A family history of alcoholism relates to alexithymia in substance use disorder patients
Bibliographic record
Abstract
OBJECTIVES: Previous research identified alexithymia as a potential risk factor for substance use disorders (SUD). More insight into the relation between alexithymia and SUD is needed in order to treat SUD effectively. Therefore, we investigated whether a familial vulnerability to alcoholism relates to the presence and severity of alexithymia in SUD patients. METHOD: Hospitalized, abstinent SUD-patients (n=187), were assessed with the Toronto Alexithymia Scale (TAS-20) and Addiction Severity Index (EuropASI). A maternal, paternal, and total continuous measure of the Family History of Alcohol (FHA) was developed. Kruskal-Wallis tests and Spearman correlations were used to relate the composite scores of FHA to alexithymia as a categorical and continuous measure. Multivariate regression models were performed to control for the effects of confounders on the relation between FHA and alexithymia. RESULTS: Compared to moderate (33%) and low (17%) alexithymic SUD-patients, high alexithymic (50%) patients were more likely to have fathers with alcohol problems (P=0.004). Such a difference was not found for mothers with alcohol problems. The composite FHA-score was significantly associated with alexithymia (Rs=.19, P=0.01). However, only a paternal FHA, independent from disturbed family functioning, related to the degree of alexithymia (beta=.13, P=0.06), especially to the Difficulty Identifying Feelings as measured by the TAS-20 (beta=.16, P=0.02). CONCLUSIONS: The relation between a paternal FHA and a higher degree of alexithymia in SUD-patients suggests that alexithymia could mediate the familiality of alcoholism or SUD in the paternal line.
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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 | 0.000 | 0.000 |
| 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) | 0.004 | 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".