ArticleInteractive journal of medical research2017
Activity Trackers Implement Different Behavior Change Techniques for Activity, Sleep, and Sedentary Behaviors.
Article in Interactive journal of medical research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 2 of them syntheses that pooled it.
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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.
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Who cites it
34 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Considering User Experience and Behavioral Approaches in the Design of mHealth Interventions for Atrial Fibrillation: Systematic Review.Journal of medical Internet research · 2024Pooled it
- The Implementation of Behavior Change Techniques in mHealth Apps for Sleep: Systematic Review.JMIR mHealth and uHealth · 2022Pooled it
- Effect of commercial wearables and digital behaviour change resources on the physical activity of adolescents attending schools in socio-economically disadvantaged areas: the RAW-PA cluster-randomised controlled trial.The international journal of behavioral nutrition and physical activity · 2021Trial
- Trial
- Effect of Wearable Activity Tracker Social Behaviors on Physical Activity and Exercise Self-Efficacy: Real-World Pilot Study.JMIR formative research · 2026Article
- Patterns and Characteristics of Mobile App Use to Promote Wellness and Manage Illness: Cross-Sectional Study.Journal of medical Internet research · 2026Article
- Photoplethysmography in Diverse Skin Tones: Evaluating Bias in Smartwatch Health Monitoring.Cureus · 2025Review
- Establishing a Consensus-Based Framework for the Use of Wearable Activity Trackers in Health Care: Delphi Study.JMIR mHealth and uHealth · 2024Article
- A Comprehensive Review of Behavior Change Techniques in Wearables and IoT: Implications for Health and Well-Being.Sensors (Basel, Switzerland) · 2024Review
- The Wearable Activity Tracker Checklist for Healthcare (WATCH): a 12-point guide for the implementation of wearable activity trackers in healthcare.The international journal of behavioral nutrition and physical activity · 2024Article
- AI and semantic ontology for personalized activity eCoaching in healthy lifestyle recommendations: a meta-heuristic approach.BMC medical informatics and decision making · 2023Article
- Strategies to Improve Physical Activity and Nutrition Behaviours in Children and Adolescents: A Review.Nutrients · 2023Review
- Validity of Two Consumer Multisport Activity Tracker and One Accelerometer against Polysomnography for Measuring Sleep Parameters and Vital Data in a Laboratory Setting in Sleep Patients.Sensors (Basel, Switzerland) · 2022Article
- Machine learning and ontology in eCoaching for personalized activity level monitoring and recommendation generation.Scientific reports · 2022Article
- A Participatory Design Approach to Develop Visualization of Wearable Actigraphy Data for Health Care Professionals: Case Study in Qatar.JMIR human factors · 2022Article
- Exploring Families' Acceptance of Wearable Activity Trackers: A Mixed-Methods Study.International journal of environmental research and public health · 2022Article
- Smartphone-Based Interventions for Physical Activity Promotion: Scoping Review of the Evidence Over the Last 10 Years.JMIR mHealth and uHealth · 2021Article
- A Home-Based Mobile Health Intervention to Replace Sedentary Time With Light Physical Activity in Older Cancer Survivors: Randomized Controlled Pilot Trial.JMIR cancer · 2021Article
- Analysis of the Behavioral Change and Utility Features of Electronic Activity Monitors.Technologies · 2020Article
- Behavior Change Techniques in Wrist-Worn Wearables to Promote Physical Activity: Content Analysis.JMIR mHealth and uHealth · 2020Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSeveral studies have examined how the implementation of behavior change techniques (BCTs) varies between different activity trackers. However, activity trackers frequently allow tracking of activity, sleep, and sedentary behaviors; yet, it is unknown how the implementation of BCTs differs between these behaviors.
objectiveThe aim of this study was to assess the number and type of BCTs that are implemented by wearable activity trackers (self-monitoring systems) in relation to activity, sleep, and sedentary behaviors and to determine whether the number and type of BCTs differ between behaviors.
methodsThree self-monitoring systems (Fitbit [Charge HR], Garmin [Vivosmart], and Jawbone [UP3]) were each used for a 1-week period in August 2015. Each self-monitoring system was used by two of the authors (MJD and BM) concurrently. The Coventry, Aberdeen, and London-Refined (CALO-RE) taxonomy was used to assess the implementation of 40 BCTs in relation to activity, sleep, and sedentary behaviors. Discrepancies in ratings were resolved by discussion, and interrater agreement in the number of BCTs implemented was assessed using kappa statistics.
resultsInterrater agreement ranged from 0.64 to 1.00. From a possible range of 40 BCTs, the number of BCTs present for activity ranged from 19 (Garmin) to 33 (Jawbone), from 4 (Garmin) to 29 (Jawbone) for sleep, and 0 (Fitbit) to 10 (Garmin) for sedentary behavior. The average number of BCTs implemented was greatest for activity (n=26) and smaller for sleep (n=14) and sedentary behavior (n=6).
conclusionsThe number and type of BCTs implemented varied between each of the systems and between activity, sleep, and sedentary behaviors. This provides an indication of the potential of these systems to change these behaviors, but the long-term effectiveness of these systems to change activity, sleep, and sedentary behaviors remains unknown.
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Registered trials
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