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Enregistrement W6982703573

Is Training in Martial Arts Beneficial to One's Health? The Devil is in the Detail

2022· dissertation· en· W6982703573 sur OpenAlexaboutno aff

Notice bibliographique

RevueUniversity Library (University of Saskatchewan) · 2022
Typedissertation
Langueen
DomaineEnvironmental Science
ThématiqueAmerican Environmental and Regional History
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMartial artsMental healthPsychological interventionPsychosocialPersonalityExploratory research
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

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.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,008
score de la tête « metaresearch » (Gemma)0,026
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,012
Score d'incertitude au seuil0,041

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0080,026
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,002
Bibliométrie0,0010,001
Études des sciences et des technologies0,0010,002
Communication savante0,0030,002
Science ouverte0,0010,001
Intégrité de la recherche0,0010,003
Charge utile insuffisante (le modèle a refusé de juger)0,0070,001

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,013
Tête enseignante GPT0,183
Écart entre enseignants0,170 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2022
Routes d'admission1
Résumé présentoui

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