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Development of a predictive model for exclusive breastfeeding at 3 months using machine learning : a secondary analysis of a cross-sectional survey.

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Názov: Development of a predictive model for exclusive breastfeeding at 3 months using machine learning : a secondary analysis of a cross-sectional survey.
Autori: Kim, Hyun Kyoung1 hkk@kongju.ac.kr
Zdroj: Journal of Korean Academy of Nursing. Nov2025, Vol. 55 Issue 4, p519-527. 9p.
Predmety: Breastfeeding, Cross-sectional method, Random forest algorithms, Attitudes toward breastfeeding, Prediction models, Human services programs, Secondary analysis, Research funding, Puerperium, Mothers, Questionnaires, Logistic regression analysis, Descriptive statistics, Breastfeeding promotion, Psychometrics, Machine learning, Comparative studies, Data analysis software, Decision trees, Self-perception, Mental depression
Geografický termín: South Korea
Abstrakt: Purpose: This study aimed to develop a machine learning model to predict exclusive breastfeeding during the first 3 months after birth and to explore factors affecting breastfeeding outcomes. Methods: Data from 2,579 participants in the Korean Early Childhood Education & Care Panel between March 1 and June 3, 2025 were analyzed using Python version 3.12.8 and Colab. The dataset was split into training and testing sets at an 80:20 ratio, and five classifiers (random forest, logistic regression, decision tree, AdaBoost, and XGBoost) were trained and evaluated using multiple performance metrics and feature importance analysis. Results: The confusion matrix of the random forest classifier model demonstrated strong performance, with a precision of 86.6%, accuracy of 84.8%, recall of 96.8%, F1-score of 91.9%, and an area under the curve of 86.0%. Twenty-one features were analyzed, from which feeding plan, breastfeeding at 1 month, marriage period, maternal prenatal weight, self-respect, alcohol consumption, grit, value placed on children, maternal age, and depression emerged as important predictors of exclusive breastfeeding in the first 3 months. Discussion: A robust model was developed to predict exclusive breastfeeding that identified feeding planning and breastfeeding at 1 month as the most influential predictors. The model could be implemented in clinical and community settings to guide tailored breastfeeding support strategies, coupled with the integration of maternal self-respect, grit, and the value placed on children in counseling programs to promote exclusive breastfeeding. [ABSTRACT FROM AUTHOR]
Databáza: Supplemental Index
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Abstrakt:Purpose: This study aimed to develop a machine learning model to predict exclusive breastfeeding during the first 3 months after birth and to explore factors affecting breastfeeding outcomes. Methods: Data from 2,579 participants in the Korean Early Childhood Education & Care Panel between March 1 and June 3, 2025 were analyzed using Python version 3.12.8 and Colab. The dataset was split into training and testing sets at an 80:20 ratio, and five classifiers (random forest, logistic regression, decision tree, AdaBoost, and XGBoost) were trained and evaluated using multiple performance metrics and feature importance analysis. Results: The confusion matrix of the random forest classifier model demonstrated strong performance, with a precision of 86.6%, accuracy of 84.8%, recall of 96.8%, F1-score of 91.9%, and an area under the curve of 86.0%. Twenty-one features were analyzed, from which feeding plan, breastfeeding at 1 month, marriage period, maternal prenatal weight, self-respect, alcohol consumption, grit, value placed on children, maternal age, and depression emerged as important predictors of exclusive breastfeeding in the first 3 months. Discussion: A robust model was developed to predict exclusive breastfeeding that identified feeding planning and breastfeeding at 1 month as the most influential predictors. The model could be implemented in clinical and community settings to guide tailored breastfeeding support strategies, coupled with the integration of maternal self-respect, grit, and the value placed on children in counseling programs to promote exclusive breastfeeding. [ABSTRACT FROM AUTHOR]
ISSN:20053673
DOI:10.4040/jkan.25086