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A randomized controlled trial of three smartphone apps for enhancing public mental health
Abstract
Many smartphone applications (apps) for mental health (MHapps) are available to the public. However, few have been the subject of a randomized controlled trial (RCT), and the change processes that are hypothesized to mediate claimed effects have not been previously studied. This RCT compared the efficacy of three publicly available MHapps to a waitlist control condition in a community sample, in which no MHapp was provided. The three MHapps included cognitive behavioural therapy (CBT) toolkit app MoodKit, mood tracking app MoodPrism, and CBT strategy app MoodMission. Participants were randomly allocated to each condition, completed a baseline assessment, downloaded their allocated MHapp, and completed a second assessment 30 days later, with n = 226 included in final analyses (81% female; M age = 34 years). Compared to the control condition, all MHapp groups experienced increases in mental wellbeing, MoodKit and MoodMission groups experienced decreases in depression, and no groups experienced effects on anxiety. Mediated regressions revealed that increasing coping self-efficacy, rather than emotional self-awareness or mental health literacy, was the underlying process contributing to effects on mental health for all three MHapps. MHapps appear to be an effective solution for improving public mental health, notably by improving users' confidence in their ability to cope.
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“The nine research articles [47-55] that examined the 10 apps were made up of seven randomized controlled trials (RCTs)—the Flett et al article contained one RCT with 2 of the listed apps: Headspace and Smiling Mind [52]—and two feasibility or pilot studies: Kinderman et al [48] and Carey et al [55].”
From Apps with maps-anxiety and depression mobile apps with evidence-based frameworks: Systematic search of major app stores (2020) · cites this paper as [50]
In the citing paper
“medical chatbots include Woebot, which proved to relieve feelings of anxiety and depression91, and Moodkit, which recommends chatting and journaling activities through text and voice notes92.”
From Sex and gender differences and biases in artificial intelligence for biomedicine and healthcare (2020) · cites this paper as [92]
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Metadata
- Authors
- Bakker, D., Kazantzis, N., Rickwood, D., & Rickard, N.
- Affiliations
- Monash University (AU)
- University of Canberra (AU)
- The University of Melbourne (AU)
- Corresponding author
- Bakker, David
- Venue
- Behaviour Research and Therapy
- Publisher
- Elsevier BV
- Published
- 2018-10
- Volume
- 109
- Pages
- 75-83
- ISSN
- 0005-7967 (ISSN-L)
- OpenAlex
- W2886788613
- Semantic Scholar
- 89a8706c21548b935dcff42ae032b89e2e7064ab
- Cited by
- 176
- References
- 62
- Citations by year
- 2026: 14 · 2025: 21 · 2024: 24 · 2023: 21 · 2022: 28 · 2021: 30 · 2020: 23 · 2019: 12 · 2018: 3
- FWCI
- 21.47
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Behaviour Research and Therapy (publishedVersion)
- PubMed (publishedVersion)
- 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 › Clinical Psychology › Mindfulness and Compassion Interventions
- Keywords
- mental health apps, mobile application, public mental health, cognitive behavioral therapy, depression, anxiety, psychological well-being, coping self-efficacy, emotional self-awareness, mental health literacy, mediation analysis, digital mental health interventions
- MeSH terms
- Adaptation, Psychological, Adult, Anxiety, Depression, Emotions, Female, Humans, Male, Self-Assessment, Cognitive Behavioral Therapy, Telemedicine, Self Efficacy, Young Adult, Health Literacy, Mobile Applications
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