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

Reviews on Human Factors (52) Artificial Intelligence (1371) Chatbots and Conversational Agents (531) Prevention and Health Promotion (986) Innovations and Technology for Physical Activity Education (742)

Published on in Vol 10 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/43227, first published .
Feasibility and Acceptability of Chatbots for Nutrition and Physical Activity Health Promotion Among Adolescents: Systematic Scoping Review With Adolescent Consultation

Feasibility and Acceptability of Chatbots for Nutrition and Physical Activity Health Promotion Among Adolescents: Systematic Scoping Review With Adolescent Consultation

Feasibility and Acceptability of Chatbots for Nutrition and Physical Activity Health Promotion Among Adolescents: Systematic Scoping Review With Adolescent Consultation

Authors of this article:

Rui Han1 Author Orcid Image ;   Allyson Todd1 Author Orcid Image ;   Sara Wardak1 Author Orcid Image ;   Stephanie R Partridge1 Author Orcid Image ;   Rebecca Raeside1 Author Orcid Image
Article Authors Cited by (11) Tweetations (26) Metrics

Journals

  1. Ashton L, Adam M, Whatnall M, Rollo M, Burrows T, Hansen V, Collins C. Exploring the design and utility of an integrated web-based chatbot for young adults to support healthy eating: a qualitative study. International Journal of Behavioral Nutrition and Physical Activity 2023;20(1) View
  2. Boesch M, Baty F, Rassouli F, Kowatsch T, Joerger M, Früh M, Brutsche M. Non-pharmaceutical interventions to optimize cancer immunotherapy. OncoImmunology 2023;12(1) View
  3. Kirk D, van Eijnatten E, Camps G, Gumpricht E. Comparison of Answers between ChatGPT and Human Dieticians to Common Nutrition Questions. Journal of Nutrition and Metabolism 2023;2023:1 View
  4. Kiuchi K, Otsu K, Hayashi Y. Psychological insights into the research and practice of embodied conversational agents, chatbots and social assistive robots: a systematic meta-review. Behaviour & Information Technology 2023:1 View
  5. Mandoh M, Raeside R, Todd A, Redfern J, Mihrshahi S, Cheng H, Phongsavan P, Partridge S. Evaluating the effect of a 12-month youth advisory group on adolescent’s leadership skills and perceptions related to chronic disease prevention research: a mixed-methods study. BMC Public Health 2023;23(1) View
  6. Peuters C, Maenhout L, Cardon G, De Paepe A, DeSmet A, Lauwerier E, Leta K, Crombez G. A mobile healthy lifestyle intervention to promote mental health in adolescence: a mixed-methods evaluation. BMC Public Health 2024;24(1) View
  7. Aiumtrakul N, Thongprayoon C, Arayangkool C, Vo K, Wannaphut C, Suppadungsuk S, Krisanapan P, Garcia Valencia O, Qureshi F, Miao J, Cheungpasitporn W. Personalized Medicine in Urolithiasis: AI Chatbot-Assisted Dietary Management of Oxalate for Kidney Stone Prevention. Journal of Personalized Medicine 2024;14(1):107 View
  8. 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
  9. McBee J, Han D, Liu L, Ma L, Adjeroh D, Xu D, Hu G. Assessing ChatGPT’s Competency in Addressing Interdisciplinary Inquiries on Chatbot Uses in Sports Rehabilitation: Simulation Study. JMIR Medical Education 2024;10:e51157 View
  10. Nguyen M, Sedoc J, Taylor C. Usability, Engagement, and Report Usefulness of Chatbot-Based Family Health History Data Collection: Mixed Methods Analysis. Journal of Medical Internet Research 2024;26:e55164 View
  11. Tse K, Zeng M, Gibson A, Partridge S, Raeside R, Valanju R, McMahon E, Ren B, Yan F, Allman‐Farinelli M, Jia S. Retrospective analysis of regional and metropolitan school food environments using Google Street View: A case study in New South Wales, Australia with youth consultation. Health Promotion Journal of Australia 2024 View