ArticlePLOS digital health2023
Exploring how informed mental health app selection may impact user engagement and satisfaction.
Article in PLOS digital health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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
10 citing papers in PubMed, 20 citations in OpenAlex.
- Minimally Guided App-Based Intervention for Nontreatment-Seeking Psychologically Distressed Adults: Protocol for a Randomized Controlled Trial.JMIR research protocols · 2026Article
- Five years of app evaluation: Insights from a framework in practice - a systematic review on the m-health index and navigation database.Internet interventions · 2025Article
- The evolving field of digital mental health: current evidence and implementation issues for smartphone apps, generative artificial intelligence, and virtual reality.World psychiatry : official journal of the World Psychiatric Association (WPA) · 2025Article
- Developing a standardized framework for evaluating health apps using natural language processing.Scientific reports · 2025Article
- Digital Interventions for People Waitlisted for Mental Health Services: A Needs Assessment and Preference Survey.Practice innovations (Washington, D.C.) · 2025Article
- The impact of neuroscience education therapy, behavioral economics, and digital navigators on patient migraine treatment adherence to a mobile health application: a prospective pilot randomized controlled trial.NPP - digital psychiatry and neuroscience · 2025Article
- The Trifecta of Industry, Academic, and Health System Partnership to Improve Mental Health Care Through Smartphone-Based Remote Patient Monitoring: Development and Usability Study.JMIR formative research · 2025Article
- Feasibility trial of a self-help digital intervention for functional cognitive disorder.Brain communications · 2025Article
- Validation of a Questionnaire to Assess the Usability of and User Experience with Mobile Health Applications.Healthcare (Basel, Switzerland) · 2024Article
- Assessing Digital Phenotyping for App Recommendations and Sustained Engagement: Cohort Study.JMIR formative research · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The prevalence of mental health app use by people suffering from mental health disorders is rapidly growing. The integration of mental health apps shows promise in increasing the accessibility and quality of treatment. However, a lack of continued engagement is one of the significant challenges of such implementation. In response, the M-health Index and Navigation Database (MIND)- derived from the American Psychiatric Association's app evaluation framework- was created to support patient autonomy and enhance engagement. This study aimed to identify factors influencing engagement with mental health apps and explore how MIND may affect user engagement around selected apps. We conducted a longitudinal online survey over six weeks after participants were instructed to find mental health apps using MIND. The survey included demographic information, technology usage, access to healthcare, app selection information, System Usability Scale, the Digital Working Alliance Inventory, and the General Self-Efficacy Scale questions. Quantitative analysis was performed to analyze the data. A total of 321 surveys were completed (178 at the initial, 90 at the 2-week mark, and 53 at the 6-week mark). The most influential factors when choosing mental health apps included cost (76%), condition supported by the app (59%), and app features offered (51%), while privacy and clinical foundation to support app claims were among the least selected filters. The top ten apps selected by participants were analyzed for engagement. Rates of engagement among the top-ten apps decreased by 43% from the initial to week two and 22% from week two to week six on average. In the context of overall low engagement with mental health apps, implementation of mental health app databases like MIND can play an essential role in maintaining higher engagement and satisfaction. Together, this study offers early data on how educational approaches like MIND may help bolster mental health apps engagement.
Identifiers
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.