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

IF 2.1 4区医学 Q3 PSYCHIATRY

Early Intervention in Psychiatry Pub Date : 2025-03-03 DOI:10.1111/eip.70017

Alba Madrid-Cagigal, Carmen Kealy, Courtney Potts, Maurice D. Mulvenna, Molly Byrne, Margaret M. Barry, Gary Donohoe

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引用次数: 0

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.

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针对大学生心理健康困难的数字心理健康干预：系统回顾与元分析

背景：虽然三级教育机构长期以来一直提供咨询，但需求的急剧增加导致许多学生，包括那些持续存在困难的学生，获得心理健康支持的机会有限。数字精神卫生干预措施是对这一未满足需求的一种回应，因为涉及的人力资源可能很低，成本可能很低，而且可扩展性也很好。目的本研究的目的是对文献进行系统回顾和荟萃分析，以检验数字心理健康干预对持续存在心理健康困难的大学生的有效性。方法检索PubMed、EBSCOhost （CINHAHL/PsycINFO/PsycArticles）和Web of Science数据库。meta分析纳入了双臂随机对照试验。进行随机效应荟萃分析，计算标准化平均差异。然后根据治疗方法比较效果大小，以及干预是全自动干预还是引导干预。本研究注册号为PROSPERO， CRD42024504265。34项符合条件的研究纳入了这一叙事综合，其中21项随机对照试验纳入了meta分析。随机效应荟萃分析表明，数字干预对抑郁症（Cohen’s d = 0.55）和焦虑症（Cohen’s d = 0）的总体中等效应均有利。46)。值得注意的是，对于焦虑结果，全自动干预似乎比引导干预（d = 0.35）更有效（d = 0.55）。结论在焦虑和抑郁症状严重程度方面，数字心理健康干预与大学生的有益效果相关。对于焦虑，全自动干预可能比引导干预更有效地降低症状严重程度。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Early Intervention in Psychiatry 医学-精神病学

CiteScore

4.80

自引率

5.00%

发文量

112

审稿时长

6-12 weeks

期刊介绍： Early Intervention in Psychiatry publishes original research articles and reviews dealing with the early recognition, diagnosis and treatment across the full range of mental and substance use disorders, as well as the underlying epidemiological, biological, psychological and social mechanisms that influence the onset and early course of these disorders. The journal provides comprehensive coverage of early intervention for the full range of psychiatric disorders and mental health problems, including schizophrenia and other psychoses, mood and anxiety disorders, substance use disorders, eating disorders and personality disorders. Papers in any of the following fields are considered: diagnostic issues, psychopathology, clinical epidemiology, biological mechanisms, treatments and other forms of intervention, clinical trials, health services and economic research and mental health policy. Special features are also published, including hypotheses, controversies and snapshots of innovative service models.