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Citing this Article

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Published on 09.02.16 in Vol 18, No 2 (2016): February

This paper is in the following e-collection/theme issue:

Works citing "Effectiveness of an Activity Tracker- and Internet-Based Adaptive Walking Program for Adults: A Randomized Controlled Trial"

According to Crossref, the following articles are citing this article (DOI 10.2196/jmir.5295):

(note that this is only a small subset of citations)

  1. Pereira CS, Padoan CS, Garcia LF, Patusco L, Magalhães PVS. Barriers and facilitators perceived by people with bipolar disorder for the practice of exercise: a qualitative study. Trends in Psychiatry and Psychotherapy 2019;41(1):1
    CrossRef
  2. Brickwood K, Watson G, O'Brien J, Williams AD. Consumer-Based Wearable Activity Trackers Increase Physical Activity Participation: Systematic Review and Meta-Analysis. JMIR mHealth and uHealth 2019;7(4):e11819
    CrossRef
  3. Adams MA, Hurley JC, Phillips CB, Todd M, Angadi SS, Berardi V, Hovell MF, Hooker S. Rationale, design, and baseline characteristics of WalkIT Arizona: A factorial randomized trial testing adaptive goals and financial reinforcement to increase walking across higher and lower walkable neighborhoods. Contemporary Clinical Trials 2019;81:87
    CrossRef
  4. Schlomann A, Seifert A, Rietz C. Relevance of Activity Tracking With Mobile Devices in the Relationship Between Physical Activity Levels and Satisfaction With Physical Fitness in Older Adults: Representative Survey. JMIR Aging 2019;2(1):e12303
    CrossRef
  5. Shin G, Feng Y, Jarrahi MH, Gafinowitz N. Beyond novelty effect: a mixed-methods exploration into the motivation for long-term activity tracker use. JAMIA Open 2019;2(1):62
    CrossRef
  6. Ceasar JN, Claudel SE, Andrews MR, Tamura K, Mitchell V, Brooks AT, Dodge T, El-Toukhy S, Farmer N, Middleton K, Sabado-Liwag M, Troncoso M, Wallen GR, Powell-Wiley TM. Community Engagement in the Development of an mHealth-Enabled Physical Activity and Cardiovascular Health Intervention (Step It Up): Pilot Focus Group Study. JMIR Formative Research 2019;3(1):e10944
    CrossRef
  7. Buckingham SA, Williams AJ, Morrissey K, Price L, Harrison J. Mobile health interventions to promote physical activity and reduce sedentary behaviour in the workplace: A systematic review. DIGITAL HEALTH 2019;5:205520761983988
    CrossRef
  8. Forman EM, Kerrigan SG, Butryn ML, Juarascio AS, Manasse SM, Ontañón S, Dallal DH, Crochiere RJ, Moskow D. Can the artificial intelligence technique of reinforcement learning use continuously-monitored digital data to optimize treatment for weight loss?. Journal of Behavioral Medicine 2019;42(2):276
    CrossRef
  9. Wu HS, Gal R, van Sleeuwen NC, Brombacher AC, IJsselsteijn WA, May AM, Monninkhof EM. Breast Cancer Survivors’ Experiences With an Activity Tracker Integrated Into a Supervised Exercise Program: Qualitative Study. JMIR mHealth and uHealth 2019;7(2):e10820
    CrossRef
  10. Rice L, Sara R. Updating the determinants of health model in the Information Age. Health Promotion International 2018;
    CrossRef
  11. Shrestha N, Kukkonen-Harjula KT, Verbeek JH, Ijaz S, Hermans V, Pedisic Z. Workplace interventions for reducing sitting at work. Cochrane Database of Systematic Reviews 2018;
    CrossRef
  12. Middelweerd A, te Velde SJ, Mollee JS, Klein MC, Brug J. App-Based Intervention Combining Evidence-Based Behavior Change Techniques With a Model-Based Reasoning System to Promote Physical Activity Among Young Adults (Active2Gether): Descriptive Study of the Development and Content. JMIR Research Protocols 2018;7(12):e185
    CrossRef
  13. Phatak SS, Freigoun MT, Martín CA, Rivera DE, Korinek EV, Adams MA, Buman MP, Klasnja P, Hekler EB. Modeling individual differences: A case study of the application of system identification for personalizing a physical activity intervention. Journal of Biomedical Informatics 2018;79:82
    CrossRef
  14. Korinek EV, Phatak SS, Martin CA, Freigoun MT, Rivera DE, Adams MA, Klasnja P, Buman MP, Hekler EB. Adaptive step goals and rewards: a longitudinal growth model of daily steps for a smartphone-based walking intervention. Journal of Behavioral Medicine 2018;41(1):74
    CrossRef
  15. Ehn M, Eriksson LC, Åkerberg N, Johansson A. Activity Monitors as Support for Older Persons’ Physical Activity in Daily Life: Qualitative Study of the Users’ Experiences. JMIR mHealth and uHealth 2018;6(2):e34
    CrossRef
  16. Zhou M, Fukuoka Y, Mintz Y, Goldberg K, Kaminsky P, Flowers E, Aswani A. Evaluating Machine Learning–Based Automated Personalized Daily Step Goals Delivered Through a Mobile Phone App: Randomized Controlled Trial. JMIR mHealth and uHealth 2018;6(1):e28
    CrossRef
  17. Dijkhuis TB, Blaauw FJ, van Ittersum MW, Velthuijsen H, Aiello M. Personalized Physical Activity Coaching: A Machine Learning Approach. Sensors 2018;18(2):623
    CrossRef
  18. Xie J, Wen D, Liang L, Jia Y, Gao L, Lei J. Evaluating the Validity of Current Mainstream Wearable Devices in Fitness Tracking Under Various Physical Activities: Comparative Study. JMIR mHealth and uHealth 2018;6(4):e94
    CrossRef
  19. Shrestha N, Kukkonen-Harjula KT, Verbeek JH, Ijaz S, Hermans V, Pedisic Z. Workplace interventions for reducing sitting at work. Cochrane Database of Systematic Reviews 2018;
    CrossRef
  20. Brakenridge CL, Healy GN, Winkler EA, Fjeldsoe BS. Usage, Acceptability, and Effectiveness of an Activity Tracker in a Randomized Trial of a Workplace Sitting Intervention: Mixed-Methods Evaluation. Interactive Journal of Medical Research 2018;7(1):e5
    CrossRef
  21. Strutz E, Browning R, Smith S, Lohse B, Cunningham-Sabo L. Accelerometry-Derived Physical Activity Correlations Between Parents and Their Fourth-Grade Child Are Specific to Time of Day and Activity Level. Journal of Physical Activity and Health 2018;15(6):440
    CrossRef
  22. Brakenridge CL, Healy GN, Winkler EA, Fjeldsoe BS. What Do Workers Do to Reduce Their Sitting Time? The Relationships of Strategy Use and Workplace Support With Desk-Based Workers’ Behavior Changes in a Workplace-Delivered Sitting-Reduction and Activity-Promoting Intervention. Journal of Occupational and Environmental Medicine 2018;60(11):1026
    CrossRef
  23. Eckerstorfer LV, Tanzer NK, Vogrincic-Haselbacher C, Kedia G, Brohmer H, Dinslaken I, Corcoran K. Key Elements of mHealth Interventions to Successfully Increase Physical Activity: Meta-Regression. JMIR mHealth and uHealth 2018;6(11):e10076
    CrossRef
  24. Bender MS, Cooper BA, Park LG, Padash S, Arai S. A Feasible and Efficacious Mobile-Phone Based Lifestyle Intervention for Filipino Americans with Type 2 Diabetes: Randomized Controlled Trial. JMIR Diabetes 2017;2(2):e30
    CrossRef
  25. Rasche P, Schlomann A, Mertens A. Who Is Still Playing Pokémon Go? A Web-Based Survey. JMIR Serious Games 2017;5(2):e7
    CrossRef
  26. Kouwenhoven-Pasmooij TA, Robroek SJ, Ling SW, van Rosmalen J, van Rossum EF, Burdorf A, Hunink MM. A Blended Web-Based Gaming Intervention on Changes in Physical Activity for Overweight and Obese Employees: Influence and Usage in an Experimental Pilot Study. JMIR Serious Games 2017;5(2):e6
    CrossRef
  27. Adams MA, Hurley JC, Todd M, Bhuiyan N, Jarrett CL, Tucker WJ, Hollingshead KE, Angadi SS. Adaptive goal setting and financial incentives: a 2 × 2 factorial randomized controlled trial to increase adults’ physical activity. BMC Public Health 2017;17(1)
    CrossRef
  28. Seifert A, Schlomann A, Rietz C, Schelling HR. The use of mobile devices for physical activity tracking in older adults’ everyday life. DIGITAL HEALTH 2017;3:205520761774008
    CrossRef
  29. Skrepnik N, Spitzer A, Altman R, Hoekstra J, Stewart J, Toselli R. Assessing the Impact of a Novel Smartphone Application Compared With Standard Follow-Up on Mobility of Patients With Knee Osteoarthritis Following Treatment With Hylan G-F 20: A Randomized Controlled Trial. JMIR mHealth and uHealth 2017;5(5):e64
    CrossRef
  30. Witteman HO, Presseau J, Nicholas Angl E, Jokhio I, Schwalm J, Grimshaw JM, Bosiak B, Natarajan MK, Ivers NM. Negotiating Tensions Between Theory and Design in the Development of Mailings for People Recovering From Acute Coronary Syndrome. JMIR Human Factors 2017;4(1):e6
    CrossRef
  31. Van Dijk MR, Koster MP, Rosman AN, Steegers-Theunissen RP. Opportunities of mHealth in Preconception Care: Preferences and Experiences of Patients and Health Care Providers and Other Involved Professionals. JMIR mHealth and uHealth 2017;5(8):e123
    CrossRef
  32. Brakenridge CL, Fjeldsoe BS, Young DC, Winkler EAH, Dunstan DW, Straker LM, Healy GN. Evaluating the effectiveness of organisational-level strategies with or without an activity tracker to reduce office workers’ sitting time: a cluster-randomised trial. International Journal of Behavioral Nutrition and Physical Activity 2016;13(1)
    CrossRef
  33. Sathyanarayana A, Joty S, Fernandez-Luque L, Ofli F, Srivastava J, Elmagarmid A, Arora T, Taheri S. Sleep Quality Prediction From Wearable Data Using Deep Learning. JMIR mHealth and uHealth 2016;4(4):e125
    CrossRef
  34. Kunkle S, Christie G, Hajat C, Yach D. The Role of the Private Sector in Tilting Health Systems Toward Chronic Disease Prevention. Global Heart 2016;11(4):451
    CrossRef
  35. Agboola S, Jethwani K, Lopez L, Searl M, O’Keefe S, Kvedar J. Text to Move: A Randomized Controlled Trial of a Text-Messaging Program to Improve Physical Activity Behaviors in Patients With Type 2 Diabetes Mellitus. Journal of Medical Internet Research 2016;18(11):e307
    CrossRef
  36. Eijsvogels TM, George KP, Thompson PD. Cardiovascular benefits and risks across the physical activity continuum. Current Opinion in Cardiology 2016;31(5):566
    CrossRef
  37. Jones D, Skrepnik N, Toselli RM, Leroy B. Incorporating Novel Mobile Health Technologies Into Management of Knee Osteoarthritis in Patients Treated With Intra-Articular Hyaluronic Acid: Rationale and Protocol of a Randomized Controlled Trial. JMIR Research Protocols 2016;5(3):e164
    CrossRef