Assessing the impact of a group mediated cognitive behavioural (GMCB) intervention on health outcomes in an obese population
Bibliographic record
Abstract
The overall goal of the Healthy Eating and Active Living for Tomorrow’s Health (HEALTH) study was to test the efficacy of a non-pharmaceutical treatment program for class I and II obese patients in a rural Eastern Canadian province. A secondary goal, and the focus of this presentation, was to test the added benefit of including a Group Mediated Cognitive Behavioural (GMCB) intervention on health, anthropometric, and psychosocial functioning outcomes. A cross-sectional pre and post intervention study measured the impact of a six-month active lifestyle intervention delivered by certified exercise physiologists, certified personal trainers and registered dieticians for all participants. This active intervention was followed by a six-month self-management period. The 146 participants (starting Body Mass Index between 30-40) came from rural and urban communities and were divided into four groups. Two (1 urban, 1 rural) of the groups also participated in a 12-session GMCB intervention delivered bi-weekly by an exercise psychologist. The suite of intervention strategies significantly improved cardiovascular health markers and anthropometric measures for participants in both groups. While differences in improvement on these markers were not observed for participants taking part in the additional GMCB sessions, the sessions were beneficial. Specifically, overall attrition from the six-month active intervention was high (39%); however, attrition among the participants who received GMCB was significantly lower than the participants who did not (29% versus 50%). Other attendance and attrition metrics support the significant positive impact of GMCB in retaining participants in this successful intervention. This study provides strong evidence that an inter-professional community-based intervention program is effective in improving the health and well-being of class I and II obese participants. Despite the self-referral nature of the project, attrition was high and it therefore appears that GMCB intervention is an essential component to participant retention. Acknowledgments: Funding Acknowledgements: Canadian Institute for Health Research (MOP 110940) and the New Brunswick Health Research Foundation.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".