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Record W4224928690 · doi:10.5430/jha.v11n1p17

Assessment of interprofessional collaborative practice components of perioperative teams

2022· article· en· W4224928690 on OpenAlexvenueno aff
La Vonne A. Downey, Reem Azhari

Bibliographic record

VenueJournal of Hospital Administration · 2022
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsnot available
Fundersnot available
KeywordsCredentialingInterprofessional educationStaffingWorkforceNursingPerioperativeMedical educationMedicineHealth care

Abstract

fetched live from OpenAlex

Objective: The purpose of this study was to conduct a hospital workforce survey of nurses to determine what interprofessional collaborative practice components they have in place at their worksites. The findings could indicate what is needed to create, expand, and maintain an effective interprofessional collaborative practice environment.Methods: The study used a random sample of working perioperative nurses who were members of a national perioperative registered nurse association database and had interprofessional collaborative practice training either by continuing medical education or micro credentialing. These nurses were sent two surveys to assess their worksite presence of interprofessional components. These validated surveys assess an organization’s capacity to have an interprofessional collaboration by examining the workplace environment, environmental mechanism, and institutional support of interprofessional collaboration.Results: Interprofessional collaboration within the perioperative worksite setting exists in most of the structures in place. However, urban sites were more likely to lack supportive components that build, evaluate, and continuously create interprofessional teams.Conclusions: There was an uneven implementation of the interprofessional collaboration components. The components vary by site, with urban hospitals having few components resulting in a more asymmetrical interprofessional team. The study’s findings indicate a need for an assessment of worksite interprofessional collaboration to ensure all components are in place and for evaluation and improvement of interprofessional collaboration.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.479
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.016
GPT teacher head0.445
Teacher spread0.428 · 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 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
Published2022
Admission routes1
Has abstractyes

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