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Assistência de saúde na crise psiquiátrica: Obstáculos no cuidado de enfermagem

2020· article· pt· W3076978448 on OpenAlexaff
Lucas dos Santos Silva, Eduardo Lúcio Cordeiro, Bianca de Souza Rodrigues

Bibliographic record

VenueRevista Científica Multidisciplinar Núcleo do Conhecimento · 2020
Typearticle
Languagept
FieldHealth Professions
TopicHealth, Nursing, Elderly Care
Canadian institutionsNortel (Canada)
Fundersnot available
KeywordsPsychologyMedicine

Abstract

fetched live from OpenAlex

Objetivo: Identificar na literatura dificuldades dos profissionais de enfermagem ao realizarem a atenção a indivíduos em crise psiquiátrica. Método: Trata-se de um estudo de abordagem qualitativa, a partir do método da revisão integrativa. O levantamento bibliográfico foi realizado no período de Junho a Novembro de 2019, nas bases de dados Biblioteca Virtual de Saúde – BVS e Scientific Electronic Library Online – SCIELO. Na busca foram utilizados os termos: “intervenção na crise”, “serviços de saúde” e “serviços de enfermagem”. Resultados: Identificou-se cinco pesquisas aptas a compor a presente revisão integrativa, publicadas entre os anos de 2011 a 2016. Da análise dos artigos surgiram seis categorias que descrevem as respostas à questão norteadora proposta, sendo elas: (i) limites do conhecimento sobre saúde mental e psiquiatria na formação; (ii) educação continuada limitada; (iii) medo em abordar o cliente em crise; (iv) cuidado empregado com a visão biomédica; (v), estigma do cliente psiquiátrico, e (vi) limites do serviço de saúde em atender a demanda de cuidado psiquiátrico. Conclusão: A assistência à crise psiquiátrica encontram barreiras específicas que se relacionam a capacitação de profissionais, bem como às questões culturais. Sugere-se a realização de pesquisas sobre o tema, como forma de possibilitar o avanço profissional.

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)0.005
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.295
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.003
Science and technology studies0.0040.001
Scholarly communication0.0010.001
Open science0.0030.002
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0050.011

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 head0.092
GPT teacher head0.410
Teacher spread0.318 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2020
Admission routes1
Has abstractyes

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