Development and validation of the Child Three-Factor Eating Questionnaire (CTFEQr17)
Bibliographic record
Abstract
OBJECTIVE: To develop and validate a child and adolescent version of the Three-Factor Eating Questionnaire (CTFEQr17) and to assess its psychometric properties and factor structure. We also examined associations between the CTFEQr17 and BMI and food preferences. DESIGN: A two-phase approach was utilized, employing both qualitative and quantitative methodologies. SETTING: Primary and secondary schools, UK. SUBJECTS: In phase 1, seventy-six children (thirty-nine boys; mean age 12·3 (sd 1·4) years) were interviewed to ascertain their understanding of the original TFEQr21 and to develop accessible and understandable items to create the CTFEQr17. In phase 2, 433 children (230 boys; mean age 12·0 (sd 1·7) years) completed the CTFEQr17 and a food preference questionnaire, a sub-sample (n 253; 131 boys) had their height and weight measured, and forty-five children (twenty-three boys) were interviewed to determine their understanding of the CTFEQr17. RESULTS: The CTFEQr17 showed good internal consistency (Cronbach's α=0·85) and the three-factor structure was retained: cognitive restraint (CR), uncontrolled eating (UE) and emotional eating (EE). Qualitative data demonstrated a high level of understanding of the questionnaire (95 %). High CR was found to be significantly associated with a higher body weight, BMI and BMI percentile. High UE and EE scores were related to a preference for high-fat savoury and high-fat sweet foods. The relationships between CTFEQr17, anthropometry and food preferences were stronger for girls than boys. CONCLUSIONS: The CTFEQr17 is a psychometrically sound questionnaire for use in children and adolescents, and associated with anthropometric and food preference measures.
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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 | 0.015 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".