Working with prisoners who self‐harm: A qualitative study on stress, denial of weakness, and encouraging resilience in a sample of correctional staff
Bibliographic record
Abstract
BACKGROUND: Rates of self-harm are high among prisoners. Most research focuses on the vulnerable prisoner, and there is little on the impact of these behaviours on staff. AIMS: To investigate staff perceptions of self-harming behaviours by prisoners, including their views on its causes, manifestation, prevention in institutions, and impact on them. METHODS: Semistructured interviews were conducted with 20 administrative and 21 therapeutic prison staff who are responsible in various ways for prisoners who self-harm. Their narratives were explored using interpretative phenomenological analysis. RESULTS: Despite prison staff being experienced with prisoners' self-harming behaviours, including severe acts of self-harm, they were apt to reject any negative impact on their own mental health or well-being. This denial of negative impact was accompanied by perceptions of the inmate's actions being manipulative and attention seeking. Prison staff also perceived institutional responses to self-harming behaviours by prisoners as being mixed, ambiguous, or showing preference for relying on existing suicide protocols rather than task-specific guidance. CONCLUSIONS: Although staff gave explanations of prisoner self-harm in terms of "manipulative behaviour," prisoners' self-harm is, in fact, complex, challenging, and often severe. This staff perception may reflect denial of impact of often distressing behaviours on them personally and their own coping mechanisms. This could be feeding in to a perceived lack of clear and effective institutional responses to the self-harm, so further research is needed to determine how staff could broaden their views, and respond more effectively to prisoners. Psychologically informed group work and/or reflective practice are among the candidates for such help for staff.
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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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.010 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| 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".