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Record W7120445072

Essential competencies of the home care program for stroke patients

2013· article· pt· W7120445072 on OpenAlexaboutno aff
Ana Maria Barretto de Menezes Sampaio de Oliveira, Alice Gabrielle de Sousa Costa, Thelma Leite de Araújo, Priscila de Souza Aquino, Ana Karina Bezerra Pinheiro, Lorena Barbosa Ximenes

Bibliographic record

VenueLA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) · 2013
Typearticle
Languagept
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsnot available
Fundersnot available
KeywordsInclusion (mineral)Agency (philosophy)Scope (computer science)Public healthHealth careProgram evaluationScope of practice
DOInot available

Abstract

fetched live from OpenAlex

The Home Care Program combines uncountable Essential Competencies among its skills, such as those proposed by the Public Health Agency of Canada. Therefore, the objective of this study was to evaluate the inclusion of these essential competencies in this program. This cross-sectional study was performed between January and April of 2010, with caregivers and patients followed in the program. Forma and field diaries were used for data collection. Later, an evaluation was made of the activities performed within the scope of the recommended essential competencies. Therefore, it was possible to realize that the attributions performed by the program remain below expectations, considering the biomedical model that is used, which led to the partial implementation of Essential Competencies, such as: Public Health Policies; Planning and Implementations; Partnership, Collaboration, Support and Leadership. This fact reveals the need for greater governmental efforts and by the professionals involved in the program with a view to improving the 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)0.002
metaresearch head score (Gemma)0.009
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 score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.021
GPT teacher head0.287
Teacher spread0.266 · 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

Citations0
Published2013
Admission routes1
Has abstractyes

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Same venueLA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas)→Same topicGeriatric Care and Nursing Homes→French-language works237,207→