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Record W4389049395 · doi:10.1590/0034-7167-2022-0497

Cross-cultural adaptation of the Breastfeeding Self-Efficacy Scale Short Form (BSES-SF) modified for preterm mothers in Brazil

2023· article· en· W4389049395 on OpenAlexaff
Clarice Borges Lucas Denobi, Lorena Maria Fernandes da Silva, Gabriela Ramos Ferreira Curan, Cindy‐Lee Dennis, Mônica Oliveira Batista Oriá, Edilaine Giovanini Rossetto

Bibliographic record

VenueRevista Brasileira de Enfermagem · 2023
Typearticle
Languageen
FieldMedicine
TopicBreastfeeding Practices and Influences
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBreastfeedingCLARITYScale (ratio)PsychologyPortugueseTest (biology)Brazilian PortugueseAdaptation (eye)Relevance (law)Content validityPopulationDevelopmental psychologyMedicineClinical psychologyPsychometricsPediatricsLinguisticsGeographyEnvironmental healthCartographyPolitical science

Abstract

fetched live from OpenAlex

OBJECTIVES: to conduct a cross-cultural adaptation of the Breastfeeding Self-Efficacy Scale-Short Form (BSES-SF) for mothers of ill and/or preterm infants among Portuguese-speaking mothers in Brazil. METHODS: a methodological study was completed, including the translation of the tool, synthesis of translations, review by experts, synthesis, reassessment of experts, back-translation, pre-test, and validation of the content. The study involved 19 participants, including a translator and experts. In addition, 18 mothers from the target population were included in the pre-test. RESULTS: the equivalences of the opinion obtained by the committee of experts were semantic (85%), idiom (89%), cultural (86%), and conceptual (94%). The content validation coefficient (CVC) on the scale was 0.93 for clarity and understanding; 0.89 for practical relevance; 0.92 for relevance; and the average overall CVC was 0.91. CONCLUSIONS: the scale was translated and adapted to the Brazilian Portuguese language, which maintained the equivalences and confirmed the content validity.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.084
Threshold uncertainty score0.654

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.070
GPT teacher head0.374
Teacher spread0.304 · 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.

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

Citations3
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueRevista Brasileira de EnfermagemSame topicBreastfeeding Practices and InfluencesFrench-language works237,207