Martial arts, combat sports, and mental health in adults: A systematic review
Bibliographic record
Abstract
Martial arts (MA) and combat sports (CS) are physical activities that may be associated with health-related outcomes. The aim of this systematic review was to synthesize and evaluate the available evidence on the relationship between MA and CS training and mental health of adult practitioners (≥18 years). CochraneLibrary, EBSCOhost, Web-of-Science, and Scopus databases were searched up to September 2022 for measures of self-related constructs, ill-being and well-being, cognition and brain structure/function, in adult MA/CS practitioners. Seventy cross-sectional and two longitudinal studies were retained and submitted to risk of bias assessments through an adapted version of the Cochrane Collaboration's Tool. Associations between MA/CS practice and self-related constructs were inconclusive for both consistency and strength of evidence. Limited evidence of significant associations emerged for sub-domains of ill-being (i.e., externalizing and internalizing emotion regulation), and well-being. In regard to cognitive and brain structural/functional variables, evidence of positive association with MA/CS practice was consistent with respect to perceptual and inhibition abilities but limited with respect to attention and memory. Evidence on negative associations of boxing with changes of brain structure integrity due to concussions was also inconclusive. Functional imaging techniques could shed light onto brain activation mechanisms underlying complex cognitive performance. In relation to moderators, mixed results were found for activity exposure, expertise, level of competitive engagement (which often covary with the length of training) and sex and type of MA/CS. The MA/CS' multifaceted nature may produce different, sometimes conflicting outcomes on mental health. Studies on MA/CS represent a flourishing research area needing extensive improvement in theoretical and practical approaches.
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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 | 0.005 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".