Social Interactions While Grieving Suicide Loss: A Qualitative Review of 58 Studies
Bibliographic record
Abstract
The effects of suicide are both widespread and long-lasting in the lives of those closest to the deceased. According to the World Health Organization (WHO), suicide is the third leading cause of death in adolescents. Some research has shown that families who lose someone to suicide are at a higher risk of complicated grief compared to those bereaving from other types of losses. These risks may be emphasized given the socio-cultural context surrounding suicide that may problematize the grieving process. In this review, we analyzed 58 qualitative studies describing the experiences of family who lost someone to suicide. We discuss how negative social interactions due to cultural views towards suicide impacted their grieving process. We provide an integrative interpretation of the experiences of family who lost someone to suicide across the following themes: social withdrawal, family communication approaches, role change, cultural attitudes, the role of professional support, interactions with health care providers, and interactions with religious institutions. We examine these findings using the Assumptive World Theory which proposes that humans seek preservation of their reality by using their perceptions of the past to establish expectations for the future. We find that suicide loss is an experience that challenges people's assumptive worlds; suicide loss can be an unexpected trauma that can have a “shock effect” on the assumptive worlds of the bereaved. The assumptive worlds of relatives grieving suicide loss face unique challenges compared to other forms of bereavement because of ambiguity in social norms surrounding suicide that influence interactions.
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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 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".