Digital Mental Health Interventions for University Students With Mental Health Difficulties: A Systematic Review and Meta-Analysis

Abstract

Background

While third-level educational institutions have long provided counselling, a sharp rise in demand has led to limited access to mental health supports for many students, including those with ongoing difficulties. Digital mental health interventions represent one response to this unmet need, given the potential low cost and scalability associated with no-to-low human resources involved.

Objective

The aim of this study was to conduct a systematic review and meta-analysis of the literature examining effectiveness of digital mental health interventions for university students with ongoing mental health difficulties.

Methods

The following databases were searched: PubMed, EBSCOhost (CINHAHL/PsycINFO/PsycArticles) and Web of Science. Two-armed randomised-control trials were included in the meta-analysis. A random-effects meta-analysis was conducted and standardised mean differences were calculated. Effect sizes were then compared in terms of therapeutic approach, and whether interventions were fully automated or guided interventions. This study was registered with PROSPERO, CRD42024504265.

Results

Thirty four eligible studies were included in this narrative synthesis, of which 21 randomised-controlled trials were included in the meta-analysis. Random-effects meta-analysis indicated an overall medium effect size in favour of digital interventions for both depression (Cohen's d = 0.55), and anxiety (Cohen's d = 0. 46). Of note, for anxiety outcomes, fully automated interventions appeared more effective (d = 0.55) than guided interventions (d = 0.35).

Conclusions

Digital mental health interventions are associated with beneficial effects for college students when measured in terms of anxiety and depression symptom severity. For anxiety, fully automated interventions may be more effective than guided interventions to reduce symptom severity.