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Record W3121009546 · doi:10.1177/2374373520981484

Patient Involvement in Medical Education Research: Results From an International Survey of Medical Education Researchers

2021· article· en· W3121009546 on OpenAlexaff
Katherine Moreau, Kaylee Eady, Sarah Heath

Bibliographic record

VenueJournal of Patient Experience · 2021
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsUniversity of Ottawa
FundersAssociation for the Study of Medical Education
KeywordsFamily medicineMedicineRelevance (law)PsychologyPolitical science

Abstract

fetched live from OpenAlex

There are demands to involve patients in medical education research (MER). This study surveyed researchers to examine the extent and nature of patient involvement in MER. It obtained 283 completed surveys (response rate of 5%). Of the respondents, 153 (54.1%) indicated that they involve patients in MER. Of these respondents, 102 (66.7%) stated that patients are data sources in MER, 41 (26.8%) noted that patients are involved as advisors and/or reviewers, and/or 22 (14.4%) indicated that patients are involved as team members. These respondents reported that they involve patients to improve the relevance of their MER to patients (n = 99; 64.7%), connect MER to patient outcomes (n = 98; 64.1%), and improve the appropriateness of MER (n = 92; 60.1%). The 130 respondents who do not involve patients in MER do not involve them because they believe that their research topic(s) are irrelevant to patients (n = 68; 52.3%), they have limited resources for patient involvement (n = 40; 30.8%), and/or they do not know how to involve patients (n = 28; 21.5%). Researchers need to consider how they can conduct their MER with patients.

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)0.008
metaresearch head score (Gemma)0.013
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.260
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.013
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 science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.506
GPT teacher head0.596
Teacher spread0.090 · 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.

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

Citations3
Published2021
Admission routes1
Has abstractyes

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