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Record W3128460018 · doi:10.5430/jnep.v11n5p60

Variables related to the comfort of the family of people in critical care

2021· article· en· W3128460018 on OpenAlexvenueno aff
Mariana de Almeida Moraes, Fernanda Carneiro Mussi, Elilian Oliveira Pereira, Eulália Cristina Leal de Oliveira Gonsalves, Kátia Santana Freitas, Carlos Antônio de Souza Teles Santos

Bibliographic record

VenueJournal of Nursing Education and Practice · 2021
Typearticle
Languageen
FieldHealth Professions
TopicFamily and Patient Care in Intensive Care Units
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Scale (ratio)PsychologySample (material)Dimension (graph theory)Family healthIntensive careFamily memberDemographyMedicineGerontologyNursingGeographyMathematicsFamily medicine

Abstract

fetched live from OpenAlex

Objective: To verify the variables related to the comfort level of family members of people in intensive care units.Methods: Cross-sectional study, conducted in six intensive care units, with 250 family members, using the Comfort Scale for Family Members of People in Critical Health State. The sample data were analyzed in absolute and relative frequencies, means and standard deviation. The level of global comfort and dimension were analyzed by the arithmetic mean of the response levels of the Comfort Scale for Family Members of People in Critical Health State. The One-Way test (ANOVA) was used to analyze differences in the means of the comfort level of the previously mentioned scale according to variables of interest.Results: The variables severity level, hospitalization time and nature of the relationship of the family member and relative, as well as gender, age, income were statistically significant in relation to the comfort level. Conclusions: Variables related to the context of hospitalization of the relative and sociodemographic data of the family members were related to the level of comfort.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
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)0.0030.000

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 head0.182
GPT teacher head0.530
Teacher spread0.349 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Nursing Education and Practice→Same topicFamily and Patient Care in Intensive Care Units→French-language works237,207→