The effectiveness of a 12 week weight loss challenge on weight loss and physical activity in commercial fitness centres
Bibliographic record
Abstract
The objective of this study was to examine the effectiveness of a 12 week weight loss intervention in a commercial fitness centre on body mass index (BMI), behavioural regulations consistent with Organismic Integration Theory (OIT, Deci & Ryan, 2002) and moderate to vigorous physical activity (MVPA). Participants were recruited from the general membership to either the intervention (n= 35) or a do-as-you-do control (n = 42) group. The intervention group received weekly one-on-one coaching sessions and bi-weekly seminars designed to increase physical activity and improve dietary intake. Pre- and post-intervention all participants received anthropometric assessments and completed self-report instruments to assess behavioural regulations and MVPA. The results of the mixed model analyses of variance showed an increase in MVPA (F = 4.79, p= .03) and a decrease in BMI (F = 8.15, p= .01) in the intervention group when compared to the control across the 12 week intervention. Changes (D) in behavioural regulations were associated with DMVPA congruent with OIT (Deci & Ryan, 2002) regardless of condition. Study results indicate that 12 week weight loss challenges in commercial fitness centres may be effective programming tools in producing short-term anthropometric, behavioural and motivational changes.Acknowledgments: Support for this research was provided by the Social Sciences and Humanities Research Council of Canada
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.003 | 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".