Validation of a child version of the Three-Factor Eating Questionnaire in a Canadian sample: a psychometric tool for the evaluation of eating behaviour
Bibliographic record
Abstract
OBJECTIVE: To examine score validity and reliability of a child version of the twenty-one-item Three-Factor Eating Questionnaire (CTFEQ-R21) in a sample of Canadian children and adolescents and its relationship with BMI Z-score and food/taste preferences. DESIGN: Cross-sectional study. SETTING: School-based. PARTICIPANTS: Children (n 158), sixty-three boys (mean age 11·5 (sd 1·6) years) and ninety-five girls (11·9 (sd 1·9) years). RESULTS: Exploratory factor analysis revealed that the CTFEQ-R21 was best represented by four factors with item 17 removed (CFFEQ-R20), representing Cognitive Restraint (CR), Cognitive Uncontrolled Eating (UE 1), External Uncontrolled Eating (UE 2) and Emotional Eating (EE), accounting for 41·2 % of the total common variance with good scale reliability. ANOVA revealed that younger children reported higher UE 1 and CR scores than older children, and boys who reported high UE 1 scores had significantly higher BMI Z-scores. Children with high UE 1 scores reported a greater preference for high-protein and -fat foods, and high-fat savoury (HFSA) and high-fat sweet (HFSW) foods. Higher preference for high-protein, -fat and -carbohydrate foods, and HFSA, HFSW and low-fat savoury foods was found in children with high UE 2 scores. CONCLUSIONS: The study suggests that the CFFEQ-R20 can be used to measure eating behaviour traits and associations with BMI Z-score and food/taste preferences in Canadian children and adolescents. Future research is needed to examine the validity of the questionnaire in larger samples and other geographical locations, as well as the inclusion of extraneous variables such as parental eating or socio-economic status.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".