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Record W3033696991 · doi:10.1097/njh.0000000000000657

The Design and Impact of an Interprofessional Education Event Among Pharmacy and Nursing Students in Palliative Care—RnRx

2020· article· en· W3033696991 on OpenAlexaff
Sherilyn K. D. Houle, Elaine Lillie, Cynthia L. Richard, Jenn Slivecka, Andrea Miller

Bibliographic record

VenueJournal of Hospice and Palliative Nursing · 2020
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsUniversity of WaterlooConestoga College
Fundersnot available
KeywordsPalliative carePharmacyNursingCompetence (human resources)Interprofessional educationPsychologyMedical educationMedicineFamily medicineHealth care

Abstract

fetched live from OpenAlex

Nearly all reports of interprofessional education (IPE) in palliative care have excluded pharmacy students. This article describes an IPE event between pharmacy and nursing students and assesses its impact on IPE competencies. Second-year nursing students and third-year pharmacy students participated in an evening-long event, focused on a married couple who each require palliative care-one for end-of-life planning and one for chronic disease progression. The impact of the event was assessed using the Interprofessional Collaborative Competency Attainment Scale (ICCAS) and qualitative feedback. Two hundred nine (96.7%) completed the ICCAS, and 16 of the 20 statements of the ICCAS showed large positive effect sizes (Cohen d ≥ 0.8), with the remaining 4 showing moderate positive effect sizes (Cohen d ≥ 0.5). The greatest effect sizes were related to improved awareness of complementary skillsets and knowledge between the professions. Addressing team conflict and including the patient/family in decision-making showed the least improvement. While ongoing interactions are ideal for the development of skills related to conflict and team development, this article demonstrates that even a 1-time activity can have an impact on students' interprofessional care competence.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.117
Threshold uncertainty score0.409

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.057
GPT teacher head0.531
Teacher spread0.474 · 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

Citations7
Published2020
Admission routes1
Has abstractyes

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