ReviewJMIR mHealth and uHealth2018
Evaluating the Impact of Physical Activity Apps and Wearables: Interdisciplinary Review.
Review in JMIR mHealth and uHealth, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers, 8 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
56 citing papers in PubMed, 8 syntheses or guidelines pooled it, 144 citations in OpenAlex.
- A Health-Related Digital Ecological Momentary Assessment in Children (Aged 5- 11 Years): Systematic Review.Journal of medical Internet research · 2026Pooled it
- Digital Tools' Effectiveness on Physical Activity Outcomes in Children and Adolescents: Umbrella Review.JMIR public health and surveillance · 2026Pooled it
- Meta-analyses of randomized controlled trials assessing the effect of digital tools on step count and moderate-to-vigorous physical activity in healthy children and adolescents.Frontiers in digital health · 2026Pooled it
- The Use of Wearable Technologies in the Assessment of Physical Activity in Preschool- and School-Age Youth: Systematic Review.International journal of environmental research and public health · 2023Pooled it
- Assessing the Acceptability and Effectiveness of Mobile-Based Physical Activity Interventions for Midlife Women During Menopause: Systematic Review of the Literature.JMIR mHealth and uHealth · 2022Pooled it
- Accuracy and Precision of Consumer-Grade Wearable Activity Monitors for Assessing Time Spent in Sedentary Behavior in Children and Adolescents: Systematic Review.JMIR mHealth and uHealth · 2022Pooled it
- Fitbit-Based Interventions for Healthy Lifestyle Outcomes: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2020Pooled it
- Trends in Persuasive Technologies for Physical Activity and Sedentary Behavior: A Systematic Review.Frontiers in artificial intelligence · 2020Pooled it
- Effect of Active Workstations on Neurocognitive Performance and Typing Skills: A Randomized Clinical Trial.Journal of the American Heart Association · 2024Trial
- Effects of Wearable Fitness Trackers and Activity Adequacy Mindsets on Affect, Behavior, and Health: Longitudinal Randomized Controlled Trial.Journal of medical Internet research · 2023Trial
- 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
- A Social Group-Based Information-Motivation-Behavior Skill Intervention to Promote Acceptability and Adoption of Wearable Activity Trackers Among Middle-Aged and Older Adults: Cluster Randomized Controlled Trial.JMIR mHealth and uHealth · 2020Trial
- Can self-monitoring mobile health apps reduce sedentary behavior? A randomized controlled trial.Journal of occupational health · 2020Trial
- Acceptability and Feasibility of Implementing Accelorometry-Based Activity Monitors and a Linked Web Portal in an Exercise Referral Scheme: Feasibility Randomized Controlled Trial.Journal of medical Internet research · 2019Trial
- Three Body-Worn Accelerometers in the French NutriNet-Santé Cohort: Feasibility and Acceptability Study.JMIR formative research · 2025Article
- Gait Pattern Differences Between Young Adults and Physically Active Older Adults.Medicina (Kaunas, Lithuania) · 2025Article
- Smartphone Apps and Wearables for Health Parameters in Young Adulthood: Cross-Sectional Study.JMIR human factors · 2025Article
- Feasibility and Usability of an Artificial Intelligence-Powered Gamification Intervention for Enhancing Physical Activity Among College Students: Quasi-Experimental Study.JMIR serious games · 2025Article
- From Steps to Context: Optimizing Digital Phenotyping for Physical Activity Monitoring in Older Adults by Integrating Wearable Data and Ecological Momentary Assessment.Sensors (Basel, Switzerland) · 2025Article
- A social media game to increase physical activity among older adult women: protocol of a randomized controlled trial to evaluate CHALLENGE.BMC public health · 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
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAlthough many smartphone apps and wearables have been designed to improve physical activity, their rapidly evolving nature and complexity present challenges for evaluating their impact. Traditional methodologies, such as randomized controlled trials (RCTs), can be slow. To keep pace with rapid technological development, evaluations of mobile health technologies must be efficient. Rapid alternative research designs have been proposed, and efficient in-app data collection methods, including in-device sensors and device-generated logs, are available. Along with effectiveness, it is important to measure engagement (ie, users' interaction and usage behavior) and acceptability (ie, users' subjective perceptions and experiences) to help explain how and why apps and wearables work.
objectivesThis study aimed to (1) explore the extent to which evaluations of physical activity apps and wearables: employ rapid research designs; assess engagement, acceptability, as well as effectiveness; use efficient data collection methods; and (2) describe which dimensions of engagement and acceptability are assessed.
methodAn interdisciplinary scoping review using 8 databases from health and computing sciences. Included studies measured physical activity, and evaluated physical activity apps or wearables that provided sensor-based feedback. Results were analyzed using descriptive numerical summaries, chi-square testing, and qualitative thematic analysis.
resultsA total of 1829 abstracts were screened, and 858 articles read in full. Of 111 included studies, 61 (55.0%) were published between 2015 and 2017. Most (55.0%, 61/111) were RCTs, and only 2 studies (1.8%) used rapid research designs: 1 single-case design and 1 multiphase optimization strategy. Other research designs included 23 (22.5%) repeated measures designs, 11 (9.9%) nonrandomized group designs, 10 (9.0%) case studies, and 4 (3.6%) observational studies. Less than one-third of the studies (32.0%, 35/111) investigated effectiveness, engagement, and acceptability together. To measure physical activity, most studies (90.1%, 101/111) employed sensors (either in-device [67.6%, 75/111] or external [23.4%, 26/111]). RCTs were more likely to employ external sensors (accelerometers: P=.005). Studies that assessed engagement (52.3%, 58/111) mostly used device-generated logs (91%, 53/58) to measure the frequency, depth, and length of engagement. Studies that assessed acceptability (57.7%, 64/111) most often used questionnaires (64%, 42/64) and/or qualitative methods (53%, 34/64) to explore appreciation, perceived effectiveness and usefulness, satisfaction, intention to continue use, and social acceptability. Some studies (14.4%, 16/111) assessed dimensions more closely related to usability (ie, burden of sensor wear and use, interface complexity, and perceived technical performance).
conclusionsThe rapid increase of research into the impact of physical activity apps and wearables means that evaluation guidelines are urgently needed to promote efficiency through the use of rapid research designs, in-device sensors and user-logs to assess effectiveness, engagement, and acceptability. Screening articles was time-consuming because reporting across health and computing sciences lacked standardization. Reporting guidelines are therefore needed to facilitate the synthesis of evidence across disciplines.
Indexed as
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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.