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Record W7007939875

THE ASSOCIATION BETWEEN CANMEDS ROLE-SPECIFIC IMPLICIT THEORIES OF INTELLIGENCE AND PLANNING FOR RESIDENT REMEDIATION

2019· dissertation· en· W7007939875 on OpenAlexaboutno aff

Bibliographic record

VenueMacSphere (McMaster University) · 2019
Typedissertation
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsnot available
Fundersnot available
KeywordsCompetence (human resources)Association (psychology)Context (archaeology)Implicit personality theoryMedical schoolImplicit-association test
DOInot available

Abstract

fetched live from OpenAlex

This thesis explores two components of motivational theory that have been unexplored in the context of medical education. First, we applied the notion of motivational dimensionality to physician competence. Previous research on implicit theories of intelligence demonstrated that people hold different beliefs regarding different aspects of intelligence/ability, instead of a global mindset. We applied this to the CanMEDS Framework and showed that respondents held different theories of intelligence regarding the Professional and Medical Expert Role. Second, we aimed to determine if one’s implicit theories are related to their decisions around remediation planning. We hypothesized that respondents would view remediation as either an opportunity for a resident to develop competence or as an opportunity for them to demonstrate their fundamental lack of ability. Here, we showed that one’s own beliefs, or theories of intelligence, not only mediate how they behave in the training environment, but also mediate how they manage others. In the first of two studies, we measured implicit theories amongst residents, faculty, and experts in medical education at McMaster University regarding both the Professional and Medical Expert CanMEDS Roles and asked them how much effort would be required for a resident to remediate performance deficits in either Role. The second study took place at University of Toronto and involved a similar design. Residents and faculty in the Department of Obstetrics and Gynaecology were invited to participate in a study that measured implicit theories of intelligence and then asked respondents to develop remediation plans for residents described in case vignettes. Drawing on experience in the Board of Examiners, 6 cases were developed, 3 that represented Medical Expert deficits, and 3 that described Professional deficits. The results showed that respondents viewed the Professional Role as relatively more “fixed” than the Medical Expert Role. Those views corresponded to stricter remediation planning, characterized by a short duration of remediation, stricter consequences of failure, and a lower perceived likelihood of success paired with a higher perceived likelihood of Professional deficits in the future. These results supported the hypotheses that the implicit theories of intelligence differ according to the dimension of physician competence in question. Professional was considered to be more fixed, relative to Medical Expert, and in keeping with the theorization, the resultant remediation plans appeared more as an opportunity to demonstrate a fundamental lack of ability than an opportunity for the resident to develop competence. These findings are consistent with those in other studies, where a fixed theory of intelligence was associated with a “helpless” behaviour pattern, characterized by low persistence, and challenge avoidance. We were able to show that one’s implicit theories extend beyond the self and can influence how an individual manages the education of another. This work sheds light on some of the factors that man influence remediation decision-making and adds to the conversation surrounding professionalism as competency versus an attribute.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.034
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.034
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.016
GPT teacher head0.271
Teacher spread0.254 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2019
Admission routes1
Has abstractyes

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