Table 3.

Socio-demographic factors affecting self medication for COVID-19

	Self-medication		No Self-medication		Total		Test statistics	P-value
	n	%	n	%	n	%
Gender
Male	94	40.0	167	42.3	261	41.4	0.315	0.574
Female	141	60.0	228	57.7	369	58.6
TOTAL	235	100.0	395	100.0	630	100.0
Age (years)
20–29	52	22.7	116	32.0	168	28.4	25.855	< 0.0001
30–39	84	36.7	167	46.0	251	42.4
40–49	64	27.9	53	14.6	117	19.8
50–59	27	11.8	27	7.4	54	9.1
≥ 60	2	0.9	0	0.0	2	0.3
	229	100.0	363	100.0	592	100.0
Marital status
Never married	70	28.9	175	42.4	245	37.4	14.680	0.012
Currently married	159	65.7	225	54.5	384	58.6
Domestic partner	2	0.8	2	0.5	4	0.6
Separated	5	2.1	2	0.5	7	1.1
Divorced	1	0.4	1	0.2	2	0.3
Widowed	5	2.1	8	1.9	13	2.0
	242	100.0	413	100.0	655	100.0
Educational status
None	0	0.0	1	0.2	1	0.2	4.849	0.183
Primary	1	0.4	5	1.2	6	0.9
Secondary	1	0.4	9	2.2	10	1.5
Tertiary	240	99.2	400	96.4	640	97.4
	242	100.0	415	100.0	657	100.0
Occupation
Doctor	94	38.7	185	44.9	279	42.7	32.585	0.037
Nurse	96	39.5	131	31.8	227	34.7
Pharmacist	13	5.4	13	3.2	26	4.0
MLSǂ	7	2.9	17	4.1	24	3.7
Health assistant	4	1.6	23	5.7	27	4.1
Record officers	4	1.6	9	2.2	13	2.0
Others**	25	10.3	33	8.1	58	8.8
	243	100.0	411	100.0	654	100.0
House hold size
0–3	106	44.0	158	40.0	264	41.5	1.573	0.455
4–6	120	49.8	204	51.6	324	50.9
7 or more	15	6.2	33	8.4	48	7.5
	241	100.0	395	100.0	636	100.0
Income
< 600,000	8	3.4	37	9.3	45	7.1	30.691	< 0.0001
600,000–1.19 M	51	21.7	95	23.8	146	23.0
1.2 M–2.39 M	78	33.2	150	37.5	228	35.9
2.4 M–5.99 M	54	23.0	92	23.0	146	23.0
6.0 M–11.9 M	42	17.9	22	5.5	64	10.1
> 12 M	2	0.9	4	1.0	6	0.9
	235	100.0	400	100.0	635	100.0

χ² = Pearson Chi-Square test. | t = Student’s T-test | P-value = Probability value | P = Probability value of statistical significance | M = Million |MLS^ǂ = Medical Laboratory Scientist | Others** = Dietician, Engineer, Dentist, Medical Laboratory Technician, Pharm Tech, Physiotherapist, Psychologist, Social worker