A Relational Analysis of End-of-Life Existential Suffering: A Qualitative Study
Bibliographic record
Abstract
The Royal Society of Canada EOL care panel identified that there is a considerable unmet need for psychosocial support for dying persons and their family members. Canadian studies have also demonstrated that dying persons perceive psychological interventions and communication to specifically support ES as lacking within EOL care. The overall objective to this qualitative study was to understand how ES is constructed and understood within the EOL care context. In order to answer my line of inquiry, I sought to understand how ES is constructed and understood within the EOL care context. I also sought to do this through the examination of the inter-subjective understandings of ES by EOL care clinicians through their professional [or personal] relationships and the broader context in which EOL care clinicians’ practice influences the construction and management of EOL ES. METHODS: Using a voice-centred relational method, I analysed the transcribed text from 16 EOL care clinicians (physicians, nurses and a pharmacist). These clinicians provided EOL care in a hospital, hospice or home care setting across the Greater Toronto Area (GTA). RESULTS: Study participants described EOL ES as inherently relational from both an intra-personal relationship and inter-personal relationships perspective. Relational remediation tools are being used to optimally manage EOL ES at the clinical level; however, institutional arrangements, such as the inequitable access to comprehensive palliative care services and societal forces, such as the legalization of MAID shape relations of EOL ES. CONCLUSION:The optimal management to EOL ES requires a relational remediation at the clinical, institutional and societal levels. Some key examples include equitable access to palliative care, addressing Western society’s death denying culture and promoting a relational view of autonomy for dying persons and their personal caregivers.
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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 | 0.022 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.016 | 0.018 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".