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Barriers to Collaborative Anesthetic Care Between Anesthesiologists and Nurses on the Labor and Delivery Unit: A Study Using Modified Delphi Technique

2018· article· en· W2803503791 on OpenAlexaff
L.Y. Fung, Kristi Downey, Nancy Watts, J.C.A. Carvalho

Bibliographic record

VenueObstetric Anesthesia Digest · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicDelphi Technique in Research
Canadian institutionsUniversity of TorontoMount Sinai Hospital
Fundersnot available
KeywordsMedicineTeamworkNursingDelphi methodCLARITYUnit (ring theory)DelphiOfficerPatient safetyIntimidationMedical educationHealth carePsychologyManagementSocial psychology

Abstract

fetched live from OpenAlex

( Can J Anaesth . 2017;64(8):836–844) Teamwork between anesthesiologists and nurses is very important for patient safety and effective care, particularly in obstetric care. Barriers to effective teamwork between nurses and physicians are varied and can be difficult to identify, but may include lack of role clarity, intimidation and bullying, linguistic or cultural barriers, dependence on electronic systems, poor communication and hesitation to challenge the authority of the physician. The Delphi technique is a survey method used to minimize bias in group interviews and acquire a consensus of ideas from experts. This study uses a modified Delphi technique to gain consensus on the perceived barriers to collaboration between perinatal registered nurses and anesthesiologists in a tertiary labor and delivery unit.

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)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.528
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0020.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.088
GPT teacher head0.388
Teacher spread0.300 · 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 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
Published2018
Admission routes1
Has abstractyes

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