Table 5.

Correlates of self-reported likelihood of using again in the future.

	Bivariable tests			Multivariable model
	No weighted %	Yes weighted %	P	aPR	(95% CI)	P
Age – Mean (SE)	25.0 (0.6)	26.3 (0.6)	.130	1.03	(1.01, 1.06)	.015
Sex			.058
Male	74.8*	60.4		1.00
Female	25.2	39.6		1.46	(1.13, 1.89)	.004
Race/Ethnicity			.029
White	37.8	55.6		1.00
Black	4.8	3.5		0.96	(0.52, 1.77)	.896
Hispanic	32.8	16.5		0.68	(0.46, 1.02)	.063
Asian	22.2	15.5		0.91	(0.63, 1.32)	.627
Other/Mixed	2.4	8.8		1.61	(1.00, 2.59)	.048
Sexual Orientation			.200
Heterosexual	88.3	76.2		1.00
Gay/Lesbian	9.1	14.2		1.31	(0.90, 1.91)	.151
Bisexual	2.4	8.2		1.11	(0.86, 1.43)	.429
Other Sexuality	0.2	1.3		0.89	(0.62, 1.27)	.526
Other Drug Use
LSD	14.7	38.2	<.001	1.42	(1.14, 1.76)	.001
Ketamine	8.3	26.4	<.001	1.21	(1.00, 1.47)	.055
Methamphetamine	2.5	3.6	.575	0.90	(0.64, 1.28)	.563

Note. Rao-Scott chi-square was used to determine whether there were bivariable differences, although differences in age, which is a ratio measurement, were determined using linear regression. All variables were then fit as covariates into separate multivariable generalized linear models using Poisson and log link to determine associations with all else being equal. This generated adjusted prevalence ratios (aPRs) and 95% confidence intervals (CIs). A Bonferroni statistical correction was applied to bivariable tests, so results are only deemed statistically significant when p < .0125 (alpha = .05/4 outcomes).