The Impact of Long-Term Physical Activity Interventions for Overweight/Obese Postmenopausal Women on Adiposity Indicators, Physical Capacity, and Mental Health Outcomes: A Systematic Review
Bibliographic record
Abstract
Physical activity interventions have recently become a popular strategy to help postmenopausal women prevent and manage obesity. The current systematic review evaluates the efficacy of physical activity interventions among overweight and obese postmenopausal women and sheds light on the behavioral change techniques that were employed in order to direct future research. Method. Five electronic databases were searched to identify all prospective RCT studies that examine the impact of physical activity on adiposity indicators, physical capacity, and/or mental health outcomes among healthy, sedentary overweight, and obese postmenopausal women in North America. The behavior change technique taxonomy was used to identify the various strategies applied in the programs. Results. Five RCTs met the inclusion criteria. The findings showed that adiposity indicators and physical capacity outcomes significantly improved following long-term interventions; however, mental health outcomes showed nonsignificant changes. Furthermore, 17 behavior change techniques were identified with the taxonomy across all trials. The intrapersonal-level techniques were the most common. Conclusion. Physical activity interventions had a positive effect on adiposity measures and physical capacity. Future research should focus on testing the effectiveness of physical activity interventions on mental health and incorporate strategies at the individual and environmental level to maximize the health impact on the population.
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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 | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".