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Record W2402198032 · doi:10.1177/1715163516647749

Trust in interprofessional collaboration

2016· article· en· W2402198032 on OpenAlex
Paul A.M. Gregory, Zubin Austin

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueCanadian Pharmacists Journal / Revue des Pharmaciens du Canada · 2016
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSnowball samplingPsychologyPrimary carePharmacistNursingHealth careCognitionFamily medicineMedicineMedical educationPharmacyPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Trust is integral to effective interprofessional collaboration. There has been scant literature characterizing how trust between practitioners is formed, maintained or lost. The objective of this study was to characterize the cognitive model of trust that exists between pharmacists and family physicians working in collaborative primary care settings. METHODS: Pharmacists and family physicians who work collaboratively in primary care were participants in this study. Family health teams were excluded from this study because of the distinct nature of these settings. Through a snowball convenience sampling method, a total of 11 pharmacists and 8 family physicians were recruited. A semistructured interview guide was used to guide discussion around trust, relationships and collaboration. Constant-comparative coding was used to identify themes emerging from these data. RESULTS: Pharmacists and family physicians demonstrate different cognitive models of trust in primary care collaboration. For pharmacists, trust appears to be conferred on physicians based on title, degree, status and positional authority. For family physicians, trust appears to be earned based on competency and performance. These differences may lead to interprofessional tension when expectations of reciprocal trust are not met. CONCLUSIONS: Further work in characterizing how trust is developed in interprofessional relationships is needed to support effective team formation and functioning.

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.

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 categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.559
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
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0090.000

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 head0.034
GPT teacher head0.390
Teacher spread0.355 · 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