TY - JOUR

T1 - A step-by-step and data-driven guide to index gender in psychiatry

AU - Cipriani, Enzo

AU - Samson-Daoust, Eugénie

AU - Giguère, Charles Edouard

AU - Kerr, Philippe

AU - Lepage, Cécile

AU - Juster, Robert Paul

AU - Consortium

N1 - Publisher Copyright: Copyright: © 2024 Cipriani et al.

PY - 2024/1

Y1 - 2024/1

N2 - Beyond sex as a binary or biological variable, within-sex variations related to sociocultural gender variables are of increasing interest in psychiatric research to better understand individual differences. Using a data-driven approach, we developed a composite gender score based on sociodemographic and psychosocial variables showing sex differences in a sample of psychiatric emergency patients upon admission (N = 1708; 39.4% birth-assigned females; mean age = 40 years; age standard deviation = 14). This gender score was extracted from a confirmatory factor analysis (CFI = 0.966; RMSEA = 0.044, SRMR = 0.030) and could predict a person’s birth-assigned sex with 67% accuracy. This score allowed the further identification of differences on impulsivity measures that were absent when looking solely at birth-assigned sex. Female birth-assigned sex was also associated with higher rates of mood and personality disorder diagnoses, while higher feminine gender scores were related to higher proportions of anxiety and mood disorder diagnoses. By contrast, male birth-assigned sex and higher masculine gender scores were associated with higher proportions of psychotic and substance use disorder diagnoses. Patients with undifferentiated gender scores (i.e., scoring between masculine and feminine threshold defined by terciles) were more represented in the psychotic disorder group. Considering both sex and gender in psychiatric research is essential and can be achieved even when using secondary data to index gender comprised of demographic and psychosocial variables.

AB - Beyond sex as a binary or biological variable, within-sex variations related to sociocultural gender variables are of increasing interest in psychiatric research to better understand individual differences. Using a data-driven approach, we developed a composite gender score based on sociodemographic and psychosocial variables showing sex differences in a sample of psychiatric emergency patients upon admission (N = 1708; 39.4% birth-assigned females; mean age = 40 years; age standard deviation = 14). This gender score was extracted from a confirmatory factor analysis (CFI = 0.966; RMSEA = 0.044, SRMR = 0.030) and could predict a person’s birth-assigned sex with 67% accuracy. This score allowed the further identification of differences on impulsivity measures that were absent when looking solely at birth-assigned sex. Female birth-assigned sex was also associated with higher rates of mood and personality disorder diagnoses, while higher feminine gender scores were related to higher proportions of anxiety and mood disorder diagnoses. By contrast, male birth-assigned sex and higher masculine gender scores were associated with higher proportions of psychotic and substance use disorder diagnoses. Patients with undifferentiated gender scores (i.e., scoring between masculine and feminine threshold defined by terciles) were more represented in the psychotic disorder group. Considering both sex and gender in psychiatric research is essential and can be achieved even when using secondary data to index gender comprised of demographic and psychosocial variables.

UR - http://www.scopus.com/inward/record.url?scp=85183496127&partnerID=8YFLogxK

U2 - 10.1371/journal.pone.0296880

DO - 10.1371/journal.pone.0296880

M3 - Journal article

C2 - 38271402

AN - SCOPUS:85183496127

VL - 19

JO - PLoS ONE

JF - PLoS ONE

SN - 1932-6203

IS - 1

M1 - e0296880

ER -