Yale Food Addiction Scale: Examining the Psychometric Properties of the French Version among Individuals with Severe Obesity Awaiting Bariatric Surgery
Bibliographic record
Abstract
The French version of the Yale Food Addiction Scale (YFAS), used to evaluate food addiction symptomatology, has only been validated among the general population. The aim of this study was thus to explore the psychometric properties (factor structure, internal consistency, convergent and divergent validity) of the French version of the YFAS in a clinical sample, namely individuals suffering from severe obesity and awaiting bariatric surgery. Participants (N = 146; mean BMI = 48.29 kg/m2) were recruited at the Quebec Heart and Lung Institute (Canada) during their pre-operative visit. They were asked to complete questionnaires, including the YFAS. Factorial and correlational analyses were performed. Some items had to be removed from the factorial analysis due to a lack of variability (#4, #10, #11, #12, and #22) and low factor loading (#24). The analysis conducted on the remaining 16 items revealed a one-factor structure, with factor loadings higher than .30 and excellent internal consistency (α = .92). The present findings are consistent with previous validation studies of samples presenting obesity and support the use of a 16-item version of the French YFAS among bariatric candidates. However, the need for further investigation remains important in order to better assess the stability of the instrument when used in clinical samples.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".