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Record W3060908494 · doi:10.1093/pch/pxaa068.065

66 Piloting a respectful challenges workshop in pediatric residency training

2020· article· en· W3060908494 on OpenAlexaff
Ashley Martin, Sarah Manos

Bibliographic record

VenuePaediatrics & Child Health · 2020
Typearticle
Languageen
FieldMedicine
TopicEthics and Legal Issues in Pediatric Healthcare
Canadian institutionsIzaak Walton Killam Health CentreDalhousie University
Fundersnot available
KeywordsCoachingCurriculumMedical educationConflict resolutionLikert scaleConflict managementPsychologyDescriptive statisticsMedicineNursingPedagogyPolitical science

Abstract

fetched live from OpenAlex

Abstract Background Unaddressed conflict has been shown to negatively impact resident wellness and patient safety, and development of communication and conflict resolution skills are key competencies in medical education. While there are a number of existing communication training programs directed at healthcare providers, these can be costly and difficult to accommodate in an already packed curriculum. We developed a conflict resolution workshop to address local conflict scenarios facing our residents that could be integrated into our program curriculum at no cost. Objectives Evaluate resident satisfaction with the addition of a “respectful challenges” workshop to our training program’s academic curriculum. Design/Methods We designed a two- hour workshop for pediatric residents at our institution focusing on addressing conflict during residency training. A didactic lecture outlining different approaches was followed by three role-playing scenarios with coaching (conflict with another resident, allied health and faculty). The workshop was facilitated by a senior resident and faculty identified by residents as “approachable”. Residents (PGY1-4) were asked to evaluate the workshop’s content and effectiveness as well as their own comfort addressing conflict using pre and post-surveys with Likert scales. Results of the survey were analyzed using descriptive statistics. Results A total of 15 residents were involved in the workshop and completed the pre and post surveys. Eleven were female. Six indicated that they had some form of previous training in conflict management. All residents reported having experienced workplace conflict at least a few times per year, but most said they didn’t always address it (73%). Twelve (80%) thought it was either “quite” or “extremely important” that conflict resolution skills be taught in residency. All 15 residents felt that the scenarios represented real life and that the format was an appropriate way to discuss conflict in the workplace. The majority of residents felt the workshop helped them better understand their approach to conflict and allowed them to feel better prepared to face challenges in the future (14/15 and 11/15 rated as “quite” or “extremely”). Eighty percent of residents reported that they would feel more comfortable addressing workplace conflict after the workshop. Conclusion This concise workshop provided a foundation on conflict resolution for our residents. The use of role play and coaching during simulated scenarios was well received, and residents reported increased comfort approaching workplace conflict in the future. Further evaluation will be important to determine if residents translate these skills into practice.

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)0.010
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0020.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.141
GPT teacher head0.376
Teacher spread0.235 · 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 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

Citations0
Published2020
Admission routes1
Has abstractyes

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