Bibliographic record
Abstract
BACKGROUND: Several authors have observed a therapeutic impact of the psychological autopsy on the interviewee, although they do not explicitly define what aspects of the process were helpful. AIMS: This article aims to identify these therapeutic effects and to discuss their potential impact on participants' narratives. METHODS: This article derives from 35 psychological autopsy interviews that were conducted to better understand adolescent and young adult suicide. Interviews lasted approximately 6 to 8 h each and consisted of both a battery of questionnaires and open-ended questions. They were mostly conducted with the families of the deceased, including parents and siblings, and on occasion were done with a single family member or friend. The time elapsed since the suicide ranged from 6 to 18 months. RESULTS: Psychological autopsies were helpful to interviewees in allowing them to find meaning in the suicide, to find purpose through their altruistic participation, to obtain psychological support, to experience connectedness with others, to accept the loss as real, and to gain insight into their functioning. Negative reactions to the interviews, albeit uncommon, are also briefly described. CONCLUSIONS: We recommend that interviewers receive preparatory training and ongoing supervision while conducting interviews, to assure a reflective and professional stance.
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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 | 0.004 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".