Non-Medical Methylphenidate Use Among Medical Students: Prevalence and Association with Type A Personality Traits
Mesut Sari1, Mustafa Çobaner1, Canan Ayvat2
1Department of Child and Adolescent Psychiatry, Bolu Abant Izzet Baysal University Medical Faculty, Bolu, Turkey.
Aim:
To estimate the prevalence of non-medical methylphenidate use (NMU) in Turkish medical students and its association with Type A personality.
Method:
This cross-sectional study surveyed 600 of 1,275 invited medical students (47.1%) at a single public medical faculty in Türkiye in 2025. A sociodemographic/methylphenidate-use questionnaire and the Type A Personality Traits Scale were administered. NMU was operationalized as methylphenidate use for academic or social performance enhancement in students without clinician-diagnosed ADHD, regardless of prescription status. Type A differences were tested with MANOVA. Given the low event count, Firth penalized logistic regression served as the primary multivariable analysis, with standard logistic regression reported for comparison.
Results:
Lifetime methylphenidate use was 6.8% (n = 41) and current use 2.2% (n = 13); 23 students (3.8%) met NMU criteria, most commonly for academic enhancement. Awareness of methylphenidate and of peer use rose markedly from preclinical to clinical years, whereas actual use did not. Type A scores did not differ between NMU and non-NMU students. In the Firth model, peer NMU awareness and past psychiatric consultation remained associated with NMU; tentative inverse associations for male sex and the standardized Type A score should be interpreted as exploratory given the low events-per-variable ratio (3.3).
Conclusion:
NMU prevalence was low and more closely linked to contextual correlates-peer exposure and prior psychiatric contact-than to Type A traits, which did not show a robust or stable association across analyses. Multivariable findings require replication. Prevention may benefit from focusing on peer-network dynamics and mental-health support rather than personality-based risk profiling.
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