The effect of food and weight‐related cues on physiological stress measures in premenopausal women differing in their levels of cognitive dietary restraint
Bibliographic record
Abstract
Cognitive dietary restraint (CDR) reflects a perception of constantly monitoring or attempting to limit food intake to control weight. Higher cortisol levels have been observed in women with high vs low CDR. This study assessed whether food and weight‐related cues differentially activate the physiological stress response in 70 healthy women aged 19–35 with low (0–5; n=35) or high (13–21; n=35) scores on the Three Factor Eating Questionnaire Restraint subscale. Participants completed questionnaires on eating attitudes, stress, anxiety, depression and physical activity (PA) in the presence of food temptations. Concurrently, blood pressure, heart rate and salivary cortisol measures were obtained every 15 min for 90 min. Results showed significant between‐group differences in eating attitudes while anthropometric, general perceived stress, anxiety, depression and PA variables were similar. Although women with high CDR perceived the protocol as more stressful, physiological measures did not differ by CDR level. Participants also provided 4 saliva samples collected within 1 hr of awakening to assess the awakening cortisol response (ACR); no between‐group differences were observed. In conclusion, women with high and low CDR had similar physiological stress responses after cue exposure; however, this may have been the result of a weak stressor. Supported by Canadian Institutes of Health Research 79563.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".