Development and Preliminary Evaluation of a Food Literacy Measure for Use With Young People in Canada
Bibliographic record
Abstract
BACKGROUND: This article presents the culmination of a multiyear research project aimed at creating a comprehensive food literacy framework and corresponding measure. Specifically, this article documents the development and validation of a food literacy measure for young people facing social inequities. OBJECTIVES: This study aimed to identify items to measure 12 attributes of food literacy; test the measure with the identified target groups, considering attribute, face, and content validity, inter-rater reliability and test-retest reliability; and refine the measure. DESIGN: The study's design consisted of a 5-phase approach that included drafting the food literacy measure, expert review, cognitive interviews, pilot testing, and validity and reliability testing. PARTICIPANTS AND SETTING: Seven international experts provided feedback on the measure, and 25 individuals aged 16 to 25 years participated in cognitive interviews. Two hundred fifty-five young people completed the test survey, and 147 completed a retest survey 2 weeks later. These surveys identified food literacy factors. To further evaluate the validity of these factors, 193 participants completed a confirmatory test that was used for confirmatory factor analysis to assess the final model's fit. Interview participants were recruited from local programs and services from across Ontario, Canada, and survey participants were recruited from across Canada via social media. The research study was conducted between January 2018 and December 2019. MAIN OUTCOME MEASURES: The main outcome measures were validity and reliability scores for a food literacy measurement tool that consisted of 50 questions across 10 attributes of food literacy. STATISTICAL ANALYSES PERFORMED: Interview analyses were guided by the 4 stages of cognitive processing. Exploratory factor analysis was used to identify the factors that improved the Cronbach's alpha of the food literacy measure. Test-retest reliability was assessed using percent agreement, Cohen's kappa, and weighted kappa. Confirmatory factor analysis was used to produce an acceptable final model with a root mean square error of approximation estimate. RESULTS: The final food literacy measure consisted of 50 questions addressing 10 food literacy attributes. Exploratory factor analysis showed an improvement in Cronbach's alpha when compared with the initial attribute construction. Test-retest reliability showed percent agreement ranging from 64% to 97%, with most items having fair (0.21 to 0.40) to moderate (0.41 to 0.60) kappa values. Confirmatory factor analysis produced an acceptable final model with a root mean square error of approximation estimate of 0.0437. CONCLUSIONS: The food literacy measure is a comprehensive tool for assessing food literacy among young people. Additional research is needed to explore the measure's modularity, its use as an evaluation tool, and its suitability for use with diverse samples, including individuals from varied gender, geographic locations, ethnicities, and cultural backgrounds.
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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 | 0.009 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".