Predictive factors for the outcome of emotional and/or behavioural disorders in 18-to 48-month-old children after parent-child psychotherapy: Protocol of a European prospective cohort study

Objectives. - Several studies have shown that in young children, behavioural and/or emotional disorders are more difficult to manage than regulatory disorders. Moreover, data are lacking on outcome predictive factors. This article presents a short synthesis of previous research about outcome predictive factors in child psychiatry. It also describes the protocol of a longitudinal observational European multicentre study the main objective of which was to identify predictive factors of behavioural and emotional disorder outcome in toddlers after parent-child psychotherapy. The secondary objectives were to study predictive factors of the outcome in parents (anxiety/depression symptoms) and parent-child relationship. Method. - In order to highlight medium-effect size, 255 toddlers (age: 18 to 48 months) needed to be included. Outcomes will be assessed by comparing the pre-and post-therapy scores of a battery of questionnaires that assess the child's symptoms, the parents' anxiety/depression, and the parent-child relationship. Multivariate linear regression analysis will be used to identify predictive factors of the outcome among the studied variables (child age and sex, socio-economic status, life events, disorder type, intensity and duration, social support, parents' psychopathology, parents' attachment, parent -child relationships, therapy length and frequency, father's involvement in the therapy, and therapeutic alliance).

Automated summary

This article summarizes previous research on predictive factors of outcome in toddlers with behavioral and emotional disorders. It also describes a European multicenter study that aims to identify predictive factors of outcome after parent-child psychotherapy. The study will assess child symptoms, parental anxiety/depression, and parent-child relationship through pre-and post-therapy questionnaires, and use multivariate linear regression analysis to identify predictive factors among various variables.