SynthesisJMIR mHealth and uHealth2019
The App Behavior Change Scale: Creation of a Scale to Assess the Potential of Apps to Promote Behavior Change.
Synthesis in JMIR mHealth and uHealth, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 61 papers, 9 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
61 citing papers in PubMed, 9 syntheses or guidelines pooled it.
- Quality and Multifunctionality in Mobile Apps for Gestational Diabetes: Systematic App Review.JMIR mHealth and uHealth · 2026Pooled it
- Smartphone application-based interventions for cardiometabolic risk factor management: A systematic review and meta-analysis.Hypertension research : official journal of the Japanese Society of Hypertension · 2026Pooled it
- The Landscape of Mobile Apps for Healthy Eating: Case Study for a Systematic Review and Quality Assessment.JMIR mHealth and uHealth · 2026Pooled it
- Assessing the Quality and Behavior Change Potential of Vaping Cessation Apps: Systematic Search and Assessment.JMIR mHealth and uHealth · 2024Pooled it
- Evaluation of Patient-Facing Mobile Apps to Support Physiotherapy Care: Systematic Review.JMIR mHealth and uHealth · 2024Pooled it
- Design Features Associated With Engagement in Mobile Health Physical Activity Interventions Among Youth: Systematic Review of Qualitative and Quantitative Studies.JMIR mHealth and uHealth · 2023Pooled it
- Digital interventions for the management of chronic obstructive pulmonary disease.The Cochrane database of systematic reviews · 2021Pooled it
- Effectiveness of Mobile Apps to Promote Health and Manage Disease: Systematic Review and Meta-analysis of Randomized Controlled Trials.JMIR mHealth and uHealth · 2021Pooled it
- Using Health and Well-Being Apps for Behavior Change: A Systematic Search and Rating of Apps.JMIR mHealth and uHealth · 2019Pooled it
- Trial
- Selecting and Evaluating Mobile Health Apps for the Healthy Life Trajectories Initiative: Development of the eHealth Resource Checklist.JMIR mHealth and uHealth · 2021Trial
- Efficacy of a Just-in-Time Adaptive Intervention to Promote HIV Risk Reduction Behaviors Among Young Adults Experiencing Homelessness: Pilot Randomized Controlled Trial.Journal of medical Internet research · 2021Trial
- Arabic Wellness Apps in the MENA Region and Saudi Arabia: Current Evidence and Systematic Evaluation.Healthcare (Basel, Switzerland) · 2026Article
- Lived Experiences of Older Adults Using Wearables With Real-Time Feedback: Phenomenological Study.JMIR mHealth and uHealth · 2026Article
- Supporting Mental Health with Apps: A Systematic Review of Potential and Quality of Implemented Behavior Change Techniques in Mobile Health Applications.European journal of investigation in health, psychology and education · 2026Review
- Personalizing mobile applications for health based on user profiles: A preference matrix from a scoping review.PLOS digital health · 2025Review
- Promoting active transportation through technology: a scoping review of mobile apps for walking and cycling.BMC public health · 2025Article
- Health professionals' use of smartphone apps for clients with low back pain: an observational study.Primary health care research & development · 2025Observational
- Evaluating the Knowledge Level, Practice, and Behavioral Change Potential of Care Managers in Pressure Injury Prevention Using a Mobile App Prototyping Model in the Home-Care Setting: Single-Arm, Pre-Post Pilot Study.JMIR formative research · 2025Article
- Developing an Evidence- and Theory-Informed Mother-Daughter mHealth Intervention Prototype Targeting Physical Activity in Preteen Girls of Low Socioeconomic Position: Multiphase Co-Design Study.JMIR pediatrics and parenting · 2025Article
1 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundUsing mobile phone apps to promote behavior change is becoming increasingly common. However, there is no clear way to rate apps against their behavior change potential.
objectiveThis study aimed to develop a reliable, theory-based scale that can be used to assess the behavior change potential of smartphone apps.
methodsA systematic review of all studies purporting to investigate app's behavior change potential was conducted. All scales and measures from the identified studies were collected to create an item pool. From this item pool, 3 health promotion exerts created the App Behavior Change Scale (ABACUS). To test the scale, 70 physical activity apps were rated to provide information on reliability.
resultsThe systematic review returned 593 papers, the abstracts and titles of all were reviewed, with the full text of 77 papers reviewed; 50 papers met the inclusion criteria. From these 50 papers, 1333 questions were identified. Removing duplicates and unnecessary questions left 130 individual questions, which were then refined into the 21-item scale. The ABACUS demonstrates high percentage agreement among reviewers (over 80%), with 3 questions scoring a Krippendorff alpha that would indicate agreement and a further 7 came close with alphas >.5. The scale overall reported high interrater reliability (2-way mixed interclass coefficient=.92, 95% CI 0.81-0.97) and high internal consistency (Cronbach alpha=.93).
conclusionsThe ABACUS is a reliable tool that can be used to determine the behavior change potential of apps. This instrument fills a gap by allowing the evaluation of a large number of apps to be standardized across a range of health categories.
Indexed as
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.