Predicting 5-year-olds mental health at birth: development and internal validation of a multivariable model using the prospective ELFE birth cohort.
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| Title: | Predicting 5-year-olds mental health at birth: development and internal validation of a multivariable model using the prospective ELFE birth cohort. |
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| Authors: | Butler, Emma (AUTHOR), Spirtos, Michelle (AUTHOR), O' Keeffe, Linda M. (AUTHOR), Clarke, Mary (AUTHOR) |
| Source: | European Child & Adolescent Psychiatry. Oct2025, Vol. 34 Issue 10, p3185-3196. 12p. |
| Subjects: | Mental illness risk factors, Children's health, Risk assessment, Self-evaluation, Mental health, Social determinants of health, Prediction models, Cronbach's alpha, Maternal age, Parent-child relationships, Neonatal intensive care units, Questionnaires, Descriptive statistics, Structural equation modeling, Economic status, Neonatal intensive care, Longitudinal method, Child development, Interpersonal relations, Confidence intervals, Perinatal period, Educational attainment, Children |
| Geographic Terms: | France |
| Abstract: | We developed and internally validated a multivariable model to be used in the perinatal period, to predict 5-year-olds mental health, using the ELFE prospective French multicentre birth cohort (n=9768). Twenty-six candidate predictors were used, spanning pre-pregnancy maternal health, pregnancy-specific-experiences, birth factors and sociodemographic risk (maternal age, education, relationship, migrancy and family income). The Strengths and Difficulties Questionnaire total score at 5-years, dichotomised at the recommended cut-off (16), was the outcome. Least Absolute Shrinkage and Selector Operator followed by bootstrapping was used. High and low-risk was classified by ≥8% risk-threshold score. Stability of the model at population- and individual-level and model performance across groups of interest (sex, sociodemographic risk and neonatal intensive care admissions) was also examined. 10 variables (total number pregnancy-specific experiences, sociodemographic risk, maternal pre-existing hypertension and psychological difficulties, gravidity, maternal mental health problems in a previous pregnancy, smoking and alcohol use in current pregnancy, how labour started and infant sex) with a C-statistic of 0.67; 95%CI (0.64-0.69) predicted mental health. The positive and negative predictive value were 12% & 95.4% respectively, leading to 78.8% of children correctly classified. Model performance was similar across groups of interest but increased for children (born ≥33-weeks-gestation) with neonatal admissions (AUC 0.78; 95%CI (0.69-0.87)). This model is most useful for identifying low-risk children. Applying this model in a tiered preventative intervention framework could be beneficial with those predicted to be high-risk receiving further screening to determine the level of intervention required. External validation and implementation research are required before considering its use in practice. [ABSTRACT FROM AUTHOR] |
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| Database: | Psychology and Behavioral Sciences Collection |
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| Abstract: | We developed and internally validated a multivariable model to be used in the perinatal period, to predict 5-year-olds mental health, using the ELFE prospective French multicentre birth cohort (n=9768). Twenty-six candidate predictors were used, spanning pre-pregnancy maternal health, pregnancy-specific-experiences, birth factors and sociodemographic risk (maternal age, education, relationship, migrancy and family income). The Strengths and Difficulties Questionnaire total score at 5-years, dichotomised at the recommended cut-off (16), was the outcome. Least Absolute Shrinkage and Selector Operator followed by bootstrapping was used. High and low-risk was classified by ≥8% risk-threshold score. Stability of the model at population- and individual-level and model performance across groups of interest (sex, sociodemographic risk and neonatal intensive care admissions) was also examined. 10 variables (total number pregnancy-specific experiences, sociodemographic risk, maternal pre-existing hypertension and psychological difficulties, gravidity, maternal mental health problems in a previous pregnancy, smoking and alcohol use in current pregnancy, how labour started and infant sex) with a C-statistic of 0.67; 95%CI (0.64-0.69) predicted mental health. The positive and negative predictive value were 12% & 95.4% respectively, leading to 78.8% of children correctly classified. Model performance was similar across groups of interest but increased for children (born ≥33-weeks-gestation) with neonatal admissions (AUC 0.78; 95%CI (0.69-0.87)). This model is most useful for identifying low-risk children. Applying this model in a tiered preventative intervention framework could be beneficial with those predicted to be high-risk receiving further screening to determine the level of intervention required. External validation and implementation research are required before considering its use in practice. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 10188827 |
| DOI: | 10.1007/s00787-025-02730-9 |
