Assessment of addictive behavior in patients with schizophrenia
Bibliographic record
Abstract
INTRODUCTION: Schizophrenia, a chronic and complex psychiatric pathology, can be isolated. However, it may have other comorbidities and thus be accompanied by addictive behaviors complicating their management. OBJECTIVES: to estimate the prevalence and identify the characteristics of addictive behavior among patients with schizophrenia. METHODS: A retrospective study of 151 patients with schizophrenia and hospitalized in the psychiatry department of the Taher Sfar university hospital in Mahdia from January 2017 to December 2021. RESULTS: The mean age of the patients was 39.8 ± 11.23 years with a predominance of age group 36-45 years (38.4%). All of the patients were males . Three quarters of patients (75.5%) were users of psychoactive substances (PSA): nearly three quarters (72.8%) dependent on tobacco, more than a third (39.7%) dependent on alcohol, more a quarter (29.1%) dependent on cannabis and almost a quarter (26.5%) dependent on other SPA. In more than half of the cases (54.4%), the age at which SPA consumption began was between 16 and 25. SPA use preceded the onset of schizophrenia in 62.3% of case. The relationship with the entourage was marked by hetero-aggressiveness in 77.5% of the patients, a withdrawal from the entourage for 16.6% of the patients and a conflict for 5.3% of the patients. The impact on the relationship with oneself was marked by self-aggressiveness in 18.5% of patients. Regarding professional impact, three quarters of patients (76.1%) had to stop working. The majority of patients (84.1%) continued their usual treatment, while 15.2% of patients stopped it. In only one patient increased doses were necessary. CONCLUSIONS: Subjects suffering from schizophrenia are particularly vulnerable to addictions, mainly to tobacco and alcohol. They are therefore a group at greater risk of harmful effects of psychoactive substances and at worsening the clinical course of their psychiatric illness. Screening and treatment measures their addictive behaviors early on, even before schizophrenia sets in, should be offered. DISCLOSURE OF INTEREST: None Declared
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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".