Surviving families: experiences of losing a family member to suicide
Bibliographic record
Abstract
to identify the interactional processes that allow surviving families to cope with the death by suicide of one of their members, to restructure themselves as a unit and transform the experience into a learning experience. a qualitative, exploratory study, guided by the concept of Family Resilience, in which eight families, who experienced the suicide of one of their members participated. Data were collected through semi-structured interviews and the data were submitted to thematic analysis. the results were organized into four thematic groups and revealed grief, despair, and perplexity of family members who could not understand the reasons for such a radical act; the feelings of pain due to the loss, overlapped with anger, relief and guilt. Blame was shared with other people and the social and health services; and the lessons that the experience provides. nurses and other healthcare professionals can help surviving families to restructure themselves after the suicide of one of their members, implementing care actions based on repeated assessments of the repercussions of suicide on the family as a whole and on its members individually; identifying the most compromised dimensions of family life; individual and family needs; and family resilience processes.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.005 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| 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".