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

mHealth for Wellness, Behavior Change and Prevention (2872) Usability of Apps and User Perceptions of mHealth (974) Use and User Demographics of mHealth (335) Instruments and Questionnaires for Nutrition and Food Intake (166) Innovations and Technology for Healthy Eating Education (414) Behavior Change (712) Electronic/Mobile Data Capture, Internet-based Survey & Research Methodology (832)

Published on in Vol 9, No 7 (2021): July

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/27885, first published .
Perspectives and Preferences of Adult Smartphone Users Regarding Nutrition and Diet Apps: Web-Based Survey Study

Perspectives and Preferences of Adult Smartphone Users Regarding Nutrition and Diet Apps: Web-Based Survey Study

Perspectives and Preferences of Adult Smartphone Users Regarding Nutrition and Diet Apps: Web-Based Survey Study

Authors of this article:

Maria F Vasiloglou1 Author Orcid Image ;   Stergios Christodoulidis1, 2 Author Orcid Image ;   Emilie Reber3 Author Orcid Image ;   Thomai Stathopoulou1 Author Orcid Image ;   Ya Lu1 Author Orcid Image ;   Zeno Stanga3 Author Orcid Image ;   Stavroula Mougiakakou1, 4 Author Orcid Image
Article Authors Cited by (19) Tweetations (12) Metrics

Journals

  1. Papathanail I, Vasiloglou M, Stathopoulou T, Ghosh A, Baumann M, Faeh D, Mougiakakou S. A feasibility study to assess Mediterranean Diet adherence using an AI-powered system. Scientific Reports 2022;12(1) View
  2. Vasiloglou M. mHealth nutrition apps in dietary assessment. Public Health and Toxicology 2022;2(Supplement 1) View
  3. Hinojosa-Nogueira D, Ortiz-Viso B, Navajas-Porras B, Pérez-Burillo S, González-Vigil V, de la Cueva S, Rufián-Henares J. Stance4Health Nutritional APP: A Path to Personalized Smart Nutrition. Nutrients 2023;15(2):276 View
  4. Vasiloglou M, Marcano I, Lizama S, Papathanail I, Spanakis E, Mougiakakou S. Multimedia Data-Based Mobile Applications for Dietary Assessment. Journal of Diabetes Science and Technology 2023;17(4):1056 View
  5. Kaiser B, Stelzl T, Finglas P, Gedrich K. The Assessment of a Personalized Nutrition Tool (eNutri) in Germany: Pilot Study on Usability Metrics and Users’ Experiences. JMIR Formative Research 2022;6(8):e34497 View
  6. van der Haar S, Raaijmakers I, Verain M, Meijboom S. Consumers’ needs in nutrition apps to start and maintain usage: a mixed methods study (Preprint). JMIR mHealth and uHealth 2022 View
  7. Ribaut J, DeVito Dabbs A, Dobbels F, Teynor A, Mess E, Hoffmann T, De Geest S. Developing a Comprehensive List of Criteria to Evaluate the Characteristics and Quality of eHealth Smartphone Apps: Systematic Review. JMIR mHealth and uHealth 2024;12:e48625 View
  8. Papathanail I, Abdur Rahman L, Brigato L, Bez N, Vasiloglou M, van der Horst K, Mougiakakou S. The Nutritional Content of Meal Images in Free-Living Conditions—Automatic Assessment with goFOODTM. Nutrients 2023;15(17):3835 View
  9. Lim J, Ali N, Rajikan R, Amit N, Hamid H, Leong H, Mohamad M, Koh B, Musa A. Need analysis of a dietary application among caregivers of patients with disorders of amino acid metabolism (AAMDs): A mixed-method approach. International Journal of Medical Informatics 2023;177:105120 View
  10. Haddad J, Vasiloglou M, Scheidegger-Balmer F, Fiedler U, van der Horst K. Home-based cooking intervention with a smartphone app to improve eating behaviors in children aged 7–9 years: a feasibility study. Discover Social Science and Health 2023;3(1) View
  11. Kheirmandparizi M, Gouin J, Bouchaud C, Kebbe M, Bergeron C, Madani Civi R, Rhodes R, Farnesi B, Bouguila N, Conklin A, Lear S, Cohen T, Sheikh S. Perceptions of self-monitoring dietary intake according to a plate-based approach: A qualitative study. PLOS ONE 2023;18(11):e0294652 View
  12. O'Hara C, Gibney E. Dietary Intake Assessment Using a Novel, Generic Meal–Based Recall and a 24-Hour Recall: Comparison Study. Journal of Medical Internet Research 2024;26:e48817 View
  13. Manaf Z, Rosli M, Noor N, Jamil N, Mazri F, Shahar S. Exploring dietitians’ views on digital nutrition educational tools in Malaysia: a qualitative study. Nutrition Research and Practice 2024;18(2):294 View
  14. Marconi S, Carrara E, Gilberti G, Castellano M, Zanini B. Digital native students using nutritional apps: are they more adherent to a mediterranean diet model? Results from the good APPetite survey. Smart Health 2024;33:100497 View
  15. Liang Y, Xiao R, Huang F, Lin Q, Guo J, Zeng W, Dong J. AI nutritionist: Intelligent software as the next generation pioneer of precision nutrition. Computers in Biology and Medicine 2024;178:108711 View
  16. Lubasinski N, Thabit H, Nutter P, Harper S. What Is the Tech Missing? Nutrition Reporting in Type 1 Diabetes. Nutrients 2024;16(11):1690 View
  17. Li X, Yin A, Choi H, Chan V, Allman-Farinelli M, Chen J. Evaluating the Quality and Comparative Validity of Manual Food Logging and Artificial Intelligence-Enabled Food Image Recognition in Apps for Nutrition Care. Nutrients 2024;16(15):2573 View

Books/Policy Documents

  1. Cerra Z, Apicella M. Smartphone Apps for Health and Wellness. View
  2. Aljabali R, Ahmad N. Advances on Intelligent Computing and Data Science. View