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Record W4306965208 · doi:10.1177/08258597221134865

Mental Healthcare Providers Understanding and Experiences of Palliative Care: A Qualitative Analysis

2022· article· en· W4306965208 on OpenAlexaff
Tanya Park, Lydia Mutoni, Ramya Sridhar, Bernadette Workun

Bibliographic record

VenueJournal of Palliative Care · 2022
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsAlberta Health ServicesUniversity of Alberta
Fundersnot available
KeywordsThematic analysisPalliative careMental healthReflexivityQualitative researchNursingHealth carePsychologyMedicinePsychiatrySociology

Abstract

fetched live from OpenAlex

Objective: To understand the experiences and perceptions of mental health providers about palliative care. Background: Little attention is paid to the experience of people with chronic persistent mental illness (CPMI) and life-threatening diseases and how their dying experience might differ from those without a CPMI. Methods: Interpretive description informed the project. Sixteen mental health care providers were interviewed using a semi-structured interview template. The interviews were recorded, transcribed, and analyzed using a reflexive, inductive-deductive thematic approach, guided by Braun & Clarke's framework for thematic analysis. Results: Four themes were identified from the data: intersectionality, limited collaboration, misconceptions about palliative care, and relationships. Mental health providers identified gaps in their knowledge of palliative care practices along with their knowledge of death and dying.

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)0.012
metaresearch head score (Gemma)0.022
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 score0.012
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.022
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0060.006
Scholarly communication0.0040.003
Open science0.0010.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.232
GPT teacher head0.498
Teacher spread0.266 · 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

Citations4
Published2022
Admission routes1
Has abstractyes

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