Predicting 5-year-olds mental health at birth: development and internal validation of a multivariable model using the prospective ELFE birth cohort.

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-spec...

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Publicado en:European Child & Adolescent Psychiatry Vol. 34; no. 10; pp. 3185 - 3197
Autores principales: Butler, Emma, Spirtos, Michelle, O' Keeffe, Linda M., Clarke, Mary
Formato: research tables/charts Journal Article
Publicado: Springer Nature Oct2025
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Oct2025
      vid: 34
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      pub: Springer Nature
      place: New York, New York
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        10.1007/s00787-025-02730-9
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        atl: Predicting 5-year-olds mental health at birth: development and internal validation of a multivariable model using the prospective ELFE birth cohort.
      aug:
        au:
          Butler, Emma
          Spirtos, Michelle
          O' Keeffe, Linda M.
          Clarke, Mary
        affil: https://ror.org/01hxy9878 Department of Population Health, Royal College of Surgeons Ireland, Dublin, Ireland
      sug:
        subj:
          Mental Health In Infancy and Childhood
          Perinatal Period
          Child Development
          Child Health
          Social Determinants of Health
          Prediction Models
          Mental Disorders Risk Factors
          Risk Assessment
          Human
          Male
          Female
          Child, Preschool
          Prospective Studies
          Descriptive Statistics
          France
          Self Report
          Structural Equation Modeling
          Coefficient alpha
          Maternal Age
          Educational Status
          Interpersonal Relations
          Economic Status
          Parent-Child Relations
          Confidence Intervals
          Intensive Care Units, Neonatal
          Questionnaires
          Child, Preschool: 2-5 years
          Male
          Female
      ab: 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.
      pubtype: Academic Journal
      doctype:
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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