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- Title
Integration of an Image-Based Dietary Assessment Paradigm into Dietetic Training Improves Food Portion Estimates by Future Dietitians.
- Authors
Ho, Dang Khanh Ngan; Chiu, Wan-Chun; Lee, Yu-Chieh; Su, Hsiu-Yueh; Chang, Chun-Chao; Yao, Chih-Yuan; Hua, Kai-Lung; Chu, Hung-Kuo; Hsu, Chien-Yeh; Chang, Jung-Su
- Abstract
The use of image-based dietary assessments (IBDAs) has rapidly increased; however, there is no formalized training program to enhance the digital viewing skills of dieticians. An IBDA was integrated into a nutritional practicum course in the School of Nutrition and Health Sciences, Taipei Medical University Taiwan. An online IBDA platform was created as an off-campus remedial teaching tool to reinforce the conceptualization of food portion sizes. Dietetic students' receptiveness and response to the IBDA, and their performance in food identification and quantification, were compared between the IBDA and real food visual estimations (RFVEs). No differences were found between the IBDA and RFVE in terms of food identification (67% vs. 71%) or quantification (±10% of estimated calories: 23% vs. 24%). A Spearman correlation analysis showed a moderate to high correlation for calorie estimates between the IBDA and RFVE (r ≥ 0.33~0.75, all p < 0.0001). Repeated IBDA training significantly improved students' image-viewing skills [food identification: first semester: 67%; pretest: 77%; second semester: 84%) and quantification [±10%: first semester: 23%; pretest: 28%; second semester: 32%; and ±20%: first semester: 38%; pretest: 48%; second semester: 59%] and reduced absolute estimated errors from 27% (first semester) to 16% (second semester). Training also greatly improved the identification of omitted foods (e.g., condiments, sugar, cooking oil, and batter coatings) and the accuracy of food portion size estimates. The integration of an IBDA into dietetic courses has the potential to help students develop knowledge and skills related to "e-dietetics".
- Subjects
TAIWAN; ACADEMIC medical centers; DIETETICS education; HEALTH occupations students; DIGITAL image processing; INTERDISCIPLINARY education; NUTRITIONAL assessment; STATISTICS; FOOD portions; DATA analysis; EDUCATIONAL outcomes; NATIONAL competency-based educational tests; DESCRIPTIVE statistics
- Publication
Nutrients, 2021, Vol 13, Issue 1, p175
- ISSN
2072-6643
- Publication type
Article
- DOI
10.3390/nu13010175