The Mediating Roles of Self-compassion and Emotion Regulation in the Relationship among Alexithymia, Gambling Frequency, Risky Decision-Making, and Gambling Severity in Online Gamblers
Bibliographic record
Abstract
Background: The research literature about the relationship between alexithymia, risky decision-making, and gambling severity has been contradictory and limited. Besides, there is no study on the mediating roles of self-compassion and emotion regulation in online gambling. Moreover, the role of these mediators in gambling frequency has not been studied. Thus, the present study aimed to investigate the relationship between alexithymia, risky decision-making, and gambling frequency by considering the mediating role of self-compassion and emotion regulation in online gamblers. Methods: A total of 319 Iranians who gambled online at least once a week in the past three months were investigated using an online survey including Farsi Toronto Alexithymia Scale-20 (FTAS-20), Difficulties in Emotion Regulation Scale (DERS), and Gambling Disorder Screening Questionnaire-Persian (GDSQ-P). Statistical analyses were conducted by SPSS 26.0 for Windows. The relationships between the variables were analyzed using correlation analysis. In cases where significant relationships were observed, the hypotheses of the regression model were tested. Findings: =0.293). Conclusion: Alexithymia had both a direct and indirect relationship with gambling severity through the mediating roles of emotion regulation and self-compassion. Moreover, alexithymia was significantly associated with risky decision-making and gambling frequency, through the mediating role of difficulties in emotion regulation, both directly and indirectly.
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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 | 0.002 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".