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Exploring the Predictive Role of Early Executive Functions and Self-Regulation on Functional Outcome in
Berni M1,2, Scatigna S2,3, Igliozzi R2
1University of Florence, Florence, Italy.
Early difficulties in executive functions and self-regulation predict later neurodevelopmental disorder symptoms. This review synthesizes evidence on their role in attention-deficit/hyperactivity disorder and autism spectrum disorder trajectories.
Area of Science:
- Neuroscience
- Developmental Psychology
- Clinical Psychology
Background:
- Executive functions and self-regulation are crucial for learning and adaptation, often impaired in neurodevelopmental disorders (NDDs).
- Research linking early executive functions/self-regulation to NDD diagnosis and development is rapidly expanding.
- A synthesis of evidence strength and methodologies is needed to understand this relationship.
Purpose of the Study:
- To systematically review and meta-analyze longitudinal studies on early executive functions/self-regulation and NDD symptoms.
- To examine the predictive value of these early functions for later NDD-related impairments.
- To assess methodological variations in studies investigating this association.
Main Methods:
- Systematic review and meta-analysis of 32 longitudinal studies.
- Analysis focused on executive functions and self-regulation in the first 6 years of life.
- Separate meta-analyses for ADHD and ASD diagnoses, measures used, and developmental periods.
Main Results:
- Significant longitudinal association found between early executive/self-regulation difficulties and later attention, socio-communication, and adaptive impairments in NDDs.
- Early difficulties demonstrated predictive value for subsequent NDD symptoms.
- Methodological characteristics of studies were found to influence findings.
Conclusions:
- Early executive and self-regulation challenges are significant predictors of later NDD symptoms.
- Findings have implications for prevention strategies in atypical neurodevelopment, particularly for ADHD and ASD.
- Methodological variability underscores the need for refined research tools and statistical approaches.
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