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Educação interprofissional e prática colaborativa na Atenção Primária à Saúde*

2015· article· pt· W2319717196 on OpenAlexaff

Bibliographic record

VenueRevista da Escola de Enfermagem da USP · 2015
Typearticle
Languagept
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsWestern University
Fundersnot available
KeywordsInterprofessional educationPerspective (graphical)Focus groupPerceptionTriangulationPrimary health careHealth careQualitative research

Abstract

fetched live from OpenAlex

Objective To understand the perceptions of professors, health care providers and students about the articulation of interprofessional education with health practices in Primary Health Care. Method To understand and interpret qualitative data collection, carried out between 2012 and 2013, through semi-structured interviews with 18 professors and four sessions of homogeneous focus groups with students, professors and health care providers of Primary Health Care. Results A triangulation of the results led to the construction of two categories: user-centered collaborative practice and barriers to interprofessional education. The first perspective indicates the need to change the model of care and training of health professionals, while the second reveals difficulties perceived by stakeholders regarding the implementation of interprofessional education. Conclusion The interprofessional education is incipient in the Brazil and the results of this analysis point out to possibilities of change toward collaborative practice, but require higher investments primarily in developing teaching-health services relationship.

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)0.009
metaresearch head score (Gemma)0.027
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.027
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0040.003
Scholarly communication0.0040.002
Open science0.0010.007
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.106
GPT teacher head0.457
Teacher spread0.352 · 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 designNot applicable
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

Citations87
Published2015
Admission routes1
Has abstractyes

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