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Record W2804252389 · doi:10.1177/2374373518765795

Patient Experience in Health Professions Curriculum Development

2018· article· en· W2804252389 on OpenAlexaff
Scott Molley, Amy Derochie, Jessica Teicher, Vibhuti Bhatt, Shara Nauth, Lynn Cockburn, Sylvia Langlois

Bibliographic record

VenueJournal of Patient Experience · 2018
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCurriculumGeneral partnershipPhenomenology (philosophy)Medical educationFocus groupHealth careCurriculum developmentHealth professionsPedagogyPsychologyMedicineNursingSociologyPolitical science

Abstract

fetched live from OpenAlex

To enhance student learning, many health profession programs are embracing involvement of patients in their curricula, yet little is known about the impact of such an experience on patients. OBJECTIVE: To understand the experiences of patients who contributed to the creation of a Verbatim Reader's Theater used in health professions curriculum. METHODS: A semi-structured interview was conducted with a focus group of 3 patients who participated in curriculum development. The interview was recorded, transcribed verbatim, and analyzed for themes using van Manen approach to hermeneutic phenomenology. RESULTS: Five themes emerged: (1) contextualizing contribution, (2) addressing expectations, (3) changing health-care service delivery, (4) sharing common experiences, and (5) coordinating participation. CONCLUSION: Patients had a positive experience contributing to curriculum development and found meaning in sharing their lived experience to shape the values of future clinicians. Strategies to promote continued success in partnership between patients and health professional curriculum developers include clear communication about the project's direction and early discussion of patient role and expectations.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.391
Threshold uncertainty score0.948

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.183
GPT teacher head0.470
Teacher spread0.287 · 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

Citations17
Published2018
Admission routes1
Has abstractyes

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