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Record W2767808188 · doi:10.1590/0034-7167-2016-0479

Cross-cultural adaptation of the Filial Responsibility protocol for use in Brazil

2017· article· en· W2767808188 on OpenAlexaboutno aff
Marinês Aires, Fernanda Laís Fengler Dal Pizzol, Duane Mocellin, Idiane Rosset, Eliane Pinheiro de Morais, Lisiane Manganelli Girardi Paskulin

Bibliographic record

VenueRevista Brasileira de Enfermagem · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicFamily Support in Illness
Canadian institutionsnot available
FundersHospital de Clínicas de Porto AlegreConselho Nacional de Desenvolvimento Científico e Tecnológico
KeywordsCronbach's alphaPsychologyCompassionTest (biology)Protocol (science)Social psychologyAdaptation (eye)Caregiver burdenQuality of life (healthcare)Context (archaeology)Developmental psychologyClinical psychologyPsychometricsMedicinePsychotherapist

Abstract

fetched live from OpenAlex

OBJECTIVE: To carry out a cross-cultural adaptation of the Filial Responsibility protocol for use in Brazil with adult child caregivers for elderly parents. METHOD: A methodological study that included the steps of initial translation, synthesis of translations, back-translation, committee of experts, pre-test, evaluation of psychometric measures and submission to authors. The protocol comprises a qualitative step, closed questions and seven scales: Filial Expectation, Subsidiary Compassion, Caregiver burden, Life Satisfaction, Personal Well-being and Quality of Relationships. RESULTS: The final version in Portuguese was applied, through a pre-test, to a sample of 30 caregivers for elderly parents. In order to verify internal consistency, we used Cronbach's alpha coefficient: Filial Expectation (α = 0.64), Filial Duty (α = 0.65), Satisfaction with Life (α = 0.75), Personal Wellbeing (α = 0.87). FINAL CONSIDERATIONS: The Brazilian version presented good conceptual and face equivalence. The results demonstrate that the concepts used in the Canadian protocol are applicable in the Brazilian context.

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)0.002
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.148
GPT teacher head0.454
Teacher spread0.306 · 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 teacher head, not a consensus.

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

Citations13
Published2017
Admission routes1
Has abstractyes

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