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Digital Psychotherapies for Adults Experiencing Depressive Symptoms: Systematic Review and Meta-Analysis
Joanna Omylinska-Thurston1, Supritha Aithal2, Shaun Liverpool2
1School of Health and Society, University of Salford, Manchester, United Kingdom.
Digital psychotherapies are effective for depression, with blended approaches showing the largest impact. These digital mental health tools offer accessibility and support for diverse populations, particularly young women.
Area of Science:
- Mental Health
- Digital Therapeutics
- Psychiatry
Background:
- Depression impacts 5% of adults globally, representing a significant cause of disability.
- Digital psychotherapies present an accessible avenue for addressing depression.
- This review synthesizes evidence on digital interventions for depression's effectiveness and user experience.
Purpose of the Study:
- Identify common digital psychotherapy modalities for depression.
- Explore client and practitioner perspectives on helpful/unhelpful aspects of digital interventions.
- Evaluate the overall effectiveness of digital psychotherapies for adult depression.
Main Methods:
- Systematic review following PRISMA guidelines, employing a PICOS framework (2010-2024).
- Searched 7 databases, with data extracted and reviewed by multiple authors to ensure rigor.
- Utilized qualitative narrative synthesis for user perceptions and meta-analysis (Hedges g) for depression outcomes.
Main Results:
- 160 studies (70,720 participants) were included; 81.8% were quantitative, 55% randomized controlled trials.
- Blended digital interventions showed a large effect size (Hedges g=-0.793), superior to human-contact (g=-0.42) or no-contact (g=-0.40) interventions.
- Positive user perceptions included motivation and accessibility; negative perceptions cited usability and lack of direction.
Conclusions:
- Digital interventions for depression are effective across various formats and frequencies.
- Blended approaches demonstrate superior efficacy compared to other digital formats.
- Future research should explore heterogeneity factors influencing intervention and population characteristics.
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