Abstract
The increasing prevalence of stress underscores the demand for effective, self-administered mobile mental health interventions, yet their efficacy and accessibility are still unclear. Here, this systematic review and meta-analysis aimed to classify self-administered mobile stress management interventions, compare their efficacy and examine their moderators. We searched PsycINFO, PubMed, Web of Science, MEDLINE, Embase, CINAHL, Scopus and PsycARTICLES from database inception to 20 November 2023. Eligible studies were randomized controlled trials on peer-reviewed, Internet-based, self-administered psychological interventions for stress reduction in healthy or subhealthy adults. A total of 63 studies with 20,454 participants were included (68.18% female; mean age 39.14 years). Integrated expert insights with large language models to develop a three-dimensional framework encompassing theoretical foundation, human support and mobile technology. Intervention labels were independently coded by the authors and ChatGPT. The included studies’ quality was assessed using the Cochrane Risk of Bias 2.0 tool. Bayesian network meta-analysis and Bayesian meta-regression were used to explore comparative efficacy and potential moderators. The framework classified and compared 19 mobile stress interventions, identifying key moderating factors for optimization. Stress management programmes, problem-solving therapy and mindfulness meditation ranked the top. There was no conclusive evidence that human support or mobile technology significantly enhanced intervention outcomes. The evidence is subject to sex imbalance and quality risk, while the limited statistical power of meta-regression warrants caution in interpreting moderator effects. Our findings provide insights for designing more effective and scalable stress interventions and offer promising strategies to reduce health service disparities and advance the Sustainable Development Goals.
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Data availability
All data that support the findings of this study are available via figshare at https://doi.org/10.6084/m9.figshare.27174252.v3 (ref. 61). Source data are provided with this paper.
Code availability
All code for data analyses associated with the current submission are available via figshare at https://doi.org/10.6084/m9.figshare.27174252.v3 (ref. 61).
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Acknowledgements
This research was supported by the National Natural Science Foundation of China under grant nos. 32171076 and 32471135, received by Y.G. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. We thank Y. Hu for help in plotting the leverage plot; J. Tang for help in prompt engineering and metrics evaluation of ChatGPT; X. Gao and X. Jiang for their help with the early literature review, study screening and coding; and S. Fan, J. Su, X. Guo, H. Huang, J. Hu and B. Li for their help with coding and rating.
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H.Z., Q.C. J.L. and Y.G conceived this work. H.Z., Q.C. and X.W. developed the methodology. H.Z., Q.C., X.W. and Q.J. produced the software. H.Z. and Q.C. obtained the resources and undertook the formal analysis. S.W., X.W. and H.Z carried out data curation. H.Z., Q.C. J.L. and Y.G created the figures. Y.G. supervised the project and obtained funding. H.Z., Q.C., S.W. and Y.G. wrote the original draft of the paper. J.L., H.Z., Q.C., X.W. and Y.G. revised the draft of the manuscript. H.Z., Q.C., S.W., X.W., Q.J., J.L.and Y.G. were involved in reviewing and editing.
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Zhu, H., Chen, Q., Wei, S. et al. A systematic review and Bayesian network meta-analysis on the efficacy and potential of mobile interventions for stress management. Nat Hum Behav 9, 1431–1441 (2025). https://doi.org/10.1038/s41562-025-02162-0
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DOI: https://doi.org/10.1038/s41562-025-02162-0
