Multilevel Predictors of Bipolar Disorder Symptomatology: A Cross-sectional Study of Neurodevelopmental and Psychosocial Risk Factors in a Greek Clinical Population,

Abstract

Background: Bipolar disorder (BD) is a complex and often misdiagnosed psychiatric condition associated with high morbidity, suicidality, and functional impairment. Early identification of risk factors is critical for improving clinical outcomes, particularly in settings with limited access to mental health services. Aim: This study aimed to identify psychosocial, neurodevelopmental, and behavioral predictors of BD symptomatology using a multidimensional assessment model. Methods: A cross-sectional study was conducted with 590 participants recruited from the outpatient psychiatric clinics of the 414 SNEN Military Hospital in Athens, Greece. Participants completed the CISQ-90 psychometric inventory and a structured questionnaire covering psychosocial, demographic, and behavioral variables. Statistical analyses included Spearman correlations, multiple regression models, and structural equation modeling (SEM). Results: Significant predictors of BD included maternal history of mental illness, comorbid ADHD, perinatal complications, male gender, and left-handedness. Unexpectedly, parental divorce was negatively associated with BD, potentially reflecting protective effects in high-conflict households. Social support emerged as the strongest protective factor, with higher levels significantly predicting lower BD symptomatology. Financial stressors (e.g., low income, loan default) contributed modestly. Substance use and suicidality showed the highest predictive value, with BD mediating the relationship between substance use and suicidal ideation. Conclusions: The findings underscore the importance of adopting a multilevel diagnostic approach to BD that incorporates familial, neurodevelopmental, psychosocial, and behavioral factors. Enhanced screening and early intervention strategies targeting at-risk populations, particularly those with neurodevelopmental vulnerabilities and reduced social support, may help reduce diagnostic delays and improve treatment outcomes.