Alexithymia And Buprenorphine Addiction
Bibliographic record
Abstract
Background and Aims:Itu2019s currently admitted that vulnerability to substance use disorders results from the interaction of several factors related to the product , the environment or to the individual. Our aim was to study the alexithymia as a personality dimension among subjects addicted to buprenorphine (Subutexu00ae) compared to controls .Methods:We conducted a cross sectional comparative study including 50 patients with addiction to buprenorphine (Subutexu00ae) and 50 witnesses. We collected sociodemographic informations, history and addictive course using a data record. We estimated alexithymia with the Toronto Alexithymia Scale (TAS-20).Results:Mean score of alexithymia on TAS-20 with users of buprenorphine (Subutexu00ae) was significantly higher than among the control population: 63,42 versus 53,54 (p<0,001). Alexithymia was strongly associated with buprenorphine addiction (54% versus 24% p= 0,002). The unemployment , the family judicial history ,the personal psychiatric history ,the poly drug use and the high level of seeking sensation were identified as risk factors of addiction to buprenorphine (Subutexu00ae). Conclusions:The good knowledge of buprenorphine addictionu2019s risk factors is absolutely crucial. It allows prevention initiatives targeted for these contexts of vulnerability, thanks to the implementation of an adapted and early psychosocial support.
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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 | 0.000 | 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".