Role of Eating Behavior and Stress in Maintenance of Dietary Changes During the PREVIEW Intervention
Bibliographic record
Abstract
OBJECTIVE: To examine whether eating behavior and perceived stress predict the maintenance of self-reported dietary change and adherence to dietary instructions during an intervention. DESIGN: A secondary analysis of the behavior maintenance stage (6-36 months) of the 3-year PREVIEW intervention (PREVention of diabetes through lifestyle Intervention and population studies in Europe and around the World). PARTICIPANTS: Adults (n = 1,311) with overweight and prediabetes at preintervention baseline. VARIABLES MEASURED: Eating behavior (Three-Factor Eating Questionnaire), stress (Perceived Stress Scale), and dietary intake (4-day food records on 4 occasions) were reported. ANALYSIS: Associations between predictors and dietary outcomes were examined with linear mixed-effects models for repeated measurements. RESULTS: Eating behaviors and stress at 6 months did not predict the subsequent change in dietary outcomes, but higher cognitive restraint predicted lower energy intake, and both higher disinhibition and hunger predicted higher energy intake during the following behavior maintenance stage. In addition, higher disinhibition predicted higher saturated fat intake and lower fiber intake, and higher hunger predicted lower fiber intake. Stress was not associated with energy intake or dietary quality. Eating behaviors and stress were not consistently associated with adherence to dietary instructions. CONCLUSIONS AND IMPLICATIONS: Higher cognitive restraint predicted lower energy intake (food quantity), but disinhibition and hunger were also associated with dietary quality.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".