Published on in Vol 4, No 3 (2016): Jul-Sept

Popular Nutrition-Related Mobile Apps: A Feature Assessment

Popular Nutrition-Related Mobile Apps: A Feature Assessment

Popular Nutrition-Related Mobile Apps: A Feature Assessment

Journals

  1. Hu E, Nguyen V, Langheier J, Shurney D. Weight Reduction Through a Digital Nutrition and Food Purchasing Platform Among Users With Obesity: Longitudinal Study. Journal of Medical Internet Research 2020;22(9):e19634 View
  2. Zhang L, Nawijn E, Boshuizen H, Ocké M. Evaluation of the Recipe Function in Popular Dietary Smartphone Applications, with Emphasize on Features Relevant for Nutrition Assessment in Large-Scale Studies. Nutrients 2019;11(1):200 View
  3. Tejpal S, Sanghera N, Manoharan V, Planas-Iglesias J, Myler K, Klein-Seetharaman J. Towards personalised molecular feedback for weight loss. BMC Obesity 2019;6(1) View
  4. Rozga M, Latulippe M, Steiber A. Advancements in Personalized Nutrition Technologies: Guiding Principles for Registered Dietitian Nutritionists. Journal of the Academy of Nutrition and Dietetics 2020;120(6):1074 View
  5. Segredo E, Miranda G, Ramos J, Leon C, Rodriguez-Leon C. SCHOOLTHY: Automatic Menu Planner for Healthy and Balanced School Meals. IEEE Access 2020;8:113200 View
  6. Agapito G, Simeoni M, Calabrese B, Caré I, Lamprinoudi T, Guzzi P, Pujia A, Fuiano G, Cannataro M. DIETOS: A dietary recommender system for chronic diseases monitoring and management. Computer Methods and Programs in Biomedicine 2018;153:93 View
  7. Kosa S, Monize J, D'Souza M, Joshi A, Philip K, Reza S, Samra S, Serrago B, Thabane L, Gafni A, Lok C. Nutritional Mobile Applications for CKD Patients: Systematic Review. Kidney International Reports 2019;4(3):399 View
  8. Franco R, Fallaize R, Hwang F, Lovegrove J. Strategies for online personalised nutrition advice employed in the development of the eNutri web app. Proceedings of the Nutrition Society 2019;78(3):407 View
  9. Ahmed M, Mandic I, Lou W, Goodman L, Jacobs I, L’Abbé M. Validation of a Tablet Application for Assessing Dietary Intakes Compared with the Measured Food Intake/Food Waste Method in Military Personnel Consuming Field Rations. Nutrients 2017;9(3):200 View
  10. Mandracchia F, Llauradó E, Tarro L, Valls R, Solà R. Mobile Phone Apps for Food Allergies or Intolerances in App Stores: Systematic Search and Quality Assessment Using the Mobile App Rating Scale (MARS). JMIR mHealth and uHealth 2020;8(9):e18339 View
  11. Honary M, Bell B, Clinch S, Wild S, McNaney R. Understanding the Role of Healthy Eating and Fitness Mobile Apps in the Formation of Maladaptive Eating and Exercise Behaviors in Young People. JMIR mHealth and uHealth 2019;7(6):e14239 View
  12. Simpson C, Mazzeo S. Calorie counting and fitness tracking technology: Associations with eating disorder symptomatology. Eating Behaviors 2017;26:89 View
  13. Sustamy R, Widyawati M, Suryono S. Information system implementation for the management of malnutrition in pregnant women: a systematic literature review. Journal of Physics: Conference Series 2020;1524:012115 View
  14. Biel J, Martin N, Labbe D, Gatica-Perez D. Bites‘n’Bits. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2018;1(4):1 View
  15. Villasana M, Pires I, Sá J, Garcia N, Zdravevski E, Chorbev I, Lameski P, Flórez-Revuelta F. Mobile Applications for the Promotion and Support of Healthy Nutrition and Physical Activity Habits: A Systematic Review, Extraction of Features and Taxonomy Proposal. The Open Bioinformatics Journal 2019;12(1):50 View
  16. Akdur G, Aydin M, Akdur G. Adoption of Mobile Health Apps in Dietetic Practice: Case Study of Diyetkolik. JMIR mHealth and uHealth 2020;8(10):e16911 View
  17. Minnens F, Marques A, Domingo J, Verbeke W. Consumers’ acceptance of an online tool with personalized health risk-benefit communication about seafood consumption. Food and Chemical Toxicology 2020;144:111573 View
  18. Katz D, Rhee L, Katz C, Aronson D, Frank G, Gardner C, Willett W, Dansinger M. Dietary assessment can be based on pattern recognition rather than recall. Medical Hypotheses 2020;140:109644 View
  19. Mauch C, Wycherley T, Laws R, Johnson B, Bell L, Golley R. Mobile Apps to Support Healthy Family Food Provision: Systematic Assessment of Popular, Commercially Available Apps. JMIR mHealth and uHealth 2018;6(12):e11867 View
  20. Zarnowiecki D, Mauch C, Middleton G, Matwiejczyk L, Watson W, Dibbs J, Dessaix A, Golley R. A systematic evaluation of digital nutrition promotion websites and apps for supporting parents to influence children’s nutrition. International Journal of Behavioral Nutrition and Physical Activity 2020;17(1) View
  21. Maringer M, van’t Veer P, Klepacz N, Verain M, Normann A, Ekman S, Timotijevic L, Raats M, Geelen A. User-documented food consumption data from publicly available apps: an analysis of opportunities and challenges for nutrition research. Nutrition Journal 2018;17(1) View
  22. Flaherty S, McCarthy M, Collins A, McAuliffe F. Can existing mobile apps support healthier food purchasing behaviour? Content analysis of nutrition content, behaviour change theory and user quality integration. Public Health Nutrition 2018;21(2):288 View
  23. Bland C, Dalrymple K, White S, Moore A, Poston L, Flynn A. Smartphone applications available to pregnant women in the United Kingdom: An assessment of nutritional information. Maternal & Child Nutrition 2020;16(2) View
  24. Tavares B, Pires I, Marques G, Garcia N, Zdravevski E, Lameski P, Trajkovik V, Jevremovic A. Mobile Applications for Training Plan Using Android Devices: A Systematic Review and a Taxonomy Proposal. Information 2020;11(7):343 View
  25. Flaherty S, McCarthy M, Collins A, McCafferty C, McAuliffe F. A phenomenological exploration of change towards healthier food purchasing behaviour in women from a lower socioeconomic background using a health app. Appetite 2020;147:104566 View
  26. Pendergast F, Leech R, McNaughton S. Novel Online or Mobile Methods to Assess Eating Patterns. Current Nutrition Reports 2017;6(3):212 View
  27. Li Y, Ding J, Wang Y, Tang C, Zhang P. Nutrition-Related Mobile Apps in the China App Store: Assessment of Functionality and Quality. JMIR mHealth and uHealth 2019;7(7):e13261 View
  28. Maringer M, Wisse-Voorwinden N, Veer P, Geelen A. Food identification by barcode scanning in the Netherlands: a quality assessment of labelled food product databases underlying popular nutrition applications. Public Health Nutrition 2018:1 View
  29. Samoggia A, Riedel B. Assessment of nutrition-focused mobile apps' influence on consumers' healthy food behaviour and nutrition knowledge. Food Research International 2020;128:108766 View
  30. Teasdale N, Elhussein A, Butcher F, Piernas C, Cowburn G, Hartmann-Boyce J, Saksena R, Scarborough P. Systematic review and meta-analysis of remotely delivered interventions using self-monitoring or tailored feedback to change dietary behavior. The American Journal of Clinical Nutrition 2018;107(2):247 View
  31. Conrad J, Nöthlings U. Innovative approaches to estimate individual usual dietary intake in large-scale epidemiological studies. Proceedings of the Nutrition Society 2017;76(3):213 View
  32. Villasana M, Pires I, Sá J, Garcia N, Zdravevski E, Chorbev I, Lameski P, Flórez-Revuelta F. Mobile Applications for the Promotion and Support of Healthy Nutrition and Physical Activity Habits: A Systematic Review, Extraction of Features and Taxonomy Proposal. The Open Bioinformatics Journal 2019;13(1):50 View
  33. Demiris G, Iribarren S, Sward K, Lee S, Yang R. Patient generated health data use in clinical practice: A systematic review. Nursing Outlook 2019;67(4):311 View
  34. Eldridge A, Piernas C, Illner A, Gibney M, Gurinović M, de Vries J, Cade J. Evaluation of New Technology-Based Tools for Dietary Intake Assessment—An ILSI Europe Dietary Intake and Exposure Task Force Evaluation. Nutrients 2018;11(1):55 View
  35. Potemkina N, Bolshakov A, Krutko V, Mamikonova O. INFORMATION AND COMPUTER SUPPORT OF HEALTHY NUTRITION AS A CURRENT METHOD OF HEALTH SAVING AND FOOD HYGIENE IN MODERN ENVIRONMENTAL CONDITIONS. Hygiene and sanitation 2019;96(11):1078 View
  36. Fallaize R, Zenun Franco R, Pasang J, Hwang F, Lovegrove J. Popular Nutrition-Related Mobile Apps: An Agreement Assessment Against a UK Reference Method. JMIR mHealth and uHealth 2019;7(2):e9838 View
  37. Osadchiy T, Poliakov I, Olivier P, Rowland M, Foster E. Progressive 24-Hour Recall: Usability Study of Short Retention Intervals in Web-Based Dietary Assessment Surveys. Journal of Medical Internet Research 2020;22(2):e13266 View
  38. Zhang P, Dong L, Chen H, Chai Y, Liu J. The Rise and Need for Mobile Apps for Maternal and Child Health Care in China: Survey Based on App Markets. JMIR mHealth and uHealth 2018;6(6):e140 View
  39. Minnens F, Marques A, Domingo J, Verbeke W. Consumers’ acceptance of an online tool with personalized health risk-benefit communication about seafood consumption (Preprint). JMIR Formative Research 2019 View
  40. Fallaize R, Franco R, Hwang F, Lovegrove J, Portero-Otin M. Evaluation of the eNutri automated personalised nutrition advice by users and nutrition professionals in the UK. PLOS ONE 2019;14(4):e0214931 View
  41. Pentikäinen S, Tanner H, Karhunen L, Kolehmainen M, Poutanen K, Pennanen K. Mobile Phone App for Self-Monitoring of Eating Rhythm: Field Experiment. JMIR mHealth and uHealth 2019;7(3):e11490 View
  42. Ahmed M, Oh A, Vanderlee L, Franco-Arellano B, Schermel A, Lou W, L’Abbé M. A randomized controlled trial examining consumers’ perceptions and opinions on using different versions of a FoodFlip© smartphone application for delivery of nutrition information. International Journal of Behavioral Nutrition and Physical Activity 2020;17(1) View
  43. Tejpal S, Sanghera N, Manoharan V, Planas-Iglesias J, Bastie C, Klein-Seetharaman J. Angiotensin Converting Enzyme (ACE): A Marker for Personalized Feedback on Dieting. Nutrients 2020;12(3):660 View
  44. Calegari L, Barbosa J, Marodin G, Fettermann D. A conjoint analysis to consumer choice in Brazil: Defining device attributes for recognizing customized foods characteristics. Food Research International 2018;109:1 View
  45. Gadenz S, Harzheim E, Amaral H, Drehmer M. Development and Assessment of a Mobile Nutritional Counseling Tool for Primary Care Physicians. Telemedicine and e-Health 2020;26(6):805 View
  46. Holmes W, Moorhead S, Coates V, Bond R, Zheng H. Impact of digital technologies for communicating messages on weight loss maintenance: a systematic literature review. European Journal of Public Health 2019;29(2):320 View
  47. Flaherty S, McCarthy M, Collins A, McAuliffe F. A different perspective on consumer engagement: exploring the experience of using health apps to support healthier food purchasing. Journal of Marketing Management 2019;35(3-4):310 View
  48. Schiro J, Shan L, Tatlow-Golden M, Li C, Wall P. #Healthy: smart digital food safety and nutrition communication strategies—a critical commentary. npj Science of Food 2020;4(1) View
  49. Alfonsi J, Choi E, Arshad T, Sammott S, Pais V, Nguyen C, Maguire B, Stinson J, Palmert M. Carbohydrate Counting App Using Image Recognition for Youth With Type 1 Diabetes: Pilot Randomized Control Trial. JMIR mHealth and uHealth 2020;8(10):e22074 View
  50. Shinozaki N, Murakami K. Evaluation of the Ability of Diet-Tracking Mobile Applications to Estimate Energy and Nutrient Intake in Japan. Nutrients 2020;12(11):3327 View
  51. Sudo K, Murasaki K, Kinebuchi T, Kimura S, Waki K. Machine Learning–Based Screening of Healthy Meals From Image Analysis: System Development and Pilot Study. JMIR Formative Research 2020;4(10):e18507 View
  52. Windasari N, Lin F, Kato-Lin Y. Continued use of wearable fitness technology: A value co-creation perspective. International Journal of Information Management 2021;57:102292 View
  53. Zečević M, Mijatović D, Kos Koklič M, Žabkar V, Gidaković P. User Perspectives of Diet-Tracking Apps: Reviews Content Analysis and Topic Modeling. Journal of Medical Internet Research 2021;23(4):e25160 View
  54. Flaherty S, McCarthy M, Collins A, McCafferty C, McAuliffe F. Exploring engagement with health apps: the emerging importance of situational involvement and individual characteristics. European Journal of Marketing 2021;ahead-of-print(ahead-of-print) View

Books/Policy Documents

  1. de Moraes Lopes M, Ferreira D, Ferreira A, da Silva G, Caetano A, Braz V. Artificial Intelligence in Precision Health. View
  2. Valentim Pereira G, Pires I, Marques G, Garcia N, Zdravevski E, Lameski P, Flórez-Revuelta F, Spinsante S. Internet of Things and Big Data Applications. View
  3. Kwong K, Collins A. Enhancing Student-Centred Teaching in Higher Education. View
  4. Giazitzi K, Karathanos V, Boskou G. Quality Assurance in the Era of Individualized Medicine. View
  5. Al-Sayed L. Food Tech Transitions. View