You Say Potato, I Say Vegetable; You Say Tomato, I Say Fruit: Cognitive Validity of Food Group–Based Dietary Recall Questions
Bibliographic record
Abstract
Background: There is a need for valid, standardized approach for list-based questionnaires to measure food group consumption for indicators of diet quality including dietary diversity. Objectives: A common method for collecting dietary diversity data consists of open-ended food group questions, e.g. "Yesterday, did you eat any vegetables, such as cucumber, cabbage, or celery?" We sought to examine the cognitive validity of open-ended questions that require respondents to categorize foods and closed-ended alternatives using sentinel foods. Methods: Pretesting and 83 cognitive interviews were conducted in 5 languages in São Paulo and New York City in 2018. In structured interviews, respondents were asked to describe their thought processes in answering each question. Their feedback and responses to closed-ended and open-ended food group questions were compared. The Gallup World Poll then piloted 2 versions of the questionnaire in a nationally representative sample of 1000 in Brazil in 2018. Results: Respondents in all settings miscategorized foods when asked open-ended food group questions (0%-82%, depending on the food group), respondents varied in their ability to think of other foods that belonged to specified food groups (35%-50% could think of any items), and open-ended questions presented an additional cognitive burden. There were no significant differences between the results from closed-ended and open-ended questions in the national pilot test. In the context of a multitopic survey, the finalized questionnaire took 3-5 min to answer, had no additional training requirements, and enumerators reported similar ease in administration as modules on other topics. Conclusions: For data collection on food group consumption, open-ended questions requiring respondents to categorize foods present cognitive validity problems. Closed-ended questions using sentinel foods reduce or eliminate ambiguity, presenting lower cognitive burden and greater comprehension. Based on these results, the closed-ended method has been adopted in international survey platforms for measuring dietary diversity and other aspects of diet quality.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.068 | 0.145 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".