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Factors Influencing Interprofessional Collaboration in Healthcare Environment

2020· book-chapter· en· W3096815448 on OpenAlexaff
Ramaraj Palanisamy, Nazım Taşkın, Jacques Verville

Bibliographic record

VenueIGI Global eBooks · 2020
Typebook-chapter
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsSt. Francis Xavier University
Fundersnot available
KeywordsHealth careKnowledge managementBusinessQuality (philosophy)Healthcare deliveryProcess managementPsychologyComputer sciencePolitical science

Abstract

fetched live from OpenAlex

The increases in complexity of patient care, healthcare costs, and technological advancements shifted the healthcare delivery to interprofessional collaborative care. The study aims for identifying factors influencing the quality of team collaboration. The study examines the impact of trust and technology orientation on collaboration with the mediating effects of communication, coordination, and cooperation. The results of the study validate that (1) collaboration has positive and significant relationship with coordination, and cooperation; (2) trust has positive and significant relationship with communication, coordination, and cooperation; and (3) technology orientation has positive and significant relationship with cooperation but not with communication and coordination. The research and managerial implications of these factors are given in the discussion. The results can be used by healthcare professionals and managers to advance their understanding on the impact of trust and technology on collaboration mediating communication, coordination, and cooperation practices.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.849
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.001

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 head0.039
GPT teacher head0.386
Teacher spread0.347 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations2
Published2020
Admission routes1
Has abstractyes

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