ArticleJMIR mHealth and uHealth2015
Validation of Physical Activity Tracking via Android Smartphones Compared to ActiGraph Accelerometer: Laboratory-Based and Free-Living Validation Studies.
Article in JMIR mHealth and uHealth, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 54 papers, 1 of them a synthesis 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
54 citing papers in PubMed, 1 synthesis or guideline pooled it, 144 citations in OpenAlex.
- Physical inactivity in chronic airways disease: an important candidate in the treatable traits paradigm.European respiratory review : an official journal of the European Respiratory Society · 2026Pooled it
- An mHealth Intervention Promoting Physical Activity to Reduce Psychological Distress Among Workers: Randomized Controlled Trial.Journal of medical Internet research · 2026Trial
- An Evaluation of the Effect of App-Based Exercise Prescription Using Reinforcement Learning on Satisfaction and Exercise Intensity: Randomized Crossover Trial.JMIR mHealth and uHealth · 2024Trial
- Which Components of a Smartphone Walking App Help Users to Reach Personalized Step Goals? Results From an Optimization Trial.Annals of behavioral medicine : a publication of the Society of Behavioral Medicine · 2020Trial
- Can self-monitoring mobile health apps reduce sedentary behavior? A randomized controlled trial.Journal of occupational health · 2020Trial
- Trial
- Trial
- Placement-Dependent Accuracy of a Smartphone-Based Sensor Application Compared to an Accelerometer-Based System for Measuring Physical Activity in Healthy Adults: A Validation Study.Sensors (Basel, Switzerland) · 2026Article
- Article
- App-Recorded Daily Step Counts, Sex Differences, and Risk of Cardiovascular Outcomes Among Middle-Aged Population.Journal of the American Heart Association · 2025Article
- Identifying factors impacting missingness within smartphone-based research: Implications for intensive longitudinal studies of adolescent suicidal thoughts and behaviors.Journal of psychopathology and clinical science · 2024Article
- Would the Actigraph Always be Sufficient for Sleep Analysis in Exercise-Based Studies? A Case Report of Negative Response of Sleep to Exercise.Sleep science (Sao Paulo, Brazil) · 2023Article
- SNapp, a Tailored Smartphone App Intervention to Promote Walking in Adults of Low Socioeconomic Position: Development and Qualitative Pilot Study.JMIR formative research · 2023Article
- Contextual and environmental factors that influence health: A within-subjects field experiment protocol.Frontiers in public health · 2023Article
- The effect of temperature on physical activity: an aggregated timeseries analysis of smartphone users in five major Chinese cities.The international journal of behavioral nutrition and physical activity · 2022Article
- Accuracy of steps measured by smartphones-based WeRun compared with ActiGraph-GT3X accelerometer in free-living conditions.Frontiers in public health · 2022Article
- What Happened Pre- and during COVID-19 in South Korea? Comparing Physical Activity, Sleep Time, and Body Weight Status.International journal of environmental research and public health · 2021Article
- Physical Activity Behavior Before, During, and After COVID-19 Restrictions: Longitudinal Smartphone-Tracking Study of Adults in the United Kingdom.Journal of medical Internet research · 2021Article
- A Smartphone App to Support Sedentary Behavior Change by Visualizing Personal Mobility Patterns and Action Planning (SedVis): Development and Pilot Study.JMIR formative research · 2021Article
- Smartphone App (2kmFIT-App) for Measuring Cardiorespiratory Fitness: Validity and Reliability Study.JMIR mHealth and uHealth · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 2 countries.
Funding
Abstract
backgroundThere is increasing interest in using smartphones as stand-alone physical activity monitors via their built-in accelerometers, but there is presently limited data on the validity of this approach.
objectiveThe purpose of this work was to determine the validity and reliability of 3 Android smartphones for measuring physical activity among midlife and older adults.
methodsA laboratory (study 1) and a free-living (study 2) protocol were conducted. In study 1, individuals engaged in prescribed activities including sedentary (eg, sitting), light (sweeping), moderate (eg, walking 3 mph on a treadmill), and vigorous (eg, jogging 5 mph on a treadmill) activity over a 2-hour period wearing both an ActiGraph and 3 Android smartphones (ie, HTC MyTouch, Google Nexus One, and Motorola Cliq). In the free-living study, individuals engaged in usual daily activities over 7 days while wearing an Android smartphone (Google Nexus One) and an ActiGraph.
resultsStudy 1 included 15 participants (age: mean 55.5, SD 6.6 years; women: 56%, 8/15). Correlations between the ActiGraph and the 3 phones were strong to very strong (ρ=.77-.82). Further, after excluding bicycling and standing, cut-point derived classifications of activities yielded a high percentage of activities classified correctly according to intensity level (eg, 78%-91% by phone) that were similar to the ActiGraph's percent correctly classified (ie, 91%). Study 2 included 23 participants (age: mean 57.0, SD 6.4 years; women: 74%, 17/23). Within the free-living context, results suggested a moderate correlation (ie, ρ=.59, P<.001) between the raw ActiGraph counts/minute and the phone's raw counts/minute and a strong correlation on minutes of moderate-to-vigorous physical activity (MVPA; ie, ρ=.67, P<.001). Results from Bland-Altman plots suggested close mean absolute estimates of sedentary (mean difference=-26 min/day of sedentary behavior) and MVPA (mean difference=-1.3 min/day of MVPA) although there was large variation.
conclusionsOverall, results suggest that an Android smartphone can provide comparable estimates of physical activity to an ActiGraph in both a laboratory-based and free-living context for estimating sedentary and MVPA and that different Android smartphones may reliably confer similar estimates.
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.