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Citing this Article

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Published on 27.10.15 in Vol 3, No 4 (2015): Oct-Dec

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

Works citing "Electronic Dietary Intake Assessment (e-DIA): Comparison of a Mobile Phone Digital Entry App for Dietary Data Collection With 24-Hour Dietary Recalls"

Anna M Rangan, Sarah O'Connor, Valentina Giannelli, Megan LH Yap, Lie Ming Tang, Rajshri Roy, Jimmy Chun Yu Louie, Lana Hebden, Judy Kay, Margaret Allman-Farinelli

JMIR Mhealth Uhealth 2015 (Oct 27); 3(4):e98 

According to Crossref, the following articles are citing this article (DOI 10.2196/mhealth.4613):

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

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  15. 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
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  26. Jenner SL, Trakman G, Coutts A, Kempton T, Ryan S, Forsyth A, Belski R. Dietary intake of professional Australian football athletes surrounding body composition assessment. Journal of the International Society of Sports Nutrition 2018;15(1)
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  27. Béjar LM, Reyes A, García-Perea MD. Electronic 12-Hour Dietary Recall (e-12HR): Comparison of a Mobile Phone App for Dietary Intake Assessment With a Food Frequency Questionnaire and Four Dietary Records. JMIR mHealth and uHealth 2018;6(6):e10409
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  28. Lancaster R, Radd‐Vagenas S, Fiatarone Singh M, Noble Y, Daniel K, Mavros Y, Sachdev PS, Lautenschlager N, Cox K, Brodaty H, O'Leary F, Flood VM. Electronic food records among middle‐aged and older people: A comparison of self‐reported and dietitian‐assisted information. Nutrition & Dietetics 2021;78(2):145
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  29. 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
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  30. Kim S, Chung S. Validity of Estimating Sodium Intake using a Mobile Phone Application of 24-hour Dietary Recall with Meal Photos. Korean Journal of Community Nutrition 2020;25(4):317
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  31. Bejar LM, Sharp BN, García-Perea MD. The e-EPIDEMIOLOGY Mobile Phone App for Dietary Intake Assessment: Comparison with a Food Frequency Questionnaire. JMIR Research Protocols 2016;5(4):e208
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  32. Fowler LA, Yingling LR, Brooks AT, Wallen GR, Peters-Lawrence M, McClurkin M, Wiley Jr KL, Mitchell VM, Johnson TD, Curry KE, Johnson AA, Graham AP, Graham LA, Powell-Wiley TM. Digital Food Records in Community-Based Interventions: Mixed-Methods Pilot Study. JMIR mHealth and uHealth 2018;6(7):e160
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  33. 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
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  34. Slavin M, Polasky A, Vieyra K, Best A, Durant L, Frankenfeld C. Single-Meal Nutrient Assessment by a Self-Administered, Electronic Exit Survey Compared with a Multipass Dietary Interview in University Undergraduates in an All-You-Care-to-Eat Campus Dining Hall. Journal of the Academy of Nutrition and Dietetics 2019;119(5):739
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  35. Pendergast FJ, Leech RM, McNaughton SA. Novel Online or Mobile Methods to Assess Eating Patterns. Current Nutrition Reports 2017;6(3):212
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  36. Roy R, Rangan A, Hebden L, Yu Louie JC, Tang LM, Kay J, Allman-Farinelli M. Dietary contribution of foods and beverages sold within a university campus and its effect on diet quality of young adults. Nutrition 2017;34:118
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  37. Béjar LM, García-Perea MD, Reyes A, Vázquez-Limón E. Relative Validity of a Method Based on a Smartphone App (Electronic 12-Hour Dietary Recall) to Estimate Habitual Dietary Intake in Adults. JMIR mHealth and uHealth 2019;7(4):e11531
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  38. Evenepoel C, Clevers E, Deroover L, Van Loo W, Matthys C, Verbeke K. Accuracy of Nutrient Calculations Using the Consumer-Focused Online App MyFitnessPal: Validation Study. Journal of Medical Internet Research 2020;22(10):e18237
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  39. Malaeb S, Harindhanavudhi T, Dietsche K, Esch N, Manoogian ENC, Panda S, Mashek DG, Wang Q, Chow LS. Time-Restricted Eating Alters Food Intake Patterns, as Prospectively Documented by a Smartphone Application. Nutrients 2020;12(11):3396
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  40. 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
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  41. Wada S, Yamamoto E, Kobayashi Y, Otsuki M, Takada C, Aoi W, Okagaki M, Neriya H, Hamaguchi M, Tanaka M, Fukui M, Higashi A. Validation of computer software to estimate dietary intake among patients with type 2 diabetes. Journal of Clinical Biochemistry and Nutrition 2021;68(1):105
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  42. Ocké M, Dinnissen C, Stafleu A, de Vries J, van Rossum C. Relative Validity of MijnEetmeter: A Food Diary App for Self-Monitoring of Dietary Intake. Nutrients 2021;13(4):1135
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  43. Ruf A, Koch ED, Ebner-Priemer U, Knopf M, Reif A, Matura S. Studying Microtemporal, Within-Person Processes of Diet, Physical Activity, and Related Factors Using the APPetite-Mobile-App: Feasibility, Usability, and Validation Study. Journal of Medical Internet Research 2021;23(7):e25850
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  44. Chen J, Bertrand S, Galy O, Raubenheimer D, Allman-Farinelli M, Caillaud C. The Design and Development of a Food Composition Database for an Electronic Tool to Assess Food Intake in New Caledonian Families. Nutrients 2021;13(5):1668
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  45. 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
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  46. Davies A, Shi Y, Bauman A, Allman-Farinelli M. Validity of New Technologies That Measure Bone-Related Dietary and Physical Activity Risk Factors in Adolescents and Young Adults: A Scoping Review. International Journal of Environmental Research and Public Health 2021;18(11):5688
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  47. Natalucci V, Marmondi F, Biraghi M, Bonato M. The Effectiveness of Wearable Devices in Non-Communicable Diseases to Manage Physical Activity and Nutrition: Where We Are?. Nutrients 2023;15(4):913
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  48. Bessell E, Meroni A, Jualim N, Fuller NR. Comparison of an Online Dietary Assessment Tool (the “Boden Food Plate”) With 24-Hour Dietary Recalls. Topics in Clinical Nutrition 2022;37(3):242
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  49. Lucassen DA, Brouwer-Brolsma EM, Slotegraaf AI, Kok E, Feskens EJM. DIetary ASSessment (DIASS) Study: Design of an Evaluation Study to Assess Validity, Usability and Perceived Burden of an Innovative Dietary Assessment Methodology. Nutrients 2022;14(6):1156
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  50. Nassif E, Davies A, Bente KB, Wellard-Cole L, Jung J, Kay J, Hughes C, Koprinska I, Watson WL, Yacef K, Chapman K, Rangan A, Bauman A, Ni Mhurchu C, Allman-Farinelli M. The Contribution of Nutrients of Concern to the Diets of 18-to-30-Year-Old Australians from Food Prepared Outside Home Differs by Food Outlet Types: The MYMeals Cross-Sectional Study. Nutrients 2022;14(18):3751
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  51. Hattab S, Badrasawi M, Anabtawi O, Zidan S. Development and validation of a smartphone image-based app for dietary intake assessment among Palestinian undergraduates. Scientific Reports 2022;12(1)
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  52. König LM, Van Emmenis M, Nurmi J, Kassavou A, Sutton S. Characteristics of smartphone-based dietary assessment tools: a systematic review. Health Psychology Review 2022;16(4):526
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  53. Long Z, Huang S, Zhang J, Zhang D, Yin J, He C, Zhang Q, Xu H, He H, Sun HC, Xie K. A Digital Smartphone-Based Self-administered Tool (R+ Dietitian) for Nutritional Risk Screening and Dietary Assessment in Hospitalized Patients With Cancer: Evaluation and Diagnostic Accuracy Study. JMIR Formative Research 2022;6(10):e40316
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  54. Tanweer A, Khan S, Mustafa FN, Imran S, Humayun A, Hussain Z. Improving dietary data collection tools for better nutritional assessment – A systematic review. Computer Methods and Programs in Biomedicine Update 2022;2:100067
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  55. Thornton L, Osman B, Champion K, Green O, Wescott AB, Gardner LA, Stewart C, Visontay R, Whife J, Parmenter B, Birrell L, Bryant Z, Chapman C, Lubans D, Slade T, Torous J, Teesson M, Van de Ven P. Measurement Properties of Smartphone Approaches to Assess Diet, Alcohol Use, and Tobacco Use: Systematic Review. JMIR mHealth and uHealth 2022;10(2):e27337
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  56. Carpenter CA, Ugwoaba UA, Cardel MI, Ross KM. Using self-monitoring technology for nutritional counseling and weight management. DIGITAL HEALTH 2022;8:205520762211027
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  57. 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
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  58. Baum Martinez I, Peters B, Schwarz J, Schuppelius B, Steckhan N, Koppold-Liebscher DA, Michalsen A, Pivovarova-Ramich O. Validation of a Smartphone Application for the Assessment of Dietary Compliance in an Intermittent Fasting Trial. Nutrients 2022;14(18):3697
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  60. Moyen A, Rappaport AI, Fleurent-Grégoire C, Tessier A, Brazeau A, Chevalier S. Relative Validation of an Artificial Intelligence–Enhanced, Image-Assisted Mobile App for Dietary Assessment in Adults: Randomized Crossover Study. Journal of Medical Internet Research 2022;24(11):e40449
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According to Crossref, the following books are citing this article (DOI 10.2196/mhealth.4613):

  1. Rajasekera J, Mishal AV, Mori Y. Big Data Analytics in Healthcare. 2020. Chapter 6:83
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  2. Fontana JM, Farooq M, Sazonov E. Wearable Sensors. 2021. :541
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  3. Karahanoğlu A, Ludden G. Advances in Longitudinal HCI Research. 2021. Chapter 6:101
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