Published on in Vol 8, No 1 (2019): January

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/11540, first published .
Investigating Intervention Components and Exploring States of Receptivity for a Smartphone App to Promote Physical Activity: Protocol of a Microrandomized Trial

Investigating Intervention Components and Exploring States of Receptivity for a Smartphone App to Promote Physical Activity: Protocol of a Microrandomized Trial

Investigating Intervention Components and Exploring States of Receptivity for a Smartphone App to Promote Physical Activity: Protocol of a Microrandomized Trial

Journals

  1. Kramer J, Künzler F, Mishra V, Smith S, Kotz D, Scholz U, Fleisch E, Kowatsch T. Which Components of a Smartphone Walking App Help Users to Reach Personalized Step Goals? Results From an Optimization Trial. Annals of Behavioral Medicine 2020;54(7):518 View
  2. Palanica A, Flaschner P, Thommandram A, Li M, Fossat Y. Physicians’ Perceptions of Chatbots in Health Care: Cross-Sectional Web-Based Survey. Journal of Medical Internet Research 2019;21(4):e12887 View
  3. Fernandez M, Bron G, Kache P, Larson S, Maus A, Gustafson Jr D, Tsao J, Bartholomay L, Paskewitz S, Diuk-Wasser M. Usability and Feasibility of a Smartphone App to Assess Human Behavioral Factors Associated with Tick Exposure (The Tick App): Quantitative and Qualitative Study. JMIR mHealth and uHealth 2019;7(10):e14769 View
  4. Kroska E, Hoel S, Victory A, Murphy S, McInnis M, Stowe Z, Cochran A. Optimizing an Acceptance and Commitment Therapy Microintervention Via a Mobile App With Two Cohorts: Protocol for Micro-Randomized Trials. JMIR Research Protocols 2020;9(9):e17086 View
  5. Massoomi M, Handberg E. Increasing and Evolving Role of Smart Devices in Modern Medicine. European Cardiology Review 2019;14(3):181 View
  6. Li S, Psihogios A, McKelvey E, Ahmed A, Rabbi M, Murphy S. Microrandomized trials for promoting engagement in mobile health data collection: Adolescent/young adult oral chemotherapy adherence as an example. Current Opinion in Systems Biology 2020;21:1 View
  7. Tudor Car L, Dhinagaran D, Kyaw B, Kowatsch T, Joty S, Theng Y, Atun R. Conversational Agents in Health Care: Scoping Review and Conceptual Analysis. Journal of Medical Internet Research 2020;22(8):e17158 View
  8. Zhang J, Oh Y, Lange P, Yu Z, Fukuoka Y. Artificial Intelligence Chatbot Behavior Change Model for Designing Artificial Intelligence Chatbots to Promote Physical Activity and a Healthy Diet: Viewpoint. Journal of Medical Internet Research 2020;22(9):e22845 View
  9. Brower J, LaBarge M, White L, Mitchell M. Examining Responsiveness to an Incentive-Based Mobile Health App: Longitudinal Observational Study. Journal of Medical Internet Research 2020;22(8):e16797 View
  10. Künzler F, Mishra V, Kramer J, Kotz D, Fleisch E, Kowatsch T. Exploring the State-of-Receptivity for mHealth Interventions. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2019;3(4):1 View
  11. Perski O, Crane D, Beard E, Brown J. Does the addition of a supportive chatbot promote user engagement with a smoking cessation app? An experimental study. DIGITAL HEALTH 2019;5 View
  12. Thompson D, Baranowski T. Chatbots as extenders of pediatric obesity intervention: an invited commentary on “Feasibility of Pediatric Obesity & Pre-Diabetes Treatment Support through Tess, the AI Behavioral Coaching Chatbot”. Translational Behavioral Medicine 2019;9(3):448 View
  13. Huang D, Chueh H. Chatbot usage intention analysis: Veterinary consultation. Journal of Innovation & Knowledge 2021;6(3):135 View
  14. Valle C, Pinto B, LaRose J, Diamond M, Horrell L, Nezami B, Hatley K, Coffman E, Polzien K, Hales D, Deal A, Rini C, Rosenstein D, Tate D. Promoting physical activity in young adult cancer survivors using mHealth and adaptive tailored feedback strategies: Design of the Improving Physical Activity after Cancer Treatment (IMPACT) randomized controlled trial. Contemporary Clinical Trials 2021;103:106293 View
  15. Kowatsch T, Schachner T, Harperink S, Barata F, Dittler U, Xiao G, Stanger C, v Wangenheim F, Fleisch E, Oswald H, Möller A. Conversational Agents as Mediating Social Actors in Chronic Disease Management Involving Health Care Professionals, Patients, and Family Members: Multisite Single-Arm Feasibility Study. Journal of Medical Internet Research 2021;23(2):e25060 View
  16. Qian T, Yoo H, Klasnja P, Almirall D, Murphy S. Estimating time-varying causal excursion effects in mobile health with binary outcomes. Biometrika 2021;108(3):507 View
  17. Luo T, Aguilera A, Lyles C, Figueroa C. Promoting Physical Activity Through Conversational Agents: Mixed Methods Systematic Review. Journal of Medical Internet Research 2021;23(9):e25486 View
  18. Becker D. Let Your Patrons Know the Benefits of Physical Fitness Apps and Five Free Apps to Try. Journal of Electronic Resources in Medical Libraries 2022;19(4):143 View
  19. Goldstein S, Zhang F, Klasnja P, Hoover A, Wing R, Thomas J. Optimizing a Just-in-Time Adaptive Intervention to Improve Dietary Adherence in Behavioral Obesity Treatment: Protocol for a Microrandomized Trial. JMIR Research Protocols 2021;10(12):e33568 View
  20. Magalhães B, Fernandes C, Santos C, Martínez-Galiano J. The Use of Mobile Applications for Managing Care Processes During Chemotherapy Treatments: A Systematic Review. Cancer Nursing 2021;44(6):E339 View
  21. Moradi S, Alivand M, KhajeBishak Y, AsghariJafarabadi M, Alipour M, faghfouri A, Alipour B. The Effect of ω3 Fatty Acids Supplementation on Levels of PPARγ and UCP2 Genes Expression, Serum Level of UCP2 Protein, Metabolic Status, and Appetite in Elite male Athletes: Protocol for a Randomized Control Trial. International Journal of Surgery: Protocols 2021;25(1):184 View
  22. Presset B, Kramer J, Kowatsch T, Ohl F. The social meaning of steps: user reception of a mobile health intervention on physical activity. Critical Public Health 2021;31(5):605 View
  23. Robles M, Newman M, Doshi A, Bailey S, Huang L, Choi S, Kurien C, Merid B, Cowdery J, Golbus J, Huang C, Dorsch M, Nallamothu B, Skolarus L. A Physical Activity Just-in-time Adaptive Intervention Designed in Partnership With a Predominantly Black Community: Virtual, Community-Based Participatory Design Approach. JMIR Formative Research 2022;6(3):e33087 View
  24. Daryabeygi-Khotbehsara R, Shariful Islam S, Dunstan D, McVicar J, Abdelrazek M, Maddison R. Smartphone-Based Interventions to Reduce Sedentary Behavior and Promote Physical Activity Using Integrated Dynamic Models: Systematic Review. Journal of Medical Internet Research 2021;23(9):e26315 View
  25. Ollier J, Neff S, Dworschak C, Sejdiji A, Santhanam P, Keller R, Xiao G, Asisof A, Rüegger D, Bérubé C, Hilfiker Tomas L, Neff J, Yao J, Alattas A, Varela-Mato V, Pitkethly A, Vara M, Herrero R, Baños R, Parada C, Agatheswaran R, Villalobos V, Keller O, Chan W, Mishra V, Jacobson N, Stanger C, He X, von Wyl V, Weidt S, Haug S, Schaub M, Kleim B, Barth J, Witt C, Scholz U, Fleisch E, Wangenheim F, Car L, Müller-Riemenschneider F, Hauser-Ulrich S, Asomoza A, Salamanca-Sanabria A, Mair J, Kowatsch T. Elena+ Care for COVID-19, a Pandemic Lifestyle Care Intervention: Intervention Design and Study Protocol. Frontiers in Public Health 2021;9 View
  26. de Buisonjé D, Reijnders T, Cohen Rodrigues T, Prabhakaran S, Kowatsch T, Lipman S, Bijmolt T, Breeman L, Janssen V, Kraaijenhagen R, Kemps H, Evers A. Investigating Rewards and Deposit Contract Financial Incentives for Physical Activity Behavior Change Using a Smartphone App: Randomized Controlled Trial. Journal of Medical Internet Research 2022;24(10):e38339 View
  27. Pogorskiy E, Beckmann J. From procrastination to engagement? An experimental exploration of the effects of an adaptive virtual assistant on self-regulation in online learning. Computers and Education: Artificial Intelligence 2023;4:100111 View
  28. Domin A, Uslu A, Schulz A, Ouzzahra Y, Vögele C. A Theory-Informed, Personalized mHealth Intervention for Adolescents (Mobile App for Physical Activity): Development and Pilot Study. JMIR Formative Research 2022;6(6):e35118 View
  29. Owens A, Krebs C, Kuruppu S, Brem A, Kowatsch T, Aarsland D, Klöppel S. Broadened assessments, health education and cognitive aids in the remote memory clinic. Frontiers in Public Health 2022;10 View
  30. Dhinagaran D, Martinengo L, Ho M, Joty S, Kowatsch T, Atun R, Tudor Car L. Designing, Developing, Evaluating, and Implementing a Smartphone-Delivered, Rule-Based Conversational Agent (DISCOVER): Development of a Conceptual Framework. JMIR mHealth and uHealth 2022;10(10):e38740 View
  31. Mishra V, Künzler F, Kramer J, Fleisch E, Kowatsch T, Kotz D. Detecting Receptivity for mHealth Interventions. GetMobile: Mobile Computing and Communications 2023;27(2):23 View
  32. Ollier J, Suryapalli P, Fleisch E, Wangenheim F, Mair J, Salamanca-Sanabria A, Kowatsch T. Can digital health researchers make a difference during the pandemic? Results of the single-arm, chatbot-led Elena+: Care for COVID-19 interventional study. Frontiers in Public Health 2023;11 View
  33. Cohen Rodrigues T, de Buisonjé D, Reijnders T, Santhanam P, Kowatsch T, Breeman L, Janssen V, Kraaijenhagen R, Atsma D, Evers A. Human cues in eHealth to promote lifestyle change: An experimental field study to examine adherence to self-help interventions. Internet Interventions 2024;35:100726 View
  34. Brons A, Wang S, Visser B, Kröse B, Bakkes S, Veltkamp R. Machine Learning Methods to Personalize Persuasive Strategies in mHealth Interventions That Promote Physical Activity: Scoping Review and Categorization Overview. Journal of Medical Internet Research 2024;26:e47774 View

Books/Policy Documents

  1. Singla S. Internet of Things Use Cases for the Healthcare Industry. View
  2. Catania L. Foundations of Artificial Intelligence in Healthcare and Bioscience. View
  3. Ofori M, El-Gayar O. Optimizing Health Monitoring Systems With Wireless Technology. View
  4. Kowatsch T, Fleisch E. Connected Business. View