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Record W4404020556 · doi:10.1590/ce.v29i0.92361

DEVELOPMENT EVALUATION AMONG FAMILIES OF PEOPLE WITH SUICIDAL BEHAVIOR: AN APPLICATION OF THE CALGARY MODEL

2024· article· pt· W4404020556 on OpenAlexaboutno aff
Isabela Carolyne Sena de Andrade, Nadirlene Pereira Gomes, Cíntia Mesquita Correia, Cátia Romano

Bibliographic record

VenueCogitare Enfermagem · 2024
Typearticle
Languagept
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsnot available
Fundersnot available
KeywordsSuicidal behaviorPsychologyDevelopmental psychologyClinical psychologyEnvironmental healthMedicineSuicide preventionPoison control

Abstract

fetched live from OpenAlex

RESUMO Objetivo: descrever os eventos que marcaram o desenvolvimento da família de pessoas com comportamento suicida. Metodologia: estudo baseado no Modelo Calgary de Avaliação Familiar. Participaram nove famílias de usuários do Núcleo de Estudo e Prevenção do Suicídio, em Salvador - Bahia, Brasil. Coleta de dados online, entre novembro de 2021 e maio de 2022. As perguntas foram estruturadas previamente em um formulário baseado no MCAF. Após transcrição das entrevistas, essas passaram pelos processos de transcriação e textualização. Resultados: entre as categorias que emergiram, destacam-se: Vivência de violência intrafamiliar como fator precipitador de comportamento suicida no ciclo vital das famílias; Abdicação de si em detrimento do cuidado a pessoa com comportamento suicida; e Vínculo com animais como fator protetivo para o comportamento suicida no desenvolvimento da família de pessoas com comportamento suicida. Conclusão: elucidando tais eventos, é possível vincular-se e intervir nos conflitos, bem como utilizá-los como fatores de proteção para as tentativas de suicídio.

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)0.007
metaresearch head score (Gemma)0.025
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 score0.071
Threshold uncertainty score0.142

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.025
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.045
GPT teacher head0.326
Teacher spread0.281 · 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
Published2024
Admission routes1
Has abstractyes

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