Published on in Vol 6, No 6 (2018): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/9459, first published .
Analysis of the Features Important for the Effectiveness of Physical Activity–Related Apps for Recreational Sports: Expert Panel Approach

Analysis of the Features Important for the Effectiveness of Physical Activity–Related Apps for Recreational Sports: Expert Panel Approach

Analysis of the Features Important for the Effectiveness of Physical Activity–Related Apps for Recreational Sports: Expert Panel Approach

Journals

  1. Perez-Aranda J, González Robles E, Urbistondo P. Sport-related physical activity in tourism: an analysis of antecedents of sport based applications use. Information Technology & Tourism 2021;23(1):97 View
  2. Janssen M, Walravens R, Thibaut E, Scheerder J, Brombacher A, Vos S. Understanding Different Types of Recreational Runners and How They Use Running-Related Technology. International Journal of Environmental Research and Public Health 2020;17(7):2276 View
  3. Boudet G, Chausse P, Thivel D, Rousset S, Mermillod M, Baker J, Parreira L, Esquirol Y, Duclos M, Dutheil F. How to Measure Sedentary Behavior at Work?. Frontiers in Public Health 2019;7 View
  4. Meixner C, Baumann H, Wollesen B. Personality Traits, Gamification and Features to Develop an App to Reduce Physical Inactivity. Information 2020;11(7):367 View
  5. Janssen M, Goudsmit J, Lauwerijssen C, Brombacher A, Lallemand C, Vos S. How Do Runners Experience Personalization of Their Training Scheme: The Inspirun E-Coach?. Sensors 2020;20(16):4590 View
  6. Olsen S, Saperstein S, Gold R. Content and Feature Preferences for a Physical Activity App for Adults with Physical Disabilities: Focus Group Findings (Preprint). JMIR mHealth and uHealth 2019 View
  7. Pinillos-Patiño Y, Herazo-Beltrán Y, Rodríguez-Cordero O, Escorcia-Bermejo A, Martelo-López E, Vidarte-Claros J, García J, Moreno G. User Preferences Related to Multimedia Elements of a Mobile Application to Prevent Diabetes. Healthcare Informatics Research 2020;26(4):295 View
  8. Zimmermann B, Fiske A, Prainsack B, Hangel N, McLennan S, Buyx A. Early Perceptions of COVID-19 Contact Tracing Apps in German-Speaking Countries: Comparative Mixed Methods Study. Journal of Medical Internet Research 2021;23(2):e25525 View
  9. Iliadis A, Tomovic M, Dervas D, Psymarnou M, Christoulas K, Kouidi E, Deligiannis A. A Novel mHealth Monitoring System during Cycling in Elite Athletes. International Journal of Environmental Research and Public Health 2021;18(9):4788 View
  10. Yang Y, Koenigstorfer J. Determinants of Fitness App Usage and Moderating Impacts of Education-, Motivation-, and Gamification-Related App Features on Physical Activity Intentions: Cross-sectional Survey Study. Journal of Medical Internet Research 2021;23(7):e26063 View
  11. Farič N, Potts H, Rowe S, Beaty T, Hon A, Fisher A. Running App “Zombies, Run!” Users' Engagement with Physical Activity: A Qualitative Study. Games for Health Journal 2021;10(6):420 View
  12. Schwarz A, Winkens L, de Vet E, Ossendrijver D, Bouwsema K, Simons M. Design Features Associated With Engagement in Mobile Health Physical Activity Interventions Among Youth: Systematic Review of Qualitative and Quantitative Studies. JMIR mHealth and uHealth 2023;11:e40898 View
  13. Gonzalez-Fimbres R. Diferencias de género en uso de aplicaciones móviles de ejercicio en alumnos de Entrenamiento Deportivo. Revista de Ciencias del Ejercicio FOD 2022;17(1) View
  14. Chembakottu B, Li H, Khomh F. A large-scale exploratory study of android sports apps in the google play store. Information and Software Technology 2023;164:107321 View
  15. Brombacher H, Houben S, Vos S. Tangible interventions for office work well-being: approaches, classification, and design considerations. Behaviour & Information Technology 2024;43(10):2151 View

Books/Policy Documents

  1. Ren S, Shen B. Translational Informatics. View