Psychiatric disorders and management of sexual offenders in the prison psychiatric consultation unit of Marseille
Bibliographic record
Abstract
Since 2017, complaints of sexual violence have increased in France. At the same time, the management of sexual offenders has been at the center of international public health policies. The prevalence of mental disorders among sexual offenders is an essential field of research. There are some published studies on the prevalence of psychiatric disorders in sexual offenders in detention, but there are few recent published studies among French individuals who were detained. Our objectives were to determine the prevalence of psychiatric disorders among persons detained for sexual offenses and the level of care received according to their diagnosis. For this purpose, we carried out a retrospective observational study from January 2017 to October 2021 of all adult sexual offenders, whether accused or convicted, who were seen in the psychiatric consultation unit of Les Baumettes prison, Marseille, France. The primary outcome measure was the psychiatric diagnosis entered in the medical records. One hundred forty-two patients were included in analysis. All patients were men, and the majority (n = 97, 68.3%) of these patients presented with at least one psychiatric disorder, principally a personality disorder (31.7%). 10.6% presented with a schizophrenic disorder, 4.9% a bipolar disorder, 3.5% a depressive disorder, 5.6% pedophilic paraphilia, and 25.4% an addictive disorder. Their management and comorbid addictions were analyzed in subgroups for each psychiatric disorder. Patients appeared to receive an appropriate level of care for their diagnosed disorder. It seems important to develop structured assessment of recidivism risk for better management of sexual offenders.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".