Published on 13.04.12 in Vol 14, No 2 (2012): Mar-Apr
Works citing "Novel Technologies for Assessing Dietary Intake: Evaluating the Usability of a Mobile Telephone Food Record Among Adults and Adolescents"
According to Crossref, the following articles are citing this article (DOI 10.2196/jmir.1967):
(note that this is only a small subset of citations)
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Gilmore LA, Duhé AF, Frost EA, Redman LM. The Technology Boom. Journal of Diabetes Science and Technology 2014;8(3):596
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Helander E, Kaipainen K, Korhonen I, Wansink B. Factors Related to Sustained Use of a Free Mobile App for Dietary Self-Monitoring With Photography and Peer Feedback: Retrospective Cohort Study. Journal of Medical Internet Research 2014;16(4):e109
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Panizza C, Boushey C, Delp E, Kerr D, Lim E, Gandhi K, Banna J. Characterizing Early Adolescent Plate Waste Using the Mobile Food Record. Nutrients 2017;9(2):93
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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
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Ashman AM, Collins CE, Brown LJ, Rae KM, Rollo ME. A Brief Tool to Assess Image-Based Dietary Records and Guide Nutrition Counselling Among Pregnant Women: An Evaluation. JMIR mHealth and uHealth 2016;4(4):e123
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Peterson CM, Apolzan JW, Wright C, Martin CK. Video chat technology to remotely quantify dietary, supplement and medication adherence in clinical trials. British Journal of Nutrition 2016;116(9):1646
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Banna J, Panizza C, Boushey C, Delp E, Lim E. Association between Cognitive Restraint, Uncontrolled Eating, Emotional Eating and BMI and the Amount of Food Wasted in Early Adolescent Girls. Nutrients 2018;10(9):1279
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Harray A, Boushey C, Pollard C, Delp E, Ahmad Z, Dhaliwal S, Mukhtar S, Kerr D. A Novel Dietary Assessment Method to Measure a Healthy and Sustainable Diet Using the Mobile Food Record: Protocol and Methodology. Nutrients 2015;7(7):5375
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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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. Sugar consumption, metabolic disease and obesity: The state of the controversy. Critical Reviews in Clinical Laboratory Sciences 2016;53(1):52
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Gemming L, Utter J, Ni Mhurchu C. Image-Assisted Dietary Assessment: A Systematic Review of the Evidence. Journal of the Academy of Nutrition and Dietetics 2015;115(1):64
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Rabbi M, Pfammatter A, Zhang M, Spring B, Choudhury T. Automated Personalized Feedback for Physical Activity and Dietary Behavior Change With Mobile Phones: A Randomized Controlled Trial on Adults. JMIR mHealth and uHealth 2015;3(2):e42
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Christoph MJ, Loman BR, Ellison B. Developing a digital photography-based method for dietary analysis in self-serve dining settings. Appetite 2017;114:217
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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
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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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Kerr DA, Pollard CM, Howat P, Delp EJ, Pickering M, Kerr KR, Dhaliwal SS, Pratt IS, Wright J, Boushey CJ. Connecting Health and Technology (CHAT): protocol of a randomized controlled trial to improve nutrition behaviours using mobile devices and tailored text messaging in young adults. BMC Public Health 2012;12(1)
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Lee J, Song S, Ahn J, Kim Y, Lee J. Use of a Mobile Application for Self-Monitoring Dietary Intake: Feasibility Test and an Intervention Study. Nutrients 2017;9(7):748
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Zapata-Lamana R, Lalanza JF, Losilla J, Parrado E, Capdevila L. mHealth technology for ecological momentary assessment in physical activity research: a systematic review. PeerJ 2020;8:e8848
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. Nutritional epidemiology: New perspectives for understanding the diet-disease relationship?. European Journal of Clinical Nutrition 2013;67(5):424
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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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Chung L, Law Q, Fong S, Chung J, Yuen P. A cost-effectiveness analysis of teledietetics in short-, intermediate-, and long-term weight reduction. Journal of Telemedicine and Telecare 2015;21(5):268
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Derbyshire E, Dancey D. Smartphone Medical Applications for Women’s Health: What Is the Evidence-Base and Feedback?. International Journal of Telemedicine and Applications 2013;2013:1
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Sanghvi A, Redman LM, Martin CK, Ravussin E, Hall KD. Validation of an inexpensive and accurate mathematical method to measure long-term changes in free-living energy intake. The American Journal of Clinical Nutrition 2015;102(2):353
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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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. 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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Kim S, Chung S. Development and User Satisfaction of a Mobile Phone Application for Image-based Dietary Assessment. Korean Journal of Community Nutrition 2017;22(6):485
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Gibney MJ, Walsh MC. The future direction of personalised nutrition: my diet, my phenotype, my genes. Proceedings of the Nutrition Society 2013;72(2):219
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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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Sun M, Burke L, Baranowski T, Fernstrom J, Zhang H, Chen H, Bai Y, Li Y, Li C, Yue Y, Li Z, Nie J, Sclabassi R, Mao Z, Jia W. An Exploratory Study on a Chest-Worn Computer for Evaluation of Diet, Physical Activity and Lifestyle. Journal of Healthcare Engineering 2015;6(1):1
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Boushey CJ, Harray AJ, Kerr DA, Schap TE, Paterson S, Aflague T, Bosch Ruiz M, Ahmad Z, Delp EJ. How Willing Are Adolescents to Record Their Dietary Intake? The Mobile Food Record. JMIR mHealth and uHealth 2015;3(2):e47
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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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Arens-Volland AG, Spassova L, Bohn T. Promising approaches of computer-supported dietary assessment and management—Current research status and available applications. International Journal of Medical Informatics 2015;84(12):997
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Rollo ME, Williams RL, Burrows T, Kirkpatrick SI, Bucher T, Collins CE. What Are They Really Eating? A Review on New Approaches to Dietary Intake Assessment and Validation. Current Nutrition Reports 2016;5(4):307
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Casperson SL, Sieling J, Moon J, Johnson L, Roemmich JN, Whigham L. A Mobile Phone Food Record App to Digitally Capture Dietary Intake for Adolescents in a Free-Living Environment: Usability Study. JMIR mHealth and uHealth 2015;3(1):e30
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Aflague TF, Leon Guerrero RT, Delormier T, Novotny R, Wilkens LR, Boushey CJ. Examining the Influence of Cultural Immersion on Willingness to Try Fruits and Vegetables among Children in Guam: The Traditions Pilot Study. Nutrients 2019;12(1):18
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da Costa FF, Schmoelz CP, Davies VF, Di Pietro PF, Kupek E, de Assis MAA. Assessment of Diet and Physical Activity of Brazilian Schoolchildren: Usability Testing of a Web-Based Questionnaire. JMIR Research Protocols 2013;2(2):e31
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Bruening M, van Woerden I, Todd M, Brennhofer S, Laska MN, Dunton G. A Mobile Ecological Momentary Assessment Tool (devilSPARC) for Nutrition and Physical Activity Behaviors in College Students: A Validation Study. Journal of Medical Internet Research 2016;18(7):e209
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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
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Chow CC, Hall KD. Short and long-term energy intake patterns and their implications for human body weight regulation. Physiology & Behavior 2014;134:60
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Fitt E, Cole D, Ziauddeen N, Pell D, Stickley E, Harvey A, Stephen AM. DINO (Diet In Nutrients Out) – an integrated dietary assessment system. Public Health Nutrition 2015;18(2):234
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Ashman A, Collins C, Brown L, Rae K, Rollo M. Validation of a Smartphone Image-Based Dietary Assessment Method for Pregnant Women. Nutrients 2017;9(1):73
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Gemming L, Doherty A, Kelly P, Utter J, Ni Mhurchu C. Feasibility of a SenseCam-assisted 24-h recall to reduce under-reporting of energy intake. European Journal of Clinical Nutrition 2013;67(10):1095
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Gibney MJ, McNulty BA, Ryan MF, Walsh MC. Nutritional Phenotype Databases and Integrated Nutrition: From Molecules to Populations. Advances in Nutrition 2014;5(3):352S
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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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Hongu N, Pope BT, Bilgiç P, Orr BJ, Suzuki A, Kim AS, Merchant NC, Roe DJ. Usability of a smartphone food picture app for assisting 24-hour dietary recall: a pilot study. Nutrition Research and Practice 2015;9(2):207
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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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Burrows T, Golley RK, Khambalia A, McNaughton SA, Magarey A, Rosenkranz RR, Alllman‐Farinelli M, Rangan AM, Truby H, Collins C. The quality of dietary intake methodology and reporting in child and adolescent obesity intervention trials: a systematic review. Obesity Reviews 2012;13(12):1125
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Lytle LA, Nicastro HL, Roberts SB, Evans M, Jakicic JM, Laposky AD, Loria CM. Accumulating Data to Optimally Predict Obesity Treatment (ADOPT) Core Measures: Behavioral Domain. Obesity 2018;26(S2)
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Panizza CE, Lim U, Yonemori KM, Cassel KD, Wilkens LR, Harvie MN, Maskarinec G, Delp EJ, Lampe JW, Shepherd JA, Le Marchand L, Boushey CJ. Effects of Intermittent Energy Restriction Combined with a Mediterranean Diet on Reducing Visceral Adiposity: A Randomized Active Comparator Pilot Study. Nutrients 2019;11(6):1386
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Turner T, Spruijt‐Metz D, Wen CKF, Hingle MD. Prevention and treatment of pediatric obesity using mobile and wireless technologies: a systematic review. Pediatric Obesity 2015;10(6):403
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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
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Ho TJH, Lee CCS, Wong SN, Lau Y. Internet-based self-monitoring interventions for overweight and obese adolescents: A systematic review and meta-analysis. International Journal of Medical Informatics 2018;120:20
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Kerr D, Dhaliwal S, Pollard C, Norman R, Wright J, Harray A, Shoneye C, Solah V, Hunt W, Zhu F, Delp E, Boushey C. BMI is Associated with the Willingness to Record Diet with a Mobile Food Record among Adults Participating in Dietary Interventions. Nutrients 2017;9(3):244
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Spook JE, Paulussen T, Kok G, Van Empelen P. Monitoring Dietary Intake and Physical Activity Electronically: Feasibility, Usability, and Ecological Validity of a Mobile-Based Ecological Momentary Assessment Tool. Journal of Medical Internet Research 2013;15(9):e214
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Raatz SK, Scheett AJ, Johnson LK, Jahns L. Validity of Electronic Diet Recording Nutrient Estimates Compared to Dietitian Analysis of Diet Records: Randomized Controlled Trial. Journal of Medical Internet Research 2015;17(1):e21
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Aflague T, Boushey C, Guerrero R, Ahmad Z, Kerr D, Delp E. Feasibility and Use of the Mobile Food Record for Capturing Eating Occasions among Children Ages 3–10 Years in Guam. Nutrients 2015;7(6):4403
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. A changing landscape. Current Opinion in Clinical Nutrition and Metabolic Care 2015;18(5):437
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Banna JC, Buchthal OV, Delormier T, Creed-Kanashiro HM, Penny ME. Influences on eating: a qualitative study of adolescents in a periurban area in Lima, Peru. BMC Public Health 2015;16(1)
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Probst Y, Zammit G. Predictors for Reporting of Dietary Assessment Methods in Food-based Randomized Controlled Trials over a Ten-year Period. Critical Reviews in Food Science and Nutrition 2016;56(12):2069
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. Considerations for Evaluation of Diabetes Prevention Programs in Hispanic Adults in the United States. American Journal of Lifestyle Medicine 2018;12(1):21
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Boushey CJ, Delp EJ, Ahmad Z, Wang Y, Roberts SM, Grattan LM. Dietary assessment of domoic acid exposure: What can be learned from traditional methods and new applications for a technology assisted device. Harmful Algae 2016;57:51
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Taylor JC, Johnson RK. Farm to School as a strategy to increase children's fruit and vegetable consumption in the United States: Research and recommendations. Nutrition Bulletin 2013;38(1):70
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Schembre SM, Liao Y, O'Connor SG, Hingle MD, Shen S, Hamoy KG, Huh J, Dunton GF, Weiss R, Thomson CA, Boushey CJ. Mobile Ecological Momentary Diet Assessment Methods for Behavioral Research: Systematic Review. JMIR mHealth and uHealth 2018;6(11):e11170
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Comulada WS, Swendeman D, Koussa MK, Mindry D, Medich M, Estrin D, Mercer N, Ramanathan N. Adherence to self-monitoring healthy lifestyle behaviours through mobile phone-based ecological momentary assessments and photographic food records over 6 months in mostly ethnic minority mothers. Public Health Nutrition 2018;21(4):679
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Park S, Palvanov A, Lee C, Jeong N, Cho Y, Lee H. The development of food image detection and recognition model of Korean food for mobile dietary management. Nutrition Research and Practice 2019;13(6):521
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Rangan AM, O'Connor S, Giannelli V, Yap ML, Tang LM, Roy R, Louie JCY, Hebden L, Kay J, Allman-Farinelli M. Electronic Dietary Intake Assessment (e-DIA): Comparison of a Mobile Phone Digital Entry App for Dietary Data Collection With 24-Hour Dietary Recalls. JMIR mHealth and uHealth 2015;3(4):e98
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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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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
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Sharp DB, Allman-Farinelli M. Feasibility and validity of mobile phones to assess dietary intake. Nutrition 2014;30(11-12):1257
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Ahn Y, Bae J, Kim H. The development of a mobile u-Health program and evaluation for self-diet management for diabetic patients. Nutrition Research and Practice 2016;10(3):342
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Stephen AM, Mak TN, Fitt E, Nicholson S, Roberts C, Sommerville J. Innovations in national nutrition surveys. Proceedings of the Nutrition Society 2013;72(1):77
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Rollo M, Ash S, Lyons-Wall P, Russell A. Evaluation of a Mobile Phone Image-Based Dietary Assessment Method in Adults with Type 2 Diabetes. Nutrients 2015;7(6):4897
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Zhao X, Xu X, Li X, He X, Yang Y, Zhu S. Emerging trends of technology-based dietary assessment: a perspective study. European Journal of Clinical Nutrition 2021;75(4):582
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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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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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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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Banna J, Danible K, Panizza C, Boushey C, Kerr D, Zhu F. A Novel to Method to Measure Food Waste: The Mobile Food Record. Journal of Extension 2021;59(Summer 2021)
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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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Liu C, Cao Y, Luo Y, Chen G, Vokkarane V, Yunsheng M, Chen S, Hou P. A New Deep Learning-Based Food Recognition System for Dietary Assessment on An Edge Computing Service Infrastructure. IEEE Transactions on Services Computing 2018;11(2):249
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According to Crossref, the following books are citing this article (DOI 10.2196/jmir.1967):
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Cui Y, Balshaw D. Unraveling the Exposome. 2019. Chapter 10:255
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Fang S, Liu C, Zhu F, Boushey C, Delp E. New Trends in Image Analysis and Processing -- ICIAP 2015 Workshops. 2015. Chapter 44:358
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Boeing H, Margetts BM. Handbook of Epidemiology. 2014. Chapter 26:1659
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. Childhood Obesity. 2016. :431
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Braconi D, Cicaloni V, Spiga O, Santucci A. Trends in Personalized Nutrition. 2019. :3
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Xu X, Hou L, Guo Z, Wang J, Li J. Big Data – BigData 2018. 2018. Chapter 30:360
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Liu C, Cao Y, Luo Y, Chen G, Vokkarane V, Ma Y. Inclusive Smart Cities and Digital Health. 2016. Chapter 4:37
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Saraf S, Bagaria RK, Kuresan H, Dhanalakshmi S. Smart Trends in Computing and Communications. 2023. Chapter 58:681
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Bagaria RK, Krithiga , Tripathi A, Ayush K. Human-Centric Smart Computing. 2024. Chapter 45:569
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