Evidence-Based Psychological Assessment and Interventions Doctoral School, Babes-Bolyai University, Cluj-Napoca, Romania.
DATA Lab, International Institute for Advanced Studies in Psychotherapy and Applied Mental Health, Babes-Bolyai University, Cluj-Napoca, Romania; Department of Clinical Psychology and Psychotherapy, Babes-Bolyai University, Cluj-Napoca, Romania.
Clin Psychol Rev. 2024 Dec;114:102515. doi: 10.1016/j.cpr.2024.102515. Epub 2024 Nov 5.
Stress is a significant mental health concern for the general population, highlighting the need for effective and scalable solutions, such as mobile health (mHealth) app interventions. This systematic review and meta-analysis aimed to investigate the effects of mHealth apps designed primarily to reduce stress and distress in non-clinical and subclinical populations. A comprehensive literature search was conducted up to August 2024, including studies that measured both self-reported and physiological stress outcomes. 80 studies were analyzed. A small but significant effect size (g = 0.33) was found for self-reported stress outcomes, with studies that used specific active controls, operated in naturalistic contexts, and had a low risk of bias showing significantly lower effect sizes. A similarly small effect size was observed for physiological outcomes (g = 0.24). Notably, studies that employed muscle and breathing relaxation, meditation strategies, personalized guidance, experimental usage settings, and measured acute stress responses demonstrated significantly higher effect sizes. Further analysis of specific physiological systems revealed small effect sizes for autonomic (g = 0.32) and cardiac outcomes (g = 0.36). The significant effects observed across both psychological and physiological outcomes support the efficacy and potential of mHealth apps for the self-management of stress responses in the broader population.
压力是一个普遍存在的重大心理健康问题,这突显了需要有效的、可扩展的解决方案,如移动健康(mHealth)应用干预。本系统评价和荟萃分析旨在调查主要旨在减少非临床和亚临床人群压力和痛苦的 mHealth 应用的效果。我们进行了全面的文献检索,截至 2024 年 8 月,包括测量自我报告和生理压力结果的研究。分析了 80 项研究。自我报告的压力结果发现了一个较小但具有统计学意义的效应量(g=0.33),使用特定主动对照、在自然主义环境中运行且具有低偏倚风险的研究显示出显著更低的效应量。生理结果也观察到了类似较小的效应量(g=0.24)。值得注意的是,采用肌肉和呼吸放松、冥想策略、个性化指导、实验使用设置以及测量急性应激反应的研究显示出更高的效应量。对特定生理系统的进一步分析显示,自主(g=0.32)和心脏(g=0.36)的效应量较小。在心理和生理结果中观察到的显著效果支持了 mHealth 应用在更广泛人群中自我管理应激反应的有效性和潜力。