The DOI matches its Crossref record; 27 of the 27 references it cites were found in a registry or an index.
Effectiveness of activity trackers with and without incentives to increase physical activity (TRIPPA): a randomised controlled trial
Abstract
Background Despite the increasing popularity of activity trackers, little evidence exists that they can improve health outcomes. We aimed to investigate whether use of activity trackers, alone or in combination with cash incentives or charitable donations, lead to increases in physical activity and improvements in health outcomes.Methods In this randomised controlled trial, employees from 13 organisations in Singapore were randomly assigned (1:1:1:1) with a computer generated assignment schedule to control (no tracker or incentives), Fitbit Zip activity tracker, tracker plus charity incentives, or tracker plus cash incentives. Participants had to be English speaking, full-time employees, aged 21-65 years, able to walk at least ten steps continuously, and non-pregnant. Incentives were tied to weekly steps, and the primary outcome, moderate-to-vigorous physical activity (MVPA) bout min per week, was measured via a sealed accelerometer and assessed on an intention-to-treat basis at 6 months (end of intervention) and 12 months (after a 6 month post-intervention follow-up period). Other outcome measures included steps, participants meeting 70 000 steps per week target, and health-related outcomes including weight, blood pressure, and quality-of-life measures. This trial is registered at ClinicalTrials.gov, number NCT01855776.Findings Between June 13, 2013, and Aug 15, 2014, 800 participants were recruited and randomly assigned to the control (n=201), Fitbit (n=203), charity (n=199), and cash (n=197) groups. At 6 months, compared with control, the cash group logged an additional 29 MVPA bout min per week (95% CI 10-47; p=0·0024) and the charity group an additional 21 MVPA bout min per week (2-39; p=0·0310); the difference between Fitbit only and control was not significant (16 MVPA bout min per week [-2 to 35; p=0·0854]). Increases in MVPA bout min per week in the cash and charity groups were not significantly greater than that of the Fitbit group. At 12 months, the Fitbit group logged an additional 37 MVPA bout min per week (19-56; p=0·0001) and the charity group an additional 32 MVPA bout min per week (12-51; p=0·0013) compared with control; the difference between cash and control was not significant (15 MVPA bout min per week [-5 to 34; p=0·1363]). A decrease in physical activity of -23 MVPA bout min per week (95% CI -42 to -4; p=0·0184) was seen when comparing the cash group with the Fitbit group. There were no improvements in any health outcomes (weight, blood pressure, etc) at either assessment.Interpretation The cash incentive was most effective at increasing MVPA bout min per week at 6 months, but this effect was not sustained 6 months after the incentives were discontinued. At 12 months, the activity tracker with or without charity incentives were effective at stemming the reduction in MVPA bout min per week seen in the control group, but we identified no evidence of improvements in health outcomes, either with or without incentives, calling into question the value of these devices for health promotion. Although other incentive strategies might generate greater increases in step activity and improvements in health outcomes, incentives would probably need to be in place long term to avoid any potential decrease in physical activity resulting from discontinuation.Funding Ministry of Health, Singapore.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Moreover, 17 studies reported activity tracker adherence data [21,22,30,32,34,35, 37,38,40,41,43-45,50-52,54], with 13 of these studies [21,22,30,34,35,40,41,43,44,50-52,54] reporting activity tracker wear on at least 50% of the study intervention days.”
From Consumer-based wearable activity trackers increase physical activity participation: systematic review and meta-analysis (2019) · cites this paper as [34]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“In addition, 4 studies included either an unstructured follow-up phase [34,42] or additional intervention phase utilizing a nonblinded activity tracker for all participants [41,50].”
From Consumer-based wearable activity trackers increase physical activity participation: systematic review and meta-analysis (2019) · cites this paper as [34]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“A total of 26 studies were included across all meta-analyses [21,22,29-48,50-53].”
From Consumer-based wearable activity trackers increase physical activity participation: systematic review and meta-analysis (2019) · cites this paper as [34]
The cited source says what the claim attributes to it.
In the citing paper
“Thirteen studies included young adults (≤39.9 years) [30-34,37,38,42,44,46-48,50], 15 included middle-aged adults (40-64.9 years) [21,22,29,35,36,39-41, 43,45,51-54], and 1 study included adults aged over 65 years [49].”
From Consumer-based wearable activity trackers increase physical activity participation: systematic review and meta-analysis (2019) · cites this paper as [34]
The cited source says what the claim attributes to it.
In the citing paper
“Overall, 8 studies included more than 1 intervention group [34,43,45-47,52-54].”
From Consumer-based wearable activity trackers increase physical activity participation: systematic review and meta-analysis (2019) · cites this paper as [34]
The cited source says what the claim attributes to it.
In the citing paper
“Two of the included studies [34,44] reported a significant increase in daily steps, 4 studies [30,34,36,53] reported a significant increase in MVPA, and 2 studies [45,47] reported a significant increase in energy expenditure for the intervention group compared with control.”
From Consumer-based wearable activity trackers increase physical activity participation: systematic review and meta-analysis (2019) · cites this paper as [34]
In the citing paper
“PA interventions did not show long-term behavioural changes or did not improve clinical outcomes”
From Smart wearable devices in cardiovascular care: Where we are and how to move forward (2021) · cites this paper as [44]
In the citing paper
“Moreover, despite the improvement in MVPA at 12 months with activity tracking, with or without incentives, these findings did not translate into an improvement in health outcomes, such as weight and BP reduction, at 12 months.”
From Smart wearable devices in cardiovascular care: Where we are and how to move forward (2021) · cites this paper as [44]
In the citing paper
“The trial showed that a cash incentive was most effective at increasing MVPA at 6 months, but this effect was not sustained 6 months after the removal of incentives.”
From Smart wearable devices in cardiovascular care: Where we are and how to move forward (2021) · cites this paper as [44]
In the citing paper
“Therefore, the use of behavioural economics and cognitive psychology to develop novel social and financial incentives can potentially sustain good habits, especially when initiated at a very young age44.”
From Smart wearable devices in cardiovascular care: Where we are and how to move forward (2021) · cites this paper as [44]
In the citing paper
“As mentioned previously, a trial with 800 participants questioned the value of wearables in sustaining long-term behavioural changes and improving clinical outcomes44.”
From Smart wearable devices in cardiovascular care: Where we are and how to move forward (2021) · cites this paper as [44]
In the citing paper
“Sedentary behavior was measured objectively, except in two studies [82,104] that utilized a self-reported questionnaire to obtain daily sitting time or sedentary behavior.”
From Fitbit-based interventions for healthy lifestyle outcomes: systematic review and meta-analysis (2020) · cites this paper as [82]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Statistical power analysis for the behavioral sciences
Cohen, J. (1990) · Computers Environment and Urban Systems · doi:10.1016/0198-9715(90)90050-4 · Cited by 65,417
(1980) · Medical Entomology and Zoology · Cited by 25,810
Statistical Power Analysis for the Behavioral Sciences
Cohen, J. (2013) · doi:10.4324/9780203771587 · Cited by 25,373
Multiple Imputation for Nonresponse in Surveys
Rubin, D. B. (1987) · Wiley Series in Probability and Statistics · doi:10.1002/9780470316696 · Cited by 20,701
EuroQol: a new facility for the measurement of health-related quality of life
(1990) · Health Policy · doi:10.1016/0168-8510(90)90421-9 · Cited by 15,736
Lee, I.-M., Shiroma, E. J., Lobelo, F., Puska, P., Blair, S. N., & Katzmarzyk, P. T. (2012) · The Lancet · doi:10.1016/s0140-6736(12)61031-9 · Cited by 8,215
Physical Activity in the United States Measured by Accelerometer
TROIANO, R. P., BERRIGAN, D., DODD, K. W., MÂSSE, L. C., TILERT, T., & MCDOWELL, M. (2008) · Medicine & Science in Sports & Exercise · doi:10.1249/mss.0b013e31815a51b3 · Cited by 7,638
Using Pedometers to Increase Physical Activity and Improve Health: A Systematic Review
Bravata, D. M., Smith-Spangler, C., Sundaram, V., Gienger, A. L., Lin, N., Lewis, R., Stave, C. D., Olkin, I., & Sirard, J. R. (2007) · JAMA · doi:10.1001/jama.298.19.2296 · Cited by 2,064
Revision of the Physical Activity Readiness Questionnaire (PAR-Q).
Thomas, S. G., Reading, J., & Shephard, R. J. (1992) · PubMed · Cited by 1,952
Validation and comparison of ActiGraph activity monitors
Sasaki, J. E., John, D., & Freedson, P. S. (2011) · Journal of Science and Medicine in Sport · doi:10.1016/j.jsams.2011.04.003 · Cited by 1,317
Cited by
Sorted by citations
Items 101–200 of 401
Changing Behavior Using Integrated Theories
Hagger, M. S., & Hamilton, K. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108677318.015 · Cited by 44
Yao, J., Lim, N., Tan, J., Müller, A. M., van Dam, R. M., Chen, C., Tan, C. S., & Müller‐Riemenschneider, F. (2022) · Journal of the American Heart Association · doi:10.1161/jaha.121.022508 · Cited by 35
Failing to encourage physical activity with wearable technology: what next?
Ellis, D. A., & Piwek, L. (2018) · Journal of the Royal Society of Medicine · doi:10.1177/0141076818788856 · Cited by 34
Redfern, J. (2019) · Clinics in Geriatric Medicine · doi:10.1016/j.cger.2019.07.004 · Cited by 38
Chatterjee, A., Pahari, N., Prinz, A., & Riegler, M. A. (2022) · Scientific Reports · doi:10.1038/s41598-022-24118-4 · Cited by 34
Ni, M. Y., Hui, R. W., Li, T. K., Tam, A. H. M., Choy, L. Y. L., Kitty, K. W., Cheung, F., & Leung, G. M. (2018) · Games for Health Journal · doi:10.1089/g4h.2017.0181 · Cited by 34
The impact of short-term incentives on physical activity in a UK behavioural incentives programme
Hajat, C., Hasan, A., Subel, S., & Noach, A. (2019) · npj Digital Medicine · doi:10.1038/s41746-019-0164-3 · Cited by 33
Johnson, A. M., Baker, K. S., Haviland, M. J., Syrjala, K. L., Abbey‐Lambertz, M., Chow, E. J., & Mendoza, J. A. (2021) · Journal of Adolescent and Young Adult Oncology · doi:10.1089/jayao.2021.0056 · Cited by 34
Changing Behavior Using the Transtheoretical Model
DiClemente, C. C., & Graydon, M. M. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108677318.010 · Cited by 35
Changing Behavior Using the Health Belief Model and Protection Motivation Theory
Orbell, S., Zahid, H., & Henderson, C. J. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108677318.004 · Cited by 35
The Potential of Object-Relations Theory for Improving Engagement With Health Apps
Cohen, J., & Torous, J. (2019) · JAMA · doi:10.1001/jama.2019.17141 · Cited by 29
Activity Tracker–Based Metrics as Digital Markers of Cardiometabolic Health: Cross-Sectional Study
Rykov, Y., Thach, T.-Q., Dunleavy, G., Roberts, A. C., Christopoulos, G., Soh, C. K., & Car, J. (2020) · JMIR mHealth and uHealth · doi:10.2196/16409 · Cited by 29
Solomon, T. P. J., Eves, F. F., & Laye, M. J. (2018) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2018.00099 · Cited by 31
Riffenburg, K. M., & Spartano, N. L. (2018) · Current Opinion in Endocrinology Diabetes and Obesity · doi:10.1097/med.0000000000000433 · Cited by 30
Cresswell, K. M., McKinstry, B., Wolters, M. K., Shah, A. S. V., & Sheikh, A. (2018) · BMJ Health & Care Informatics · doi:10.14236/jhi.v25i4.1068 · Cited by 35
Staying Active While Staying Home: The Use of Physical Activity Technologies During Life Disruptions
Newbold, J. W., Rudnicka, A., & Cox, A. L. (2021) · Frontiers in Digital Health · doi:10.3389/fdgth.2021.753115 · Cited by 32
Breteler, M. J. M., Janssen, J. H., Spiering, W., Kalkman, C. J., van Solinge, W. W., & Dohmen, D. (2019) · JMIR Formative Research · doi:10.2196/11489 · Cited by 29
Hafner, M., Pollard, J., & Stolk, C. V. (2018) · Rand health quarterly · doi:10.7249/rhq-09-01-04 · Cited by 29
Rouyard, T., Yoda, E., Akksilp, K., Dieterich, A. V., Sarin, K. C., Dabak, S. V., & Müller, A. M. (2025) · The Lancet Public Health · doi:10.1016/s2468-2667(25)00038-6 · Cited by 34
Changing Behavior by Changing Environments
Marteau, T. M., Fletcher, P. C., Hollands, G. J., & Munafo, M. R. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108677318.014 · Cited by 32
The Role of Behavioral Economics in Improving Cardiovascular Health Behaviors and Outcomes
Hare, A. J., Patel, M. S., Volpp, K. G. M., & Adusumalli, S. (2021) · Current Cardiology Reports · doi:10.1007/s11886-021-01584-2 · Cited by 28
Short, K. R., Chadwick, J. Q., Cannady, T. K., Branam, D. E., Wharton, D. F., Tullier, M. A., Thompson, D. M., & Copeland, K. C. (2018) · PLoS ONE · doi:10.1371/journal.pone.0198390 · Cited by 28
Lennefer, T., Lopper, E., Wiedemann, A. U., Heß, U., & Hoppe, A. (2019) · Journal of Occupational Health Psychology · doi:10.1037/ocp0000169 · Cited by 27
Policy Implications of Artificial Intelligence and Machine Learning in Diabetes Management
Broome, D. T., Hilton, C. B., & Mehta, N. (2020) · Current Diabetes Reports · doi:10.1007/s11892-020-1287-2 · Cited by 27
Chew, L., Tavitian‐Exley, I., Lim, N., & Ong, A. C. L. (2021) · BMC Public Health · doi:10.1186/s12889-020-10092-x · Cited by 26
Wong, S. H., Tan, Z. Y. A., Cheng, L. J., & Lau, S. T. (2021) · International Journal of Nursing Studies · doi:10.1016/j.ijnurstu.2021.104163 · Cited by 29
Worley, V., Fraser, P., Allender, S. E., & Bolton, K. A. (2022) · BMC Health Services Research · doi:10.1186/s12913-021-07418-9 · Cited by 28
A Cluster-Randomized Trial on Small Incentives to Promote Physical Activity
Kramer, J.-N., Tinschert, P., Scholz, U., Fleisch, E., & Kowatsch, T. (2018) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2018.09.018 · Cited by 29
Nelson, S. H., Weiner, L. S., Natarajan, L., Parker, B. A., Patterson, R. E., & Hartman, S. J. (2019) · Translational Behavioral Medicine · doi:10.1093/tbm/ibz079 · Cited by 27
Design, Implementation, and Evaluation of Behavior Change Interventions: A Ten-Task Guide
Abraham, C., & Denford, S. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108677318.019 · Cited by 27
Changing Behavior Using the Reflective-Impulsive Model
Deutsch, R., & Strack, F. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108677318.012 · Cited by 30
Laranjo, L., Quiroz, J. C., Tong, H. L., Bazalar, M. A., & Coiera, E. W. (2020) · Journal of Medical Internet Research · doi:10.2196/19991 · Cited by 31
Exercise in Obesity—the Role of Technology in Health Services: Can This Approach Work?
Dobbie, L. J., Tahrani, A. A., Alam, U., James, J., Wilding, J. P. H., & Cuthbertson, D. J. (2021) · Current Obesity Reports · doi:10.1007/s13679-021-00461-x · Cited by 26
Byun, W., Lee, J. M., Kim, Y., & Brusseau, T. A. (2018) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph15040594 · Cited by 25
Well-being and Long-term Physical Activity Participation in Midlife Adults: A Latent Class Analysis
Rector, J. L., Christ, S. L., & Friedman, E. M. (2018) · Annals of Behavioral Medicine · doi:10.1093/abm/kay016 · Cited by 30
Orstad, S. L., Gerchow, L., Patel, N., Reddy, M., Hernandez, C., Wilson, D. K., & Jay, M. R. (2021) · Informatics · doi:10.3390/informatics8020039 · Cited by 28
Melia, R., Monahan, L., Duggan, J., Bogue, J., O’Sullivan, M., Young, K. L., Chambers, D., & McInerney, S. J. (2021) · BMC Psychiatry · doi:10.1186/s12888-021-03426-5 · Cited by 25
Dyadic Behavior Change Interventions
Scholz, U., Berli, C., Lüscher, J., & Knoll, N. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108677318.043 · Cited by 26
Alley, S., Schöeppe, S., To, Q. G., Parkinson, L., van Uffelen, J. G. Z., Hunt, S., Duncan, M. J., Schneiders, A. G., & Vandelanotte, C. (2023) · International Journal of Behavioral Nutrition and Physical Activity · doi:10.1186/s12966-023-01406-4 · Cited by 27
Losina, E., Smith, S. R., Usiskin, I. M., Klara, K. M., Michl, G. L., Deshpande, B. R., Yang, H. Y., Smith, K. C., Collins, J. E., & Katz, J. N. (2017) · BMC Public Health · doi:10.1186/s12889-017-4931-2 · Cited by 26
Lim, B. Y., Kay, J., & Liu, W. (2019) · Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies · doi:10.1145/3328928 · Cited by 24
Developing Behavior Change Interventions
Hankonen, N. E., & Hardeman, W. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108677318.021 · Cited by 28
Wearables, Physical Activity, and Exercise Testing in Liver Disease
Dunn, M. A., Kappus, M. R., Bloomer, P. M., Duarte‐Rojo, A., Josbeno, D. A., & Jakicic, J. M. (2021) · Seminars in Liver Disease · doi:10.1055/s-0040-1716564 · Cited by 23
Engagement in Digital Mental Health Interventions: Can Monetary Incentives Help?
Boucher, E. M., Ward, H. E., Mounts, A. C., & Parks, A. C. (2021) · Frontiers in Psychology · doi:10.3389/fpsyg.2021.746324 · Cited by 23
Michaud, T. L., Estabrooks, P. A., You, W., Ern, J., Scoggins, D., Gonzales, K., King, K. M., Dai, H. D., & Su, D. (2022) · Preventive Medicine · doi:10.1016/j.ypmed.2022.107141 · Cited by 23
Rothman, A. J., Klein, W. M. P., & Sheeran, P. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108677318.020 · Cited by 26
Pearson, E., Harry Prapavessis, A., Higgins, C., Petrella, R. J., White, L., & Mitchell, M. (2020) · International Journal of Behavioral Nutrition and Physical Activity · doi:10.1186/s12966-020-01043-1 · Cited by 21
Brakenridge, C. L., Healy, G. N., WINKLER, E. A. H., & Fjeldsoe, B. S. (2018) · Interactive Journal of Medical Research · doi:10.2196/ijmr.9001 · Cited by 24
Imagery, Visualization, and Mental Simulation Interventions
Hagger, M. S., & Conroy, D. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108677318.033 · Cited by 23
Changing Behavior Using the Common-Sense Model of Self-Regulation
Cameron, L. D., Fleszar‐Pavlović, S. E., & Khachikian, T. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108677318.005 · Cited by 29
Sloan, R. A., Kim, Y., Sahasranaman, A., Müller‐Riemenschneider, F., Biddle, S., & Finkelstein, E. A. (2018) · BMC Research Notes · doi:10.1186/s13104-018-3306-9 · Cited by 21
Self-citationLindgren, T. G., Hooper, J., & Fukuoka, Y. (2019) · JMIR Public Health and Surveillance · doi:10.2196/13570 · Cited by 20
Usability of a Wrist-Worn Smartwatch in a Direct-to-Participant Randomized Pragmatic Clinical Trial
Galarnyk, M., Quer, G., McLaughlin, K., Ariniello, L. M., & Steinhubl, S. R. (2019) · Digital Biomarkers · doi:10.1159/000504838 · Cited by 21
Engagement of Stakeholders in the Design, Evaluation, and Implementation of Complex Interventions
Hudson, J. L., Moon, Z., Hughes, L. D., & Moss-Morris, R. E. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108677318.024 · Cited by 20
Keadle, S. K., Meuter, L., Phelan, S., & Phillips, S. M. (2021) · Journal of Behavioral Medicine · doi:10.1007/s10865-021-00218-w · Cited by 21
Uri Gneezy, B., Kajackaite, A., & Meier, S. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108677318.036 · Cited by 20
Valle, C. G., Pinto, B. M., LaRose, J. G., Diamond, M. A., Horrell, L. N., Nezami, B. T., Hatley, K. E., Coffman, E. M., Polzien, K. M., Hales, D. P., et al. (2021) · Contemporary Clinical Trials · doi:10.1016/j.cct.2021.106293 · Cited by 21
Bai, Y., Copeland, W., Burns, R. D., Nardone, H. Y., Devadanam, V., Rettew, J., & Hudziak, J. J. (2021) · JMIR Public Health and Surveillance · doi:10.2196/25375 · Cited by 19
Comparing Types of Financial Incentives to Promote Walking: An Experimental Test
Burns, R. J., & Rothman, A. J. (2018) · Applied Psychology Health and Well-Being · doi:10.1111/aphw.12126 · Cited by 19
Mason, M. R., Ickes, M. J., Campbell, M. S., & Bollinger, L. M. (2017) · American Journal of Health Promotion · doi:10.1177/0890117117723803 · Cited by 19
Li, K., Elgalad, A., Cardoso, C. D. O., & Perin, E. C. (2022) · Texas Heart Institute Journal · doi:10.14503/thij-22-7845 · Cited by 18
Ruiter, R. A. C., Crutzen, R., de Leeuw, E., & Kok, G. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108677318.018 · Cited by 20
Active Use and Engagement in an mHealth Initiative Among Young Men With Obesity: Mixed Methods Study
Gorny, A. W., Chee, D., & Müller‐Riemenschneider, F. (2022) · JMIR Formative Research · doi:10.2196/33798 · Cited by 16
Mobile health: an emerging technology with implications for global internal medicine
O’Shea, C., McGavigan, A. D., Clark, R. A., Chew, D. P., & Ganesan, A. N. (2017) · Internal Medicine Journal · doi:10.1111/imj.13440 · Cited by 18
Tully, J. L., Dameff, C. J., & Longhurst, C. (2020) · Clinics in Laboratory Medicine · doi:10.1016/j.cll.2019.11.004 · Cited by 20
Yen, H., & Huang, W. (2021) · Journal of Nursing Scholarship · doi:10.1111/jnu.12740 · Cited by 20
Effectiveness of eHealth Interventions Targeting Employee Health Behaviors: Systematic Review
Sevic, A., Hashemi, N. S. P., Thørrisen, M. M., Strømstad, K., Skarpaas, L. S., Storm, M., & Brønnick, K. (2023) · Journal of Medical Internet Research · doi:10.2196/38307 · Cited by 19
Investing in college students: the role of the fitness tracker
Schaben, J. A., & Furness, S. (2018) · Digital Health · doi:10.1177/2055207618766800 · Cited by 20
Gilmartin, C., Arbe-Barnes, E. H., Diamond, M., Fretwell, S., McGivern, E. J., Vlazaki, M., & Zhu, L. (2018) · Philosophy Ethics and Humanities in Medicine · doi:10.1186/s13010-018-0065-0 · Cited by 17
Hannan, A. L., Hing, W. A., Coombes, J. S., Gough, S., Climstein, M., Adsett, G., Jayasinghe, R., & Furness, J. W. (2021) · BMC Sports Science Medicine and Rehabilitation · doi:10.1186/s13102-021-00350-9 · Cited by 17
Grimes, A. R., Lightner, J. S., Piña, K., Miranda, E. D. D., Meissen-Sebelius, E. M., Shook, R. P., & Hurley, E. A. (2021) · JMIR Formative Research · doi:10.2196/33322 · Cited by 17
Veerubhotla, A. L., Krantz, A., Ibironke, O., & Pilkar, R. B. (2021) · PM&R · doi:10.1002/pmrj.12725 · Cited by 15
Personalized weight loss strategies by mining activity tracker data
Gasparetti, F., Aiello, L. M., & Quercia, D. (2019) · User Modeling and User-Adapted Interaction · doi:10.1007/s11257-019-09242-7 · Cited by 18
Changing Behavior Using Social Identity Processes
Reynolds, K. J., Branscombe, N. R., Subašić, E., & Willis, L. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108677318.016 · Cited by 21
Stanislaus, S., Vinberg, M., Melbye, S. A., Frost, M. M., Busk, J., Bardram, J. E., Faurholt‐Jepsen, M., & Kessing, L. V. (2020) · Evidence-Based Mental Health · doi:10.1136/ebmental-2020-300148 · Cited by 17
O’Loughlin, E. K., Sabiston, C. M., deJonge, M. L., Lucibello, K. M., & O’Loughlin, J. L. (2021) · Journal of Health Psychology · doi:10.1177/13591053211008209 · Cited by 17
Sypes, E. E., Newton, G. S., & Lewis, Z. H. (2019) · Journal of Physical Activity and Health · doi:10.1123/jpah.2017-0660 · Cited by 16
Spartano, N. L., Lin, H., Sun, F. X., Lunetta, K. L., Trinquart, L., Valentino, M., Manders, E. S., Pletcher, M. J., Marcus, G. M., McManus, D. D., et al. (2019) · JMIR mhealth and uhealth · doi:10.2196/13238 · Cited by 13
Monroe, C. M., Cai, B., Edney, S. M., Jake‐Schoffman, D. E., Brazendale, K., Bucko, A., Armstrong, B., Yang, C., & Turner‐McGrievy, G. M. (2023) · International Journal of Behavioral Nutrition and Physical Activity · doi:10.1186/s12966-023-01530-1 · Cited by 21
Smartphones within Psychological Science
Ellis, D. A. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108671408 · Cited by 14
Baek, J. Y., Na, S. H., Lee, H., Jung, H., Lee, E., Jo, M., Park, Y. R., & Jang, I. (2022) · Scientific Reports · doi:10.1038/s41598-022-05963-9 · Cited by 14
Impact of a workplace physical activity tracking program on biometric health outcomes
Yu, J., Abraham, J. M., Dowd, B. E., Higuera, L., & Nyman, J. A. (2017) · Preventive Medicine · doi:10.1016/j.ypmed.2017.09.002 · Cited by 14
Halloway, S., Schoeny, M. E., Barnes, L. L., Arvanitakis, Z., Pressler, S. J., Braun, L. T., Volgman, A. S., Gamboa, C. J., & Wilbur, J. (2020) · Contemporary Clinical Trials · doi:10.1016/j.cct.2020.106254 · Cited by 15
Strategies for Physical Activity Interventions in the Treatment of Obesity
Jakicic, J. M., Rogers, R. J., Collins, A. M., & Jackson, R. E. (2020) · Endocrinology and Metabolism Clinics of North America · doi:10.1016/j.ecl.2020.02.004 · Cited by 14
Webb, T. L., & de Bruin, M. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108677318.037 · Cited by 16
Is wearable technology an activity motivator, or a fad that wears thin?
Salmon, J., & Ridgers, N. D. (2017) · The Medical Journal of Australia · doi:10.5694/mja16.01242 · Cited by 14
An umbrella review of efficacy of digital health interventions for workers
Iwakura, M., Ozeki, C., Jung, S., Yamazaki, T., Miki, T., Nohara, M., & Nomura, K. (2025) · npj Digital Medicine · doi:10.1038/s41746-025-01578-2 · Cited by 19
Liew, S. J., Gorny, A. W., Tan, C. S., & Müller‐Riemenschneider, F. (2019) · JMIR mhealth and uhealth · doi:10.2196/12665 · Cited by 13
Galárraga, O., Bohlen, L. C., DUNSIGER, S. I., Lee, H., Emerson, J. A., Boyle, H. K., Strohacker, K. A., & Williams, D. M. (2019) · Health Psychology · doi:10.1037/hea0000818 · Cited by 13
Bowen, K. A., Lopez, O. N., Wright, A., Fuchs, E. L., Ahn, M., Lyons, E., Jupiter, D. C., Berry, L., Suman-Vejas, O. E., Radhakrishnan, R. S., et al. (2021) · Journal of Obesity · doi:10.1155/2021/7625034 · Cited by 13
Krops, L. A., Dekker, R., Geertzen, J. H. B., & Dijkstra, P. U. (2018) · BMJ Open · doi:10.1136/bmjopen-2017-020934 · Cited by 14
Brakenridge, C. L., Healy, G. N., WINKLER, E. A. H., & Fjeldsoe, B. S. (2018) · Journal of Occupational and Environmental Medicine · doi:10.1097/jom.0000000000001419 · Cited by 13
Physical activity and behaviour change: the role of distributed motivation
Gough, A., Prior, L., Kee, F., & Hunter, R. F. (2018) · Critical Public Health · doi:10.1080/09581596.2018.1535169 · Cited by 16
Achananuparp, P., Lim, E.-P., Abhishek, V., & Yun, T. (2018) · International Conference on Digital Health · doi:10.1145/3194658.3194662 · Cited by 12
Cavallo, F. R., & Toumazou, C. (2023) · PLOS Digital Health · doi:10.1371/journal.pdig.0000333 · Cited by 12
Changes in physical activity during the initial stages of the COVID-19 pandemic
Mason, M. R., Hudgins, J. H., Campbell, M. S., Biddle, M., Ickes, M. J., Dugan, A. J., & Bollinger, L. M. (2021) · Journal of Sports Sciences · doi:10.1080/02640414.2021.1976569 · Cited by 14
Utesch, T., Piesch, L., Busch, L., Strauß, B., & Geukes, K. (2022) · German Journal of Exercise and Sport Research · doi:10.1007/s12662-022-00821-2 · Cited by 12
Critical and Qualitative Approaches to Behavior Change
Chamberlain, K., & Lyons, A. C. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108677318.030 · Cited by 13
Nulty, A. K., Chen, E. S., & Thompson, A. L. (2022) · Digital Health · doi:10.1177/20552076221084461 · Cited by 13
A loyalty scheme to encourage physical activity in office workers: a cluster RCT
Hunter, R. F., Gough, A., Murray, J., Tang, J., Brennan, S., Chrzanowski‐Smith, O. J., Carlin, A., Patterson, C. C., Longo, A., Hutchinson, G., et al. (2019) · Public Health Research · doi:10.3310/phr07150 · Cited by 12
Metadata
- Authors
- Finkelstein, E. A., Haaland, B. A., Bilger, M., Sahasranaman, A., Sloan, R. A., Nang, E. E. K., & Evenson, K. R.
- Affiliations
- National University of Singapore (SG)
- Georgia Institute of Technology (US)
- Duke-NUS Medical School (SG)
- Kagoshima University (JP)
- University of North Carolina at Chapel Hill (US)
- Corresponding author
- Finkelstein, Eric A
- Venue
- The Lancet Diabetes & Endocrinology
- Publisher
- Elsevier BV
- Published
- 2016-12
- Volume
- 4
- Issue
- 12
- Pages
- 983-995
- ISSN
- 2213-8587 (ISSN-L)
- OpenAlex
- W2528113844
- Cited by
- 402
- References
- 27
- Citations by year
- 2026: 11 · 2025: 17 · 2024: 23 · 2023: 24 · 2022: 33 · 2021: 62 · 2020: 102 · 2019: 53 · 2018: 43 · 2017: 30 · 2016: 4
- FWCI
- 34.93
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- The Lancet Diabetes & Endocrinology (publishedVersion)
- PubMed (publishedVersion)
- WU Research (publishedVersion)
- Funders
- Health Services Research Competitive Research Grant (HSRG/0022/2012)
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Physical Activity and Health
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Keywords
- wearable activity trackers, Fitbit, physical activity, cash incentives, moderate-to-vigorous physical activity, step count, workplace health promotion, employee health, blood pressure, body weight, quality of life, accelerometer-measured activity, gamification
- MeSH terms
- Adult, Charities, Female, Habits, Humans, Male, Motivation, Exercise, Occupational Health, Accelerometry
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
