Published on in Vol 6, No 11 (2018): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/11170, first published .
Mobile Ecological Momentary Diet Assessment Methods for Behavioral Research: Systematic Review

Mobile Ecological Momentary Diet Assessment Methods for Behavioral Research: Systematic Review

Mobile Ecological Momentary Diet Assessment Methods for Behavioral Research: Systematic Review

Journals

  1. Alshurafa N, Lin A, Zhu F, Ghaffari R, Hester J, Delp E, Rogers J, Spring B. Counting Bites With Bits: Expert Workshop Addressing Calorie and Macronutrient Intake Monitoring. Journal of Medical Internet Research 2019;21(12):e14904 View
  2. Wilhelm S, Weingarden H, Ladis I, Braddick V, Shin J, Jacobson N. Cognitive-Behavioral Therapy in the Digital Age: Presidential Address. Behavior Therapy 2020;51(1):1 View
  3. Bell B, Alam R, Alshurafa N, Thomaz E, Mondol A, de la Haye K, Stankovic J, Lach J, Spruijt-Metz D. Automatic, wearable-based, in-field eating detection approaches for public health research: a scoping review. npj Digital Medicine 2020;3(1) View
  4. Wani R. Lifestyle medicine and use of technology in current healthcare. BMJ Innovations 2019;5(4):135.2 View
  5. Reichenberger J, Schnepper R, Arend A, Blechert J. Emotional eating in healthy individuals and patients with an eating disorder: evidence from psychometric, experimental and naturalistic studies. Proceedings of the Nutrition Society 2020;79(3):290 View
  6. Biello K, Salhaney P, Valente P, Childs E, Olson J, Earlywine J, Marshall B, R Bazzi A. Ecological momentary assessment of daily drug use and harm reduction service utilization among people who inject drugs in non-urban areas: A concurrent mixed-method feasibility study. Drug and Alcohol Dependence 2020;214:108167 View
  7. Maugeri A, Barchitta M. A Systematic Review of Ecological Momentary Assessment of Diet: Implications and Perspectives for Nutritional Epidemiology. Nutrients 2019;11(11):2696 View
  8. Maher J, Harduk M, Hevel D, Adams W, McGuirt J. Momentary Physical Activity Co-Occurs with Healthy and Unhealthy Dietary Intake in African American College Freshmen. Nutrients 2020;12(5):1360 View
  9. Wahl D, Villinger K, Blumenschein M, König L, Ziesemer K, Sproesser G, Schupp H, Renner B. Why We Eat What We Eat: Assessing Dispositional and In-the-Moment Eating Motives by Using Ecological Momentary Assessment. JMIR mHealth and uHealth 2020;8(1):e13191 View
  10. Yang Y, Ryu G, Park C, Yeom I, Shim K, Choi M. Mood and Stress Evaluation of Adult Patients With Moyamoya Disease in Korea: Ecological Momentary Assessment Method Using a Mobile Phone App. JMIR mHealth and uHealth 2020;8(5):e17034 View
  11. Mason T, Do B, Wang S, Dunton G. Ecological momentary assessment of eating and dietary intake behaviors in children and adolescents: A systematic review of the literature. Appetite 2020;144:104465 View
  12. Ziesemer K, König L, Boushey C, Villinger K, Wahl D, Butscher S, Müller J, Reiterer H, Schupp H, Renner B. Occurrence of and Reasons for “Missing Events” in Mobile Dietary Assessments: Results From Three Event-Based Ecological Momentary Assessment Studies. JMIR mHealth and uHealth 2020;8(10):e15430 View
  13. Smith K, Mason T, Juarascio A, Schaefer L, Crosby R, Engel S, Wonderlich S. Moving beyond self‐report data collection in the natural environment: A review of the past and future directions for ambulatory assessment in eating disorders. International Journal of Eating Disorders 2019;52(10):1157 View
  14. Doherty K, Balaskas A, Doherty G. The Design of Ecological Momentary Assessment Technologies. Interacting with Computers 2020;32(3):257 View
  15. Demers M, Winstein C. A perspective on the use of ecological momentary assessment and intervention to promote stroke recovery and rehabilitation. Topics in Stroke Rehabilitation 2021;28(8):594 View
  16. Turner-McGrievy G, Yang C, Monroe C, Pellegrini C, West D. Is Burden Always Bad? Emerging Low-Burden Approaches to Mobile Dietary Self-monitoring and the Role Burden Plays with Engagement. Journal of Technology in Behavioral Science 2021;6(3):447 View
  17. Primack B, Shensa A, Sidani J, Escobar-Viera C, Fine M. Temporal Associations Between Social Media Use and Depression. American Journal of Preventive Medicine 2021;60(2):179 View
  18. Goldstein S, Hoover A, Evans E, Thomas J. Combining ecological momentary assessment, wrist-based eating detection, and dietary assessment to characterize dietary lapse: A multi-method study protocol. DIGITAL HEALTH 2021;7 View
  19. Williams M, Lewthwaite H, Fraysse F, Gajewska A, Ignatavicius J, Ferrar K. Compliance With Mobile Ecological Momentary Assessment of Self-Reported Health-Related Behaviors and Psychological Constructs in Adults: Systematic Review and Meta-analysis. Journal of Medical Internet Research 2021;23(3):e17023 View
  20. LC R, B S, D A, DB H, PG H, AR P. Assessment of polyunsaturated fatty acids: A self-report and biomarker assessment with a racially and ethnically diverse sample of women. Prostaglandins, Leukotrienes and Essential Fatty Acids 2021;164:102214 View
  21. Mason T, Crosby R, Dvorak R, Engel S, Wonderlich S, Smith K. An Ecological Momentary Assessment Examination of the Transdiagnostic Model of Food and Alcohol Disturbance. Journal of Psychopathology and Behavioral Assessment 2021;43(4):730 View
  22. Richardson K, Cota Aguirre G, Weiss R, Cinar A, Liao Y, Marano K, Bedoya A, Schembre S. Abbreviated Dietary Self-monitoring for Type 2 Diabetes Management: Mixed Methods Feasibility Study. JMIR Diabetes 2021;6(3):e28930 View
  23. König L, Attig C, Franke T, Renner B. Barriers to and Facilitators for Using Nutrition Apps: Systematic Review and Conceptual Framework. JMIR mHealth and uHealth 2021;9(6):e20037 View
  24. Kwasnicka D, Kale D, Schneider V, Keller J, Yeboah-Asiamah Asare B, Powell D, Naughton F, ten Hoor G, Verboon P, Perski O. Systematic review of ecological momentary assessment (EMA) studies of five public health-related behaviours: review protocol. BMJ Open 2021;11(7):e046435 View
  25. Dao K, De Cocker K, Tong H, Kocaballi A, Chow C, Laranjo L. Smartphone-Delivered Ecological Momentary Interventions Based on Ecological Momentary Assessments to Promote Health Behaviors: Systematic Review and Adapted Checklist for Reporting Ecological Momentary Assessment and Intervention Studies. JMIR mHealth and uHealth 2021;9(11):e22890 View
  26. Kumar D, Bhardwaj A, Sharma S, Malhotra B, Amadi-Mgbenka C, Grover A, Joshi A. Designing and Evaluating a Personalized, Human-Centered Dietary Decision Support System for Use Among People With Diabetes in an Indian Setting: Protocol for a Quasi-Experimental Study. JMIR Research Protocols 2022;11(3):e13635 View
  27. Packheiser J, Malek I, Reichart J, Katona L, Luhmann M, Ocklenburg S. The Association of Embracing with Daily Mood and General Life Satisfaction: An Ecological Momentary Assessment Study. Journal of Nonverbal Behavior 2022;46(4):519 View
  28. Na M, Dou N, Liao Y, Rincon S, Francis L, Graham-Engeland J, Murray-Kolb L, Li R. Daily Food Insecurity Predicts Lower Positive and Higher Negative Affect: An Ecological Momentary Assessment Study. Frontiers in Nutrition 2022;9 View
  29. Asare B, Robinson S, Kwasnicka D, Powell D. Application of Ecological Momentary Assessment in Studies with Rotation Workers in the Resources and Related Construction Sectors: A Systematic Review. Safety and Health at Work 2023;14(1):10 View
  30. Perski O, Keller J, Kale D, Asare B, Schneider V, Powell D, Naughton F, ten Hoor G, Verboon P, Kwasnicka D. Understanding health behaviours in context: A systematic review and meta-analysis of ecological momentary assessment studies of five key health behaviours. Health Psychology Review 2022;16(4):576 View
  31. Barrett B. Health and sustainability co-benefits of eating behaviors: Towards a science of dietary eco-wellness. Preventive Medicine Reports 2022;28:101878 View
  32. Sun M, Jia W, Chen G, Hou M, Chen J, Mao Z. Improved Wearable Devices for Dietary Assessment Using a New Camera System. Sensors 2022;22(20):8006 View
  33. Wang L, Allman-Farinelli M, Yang J, Taylor J, Gemming L, Hekler E, Rangan A. Enhancing Nutrition Care Through Real-Time, Sensor-Based Capture of Eating Occasions: A Scoping Review. Frontiers in Nutrition 2022;9 View
  34. van Rossum C, ter Borg S, Nawijn E, Oliveira A, Carvalho C, Ocké M. Literature review on methodologies and tools for national dietary surveys; results of ERA EU‐menu‐project. EFSA Supporting Publications 2022;19(12) View
  35. Clark D, Keith N, Ofner S, Hackett J, Li R, Agarwal N, Tu W. Environments and situations as correlates of eating and drinking among women living with obesity and urban poverty. Obesity Science & Practice 2022;8(2):153 View
  36. Beres L, Mbabali I, Anok A, Katabalwa C, Mulamba J, Thomas A, Bugos E, Grabowski M, Nakigozi G, Chang L, Mockridge J. Acceptability and feasibility of mobile phone-based ecological momentary assessment and intervention in Uganda: A pilot randomized controlled trial. PLOS ONE 2022;17(8):e0273228 View
  37. Wang L, Chan V, Allman-Farinelli M, Davies A, Wellard-Cole L, Rangan A. Wearable Cameras Reveal Large Intra-Individual Variability in Timing of Eating among Young Adults. Nutrients 2022;14(20):4349 View
  38. König L, 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 View
  39. Bell B, Alam R, Mondol A, Ma M, Emi I, Preum S, de la Haye K, Stankovic J, Lach J, Spruijt-Metz D. Validity and Feasibility of the Monitoring and Modeling Family Eating Dynamics System to Automatically Detect In-field Family Eating Behavior: Observational Study. JMIR mHealth and uHealth 2022;10(2):e30211 View
  40. Saha S, Lozano C, Broyles S, Martin C, Apolzan J. Assessing the Initial Validity of the PortionSize App to Estimate Dietary Intake Among Adults: Pilot and Feasibility App Validation Study. JMIR Formative Research 2022;6(6):e38283 View
  41. Ponnada A, Wang S, Chu D, Do B, Dunton G, Intille S. Intensive Longitudinal Data Collection Using Microinteraction Ecological Momentary Assessment: Pilot and Preliminary Results. JMIR Formative Research 2022;6(2):e32772 View
  42. Houben K, Aulbach M. Is there a difference between stopping and avoiding? A review of the mechanisms underlying Go/No-Go and Approach-Avoidance training for food choice. Current Opinion in Behavioral Sciences 2023;49:101245 View
  43. Ruf A, Neubauer A, Ebner-Priemer U, Reif A, Matura S. Studying dietary intake in daily life through multilevel two-part modelling: a novel analytical approach and its practical application. International Journal of Behavioral Nutrition and Physical Activity 2021;18(1) View
  44. Taylor J, Allman-Farinelli M, Chen J, Gauglitz J, Hamideh D, Jankowska M, Johnson A, Rangan A, Spruijt-Metz D, Yang J, Hekler E. Perspective: A Framework for Addressing Dynamic Food Consumption Processes. Advances in Nutrition 2022;13(4):992 View
  45. Harrington K, Zenk S, Van Horn L, Giurini L, Mahakala N, Kershaw K. The Use of Food Images and Crowdsourcing to Capture Real-time Eating Behaviors: Acceptability and Usability Study. JMIR Formative Research 2021;5(12):e27512 View
  46. Battaglia B, Lee L, Jia S, Partridge S, Allman-Farinelli M. The Use of Mobile-Based Ecological Momentary Assessment (mEMA) Methodology to Assess Dietary Intake, Food Consumption Behaviours and Context in Young People: A Systematic Review. Healthcare 2022;10(7):1329 View
  47. Gibbons S, Gurry T, Lampe J, Chakrabarti A, Dam V, Everard A, Goas A, Gross G, Kleerebezem M, Lane J, Maukonen J, Penna A, Pot B, Valdes A, Walton G, Weiss A, Zanzer Y, Venlet N, Miani M. Perspective: Leveraging the Gut Microbiota to Predict Personalized Responses to Dietary, Prebiotic, and Probiotic Interventions. Advances in Nutrition 2022;13(5):1450 View
  48. Murai U, Tajima R, Matsumoto M, Sato Y, Horie S, Fujiwara A, Koshida E, Okada E, Sumikura T, Yokoyama T, Ishikawa M, Kurotani K, Takimoto H. Validation of Dietary Intake Estimated by Web-Based Dietary Assessment Methods and Usability Using Dietary Records or 24-h Dietary Recalls: A Scoping Review. Nutrients 2023;15(8):1816 View
  49. Neuhouser M, Prentice R, Tinker L, Lampe J. Enhancing Capacity for Food and Nutrient Intake Assessment in Population Sciences Research. Annual Review of Public Health 2023;44(1):37 View
  50. Renner B, Buyken A, Gedrich K, Lorkowski S, Watzl B, Linseisen J, Daniel H, Conrad J, Ferrario P, Holzapfel C, Leitzmann M, Richter M, Simon M, Sina C, Wirsam J. Perspective: A Conceptual Framework for Adaptive Personalized Nutrition Advice Systems (APNASs). Advances in Nutrition 2023;14(5):983 View
  51. O'Connor S, O’Connor L, Higgins K, Bell B, Krueger E, Rawal R, Hartmuller R, Reedy J, Shams-White M. Conceptualization and Assessment of 24-H Timing of Eating and Energy Intake: A Methodological Systematic Review of the Chronic Disease Literature. Advances in Nutrition 2024;15(3):100178 View
  52. Shinozaki N, Murakami K, Kimoto N, Masayasu S, Sasaki S. Association between meal context and meal quality: an ecological momentary assessment in Japanese adults. European Journal of Nutrition 2024;63(6):2081 View
  53. Dell'Acqua C, Allison G, Yun C, Weinberg A. Linking social reward responsiveness and affective responses to the social environment: An ecological momentary assessment study. Psychophysiology 2024;61(10) View
  54. Taylor C, Madril P, Weiss R, Thomson C, Dunton G, Jospe M, Richardson K, Bedrick E, Schembre S. Identifying the Leading Sources of Saturated Fat and Added Sugar in U.S. Adults. Nutrients 2024;16(15):2474 View
  55. Verbeke J, Matthys C. Experience Sampling as a dietary assessment method: a scoping review towards implementation. International Journal of Behavioral Nutrition and Physical Activity 2024;21(1) View
  56. Verbeke J, Matthys C. Development and User Experience Evaluation of an Experience Sampling-Based Dietary Assessment Method. Current Developments in Nutrition 2024;8(11):104479 View

Books/Policy Documents

  1. Kopyto D, Uhlenberg L, Zhang R, Stonawski V, Horndasch S, Amft O. Artificial Intelligence in Medicine. View
  2. Kopyto D, Uhlenberg L, Zhang R, Stonawski V, Horndasch S, Amft O. Artificial Intelligence in Medicine. View