Assessing the Efficacy of Mobile Health Apps Using the Basic Principles of Cognitive Behavioral Therapy: Systematic Review
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Abstract
BACKGROUND: Cognitive behavioral therapy (CBT) in its basic principle has developed itself as a stand-alone, substantial method of therapy. With effective application in therapy for a range of mental health issues, the spread of CBT methods to Web-based therapy sources is evident. The development of mobile phone apps using CBT principles is increasing within the research area. Despite the move to Web-based methods of therapy, it is argued that these methods lack the same efficacy of face-to-face therapy sessions. OBJECTIVE: The aim of this review was to assess extent research findings with regard to the effectiveness of CBT-related mobile health (mHealth) apps. By assessing only studies employing a randomized controlled trial design, the review aimed to determine app efficacy within the highly regarded method of investigation. METHODS: A comprehensive literature search was conducted across several databases. Search results were filtered, and results were subject to strict inclusion and exclusion criteria because of the nature of the review. Where possible, analysis of effect size was calculated and results reported. RESULTS: A total of 8 studies investigating the effectiveness of mHealth CBT-related apps across a range of mental health issues were reviewed. Three studies used the app against a control group, and 5 studies used the app intervention against another form of treatment or intervention. A range of effect sizes were seen across all included studies (d=-0.13 to 1.83; 0.03-1.44), with the largest effects often being seen when comparing the data from pre- to posttest for the app engaged group. CONCLUSIONS: The studies reviewed support the use of mHealth apps containing CBT principles for a range of mental health issues. However, the effectiveness over longer time periods should be assessed. Researchers and professionals should seek to collaborate effectively when creating new apps to enhance their effectiveness as a treatment for the general public.
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Studies have shown that CBT smartphone apps have therapeutic potential.
“Studies have shown that CBT smartphone apps have therapeutic potential [31]”
From Technology enabled clinical care (TECC): Protocol for a prospective longitudinal cohort study of smartphone-augmented mental health treatment (2021) · cites this paper as [31]
A systematic review of eight randomized controlled trials (n = 1794) investigating psychological outcomes from the use of mHealth apps to manage depression, chronic pain acceptance, insomnia severity, stress or PTSD symptoms showed variations in effect sizes (d = −0.13 to 1.83; 0.03-1.44) with higher engagement associated with improved outcomes.
“A systematic review of eight randomized controlled trials (n = 1794) investigating psychological outcomes from the use of mHealth apps to manage depression, chronic pain acceptance, insomnia severity, stress or PTSD symptoms showed variations in effect sizes (d = −0.13 to 1.83; 0.03–1.44) with higher engagement associated with improved outcomes.”
From What is the clinical value of mHealth for patients? (2020) · cites this paper as [18]
Many mental health applications for emotion regulation training were developed, mainly focused on cognitive change, mindfulness, or cognitive behavioral therapy principles.
“Many mHealth applications for ER training were developed, mainly focused on cognitive change (Beck, 2017), mindfulness (Plaza et al., 2013), or more generally, on cognitive behavioral therapy (CBT) principles (Rathbone et al., 2017).”
From New Technologies for the Understanding, Assessment, and Intervention of Emotion Regulation (2019) · cites this paper as Rathbone et al., 2017
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Mobile App Tools for Identifying and Managing Mental Health Disorders in Primary Care
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Purkayastha, S., Addepally, S. A., & Bucher, S. (2019) · JMIR Human Factors · doi:10.2196/14146 · Cited by 28 · see citing works
Emerging digital technologies in cancer treatment, prevention, and control
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Person, H., & Keefer, L. (2019) · Current Gastroenterology Reports · doi:10.1007/s11894-019-0683-8 · Cited by 24 · see citing works
Meditation and mental health apps: relaxation, yoga, and meditation apps
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Machine Learning Applied to Low Back Pain Rehabilitation – A Systematic Review
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Morello, K., Schäfer, S. K., Kunzler, A. M., Priesterroth, L., Tüscher, O., & Kubiak, T. (2023) · Frontiers in Digital Health · doi:10.3389/fdgth.2023.1253390 · Cited by 23 · see citing works
Usability and feasibility of a cognitive-behavioral mobile app for ADHD in adults
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Tools of Engagement: Practical Considerations for Utilizing Technology-Based Tools in CBT Practice
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Empower Psychotherapy with mHealth Apps: The Design of “Safer”, an Emotion Regulation Application
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Social media use for supporting mental health (SMILE)
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Using Applied Games to Engage mHealth Users
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Digitale Technologien zur Verbesserung der psychischen Gesundheit
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How Does Digital Integration Influence the Mental Health of Low-Income Populations?
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Characteristics and Outcomes of mHealth Interventions in Psychosis: Systematic Mapping Review
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Aplicaciones móviles para ansiedad: una revisión en Argentina
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- Authors
- Rathbone, A. L., Clarry, L., & Prescott, J.
- Affiliations
- University of Greater Manchester (GB)
- Corresponding author
- Prescott, Julie
- Venue
- Journal of Medical Internet Research
- Publisher
- JMIR Publications Inc.
- Published
- 2017-11-28
- Volume
- 19
- Issue
- 11
- Pages
- e399
- ISSN
- 1438-8871 (ISSN-L)
- PMC
- PMC5727354
- OpenAlex
- W2768506072
- Cited by
- 158
- References
- 51
- Citations by year
- 2026: 8 · 2025: 14 · 2024: 18 · 2023: 21 · 2022: 16 · 2021: 25 · 2020: 28 · 2019: 13 · 2018: 15
- FWCI
- 1.79
- 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)
- Research Explorer (The University of Manchester) (publishedVersion, other-oa)
- Lancaster EPrints (Lancaster University) (acceptedVersion)
- UBIR (University of Greater Manchester) (submittedVersion, cc-by)
- UBIR (University of Greater Manchester) (submittedVersion)
- Lancaster EPrints (Lancaster University) (submittedVersion)
- Funders
- University of Bolton
- 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
- mobile health apps, cognitive behavioral therapy, digital mental health interventions, app efficacy, mental illness, effect size, online therapy
- MeSH terms
- Humans, Cognitive Behavioral Therapy, Telemedicine, Mobile Applications
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