Explore our sister journals here.

Maintenance Notice

Due to necessary scheduled maintenance, the JMIR Publications website will be unavailable from Wednesday, July 01, 2020 at 8:00 PM to 10:00 PM EST. We apologize in advance for any inconvenience this may cause you.

Who will be affected?

Citing this Article

Right click to copy or hit: ctrl+c (cmd+c on mac)

Published on 16.12.15 in Vol 3, No 4 (2015): Oct-Dec

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

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

Juliana Chen, Janet E Cade, Margaret Allman-Farinelli

JMIR Mhealth Uhealth 2015 (Dec 16); 3(4):e104 

According to Crossref, the following articles are citing this article (DOI 10.2196/mhealth.4334):

(note that this is only a small subset of citations)

  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
    CrossRef
  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
    CrossRef
  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
    CrossRef
  4. Willcox JC, 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
    CrossRef
  5. Griffiths C, Harnack L, Pereira MA. Assessment of the accuracy of nutrient calculations of five popular nutrition tracking applications. Public Health Nutrition 2018;21(8):1495
    CrossRef
  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
    CrossRef
  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
    CrossRef
  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
    CrossRef
  9. Nikolaou CK, Lean MEJ. Mobile applications for obesity and weight management: current market characteristics. International Journal of Obesity 2017;41(1):200
    CrossRef
  10. Liu HT, Chia R, Setiawan IMA, Crytzer TM, Ding D. Development of “My Wheelchair Guide” app: a qualitative study. Disability and Rehabilitation: Assistive Technology 2019;14(8):839
    CrossRef
  11. Villasana MV, Pires IM, Sá J, Garcia NM, 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
    CrossRef
  12. Holzmann SL, Holzapfel C. A Scientific Overview of Smartphone Applications and Electronic Devices for Weight Management in Adults. Journal of Personalized Medicine 2019;9(2):31
    CrossRef
  13. Zhou L, Saptono A, Setiawan IMA, 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
    CrossRef
  14. Honary M, Bell BT, Clinch S, Wild SE, 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
    CrossRef
  15. Kim M, Kim Y, Go Y, Lee S, Na M, Lee Y, Choi S, Choi HJ. 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
    CrossRef
  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
    CrossRef
  17. Azar KMJ, Bennett GG, Nolting LA, Rosas LG, Burke LE, Ma J. A framework for examining the function of digital health technologies for weight management. Translational Behavioral Medicine 2018;8(2):280
    CrossRef
  18. Hoppe CD, Cade JE, 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
    CrossRef
  19. Abrahams M, Matusheski NV. 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
    CrossRef
  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
    CrossRef
  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
    CrossRef
  22. DiFilippo KN, Huang W, Chapman-Novakofski KM. A New Tool for Nutrition App Quality Evaluation (AQEL): Development, Validation, and Reliability Testing. JMIR mHealth and uHealth 2017;5(10):e163
    CrossRef
  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
    CrossRef
  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
    CrossRef
  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
    CrossRef
  26. Simpson SA, 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
    CrossRef
  27. Christmann CA, 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
    CrossRef
  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
    CrossRef
  29. Maheu MM, Nicolucci V, Pulier ML, Wall KM, Frye TJ, 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
    CrossRef
  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
    CrossRef
  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
    CrossRef
  32. Rivera J, McPherson AC, 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
    CrossRef
  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
    CrossRef
  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
    CrossRef
  35. Wills AM, Garry J, Hubbard J, Mezoian T, Breen CT, Ortiz-Miller C, Nalipinski P, Sullivan S, Berry JD, Cudkowicz M, Paganoni S, Chan J, Macklin EA. Nutritional counseling with or without mobile health technology: a randomized open-label standard-of-care-controlled trial in ALS. BMC Neurology 2019;19(1)
    CrossRef
  36. . ‘I Just Want It to Be Done, Done, Done!’ Food Tracking Apps, Affects, and Agential Capacities. Multimodal Technologies and Interaction 2018;2(2):29
    CrossRef
  37. Hendrie GA, Hussain MS, 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
    CrossRef
  38. Forman EM, Goldstein SP, Crochiere RJ, Butryn ML, Juarascio AS, Zhang F, Foster GD. Randomized controlled trial of OnTrack, a just-in-time adaptive intervention designed to enhance weight loss. Translational Behavioral Medicine 2019;9(6):989
    CrossRef
  39. Teixeira V, Voci SM, Mendes‐Netto RS, da Silva DG. The relative validity of a food record using the smartphone application MyFitnessPal. Nutrition & Dietetics 2018;75(2):219
    CrossRef
  40. Flaherty SJ, McCarthy MB, Collins AM, McAuliffe FM. 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
    CrossRef
  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
    CrossRef
  42. Alamoodi AH, Garfan S, Zaidan BB, Zaidan AA, Shuwandy ML, Alaa M, Alsalem MA, Mohammed A, Aleesa AM, Albahri OS, Al-Hussein WA, Alobaidi OR. A systematic review into the assessment of medical apps: motivations, challenges, recommendations and methodological aspect. Health and Technology 2020;10(5):1045
    CrossRef
  43. Forman EM, Goldstein SP, Zhang F, Evans BC, Manasse SM, Butryn ML, Juarascio AS, Abichandani P, Martin GJ, Foster GD. OnTrack: development and feasibility of a smartphone app designed to predict and prevent dietary lapses. Translational Behavioral Medicine 2019;9(2):236
    CrossRef
  44. Mummah SA, Robinson TN, King AC, Gardner CD, 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
    CrossRef
  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
    CrossRef
  46. Pulier ML, Daviss S. A Call for a Global Digital Health Consortium. Journal of Technology in Behavioral Science 2016;1(1-4):16
    CrossRef
  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
    CrossRef
  48. Eikey EV, Reddy MC, Booth KM, Kvasny L, Blair JL, Li V, Poole ES. 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
    CrossRef
  49. Partridge S, Redfern J. Strategies to Engage Adolescents in Digital Health Interventions for Obesity Prevention and Management. Healthcare 2018;6(3):70
    CrossRef
  50. Allman-Farinelli M, Gemming L. Technology Interventions to Manage Food Intake: Where Are We Now?. Current Diabetes Reports 2017;17(11)
    CrossRef
  51. . Measuring diet in the 21st century: use of new technologies. Proceedings of the Nutrition Society 2017;76(3):276
    CrossRef
  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
    CrossRef
  53. Gabizon I, Bhagirath V, Lokker C, Bhavnani SP, 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
    CrossRef
  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
    CrossRef
  55. Maringer M, van’t Veer P, Klepacz N, Verain MCD, Normann A, Ekman S, Timotijevic L, Raats MM, 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)
    CrossRef
  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
    CrossRef
  57. Bouslimani A, Melnik AV, Xu Z, Amir A, da Silva RR, Wang M, Bandeira N, Alexandrov T, Knight R, Dorrestein PC. Lifestyle chemistries from phones for individual profiling. Proceedings of the National Academy of Sciences 2016;113(48)
    CrossRef
  58. Bland C, Dalrymple KV, White SL, Moore A, Poston L, Flynn AC. Smartphone applications available to pregnant women in the United Kingdom: An assessment of nutritional information. Maternal & Child Nutrition 2020;16(2)
    CrossRef
  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
    CrossRef
  60. Franco RZ, Fallaize R, Lovegrove JA, Hwang F. Popular Nutrition-Related Mobile Apps: A Feature Assessment. JMIR mHealth and uHealth 2016;4(3):e85
    CrossRef
  61. Chen J, Berkman W, Bardouh M, Ng CYK, 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
    CrossRef
  62. Jones A, Mitchell LJ, O'Connor R, Rollo ME, Slater K, Williams LT, 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
    CrossRef
  63. Banerjee P, Mendu VVR, Korrapati D, Gavaravarapu SM. 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
    CrossRef
  64. Ghelani DP, Moran LJ, 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
    CrossRef
  65. Siddiqui NR, Hodges S, Sharif MO. Availability of orthodontic smartphone apps. Journal of Orthodontics 2019;46(3):235
    CrossRef
  66. Maringer M, Wisse-Voorwinden N, Veer PV, 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
    CrossRef
  67. Tavares BF, Pires IM, Marques G, Garcia NM, 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
    CrossRef
  68. Sullivan RK, Marsh S, Halvarsson J, Holdsworth M, Waterlander W, Poelman MP, Salmond JA, Christian H, Koh LS, Cade JE, Spence JC, 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
    CrossRef
  69. Gilmore LA, Klempel MC, Martin CK, Myers CA, Burton JH, Sutton EF, Redman LM. 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
    CrossRef
  70. Bondaronek P, Alkhaldi G, Slee A, Hamilton FL, Murray E. Quality of Publicly Available Physical Activity Apps: Review and Content Analysis. JMIR mHealth and uHealth 2018;6(3):e53
    CrossRef
  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
    CrossRef
  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
    CrossRef
  73. Gómez-de-Regil L, Avila-Nava A, Gutierrez-Solis AL, Lugo R. Mobile Apps for the Management of Comorbid Overweight/Obesity and Depression/Anxiety: A Systematic Review. Journal of Healthcare Engineering 2020;2020:1
    CrossRef
  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
    CrossRef
  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
    CrossRef
  76. Villasana MV, Pires IM, Sá J, Garcia NM, 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
    CrossRef
  77. Fong SS, Ng SS, Cheng YT, Zhang J, Chung LM, Chow GC, Chak YT, Chan IK, Macfarlane DJ. 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
    CrossRef
  78. Gentili C, Zetterqvist V, Rickardsson J, Holmström L, Simons LE, Wicksell RK. ACTsmart – development and feasibility of digital Acceptance and Commitment Therapy for adults with chronic pain. npj Digital Medicine 2020;3(1)
    CrossRef
  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
    CrossRef
  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
    CrossRef
  81. Ryan K, Murphy LE, 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
    CrossRef
  82. Bauer M, Glenn T, Geddes J, Gitlin M, Grof P, Kessing LV, Monteith S, Faurholt-Jepsen M, Severus E, Whybrow PC. Smartphones in mental health: a critical review of background issues, current status and future concerns. International Journal of Bipolar Disorders 2020;8(1)
    CrossRef
  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
    CrossRef
  84. Hoj TH, Covey EL, Jones AC, Haines AC, Hall PC, Crookston BT, West JH. How Do Apps Work? An Analysis of Physical Activity App Users’ Perceptions of Behavior Change Mechanisms. JMIR mHealth and uHealth 2017;5(8):e114
    CrossRef
  85. Thompson-Felty C, Johnston CS. 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
    CrossRef
  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
    CrossRef
  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
    CrossRef
  88. Agapito G, Simeoni M, Calabrese B, Caré I, Lamprinoudi T, Guzzi PH, 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
    CrossRef
  89. Toro-Ramos T, Lee D, Kim Y, Michaelides A, Oh TJ, Kim KM, Jang HC, 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
    CrossRef
  90. DiFilippo KN, Huang WD, Chapman-Novakofski KM. Mobile Apps for the Dietary Approaches to Stop Hypertension (DASH): App Quality Evaluation. Journal of Nutrition Education and Behavior 2018;50(6):620
    CrossRef
  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
    CrossRef
  92. Wellard-Cole L, Jung J, Kay J, Rangan A, Chapman K, Watson WL, 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
    CrossRef
  93. van Beurden SB, Smith JR, Lawrence NS, Abraham C, Greaves CJ. 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
    CrossRef
  94. Robbins R, Krebs P, Jagannathan R, Jean-Louis G, Duncan DT. Health App Use Among US Mobile Phone Users: Analysis of Trends by Chronic Disease Status. JMIR mHealth and uHealth 2017;5(12):e197
    CrossRef
  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
    CrossRef
  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
    CrossRef
  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
    CrossRef
  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)
    CrossRef
  99. Asbjørnsen RA, Wentzel J, Smedsrød ML, Hjelmesæth J, Clark MM, Solberg Nes L, Van Gemert-Pijnen JEWC. 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
    CrossRef
  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
    CrossRef
  101. Trottier CF, Lieffers JRL, Johnson ST, Mota JF, Gill RK, Prado CM. 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
    CrossRef
  102. Blanchard CM, Chin MK, Gilhooly CH, Barger K, Matuszek G, Miki AJ, Côté RG, Eldridge AL, Green H, Mainardi F, Mehers D, Ronga F, Steullet V, Das SK. Evaluation of PIQNIQ, a Novel Mobile Application for Capturing Dietary Intake. The Journal of Nutrition 2021;151(5):1347
    CrossRef
  103. . Applicability of innovation in clinical nutrition. Nutrición Hospitalaria 2021;
    CrossRef
  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
    CrossRef
  105. Lugones-Sanchez C, Sanchez-Calavera MA, Repiso-Gento I, Adalia EG, Ramirez-Manent JI, Agudo-Conde C, Rodriguez-Sanchez E, Gomez-Marcos MA, Recio-Rodriguez JI, 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
    CrossRef
  106. Shaw MP, Satchell LP, Thompson S, Harper ET, Balsalobre-Fernández C, Peart DJ. 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
    CrossRef
  107. Turner-McGrievy GM, Yang C, Monroe C, Pellegrini C, West DS. 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
    CrossRef
  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
    CrossRef
  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
    CrossRef
  110. Jacobsen LF, Stancu V, Wang QJ, 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
    CrossRef
  111. Hensher M, Cooper P, Dona SWA, Angeles MR, Nguyen D, Heynsbergh N, Chatterton ML, 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
    CrossRef
  112. Olson KL, Goldstein SP, 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
    CrossRef
  113. Kelly JT, Collins PF, McCamley J, Ball L, Roberts S, Campbell KL. Digital disruption of dietetics: are we ready?. Journal of Human Nutrition and Dietetics 2021;34(1):134
    CrossRef
  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
    CrossRef
  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;12(6):2321
    CrossRef
  116. Tam E, Boas PKV, 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
    CrossRef
  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
    CrossRef
  118. Yang Q, Mitchell ES, Ho AS, 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
    CrossRef
  119. Briggs T, Quick V, Hallman WK. Feature Availability Comparison in Free and Paid Versions of Popular Smartphone Weight Management Applications. Journal of Nutrition Education and Behavior 2021;53(9):732
    CrossRef
  120. Woulfe F, Fadahunsi KP, Smith S, Chirambo GB, Larsson E, Henn P, Mawkin M, O’ Donoghue J. Identification and Evaluation of Methodologies to Assess the Quality of Mobile Health Apps in High-, Low-, and Middle-Income Countries: Rapid Review. JMIR mHealth and uHealth 2021;9(10):e28384
    CrossRef
  121. Abdul Basir SM, Abdul Manaf Z, Mohd. Noor N, Mat Ludin AF, Shahar S, Abdul Manaf MR. The Challenges and Strategies towards Healthy Eating during COVID-19 Home Confinement Period among Working Adults with BMI ≥ 25 kg/m2 Enrolled in a Weight Loss Program: Qualitative Findings. International Journal of Environmental Research and Public Health 2022;19(11):6656
    CrossRef
  122. Gadde NS, Yap KY. Mobile Health Apps That Act as Surgical Preparatory Guides: App Store Search and Quality Evaluation. JMIR Perioperative Medicine 2021;4(2):e27037
    CrossRef
  123. Shoneye CL, Kwasnicka D, Mullan B, Pollard CM, Boushey CJ, Kerr DA. Dietary assessment methods used in adult digital weight loss interventions: A systematic literature review. Journal of Human Nutrition and Dietetics 2023;36(3):997
    CrossRef
  124. Miller K, Jerome GJ. Self-Monitoring Physical Activity, Diet, and Weight Among Adults Who Are Legally Blind: Exploratory Investigation. JMIR Rehabilitation and Assistive Technologies 2022;9(4):e42923
    CrossRef
  125. Khazaal Y, Potvin S, Pennou A, Djomo W, Borgeat F, Lecomte T. Des repères pour la conception des apps ?. Santé mentale au Québec 2021;46(1):119
    CrossRef
  126. Lin AW, Morgan N, Ward D, Tangney C, Alshurafa N, Van Horn L, Spring B. Comparative Validity of Mostly Unprocessed and Minimally Processed Food Items Differs Among Popular Commercial Nutrition Apps Compared with a Research Food Database. Journal of the Academy of Nutrition and Dietetics 2022;122(4):825
    CrossRef
  127. Ang SM, Chen J, Liew JH, Johal J, Dan YY, Allman-Farinelli M, Lim SL. Efficacy of Interventions That Incorporate Mobile Apps in Facilitating Weight Loss and Health Behavior Change in the Asian Population: Systematic Review and Meta-analysis. Journal of Medical Internet Research 2021;23(11):e28185
    CrossRef
  128. Samad S, Ahmed F, Naher S, Kabir MA, Das A, Amin S, Islam SMS. Smartphone apps for tracking food consumption and recommendations: Evaluating artificial intelligence-based functionalities, features and quality of current apps. Intelligent Systems with Applications 2022;15:200103
    CrossRef
  129. Corrêa CR, Costa BGGD, Dezanetti T, Filipini RE, Nunes EA. Changes in eating habits, sleep, and physical activity during coronavirus disease (COVID-19) pandemic: A longitudinal study in young Brazilian adult males. Nutrition and Health 2022;28(4):701
    CrossRef
  130. Zuppinger C, Taffé P, Burger G, Badran-Amstutz W, Niemi T, Cornuz C, Belle FN, Chatelan A, Paclet Lafaille M, Bochud M, Gonseth Nusslé S. Performance of the Digital Dietary Assessment Tool MyFoodRepo. Nutrients 2022;14(3):635
    CrossRef
  131. Mistura L, Comendador Azcarraga FJ, D’Addezio L, Martone D, Turrini A. An Italian Case Study for Assessing Nutrient Intake through Nutrition-Related Mobile Apps. Nutrients 2021;13(9):3073
    CrossRef
  132. Stancu V, Frank D, Lähteenmäki L, Grunert KG. Motivating consumers for health and fitness: The role of app features. Journal of Consumer Behaviour 2022;21(6):1506
    CrossRef
  133. Jung J, Wellard-Cole L, Cai C, Koprinska I, Yacef K, Allman-Farinelli M, Kay J. Foundations for Systematic Evaluation and Benchmarking of a Mobile Food Logger in a Large-scale Nutrition Study. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2020;4(2):1
    CrossRef
  134. Threapleton DE, Beer SL, Foley DJ, Gibson LE, Trevillion S, Burke D, Wheatstone P, Gath J, Hex N, Setters J, Greenwood DC, Cade JE. Usability of myfood24 Healthcare and Mathematical Diet Optimisation in Clinical Populations: A Pilot Feasibility Randomised Controlled Trial. Nutrients 2022;14(9):1768
    CrossRef
  135. Castro Sweet C, Kaye L, Alabduljabbar M, Myers V. Training the next generation of behavioral medicine scientists to accelerate digital health. Translational Behavioral Medicine 2022;12(8):834
    CrossRef
  136. McNitt KM, Hohman EE, Rivera DE, Guo P, Pauley AM, Gernand AD, Symons Downs D, Savage JS. Underreporting of Energy Intake Increases over Pregnancy: An Intensive Longitudinal Study of Women with Overweight and Obesity. Nutrients 2022;14(11):2326
    CrossRef
  137. Siddiqui NR, Hodges SJ, Sharif MO. Orthodontic apps: an assessment of quality (using the Mobile App Rating Scale (MARS)) and behaviour change techniques (BCTs). Progress in Orthodontics 2021;22(1)
    CrossRef
  138. Festic N, Latzer M, Smirnova S. Algorithmic Self-Tracking for Health: User Perspectives on Risk Awareness and Coping Strategies. Media and Communication 2021;9(4):145
    CrossRef
  139. Bzikowska-Jura A, Sobieraj P, Raciborski F. Low Comparability of Nutrition-Related Mobile Apps against the Polish Reference Method—A Validity Study. Nutrients 2021;13(8):2868
    CrossRef
  140. van der Linden MJW, Nahar van Venrooij LMW, Verdaasdonk EGG. Personal Devices to Monitor Physical Activity and Nutritional Intake After Colorectal Cancer Surgery: Feasibility Study. JMIR Perioperative Medicine 2022;5(1):e40352
    CrossRef
  141. Chen J, Grech A, Allman-Farinelli M. Using Popular Foods Consumed to Inform Development of Digital Tools for Dietary Assessment and Monitoring. Nutrients 2022;14(22):4822
    CrossRef
  142. Rahmani Z, Houge Mackenzie S, Carr A. How virtual wellness retreat experiences may influence psychological well-being. Journal of Hospitality and Tourism Management 2024;58:516
    CrossRef
  143. Shreya Kharche , Neha Saraf , Omsing Bhonde . A System for Fitness and Health Care. International Journal of Advanced Research in Science, Communication and Technology 2023;:294
    CrossRef
  144. Martin-Vicario L, Bustos Díaz J, Nicolas-Sans R, Yan Z. Weight Loss App Descriptors in App Stores: A Qualitative Analysis of the Spanish Market. Human Behavior and Emerging Technologies 2023;2023:1
    CrossRef
  145. Sithole BR, Pappas Y, Randhawa G. eHealth in obesity care. Clinical Medicine 2023;23(4):347
    CrossRef
  146. Gioia S, Vlasac IM, Babazadeh D, Fryou NL, Do E, Love J, Robbins R, Dashti HS, Lane JM. Mobile Apps for Dietary and Food Timing Assessment: Evaluation for Use in Clinical Research. JMIR Formative Research 2023;7:e35858
    CrossRef
  147. Larson D, Henning J, Burgermaster M. Smartphone Applications (Apps) for Nutrition Education: A Qualitative Analysis of Outpatient Dietitian Perspectives. Journal of Nutrition Education and Behavior 2023;55(8):596
    CrossRef
  148. Abdul Khalil NM, Mohd Mydin FH, Moy FM, Diviani N. Healthy adults’ views and experiences on behavior change strategies in mobile applications for diet monitoring: A single centre qualitative study. PLOS ONE 2023;18(11):e0292390
    CrossRef
  149. Chew HSJ, Achananuparp P, Dalakoti M, Chew NWS, Chin YH, Gao Y, So BYJ, Shabbir A, Peng LE, Ngiam KY. Public acceptance of using artificial intelligence-assisted weight management apps in high-income southeast Asian adults with overweight and obesity: a cross-sectional study. Frontiers in Nutrition 2024;11
    CrossRef

According to Crossref, the following books are citing this article (DOI 10.2196/mhealth.4334):

  1. Valentim Pereira GF, Pires IM, Marques G, Garcia NM, Zdravevski E, Lameski P, Flórez-Revuelta F, Spinsante S. Internet of Things and Big Data Applications. 2020. Chapter 7:107
    CrossRef
  2. . Nutrients in Dairy and their Implications on Health and Disease. 2017. :43
    CrossRef
  3. Šmahel D, Macháčková H, Šmahelová M, Čevelíček M, Almenara CA, Holubčíková J. Digital Technology, Eating Behaviors, and Eating Disorders. 2018. Chapter 6:101
    CrossRef
  4. Adewumi A, Olatunde G, Misra S, Maskeliūnas R, Damaševičius R. Information Technology Science. 2018. Chapter 3:23
    CrossRef
  5. Dufort A, Gregory E, Woo T. Humanism and Resilience in Residency Training. 2020. Chapter 12:371
    CrossRef
  6. . Obesity and Diabetes. 2020. Chapter 64:865
    CrossRef
  7. Weech M, Fallaize R, Kelly E, Hwang F, Franco RZ, Lovegrove JA. Smartphone Apps for Health and Wellness. 2023. :93
    CrossRef
  8. Lodha C, Dhingra K, Mondal R, Goyal S. Smart Intelligent Computing and Applications, Volume 2. 2022. Chapter 39:403
    CrossRef