Assessing food and nutrition literacy in children and adolescents: a systematic review of existing tools
Bibliographic record
Abstract
OBJECTIVE: Food literacy (FL) and nutrition literacy (NL) are concepts that can help individuals to navigate the current food environment. Building these skills and knowledge at a young age is important for skill retention, confidence in food practices and supporting lifelong healthy eating habits. The objectives of this systematic review were to: (i) identify existing tools that measure FL and NL among children and/or adolescents and (ii) describe the psychometric properties. DESIGN: A 4-phase protocol was used to systematically retrieve articles. The search was performed in May 2021. Study characteristics and psychometric properties were extracted, and a narrative synthesis was used to summarise findings. Risk of bias was assessed using the COSMIN checklist. SETTING: Six databases were searched to identify current tools. PARTICIPANTS: Children (2-12 years) and adolescents (13-18 years) participated in this study. RESULTS: Twelve tools were identified. Three tools measured FL, 1 tool measured NL, 4 tools measured both FL and NL, and 4 tools measured subareas of NL-more specifically, critical NL, food label and menu board literacy. Most tools were self-reported, developed based on a theoretical framework and assessed some components of validity and/or reliability for a specific age and ethnic group. The majority of tools targeted older children and adolescents (9-18 years of age), and one tool targeted preschoolers (3-6 years of age). CONCLUSIONS: Most widely used definitions of FL and NL do not acknowledge life-stage specific criterion. Continued efforts are needed to develop a comprehensive definition and framework of FL and NL appropriate for children, which will help inform future assessment tools.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.004 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".