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

Formative Evaluation of Digital Health Interventions (2801) Innovations and Technology for Healthy Eating Education (446) mHealth for Data Collection and Research (1077) Mobile Health (mhealth) (3142) mHealth for Wellness, Behavior Change and Prevention (3088) mHealth in the Developing World/LMICs, Underserved Communities, and for Global Health (631) Artificial Intelligence (1700)

Published on in Vol 6, No 7 (2022): July

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/35197, first published .
Exploring an Artificial Intelligence–Based, Gamified Phone App Prototype to Track and Improve Food Choices of Adolescent Girls in Vietnam: Acceptability, Usability, and Likeability Study

Exploring an Artificial Intelligence–Based, Gamified Phone App Prototype to Track and Improve Food Choices of Adolescent Girls in Vietnam: Acceptability, Usability, and Likeability Study

Exploring an Artificial Intelligence–Based, Gamified Phone App Prototype to Track and Improve Food Choices of Adolescent Girls in Vietnam: Acceptability, Usability, and Likeability Study

Authors of this article:

Bianca C Braga1 Author Orcid Image ;   Phuong H Nguyen2 Author Orcid Image ;   Noora-Lisa Aberman3 Author Orcid Image ;   Frank Doyle4 Author Orcid Image ;   Gloria Folson5 Author Orcid Image ;   Nga Hoang6 Author Orcid Image ;   Phuong Huynh6 Author Orcid Image ;   Bastien Koch2 Author Orcid Image ;   Peter McCloskey4 Author Orcid Image ;   Lan Tran7 Author Orcid Image ;   David Hughes4 Author Orcid Image ;   Aulo Gelli2 Author Orcid Image
Article Authors Cited by (5) Tweetations (3) Metrics

Journals

  1. Nguyen P, Tran L, Hoang N, Trương D, Tran T, Huynh P, Koch B, McCloskey P, Gangupantulu R, Folson G, Bannerman B, Arrieta A, Braga B, Arsenault J, Kehs A, Doyle F, Hughes D, Gelli A. Relative validity of a mobile AI-technology–assisted dietary assessment in adolescent females in Vietnam. The American Journal of Clinical Nutrition 2022;116(4):992 View
  2. Braga B, Nguyen P, Tran L, Hoang N, Bannerman B, Doyle F, Folson G, Gangupantulu R, Karachiwalla N, Kolt B, McCloskey P, Palloni G, Thi Tran T, Thuy Thi Trơưng D, Hughes D, Gelli A. Feasibility of Using an Artificial Intelligence-based Telephone Application for Dietary Assessment and Nudging to Improve the Quality of Food Choices of Female Adolescents in Vietnam: Evidence from a Randomized Pilot Study. Current Developments in Nutrition 2024;8(6):102063 View
  3. Young A, Johnson M, Beattie R. The use of machine learning in paediatric nutrition. Current Opinion in Clinical Nutrition & Metabolic Care 2024;27(3):290 View
  4. Oei K, Choi E, Bar-Dayan A, Stinson J, Palmert M, Alfonsi J, Hamilton J. An Image-Recognition Dietary Assessment App for Adolescents With Obesity: Pilot Randomized Controlled Trial. JMIR Formative Research 2024;8:e58682 View
  5. Liu Y, Zhang Z, Wu Y. What drives Chinese university students’ long-term use of GenAI? Evidence from the heuristic-systematic model. Education and Information Technologies 2025 View