Characteristics and impact of physical activity interventions during substance use disorder treatment excluding tobacco: A systematic review
Bibliographic record
Abstract
Substance use disorder is a worldwide issue that entails negative health and physical activity is a promising complementary therapy for alleviating the consequences. The objective of this reviews is to characterize physical activity interventions offered in the literature and explore their effects during treatment for people with substance use disorders with excluding studies focusing only on tobacco use. A systematic search of seven databases on articles including a physical activity intervention during a treatment for substance use disorder was done and an examination of the presence of bias was performed. A total of 43 articles including 3135 participants were identified. Most studies were randomized controlled trial (81%), followed by pre-post design (14%) and cohort studies (5%). The most common physical activity intervention identified was of moderate intensity, 3 times per week (≈ 1 hour) for 13 weeks. Cessation/reduction of substance use was the most studied outcome (21 studies, 49%), and 75% showed a decrease in substance use following physical activity intervention. Aerobic capacity was the second most studied effect (14 studies, 33%), with more than 71% of studies showing improvement. Twelve studies (28%) reported a decrease of depressive symptoms. Physical activity interventions in a treatment for substance use disorder seem to be a promising, but more methodologically rigorous scientific studies are needed.
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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 | 0.006 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.009 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| 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".