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Record W4388575726 · doi:10.1080/15524256.2023.2272590

Nonphysical Suffering: An Under-Resourced and Key Role for Hospice and Palliative Care Social Workers

2023· article· en· W4388575726 on OpenAlexaffabout
Maxxine Rattner, Cheryl-Anne Cait

Bibliographic record

VenueJournal of Social Work in End-of-Life & Palliative Care · 2023
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsHospice carePalliative careNursingKey (lock)Social workMedicinePsychologyPolitical scienceLaw

Abstract

fetched live from OpenAlex

This article highlights recent research findings that have significance for hospice and palliative care social work in Canada, and for the field of hospice and palliative care more broadly. A 2020 discourse analysis study examined the experiences of 24 interdisciplinary palliative care clinicians across Canada in their work with patients' nonphysical suffering. Nonphysical suffering is suffering that may be emotional, psychological, social, spiritual and/or existential in nature. The study found an absence of specialist social workers on hospice and palliative care teams or limited time for specialist social workers to address patients' nonphysical suffering due to high caseloads and complex practical needs. While the study recognizes social workers have expertise in supporting patients' nonphysical suffering, a competency and skill that has not been sufficiently captured in the existing literature, the systemic barriers they face in providing care may leave patients' needs unmet. The study also highlights the unique pressure social workers may feel to relieve patients' nonphysical suffering due to the psychosocial focus of their role. The need for specialist social workers to be included and adequately resourced on hospice and palliative care teams across diverse settings in Canada is evident.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.434
Threshold uncertainty score0.863

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0200.015
Scholarly communication0.0080.005
Open science0.0020.014
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0060.000

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.

Opus teacher head0.102
GPT teacher head0.413
Teacher spread0.311 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2023
Admission routes2
Has abstractyes

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