Community-Based Physical Activity Interventions for Treatment of Type 2 Diabetes: A Systematic Review with Meta-Analysis
Bibliographic record
Abstract
Evidence suggests engaging in regular physical activity (PA) can have beneficial outcomes for adults with type 2 diabetes (TD2), including weight loss, reduction of medication usage and improvements in hemoglobin A1c (HbA1c)/fasting glucose. While a number of clinical-based PA interventions exist, community-based approaches are limited. The objective of this study is to conduct a systematic review with meta-analysis to assess the effectiveness of community-based PA interventions for the treatment of TD2 in adult populations. A search of peer-reviewed publications from 2002 to June 2012 was conducted across several electronic databases to identify interventions evaluated in community settings. Twenty-two studies were identified, and 11 studies reporting HbA1c as an outcome measure were pooled in the meta-analysis. Risk of bias assessment was also conducted. The findings demonstrate community-based PA interventions can be effective in producing increases in PA. Meta-analysis revealed a lowering of HbA1c levels by -0.32% [95% CI -0.65, 0.01], which approached statistical significance (p < 0.06). Our findings can guide future PA community-based interventions in adult populations diagnosed with TD2.
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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 | 0.011 | 0.029 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.027 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".