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Investigação dos óbitos infantis através do modelo Calgary de avaliação e intervenção em famílias

2009· article· en· W1811740515 on OpenAlexaboutno aff
Sidnéia Tessmer Casarin, Teila Ceolin, Rita de Cássia Mourão dos Reis Carvalho, Rita Maria Heck, Eda Schwartz, José Richard de Sosa Silva

Bibliographic record

VenueRevista de Enfermagem UFPE on line · 2009
Typearticle
Languageen
FieldHealth Professions
TopicMaternal and Neonatal Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsGenogramFamily healthNursingWelfareExploratory researchPsychologyMedicineHumanitiesSociologyGerontologyPolitical scienceSocial scienceArtLaw

Abstract

fetched live from OpenAlex

Objective: to report the use of the Calgary Family Assessment Model (CFAM) in family interviews in an infant death survey in two counties in southern Rio Grande do Sul state. Methods: a descriptive, exploratory and qualitative approach study performed in 2007 in two southern Rio Grande do Sul counties. One family in each county who had gone through infant death was surveyed by means of home visitations through the use of the CFAM. The study has a qualitative approach and the pieces of information obtained during the interviews, genogram and ecomap preparation, as well as those collected on the infant death survey form, were considered for data analysis. The study has been approved by the Committee of Ethics in Research of the Medicine Faculty of the Federal University of Pelotas (063/07). Results: the Calgary Family Assessment Model proved to be useful in approaching families that mourned the early loss of one of their members, bringing together the nursing professional and the family, as well as strengthening the bonds between the family and the public welfare system. Conclusion: this study led us to the conclusion that the nursing professional, by means of a systemic family care approach, is able to provide a broader assistance to family needs. Descriptors: infant mortality; nursing; family; public health.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.639
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.001

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 head0.119
GPT teacher head0.447
Teacher spread0.328 · 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

Citations1
Published2009
Admission routes1
Has abstractyes

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