Attitudes of Forensic Psychiatric Staff to Self-Harm Behaviors of Their Female Patients
Bibliographic record
Abstract
The management of self-harm presents a major challenge in correctional and forensic psychiatric services, especially for women offenders, among whom it is reported to be highly prevalent. Even though staff play an important role in managing self-harm, few studies have evaluated their attitudes to this behavior. In order to understand the attitudes of staff to women’s self-harm, 16 staff members working in a forensic psychiatric hospital participated in semi-structured interviews designed to explore their experience in depth. The staff members presented, on the one hand, positive attitudes expressed as empathy, sensitivity, and positive feelings but, on the other hand, negative attitudes expressed in the form of preconceived ideas and negative feelings. Differences were also noted in their perceptions of the seriousness of self-harm. Self-harm behaviors seem to have a considerable impact not only on caregivers, but also on the entire care unit. Our study supports the importance of both professional support and training for staff who are exposed to this type of behavior. Clinical and research implications are discussed.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".