Smartphone tool to collect repeated 24 h dietary recall data in Nepal. Issue 2 (31st August 2017)

• Record Type: Journal Article
• Authors: Harris-Fry, Helen; Beard, B James; Harrisson, Tom; Paudel, Puskar; Shrestha, Niva; Jha, Sonali; Shrestha, Bhim P; Manandhar, Dharma S; Costello, Anthony; Saville, Naomi M
• Is Part Of: Public health nutrition. Volume 21:Issue 2(2018)
• Page Start: 260
• Page End: 272
• Publication Date: 2017-08-31
• Subjects: Nutrition, -- Data collection, -- Electronic data capture, -- Smartphones, -- Dietary recall; Nutrition -- Periodicals; Nutrition policy -- Periodicals; Public health -- Periodicals; 613.2
• DOI: 10.1017/S136898001700204X
• Languages: English
• ISSNs: 1368-9800

Abstract

Abstract: Objective: To outline the development of a smartphone-based tool to collect thrice-repeated 24 h dietary recall data in rural Nepal, and to describe energy intakes, common errors and researchers' experiences using the tool. Design: We designed a novel tool to collect multi-pass 24 h dietary recalls in rural Nepal by combining the use of a CommCare questionnaire on smartphones, a paper form, a QR (quick response)-coded list of foods and a photographic atlas of portion sizes. Twenty interviewers collected dietary data on three non-consecutive days per respondent, with three respondents per household. Intakes were converted into nutrients using databases on nutritional composition of foods, recipes and portion sizes. Setting: Dhanusha and Mahottari districts, Nepal. Subjects: Pregnant women, their mothers-in-law and male household heads. Energy intakes assessed in 150 households; data corrections and our experiences reported from 805 households and 6765 individual recalls. Results: Dietary intake estimates gave plausible values, with male household heads appearing to have higher energy intakes (median (25th–75th centile): 12 079 (9293–14 108) kJ/d) than female members (8979 (7234–11 042) kJ/d for pregnant women). Manual editing of data was required when interviewers mistook portions for food codes and for coding items not on the food list. Smartphones enabled quick monitoring of data and interviewer performance, but we initially faced technical challenges with CommCare forms crashing. Conclusions: With sufficient time dedicated to development and pre-testing, this novel smartphone-based tool provides a useful method to collect data. Future work is needed to further validate this tool and adapt it for other contexts.