Childhood trauma (CT) and parental bonding (PB) have been correlated with later antisocial personality disorder (ASPD). Aiming to better understand this complex interaction we analyzed the data from a cross-sectional study that evaluated 346 male inpatient cocaine users, using both traditional statistical analysis and machine learning (ML) approaches. Childhood Trauma Questionnaire (CTQ), Parental Bonding Instrument (PBI), and Mini International Neuropsychiatric Interview (MINI) were applied. We found a markedly higher prevalence of mental illness in the ASPD group. The ML method and the traditional analysis showed that emotional and physical abuse were the factors with the strongest relationship with ASPD. Also, there were discrepancies between the findings of both methods regarding physical neglect and paternal care. Although this study does not allow definitive answers in this matter, we do propose that these two methods can aid in better comprehending how multiple variables interact with each other in the development of psychological disorders.
Keywords: Antisocial personality disorder; Child abuse; Machine learning; Parental bonding; Statistical analysis.
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