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Record W3137455140

Midwifery Students and Obstetrical Residents Learning, Understanding and Application of Shared Decision Making

2020· dissertation· en· W3137455140 on OpenAlexaboutno aff
Meagan Furnivall

Bibliographic record

VenueMacSphere (McMaster University) · 2020
Typedissertation
Languageen
FieldNursing
TopicHealthcare Education and Workforce Issues
Canadian institutionsnot available
Fundersnot available
KeywordsObstetricsMedicineMedical educationPsychologyNursing
DOInot available

Abstract

fetched live from OpenAlex

Introduction: Childbirth is an important time in a client and patient’s life. The pregnant client seeks to obtain as much control over their circumstance as possible. The more perceived control in childbirth by the client, the better the outcomes are for the client-newborn dyad. One way that clients obtain control during childbirth is by participating in clinical decision making with their healthcare providers. This research intended to study the ways in which OB residents and midwifery students engaged in the understanding, learning and application of shared decision making with clients and patients. Methodology: This study utilised a constructivist grounded theory approach to obtain data and formulate a theory using semi-structured interviews with five senior obstetrical residents and five senior midwifery students from Ontario. Results: Qualitative data revealed four themes and eight sub-themes. Our theory describes the way residents and students absorb, mirror, and perform shared decision making through an informal process of observation and experience throughout their training. Our theory further describes how support for students and residents creates the foundation for learning shared decision making. Support includes how the mentor minimizes the impacts of the hierarchy of power in medical and midwifery education, as well as increasing psychological safety for the learner. Conclusion: The study results support the exploration of future methods for the teaching of shared decision making to obstetrical residents and midwifery students. Participants of this study agreed that more training is needed for shared decision making, as well as training for the mentor to ensure learners are optimizing their experience. More training needs to be available for mentors to help reduce the negative impacts of the hierarchy of power, and to increase psychological safety for the learner.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.761
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.042
GPT teacher head0.327
Teacher spread0.285 · 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 designOther design
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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