Is Training in Martial Arts Beneficial to One's Health? The Devil is in the Detail
Bibliographic record
Abstract
The World Bank and World Health Organization have noted that due to the significant economic, social, and healthcare costs of mental disorders, governments should direct more support towards developing or strengthening programs that promote mental health (Mnookin et al., 2016). Martial arts (MA) may be a valuable and holistic resource for such programs, as they are believed to be beneficial for mental health and have been recommended by some researchers as potential adjuncts to traditional psychotherapy, given their psychotherapeutic components (Draxler et al., 2011; Gleser et al., 1992; Weiser et al., 1995). Although the literature contains conflicting findings, martial arts have already been incorporated into mental health programs and interventions for youth (Harwood et al., 2017; Theeboom & De Knop, 1999; Twemlow et al., 2008), veterans (Weiss et al., 2017; Winsmann, 2005), and the elderly (Lee et al., 2010; Li et al., 2014). \nIn addition, while mixed martial arts (MMA) has grown in popularity in the Western world over the previous three decades (Dixon, 2015), relatively little is known about mental health associations with MMA training, particularly in Canada. This dissertation aimed to explore the relations between MA training, indicators of mental health, and personality variables. More specifically, Study 1, a meta-analysis was used to examine what conclusions could be drawn from the existing literature about the relations between MA training and psychosocial variables across the lifespan. Study 2, an exploratory correlational study, was intended to explore what correlates of mental health and personality are associated with MMA training among Canadians. Due to relatively low recruitment of MMA participants, the focus shifted from MMAP to a broader MAP group (which included MMAP) to test substantive hypotheses. \nIn Study 1, MA training outcomes were examined in pre-post studies, and those outcomes included anger, anxiety, depression, externalizing behaviors, happiness, mental health, self-efficacy, and self-esteem. The magnitude of effect sizes ranged from small to large. Differences in effect size magnitude varied per correlate by martial art discipline, with some martial arts being associated with greater differences in anger, anxiety, and depression. \nIn Study 2, results were a combination of expected and unexpected associations between MA training, personality, and indicators of mental health. Martial arts training was negatively associated with neuroticism and hostility, and positively associated with self-esteem. MA/sport involvement was negatively associated with neuroticism and hostility while it was positively associated with physical aggression. Frequency of MA training per week was negatively associated with self-esteem. Principal components analysis (PCA) with varimax rotation was conducted on a Martial Arts Experience Questionnaire (MAEQ) and a two-component solution emerged. The two components were labelled Integrity of MA training and Tradition of MA training based on respective item content. Integrity of MA training was positively associated with self-esteem, agreeableness, openness, conscientiousness, self-efficacy/will-power, and social support and negatively associated with neuroticism and hostility. Correlations between Tradition of MA training and all the criterion variables were non-significant. \nMultivariate regressions analyses were conducted with select MA variables and select criterion variables based on significant correlations that were observed in earlier analyses. The findings of the three regression models are examined. Implications, limitations, and future directions are discussed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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 teacher head, 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".