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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"

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. 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
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  2. 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 2018;
    CrossRef
  3. 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
  4. 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
  5. 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
  6. 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
  7. 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
  8. 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
    CrossRef
  9. 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
  10. 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
  11. 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
  12. 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
  13. 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
  14. 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(02):288
    CrossRef
  15. 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
  16. 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
  17. Griffiths C, Harnack L, Pereira MA. Assessment of the accuracy of nutrient calculations of five popular nutrition tracking applications. Public Health Nutrition 2018;21(08):1495
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  18. Liu HT, Chia R, Setiawan IMA, Crytzer TM, Ding D. Development of “My Wheelchair Guide” app: a qualitative study. Disability and Rehabilitation: Assistive Technology 2018;:1
    CrossRef
  19. 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
  20. 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
  21. 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
  22. Partridge S, Redfern J. Strategies to Engage Adolescents in Digital Health Interventions for Obesity Prevention and Management. Healthcare 2018;6(3):70
    CrossRef
  23. 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
  24. 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
  25. 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
  26. 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
  27. 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
  28. 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
  29. Nikolaou CK, Lean MEJ. Mobile applications for obesity and weight management: current market characteristics. International Journal of Obesity 2017;41(1):200
    CrossRef
  30. 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 2017;1(1-4):3
    CrossRef
  31. 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
  32. 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
  33. 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
  34. 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
  35. Allman-Farinelli M, Gemming L. Technology Interventions to Manage Food Intake: Where Are We Now?. Current Diabetes Reports 2017;17(11)
    CrossRef
  36. Cade JE. Measuring diet in the 21st century: use of new technologies. Proceedings of the Nutrition Society 2017;76(03):276
    CrossRef
  37. 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
  38. 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
  39. 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
  40. Pulier ML, Daviss S. A Call for a Global Digital Health Consortium. Journal of Technology in Behavioral Science 2017;1(1-4):16
    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. 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
  43. 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
  44. 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
  45. 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
  46. 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
  47. 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
  48. 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):E7645
    CrossRef
  49. 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
  50. 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

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

:
  1. Adewumi A, Olatunde G, Misra S, Maskeliūnas R, Damaševičius R. Information Technology Science. 2018. Chapter 3:23
    CrossRef
  2. Šmahel D, Macháčková H, Šmahelová M, Čevelíček M, Almenara CA, Holubčíková J. Digital Technology, Eating Behaviors, and Eating Disorders. 2018. Chapter 6:101
    CrossRef
  3. Galhotra R. Nutrients in Dairy and their Implications on Health and Disease. 2017. :43
    CrossRef