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Citing this Article

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Published on 13.03.15 in Vol 3, No 1 (2015): Jan-Mar

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

Works citing "A Mobile Phone Food Record App to Digitally Capture Dietary Intake for Adolescents in a Free-Living Environment: Usability Study"

Shanon L Casperson, Jared Sieling, Jon Moon, LuAnn Johnson, James N Roemmich, Leah Whigham

JMIR Mhealth Uhealth 2015 (Mar 13); 3(1):e30 

According to Crossref, the following articles are citing this article (DOI 10.2196/mhealth.3324):

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

  1. 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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  2. Kourkoutas Y, Chorianopoulos N, Nisiotou A, Valdramidis VP, Karatzas KAG. Application of Innovative Technologies for Improved Food Quality and Safety. BioMed Research International 2016;2016:1
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  3. Boushey C, Spoden M, Delp E, Zhu F, Bosch M, Ahmad Z, Shvetsov Y, DeLany J, Kerr D. Reported Energy Intake Accuracy Compared to Doubly Labeled Water and Usability of the Mobile Food Record among Community Dwelling Adults. Nutrients 2017;9(3):312
    CrossRef
  4. 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
    CrossRef
  5. Eslick S, Jensen ME, Collins CE, Gibson PG, Hilton J, Wood LG. Characterising a Weight Loss Intervention in Obese Asthmatic Children. Nutrients 2020;12(2):507
    CrossRef
  6. Ferri E, Galimberti A, Casiraghi M, Airoldi C, Ciaramelli C, Palmioli A, Mezzasalma V, Bruni I, Labra M. Towards a Universal Approach Based on Omics Technologies for the Quality Control of Food. BioMed Research International 2015;2015:1
    CrossRef
  7. Bathgate K, Sherriff J, Leonard H, Dhaliwal S, Delp E, Boushey C, Kerr D. Feasibility of Assessing Diet with a Mobile Food  Record for Adolescents and Young Adults with  Down Syndrome. Nutrients 2017;9(3):273
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  8. Segovia-Siapco G, Sabaté J. Using Personal Mobile Phones to Assess Dietary Intake in Free-Living Adolescents: Comparison of Face-to-Face Versus Telephone Training. JMIR mHealth and uHealth 2016;4(3):e91
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  9. Amoutzopoulos B, Steer T, Roberts C, Cade JE, Boushey CJ, Collins CE, Trolle E, Boer EJD, Ziauddeen N, van Rossum C, Buurma E, Coyle D, Page P. Traditional methodsv.new technologies – dilemmas for dietary assessment in large-scale nutrition surveys and studies: a report following an international panel discussion at the 9th International Conference on Diet and Activity Methods (ICDAM9), Brisbane, 3 September 2015. Journal of Nutritional Science 2018;7
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  10. Gonçalves RFDM, Barreto DDA, Monteiro PI, Zangeronimo MG, Castelo PM, van der Bilt A, Pereira LJ. Smartphone use while eating increases caloric ingestion. Physiology & Behavior 2019;204:93
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  11. Reber E, Gomes F, Vasiloglou MF, Schuetz P, Stanga Z. Nutritional Risk Screening and Assessment. Journal of Clinical Medicine 2019;8(7):1065
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  12. Tay I, Garland S, Gorelik A, Wark JD. Development and Testing of a Mobile Phone App for Self-Monitoring of Calcium Intake in Young Women. JMIR mHealth and uHealth 2017;5(3):e27
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  13. Wahl DR, Villinger K, König LM, Ziesemer K, Schupp HT, Renner B. Healthy food choices are happy food choices: Evidence from a real life sample using smartphone based assessments. Scientific Reports 2017;7(1)
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  14. 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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  15. Chen Y, Wong J, Ayob A, Othman N, Poh B. Can Malaysian Young Adults Report Dietary Intake Using a Food Diary Mobile Application? A Pilot Study on Acceptability and Compliance. Nutrients 2017;9(1):62
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  16. Dunn CG, Turner-McGrievy GM, Wilcox S, Hutto B. Dietary Self-Monitoring Through Calorie Tracking but Not Through a Digital Photography App Is Associated with Significant Weight Loss: The 2SMART Pilot Study—A 6-Month Randomized Trial. Journal of the Academy of Nutrition and Dietetics 2019;119(9):1525
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  17. Wang J, Hsieh R, Tung Y, Chen Y, Yang C, Chen YC. Evaluation of a Technological Image-Based Dietary Assessment Tool for Children during Pubertal Growth: A Pilot Study. Nutrients 2019;11(10):2527
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  18. Chib A, Lin SH. Theoretical Advancements in mHealth: A Systematic Review of Mobile Apps. Journal of Health Communication 2018;23(10-11):909
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  19. Fatehah AA, Poh BK, Shanita SN, Wong JE. Feasibility of Reviewing Digital Food Images for Dietary Assessment among Nutrition Professionals. Nutrients 2018;10(8):984
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  20. . First evaluation steps of a new method for dietary intake estimation regarding a list of key food groups in adults and in different sociodemographic and health-related behaviour strata. Public Health Nutrition 2017;20(15):2660
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  21. Gunther C, Rogers C, Holloman C, Hopkins LC, Anderson SE, Miller CK, Copeland KA, Dollahite JS, Pratt KJ, Webster A, Labyk AN, Penicka C. Child diet and health outcomes of the simple suppers program: a 10-week, 2-group quasi-experimental family meals trial. BMC Public Health 2019;19(1)
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  22. Spruijt-Metz D, Wen CKF, Bell BM, Intille S, Huang JS, Baranowski T. Advances and Controversies in Diet and Physical Activity Measurement in Youth. American Journal of Preventive Medicine 2018;55(4):e81
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  23. Beltran A, Dadabhoy H, Ryan C, Dholakia R, Jia W, Baranowski J, Sun M, Baranowski T. Dietary Assessment with a Wearable Camera among Children: Feasibility and Intercoder Reliability. Journal of the Academy of Nutrition and Dietetics 2018;118(11):2144
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  24. . A changing landscape. Current Opinion in Clinical Nutrition and Metabolic Care 2015;18(5):437
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  25. 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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  26. Warren J, Guelinckx I, Livingstone B, Potischman N, Nelson M, Foster E, Holmes B. Challenges in the assessment of total fluid intake in children and adolescents: a discussion paper. European Journal of Nutrition 2018;57(S3):43
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  27. Boushey CJ, Spoden M, Zhu FM, Delp EJ, Kerr DA. New mobile methods for dietary assessment: review of image-assisted and image-based dietary assessment methods. Proceedings of the Nutrition Society 2017;76(3):283
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  28. Burns K, McBride CA, Patel B, FitzGerald G, Mathews S, Drennan J. Creating Consumer-Generated Health Data: Interviews and a Pilot Trial Exploring How and Why Patients Engage. Journal of Medical Internet Research 2019;21(6):e12367
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  29. Ji Y, Plourde H, Bouzo V, Kilgour RD, Cohen TR. Validity and Usability of a Smartphone Image-Based Dietary Assessment App Compared to 3-Day Food Diaries in Assessing Dietary Intake Among Canadian Adults: Randomized Controlled Trial. JMIR mHealth and uHealth 2020;8(9):e16953
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  30. Vasiloglou MF, Christodoulidis S, Reber E, Stathopoulou T, Lu Y, Stanga Z, Mougiakakou S. What Healthcare Professionals Think of “Nutrition & Diet” Apps: An International Survey. Nutrients 2020;12(8):2214
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  31. Vasiloglou MF, van der Horst K, Stathopoulou T, Jaeggi MP, Tedde GS, Lu Y, Mougiakakou S. The Human Factor in Automated Image-Based Nutrition Apps: Analysis of Common Mistakes Using the goFOOD Lite App. JMIR mHealth and uHealth 2021;9(1):e24467
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  32. Naaman R, Parrett A, Bashawri D, Campo I, Fleming K, Nichols B, Burleigh E, Murtagh J, Reid J, Gerasimidis K. Assessment of Dietary Intake Using Food Photography and Video Recording in Free-Living Young Adults: A Comparative Study. Journal of the Academy of Nutrition and Dietetics 2021;121(4):749
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  33. Höchsmann C, Martin CK. Review of the validity and feasibility of image-assisted methods for dietary assessment. International Journal of Obesity 2020;44(12):2358
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  34. Hoare JK, Jebeile H, Garnett SP, Lister NB. Novel dietary interventions for adolescents with obesity: A narrative review. Pediatric Obesity 2021;16(9)
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  35. Jong ST, Stevenson R, Winpenny EM, Corder K, van Sluijs EMF. Recruitment and retention into longitudinal health research from an adolescent perspective: a qualitative study. BMC Medical Research Methodology 2023;23(1)
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  36. Caon M, Prinelli F, Angelini L, Carrino S, Mugellini E, Orte S, Serrano JCE, Atkinson S, Martin A, Adorni F. PEGASO e-Diary: User Engagement and Dietary Behavior Change of a Mobile Food Record for Adolescents. Frontiers in Nutrition 2022;9
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  37. Muzenda T, Kamkuemah M, Battersby J, Oni T. Assessing adolescent diet and physical activity behaviour, knowledge and awareness in low- and middle-income countries: a systematised review of quantitative epidemiological tools. BMC Public Health 2022;22(1)
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  38. 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
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  39. Idris G, Smith C, Galland B, Taylor R, Robertson CJ, Farella M. Home-Based Monitoring of Eating in Adolescents: A Pilot Study. Nutrients 2021;13(12):4354
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  40. Van Wymelbeke-Delannoy V, Juhel C, Bole H, Sow A, Guyot C, Belbaghdadi F, Brousse O, Paindavoine M. A Cross-Sectional Reproducibility Study of a Standard Camera Sensor Using Artificial Intelligence to Assess Food Items: The FoodIntech Project. Nutrients 2022;14(1):221
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  41. Ploderer B, Rezaei Aghdam A, Burns K. Patient-Generated Health Photos and Videos Across Health and Well-being Contexts: Scoping Review. Journal of Medical Internet Research 2022;24(4):e28867
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  42. 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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  43. Ramírez-Contreras C, Farran-Codina A, Zerón-Rugerio MF, Izquierdo-Pulido M. Relative Validity and Reliability of the Remind App as an Image-Based Method to Assess Dietary Intake and Meal Timing in Young Adults. Nutrients 2023;15(8):1824
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  44. Ho DKN, Chiu W, Kao J, Tseng H, Yao C, Su H, Wei P, Le NQK, Nguyen HT, Chang J. Mitigating errors in mobile-based dietary assessments: Effects of a data modification process on the validity of an image-assisted food and nutrition app. Nutrition 2023;116:112212
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  45. Ghosh T, Han Y, Raju V, Hossain D, McCrory MA, Higgins J, Boushey C, Delp EJ, Sazonov E. Integrated image and sensor-based food intake detection in free-living. Scientific Reports 2024;14(1)
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  46. Schenk JM, Boynton A, Kulik P, Zyuzin A, Neuhouser ML, Kristal AR. The Use of Three-Dimensional Images and Food Descriptions from a Smartphone Device Is Feasible and Accurate for Dietary Assessment. Nutrients 2024;16(6):828
    CrossRef

According to Crossref, the following books are citing this article (DOI 10.2196/mhealth.3324):

  1. . Nutrients in Dairy and their Implications on Health and Disease. 2017. :43
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  2. Thompson FE, Subar AF. Nutrition in the Prevention and Treatment of Disease. 2017. :5
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  3. Konishi T, Nagata M, Honjo M, Yoneyama A, Kurokawa M, Mishima K. Persuasive Technology: Development of Persuasive and Behavior Change Support Systems. 2019. Chapter 25:310
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  4. de Moraes Lopes MHB, Ferreira DD, Ferreira ACBH, da Silva GR, Caetano AS, Braz VN. Artificial Intelligence in Precision Health. 2020. :465
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  5. Mao R, He J, Shao Z, Yarlagadda SK, Zhu F. Pattern Recognition. ICPR International Workshops and Challenges. 2021. Chapter 47:571
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