Health behaviours, intentions and barriers to change among obesity classes I, II and III
Bibliographic record
Abstract
Summary Health behaviour change is a cornerstone in the management of obesity, and data on health behaviours, intentions and barriers to change would be useful to inform the development of interventions. The aim of this study was to describe these variables in individuals with obesity, and to compare obesity classes. The study obtained data from the Canadian Community Health Survey 2011–2012 including 5614 adults with body mass index (BMI) ≥30 kg m −2 . The majority of participants reported eating four or more fruits and vegetables daily (65.3% [95% confidence interval {CI}: 64.1–66.6]), being a regular drinker (59.6% [95% CI: 58.4–61.0]) and inactive (58.0% [95% CI: 56.7–59.3]). About 84% of participants answered they should do and/or intend to do something in the next year to improve their health, with increasing exercise being the most reported choice (69.2% [95% CI: 67.1–71.5]). Among the 58.0% (95% CI: 55.9–60.2) of participants facing barriers to change, the lack of willpower was the most reported (37.0% [95% CI: 34.2–39.7]). No difference between classes for intention to change and barriers were found. Comorbidities were the most important factor explaining several health behaviours and barriers to change. The vast majority of participants, regardless of the severity of obesity, know they should do and also want to do something to improve their health, but faced a lack of willpower. Thus, the most important thing to consider during an obesity intervention is the lack of motivation to modify health behaviours and beyond BMI, the presence of comorbidities.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".