The Relationship Between Alexithymia, Impulsivity, and Aggression in Mixed Martial Arts Athletes
Bibliographic record
Abstract
This study investigated the relationships among alexithymia, impulsivity, and aggression in mixed martial arts (MMA) athletes. Participants (N = 60, 51 men, and 9 women) were recruited from MMA clubs and training centers in Lebanon. They completed self-report measures including the Toronto Alexithymia Scale-20 (TAS-20) to assess alexithymia, the Barratt Impulsiveness Scale (BIS-11) to measure impulsivity, and the Buss-Perry Aggression Scale short form (BPAS-SF) to evaluate aggression tendencies. Results indicated that alexithymia was positively correlated with impulsivity (attentional, r = 0.41, and p < 0.01; motor, r = 0.32, and p < 0.05), aggression (r = 0.49 and p < 0.001), and its various forms of aggression (physical, verbal, anger, and hostility). Mediation analyses showed that attentional impulsivity significantly mediated the link between alexithymia and aggression (β = 0.10 and 95% CI [0.02, 0.22]), whereas motor impulsivity accounted for a smaller portion of the effect (β = 0.08 and 95% CI [0.00, 0.22]). The direct effect remained significant (β = 0.28 and 95% CI [0.03, 0.52]), indicating partial mediation. These findings underscore the importance of emotional and behavioral regulation in competitive sports contexts, highlighting potential implications for athlete development programs.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".