Effect of a Group Behavioural Management Program on Emotional Regulation of Food Choices: A Pilot Randomized Controlled Trial
Bibliographic record
Abstract
PURPOSE: In Ontario, group programs to increase mindfulness of food choices are provided in Family Health Teams (FHTs), but evaluation is limited. We targeted patients with chronic conditions that could benefit from intensified management and evaluated an existing program. METHODS: We included 3 FHTs. Patients were randomized to immediate participation in the intervention (n = 16) or to wait-list control (n = 14). Eligible participants were between 40 and 70 years old, living with diabetes and/or hypertension and had at least 2 of: elevated cholesterol (LDL >4 if hypertension or LDL >2 mmol/L if diabetes), blood sugar (A1c >7.5%), or blood pressure (systolic BP >140). The intervention was a 6-week group program of 2-hour weekly sessions addressing mindfulness of food choices facilitated by a trained dietitian and social worker. We used the Emotional Eating Questionnaire (EEQ) a validated 10-item questionnaire measuring the degree of interaction between food intake and emotion. The primary outcome was change in the EEQ over 6 weeks. RESULTS: There was no difference in the change in EEQ in either unadjusted (P = 0.4) or adjusted (P = 0.3) analysis. CONCLUSIONS: We found no effect for this intervention, although the small sample size limits interpretation. The results were contrary to what was expected.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".