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Logistic regression with machine learning sheds light on the problematic sexual behavior phenotype

There has been a longstanding debate about whether the mechanisms involved in problematic sexual behavior (PSB) are similar to those observed in addictive disorders, or related to impulse control or compulsivity. The aim of this report was therefore to contribute to this debate by investigating the association between PSB, addictive disorders (internet addiction, compulsive buying), other measures associated with the construct known as reward deficiency (attention deficit disorder and personality disorder), and obsessive-compulsive disorder (OCD) in young adults in post-secondary education. A Canadian University Office of the Registrar invited 68846 eligible students and postdoctoral fellows. Out of 4710 expressing interest in participating, 3359 completed on-line questionnaires and 1801 completed the Mini-International Neuropsychiatric Interview (MINI). PSB was measured by combining those screening positive (greater or equal to 6) on the Sexual Addiction Screening Test-Revised (SAST-R) Core with those self-reporting monthly PSB. Current mental health condition(s) and childhood trauma were measured by self-report. OCD was assessed by a combination of self-report and MINI data. 12.18% (407/3341) of participants screened positive on the SAST-R Core. On logistic regression analysis (conventional and by machine learning), OCD, attention deficit, internet addiction, a family history of PSB, childhood trauma, compulsive buying and male gender were associated with PSB. On multiple correspondence analysis (MCA), OCD appeared to cluster separately from the other measures, and the pattern of data differed by gender.