I'm Not That Person: A Qualitative Study of Moral Injury in Forensic Psychiatric Patients
Bibliographic record
Abstract
Few studies have examined how committing criminal acts of violence impacts the lives of perpetrators who were mentally ill at the time of offence and in which the act itself reflects behaviour that is uncharacteristic of the individual. Theoretical accounts and clinical reports describe a phenomenon termed moral injury, which profiles the deleterious emotional effects that can arise from actions that transgress moral beliefs and expectations. Shame, guilt, spiritual/existential conflict, and loss of trust are considered to be core symptoms of moral injury with growing empirical studies which examine moral injury in military and public safety worker samples. The extent to which these kinds of moral injury phenomena might be evident among mentally ill perpetrators was explored using a qualitative-methods approach in a sample of 19 adult participants hospitalized in a Canadian forensic programme inpatient service. The sample consisted of 13 male and 6 female patients, with a mean age of 36.2 years ( SD = 10.8), and the majority diagnosed with schizophrenia or schizoaffective disorder. A qualitative interview was conducted where participants were asked to describe feelings about the index offence, the effect it has had on their well-being, and how they have coped with having committed the offence. Using a reflexive thematic analysis process, 5 themes and 23 subthemes were generated that relate to the various resultant impacts. The five themes which emerged were (1) Living with the Emotional Aftermath; (2) Trying to Make Sense and Coming to Terms; (3) My Eyes Have Opened; (4) Facing the Music; and (5) Moving On. The findings are discussed in terms of their implications for understanding forensic inpatients who may be attempting to come to terms with violence they committed while mentally ill and for informing moral injury intervention strategies which might be adapted for forensic mental health services and public health recidivism prevention programmes.
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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 | 0.018 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.023 | 0.020 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 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".