Efficacy of app-based mobile health interventions for stress management: A systematic review and meta-analysis of self-reported, physiological, and neuroendocrine stress-related outcomes

Abstract

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.

Keywords: HPA axis; Meta-analysis; Mobile health; Physiological; Sleep; Stress.