Madrid-Cagigal Alba, Kealy Carmen, Potts Courtney, Mulvenna Maurice D, Byrne Molly, Barry Margaret M, Donohoe Gary
School of Psychology, University of Galway, Galway, Ireland.
Health Promotion Research Centre, University of Galway, Galway, Ireland.
Early Interv Psychiatry. 2025 Mar;19(3):e70017. doi: 10.1111/eip.70017.
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.
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.
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.
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).
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.
虽然高等教育机构长期以来一直提供咨询服务，但需求的急剧上升导致许多学生，包括那些有持续困难的学生，获得心理健康支持的机会有限。鉴于数字心理健康干预可能具有低成本以及无需或只需少量人力资源参与即可扩展的特点，它成为了满足这一未被满足需求的一种应对方式。
本研究的目的是对有关数字心理健康干预对有持续心理健康困难的大学生有效性的文献进行系统综述和荟萃分析。
检索了以下数据库：PubMed、EBSCOhost（CINHAHL/PsycINFO/PsycArticles）和Web of Science。荟萃分析纳入了双臂随机对照试验。进行了随机效应荟萃分析并计算了标准化均值差异。然后根据治疗方法以及干预是完全自动化还是有指导的干预来比较效应大小。本研究已在国际系统评价注册库（PROSPERO）注册，注册号为CRD42024504265。
本叙述性综述纳入了34项符合条件的研究，其中21项随机对照试验纳入了荟萃分析。随机效应荟萃分析表明，对于抑郁症（科恩d值 = 0.55）和焦虑症（科恩d值 = 0.46），数字干预总体上具有中等效应大小。值得注意的是，对于焦虑症结果，完全自动化干预似乎比有指导的干预更有效（d值 = 0.55）（d值 = 0.35）。
以焦虑和抑郁症状严重程度衡量，数字心理健康干预对大学生有有益影响。对于焦虑症，完全自动化干预在减轻症状严重程度方面可能比有指导的干预更有效。
