Published on in Vol 3, No 4 (2015): Oct-Dec

The Most Popular Smartphone Apps for Weight Loss: A Quality Assessment

The Most Popular Smartphone Apps for Weight Loss: A Quality Assessment

The Most Popular Smartphone Apps for Weight Loss: A Quality Assessment

Journals

  1. 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
  2. Puigdomenech Puig E, Robles N, Saigí-Rubió F, Zamora A, Moharra M, Paluzie G, Balfegó M, Cuatrecasas Cambra G, Garcia-Lorda P, Carrion C. Assessment of the Efficacy, Safety, and Effectiveness of Weight Control and Obesity Management Mobile Health Interventions: Systematic Review. JMIR mHealth and uHealth 2019;7(10):e12612 View
  3. Chen J, Lieffers J, Bauman A, Hanning R, Allman-Farinelli M. The use of smartphone health apps and other mobile health (mHealth) technologies in dietetic practice: a three country study. Journal of Human Nutrition and Dietetics 2017;30(4):439 View
  4. Willcox J, Dobson R, Whittaker R. Old-Fashioned Technology in the Era of “Bling”: Is There a Future for Text Messaging in Health Care?. Journal of Medical Internet Research 2019;21(12):e16630 View
  5. Griffiths C, Harnack L, Pereira M. Assessment of the accuracy of nutrient calculations of five popular nutrition tracking applications. Public Health Nutrition 2018;21(8):1495 View
  6. Wang Y, Wang Y, Greene B, Sun L. An analysis and evaluation of quality and behavioral change techniques among physical activity apps in China. International Journal of Medical Informatics 2020;133:104029 View
  7. Chen J, Allman-Farinelli M. Impact of Training and Integration of Apps Into Dietetic Practice on Dietitians’ Self-Efficacy With Using Mobile Health Apps and Patient Satisfaction. JMIR mHealth and uHealth 2019;7(3):e12349 View
  8. Castellano-Tejedor C, Moreno J, Ciudin A, Parramón G, Lusilla-Palacios P. PREventive Care Infrastructure based On Ubiquitous Sensing (PRECIOUS): A Study Protocol. JMIR Research Protocols 2017;6(5):e105 View
  9. Nikolaou C, Lean M. Mobile applications for obesity and weight management: current market characteristics. International Journal of Obesity 2017;41(1):200 View
  10. Liu H, Chia R, Setiawan I, Crytzer T, Ding D. Development of “My Wheelchair Guide” app: a qualitative study. Disability and Rehabilitation: Assistive Technology 2019;14(8):839 View
  11. 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
  12. Holzmann S, Holzapfel C. A Scientific Overview of Smartphone Applications and Electronic Devices for Weight Management in Adults. Journal of Personalized Medicine 2019;9(2):31 View
  13. Zhou L, Saptono A, Setiawan I, Parmanto B. Making Self-Management Mobile Health Apps Accessible to People With Disabilities: Qualitative Single-Subject Study. JMIR mHealth and uHealth 2020;8(1):e15060 View
  14. 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
  15. Kim M, Kim Y, Go Y, Lee S, Na M, Lee Y, Choi S, Choi H. Multidimensional Cognitive Behavioral Therapy for Obesity Applied by Psychologists Using a Digital Platform: Open-Label Randomized Controlled Trial. JMIR mHealth and uHealth 2020;8(4):e14817 View
  16. Liu Y, Wu S, Lin S, Chen C, Lin Y, Chen H. Usability of Food Size Aids in Mobile Dietary Reporting Apps for Young Adults: Randomized Controlled Trial. JMIR mHealth and uHealth 2020;8(4):e14543 View
  17. Azar K, Bennett G, Nolting L, Rosas L, Burke L, Ma J. A framework for examining the function of digital health technologies for weight management. Translational Behavioral Medicine 2018;8(2):280 View
  18. Hoppe C, Cade J, Carter M. An evaluation of diabetes targeted apps for Android smartphone in relation to behaviour change techniques. Journal of Human Nutrition and Dietetics 2017;30(3):326 View
  19. Abrahams M, Matusheski N. Personalised nutrition technologies: a new paradigm for dietetic practice and training in a digital transformation era. Journal of Human Nutrition and Dietetics 2020;33(3):295 View
  20. Alnasser A, Kyle J, Alkhalifah A, Marais D. Relationship Between Evidence Requirements, User Expectations, and Actual Experiences: Usability Evaluation of the Twazon Arabic Weight Loss App. JMIR Human Factors 2018;5(2):e16 View
  21. Wang Y, Min J, Khuri J, Xue H, Xie B, A Kaminsky L, J Cheskin L. Effectiveness of Mobile Health Interventions on Diabetes and Obesity Treatment and Management: Systematic Review of Systematic Reviews. JMIR mHealth and uHealth 2020;8(4):e15400 View
  22. DiFilippo K, Huang W, Chapman-Novakofski K. A New Tool for Nutrition App Quality Evaluation (AQEL): Development, Validation, and Reliability Testing. JMIR mHealth and uHealth 2017;5(10):e163 View
  23. Cho J, Kim S. Personal and social predictors of use and non-use of fitness/diet app: Application of Random Forest algorithm. Telematics and Informatics 2020;55:101301 View
  24. 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
  25. 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
  26. Simpson S, Matthews L, Pugmire J, McConnachie A, McIntosh E, Coulman E, Hughes K, Kelson M, Morgan-Trimmer S, Murphy S, Utkina-Macaskill O, Moore L. An app-, web- and social support-based weight loss intervention for adults with obesity: the HelpMeDoIt! feasibility RCT. Public Health Research 2020;8(3):1 View
  27. Christmann C, Hoffmann A, Bleser G. Stress Management Apps With Regard to Emotion-Focused Coping and Behavior Change Techniques: A Content Analysis. JMIR mHealth and uHealth 2017;5(2):e22 View
  28. Chen R, Santo K, Wong G, Sohn W, Spallek H, Chow C, Irving M. Mobile Apps for Dental Caries Prevention: Systematic Search and Quality Evaluation. JMIR mHealth and uHealth 2021;9(1):e19958 View
  29. Maheu M, Nicolucci V, Pulier M, Wall K, Frye T, Hudlicka E. The Interactive Mobile App Review Toolkit (IMART): a Clinical Practice-Oriented System. Journal of Technology in Behavioral Science 2016;1(1-4):3 View
  30. Smyth B, Fehlberg B. Australian post-separation parenting on the smartphone: What’s ‘App-ening?. Journal of Social Welfare and Family Law 2019;41(1):53 View
  31. Khazen W, Jeanne J, Demaretz L, Schäfer F, Fagherazzi G. Rethinking the Use of Mobile Apps for Dietary Assessment in Medical Research. Journal of Medical Internet Research 2020;22(6):e15619 View
  32. Rivera J, McPherson A, Hamilton J, Birken C, Coons M, Peters M, Iyer S, George T, Nguyen C, Stinson J. User-Centered Design of a Mobile App for Weight and Health Management in Adolescents With Complex Health Needs: Qualitative Study. JMIR Formative Research 2018;2(1):e7 View
  33. Balapour A, Reychav I, Sabherwal R, Azuri J. Mobile technology identity and self-efficacy: Implications for the adoption of clinically supported mobile health apps. International Journal of Information Management 2019;49:58 View
  34. Aromatario O, Van Hoye A, Vuillemin A, Foucaut A, Crozet C, Pommier J, Cambon L. How do mobile health applications support behaviour changes? A scoping review of mobile health applications relating to physical activity and eating behaviours. Public Health 2019;175:8 View
  35. Wills A, Garry J, Hubbard J, Mezoian T, Breen C, Ortiz-Miller C, Nalipinski P, Sullivan S, Berry J, Cudkowicz M, Paganoni S, Chan J, Macklin E. Nutritional counseling with or without mobile health technology: a randomized open-label standard-of-care-controlled trial in ALS. BMC Neurology 2019;19(1) View
  36. Lupton D. ‘I Just Want It to Be Done, Done, Done!’ Food Tracking Apps, Affects, and Agential Capacities. Multimodal Technologies and Interaction 2018;2(2):29 View
  37. Hendrie G, Hussain M, Brindal E, James-Martin G, Williams G, Crook A. Impact of a Mobile Phone App to Increase Vegetable Consumption and Variety in Adults: Large-Scale Community Cohort Study. JMIR mHealth and uHealth 2020;8(4):e14726 View
  38. Forman E, Goldstein S, Crochiere R, Butryn M, Juarascio A, Zhang F, Foster G. Randomized controlled trial of OnTrack, a just-in-time adaptive intervention designed to enhance weight loss. Translational Behavioral Medicine 2019;9(6):989 View
  39. Teixeira V, Voci S, Mendes-Netto R, da Silva D. The relative validity of a food record using the smartphone application MyFitnessPal. Nutrition & Dietetics 2018;75(2):219 View
  40. 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
  41. Chen J, Lieffers J, Bauman A, Hanning R, Allman-Farinelli M. Designing Health Apps to Support Dietetic Professional Practice and Their Patients: Qualitative Results From an International Survey. JMIR mHealth and uHealth 2017;5(3):e40 View
  42. Alamoodi A, Garfan S, Zaidan B, Zaidan A, Shuwandy M, Alaa M, Alsalem M, Mohammed A, Aleesa A, Albahri O, Al-Hussein W, Alobaidi O. A systematic review into the assessment of medical apps: motivations, challenges, recommendations and methodological aspect. Health and Technology 2020;10(5):1045 View
  43. Forman E, Goldstein S, Zhang F, Evans B, Manasse S, Butryn M, Juarascio A, Abichandani P, Martin G, Foster G. OnTrack: development and feasibility of a smartphone app designed to predict and prevent dietary lapses. Translational Behavioral Medicine 2019;9(2):236 View
  44. Mummah S, Robinson T, King A, Gardner C, Sutton S. IDEAS (Integrate, Design, Assess, and Share): A Framework and Toolkit of Strategies for the Development of More Effective Digital Interventions to Change Health Behavior. Journal of Medical Internet Research 2016;18(12):e317 View
  45. Chen J, Gemming L, Hanning R, Allman-Farinelli M. Smartphone apps and the nutrition care process: Current perspectives and future considerations. Patient Education and Counseling 2018;101(4):750 View
  46. Pulier M, Daviss S. A Call for a Global Digital Health Consortium. Journal of Technology in Behavioral Science 2016;1(1-4):16 View
  47. Nouri R, R Niakan Kalhori S, Ghazisaeedi M, Marchand G, Yasini M. Criteria for assessing the quality of mHealth apps: a systematic review. Journal of the American Medical Informatics Association 2018;25(8):1089 View
  48. Eikey E, Reddy M, Booth K, Kvasny L, Blair J, Li V, Poole E. Desire to Be Underweight: Exploratory Study on a Weight Loss App Community and User Perceptions of the Impact on Disordered Eating Behaviors. JMIR mHealth and uHealth 2017;5(10):e150 View
  49. Partridge S, Redfern J. Strategies to Engage Adolescents in Digital Health Interventions for Obesity Prevention and Management. Healthcare 2018;6(3):70 View
  50. Allman-Farinelli M, Gemming L. Technology Interventions to Manage Food Intake: Where Are We Now?. Current Diabetes Reports 2017;17(11) View
  51. Cade J. Measuring diet in the 21st century: use of new technologies. Proceedings of the Nutrition Society 2017;76(3):276 View
  52. Hood M, Wilson R, Corsica J, Bradley L, Chirinos D, Vivo A. What do we know about mobile applications for diabetes self-management? A review of reviews. Journal of Behavioral Medicine 2016;39(6):981 View
  53. Gabizon I, Bhagirath V, Lokker C, Bhavnani S, Lonn E. What do physicians need to know in order to ‘prescribe’ mobile applications to patients with cardiovascular disease?. Personalized Medicine 2019;16(4):263 View
  54. Huang Z, Lum E, Car J. Medication Management Apps for Diabetes: Systematic Assessment of the Transparency and Reliability of Health Information Dissemination. JMIR mHealth and uHealth 2020;8(2):e15364 View
  55. 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
  56. Chen J, Bauman A, Allman-Farinelli M. A Study to Determine the Most Popular Lifestyle Smartphone Applications and Willingness of the Public to Share Their Personal Data for Health Research. Telemedicine and e-Health 2016;22(8):655 View
  57. Bouslimani A, Melnik A, Xu Z, Amir A, da Silva R, Wang M, Bandeira N, Alexandrov T, Knight R, Dorrestein P. Lifestyle chemistries from phones for individual profiling. Proceedings of the National Academy of Sciences 2016;113(48):E7645 View
  58. 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
  59. Albrecht U, Malinka C, Long S, Raupach T, Hasenfuß G, von Jan U. Quality Principles of App Description Texts and Their Significance in Deciding to Use Health Apps as Assessed by Medical Students: Survey Study. JMIR mHealth and uHealth 2019;7(2):e13375 View
  60. Franco R, Fallaize R, Lovegrove J, Hwang F. Popular Nutrition-Related Mobile Apps: A Feature Assessment. JMIR mHealth and uHealth 2016;4(3):e85 View
  61. Chen J, Berkman W, Bardouh M, Ng C, Allman-Farinelli M. The use of a food logging app in the naturalistic setting fails to provide accurate measurements of nutrients and poses usability challenges. Nutrition 2019;57:208 View
  62. Jones A, Mitchell L, O'Connor R, Rollo M, Slater K, Williams L, Ball L. Investigating the Perceptions of Primary Care Dietitians on the Potential for Information Technology in the Workplace: Qualitative Study. Journal of Medical Internet Research 2018;20(10):e265 View
  63. Banerjee P, Mendu V, Korrapati D, Gavaravarapu S. Calorie counting smart phone apps: Effectiveness in nutritional awareness, lifestyle modification and weight management among young Indian adults. Health Informatics Journal 2020;26(2):816 View
  64. Ghelani D, Moran L, Johnson C, Mousa A, Naderpoor N. Mobile Apps for Weight Management: A Review of the Latest Evidence to Inform Practice. Frontiers in Endocrinology 2020;11 View
  65. Siddiqui N, Hodges S, Sharif M. Availability of orthodontic smartphone apps. Journal of Orthodontics 2019;46(3):235 View
  66. 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
  67. 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
  68. Sullivan R, Marsh S, Halvarsson J, Holdsworth M, Waterlander W, Poelman M, Salmond J, Christian H, Koh L, Cade J, Spence J, Woodward A, Maddison R. Smartphone Apps for Measuring Human Health and Climate Change Co-Benefits: A Comparison and Quality Rating of Available Apps. JMIR mHealth and uHealth 2016;4(4):e135 View
  69. Gilmore L, Klempel M, Martin C, Myers C, Burton J, Sutton E, Redman L. Personalized Mobile Health Intervention for Health and Weight Loss in Postpartum Women Receiving Women, Infants, and Children Benefit: A Randomized Controlled Pilot Study. Journal of Women's Health 2017;26(7):719 View
  70. Bondaronek P, Alkhaldi G, Slee A, Hamilton F, Murray E. Quality of Publicly Available Physical Activity Apps: Review and Content Analysis. JMIR mHealth and uHealth 2018;6(3):e53 View
  71. Andersson A, Winslott Hiselius L, Adell E. Promoting sustainable travel behaviour through the use of smartphone applications: A review and development of a conceptual model. Travel Behaviour and Society 2018;11:52 View
  72. Kim J, Talikoti A, Boutin M. A 3-Step Process to Estimate Phenylalanine in Commercial Foods for PKU Management. IEEE Access 2018;6:30758 View
  73. Gómez-de-Regil L, Avila-Nava A, Gutierrez-Solis A, Lugo R. Mobile Apps for the Management of Comorbid Overweight/Obesity and Depression/Anxiety: A Systematic Review. Journal of Healthcare Engineering 2020;2020:1 View
  74. 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
  75. Carter M, Hancock N, Albar S, Brown H, Greenwood D, Hardie L, Frost G, Wark P, Cade J. Development of a New Branded UK Food Composition Database for an Online Dietary Assessment Tool. Nutrients 2016;8(8):480 View
  76. 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
  77. Fong S, Ng S, Cheng Y, Zhang J, Chung L, Chow G, Chak Y, Chan I, Macfarlane D. Comparison between smartphone pedometer applications and traditional pedometers for improving physical activity and body mass index in community-dwelling older adults. Journal of Physical Therapy Science 2016;28(5):1651 View
  78. Gentili C, Zetterqvist V, Rickardsson J, Holmström L, Simons L, Wicksell R. ACTsmart – development and feasibility of digital Acceptance and Commitment Therapy for adults with chronic pain. npj Digital Medicine 2020;3(1) View
  79. Xiao Q, Lu S, Wang Y, Sun L, Wu Y. Current Status of Cardiovascular Disease-Related Smartphone Apps Downloadable in China. Telemedicine and e-Health 2017;23(3):219 View
  80. Lee K, Kim H, Lee S, Ha H. Changes in Weight and Health-Related Behavior Using Smartphone Applications in Patients With Colorectal Polyps. Journal of Nutrition Education and Behavior 2019;51(5):539 View
  81. Ryan K, Murphy L, Linehan C, Dockray S. Theory in practice: identifying theory-based techniques in health coaches’ tailored feedback during a weight loss intervention. Psychology & Health 2020;35(11):1384 View
  82. Bauer M, Glenn T, Geddes J, Gitlin M, Grof P, Kessing L, Monteith S, Faurholt-Jepsen M, Severus E, Whybrow P. Smartphones in mental health: a critical review of background issues, current status and future concerns. International Journal of Bipolar Disorders 2020;8(1) View
  83. Zhao J, Freeman B, Li M. How Do Infant Feeding Apps in China Measure Up? A Content Quality Assessment. JMIR mHealth and uHealth 2017;5(12):e186 View
  84. Hoj T, Covey E, Jones A, Haines A, Hall P, Crookston B, West J. How Do Apps Work? An Analysis of Physical Activity App Users’ Perceptions of Behavior Change Mechanisms. JMIR mHealth and uHealth 2017;5(8):e114 View
  85. Thompson-Felty C, Johnston C. Adherence to Diet Applications Using a Smartphone Was Associated With Weight Loss in Healthy Overweight Adults Irrespective of the Application. Journal of Diabetes Science and Technology 2017;11(1):184 View
  86. Wellard-Cole L, Chen J, Davies A, Wong A, Huynh S, Rangan A, Allman-Farinelli M. Relative Validity of the Eat and Track (EaT) Smartphone App for Collection of Dietary Intake Data in 18-to-30-Year Olds. Nutrients 2019;11(3):621 View
  87. Tosi M, Radice D, Carioni G, Vecchiati T, Fiori F, Parpinel M, Gnagnarella P. Accuracy of applications to monitor food intake: Evaluation by comparison with 3-d food diary. Nutrition 2021;84:111018 View
  88. 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
  89. Toro-Ramos T, Lee D, Kim Y, Michaelides A, Oh T, Kim K, Jang H, Lim S. Effectiveness of a Smartphone Application for the Management of Metabolic Syndrome Components Focusing on Weight Loss: A Preliminary Study. Metabolic Syndrome and Related Disorders 2017;15(9):465 View
  90. DiFilippo K, Huang W, Chapman-Novakofski K. Mobile Apps for the Dietary Approaches to Stop Hypertension (DASH): App Quality Evaluation. Journal of Nutrition Education and Behavior 2018;50(6):620 View
  91. Ferrara G, Kim J, Lin S, Hua J, Seto E. A Focused Review of Smartphone Diet-Tracking Apps: Usability, Functionality, Coherence With Behavior Change Theory, and Comparative Validity of Nutrient Intake and Energy Estimates. JMIR mHealth and uHealth 2019;7(5):e9232 View
  92. Wellard-Cole L, Jung J, Kay J, Rangan A, Chapman K, Watson W, Hughes C, Ni Mhurchu C, Bauman A, Gemming L, Yacef K, Koprinska I, Allman-Farinelli M. Examining the Frequency and Contribution of Foods Eaten Away From Home in the Diets of 18- to 30-Year-Old Australians Using Smartphone Dietary Assessment (MYMeals): Protocol for a Cross-Sectional Study. JMIR Research Protocols 2018;7(1):e24 View
  93. van Beurden S, Smith J, Lawrence N, Abraham C, Greaves C. Feasibility Randomized Controlled Trial of ImpulsePal: Smartphone App–Based Weight Management Intervention to Reduce Impulsive Eating in Overweight Adults. JMIR Formative Research 2019;3(2):e11586 View
  94. Robbins R, Krebs P, Jagannathan R, Jean-Louis G, Duncan D. Health App Use Among US Mobile Phone Users: Analysis of Trends by Chronic Disease Status. JMIR mHealth and uHealth 2017;5(12):e197 View
  95. Frie K, Hartmann-Boyce J, Jebb S, Albury C, Nourse R, Aveyard P. Insights From Google Play Store User Reviews for the Development of Weight Loss Apps: Mixed-Method Analysis. JMIR mHealth and uHealth 2017;5(12):e203 View
  96. Baretta D, Bondaronek P, Direito A, Steca P. Implementation of the goal-setting components in popular physical activity apps: Review and content analysis. DIGITAL HEALTH 2019;5:205520761986270 View
  97. Milne-Ives M, Lam C, van Velthoven M, Meinert E. Mobile Fitness and Weight Management Apps: Protocol for a Quality Evaluation. JMIR Research Protocols 2020;9(9):e17685 View
  98. Lee J, Bae S, Park D, Kim Y, Park J. The effectiveness of a monetary reimbursement model for weight reduction via a smartphone application: a preliminary retrospective study. Scientific Reports 2020;10(1) View
  99. Asbjørnsen R, Wentzel J, Smedsrød M, Hjelmesæth J, Clark M, Solberg Nes L, Van Gemert-Pijnen J. Identifying Persuasive Design Principles and Behavior Change Techniques Supporting End User Values and Needs in eHealth Interventions for Long-Term Weight Loss Maintenance: Qualitative Study. Journal of Medical Internet Research 2020;22(11):e22598 View
  100. Joo E, Kononova A, Kanthawala S, Peng W, Cotten S. Smartphone Users’ Persuasion Knowledge in the Context of Consumer mHealth Apps: Qualitative Study. JMIR mHealth and uHealth 2021;9(4):e16518 View
  101. Trottier C, Lieffers J, Johnson S, Mota J, Gill R, Prado C. The Impact of a Web-Based Mindfulness, Nutrition, and Physical Activity Platform on the Health Status of First-Year University Students: Protocol for a Randomized Controlled Trial. JMIR Research Protocols 2021;10(3):e24534 View
  102. Blanchard C, Chin M, Gilhooly C, Barger K, Matuszek G, Miki A, Côté R, Eldridge A, Green H, Mainardi F, Mehers D, Ronga F, Steullet V, Das S. Evaluation of PIQNIQ, a Novel Mobile Application for Capturing Dietary Intake. The Journal of Nutrition 2021;151(5):1347 View
  103. Zugasti Murillo A. Applicability of innovation in clinical nutrition. Nutrición Hospitalaria 2021 View
  104. Keaver L, Loftus A, Quinn L. A review of iPhone and Android apps for cancer patients and survivors: assessing their quality, nutrition information and behaviour change techniques. Journal of Human Nutrition and Dietetics 2021;34(3):572 View
  105. Lugones-Sanchez C, Sanchez-Calavera M, Repiso-Gento I, Adalia E, Ramirez-Manent J, Agudo-Conde C, Rodriguez-Sanchez E, Gomez-Marcos M, Recio-Rodriguez J, Garcia-Ortiz L. Effectiveness of an mHealth Intervention Combining a Smartphone App and Smart Band on Body Composition in an Overweight and Obese Population: Randomized Controlled Trial (EVIDENT 3 Study). JMIR mHealth and uHealth 2020;8(11):e21771 View
  106. Shaw M, Satchell L, Thompson S, Harper E, Balsalobre-Fernández C, Peart D. Smartphone and Tablet Software Apps to Collect Data in Sport and Exercise Settings: Cross-sectional International Survey. JMIR mHealth and uHealth 2021;9(5):e21763 View
  107. Turner-McGrievy G, Yang C, Monroe C, Pellegrini C, West D. Is Burden Always Bad? Emerging Low-Burden Approaches to Mobile Dietary Self-monitoring and the Role Burden Plays with Engagement. Journal of Technology in Behavioral Science 2021;6(3):447 View
  108. Choi J, Chung C, Woo H. Diet-Related Mobile Apps to Promote Healthy Eating and Proper Nutrition: A Content Analysis and Quality Assessment. International Journal of Environmental Research and Public Health 2021;18(7):3496 View
  109. 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
  110. Jacobsen L, Stancu V, Wang Q, Aschemann-Witzel J, Lähteenmäki L. Connecting food consumers to organisations, peers, and technical devices: The potential of interactive communication technology to support consumers’ value creation. Trends in Food Science & Technology 2021;109:622 View
  111. Hensher M, Cooper P, Dona S, Angeles M, Nguyen D, Heynsbergh N, Chatterton M, Peeters A. Scoping review: Development and assessment of evaluation frameworks of mobile health apps for recommendations to consumers. Journal of the American Medical Informatics Association 2021;28(6):1318 View
  112. Olson K, Goldstein S, Lillis J, Panza E. Weight stigma is overlooked in commercial‐grade mobile applications for weight loss and weight‐related behaviors. Obesity Science & Practice 2021;7(2):244 View
  113. Kelly J, Collins P, McCamley J, Ball L, Roberts S, Campbell K. Digital disruption of dietetics: are we ready?. Journal of Human Nutrition and Dietetics 2021;34(1):134 View
  114. 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
  115. Zhang L, Misir A, Boshuizen H, Ocké M. A Systematic Review and Meta-Analysis of Validation Studies Performed on Dietary Record Apps. Advances in Nutrition 2021 View
  116. Tam E, Boas P, Ruaro F, Flesch J, Wu J, Thomas A, Li J, Lopes F. Feasibility and Adoption of a Focused Digital Wellness Program in Older Adults. Geriatrics 2021;6(2):54 View
  117. Chan V, Davies A, Wellard-Cole L, Lu S, Ng H, Tsoi L, Tiscia A, Signal L, Rangan A, Gemming L, Allman-Farinelli M. Using Wearable Cameras to Assess Foods and Beverages Omitted in 24 Hour Dietary Recalls and a Text Entry Food Record App. Nutrients 2021;13(6):1806 View
  118. Yang Q, Mitchell E, Ho A, DeLuca L, Behr H, Michaelides A. Cross-National Outcomes of a Digital Weight Loss Intervention in the United States, Canada, United Kingdom and Ireland, and Australia and New Zealand: A Retrospective Analysis. Frontiers in Public Health 2021;9 View
  119. Briggs T, Quick V, Hallman W. Feature Availability Comparison in Free and Paid Versions of Popular Smartphone Weight Management Applications. Journal of Nutrition Education and Behavior 2021 View
  120. Woulfe F, Fadahunsi P, Smith S, Chirambo G, Larsson E, Henn P, Mawkin M, O’ Donoghue J. The Identification and Evaluation of Methodologies to Assess the Quality of mHealth apps in High, Low & Middle-Income Countries: a Rapid Review (Preprint). JMIR mHealth and uHealth 2021 View

Books/Policy Documents

  1. 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
  2. Galhotra R. Nutrients in Dairy and their Implications on Health and Disease. View
  3. Šmahel D, Macháčková H, Šmahelová M, Čevelíček M, Almenara C, Holubčíková J. Digital Technology, Eating Behaviors, and Eating Disorders. View
  4. Adewumi A, Olatunde G, Misra S, Maskeliūnas R, Damaševičius R. Information Technology Science. View
  5. Dufort A, Gregory E, Woo T. Humanism and Resilience in Residency Training. View
  6. Lyzwinski L. Obesity and Diabetes. View