Korean Journal of Community Nutrition (대한지역사회영양학회지)

The Korean Society of Community Nutrition (대한지역사회영양학회)
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Development and User Satisfaction of a Mobile Phone Application for Image-based Dietary Assessment

카메라가 장착된 모바일 폰을 이용한 24시간 식사 회상 앱 개발 및 만족도 연구

  • 김서윤 (국민대학교 식품영양학과) ;
  • 정상진 (국민대학교 식품영양학과)
  • Received : 2017.12.07
  • Accepted : 2017.12.25
  • Published : 2017.12.31
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Abstract

Objectives: The objective of this study was to develop mobile phone application for image-based dietary assessment and evaluate satisfaction regarding respondent's use of the mobile phone application. Methods: We developed a mobile phone application to assess dietary intakes using 24 hour dietary recall. After initial development, application was reviewed by ten adults and revised based on their comments. We recruited 192 volunteers (92 males, 100 females) to use the mobile phone application and to respond to a satisfaction survey. Participants were instructed to use the mobile phone application with fiducial marker five centimeter in width, length and two centimeter height at each eating occasion during designated 4 days, capturing $45^{\circ}$ angle and $90^{\circ}$ angle images of all food and beverage items before and after consumption. After using the mobile phone application for 4 days, participants were asked to complete an online questionnaire on the satisfaction of the mobile phone app. User satisfaction items composed of 12 questions of application user interface, 8 questions of emotional response, 9 questions of eating behavior in 5 likert scale. Participants were also asked to provide additional open-ended comments on the use of mobile phone application. Statistical analysis was performed by using the SPSS 23.0 (Statistical Package for the Social Science). Results: The average user interface score was $2.82{\pm}1.08$, which was close to the 'normal' response. Responses for emotion and eating behavior also were borderline to the 'normal'. Conclusions: This study found that the mobile phone application using 24-hour recall was acceptable to be used to assess dietary intakes for several days. However, there should be a need for such technology to be user-oriented instead of researcher-oriented. Easy and cost-effective new technology is needed for estimating the amounts of food eaten automatically when the photos are taken.

Keywords

References

  1. Kim MK, Lee SS, Ahn YO. Reproducibility and validity of a self-administered semiquantitative food frequency questionnaire among middle-aged men in Seoul. Korean J Community Nutr 1996; 1(3): 376-394.
  2. Kim HR. A study on the association of diet quality and risk of mortality and major chronic diseases from nationally representative longitudinal data. Health Soc Welf Rev 2013; 33(3): 5-30.
  3. Kang HR, Jung HJ, Paik HY. Analysis of foods and nutrients intake obtained at the final probing step in 24-hour recall method. Korean J Nutr 2009; 42(2): 158-170. https://doi.org/10.4163/kjn.2009.42.2.158
  4. Cameron ME, Van Staveren WA. Manual on methodology for food consumption studies. 1st revision. Boston: Oxford University Press; 1988. p. 33.
  5. Willet W. Nutritional epidemiology. 1st revision. New York: Oxford University Press; 1990. p. 100.
  6. Schatzkin A, Kipnis V, Carroll RJ, Midthune D, Subar AF, Bingham S et al. A comparison of a food frequency questionnaire with a 24-hour recall for use in an epidemiological cohort study: Results from the biomarker-based observing protein and energy nutrition (OPEN) study. Int J Epidemiol 2003; 32(6): 1054-1062. https://doi.org/10.1093/ije/dyg264
  7. Lee SY, Ju DL, Paik HY, Shin CS, Lee HK. Assessment of dietary intake obtained by 24-hour recall method in adults living in Yeonchon area (1): assessment based on nutrient intake. Korean J Nutr 1998; 31(3): 333-342.
  8. Dwyer JT, Krall EA, Coleman KA. The problem of memory in nutritional epidemiological research. J Am Diet Assoc 1987; 87(11): 1509-1512.
  9. Jobe JB, Mingay DJ. Cognitive research improves questionnaires. Am J Public health 1989; 79(8): 1053-1055. https://doi.org/10.2105/AJPH.79.8.1053
  10. Willet W. Nutritional epidemiology. 2nd ed. New York: Oxford University Press; 1995. p. 111.
  11. Krall EA, Dwyer JT, Coleman KA. Factors influencing accuracy of dietary recall. Nutr Res 1988; 8(7): 829-841. https://doi.org/10.1016/S0271-5317(88)80162-3
  12. Lee JE, Ahn YJ, Kim KC, Park C. Study on the associations of dietary variety and nutrition intake level by the number of survey days. Kor J Nutr 2004; 37(10): 908-916.
  13. Chang UJ, Ko S. A study on the dietary intake survey method using a cameraphone. Korean J Community Nutr 2007; 12(2): 198-205.
  14. Kim SB, Kim SK, Kim SN, Cho YS, Kim MH. Establishment of one portion size of dishes frequently consumed by Korean adults using 2010 KNHANES and its comparison with the one portion size using 2005 KNHANES: focusing on rice, noodles, soups, and stews. Korean J Food Nutr 2013; 26(4): 745-752. https://doi.org/10.9799/ksfan.2013.26.4.745
  15. Nelson M, Atkinson M, Darbyshire S. Food photography I: the perception of food portion size from photographs. Br J Nutr 1994; 72(5): 649-663. https://doi.org/10.1079/BJN19940069
  16. Nelson M, Atkinson M, Darbyshire S. Food photography II: use of food photographs for estimating portion size and the nutrient content of meals. Br J Nutr 1996; 76(1): 31-49. https://doi.org/10.1079/BJN19960007
  17. Turconi G, Guarcello M, Berzolari FG, Carolei A, Bazzano R, Roggi C. Evaluation of a colour food photography atlas as a tool for quantifying food portion size in epidemiological dietary survey. Eur J Clin Nutr 2005; 59(8): 923-931. https://doi.org/10.1038/sj.ejcn.1602162
  18. Ovaskainen ML, Paturi M, Reinivuo H, Hannila ML, Sinkko H, Lehtisalo J et al. Accuracy in the estimation of food servings against the portions in food photographs. Eur J Clin Nutr 2008; 62(5): 674-681. https://doi.org/10.1038/sj.ejcn.1602758
  19. Lazarte CE, Encinas ME, Alegre C, Granfeldt Y. Validation of digital photographs, as a tool in 24-h recall, for the improvement of dietary assessment among rural populations in developing countries. Nutr J 2012; 11(1): 570.
  20. Kim HS, Lee EY, Kim KM, Kim KW, Pyun JW, Chung SJ et al. Survey on dietary behaviors and intakes of instant noodle (Ramyeon) soup among college students. Korean J Community Nutr 2013; 18(4): 365-371. https://doi.org/10.5720/kjcn.2013.18.4.365
  21. Wang DH, Kogashiwa M, Ohta S, Kira S. Validity and reliability of dietary assessment method: The application of a digital camera with a mobile phone card attachment. J Nutr Sci Vitaminol 2002; 48(6): 498-504. https://doi.org/10.3177/jnsv.48.498
  22. Williamson DA, Allen HR, Martin PD, Alfonso AJ, Gerald B, Hunt A. Comparison of digital photography to weighed and visual estimation of portion size. J Am Diet Assoc 2003; 103(9): 1139-1145. https://doi.org/10.1016/S0002-8223(03)00974-X
  23. Wang DH, Kogashiwa M, Kira S. Development of a new instrument for evaluating individuals' dietary intakes. J Am Diet Assoc 2006; 106(10): 1588-1593. https://doi.org/10.1016/j.jada.2006.07.004
  24. Kwon JS, Kim KM, Kim HK. A study on application of food photographs for estimating individual' dietary intake. Korean J Community Nutr 2010; 15(6): 760-775.
  25. Six BL, Schap TE, Zhu FM, Mariappan A, Bosch M, Delp EJ et al. Evidence-based development of a mobile telephone food record. J Am Diet Assoc 2010; 110(1): 74-79. https://doi.org/10.1016/j.jada.2009.10.010
  26. Stumbo PJ. New technology in dietary assessment: a review of digital methods in improving food record accuracy. Proc Nutr Soc 2013; 72(1): 70-76. https://doi.org/10.1017/S0029665112002911
  27. Hongu N, Pope BT, Bilgic P, Orr BJ, Suzuki A, Kim AS et al. Usability of a smartphone food picture app for assisting 24-hour dietary recall: a pilot study. Nutr Res Pract 2015; 9(2): 207-212. https://doi.org/10.4162/nrp.2015.9.2.207
  28. Choi H, Choi YJ. The impact of smartphone application quality factors on trust and the users' continuance intention according to gender. J Korea Ind Inf Syst Res 2011; 16(4): 151-162. https://doi.org/10.9723/jksiis.2011.16.4.151
  29. Conway JM, Ingwersen LA, Vinyard BT, Moshfegh AJ. Effectiveness of the US department of agriculture 5-step multiple-pass method in assessing food intake in obese and nonobese women. Am J Clin Nutr 2003; 77(5): 1171-1178. https://doi.org/10.1093/ajcn/77.5.1171
  30. Chang WS, Ji YG. Usability evaluation for smart phone augmented reality application user interface. Soc e-Bus Stud 2011; 16(1): 35-47. https://doi.org/10.7838/jsebs.2011.16.1.035
  31. Wong Jyh Eiin, Yoke San Chen, Nor Effendy Othman, Bee Koon Poh. Development of and electronic food diary to assess dietary intake among young adults. Proceedings of Asian congress of nutrition 12th; 2015 May 14; Japan: p. 145.
  32. Daugherty BL, Schap TE, Ettienne-Gittens R, Zhu FM, Bosch M, Delp EJ et al. Novel technologies for assessing dietary intake: Evaluating the usability of a mobile telephone food record among adults and adolescents. J Med Internet Res 2012; 14(2): e58. https://doi.org/10.2196/jmir.1967
  33. Lee HJ, Lee JS. Supporting sustainable food logging by adjusting the degree of data input structure. Proceedings of HCI KOREA; 2016 Jan 27; Kangwon: p. 677-679.
  34. Pouladzadeh P, Shirmohammadi S, Almaghrabi R. Measuring calorie and nutrition from food image. IEEE Trans Instrum Meas 2014; 63(8): 1947-1956. https://doi.org/10.1109/TIM.2014.2303533
  35. Noom, Inc. Noom [internet]. Noom, Inc; 2016 [cited 2016 Dec 1]. Available from: https://www.noom.com/.
  36. JUVIS co., Ltd. JUVIS [internet]. JUVIS co., Ltd; 2016 [cited 2016 Dec 1]. Available from: http://www.juviscorp.co.kr/.

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