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Comparison of chatbot and paper-based FFQs in participants who underwent colorectal or gastric cancer screeningopen access

Authors
임의연Yun Jeong Lim김상훈김웅섭이정은
Issue Date
Dec-2025
Publisher
한국영양학회
Keywords
Telemedicine; artificial intelligence; nutrition assessment; diet surveys
Citation
Nutrition Research and Practice, v.19, no.6, pp 932 - 942
Pages
11
Indexed
SCIE
SCOPUS
KCI
Journal Title
Nutrition Research and Practice
Volume
19
Number
6
Start Page
932
End Page
942
URI
https://scholarworks.dongguk.edu/handle/sw.dongguk/62291
DOI
10.4162/nrp.2025.19.6.932
ISSN
1976-1457
2005-6168
Abstract
BACKGROUND/OBJECTIVES: The food frequency questionnaire (FFQ) is a commonly used tool for assessing the usual diet of groups and individuals. This study developed a chatbot- based mobile FFQ, embedded within KakaoTalk, Korea’s most popular mobile instant messenger. This study compared the energy and nutrient intake reported by participants using a chatbot versus a paper-based FFQ. SUBJECTS/METHODS: This study included 95 participants (50 men and 45 women, aged24–79 yrs) who underwent gastroscopy or colonoscopy for cancer screening at Dongguk University Ilsan Hospital between April and August 2022. The participants completedboth the chatbot and paper-based FFQs within a 3-mon period. The comparability of the chatbot-based FFQ with traditional paper-based FFQ was examined by comparing thelog-transformed intakes of energy and nutrients using Pearson correlation coefficients. The Cohen’s Kappa coefficients, Bland–Altman plots, and cross-classification percent agreement were used to evaluate the compatibility. RESULTS: The Pearson correlation coefficients of energy and energy-adjusted nutrients ranged from 0.74 (niacin) to 0.90 (vitamin A), with a median coefficient of 0.85. The Cohen kappa coefficients varied from 0.42 (niacin) to 0.64 (n-6 fatty acid). The Bland–Altman plots suggested that most of the data points fell between the lower and upper limits of agreement, and 88% to 98% of the participants were classified into the same or adjacent quartiles for energy-adjusted nutrients. CONCLUSION: These findings indicate good comparability between chatbot- and paper- based FFQs. A chatbot-based mobile FFQ can provide comparable dietary intake rankings, making it a viable tool for evaluating the associations between diet and various disease risks in longitudinal studies.
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