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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.
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]
Copyright of European Child & Adolescent Psychiatry is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: 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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  Data: <searchLink fieldCode="JN" term="%22European+Child+%26+Adolescent+Psychiatry%22">European Child & Adolescent Psychiatry</searchLink>. Oct2025, Vol. 34 Issue 10, p3185-3196. 12p.
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  Data: 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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  Data: <i>Copyright of European Child & Adolescent Psychiatry is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=pbh&AN=189168606
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        Value: 10.1007/s00787-025-02730-9
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        Text: English
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      – SubjectFull: Mental illness risk factors
        Type: general
      – SubjectFull: Children's health
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      – SubjectFull: Risk assessment
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      – SubjectFull: Self-evaluation
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      – TitleFull: 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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              Text: Oct2025
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