Description

CONTEXT: Mental health interventions are mostly provided once mental health is lost, that is, in context of psychopathology (i.e., when clinical levels of severity or impairment are reached). James Heckman's Equation suggests that investing in mental health before it is severely impaired would lead to high returns. We want to test: 1) to what extent is possible to transfer active ingredients for mental health from the clinical context to the community, and 2) to what extent an intervention aimed to enrich parents with higher mentalization and interaction skills improves children's mental health. Because this intervention aims to reach a wide community in non-clinical settings, it should be extensive (to ensure solid changes in the child environment) and cost-efficient, that is: cheaper than those individually transmitted in the classic therapist-client relationship.

METHODOLOGY: 12-month multisite, Randomized, Controlled Trial (RCT).

MEASURES OPERATIONALIZATION: It is expected that this translational intervention which aims to move factors for salutogenesis from the clinical setting to the non-clinical range of the mental ill-health continuum could benefit both the caregivers (parents) who receive the intervention and their children, who are daily exposed to them. Caregivers' benefits are expected in terms of improved mentalizing capacities (primary outcome) but also in terms of higher quality interactions, lower stress, lower distress symptoms, higher well-being and higher sense of self- efficacy (secondary outcomes). Child's mental health (primary outcome) is operationalized as multidimensional using: the number of symptoms, the level of role- and social functioning, and well-being. Child's benefits in terms of mentalization and pro-social behavior (secondary outcomes) are also expected because of the long-term exposition to adults enriched with new social-emotional skills based on the intervention. It is expected that parent's interventions could foster children mental health by promoting children mentalization skills (mediational or process variable).

STATISTICAL ANALYSES: The analysis under the Intention-To-Treat (ITT) approach will encompass all participants subjected to random allocation, with the utilization of multiple imputation techniques to address any missing data. Estimation of parameters, accounting for the specific statistical assumptions of each model and the data's characteristics, will be carried out through the implementation of Linear Mixed-Effect Models and Structural Equation Modeling (SEM). Various R packages will be employed to execute these models, primarily "lme4" and "nlme" for linear mixed-effect models, and "lavaan" for SEM models. Concerning statistical power, a sample size of 105 participants (35 per arm) has been proposed, which exceeds the minimum of 54 participants (18 per arm) required to detect a medium effect size (Cohen's d=0.25) in the design comprising 3 arms, 3 repeated measures (pre, post, and 1 follow-up), and a power level of .95. An empirical power close to 1.00 is anticipated. Effect size measures, including Cohen's d and squared Omega statistics, will be employed.