Validation study assesses automated dietary data collection in low-literacy women, indicating feasibility for food policy design.
BackgroundDietary data gaps limit the design of effective food policies and programs in low-and middle-income countries (LMICs).Automated mobile phone-based tools offer an opportunity to fill data gaps using less resources compared with face-to-face methods, especially for high-frequency dietary quality monitoring in resourceconstrained environments. ObjectiveThis study assessed the validity of automated participant-recorded dietary data via Interactive Voice Response (IVR) on basic mobile phones to assess dietary quality amongst rural women in a sub-Saharan African context, against same-day gold standard observed weighed food records (WFR). MethodsAutomated IVR collected list-based recalls of food groups consumed in the last 24 hour using yes/no push-button response from 156 randomly selected women in rural Northern Uganda (wet season).Inter-method agreement was assessed by comparing mean women's dietary diversity scores (WDDS) using Weighted Cohen's kappa, Bland-Altman plots and Wilcoxon signed-rank test.Agreement in percentage achieving minimum DDS for women (MDD-W) and consumption of unhealthy foods and beverages was tested using Cohen's kappa and McNemar's test.
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O’Meara et al. (2026) studied this question.
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