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Record W4388975195 · doi:10.5430/ijhe.v12n6p89

Through the Lens of the Donabedian Structure-Process-Outcomes Model: Lessons Learned and Recommendations for Interprofessional Collaboration in Higher Education

2023· article· en· W4388975195 on OpenAlexvenueno aff
Deborah Witt Sherman, Lisa Cain, Amy Paul‐Ward, Ken C. Winters

Bibliographic record

VenueInternational Journal of Higher Education · 2023
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsnot available
Fundersnot available
KeywordsIntrapersonal communicationInterpersonal communicationProcess (computing)Transformative learningOrganizational structureOrganizational cultureMedical educationIdentification (biology)PsychologyHigher educationKnowledge managementProcess managementPublic relationsPedagogyMedicineBusinessPolitical scienceComputer science

Abstract

fetched live from OpenAlex

Through interprofessional collaboration (IPC), scholars with diverse knowledge and skills enhance the integration and communication of ideas and services in the pursuit of high-quality education. This article explores the structure, process, and outcomes of IPC and proposes recommendations to create a culture of interprofessional collaboration in higher education. Semi-structured interviews were conducted with 17 participants with extensive IPC experience in a research-intensive university. Results regarding IPC were organized around structure-related factors, including physical structure, organizational characteristics, external and internal factors, and group structure, as well as process-related factors, which include intrapersonal, interpersonal, and institutional facilitators and barriers. Outcomes included intrapersonal, interpersonal, and institutional, including drawbacks and benefits. Structure-process-outcomes of IPC inform recommendations to strategically create a culture of IPC in higher education. Transformative culture change begins with the identification of champions of IPC, who spearhead the implementation of IPC goals within an organization’s strategic plan. Policies, procedures, and resources of an organization are needed for successful interprofessional collaborations.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Theoretical or conceptuallow
gptno category
Domain: not available · Genre: Commentary
About the Canadian research system: no · About a Canadian topic: no
Theoretical or conceptuallow
models agreeAgreement compares identical category sets and study designs across arms.

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)0.048
metaresearch head score (Gemma)0.031
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: none
Teacher disagreement score0.048
Threshold uncertainty score0.256

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0480.031
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0120.009
Science and technology studies0.0050.034
Scholarly communication0.0180.024
Open science0.0050.008
Research integrity0.0060.011
Insufficient payload (model declined to judge)0.0060.001

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 head0.089
GPT teacher head0.524
Teacher spread0.435 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical · Commentary

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
Published2023
Admission routes1
Has abstractyes

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