Breastfeeding Measurement Instruments: A COSMIN Review and Recommendation
Bingjie Liu1, Fen Zhou1,2, Yunpeng Lv3
1Beijing University of Chinese Medicine, China.
Aim:
To comprehensively assess the quality of current breastfeeding measurement instruments and to recommend instruments.
Background:
The field of breastfeeding assessment is characterized by a diverse array of measurement tools, yet their application is complicated by heterogeneity in psychometric quality and inconsistent findings. Previous systematic reviews employing the COSMIN (CONsensus-based Standards for the selection of health Measurement INstruments) framework have been limited in scope, highlighting the need for a contemporary and comprehensive evaluation to guide instrument selection.
Methods:
Following COSMIN guidelines, we systematically searched 10 Chinese and English databases from inception to September 30, 2024. Two reviewers independently conducted study screening, data extraction, and methodological quality assessment. Evidence was synthesized and recommendations were formulated based on predefined criteria.
Results:
Analysis of 54 studies evaluating 24 instruments revealed substantial evidence gaps in key measurement properties. Reliability data were missing for 52% of instruments, while cross-cultural validity/measurement invariance, criterion validity, and responsiveness were assessed in fewer than 30% of cases. No instrument had established values for minimal important change or smallest detectable change. Seven instruments measuring self-efficacy, support needs, and breastfeeding behavior prediction received Grade A recommendations.
Discussion:
The review offers a validated evidence base to guide instrument selection. Future research should prioritize closing the identified evidence gaps, particularly establishing reliability and clinically meaningful change parameters for all recommended tools.
Conclusions:
This review provides an evidence base for instrument selection while identifying critical gaps in measurement property evidence, particularly in reliability and clinically interpretable parameters, directing future validation research priorities.
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