Development of the Canadian Eating Practices Screener for Adolescents to assess eating practices based on Canada’s Food Guide 2019 recommendations
Bibliographic record
Abstract
BACKGROUND: In addition to guidance on food choices, the Canada’s Food Guide 2019 (CFG-2019) provides recommendations to support healthy eating habits. A brief self-administered eating practices questionnaire informed by CFG-2019 recommendations was recently developed and validated among adults, but no such measure is available for adolescents. The objective of this study was to develop and assess the content validity of a self-administered screener to measure eating practices based on CFG-2019 recommendations among English- and French-speaking adolescents aged 10 to 17 years. METHODS: Following a literature review of existing measures and the identification of guiding principles for questionnaire development, a 26-item draft screener was created. The content validity of the draft screener was assessed by an expert panel with expertise in nutrition, eating behaviours, public health and/or questionnaire validation (English n = 13, French n = 7) and through two rounds of cognitive interviews with adolescents (English n = 18, French n = 13). RESULTS: The number of items was reduced from 26 to 12 following review by the expert panel, and further reduced to 11 after the cognitive interviews with adolescents. Minor wording changes were made to improve clarity of a few items. CONCLUSIONS: This study resulted in the development of the 11-item Canadian Eating Practices Screener for Adolescents/Questionnaire court canadien sur les pratiques alimentaires des adolescents designed for use among adolescents aged 10 to 17 years. Further work is needed to test the screener for construct validity and reliability. After which, this measure can be used for research and nutrition surveillance of eating practices among adolescents living in Canada.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".