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Citing this Article

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Published on 01.08.16 in Vol 4, No 3 (2016): Jul-Sept

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

Works citing "Popular Nutrition-Related Mobile Apps: A Feature Assessment"

According to Crossref, the following articles are citing this article (DOI 10.2196/mhealth.5846):

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

  1. Fallaize R, Franco RZ, Hwang F, Lovegrove JA, 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
    CrossRef
  2. 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)
    CrossRef
  3. 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
  4. Fallaize R, Zenun Franco R, Pasang J, Hwang F, Lovegrove JA. Popular Nutrition-Related Mobile Apps: An Agreement Assessment Against a UK Reference Method. JMIR mHealth and uHealth 2019;7(2):e9838
    CrossRef
  5. Holmes WS, Moorhead SA, Coates VE, Bond RR, 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
    CrossRef
  6. Kosa SD, Monize J, D'Souza M, Joshi A, Philip K, Reza S, Samra S, Serrago B, Thabane L, Gafni A, Lok CE. Nutritional Mobile Applications for CKD Patients: Systematic Review. Kidney International Reports 2019;4(3):399
    CrossRef
  7. Demiris G, Iribarren SJ, Sward K, Lee S, Yang R. Patient Generated Health Data Use in Clinical Practice: A Systematic Review. Nursing Outlook 2019;
    CrossRef
  8. 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
    CrossRef
  9. 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
  10. Mauch CE, Wycherley TP, Laws RA, Johnson BJ, Bell LK, Golley RK. Mobile Apps to Support Healthy Family Food Provision: Systematic Assessment of Popular, Commercially Available Apps. JMIR mHealth and uHealth 2018;6(12):e11867
    CrossRef
  11. 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
  12. 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
    CrossRef
  13. 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
  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(2):288
    CrossRef
  15. Franco RZ, Fallaize R, Hwang F, Lovegrove JA. Strategies for online personalised nutrition advice employed in the development of the eNutri web app. Proceedings of the Nutrition Society 2018;:1
    CrossRef
  16. 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
    CrossRef
  17. 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
    CrossRef
  18. 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
  19. 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
    CrossRef
  20. Pendergast FJ, Leech RM, McNaughton SA. Novel Online or Mobile Methods to Assess Eating Patterns. Current Nutrition Reports 2017;6(3):212
    CrossRef
  21. 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
    CrossRef
  22. 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
    CrossRef
  23. Simpson CC, Mazzeo SE. Calorie counting and fitness tracking technology: Associations with eating disorder symptomatology. Eating Behaviors 2017;26:89
    CrossRef