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2014· article· en· W2317484788 on OpenAlexaboutno aff
Mélanie Lavoie‐Tremblay, Patricia OʼConnor, Anastasia Harripaul, Alain Biron, Judith A. Ritchie, Brenda MacGibbon, Guylaine Cyr

Bibliographic record

VenueAJN American Journal of Nursing · 2014
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsnot available
Fundersnot available
KeywordsPsychology

Abstract

fetched live from OpenAlex

OBJECTIVE: This study sought to explore the perceptions of health care workers about engaging patients as partners on care redesign teams under a program called Transforming Care at the Bedside (TCAB), and to examine the facilitating factors, barriers, and effects of such engagement. DESIGN: This descriptive, qualitative study collected data through focus groups and individual interviews. Participants included health care providers and managers from five units at three hospitals in a university-affiliated health care center in Canada. METHODS: A total of nine focus groups and 13 individual interviews were conducted in April 2012, 18 months after the TCAB program began in September 2010. Content analysis was used to analyze the qualitative data. FINDINGS: Health care providers and managers benefited from engaging patients in the decision-making process because the patients brought a new point of view. Involving the patients exposed team members to valuable information that they hadn't previously thought about during decision making. CONCLUSION: Health care teams stand to benefit from engaging patients in the change process. Patients contribute a different point of view, and this helps to ensure that the changes proposed and implemented address their needs.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.856
Threshold uncertainty score0.405

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.033
GPT teacher head0.487
Teacher spread0.454 · 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.

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

Citations21
Published2014
Admission routes1
Has abstractyes

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