Cited by 49Digital Mental Health InterventionsMobile Health and mHealth ApplicationsAnxiety, Depression, Psychometrics, Treatment, Cognitive Processes

Toward the Design of Evidence-Based Mental Health Information Systems for People With Depression: A Systematic Literature Review and Meta-Analysis

Open access
Wahle, Fabian, Bollhalder, Lea, Kowatsch, Tobias, Fleisch, Elgar·2017·Journal of Medical Internet Research

Abstract

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)

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  • Another 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].”
  • 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].”

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  1. [16]Wahle F Kowatsch T Towards the design of evidence-based mental health information systems: a preliminary literature review Proceedings of the Thirty Fifth International Conference on Information Systems, Auckland 2014 2014 Thirty Fifth International Conference on Information Systems Dec 14-17, 2014 Auckland, New Zealand 12 14
  2. [68]Effective Practice and Organisation of Care Synthesising results when it does not make sense to do a meta-analysis. EPOC Resources for review authors 2013 Oslo Norwegian Knowledge Centre for the Health Services http://epoc.cochrane.org/sites/epoc.cochrane.org/files/uploads/20
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  5. [111]Oinas-Kukkonen H Harjumaa M A systematic framework for designing and evaluating persuasive systems Persuasive Technology. PERSUASIVE 2008. Lecture Notes in Computer Science, vol 5033 2008 Berlin Springer 164 169

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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
Published
2017-05-31
Volume
19
Issue
5
Pages
e191
ISSN
1438-8871 (ISSN-L)
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
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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