused on high income countries while there is still scarce evidence for low-and-middle-income countries (LMICs). The objective of the present study was to examine the effectiveness of SMIs in reducing stress level experienced by university students in LMICs.

Systematic searches were carried out in PubMed, Embase, APA PsycInfo, ERIC, Web of Science, and Cochrane Central up to March 2024. Of 8180 hits, we identified 28 Randomized Control Trials to be included in the analysis. Effect size (Hedge's g) were calculated for stress level outcomes at post-treatment.

The effect size of all included studies was high and statistically significant [g = -0.85; 95% CI (-1.34, -0.36); p = .002] with high heterogeneity across studies [I ² = 92.89%; 95% CI (90.94, 94.42); p < 0.001]. After removing outliers, the pooled effect size was corrected to medium effect [g = -0.61; 95% CI (-0.75, -0.47); p < .001] with moderate heterogeneity [I ² = 38.9%; 95% CI (0, 62.7); p = .033]. Most studies had methodological limitations, including high risk of bias, small sample sizes, and the use of passive control groups (e.g., waitlist or no treatment). No significant subgroup differences were found in theoretical orientation, format of intervention, control condition, country region, and risk of bias category.

Our results indicated that SMIs effectively reduce stress among university students in LMICs. However, the overall body of evidence is limited by concerns regarding methodological rigor, and findings should be interpreted with caution. Despite these limitations, digital formats appear to hold promising potential for further development and implementation in LMIC settings, particularly given their promising scalability and cost-efficiency.

The study protocol was registered in the Open Science Framework. The accessible link is https://doi.org/10.17605/OSF.IO/GHSEB.