ALEXITHYMIA AND IMPULSIVITY IN PATIENTS WITH SUBSTANCE USE DISORDERS
Bibliographic record
Abstract
INTRODUCTION Impulsivity and Alexithymia are related to substance use disorders (SUD) as risk factors (1,2), several cognitive skills are implied in both traits (1,2). However, few researches are published on their mutual relationship in SUD patients. OBJECTIVES To describe the correlations between alexithymia and impulsivity in SUD patients. METHODS Patients with SUD (according to DSM-5) were evaluated with invited to participate in an addiction treatment Ad-Hoc questionnaire, Toronto Alexithymia Scale-20 (TAS-20), Barratt impulsivity scales (BIS-11) and Dickamn functional dysfunctional impulsivity scale (FIDI) were performed in all patients. RESULTS 93 patients completed the full evaluation, the total score of TAS-20 was significantly related to total scores of BIS-11 and FIDI. Analyzing subscales, Difficulty Describing Feelings subscale describe better the association between total TAS-20 scores and impulsivity, and it may be the link between dysfunctional impulsivity and alexithymia. Externally-Oriented Thinking subscale was fewer correlated to any BIS-11 factor compared to the other subscales of TAS-20. Interestingly, cognitive impulsivity is not related to total TAS-20 scores and the TAS-20 subscales. CONCLUSIONS Alexythimia and impulsivity are related in SUD (especially some subfactors are better associated), and hence these relations should be considered when conducting therapeutic approaches. REFERENCIAS 1. Morie KP, Yip SW, Nich C, Hunkele K, Carroll KM, Potenza MN. Alexithymia and Addiction: A Review and Preliminary Data Suggesting Neurobiological Links to Reward/Loss Processing. Curr Addict Rep. 2016;3(2):239-248 2. Shishido H, Gaher RM, Simons JS. I don't know how I feel, therefore I act: alexithymia, urgency, and alcohol problems. Addict Behav. 2013;38(4):2014-7. doi: 10.1016/j.addbeh.2012.12.014.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".