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Record W2884298535 · doi:10.1080/10872981.2018.1497374

An innovative approach to identifying learning needs for intrinsic CanMEDS roles in continuing professional development

2018· article· en· W2884298535 on OpenAlex
Meghan McConnell, Ada Gu, Aysha Arshad, Arastoo Mokhtari, Khalid Azzam

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueMedical Education Online · 2018
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsMcMaster UniversityUniversity of Ottawa
Fundersnot available
KeywordsMedical educationContinuing professional developmentProfessional developmentContinuing educationMedicinePsychologyEngineering ethicsEngineering

Abstract

fetched live from OpenAlex

CONTEXT: The CanMEDS framework promotes the development of competencies required to be an effective physician. However, it is still not well understood how to apply such frameworks to CPD contexts, particularly with respect to intrinsic competencies. OBJECTIVE: This study explores whether physician narratives around challenging cases would provide information regarding learning needs that could help guide the development of CPD activities for intrinsic CanMEDS competencies. METHODS: We surveyed medical and surgical specialists from Southern Ontario using an online survey. To assess perceived needs, participants were asked, 'Describe three CPD topic you would like to learn about in the next 12 months'. To identify learning needs that may have arisen from problems encountered in practice, participants were asked, 'Describe three challenging situations encountered in the past 12 months.' Responses to the two open-ended questions were analyzed using thematic content analysis. RESULTS: Responses were received from 411 physicians, resulting in 226 intrinsic CanMEDS codes for perceived learning needs and 210 intrinsic codes for challenges encountered in practices. Discrepancies in the frequency of intrinsic roles were observed between the two questions. Specifically, Leader (28%), Scholar (43%), and Professional (16%) roles were frequently described perceived learning needs, as opposed to challenges in practice (Leader: 3%; Scholar: 2%; and Professional: 8%. Conversely, Communicator 39%, Health Advocate 39%, and to a lesser extent Collaborator 11%) roles were frequently described in narratives surrounding challenges in practice, but appeared in <10% of descriptions of perceived learning needs (Communicator: 4%; Health Advocate 6%; Collaborator: 3%). CONCLUSION: The present study provides insight into potential learning needs associated with intrinsic CanMEDS competencies. Discrepancies in the frequency of intrinsic CanMEDS roles coded for perceived learning needs and challenges encountered in practice may provide insight into the selection and design of CPD activities.

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.

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)0.002
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.921
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
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 head0.026
GPT teacher head0.407
Teacher spread0.381 · 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