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Record W2951058934 · doi:10.1093/milmed/usz140

Leadership Training in Graduate Medical Education: Time for a Requirement?

2019· article· en· W2951058934 on OpenAlexaboutno aff
Mark W. True, Irene Folaron, Jeffrey A. Colburn, Jana Wardian, Joshua S. Hawley-Molloy, Joshua D. Hartzell

Bibliographic record

VenueMilitary Medicine · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicEducation, Leadership, and Health Research
Canadian institutionsnot available
Fundersnot available
KeywordsGraduate medical educationAccreditationMedical educationCurriculumFeelingLikert scalePsychologyMedicinePedagogy

Abstract

fetched live from OpenAlex

INTRODUCTION: The need for all physicians to function as leaders in their various roles is becoming more widely recognized. There are increasing opportunities for physicians at all levels including Graduate Medical Education (GME) to gain leadership skills, but most of these opportunities are only for those interested. Although not an Accreditation Council for Graduate Medical Education (ACGME) requirement, some US graduate medical education programs have incorporated leadership training into their curricula. Interestingly, the Royal College of Physicians and Surgeons of Canada adopted the Leader role in its 2015 CanMEDS physician training model and requires leadership training. We sought to understand the value of a leadership training program in residency in our institution. MATERIALS AND METHODS: Our 2017 pilot leadership training program for senior military internal medicine residents consisted of four one-hour sessions of mini-lectures, self-assessments, case discussions, and small group activities. The themes were: Introduction to Leadership, Emotional Intelligence, Teambuilding, and Conflict Management. Participants were given an 18-question survey (14 Likert scale multiple-choice questions and 4 open-ended response questions) to provide feedback about the course. The Brooke Army Medical Center Institutional Review Board approved this project as a Quality Improvement effort. RESULTS: The survey response rate was 48.1% (26 of 54). The majority of respondents (84.6%) agreed the leadership training sessions were helpful and relevant. Following the sessions, 80.8% saw a greater role for physicians to function as leaders. Most (88.4%) agreed that these sessions helped them understand the importance of their roles as leaders, with 80.8% feeling more empowered to be leaders in their areas, 76.9% gaining a better understanding of their own strengths and weaknesses as leaders, and 80.8% feeling better prepared to meet challenges in the future. After exposure to leadership training, 73.1% indicated a plan to pursue additional leadership development opportunities. All respondents agreed that internists should be able to lead and manage a clinical team, and every respondent agreed that leadership principles should be taught in residency. CONCLUSIONS: This pilot project supports the premise that leadership training should be integrated into GME. Initial results suggest training can improve leadership skills and inspire trainees to seek additional leadership education. Moreover, much like the published literature, residents believe they should learn about leadership during residency. While more effort is needed to determine the best approach to deliver and evaluate this content, it appears even small interventions can make a difference. Next steps for this program include developing assessment tools for observation of leadership behaviors during routine GME activities, which would allow for reinforcement of the principles being taught. Additionally, our experience has led our institution to make leadership training a requirement in all of our GME programs, and we look forward to reporting future progress. Finally, an ACGME requirement to incorporate leadership training into GME programs nationwide would prove useful, as doing so would reinforce its importance, accelerate implementation, and expand knowledge of best approaches on a national level.

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)0.024
metaresearch head score (Gemma)0.085
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.044
Threshold uncertainty score0.147

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.085
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0030.004
Open science0.0030.005
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0440.010

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 head0.423
GPT teacher head0.497
Teacher spread0.073 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations47
Published2019
Admission routes1
Has abstractyes

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