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Record W2960277582 · doi:10.1177/2158244019858436

Exploring Interpersonal Relationships in a Nurse-Managed Clinic and Their Impact on Clinical Outcomes

2019· article· en· W2960277582 on OpenAlexaff
Charlotte Lee, Susanne J. Phillips, Susan Tiso, Camille Fitzpatrick

Bibliographic record

VenueSAGE Open · 2019
Typearticle
Languageen
FieldHealth Professions
TopicPatient Satisfaction in Healthcare
Canadian institutionsToronto Metropolitan University
FundersUniversity of California, Irvine
KeywordsInterpersonal communicationThematic analysisNursingInterpersonal relationshipAffect (linguistics)Health carePsychologyPopulationQualitative researchMedicineSocial psychology

Abstract

fetched live from OpenAlex

This study explores the impact of interpersonal relationships on processes and outcomes of care at a nurse-managed, primary care clinic in Southern California serving a vulnerable population. Ten semistructured interviews were conducted with all health care providers in the clinic to explore patient characteristics, types of relationships experienced, and how they may have affected processes and outcomes of care. Themes in interviews were identified through thematic analysis. We found that (a) patients with limited access to health care and resources establish different types of relationships to support their needs, and (b) interpersonal relationships, including those among providers, affect quality of care.

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 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)0.005
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.511
GPT teacher head0.551
Teacher spread0.040 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations4
Published2019
Admission routes1
Has abstractyes

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