Knowledge and attitude on infant vaccination among university staff in Malaysian public university

Figures & data

Table 1. Distribution of sociodemographic

	Frequency (%)	Mean
Gender
Male	29 (29.90)	1.70
Female	68 (70.10)
Race
Malay	94 (96.90)
Chinese	2 (2.10)	1.04
Indian	1 (1.00)
Age
<35	47 (48.50)	1.52
≥35	50 (51.50)
Family Monthly Income	33 (34.00)
<RM5000
RM 5000- RM 10000	39 (40.20)	1.92
>RM 10000	25 (25.80)
Decision Maker for Immunization
Friends	3 (3.10)
Health care professionals	10 (10.30)	2.84
Parents	84 (86.60)
From where your children get Vaccination
Government hospital/clinic	68 (70.1)	1.30
Private hospital/clinic	29 (29.9)
Source of information regarding Immunization program
Television	43 (44.3)
Internet	64 (66.0)
Radio	17 (17.5)	1.90
Newspaper	23 (23.7)
Doctor	75 (77.3)
Family/ Friend	48 (49.5)
Educational Level
UPSR	1 (1.00)
SRP/PMR/SPM/STPM	16 (16.5)	2.81
Diploma/Degree /Master/PhD	80 (82.5)
Type of Faculty
Science-based	48 (49.50)	1.51
Non-science-based	49 (50.50)
Occupation
Academic	30 (30.90)	1.69
Non-academic	67 (69.10)

Figure 1. Prevalence of staff that refuse infant vaccination.

Table 2. Level of knowledge and attitude

Variables	N	(%)	Mean (±SD)	Min-Max
Knowledge
Low	78	80.4	85.57 (±11.57)	53–100
Moderate	17	17.5
High	2	2.1
Total	97	100
Attitude
High	47	48.5	82.76) (±11.29)	50–100
Moderate	49	50.5
Low	1	1.0
Total	97	100

Based on Table 3, there was a significant association between educational level and the level of knowledge (p-value = .019). Table 4 shows that there was no significant association between socio-demographic and attitude (p-value > 0.05).

Table 3. Association between socio-demographic and knowledge

	Knowledge, n (%)		^aX^2
Demographic variable	High	Moderate	Low	*p-Value
Gender
Male	22 (75.86)	6 (20.69)	1 (3.45)	.728	.695
Female	56 (82.35)	11 (16.18)	1 (1.47)
Total	78 (80.41)	17 (17.53)	2 (2.10)
Age
<35	39 (83.00)	8 (17.02)	0 (0.00)	1.968	.374
≥35	39 (78.00)	9 (18.00)	2 (4.00)
Total	78 (80.41)	17 (17.53)	2 (2.10)
Educational Level
UPSR	1 (100.00)	0 (0.00)	0 (0.00)
PMR/SPM/STPM	13 (81.25)	1 (6.25)	2 (12.50)	11.791	*.019
Diploma/Degree/Master/PhD	64 (80.00)	16 (20.00)	0 (0.00)
Total	78 (80.41)	17 (17.53)	2 (2.10)
Monthly Income
<RM 5000	26 (78.79)	6 (18.18)	1 (3.03)
RM 5000-RM 10000	32 (82.05)	7 (17.95)	0 (0.00)	1.479	.830
>RM 10000	20 (80.00)	4 (16.00)	1 (4.00)
Total	78 (80.41)	17 (17.53)	2 (2.10)

^aFisher’s Exact Test.

*p-value <0.05 is significant.

Table 4. Association between socio-demographic and attitude

	Knowledge, n (%)
Demographic variable	High	Moderate	Low	^aX2	*p-Value
Educational Level
UPSR	1 (100.00)	0 (0.00)	0 (0.00)
PMR/SPM/STPM	13 (81.25)	1 (6.25)	2 (12.50)	11.791	*.019
Diploma/Degree/Master/PhD	64 (80.00)	16 (20.00)	0 (0.00)
Total	78 (80.41)	17 (17.53)	2 (2.10)
Monthly Income
<RM 5000	26 (78.79)	6 (18.18)	1 (3.03)
RM 5000-RM 10000	32 (82.05)	7 (17.95)	0 (0.00)	1.479	.830
≥RM 10000	20 (80.00)	4 (16.00)	1 (4.00)
Total	78 (80.41)	17 (17.53)	2 (2.10)

^aPearson Chi-square.

*p-value <0.05 is significant.

Table 5. Comparison of knowledge and attitude between staff in science-based and non-science-based faculty

Demographic Variable	Knowledge, n (%)		aX^2	*p-Value
	Science-based Non-science-based
Knowledge
High	41 (85.4)	37 (75.5)	2.725	.256
Moderate	7 (14.6)	10 (20.4)
Low	0 (0.0)	2 (4.1)
Attitude
High	23 (47.9)	24 (49.0)	1.031	.597
Moderate	25 (52.1)	24 (49.0)
Low	0 (0.0)	1 (2.0)

^aPearson Chi-square.

*p-value <0.05 is significant.