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Record W17902780 · doi:10.1177/082585970702300404

Sustainable Practice Improvements: Impact of the Comprehensive Advanced Palliative Care Education (CAPCE) Program

2007· article· en· W17902780 on OpenAlexaff
Diane Harris, Loretta M. Hillier, Nancy Keat

Bibliographic record

VenueJournal of Palliative Care · 2007
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsMiddlesex London Health UnitSt Joseph's Health CareLawson Health Research InstituteGolder Associates (Canada)
Fundersnot available
KeywordsPalliative carePrioritizationNursingMedicineWork (physics)Clinical PracticePsychologyMedical educationBusinessProcess management

Abstract

fetched live from OpenAlex

This paper describes an education program designed to improve palliative care practice through the development of workplace hospice palliative care resources (PCRs), and its impact on knowledge transfer and longer-term changes to clinical practice. Evaluation methods included pre- and post-program questionnaires, and a survey of learners' (n=301) perceptions of program learning strategies. Interviews (n=21) were conducted with a purposeful sample of PCRs and representatives from their work sites. Ratings of the sessions indicated that they were relevant to learners' clinical practice. At follow up, the majority of learners (83%) continued to serve as PCRs. Many positive effects were identified, including enhanced pain and symptom management, staff education, and development of care policies and guidelines. Management support, particularly the prioritization of palliative care and staff development, were factors facilitating sustained implementation. These findings highlight the importance of multimodal learning strategies and supportive work environments in the development of PCRs to enhance palliative care practice.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.419
Threshold uncertainty score0.867

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.059
GPT teacher head0.480
Teacher spread0.422 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations9
Published2007
Admission routes1
Has abstractyes

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