Toward the Design of Evidence-Based Mental Health Information Systems for People With Depression: A Systematic Literature Review and Meta-Analysis
Open accessAbstract
BACKGROUND: Existing research postulates a variety of components that show an impact on utilization of technology-mediated mental health information systems (MHIS) and treatment outcome. Although researchers assessed the effect of isolated design elements on the results of Web-based interventions and the associations between symptom reduction and use of components across computer and mobile phone platforms, there remains uncertainty with regard to which components of technology-mediated interventions for mental health exert the greatest therapeutic gain. Until now, no studies have presented results on the therapeutic benefit associated with specific service components of technology-mediated MHIS for depression. OBJECTIVE: This systematic review aims at identifying components of technology-mediated MHIS for patients with depression. Consequently, all randomized controlled trials comparing technology-mediated treatments for depression to either waiting-list control, treatment as usual, or any other form of treatment for depression were reviewed. Updating prior reviews, this study aims to (1) assess the effectiveness of technology-supported interventions for the treatment of depression and (2) add to the debate on what components in technology-mediated MHIS for the treatment of depression should be standard of care. METHODS: Systematic searches in MEDLINE, PsycINFO, and the Cochrane Library were conducted. Effect sizes for each comparison between a technology-enabled intervention and a control condition were computed using the standard mean difference (SMD). Chi-square tests were used to test for heterogeneity. Using subgroup analysis, potential sources of heterogeneity were analyzed. Publication bias was examined using visual inspection of funnel plots and Begg's test. Qualitative data analysis was also used. In an explorative approach, a list of relevant components was extracted from the body of literature by consensus between two researchers. RESULTS: Of 6387 studies initially identified, 45 met all inclusion criteria. Programs analyzed showed a significant trend toward reduced depressive symptoms (SMD -0.58, 95% CI -0.71 to -0.45, P<.001). Heterogeneity was large (I2≥76). A total of 15 components were identified. CONCLUSIONS: Technology-mediated MHIS for the treatment of depression has a consistent positive overall effect compared to controls. A total of 15 components have been identified. Further studies are needed to quantify the impact of individual components on treatment effects and to identify further components that are relevant for the design of future technology-mediated interventions for the treatment of depression and other mental disorders.
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Mental health app interventions are moderately effective in reducing depressive symptoms compared to controls, consistent with prior meta-analyses.
“Consistent with prior systematic reviews and meta-analyses on digital interventions for depression, we found that mental health app interventions are moderately effective in reducing depressive symptoms compared to controls [26,37,38,41,89].”
From Examining the effectiveness of gamification in mental health apps for depression: Systematic review and meta-analysis (2021) · cites this paper as [38]
The Results (Synthesis of Results: Impact on Symptoms of Depression; page unavailable) report a moderate reduction in depressive symptoms across 45 trials of technology-based interventions, compared with controls as described in Methods (Statistical Analyses). But the Discussion (Principal Results; page unavailable) says 42 of the 45 trials did not use mobile phones or tablets, so the pooled finding does not establish a moderate effect specifically for app interventions. (LLM, conf=0.88)
Experimental — accuracy not yet measuredAnother meta-analysis of 45 randomized controlled trials found that depressive symptoms showed significant reductions compared to wait-list or treatment-as-usual controls.
“Depressive symptoms showed significant reductions in comparison to either wait-list or treatment-as-usual controls [38].”
From Examining the effectiveness of gamification in mental health apps for depression: Systematic review and meta-analysis (2021) · cites this paper as [38]
Incorporating reminders into digital mental health interventions can promote engagement and adherence, which may enhance therapeutic benefits.
“Other work suggests that incorporating reminders into digital mental health interventions can promote engagement and adherence with the intervention, which may, in turn, enhance the intervention’s therapeutic benefits [38].”
From Examining the effectiveness of gamification in mental health apps for depression: Systematic review and meta-analysis (2021) · cites this paper as [38]
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Bhatnagar, N., Swaroop, V., Mandal, I., & Singh, M. M. (2025) · Indian Journal of Occupational and Environmental Medicine · doi:10.4103/ijoem.ijoem_144_24
Wang, Q., Zhong, J., Qi, K., Bao, H., Wang, Y., Guo, S., & Chen, A. (2026) · Psychiatry Research · doi:10.1016/j.psychres.2026.117459
Using Simulations, Games, and Apps to Support the Mental Health of First Responders
Englert, D. R., Sachau, D. A., & Lassiter, A. (2026) · Springer eBooks · doi:10.1007/978-3-032-27978-1_16
- Authors
- Wahle, F., Bollhalder, L., Kowatsch, T., & Fleisch, E.
- Affiliations
- ETH Zurich (CH)
- University of St.Gallen (CH)
- Corresponding author
- Kowatsch, Tobias
- Venue
- Journal of Medical Internet Research
- Publisher
- JMIR Publications Inc.
- Published
- 2017-05-31
- Volume
- 19
- Issue
- 5
- Pages
- e191
- ISSN
- 1438-8871 (ISSN-L)
- PMC
- PMC5471345
- OpenAlex
- W2618967963
- Cited by
- 48
- References
- 140
- Citations by year
- 2026: 2 · 2025: 3 · 2024: 4 · 2023: 3 · 2022: 5 · 2021: 9 · 2020: 10 · 2019: 7 · 2018: 2 · 2017: 3
- FWCI
- 0.70
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Journal of Medical Internet Research (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Alexandria (UniSG) (University of St.Gallen) (acceptedVersion)
- Alexandria (UniSG) (University of St.Gallen) (submittedVersion)
- Repository for Publications and Research Data (ETH Zurich) (submittedVersion, cc-by)
- ETH Zürich Research Collection (cc-by)
- Topics
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
- Keywords
- depression, mental health information systems, technology-based interventions, online intervention, mobile phone intervention, treatment components, depressive symptom reduction
- MeSH terms
- Depression, Humans, Mental Health, Treatment Outcome, Health Information Systems
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