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Record W2086536539 · doi:10.1002/nur.21493

Translation and validation of the Hong Kong Chinese version of the breastfeeding self‐efficacy scale—short form

2012· article· en· W2086536539 on OpenAlexaff
Wan‐Yim Ip, Kai Chow Choi, Sek Ying Chair, Cindy‐Lee Dennis

Bibliographic record

VenueResearch in Nursing & Health · 2012
Typearticle
Languageen
FieldMedicine
TopicBreastfeeding Practices and Influences
Canadian institutionsWomen's Health Research InstituteWomen's College Hospital
Fundersnot available
KeywordsBreastfeedingScale (ratio)Confirmatory factor analysisMedicineConstruct validityPsychometricsPsychologyClinical psychologyStructural equation modelingPediatricsStatistics

Abstract

fetched live from OpenAlex

Healthcare providers do not have a validated instrument to measure breastfeeding self-efficacy among Hong Kong Chinese. In this study, we sought to translate the breastfeeding self-efficacy scale-short form (BSES-SF) into Hong Kong Chinese and to examine the psychometric properties in a sample of 185 breastfeeding mothers. The construct validity of the translated scale was supported by confirmatory factor analysis and known group analysis. The receiver operating characteristics analysis indicated that the total score of the translated scale at 48-72 hours after delivery could be a useful diagnostic tool for identifying mothers likely to discontinue breastfeeding prematurely, before 6 months postpartum. Further research to cross-validate the suggested cut-off value of the scale is recommended.

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)0.008
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.077
GPT teacher head0.442
Teacher spread0.365 · 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 designBench or experimental
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

Citations63
Published2012
Admission routes1
Has abstractyes

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