Driving-related behaviors, attitudes, and perceptions among Australian medical cannabis users: results from the CAMS 20 survey

Table 3 Binary logistic regression model assessing likelihood of driving under the influence of cannabis (DUIC)

Variable	Category	Ref	OR	Lower 95% CI	Upper 95% CI	p
Age			0.44	1.00	0.98	0.442
Gender	Male	Female	1.11	0.80	1.54	0.529
Education	Primary	Undergrad	2.74	0.55	13.74	0.221
	Secondary	Undergrad	1.13	0.71	1.80	0.613
	Trade	Undergrad	1.61	1.10	2.35	0.015
	Postgrad	Undergrad	0.85	0.50	1.44	0.541
Employment	Not employed	FT/PT	0.98	0.58	1.66	0.848
Employment	Other	FT/PT	0.97	0.68	1.38	0.940
User type	Illicit only	Prescr. only	2.06	1.01	4.22	0.049
User type	Dual	Prescr. only	1.73	0.78	3.86	0.178
Admin	Oral only	Inhaled only	0.51	0.33	0.78	0.002
Admin	Oral, inhaled	Inhaled only	0.92	0.50	1.70	0.799
Cannabinoid	Balanced	THC dom	0.62	0.38	1.03	0.063
	Variable	THC dom	0.77	0.54	1.10	0.146
	CBD dom	THC dom	0.33	0.18	0.63	< 0.001
NMC impairs	No	Yes	3.83	2.47	5.95	< 0.001
MC impairs	No	Yes	0.91	0.54	1.55	0.733
RDT deter	No	Yes	1.90	1.40	2.58	< 0.001

Abbreviations: MC impairs, “Do you believe medicinal cannabis impairs driving?”; NMC impairs, “Do you believe recreational cannabis impairs driving?”; RDT deter, “Does the presence of RDT (roadside drug testing) deter you from DUIC?”; bolded ORs are significant at the p < 0.05 level

ISSN: 2522-5782