ReviewJournal of medical Internet research2021
Self-guided Cognitive Behavioral Therapy Apps for Depression: Systematic Assessment of Features, Functionality, and Congruence With Evidence.
Review in Journal of medical Internet research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 6 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
34 citing papers in PubMed, 6 syntheses or guidelines pooled it, 59 citations in OpenAlex.
- Evaluating Characteristics and Quality of Mental Health Apps Available in App Stores for Indian Users: Systematic App Search and Review.JMIR mHealth and uHealth · 2025Pooled it
- Could the use of web-based applications assist in neuropsychiatric treatment? An umbrella review.BMC psychology · 2025Pooled it
- Initial Requirements for the Prototyping of an App for a Psychosocial Rehabilitation Project: An Integrative Review.International journal of environmental research and public health · 2025Pooled it
- Bibliometric analysis of trends, innovations, and the future of CBT-based mobile interventions for depression.Frontiers in medicine · 2025Pooled it
- Self-Management Support Apps for Spinal Cord Injury: Results of a Systematic Search in App Stores and Mobile App Rating Scale Evaluation.JMIR mHealth and uHealth · 2024Pooled it
- Scope, Characteristics, Behavior Change Techniques, and Quality of Conversational Agents for Mental Health and Well-Being: Systematic Assessment of Apps.Journal of medical Internet research · 2023Pooled it
- Facilitating Thought Progression to Reduce Depressive Symptoms: Randomized Controlled Trial.Journal of medical Internet research · 2024Trial
- Preliminary Efficacy of a Digital Intervention for Adolescent Depression: Randomized Controlled Trial.Journal of medical Internet research · 2024Trial
- Effectiveness of Mental Health Apps for Distress During COVID-19 in US Unemployed and Essential Workers: Remote Pragmatic Randomized Clinical Trial.JMIR mHealth and uHealth · 2022Trial
- Integration of cognitive behavioral therapy and mobile health applications among university students with depression: a qualitative study.International journal of qualitative studies on health and well-being · 2026Article
- Mobile Apps for Tinnitus: Systematic Search in App Stores and Review of Intervention Components and Behavior Change Techniques.JMIR mHealth and uHealth · 2026Article
- Identifying Evidence-Based Strategies in a Digital Mental Health Intervention for Depression: Qualitative Content Analysis.Journal of medical Internet research · 2026Article
- A framework for culturally adapting mental mHealth apps.Frontiers in digital health · 2026Article
- Multimodal Sensing-Enabled Large Language Models for Automated Emotional Regulation: A Review of Current Technologies, Opportunities, and Challenges.Sensors (Basel, Switzerland) · 2025Review
- Just-in-Time Delivery of Cognitive Behavioral Therapy-Based Exercises: Single-Case Experimental Design With Random Multiple Baselines.JMIR formative research · 2025Article
- Development of the Psychosocial Rehabilitation Web Application (Psychosocial Rehab App).Nursing reports (Pavia, Italy) · 2025Article
- Classifying the features of digital mental health interventions to inform the development of a patient decision aid.PLOS digital health · 2025Review
- Provider Perspectives on the Use of Mental Health Apps, and the BritePath App in Particular, With Adolescents at Risk for Suicidal Behavior: Qualitative Study.JMIR human factors · 2025Article
- Depression Self-Care Apps' Characteristics and Applicability to Older Adults: Systematic Assessment.Journal of medical Internet research · 2025Article
- The Goldilocks Zone: Finding the right balance of user and institutional risk for suicide-related generative AI queries.PLOS digital health · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 3 institutions in 3 countries.
Funding
Abstract
backgroundMental health disorders affect 1 in 10 people globally, of whom approximately 300 million are affected by depression. At least half of the people affected by depression remain untreated. Although cognitive behavioral therapy (CBT) is an effective treatment, access to mental health specialists, habitually challenging, has worsened because of the COVID-19 pandemic. Internet-based CBT is an effective and feasible strategy to increase access to treatment for people with depression. Mental health apps may further assist in facilitating self-management for people affected by depression; however, accessing the correct app may be cumbersome given the large number and wide variety of apps offered by public app marketplaces.
objectiveThis study aims to systematically assess the features, functionality, data security, and congruence with evidence of self-guided CBT-based apps targeting users affected by depression that are available in major app stores.
methodsWe conducted a systematic assessment of self-guided CBT-based apps available in Google Play and the Apple App Store. Apps launched or updated since August 2018 were identified through a systematic search in the 42matters database using CBT-related terms. Apps meeting the inclusion criteria were downloaded and assessed using a Samsung Galaxy J7 Pro (Android 9) and iPhone 7 (iOS 13.3.1). Apps were appraised using a 182-question checklist developed by the research team, assessing their general characteristics, technical aspects and quality assurance, and CBT-related features, including 6 evidence-based CBT techniques (ie, psychoeducation, behavioral activation, cognitive restructuring, problem solving, relaxation, and exposure for comorbid anxiety) as informed by a CBT manual, CBT competence framework, and a literature review of internet-based CBT clinical trial protocols. The results were reported as a narrative review using descriptive statistics.
resultsThe initial search yielded 3006 apps, of which 98 met the inclusion criteria and were systematically assessed. There were 20 well-being apps; 65 mental health apps, targeting two or more common mental health disorders, including depression; and 13 depression apps. A total of 28 apps offered at least four evidence-based CBT techniques, particularly depression apps. Cognitive restructuring was the most common technique, offered by 79% (77/98) of the apps. Only one-third of the apps offered suicide risk management resources, whereas 17% (17/98) of the apps offered COVID-19-related information. Although most apps included a privacy policy, only a third of the apps presented it before account creation. In total, 82% (74/90) of privacy policies stated sharing data with third-party service providers. Half of the app development teams included academic institutions or health care providers.
conclusionsOnly a few self-guided CBT-based apps offer comprehensive CBT programs or suicide risk management resources. Sharing of users' data is widespread, highlighting shortcomings in health app market governance. To fulfill their potential, self-guided CBT-based apps should follow evidence-based clinical guidelines, be patient centered, and enhance users' data security.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.