Knowledge, acceptance and perception on COVID-19 vaccine among Malaysians: A web-based survey

Nurul Azmawati Mohamed; Hana Maizuliana Solehan; Mohd Dzulkhairi Mohd Rani; Muslimah Ithnin; Che Ilina Che Isahak

doi:10.1371/journal.pone.0256110

. 2021 Aug 13;16(8):e0256110. doi: 10.1371/journal.pone.0256110

Knowledge, acceptance and perception on COVID-19 vaccine among Malaysians: A web-based survey

Nurul Azmawati Mohamed ^1,^#, Hana Maizuliana Solehan ^1,^*, Mohd Dzulkhairi Mohd Rani ^1,^#, Muslimah Ithnin ^1,^#, Che Ilina Che Isahak ^1,^#

Editor: Eman Sobh²

PMCID: PMC8362951 PMID: 34388202

Abstract

Background

Coronavirus disease 2019 or COVID-19 is caused by a newly discovered coronavirus, SARS-CoV-2. The Malaysian government has planned to procure COVID-19 vaccine through multiple agencies and companies in order to vaccinate at least 70% of the population. This study aimed to determine the knowledge, acceptance and perception of Malaysian adults regarding the COVID-19 vaccine.

Methodology

An online survey was conducted for two weeks in December 2020. A bilingual, semi-structured questionnaire was set up using Google Forms and the generated link was shared on social media (i.e., Facebook and WhatsApp). The questionnaire consisted of questions on knowledge, acceptance and perception of COVID-19 vaccine. The association between demographic factors with scores on knowledge about COVID-19 vaccine were analysed using the Mann-Whitney test for two categorical variables, and the Kruskal-Wallis test used for more than two categorical variables.

Results

A total of 1406 respondents participated, with the mean age of 37.07 years (SD = 16.05) years, and among them 926 (65.9%) were female. Sixty two percent of respondents had poor knowledge about COVID-19 vaccine (mean knowledge score 4.65; SD = 2.32) and 64.5% were willing to get a COVID-19 vaccine. High knowledge scores associated with higher education background, higher-income category and living with who is at higher risk of getting severe COVID-19. They were more likely to be willing to get vaccinated if they were in a lower age group, have higher education levels and were female.

Conclusion

Even though knowledge about vaccine COVID-19 is inadequate, the majority of the respondents were willing to get vaccinated. This finding can help the Ministry of Health plan for future efforts to increase vaccine uptake that may eventually lead to herd immunity against COVID-19.

Introduction

Coronavirus disease 2019 or COVID-19 is caused by a newly discovered coronavirus, SARS- CoV-2. This new infection was believed to have emerged from Wuhan City, Hubei Province, China in December 2019. On March 11 2020, the World Health Organization (WHO) declared COVID-19 as a pandemic [1]. Until early June 2021, this emergent disease has infected more than 170 million people around the world and caused more than 3 million deaths [1]. The rate of infection had not seem to slow down in the majority of the affected countries, and varying degrees of lockdowns have been issued in the effort to contain the spread of the virus. In Malaysia, a resurgence of infections began in late September 2020 with a rapid increase in the number of infections, at more than 4000 cases daily since mid-January 2021 [2]. As of June 15 2021, Malaysia has reported 3968 COVID-19 deaths or a 0.6 percent fatality rate out of 662,457 cases [2].

Currently, there are more than 100 candidates of COVID-19 vaccines under development [3]. About 11 months after the emergence of the disease, the Food and Drug Administration (FDA) has approved the use of Pfizer/BioNTech and Moderna COVID-19 vaccines in a mass immunization programme [4]. Phase three clinical trials for Pfizer/BioNTech vaccines enrolled 43,661 participants, while Moderna vaccines involving 30,000 participants [5, 6]. The clinical trial results showed that these vaccines can protect recipients from a COVID-19 infection by forming antibodies and providing immunity against a COVID-19 virus [4]. There are also other companies in the race for vaccine development and in the final stages of trials. It is expected that many vaccines will be ready for distribution by early or mid-2021 [7]. The United Kingdom was among the first countries that have started mass immunization COVID-19 vaccine [8]. Apart from Moderna and Pfizer that use mRNA as the active substance, other vaccines use various other types of antigen such as viral vector, attenuated virus and inactivated virus [9]. The use of mRNA is a new technology for vaccine development, where the vaccine contains messenger RNA instructs cells to produce a protein that acts as an antigen.

As safe and effective vaccines are being made available, the next challenge will be dealing with vaccine hesitancy. Vaccine hesitancy, identified as one of the ten most important current health threats, is defined as the reluctance or refusal to vaccinate despite the availability of vaccines [10]. Wong et al. (2011) conducted a population-based study in Hong Kong on the acceptance of the COVID-19 vaccine using the health belief model (HBM) and found that perceived severity, perceived vaccine benefits, cues to action, self-reported health outcomes, and trust were all positive indicators of acceptance. Perceived vulnerability to infection had no significant association with acceptance, whereas perceived access barriers and harm were negative predictors [11]. In addition, another community-based study found that people’s desire to get vaccinated against COVID-19 has fallen dramatically during the pandemic, with over half of the population were hesitant or unwilling to get vaccinated [12].

Misinformation and unsubstantiated rumours regarding COVID-19 vaccines have been around and repeatedly shared on social media platforms even before the release of an effective vaccine [13]. The use of mRNA genetic material in several vaccines have been sensationalized by some, with the false claims that the vaccine can alter human DNA [14] Additionally, the rapid development of COVID-19 vaccines has reportedly raised concerns regarding the safety and long term effects, even among the medical staffs [15]. Findings from studies among healthcare workers (HCWs) are alarming, as a small percentage of HCWs do not intend to get the COVID-19 vaccine [16, 17].

The Malaysian government has procured COVID-19 vaccine through a government-to- government deal with the Republic of China, direct purchase from pharmaceutical companies and the COVID-19 Global Vaccine Access (Covax) Facility. With these arrangements, Malaysia is expected to receive its first batch of COVID-19 vaccines to immunise 6.4 million people as early as end of February 2021 [18]. We embarked on this study to determine the knowledge, acceptance and perception of the COVID-19 vaccine among the Malaysian adult population. The findings from this study will provide data and crucial information for the government to find strategies to increase public understanding and the uptake of COVID-19 vaccine.

Methodology

This cross-sectional, online population-based survey was conducted from 1^st to 15^th December 2020. The study sample size was estimated using the Raosoft sample size calculator. A minimum of 385 participants were required at a margin of error of 5%, a 95% confidence interval (CI), and a population size of 32.6 million at a 50% response distribution. A bilingual, semi-structured questionnaire was adopted and adapted from Reiter et al. (2020) [19], and then set up via Google Forms. The access link was then shared via online platforms including Facebook and WhatsApp, initiated by all project members. The sharing was escalated by our family members, friends, colleagues, and acquaintances. The inclusion criteria for respondents’ eligibility include those more than 18 years old, and an understanding of the Malay or English language. The respondents were requested to take part in the survey by completing the questionnaire without any time restrictions. Reliability measurement was tested earlier on 50 respondents for both the English and Malay version of the questionnaire. Cronbach alpha values for knowledge, perceived susceptibility, perceived barriers and perceived benefits were 0.718, 0.714, 0.714 and 0.834, respectively for the English version. Whereas the Cronbach alpha values for the Malay version were 0.665, 0.688, 0.787 and 0.889, respectively.

The questionnaire consists of four sections: Section A on demographic and COVID-19 status, Section B on the knowledge on COVID-19 vaccine, Section C on the acceptance of COVID- 19 vaccine and Section D on perception based on the Health Belief Model (HBM). For section B (knowledge), participants were given three options: Yes, No and Do not know. One mark was given for any correct answer and 0 mark for any wrong answer and do not know answers. The maximum knowledge score was 10, and those who obtained marks above the median of the total score (6 and above) will be categorized as having good knowledge. Section C consists of questions on the willingness to take the vaccine and the reason, cost of the vaccine and factors influencing the decision. For Section D, five options were given: strongly agree, agree, neutral, disagree and strongly disagree, for perceived susceptibility and barriers. The questionnaire used in this study is not published under a CC-BY license, and other researchers may cite the related article when referencing the questionnaire.

Ethical consideration

This research was approved by the Ethics Committee of Universiti Sains Islam Malaysia with the code project of USIM/JKEP/2021-126. The subjects consented to participate in this survey by volunteering to complete and submit the questionnaire.

Study variables

Dependent variables

COVID-19 knowledge score.

Acceptance to COVID-19 vaccine.

Independent variables

Age, gender, educational status, income category, presence of any chronic diseases, history of been infected with COVID-19, history of family members or friends been infected with COVID-19, living with someone who is at higher risks of getting severe COVID-19 including living with elderly or family members with comorbidity or having long-term medical follow up or chronic medication.

Data analysis

All data were entered into the Microsoft Excel spreadsheet and then loaded and coded into the SPSS version 23 software for final analysis. Simple descriptive analyses, including frequencies, percentages, mean, and standard deviation (SD) were computed for demographic characteristics, the knowledge scores regarding COVID-19 vaccine, and the perceived susceptibility, barriers and benefits to the COVID-19 vaccine. Histogram with normality curve and Kolmogorov–Smirnov test was used to check for the normal distribution of data in this study. Since the data were not normally distributed, the non-parametric tests were used for inferential analysis. The association between demographic factors with scores on knowledge regarding COVID-19 vaccine was analysed using the Mann-Whitney test for two categorical variables, and the Kruskal-Wallis test used for more than two categorical variables. A Chi-square test was carried out to determine the significant level of association and the relationship between the categorical independent variables of demographic factors and outcome variables of acceptance to the COVID-19 vaccine. Statistical significance was defined at p <0.05.

Results

Demographic data

A total of 1406 respondents participated in this online survey. The mean age was 37.07 years (SD = 16.05; range = 18–81) and 926 (65.9%) of the respondents were female. The detailed characteristics of the respondents are shown in Table 1.

Table 1. Socio-demographic characteristics (N = 1406).

No.	Characteristic		n	%
1.	Age	Mean: 37.07 (SD = 16.054)^a
		Median: 35 (IQR = 22–49)
		Range: 18–91
2.	Age group	18–29	602	42.8
		30–39	214	15.2
		40–49	259	18.4
		50–59	156	11.1
		60 and above	175	12.4
3. Gender		Male	480	34.1
		Female	926	65.9
4. Education		No formal education	2	0.1
		Secondary Education	80	5.7
		Certificate or Diploma	271	19.3
		Bachelor’s Degree	775	55.1
		Postgraduate studies (Master’s or PhD)	278	19.8
5. Income (RM)		Mean: 11249.77 (SD = 29565.239) a [USD 2717 (SD = 7140)]
		Median: 8000 (IQR = 4000–11000) a [USD 1932 (IQR = 966–2656)]
		Range: 0–800000 [USD 0–193190]
6. Income category^*		B40: Less than RM 4850	408	29.0
		M40: RM4851-RM10970	639	45.4
		T20: Above RM 10971	359	25.5
7. Chronic diseases		Hypertension	148	10.5
		Hypercholesterolemia	134	9.5
		Diabetes mellitus	93	6.6
		Chronic Lung Diseases	52	3.7
		Heart Diseases	36	2.6
		Cancer	16	1.1
		Chronic Kidney Diseases	4	0.3
		Others	44	3.1

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a Shapiro-Wilk p <0.001

*Department of Statistics, Malaysia, 2020. Household Income and Basic Amenities [20]

Knowledge regarding COVID-19 vaccine

A total of 872 (62.0%) of the respondents had poor knowledge about COVID-19 vaccine (Fig 1). The statement “COVID-19 vaccines will be given via injection”, had the most percentage of correct answers (82.1%). The statement with the lowest percentage of correct answers was “Everyone including children can receive COVID-19 vaccination” and “COVID-19 vaccine can also protect us from influenza,” in which only 14.7% and 18.5% of respondents gave the correct answer. Table 2 shows the knowledge questions and scores for each statement.

Table 2. Knowledge about COVID-19 vaccine (N = 1406).

No.	Mean (SD)	Correct		Wrong/Do not Know
		n	%	n	%
1. COVID-19 vaccines use inactivated coronavirus as the antigen.^*	0.40 (0.489)	557	39.6	849	60.4
2.COVID-19 vaccines use genetic material from coronavirus as the active ingredient. ^*	0.37 (0.234)	527	37.5	879	62.5
3. COVID-19 vaccine stimulates our body to produce antibody, T cells and memory cells to combat COVID-19 infection.^*	0.73 (0.446)	1021	72.6	385	27.4
4. COVID-19 vaccine protects the receiver from getting COVID-19 infection. ^*	0.74 (0.438)	1043	74.2	363	25.8
5. COVID-19 vaccination may protect other people who do not receive vaccine. ^*	0.43 (0.495)	598	42.5	808	57.5
6. Vaccine production involves animal study, 3 phases of clinical trials that cover thousands of people and evaluated by the authority to ensure the vaccine efficacy and safety. ^*	0.58 (0.493)	820	58.3	586	41.7
7. COVID-19 vaccines will be given via injection. ^*	0.82 (0.384)	1154	82.1	252	17.9
8. COVID-19 vaccines do not have side effects.	0.25 (0.431)	346	24.6	1060	75.4
9. Everyone including children can receive COVID-19 vaccination.	0.46 (0.499)	207	14.7	1199	85.3
10. COVID-19 vaccine can also protect us from influenza.	0.18 (0.388)	260	18.5	1146	81.5

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*Yes is the correct answer

Table 3 shows the association between demographic factors and knowledge scores. Higher education level, higher income and living with high-risk individuals were significantly associated with higher knowledge score.

Table 3. Association between demographic factors and knowledge score (N = 1406).

Variables		Mean (SD)	Median (IQR)	p-value
Age group	18–29	4.79 (2.167)	5 (3)	.083^a
	30–39	4.60 (2.327)	5 (3)
	40–49	4.86 (2.290)	5 (4)
	50–59	4.25 (2.231)	4 (4)
	60 and above	4.65 (2.017)	5 (3)
Gender	Male	4.63 (2.326)	5 (3)	.786^b
	Female	4.66 (2.145)	5 (3)
Education	No formal education	2.50 (3.536)	2.5 (0)	< .001^b ^*
	Secondary	3.98 (2.444)	4 (4)
	Diploma	4.30 (2.187)	5 (3)
	Degree	4.70 (2.194)	5 (3)
	Master/PhD	5.04 (2.100)	5 (3)
Income category	B40: Less than RM 4850	4.35 (2.285)	4 (3)	< .001^b ^*
	M40:RM4851-RM10970	4.62 (2.160)	5 (3)
	T20:Above RM 10971	5.03 (2.135)	5 (3)
Chronic diseases	Yes	4.68 (2.207)	5 (3)	.317^b
	No	4.53 (2.212)	5 (3)
Been infected with COVID-19	Yes	4.68 (2.207)	5 (3)	.296^b
Been infected with COVID-19	No	4.53 (2.212)	5 (3)
Family members or friends been infected with COVID-19	Yes	4.65 (2.205)	5 (3)	.815^b
Family members or friends been infected with COVID-19	No	4.59 (2.234)	5 (3)
Live with someone who is at higher risk of getting severe COVID-19	Yes	4.65 (2.205)	5 (3)	.003^b ^*
	No	4.59 (2.234)	5 (3)

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a Kruskal-Wallis test

b Mann-Whitney test

* significant at p-value < .05

Acceptance towards COVID-19 vaccine

Almost two thirds of the respondents (64.5%) indicated willingness to get vaccinated (Fig 2). The majority agreed that the government should provide free vaccination to high-risk groups. More than 70% of the respondents would pay a maximum of RM 100 for the vaccine and only a small proportion (4.6%) reported not being able to afford the vaccine at any price. The effectiveness of the vaccine and suggestions from the Ministry of Health were the factors that most strongly influenced the decision to get the vaccination. Table 4 shows the details of the questions and their scores.

Table 4. Questions on factors influencing acceptance for COVID-19 vaccine (N = 1406).

No.	Statements		n	%
1.	In your opinion, should the government provide free COVID-19 vaccine to the high-risk groups?	Yes	1272	90.5
		No	30	2.1
		Do not know	46	3.3
		Others	58	4.1
2.	What is the most you would pay out of pocket to get the COVID-19 vaccine?	I can’t afford to pay at all	65	4.6
		less than RM50 [USD 12]	550	39.1
		RM50 -RM100 [USD 12–24]	484	34.4
		RM101-RM150 [USD 24–36]	126	9.0
		More than RM150 [USD 36]	46	3.3
		I don’t mind any cost	128	9.1
		Others	7	0.5
3.	What are the factors that influence your decision to take the COVID-19 vaccine?	Effectiveness	1028	73.1
		Suggestion from doctors or Ministry	874	62.2
		of Health
		Number of positive COVID-19 cases	691	49.1
		Adverse effects	564	40.1
	*This question allows multiple responses	Number of deaths due to COVID-19	542	38.5
		Health status	539	38.3
		Cost	482	34.3
		Duration of protection	470	33.4
		Age	414	29.4
		Type of vaccine	362	25.7
		Number of Vaccine doses	313	22.3
		Country that produces the vaccine	263	18.7
		Suggestion from friends or family	203	14.4
		members
		Others	43	3.1

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Table 5 shows the association of demographic factors and the acceptance to COVID-19 vaccines. Lower age group, higher education level, female, and not having chronic diseases were significantly associated with acceptance to COVID-19 vaccine.

Table 5. Association between demographic factors and acceptance to COVID-19 vaccine (N = 1406).

Variables		Response, n (%)					p-value^a
Variables		Strongly disagree	Disagree	Neutral	Agree	Strongly agree	p-value^a
Age group	18–29	25 (37.3)	15 (16.9)	130 (37.8)	144 (35.1)	288 (58.1)	. < .001^*
	30–39	11 (16.4)	18 (20.2)	41 (11.9)	76 (18.5)	68 (13.7)
	40–49	14 (20.9)	19 (21.3)	63 (18.3)	84 (20.5)	79 (15.9)
	50–59	6 (9.0)	11 (12.4)	45 (13.1)	53 (12.9)	41 (8.3)
	60 and above	11 (16.4)	26 (29.2)	65 (18.9)	53 (12.9)	20 (2.0)
Gender	Male	34 (50.7)	28 (31.5)	112 (32.6)	130 (31.7)	176 (35.5)	.035^*
Gender	Female	33 (49.3)	61 (68.5)	232 (67.4)	280 (68.3)	320 (64.5)	.035^*
Education	No formal education	0	0	2 (0.6)	0	0	. 022^*
	Secondary Education	6 (9.0)	8 (9.0)	14 (4.1)	21 (5.1)	31 (6.3)
	Certificate or Diploma	4 (6.0)	15 (16.9)	68 (19.8)	87 (21.2)	97 (19.6)
	Bachelor’s degree	37 (55.2)	36 (40.4)	188 (54.7)	233 (56.8)	281 (56.7)
	Postgraduate studies	20 (29.9)	30 (33.7)	72 (20.9)	69 (16.8)	87 (17.5)
Income category ^#	B40	20 (29.9)	21 (23.6)	102 (29.7)	109 (26.6)	156 (31.5)	.356
	M40	26 (38.8)	46 (51.7)	165 (48.0)	184 (44.9)	218 (44.0)
	T20	21 (31.3)	22 (24.7)	77 (22.4)	117 (28.5)	122 (24.6)
Chronic diseases	Yes	11 (16.4)	31 (34.8)	94 (27.3)	99 (24.1)	81 (16.4)	< .001^*
Chronic diseases	No	56 (83.6)	58 (65.2)	250 (72.7)	311 (75.9)	414 (83.6)	< .001^*
Been infected with COVID-19	Yes	0	1 (1.1)	2 (0.6)	1 (0.2)	0	.158
Been infected with COVID-19	No	67 (100)	88 (98.9)	342 (99.4)	409 (99.8)	496 (100)	.158
Familymembers or friends been infected with COVID-19	Yes	5 (7.5)	12 (13.5)	37 (10.8)	41 (10.0)	45 (9.1)	.667
Familymembers or friends been infected with COVID-19	No	62 (92.5)	77 (86.5)	307 (89.2)	369 (90.0)	451 (90.9)	.667
Live with someone who is at higher risk of getting severe COVID-19	Yes	23 (34.3)	31 (34.8)	107 (31.1)	119 (29.0)	169 (34.1)	.515
	No	44 (65.7)	58 (65.2)	237 (68.9)	291 (71.0)	327 (65.9)	.515

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a Chi-square test

*p < .05

^# Department of Statistics, Malaysia, 2020. Household Income and Basic Amenities [20]

Perceived susceptibilities, barriers, benefits, and cues to action towards COVID-19 vaccine

About 55.9% perceived that they were able to spread the virus to other people and 30% of the respondents perceived that they were susceptible to get severe COVID-19 infection About 75% did not agree that COVID-19 vaccine could cause infection. More than half were worried about the vaccine’s adverse effects and almost one third of them agreed that scary information about COVID-19 vaccine was rampant on social media. The majority believed that the vaccine could protect themselves and other people who are not vaccinated. Almost half were neutral in terms of vaccine cost and safety. Table 6 provides details of the perception scores. All components in HBM have a significant association with acceptance towards COVID-19, as shown in Table 7.

Table 6. Perception on susceptibilities, severity, barriers and benefits, and cues to action (N = 1406).

No.	Statements	Strongl y agree, n (%)	Agree,	Neutral,	Disagree,	Strongly disagree, n (%)
No.	Statements	Strongl y agree, n (%)	n (%)	n (%)	n (%)	Strongly disagree, n (%)
Perceived Susceptibilities
I can spread the virus to other people		226 (16.1)	560 (39.8)	355 (25.2)	151 (10.7)	114 (8.1)
Perceived Severity
I am at risk of getting a severe COVID-19 infection.		88 (6.3)	335 (23.8)	514 (36.6)	310 (22.0)	159 (11.3)
Perceived Barriers
1. COVID-19 vaccine may cause infection		45 (3.2)	180 (12.8)	636 (45.2)	636 (45.2)	418 (29.7)
2. COVID-19 vaccine may not be effective		52 (3.7)	422 (30.0)	645 (45.9)	236 (16.8)	51 (3.6)
3. I am worried about the adverse effects of the vaccine		170 (12.1)	579 (41.2)	476 (33.9)	140 (10.0)	41 (2.9)
4. I am not sure whether or not I have to get the vaccine		55 (3.9)	302 (21.5)	466 (33.1)	389 (27.7)	194 (13.8)
5. I don’t have time to get the vaccine		16 (1.1)	46 (3.3)	327 (23.3)	620 (44.1)	397 (28.2)
6. I don’t have money to buy the vaccine		34 (2.4)	126 (9.0)	554 (39.4)	481 (34.2)	211 (15.0)
7. Scary information about COVID-19 vaccines are rampant on social media		86 (6.1)	351 (25.0)	481 (34.2)	309 (22.0)	179 (12.7)
8. It will be difficult to get vaccine from nearby clinic due to high demand		118 (8.4)	432 (30.7)	512 (36.4)	251 (17.9)	93 (6.6)
Perceived Benefits
1. Vaccine protects me from getting infected		396 (28.2)	740 (52.6)	219 (15.6)	25 (1.8)	26 (1.8)
2. Vaccine also protects other people who are vaccinated not		384 (27.3)	654 (46.5)	239 (17.0)	90 (6.4)	39 (2.8)
3. After vaccination, I can lead a normal lifestyle		281 (20.0)	559 (39.8)	422 (30.0)	111 (7.9)	33 (2.3)
Cues to action
1. Affordable cost		121 (8.6)	366 (26.0)	787 (56.0)	94 (6.7)	38 (2.7)
2. Safe		213 (15.1)	506 (36.0)	581 (41.3)	77 (5.5)	29 (2.1)
3. It is recommended by doctors and MOH		330 (23.5)	685 (48.7)	336 (23.9)	32 (2.3)	23 (1.6)
4. Good information about vaccine in the mass media		260 (18.5)	561 (39.9)	441 (31.4)	97 (6.9)	47 (3.3)

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Table 7. Association between perception on susceptibilities, severity, barriers and benefits, and cues to action with acceptance towards COVID-19 vaccine (N = 1406).

Perception theme	Statements		Acceptance, n (%)					p-value
Perception theme	Statements		Strongly disagree	Disagree	Neutral	Agree	Strongly agree
Perceived Susceptibilities	1. I can spread the virus to other people	Strongly disagree	13 (19.4)	10 (11.2)	22 (6.4)	34 (8.3)	35 (7.1)	< .001*
		Disagree	8 (11.9)	12 (13.5)	50 (14.5)	45 (11.0)	36 (7.3)
		Neutral	20 (29.9)	25 (28.1)	116 (33.7)	93 (22.7)	101 (20.4)
		Agree	19 (28.4)	33 (37.1)	119 (34.6)	195 (47.6)	194 (39.1)
		Strongly agree	7 (10.4)	9 (10.1)	37 (10.8)	43 (10.5)	130 (26.2)
Perceived Severity	2. I am at risk of getting a severe COVID-19 infection.	Strongly disagree	17 (25.4)	14 (15.7)	42 (12.2)	33 (8.0)	53 (10.7)	< .001*
		Disagree	11 (16.4)	25 (28.1)	82 (23.8)	93 (22.7)	99 (20.0)
		Neutral	24 (35.8)	26 (29.2)	148 (43.0)	155 (37.8)	161 (32.5)
		Agree	12 (17.9)	21 (23.6)	60 (17.4)	113 (27.6)	129 (26.0)
		Strongly agree	3 (4.5)	3 (3.4)	12 (3.5)	16 (3.9)	54 (10.9)
Perceived Barriers	3. COVID-19 vaccine may cause infection	Strongly disagree	13 (19.4)	1 (1.1)	11 (13.2)	22 (5.4)	80 (16.1)	< .001*
		Disagree	11 (16.4)	10 (11.2)	58 (16.9)	144 (35.1)	195 (39.3)
		Neutral	21 (31.3)	39 (43.8)	224 (65.1)	188 (45.9)	164 (33.1)
		Agree	12 (17.9)	32 (36.0)	40 (11.6)	51 (12.4)	45 (9.1)
		Strongly agree	10 (14.9)	7 (7.9)	11 (3.2)	5 (1.2)	12 (2.4)
	4. COVID-19 vaccine may not be effective	Strongly disagree	8 (11.9)	1 (1.1)	3 (0.9)	5 (1.2)	34 (6.9)	< .001*
		Disagree	7 (10.4)	6 (6.7)	22 (6.4)	71 (17.3)	130 (26.2)
		Neutral	18 (26.9)	17 (19.1)	178 (51.7)	207 (50.5)	225 (45.4)
		Agree	13 (19.4)	55 (61.8)	127 (36.9)	127 (31.0)	100 (20.2)
		Strongly agree	21 (31.3)	10 (11.2)	14 (4.1)	0	7 (1.4)
	3. I am worried about the adverse effects of the vaccine	Strongly disagree	3 (4.5)	0	3 (0.9)	6 (1.5)	29 (5.8)	< .001*
		Disagree	6 (9.0)	0	10 (2.9)	32 (7.8)	92 (18.5)
		Neutral	16 (23.9)	11 (12.4)	102 (29.7)	151 (36.8)	196 (39.5)
		Agree	17 (25.4)	42 (47.2)	154 (44.8)	205 (50.0)	161 (32.5)
		Strongly agree	25 (37.3)	36 (7.9)	75 (21.8)	16 (3.9)	18 (3.6)
	4. I am not sure whether or not I have to get the vaccine	Strongly disagree	20 (29.9)	4 (4.5)	5 (1.5)	22 (5.4)	143 (28.8)	< .001*
		Disagree	13 (19.4)	9 (9.0)	30 (8.7)	144 (35.1)	194 (39.1)
		Neutral	17 (25.4)	24 (27.0)	159 (46.2)	160 (39.0)	106 (21.4)
		Agree	10 (14.9)	37 (41.6)	129 (37.5)	80 (19.5)	46 (9.3)
		Strongly agree	7 (10.4)	16 (8.0)	21 (6.1)	4 (1.0)	7 (1.4)
	5. I don’t have time to get the vaccine	Strongly disagree	21 (31.3)	16 (18.0)	47 (13.7)	92 (22.4)	221 (44.6)	< .001*
		Disagree	18 (26.9)	29 (32.6)	151 (43.9)	223 (54.4)	199 (40.1)
		Neutral	19 (28.4)	33 (37.1)	132 (38.4)	77 (18.8)	66 (13.3)
		Agree	3 (4.5)	7 (7.9)	13 (3.8)	15 (3.7)	8 (1.6)
		Strongly agree	6 (9.0)	4 (4.5)	1 (0.3)	3 (0.7)	2 (0.4)
	6. I don’t have money to buy the vaccine	Strongly disagree	15 (22.4)	13 (14.6)	34 (9.9)	42 (10.2)	107 (21.6)	< .001*
		Disagree	21 (31.3)	32 (36.0)	86 (25.0)	160 (39.0)	182 (36.7)
		Neutral	21 (31.3)	26 (29.2)	177 (51.5)	167 (40.7)	163 (32.9)
		Agree	6 (9.0)	13 (14.6)	39 (11.3)	35 (8.5)	33 (6.7)
		Strongly agree	4 (6.0)	5 (5.6)	8 (2.3)	6 (1.5)	11 (2.2)
	7. Scary information about COVID -19 vaccines are rampant on social media	Strongly disagree	7 (10.4)	4 (4.5)	13 (3.8)	42 (10.2)	113 (22.8)	< .001*
		Disagree	11 (16.4)	14 (15.7)	56 (16.3)	100 (24.4)	128 (25.8)
		Neutral	18 (26.9)	35 (39.3)	144 (41.9)	152 (37.1)	132 (26.6)
		Agree	18 (26.9)	28 (31.5)	110 (32.0)	99 (24.1)	96 (19.4)
		Strongly agree	13 (19.4)	8 (9.0)	21 (6.1)	17 (4.1)	27 (5.4)
	8. It will be difficult to get vaccine from nearby clinic due to high demand	Strongly disagree	10 (14.9)	7 (7.9)	6 (1.7)	13 (3.2)	57 (11.5)	< .001*
		Disagree	10 (14.9)	19 (21.3)	45 (13.1)	79 (19.3)	98 (19.8)
		Neutral	25 (37.3)	33 (37.1)	158 (45.9)	154 (37.6)	142 (28.6)
		Agree	15 (22.4)	24 (27.0)	107 (31.3)	135 (32.9)	151 (30.4)
		Strongly agree	7 (10.4)	6 (6.7)	28 (8.1)	29 (7.1)	48 (9.7)
Perceived Benefits	1. Vaccine protects me from getting infected	Strongly disagree	17 (25.4)	3 (3.4)	2 (0.6)	2 (0.5)	2 (0.4)	< .001*
		Disagree	7 (10.4)	8 (9.0)	4 (1.2)	3 (0.7)	3 (0.6)
		Neutral	15 (22.4)	42 (47.2)	109 (31.7)	41 (10.0)	12 (2.4)
		Agree	21 (31.3)	33 (37.1)	190 (55.2)	289 (70.5)	207 (41.7)
		Strongly agree	7 (10.4)	3 (3.4)	39 (11.3)	75 (18.3)	272 (54.8)
	2. Vaccine also protects others people who are not vaccinated	Strongly disagree	18 (26.9)	3 (3.4)	10 (2.9)	4 (1.0)	4 (0.8)	< .001*
		Disagree	10 (14.9)	11 (12.4)	30 (8.7)	21 (5.1)	18 (3.6)
		Neutral	15 (22.4)	33 (37.1)	98 (28.5)	55 (13.4)	38 (7.7)
		Agree	17 (25.4)	36 (40.4)	171 (49.7)	257 (62.7)	173 (34.9)
		Strongly agree	7 (10.4)	6 (6.7)	35 (10.2)	73 (17.8)	263 (53.0)
	3. After vaccination, I can lead a normal lifestyle	Strongly disagree	15 (22.4)	6 (6.7)	4 (1.2)	4 (1.0)	4 (0.8)	< .001*
		Disagree	9 (13.4)	24 (27.0)	38 (11.0)	25 (6.1)	15 (3.0)
		Neutral	23 (34.3)	45 (50.6)	166 (48.3)	91 (22.2)	97 (19.6)
		Agree	15 (22.4)	11 (12.4)	109 (31.7)	234 (57.1)	190 (38.3)
		Strongly agree	5 (7.5)	3 (3.4)	27 (7.8)	56 (13.7)	190 (38.3)
Cues to action
	1. Affordable cost	Strongly disagree	12 (17.9)	6 (6.7)	11 (3.2)	2 (0.5)	7 (1.4)	< .001*
		Disagree	6 (9.0)	16 (18.0)	33 (9.6)	22 (5.4)	17 (3.4)
		Neutral	35 (52.2)	51 (57.3)	220 (64.0)	213 (52.0)	268 (54.0)
		Agree	11 (16.4)	15 (16.9)	70 (20.3)	141 (34.4)	129 (26.0)
		Strongly agree	3 (4.5)	1 (1.1)	10 (2.9)	32 (7.8)	75 (15.1)
	2. Safe	Strongly disagree	19 (28.4)	5 (5.6)	2 (0.6)	1 (0.2)	2 (0.4)	< .001*
		Disagree	8 (11.9)	32 (36.0)	25 (7.3)	6 (1.5)	6 (1.2)
		Neutral	19 (28.4)	40 (44.9)	225 (65.4)	171 (41.7)	126 (25.4)
		Agree	16 (23.9)	9 (10.1)	66 (19.2)	195 (47.6)	220 (44.4)
		Strongly agree	5 (7.5)	3 (3.4)	26 (7.6)	37 (9.0)	142 (28.6)
	3. It is recommended by doctors and MOH	Strongly disagree	10 (14.9)	5 (5.6)	2 (0.6)	3 (3.7)	3 (0.6)	< .001*
		Disagree	8 (11.9)	8 (9.0)	9 (2.6)	5 (1.2)	2 (0.4)
		Neutral	25 (37.3)	45 (50.6)	151 (43.9)	62 (15.1)	53 (10.7)
		Agree	15 (22.4)	28 (31.5)	159 (46.2)	263 (64.1)	220 (44.4)
		Strongly agree	9 (13.4)	3 (3.4)	23 (6.7)	77 (18.8)	218 (44.0)
	4. Good information about vaccine in the mass media	Strongly disagree	14 (20.9)	11 (12.4)	10 (2.9)	5 (1.2)	7 (1.4)	< .001*
		Disagree	5 (7.5)	16 (18.0)	42 (12.2)	18 (4.4)	16 (3.2)
		Neutral	25 (37.3)	34 (38.2)	160 (46.5)	118 (28.8)	104 (21.0)
		Agree	14 (20.9)	23 (25.8)	111 (32.3)	223 (54.4)	190 (38.3)
		Strongly agree	9 (13.4)	5 (5.6)	21 (6.1)	46 (11.2)	179 (36.1)

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Discussions

Since the announcement of the effectiveness of the two rapidly developed vaccines by Pfizer and Moderna, news and articles about vaccines have been circulating in the mass media and social media. This study found that electronic media and social media, including the Malaysian Ministry of Health (MOH) website were the most sought platforms for information regarding the COVID-19 vaccine. Only a small proportion of respondents received the information via newspapers, journal articles and medical-related websites. Previous studies have shown that the use of mass media can yield a positive impact on health-risk behaviours in the community [21]. However, with the recent advancement of informative technologies, social media is rapidly evolving and gaining more popularity than traditional mass media. Even the traditional mass media is adapting and evolving to fit into the social media platforms. Validated health information shared in social media delivers rapid and successful dissemination of knowledge [22]. On the other hand, excess information can lead to media fatigue, misinformation and the spread of fake news [23]. Health literacy is also an important aspect to determine the effectiveness of understanding and appraising the information [24].

To date, there is no published article about the level of knowledge of the COVID-19 vaccine among the Malaysian population. Previously, a study was done among Malaysian parents revealed that poor knowledge has interfered with their decision on HPV vaccination among their children [25]. Inadequate knowledge regarding vaccination can be due to low education background, poor socioeconomic status or obtaining information from their peer layman [26, 27]. This study found that more than half of the respondents had poor knowledge of the COVID-19 vaccine. Higher education level, higher income and living with high-risk individuals were significantly associated with higher knowledge score.

Malaysian populations were found to have good knowledge, attitude and perception regarding COVID-19 prevention [28]. This is possibly the main reason for the higher acceptance of COVID-19 vaccine among the respondents, despite having low knowledge on the vaccine. Our acceptance rate is almost similar to Saudi Arabia (64.7%) [29] and the United Kingdom (64%) [30], better than Turkey (49.7%) [31], but lower than China (91.3%) [32] and Indonesia (93.3%) [33]. Lower age group, higher education level, female, and not having chronic diseases were significantly associated with acceptance to COVID-19 vaccine. In Saudi Arabia, willingness to accept the COVID-19 vaccine was relatively high among older age groups, married, education level postgraduate degree or higher, non-Saudi, and those employed in the government sector [29]. Although the acceptance rate is similar to Saudi Arabia, one distinct difference is that while in Malaysia, the younger age groups showed greater acceptance, in Saudi it is the older age groups.

The success of any vaccination programme to achieve herd immunity depends on the vaccine acceptance and uptake rate. The herd immunity threshold depends on the basic reproduction number (R0). With the R0 of 2–3, no population immunity and that all individuals are equally susceptible and equally infectious, the herd immunity threshold for SARS-CoV-2 would be expected to range between 50% and 67% in the absence of any interventions [34]. In this study, only one-third of the respondents were not willing to get vaccinated. This finding is in line with other studies done in other parts of the world. A study done in France in March 2020 showed that 26% of respondents refused vaccination, more prevalent among low-income people, young women and people older than 75 years old [30]. Another study done in the USA among the general population found that only 21% of respondents were not willing to be vaccinated [19]. Reasons for vaccine refusal including but not limited to safety, effectiveness, costs and side effects.

In order to achieve herd immunity, the vaccine hesitancy issue should be addressed. The Ministry of Health Malaysia has scaled up the vaccine promotional programmes, particularly through social media and mass media. More dialogues and forums involving experts from the ministry and universities have frequently been aired in the television and Facebook Live. In the beginning of the mass vaccination programme, the media also highlighted the vaccination process of the top leaders to increase the public confidence. Misinformation about the negative effects of vaccine from irresponsible parties had been monitored closely by the government. In addition, an emergency law to tackle fake news related to COVID-19 was introduced in March 2021 with hefty fines and jail terms of up to six years [35].

Worryingly, we found that those with existing chronic diseases have significantly lower acceptance rates than those who were healthy. Patients with cardiovascular disease, hypertension, diabetes, congestive heart failure, chronic kidney disease and cancer have been shown to have a greater risk of mortality compared to patients with COVID-19 without these comorbidities [36]. Early vaccination for this population is critical to ensure their health and safety. Therefore, they will be given high priority for the COVID-19 vaccine. More information should be conveyed to this population about the risk of severe COVID-19 and the benefit of vaccination.

While the majority agreed that the government should provide free vaccination to the high-risk groups, more than 70% of the respondents would pay a maximum of RM 100 for the vaccine and only a small proportion (4.6%) cannot afford the vaccine. This is consistent with a previous Malaysian study in April 2020 when the COVID-19 vaccine was still in its early development [37]. However, the cost is not an issue since the Malaysian Government has decided to give free vaccination to Malaysian citizen. The effectiveness of the vaccine and recommendation from the MOH were the highest factors that influence the decision to get the vaccination. This agrees with a study in Indonesia where 93.3% of respondents would like to be vaccinated if the vaccine is 95% effective and the acceptance decreased to 60.7% for a vaccine with 50% effectiveness [33].

A previous study done in Malaysia showed an increase in the perception of susceptibility to infection as the COVID-19 pandemic progressed [38]. Effective preventative behaviours such as personal hygiene and physical distancing to control SAR- CoV-2 transmission largely depend on the perceived susceptibility to infection [39, 40]. Perception of disease susceptibility also correlates with better health-seeking behaviour [41, 42].

More than half of our respondents perceived that they could cause the spread of the virus. People with a higher perceived risk of COVID-19 infection are also more likely to support the vaccine [33]. The low percentage of perceived severity is likely due to the large number of younger respondents with no medical illness. Our respondents had perceived barriers to accepting the COVID-19 vaccine due to its adverse effects, vaccine availability and scary information about vaccines in social media. The majority perceived that vaccination could protect them and others from COVID-19 infection. This is consistent with other findings from other countries [43–45]. Moreover, the respondents believed that the vaccine is beneficial due to recommendations by the MOH and the fact that they can lead a normal life after vaccination. Conversely, more studies have to be done to assess the ability of vaccines to prevent disease transmissibility. According to the CDC, people should continue wearing masks, wash hands frequently and practise physical distancing after getting the COVID-19 vaccine until herd immunity is achieved [46]. Perceived susceptibility, benefit and cues to action are associated with higher acceptance toward COVID-19 vaccine, and our finding is in concordance with other HBM studies [11, 47, 48].

To the best of our knowledge, this is the first study on the knowledge, acceptability and perception of COVID-19 vaccine in Malaysia. One limitation of this study was the use of convenience sampling via social media platforms. The distribution of the respondents might not reflect the actual population since most respondents were internet-savvy young adults. We suggest a larger study that includes respondents from diverse backgrounds, ethnicity, economic status and locations. Multiple public platform sharing is needed to increase the respondent’s rate. Various data collection methods such as telephone interviews and face-to-face interviews should also be employed.

While waiting for vaccines to arrive, continuous education should be conducted to increase understanding and to clear up any misunderstandings or misinformation about the vaccine. Ideally, health education should be comprehensive and multilingual yet layman friendly. The important messages should reach out to all citizens from all walks of life, including those in the rural areas and technology illiterates. In addition to web-based and application-based educational tools, printed materials and face-to-face public talks may benefit certain groups of the population. Public talks involving religious groups can be conducted in the houses of worship by the experts.

Conclusions

This study provides early insight into the Malaysian population’s knowledge, acceptability and perception regarding COVID-19 vaccines. Knowledge about vaccines was relatively poor, particularly among low education levels, low income and not living with high-risk groups. The acceptability rate was significantly low among males, those with chronic diseases and those with low income. Education level of bachelor’s degree and higher was associated with better acceptance towards COVID-19 vaccine. This finding can help the Ministry of Health to plan for future efforts to increase vaccine uptake that may eventually lead to herd immunity against SARS-CoV-2. The efforts should focus on those with insufficient knowledge and low acceptance, particularly those with chronic diseases and less financially fortunate people.

Acknowledgments

We like to thank the Faculty of Medicine and Health Sciences and Universiti Sains Islam Malaysia for assisting us in publishing this paper.

Data Availability

The Supporting Information File is available at 10.6084/m9.figshare.14932605.

Funding Statement

The authors received no specific funding for this work.

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PLoS One. doi: 10.1371/journal.pone.0256110.r001

Decision Letter 0

Eman Sobh

Transfer Alert

This paper was transferred from another journal. As a result, its full editorial history (including decision letters, peer reviews and author responses) may not be present.

21 Apr 2021

PONE-D-21-00966

Knowledge, acceptance and perception on COVID-19 vaccine among Malaysians: A web-based survey

PLOS ONE

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Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

**********

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Reviewer #1: Summary and general impression:

The paper made by N. A. Mohamed et al. team had great and fruitful efforts to discuss community knowledge, acceptance, and perception about the COVID-19 vaccines. It gave a good insight into the level of knowledge regarding nature, benefits, and risks among the Malaysian community as an important predictor of vaccine adoption and good effective community participation.

It also examined the acceptance proportion of the study units to the vaccination idea against COVID-19 emphasized the ability to pay for it and the common factors triggering for vaccination.

It also used the HBM as one of the popular models studying human behavior changes or health perceptions illustrating the benefits, barriers, cues to action, and other perspectives that could motivate or render the COVID-19 vaccination.

A large sample size of the study was good to validate the results putting the convenient sample technique limitations into consideration. Sociodemographic predictors of knowledge, acceptance, or perception are crucial, especially for recommendations directed to policymakers (who, where, what, when, and whom) to put in their priorities during COVID-19 vaccine health education and awareness campaigns planning.

Special issues:

Major issues:

1. The study should clarify the variables (dependent and independent) of the study in the methodology section to avoid confusion of the reader regarding the specific objectives of the study. It was hinted only at the last paragraph of the statistical analysis.

2. "Knowledge" is one of the dependent variables (outcomes) of the study it's categorized in the 2nd paragraph of the methodology to: good (≥6) and poor (<6) but its (table 3) relationship with Demographic factors weren’t presented according to that categorization (did not reveal who was good or poor regarding Demographic factors).

3. HBM has six fundamental perspectives (Benefits- Barriers- susceptibility- severity- Cues to action- self efficacy); (some other factors may be added by some psychiatrists in literature). So, Table 6 targets only three perspectives from them without any mentioned rationale or clarification even as a limitation. On the other hand, in the Susceptibilities section question (1) is severity perspective. Also, questions (3, 4, 6, and 7) in the benefits section are considered cues to action.

4. The HBM perspective association (relationship or prediction) with the acceptance of the COVID-19 vaccine is highly necessary to be presented in the results section to be able to recommend an appropriate situation analysis for active community mobilization intervention programmers.

Minor issues:

1. Title: "perception on" expression is not used a lot in this context; I think "perception about" is more informative.

2. Introduction: The authors should rewrite their Introduction to refer to the related literature of situation of the study outcomes worldwide, especially recently published work such as

• Wong MC, Wong EL, Huang J, Cheung AW, Law K, Chong MK, Ng RW, Lai CK, Boon SS, Lau JT, Chen Z. Acceptance of the COVID-19 vaccine based on the health belief model: A population-based survey in Hong Kong. Vaccine. 2021;39(7):1148–56.

• Shekhar R, sheik AB, Upadhyay S et al. COVID-19 Vaccine Acceptance among Health Care Workers in the United States. Vaccines (Basel). 2021;9(2):119. Published 2021 Feb 3. doi:10.3390/vaccines9020119

• Daly M, Robinson E. Willingness to Vaccinate against COVID-19 in the U.S.: Representative Longitudinal Evidence From April to October 2020 [published online ahead of print, 2021 Feb 15]. Am J Prev Med. 2021;doi:10.1016/j.amepre.2021.01.008

• Gagneux-Brunon A, Detoc M, Bruel S, et al. Intention to get vaccinations against COVID-19 in French healthcare workers during the first pandemic wave: a cross-sectional survey. J Hosp Infect. 2021;108:168-173. doi:10.1016/j.jhin.2020.11.020

3. Methodology: (page 5, 3rd sentence)

• The authors should clarify the reliability measurement was for the English version or Malay Version or both written together in the same form.

4. Data analysis: (page 6, 2nd sentence)

• Kolmogorov–Smirnov test is the standard for normality testing when the sample is more than 50.

5. Results:

• Table 2: score system analysis is considered a binary qualitative data (expressed 1: correct, 0: Not correct) which can't be presented as mean (SD) like continuous (scale) quantitative data; it will not be informative.

• Tables 1 and 5: Education categories' should follow the common international classifications or standardized (example: Diploma = High school, it may be conflicted with another postgraduate degree in other countries). Also, Currency should be converted (or symbol) to a dollar ($) to be more understood, especially with changes of currency all over the world.

• Table 5: The authors should clarify the operational definition (high-risk someone) in the variable "Live with someone who is at a higher risk of getting severe COVID- 19," what they meant?

Miscellaneous points:

The discussion section was written in a good and informative manner.

Reviewer #2: In this research survey from Malaysia, the authors attempt to better characterize public knowledge and acceptance regarding the SARS CoV 2 vaccine. Overall, this qualitative survey is reasonably well written. There are general grammatical errors throughout the document, and so a thorough proofreading will be needed prior to further submissions. I would also encourage the authors to review the manuscript (and, in particular, the introduction), to be more factual and succinct. I have other specific comments for the authors which are outlined below.

In the introduction, please refrain from using social media references (such as the BBC). In addition, please rework paragraph 2 on page 3 to more accurately reflect the number of people enrolled each vaccine trial, and that these vaccines were effective at preventing symptomatic/severe disease, and data on preventing disease transmission is less robust.

In the methodology, you mention intra-respondent consistency in knowledge/susceptibility, barriers, and benefits. I think review of these values and their implications would be better done in the results.

Your data analysis seems straightforward and is described reasonably well.

Table 4 is particularly interesting to me. It may be worth considering what roles the ministry of health or private doctors could provide in addressing vaccine hesitancy in the discussion.

Also, am I correct in assuming that those with a masters/PhD degree were less likely than those with a diploma/degree to be neutral or positive about acceptance of a COVID-19 degree? If so, why do you think that is (could also be addressed in the conclusions).

There needs to be a section that better outlines the limitations of this study. For instance, the demographics of your study group (in particular the gender makeup) are not consistent with World Bank estimates. In addition, those who might use Facebook or other social media platforms might have a different level of knowledge and acceptance of COVID-19 vaccines then the general population. It would be important to mention these limitations and how they may affect the conclusions.

**********

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Reviewer #1: Yes: Ahmed M. Yousef

Reviewer #2: No

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PLoS One. 2021 Aug 13;16(8):e0256110. doi: 10.1371/journal.pone.0256110.r002

Author response to Decision Letter 0

8 Jul 2021

Here is a point-by-point response to the reviewers’ comments and concerns.

Comments from Reviewer 1

Major issues:

Response: Thank you for pointing this out. To avoid confusion to the reader, we have added the variables subheading in the methodology section.

Study Variables

Dependent Variables

COVID-19 knowledge score.

Acceptance to COVID-19 vaccine.

Independent Variables

Age, gender, Educational status, Income category, present of any Chronic diseases, history of been infected with COVID-19, history of family members or friends been infected with COVID-19, living with someone who is at higher risks of getting severe COVID-19 including living with elderly or family members with comorbidity or having long-term medical follow up or chronic medication.

Response: We thank the reviewer for this point. One of the primary rationales of the study is to investigate the association between demographic factors and knowledge of the respondents. In table 3, we are testing the association between the independent variables of demographic factors and total knowledge scores of the respondents. As the dependent variable, knowledge scores are continuous data, thus the mean and median of each independent variable is presented in Table 3.

Response:

We thank the reviewer for this point. We have made the correction on the table 6 accordingly. In response to this, we have made amendment to methodology section, paragraph 2, last sentence.

“For Section D, five options were given: strongly agree, agree, neutral, disagree and strongly disagree, for perceived susceptibility, perceived severity, perceived barriers, perceived benefits and cue to action.”

Response: In corresponds to this point raised by reviewer, table 7 on the HBM perspective association with the acceptance of the COVID-19 vaccine is presented in the results section.

Minor issues:

1. Title: "perception on" expression is not used a lot in this context; I think "perception about" is more informative.

Response: Changed the word ‘on’ to ‘about’

2. Introduction: The authors should rewrite their Introduction to refer to the related literature of situation of the study outcomes worldwide, especially recently published work such as

Response: We appreciate the reviewer’s comment. We have accordingly added all the related literature as suggested by the reviewer in the introduction section.

As safe and effective vaccines are being made available, the next challenge will be in dealing with vaccine hesitancy. Vaccine hesitancy, identified as one of the ten most important current health threats, is defined as the reluctance or refusal to vaccinate despite the availability of vaccines.10 Wong et al. (2011) conducted a population-based study in Hong Kong on the acceptance of the COVID-19 vaccine using the health belief model (HBM) and found that perceived severity, perceived vaccine benefits, cues to action, self-reported health outcomes, and trust were all positive indicators of acceptance. Perceived vulnerability to infection had no significant association with acceptance, whereas perceived access barriers and harm were negative predictors. 11 In addition, another community-based study found that during the pandemic, people's desire to get vaccinated against COVID-19 has fallen dramatically, with over half of the population hesitant or unwilling to get vaccinated. 12

Misinformation and unsubstantiated rumors regarding COVID-19 vaccines have been around and repeatedly shared on social media platforms even before the release of an effective vaccine.13 The use of mRNA genetic material in several vaccines also have been sensationalized by some, with the false claims that the vaccine can alter human DNA. 14 Additionally, the rapid development of COVID-19 vaccines has reportedly raised concerns regarding the safety and long term effects, even among medical staff.15 Findings from studies among healthcare workers (HCWs) are especially concerning, as a small percentage of HCWs do not intend to get the COVID-19 vaccine. 16,17

3. Methodology: (page 5, 3rd sentence)

3.1 The authors should clarify the reliability measurement was for the English version or Malay Version or both written together in the same form.

Response: Thank you for pointing this out. The reliability assessment conducted through a pre-test survey to determine the Cronbach’s α of the questionnaire. Cronbach alpha for both English and Malay version has been added and reported separately in the methodology section.

Reliability measurement was tested earlier on 50 respondents for both the English and Malay version of the questionnaire. Cronbach alpha values for knowledge, perceived susceptibility, perceived barriers and perceived benefits were 0.718, 0.714, 0.714 and 0.834, respectively for the English version. Whereas the Cronbach alpha values for the Malay version were 0.665, 0.688, 0.787 and 0.889, respectively.

3.2 Data analysis: (page 6, 2nd sentence) Kolmogorov–Smirnov test is the standard for normality testing when the sample is more than 50.

Response: Thank you for pointing this out. We agree with this comment. In response to this point, we had made amendment to the sentence.

Histogram with normality curve and Kolmogorov–Smirnov test was used to check for the normal distribution of data in this study.

4 Results:

4.1 Table 2: score system analysis is considered a binary qualitative data (expressed 1: correct, 0: Not correct) which can't be presented as mean (SD) like continuous (scale) quantitative data; it will not be informative.

Response: Agree. We have, accordingly, modified the Table 2. The mean (SD) was removed from the Table 2.

4.2 Tables 1 and 5: Education categories' should follow the common international classifications or standardized (example: Diploma = High school, it may be conflicted with another postgraduate degree in other countries). Also, Currency should be converted (or symbol) to a dollar ($) to be more understood, especially with changes of currency all over the world.

Response: Thank you. As suggested, the education categories were amended following the common international classification for Tables, 1, 3 and 5. Information on the converted currency of dollar ($) were added next to the Ringgit Malaysia currency in Table 1 and 4.

4.3 Table 5: The authors should clarify the operational definition (high-risk someone) in the variable "Live with someone who is at a higher risk of getting severe COVID- 19," what they meant?

Response: We agree with this and have added the details on the definition used for "Live with someone who is at a higher risk of getting severe COVID- 19," in the methodology section, in the independent variables of variables subheading.

….. living with someone who is at higher risks of getting severe COVID-19 including living with elderly or family members with comorbidity or having long-term medical follow up or chronic medication.

Comments from Reviewer 2

1. In the introduction, please refrain from using social media references (such as the BBC). In addition, please rework paragraph 2 on page 3 to more accurately reflect the number of people enrolled each vaccine trial, and that these vaccines were effective at preventing symptomatic/severe disease, and data on preventing disease transmission is less robust.

Response: Thank for pointing this. As suggested, we had revised the reference used for paragraph 2 that used the social media reference. Additionally, we also have rework paragraph 2 reflect the number of people enrolled each vaccine trial, and that these vaccines were effective in protecting the recipient from a COVID-19 infection.

Currently, there are more than 100 candidates of COVID-19 vaccines under development.3 About 11 months after the emergence of the disease, the Food and Drug Administration (FDA) has approved the use of Pfizer/BioNTech and Moderna COVID-19 vaccines in a mass immunization programme.4 Phase three clinical trials for Pfizer/BioNTech vaccines enrolled 43,661 participants, while Moderna vaccines involving 30,000 participants. 5,6 The clinical trial results showed that these vaccines can protect recipients from a COVID-19 infection by forming antibodies and providing immunity against a COVID-19 virus. 4 There are also other companies in the race for vaccine development and in the final stages of trials. It is expected that many vaccines will be ready for distribution by early or mid-2021.7 The United Kingdom was among the first countries that have started mass immunization COVID-19 vaccine. 8

8 Mathieu, E., Ritchie, H., Ortiz-Ospina, E. et al. A global database of COVID-19 vaccinations. Nat Hum Behav. 2021. https://doi.org/10.1038/s41562-021-01122-8

2. In the methodology, you mention intra-respondent consistency in knowledge/susceptibility, barriers, and benefits. I think review of these values and their implications would be better done in the results.

Response: We appreciate the reviewer's question. After discussion we would like to retain the intra-respondent consistency of the knowledge, susceptibility, barriers, and benefits of the questionnaire in the methodology section of the manuscript. The Cronbach’s alpha value reported in this section is a value of the internal consistency of the score from the pilot test. This value was commonly reported in the methodology section of research articles.

Reference: Taber, K.S. The Use of Cronbach’s Alpha When Developing and Reporting Research Instruments in Science Education. Res Sci Educ 48, 1273–1296 (2018). https://doi.org/10.1007/s11165-016-9602-2.

3. Table 4 is particularly interesting to me. It may be worth considering what roles the ministry of health or private doctors could provide in addressing vaccine hesitancy in the discussion.

Response: Thank you for pointing it out. We have added it in the discussion

4. Also, am I correct in assuming that those with a masters/PhD degree were less likely than those with a diploma/degree to be neutral or positive about acceptance of a COVID-19 degree? If so, why do you think that is (could also be addressed in the conclusions).

Response: Thank you for pointing this out. We have found that those with higher education

level (i.e. bachelor’s degree and master/PhD) have positive acceptance towards COVID-19

vaccine. We have included this in the conclusion.

5. There needs to be a section that better outlines the limitations of this study. For instance, the demographics of your study group (in particular the gender makeup) are not consistent with World Bank estimates. In addition, those who might use Facebook or other social media platforms might have a different level of knowledge and acceptance of COVID-19 vaccines then the general population. It would be important to mention these limitations and how they may affect the conclusions.

Response: Thank you for pointing this out. We have added the limitations in the discussion

Attachment

Submitted filename: Response to Reviewers.pdf

Click here for additional data file.^{(277.3KB, pdf)}

PLoS One. doi: 10.1371/journal.pone.0256110.r003

Decision Letter 1

Eman Sobh

2 Aug 2021

Knowledge, acceptance and perception on COVID-19 vaccine among Malaysians: a web-based survey

PONE-D-21-00966R1

Dear Dr. Solehan,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements. Please note to add study data to the link as per your data statement you provided (the link contains link to results and not to data).

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Academic Editor

PLOS ONE

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Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Yes

Reviewer #2: (No Response)

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: (No Response)

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #1: Yes

Reviewer #2: (No Response)

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #1: Yes

Reviewer #2: (No Response)

**********

6. Review Comments to the Author

Reviewer #1: (No Response)

Reviewer #2: (No Response)

**********

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Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

PLoS One. doi: 10.1371/journal.pone.0256110.r004

Acceptance letter

Eman Sobh

5 Aug 2021

PONE-D-21-00966R1

Knowledge, acceptance and perception on COVID-19 vaccine among Malaysians: a web-based survey

Dear Dr. Solehan:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

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on behalf of

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Attachment

Submitted filename: Response to Reviewers.pdf

Click here for additional data file.^{(277.3KB, pdf)}

Data Availability Statement

The Supporting Information File is available at 10.6084/m9.figshare.14932605.

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PERMALINK

Knowledge, acceptance and perception on COVID-19 vaccine among Malaysians: A web-based survey

Nurul Azmawati Mohamed

Hana Maizuliana Solehan

Mohd Dzulkhairi Mohd Rani

Muslimah Ithnin

Che Ilina Che Isahak

Roles

Abstract

Background

Methodology

Results

Conclusion

Introduction

Methodology

Ethical consideration

Study variables

Dependent variables

Independent variables

Data analysis

Results

Demographic data

Table 1. Socio-demographic characteristics (N = 1406).

Knowledge regarding COVID-19 vaccine

Fig 1. Knowledge regarding COVID-19 vaccine category (N = 1406).

Table 2. Knowledge about COVID-19 vaccine (N = 1406).

Table 3. Association between demographic factors and knowledge score (N = 1406).

Acceptance towards COVID-19 vaccine

Fig 2. Acceptance towards COVID-19 vaccine (N = 1406).

Table 4. Questions on factors influencing acceptance for COVID-19 vaccine (N = 1406).

Table 5. Association between demographic factors and acceptance to COVID-19 vaccine (N = 1406).

Perceived susceptibilities, barriers, benefits, and cues to action towards COVID-19 vaccine

Table 6. Perception on susceptibilities, severity, barriers and benefits, and cues to action (N = 1406).

Table 7. Association between perception on susceptibilities, severity, barriers and benefits, and cues to action with acceptance towards COVID-19 vaccine (N = 1406).

Discussions

Conclusions

Acknowledgments

Data Availability

Funding Statement

References

Decision Letter 0

Eman Sobh

Roles

Transfer Alert

Author response to Decision Letter 0

Decision Letter 1

Eman Sobh

Roles

Acceptance letter

Eman Sobh

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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