To identify factors associated with psychological distress among family caregivers of preschool-aged children with Autism Spectrum Disorder (ASD) using advanced machine learning techniques.
Key Findings:
Comorbid conditions in children with ASD are the strongest predictor of caregiver distress.
Longer daily care hours correlate with increased psychological distress.
Marital status significantly influences caregiver mental health.
The severity of the child's ASD is linked to caregiver distress.
Employment status affects the psychological well-being of caregivers.
The predictive model outperformed logistic regression with an AUC of 0.845.
Interpretation:
The study highlights critical factors contributing to psychological distress in caregivers, suggesting targeted interventions for those at higher risk and providing a basis for future research.
Limitations:
The study used a convenience sampling method, which may limit generalizability and the ability to apply findings to broader populations.
The cross-sectional design does not allow for causal inferences, limiting the understanding of the directionality of relationships.
Conclusion:
Identifying key factors associated with caregiver distress can inform early psychological interventions to support high-risk caregivers, emphasizing the need for targeted support strategies.
