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User Acceptance of Computerized Cognitive Behavioral Therapy for Depression: Systematic Review
Theresia Rost1, Janine Stein1, Margrit Löbner1
1Institute of Social Medicine, Occupational Health and Public Health, Medical Faculty, University of Leipzig, Leipzig, Germany.
Journal of Medical Internet Research
|September 15, 2017
Summary
Computerized cognitive behavioral therapy (cCBT) for depression is generally well-accepted by users. However, research shows inconsistencies in how user acceptance is defined and measured, highlighting areas for methodological improvement.
Area of Science:
- Mental Health Technology
- Digital Therapeutics
- Psychiatry
Background:
- Computerized cognitive behavioral therapy (cCBT) is an increasingly popular and effective treatment for depression.
- User acceptance is a critical factor for the success and widespread adoption of any therapeutic intervention.
Purpose of the Study:
- To systematically review and update existing research on user acceptance of cCBT for depression.
- To identify trends and challenges in evaluating user acceptance of digital mental health tools.
Main Methods:
- Systematic literature review of quantitative and qualitative studies.
- Searched major databases (Web of Science, PubMed, Cochrane Library, PsycINFO) for studies published from July 2007 onward.
- Included studies examining user acceptance, experiences, or satisfaction with cCBT for depression.
Main Results:
- 29 studies were included in the review, with user acceptance operationalized and analyzed heterogeneously.
- A high level of user acceptance was reported in most studies (8 very high, 17 high, 1 moderate).
- Qualitative studies identified both positive and negative aspects influencing user acceptance, alongside methodological shortcomings.
Conclusions:
- cCBT for depression is generally perceived positively by users, indicating its potential as an innovative treatment.
- Methodological challenges persist in defining, operationalizing, and measuring user acceptance of cCBT.
- Further research is needed to standardize methodologies for assessing user acceptance in digital mental health interventions.
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