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Record W4382401699 · doi:10.1177/23743735231183674

Listening to Cancer Patients’ Narratives During Residency: A Pilot Study on a Communication Skills’ Workshop Involving Patients-Partners

2023· article· en· W4382401699 on OpenAlexaffabout
Jacynthe Rivest, Philippe Karazivan, Véronique Desbeaumes Jodoin, Luigi Flora, Carole Lambert, Constantin Tranulis, Serge Daneault

Bibliographic record

VenueJournal of Patient Experience · 2023
Typearticle
Languageen
FieldMedicine
TopicEmpathy and Medical Education
Canadian institutionsInstitut Universitaire de Gériatrie de MontréalInstitut universitaire en santé mentale de MontréalUniversité de MontréalCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsActive listeningThematic analysisNarrativeEmpathyMedical educationCommunication skills trainingGeneral partnershipPsychologyQualitative researchSimulated patientCommunication skillsMedicineNursingSocial psychologySociology

Abstract

fetched live from OpenAlex

The field of cancer care still lacks best practices in communication. Few postgraduate training programs offer formal training to develop such skills. The patient partnership has been used in medical education to increase the sensitivity of the subjective experiences of patients. In our Canadian center, residents and patient-partners participated in an educational workshop on communication focusing on patient's narrative. The aim of this pilot qualitative study was to explore the experiences of participants in the workshop. Using theoretical sampling, we recruited 6 residents and 6 patient-partners. Semi-structured interviews were conducted and transcribed. A thematic analysis was performed. From analysis, 4 themes emerged: (1) lack of communication skills training; (2) barriers to effective communication in cancer care; (3) the empathy of patient-partners towards the communication challenges faced by residents; and (4) the participants' reactions to the workshop. Based on our findings, our communication skills workshop centered on narrative medicine and involving patient-partners appears feasible. Future research could study its pedagogical value and the optimal learning environment required.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.424
Threshold uncertainty score0.610

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.046
GPT teacher head0.386
Teacher spread0.340 · 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 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
Published2023
Admission routes2
Has abstractyes

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