Alexithymia, Dissociation, and Family Functioning in a Sample of Online Gamblers: A Moderated Mediation Study
Bibliographic record
Abstract
The diffusion of the internet and technological progress have made gambling on online platforms possible, also making it more anonymous, convenient, and available, increasing the risk of pathological outcomes for vulnerable individuals. Given this context, the present study explores the role of some protective and risk factors for problematic gambling in online gamblers by focusing on the interaction between alexithymia, dissociation, and family functioning. A sample of 193 online gamblers (Mage = 28.8 years, SD = 10.59; 17% females, 83% males) completed the South Oaks Gambling Screen, Twenty-Items Toronto Alexithymia Scale, Dissociative Experience Scale-II, and Family Adaptability and Cohesion Evaluation Scales-IV through an online survey. MANOVA, ANOVA and moderated mediation analyses were carried out to analyse the data. Significant differences in cohesive family functioning, alexithymia and dissociation have been found between online gamblers with problematic, at-risk or absent levels of gambling disease. Furthermore, the results showed a significant and positive association between alexithymia and problematic online gambling, partially mediated by dissociation, with the moderation of cohesive family functioning. Such data may have relevant clinical implications, highlighting the interaction of some core personal and environmental variables that may be involved in the etiology of online pathological gambling and could be kept in mind to tailor preventive interventions.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".