. Author manuscript; available in PMC: 2024 Feb 9.

Published in final edited form as: Curr Psychol. 2021 May 20;42(6):5075–5087. doi: 10.1007/s12144-021-01812-6

Table 3.

Unconditional and conditional models testing the confounding effects of victimization, cybervictimization, and non-parental adult support in the association between sexual identity and substance use

	Females							Males							Sex differences
	Unconditional Model			Conditional Model				Uncoiliditional Model			Conditional Model				Direct Assoc.	IndirectAssoc.
	B	SE	OR	B	SE	OR	% Reduction	B	SE	OR	B	SE	OR	% Reduction	Wald χ²	Wald χ²
Binge drinking
LGBQ	.59	.30	1.81^*	.48	.29	1.62		−.73	.68	.48	−.98	.67	0.37	–	7.27^**
Victimization				.37	.12	1.44^**	14.19%^*				.71	.14	2.03^***	–	2.36
Cybervictimization				.37	.25	1.45	4.83%				.63	.40	1.88	–	1.32
Non-Parental Adult Support				.00	−.05	1.00	.25%				.05	.07	1.06	–	0.51
Marijuana use
LGBQ	1.01	.31	2.76^**	.86	.29	2.35^**		.44	.27	1.56	.19	.29	1.21	–	2.01
Victimization				.37	.07	1.45^***	9.07%^**				.59	.14	1.81^***	–	0.61
Cybervictimization				.15	.28	1.16	1.39%				−.40	.28	0.67	–	1.04
Non-Parental Adult Support				−.10	.07	0.90	5.18%				−.03	.04	0.97	–	1.22
Illicit drug use
LGBQ	.97	.25	2.64^***	.77	.24	2.16^**		.93	.39	2.53^*	.55	.38	1.74		0.14
Victimization				.52	.10	1.68^***	12.47%^**				.71	.11	204^***	35.77%^***	0.29	6.61^*
Cybervictimization				.36	.28	1.43	3.35%				−.13	.39	0.88		0.50
Non-Parental Adult Support				−.09	.06	0.91	4.79%				−.11	.06	0.90	5.63%	0.06	0.06
Poly sub stance use
LGBQ	.79	.19	2.14^***	.64	.19	1.89^**		.58	.21	1.79^**	.30	.22	1.33		0.02
Victimization				.36	.07	1.44^***	10.67%^**				.63	.09	1.87^***	45.97%^***	3.57^†	8.22^**
Cybervictimization				.13	.21	1.14	1.51%				.03	.26	1.03		0.01
Non-Parental Adult Support				−.12	.05	1.13^*	7.76%^*				−.09	.03	1.10^**	7.07%	0.01	0.01

Note.

^***

p < .001;

^**

p < .01;

p < .05;

^†

p < .10.

% Reduction = percentage reduction in coefficients of LGBQ attributable to the confounder variable. N_female range = 948–1049 and N_male range = 796–891. Coefficients are adjusted by age, race and ethnicity. Wald Chi-square tests were employed by constraining each direct and indirect association of sexual identity and the confounders on the outcomes to be equal across females and males. A significant wald chi square indicates that beta coefficients are significantly different between females and males