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

mHealth for Wellness, Behavior Change and Prevention (2347) Innovations and Technology for Healthy Eating Education (331) Adoption and Change Management of eHealth Systems (484) Usability of Apps and User Perceptions of mHealth (736)

Published on in Vol 8 , No 10 (2020) :October

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/16911, first published .
Adoption of Mobile Health Apps in Dietetic Practice: Case Study of Diyetkolik

Adoption of Mobile Health Apps in Dietetic Practice: Case Study of Diyetkolik

Adoption of Mobile Health Apps in Dietetic Practice: Case Study of Diyetkolik

Authors of this article:

Gorkem Akdur 1 Author Orcid Image ;   Mehmet Nafiz Aydin 1 Author Orcid Image ;   Gizdem Akdur 2 Author Orcid Image
Article Authors Cited by (12) Tweetations Metrics

Journals

  1. Wattanapisit A, Amaek W, Wattanapisit S, Tuangratananon T, Wongsiri S, Pengkaew P. Challenges of Implementing an mHealth Application for Personalized Physical Activity Counselling in Primary Health Care: A Qualitative Study. International Journal of General Medicine 2021;Volume 14:3821 View
  2. Schretzlmaier P, Hecker A, Ammenwerth E. Extension of the Unified Theory of Acceptance and Use of Technology 2 model for predicting mHealth acceptance using diabetes as an example: a cross-sectional validation study. BMJ Health & Care Informatics Online 2022;29(1):e100640 View
  3. Palos-Sanchez P, Saura J, Rios Martin M, Aguayo-Camacho M. Toward a Better Understanding of the Intention to Use mHealth Apps: Exploratory Study. JMIR mHealth and uHealth 2021;9(9):e27021 View
  4. Li C, Li Y. Factors Influencing Public Risk Perception of Emerging Technologies: A Meta-Analysis. Sustainability 2023;15(5):3939 View
  5. Fitri Kinasih Husnul Khotimah , Fahmi I, Sri Hartono . The Antecedents of Intention to Use Telemedicine. Journal of Consumer Sciences 2022;7(2):97 View
  6. Dias S, Oikonomidis Y, Diniz J, Baptista F, Carnide F, Bensenousi A, Botana J, Tsatsou D, Stefanidis K, Gymnopoulos L, Dimitropoulos K, Daras P, Argiriou A, Rouskas K, Wilson-Barnes S, Hart K, Merry N, Russell D, Konstantinova J, Lalama E, Pfeiffer A, Kokkinopoulou A, Hassapidou M, Pagkalos I, Patra E, Buys R, Cornelissen V, Batista A, Cobello S, Milli E, Vagnozzi C, Bryant S, Maas S, Bacelar P, Gravina S, Vlaskalin J, Brkic B, Telo G, Mantovani E, Gkotsopoulou O, Iakovakis D, Hadjidimitriou S, Charisis V, Hadjileontiadis L. Users' Perspective on the AI-Based Smartphone PROTEIN App for Personalized Nutrition and Healthy Living: A Modified Technology Acceptance Model (mTAM) Approach. Frontiers in Nutrition 2022;9 View
  7. Albastaki Y. Assessing the perceived usability of an intelligent contact tracing app to prevent the spread of COVID-19 using SUS and TAM: be aware Bahrain. Journal of Decision Systems 2022:1 View
  8. Loh K, Liu J, Ganzhorn S, Sanabria G, Schnall R. Establishing a usability cut-point for the health information technology usability evaluation scale (Health-ITUES). International Journal of Medical Informatics 2022;160:104713 View
  9. Kang H, Han J, Kwon G. The Acceptance Behavior of Smart Home Health Care Services in South Korea: An Integrated Model of UTAUT and TTF. International Journal of Environmental Research and Public Health 2022;19(20):13279 View

Books/Policy Documents

  1. Antolín-Prieto R, Ruiz-Lacaci N, Reyes-Menendez A. Management and Marketing for Improved Competitiveness and Performance in the Healthcare Sector. View
  2. Sarasa-Cabezuelo A. Data Intelligence and Cognitive Informatics. View
  3. Haridi H, Alsaleh S, Alzabin S, Almasabi M, Almakrami A, Al-Swedan A, Aman A. Proceedings of Seventh International Congress on Information and Communication Technology. View