Predicting 7-year-olds mental health in the perinatal period: Development and internal validation of a multivariable model using the prospective ALSPAC cohort.

Background: Mental health difficulties in childhood are increasing. Prevention is the only sustainable and ethical public health approach. However, predicting which children are most at-risk of mental health difficulties prior to symptoms emerging remains elusive. Methods: We developed and internally validated a perinatal multivariable model, predicting 7-year-olds mental health, using the Avon Longitudinal Study of Parents and Children ( Results: Combining eight variables predicted poor mental health, with a C-statistic of 0.66; 95% Confidence-Interval (0.64-0.68). It accurately predicted 85.6% of the participants mental health at 7-years in the perinatal period. Model performance was similar across groups of interest. Applying this model leads to a higher benefit than serving 'all' or 'no' children, that is, using the model, 30.9% of children who later had poor mental health would have been identified in the perinatal period. Conclusion: It is possible to predict childhood mental health at birth with moderate accuracy. Similar patterns of model performance were observed in this English cohort compared to a previous French cohort. At population-level, the model is most useful for ruling-out babies who are not predicted to be high-risk. In addition to improving its positive predictive value and external validation, future research should examine the model's performance at service-delivery level before implementation.