Can certified health professionals treat obesity in a community-based programme? A quasi-experimental study
Bibliographic record
Abstract
OBJECTIVE: To test the effectiveness of a non-pharmaceutical programme for obese participants in a rural Eastern Canadian Province using certified health professionals. DESIGN: A prospective quasi-experimental design with repeated premeasure and postmeasure. PARTICIPANTS: 146 participants with obesity (body mass index >30 kg/m(2)) from rural and urban communities in an Eastern Canadian Province were divided into four groups. INTERVENTION: A 6-month intensive active community-based lifestyle intervention (InI) delivered by Certified Exercise Physiologists, Certified Personal Trainers and Registered Dietitians, followed by 6 months of self-management. A second intervention (InII) was nested in InI and consisted of group-mediated cognitive-behavioral intervention (GMCBI) delivered by an exercise psychologist to two of the four InI groups. OUTCOMES: (1) Improving health outcomes among the participants' preactive and postactive 6-month intervention and self-management period, (2) Documenting the impact of InII (GMCBI) and location of the intervention (urban vs rural). RESULTS: The 6-month active InI significantly improved cardiovascular health for participants who completed the intervention. InII (GMCBI) significantly lowered the attrition rate among the participants. The self-management period was challenging for the participants and they did not make further gains; however, most were able to maintain the gains achieved during the active intervention. The location of the intervention, urban or rural, had little impact on outcomes. CONCLUSIONS: A community-based programme utilising healthcare professionals other than physicians to treat obese patients was effective based on premeasure and postmeasure. During the self-management phase, the participants were able to maintain the gains. Psychological support is essential to participant retention.
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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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".