The association of physical activity and depression in Type 2 diabetes
Bibliographic record
Abstract
AIMS: Physical inactivity and depressed mood are both associated with a higher likelihood of diabetes-related complications; the association between physical activity and depressed mood in Type 2 diabetes has not been reviewed previously. We have reviewed (i) the strength of this association and (ii) the impact of depression-specific management and physical activity interventions on mood and activity levels in overweight adults with Type 2 diabetes. METHODS: Studies published between January 1996 and September 2007 were identified (OVID-MEDLINE, PSYCH-INFO and EMBASE) using pertinent search terms (keyword/title). RESULTS: Of the 12 studies included (10 cross-sectional, two trials), most employed a standardized questionnaire for depressed mood but only one item for physical activity. In adults with Type 2 diabetes, the inactive are 1.72 to 1.75 times more likely to be depressed than the more active; the depressed are 1.22 to 1.9 times more likely to be physically inactive than the non-depressed. Two randomized trials demonstrated that a depression management programme improved mood, but only one demonstrated increased physical activity. CONCLUSIONS: Studies to date suggest an association between depressed mood and physical inactivity in adults with Type 2 diabetes, although objective measures of physical activity have not been employed. Depression-specific management may improve mood and possibly activity. A trial comparing the impact of depression-specific management compared with exercise intervention on depressed mood and activity in Type 2 diabetes is justified.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".