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Abstract

This study identified the significant COVID-19 vaccine hesitancy and intention to uptake motives and sociodemographic predictors among vaccinated Malaysian adults. A cross-sectional study using a self-administered online questionnaire adapted from the COVID-19 Vaccine Hesitancy Scale and extended based on previous studies was used to solicit data from 698 Malaysians. A theoretical framework comprising Trust, Vaccine Concerns, Unreliable Entities, Uptake Influencers, Brand Influencers, and Brand_Side-effect was used as a guide to assess intention to receive COVID-19 vaccines in the future. Hierarchical linear regressions revealed Trust, Vaccine Concerns, Brand_Side-effect and Uptake Influencers to significantly predict intention to receive vaccines in the future when controlled for sociodemographic correlates. Ethnicity and technology literacy were found to have significant impacts on future vaccine uptake. Age significantly correlated with intention to be vaccinated as well. Underlying motives and sociodemographic correlates were identified for COVID-19 vaccine hesitancy and uptake.

Plain Language Summary

COVID-19 Vaccine hesitancy and uptake

This study investigated COVID-19 vaccine hesitancy and intention to uptake among 698 vaccinated Malaysian adults, using a self-administered online questionnaire based on the COVID-19 Vaccine Hesitancy Scale and a theoretical framework encompassing Trust, Vaccine Concerns, Unreliable Entities, Uptake Influencers, Brand Influencers, and Brand_Side-effect. The analysis, conducted through hierarchical linear regressions, revealed significant predictors for future vaccine intention, including Trust, Vaccine Concerns, brand side effects, and Uptake Influencers, after controlling for sociodemographic factors. Ethnicity, technology literacy, and age were identified as significant influencers on future vaccine uptake. This study provides insights into the underlying motives and sociodemographic correlates of COVID-19 vaccine hesitancy and uptake among Malaysians.

Keywords

sociodemographic motives vaccine hesitancy vaccine uptake COVID-19

Introduction

As of April 2023, more than 700 million people have been infected with COVID-19 globally, more than 6 million have died and more than 13 billion vaccine doses administered (World Health Organization, 2023). The impact of the pandemic was devastating, with increased hospitalization and death on a global scale leading to significant pressure on the healthcare systems, economic downturn due to many businesses closing, unemployment and increased mental health issues, among others (Ambrosetti et al., 2021; Amerio et al., 2021; Chattu et al., 2021). One of the most reliable and safest ways to control and eventually bring the COVID-19 pandemic to an end is through vaccination (Alihosseini et al., 2022). Due to the urgency of the issue, COVID-19 vaccine production was done in haste and several vaccines were approved for use in less than a year (Dror et al., 2020; Rodrigues & Plotkin, 2020).

Evidence shows that COVID-19 vaccines can reduce the odds of disease severity and mortality. However, many people are still hesitant and in doubt and adopted a “wait and see” attitude (Basyir, 2023; Pormohammad et al., 2021). Vaccine hesitancy refers to the delay or refusal of the vaccine (MacDonald, 2015), with its underlying motives differing from regions, time and across vaccine types. This includes perceived risks and benefits, lack of knowledge and awareness, prior vaccination experience, religion and safety, among others (Karlsson et al., 2021; Olagoke et al., 2020; Wong et al., 2020).

The COVID-19 vaccine was first rolled out on February 24, 2021 in Malaysia. Negative perceptions and attitudes were widespread at the early stage of the vaccination program, especially with the introduction of AstraZeneca due to concerns pertaining to its side effects, which include blood clots (Lee et al., 2022). At the time of writing, statistics show that 84.3% (n = 27,532,071) of Malaysians have completed their primary COVID-19 vaccination (i.e., two shots), and only 49.9% are fully vaccinated (i.e., three shots). Unfortunately, the current uptake of the second booster in the country is extremely low (i.e., 2.1%), largely due to hesitancy and doubt resulting in a general “wait and see” attitude (Basyir, 2023; The Malaysian Reserve, 2023). Low vaccine acceptance is a primary concern as new variants such as BA.5.2 and BF.7 have emerged, increasing pressure on the government, healthcare workers and the public in general.

Literature shows an increasing scholarly interest in identifying the enablers and barriers to vaccine hesitancy and uptake worldwide, with factors such as perceived side-effects, long- and short-term impacts, misinformation and low trust in science, government and medical practitioners to enable vaccine hesitancy (Hotez, 2022; Silver et al., 2022; Zimmerman et al., 2023). Studies focusing on sociodemographic correlates reported mixed results, mostly due to the nature of the targeted samples. For example, a Jordanian study among 3,100 respondents found younger people (i.e., <35 years old) to be more likely to accept vaccines, contrary to others reporting a higher acceptance among older age groups (Al-Mohaithef & Padhi, 2020; Lazarus et al., 2021).

The COVID-19 vaccines available are considered highly effective at preventing severe diseases and complications, however there is the perpetual threat of new variants (e.g., Arcturus), and with the re-opening of borders in most of the countries, COVID-19 cases are increasing again—a pattern currently observed in most of the countries. Currently, booster shot programs are being implemented worldwide; however, the uptake of booster shots in Malaysia remains remarkably low. Ensuring minimal vaccine hesitancy among the population is crucial from a public health standpoint. In light of this, our objective is to investigate the underlying motives and sociodemographic correlates related to vaccine hesitancy and uptake. The study specifically focused on Malaysian adults aged between 18 and 50 years and those who have been vaccinated (at least one dose) to examine their motives to have received the COVID-19 vaccine and their future intentions to receive further shots.

Theoretical Framework and Hypotheses

Figure 1 depicts the theoretical framework used in this study, with six independent variables and one dependent variable (Future Vaccine Uptake). The theoretical framework is an extension of our work (Balakrishnan et al., 2021), whereby Uptake and Brand Influencers have been included as additional elements. Specifically, the previous work assessed Uptake and Brand Influencers using descriptive statistics with results showing most of the respondents preferred making their own decisions in receiving vaccines and determining the choice of vaccine brands. Literature shows social influence to be a robust predictor in predicting behaviours and attitudes, including in healthcare (Graupensperger et al., 2020; Quinn et al., 2017; Wizła et al., 2022), and thus the previous framework was modified to incorporate both Uptake and Brand Influencers as the underlying motives for vaccine hesitancy and intention to receive the vaccine in the future.

Figure 1.

Theoretical framework for vaccine hesitancy and future vaccine uptake.

Trust refers to the belief, truth and reliability of someone or something (Silver et al., 2022). In the context of vaccines, it can refer to an individual’s belief or confidence in the ability of the vaccine to treat and prevent diseases. According to Soares et al. (2021), trust also encompasses people’s confidence in vaccine manufacturers and vaccine safety profiles, confidence in healthcare workers delivering the vaccine as well as in political leaders who are making the decisions to approve vaccines for a population. In fact, previous studies on vaccine acceptance and hesitancy have shown low levels of trust in government, science, and vaccine effectiveness significantly and negatively impact vaccine acceptance (Silver et al., 2022; Zimmerman et al., 2023). For example, a US study (n = 3,041) found lower levels of trust in experts were associated with hesitancy, with a higher level of mistrust observed among their Hispanic respondents (Silver et al., 2022). We, therefore hypothesize trust to positively affect future vaccine uptake. Hypothesis one is formulated as:

H₁—Trust positively predicts future vaccine uptake

An individual’s decision to receive a vaccine can be influenced by their social contacts, including family members, friends and medical practitioners (Silver et al., 2022). In fact, studies have shown that people’s health behaviours and attitudes are often influenced by their peers (i.e., social norms). Social norms refer to two primary sources of influence, namely, descriptive (perceptions of others’ behaviour) and injunctive (perceptions of others’ opinions toward a behaviour; Cialdini et al., 1990), both of which have been reported to be key predictors for numerous health-related behaviours such as alcohol consumption (Graupensperger et al., 2020), risky sexual behaviours (Wizła et al., 2022) as well as intentions to receive influenza (Quinn et al., 2017) and Human Papillomavirus (Stout et al., 2020) vaccines. The same can be said about COVID-19 brands, considering the widespread (false) news on AstraZeneca and Sinovac (Chinese-manufactured), the latter of which was rolled out in Malaysia to expedite vaccination rates. A similar phenomenon was observed in many other Asian countries, such as Hong Kong and the Philippines, where clear brand inclinations were found amongst citizens who prefer Pfizer and Moderna vaccines over those produced by Chinese manufacturers due to reported efficacy rates and concerns about quality control (Ong et al., 2022). Therefore, it is important to examine if social norms impact an individual’s decision to be vaccinated and the choice of vaccine brand. As these are two separate points, we propose to investigate this through two independent factors, namely, Uptake Influencers and Brand Influencers (see Figure 1). In line with previous studies (Quinn et al., 2017; Stout et al., 2020), we posit that influencers have a positive impact on one’s vaccine uptake decision and choice of vaccine brand. The hypotheses are:

H_2a—Uptake influencers positively predict future vaccine uptake

H_2b—Brand influencers positively predict future vaccine uptake

Studies worldwide have reported COVID-19 vaccine concerns which include long- and short-term impacts, its availability (particularly in low- and middle-income countries) and its effect against new strains (Gregory et al., 2022; Soares et al., 2021; Rusgis et al., 2022). For example, there was a worldwide concern about the safety, reliability and long-term impact when COVID-19 vaccines were rolled out as they were developed relatively quickly compared to traditional vaccine development timelines (Dror et al., 2020; Rodrigues & Plotkin, 2020)—a concern that was observed even among the healthcare workers (Gagneux-Brunon et al., 2021). Side effects are common in any vaccinations, with the majority often involving mild fever, fatigue, headaches and/or sore arm that lasts for a few days (Centers for Disease Control and Prevention, n.d.). However, in the context of COVID-19 vaccines, numerous reports on adverse side-effects of the vaccines, such as AstraZeneca that was believed to result in blood clots, and eventually lead to casualty caused great concerns among the public (Lee et al., 2022 This was further exacerbated by the dissemination of misinformation about COVID-19 vaccines and their side-effects (Gregory et al., 2022; Silver et al., 2022; Zimmerman et al., 2023). Therefore, we hypothesize that negative vaccine concerns affect the intention to receive the vaccine. Hypothesis 3 is given as follows:

H₃—Vaccine Concerns negatively predict future vaccine uptake

The pandemic also witnessed a spike in global fake news or misinformation peddling, including those related to the disease and vaccines (Leng et al., 2021; Pennycook et al., 2020; Balakrishnan et al., 2021). This had a significant impact on COVID-19 vaccine acceptance/hesitance as false information can create confusion and fear about the safety and efficacy of the vaccine. For instance, there was widespread misinformation claiming COVID-19 vaccines can cause infertility, which was reported to have increased vaccine hesitancy (Abbasi, 2022). Another example of misinformation that affected vaccine acceptance was the false claim that the vaccines contain pork products, which is forbidden in Islam and Judaism (Syed Alwi et al., 2021). Misinformation such as these can amplify the voices of anti-vaccine groups, hence making it difficult for people to discern what information is accurate and reliable. This creates a lack of trust in public health agencies and medical professionals, leading to further vaccine hesitancy—an issue that is further exacerbated by a lack of reliable information and low levels of confidence in authorities such as politicians and gatekeepers (Lee et al., 2022). We identify such themes as Unreliable Entities and hypothesis four is as follows:

H₄—Unreliable Entities negatively predict future vaccine uptake

Finally, as stated above, vaccine brands are deemed important to many people, and evidence exists showing higher concerns for certain brands and their side effects (e.g., AstraZeneca and Sinovac). Further, recent studies confirming the rare occurrence of heart inflammation (myocarditis and pericarditis), particularly among young males who received mRNA vaccination (i.e., Moderna; Pillay et al., 2022) tend to increase one’s apprehension in getting further shots. Although the reported incidence of these rare adverse effects is low and the benefits of COVID-19 vaccination in preventing severe illness, hospitalization and death outweigh the risks of these side effects, such concerns nevertheless can have a negative effect on an individual’s vaccine uptake in the future (Bozkurt et al., 2021; Lee et al., 2022; Ong et al., 2022). Therefore, the final hypothesis is:

H₅—Brand_Side-effect negatively predict future vaccine uptake

Using the theoretical framework in Figure 1, the study aims to answer five main research questions (RQs):

RQ 1a—Is there a correlation between age and the underlying motives for vaccine hesitancy?

RQ 1b—Is there a correlation between age and future vaccine uptake?

RQ 2a—What are the effect(s) of sociodemographic correlates on the underlying motives for vaccine hesitancy?

RQ 2b—What are the effect(s) of sociodemographic correlates on future vaccine uptake?

RQ 3a—What are the significant predictors for future vaccine uptake?

In summary, the study aims to identify the underlying motives for COVID-19 vaccine hesitancy and the future intention to receive further shots. Guided by the five RQs above, the study specifically focuses on six hypotheses as given below:

H₁—Trust positively predicts future vaccine uptake

H_2a—Uptake influencers positively predict future vaccine uptake

H_2b—Brand influencers positively predict future vaccine uptake

H₃—Vaccine Concerns negatively predict future vaccine uptake

H₄—Unreliable Entities negatively predict future vaccine uptake

H₅—Brand_Side-effect negatively predict future vaccine uptake

Materials and Methods

Instrument

The COVID-19 Vaccine Hesitancy Scale (VHS) was adapted and extended with items from previous studies (Freeman et al., 2022; Gregory et al., 2022; Soares et al., 2021; Rusgis et al., 2022; Silver et al., 2022). The survey questionnaire was prepared in English and the Malay language (the national language of Malaysia). A total of 40 respondents piloted the English version, which was then translated into the Malay language. During the pilot test, statements and questions were checked, and issues pertaining to ambiguity, redundancy, etc., were addressed. The final version of the English questionnaire was validated by an expert in the field and then translated into the Malay language. The translation accuracy was checked by fifteen students who are well-versed in the Malay language, and who participated in the pilot test.

The questionnaire had two primary sections:

Sociodemographic—Respondents stated their sociodemographic details, namely their age, gender, ethnicity, number of hours spent daily in checking news and social media, etc. There were a total of 15 questions in this section.

Motives—Respondents stated their agreement/disagreement levels on items focusing on factors determining their vaccination decision and intention to uptake vaccine using a five-point Likert scale (1—strongly disagree; 5—strongly agree). Table 1 shows the factors as well as the mean and standard deviations (SDs). We used Cronbach’s Alpha (α) to determine the internal consistency and reliability of the items, whereby a score of more than .70 is considered to be good (Nunnally, 1978).

Table 1.

Descriptive Statistics and Reliability Analysis for the Variables.

Items	α	M	SD
Trust	.844	3.87	0.87
Religious compatibility		3.79	1.08
Vaccine is effective in protecting health		3.92	0.84
Vaccine is important for health		4.08	0.80
Reliable information related to vaccine		3.96	0.76
Trust government		3.56	0.91
Trust vaccines		3.89	0.81
Vaccine concerns	.816	3.75	0.99
Concerned short-term safety		3.48	1.07
Concerned long-term safety		3.80	1.02
Concerned vaccine effectiveness		3.91	0.94
Concerned vaccine availability		3.81	0.93
Untrustworthy entities	.736	3.40	1.06
Untrustworthy source of information		3.15	1.10
Misinformation on vaccine		3.71	1.05
Uncertainty of vaccine effectiveness due to new strains		3.52	0.98
Lack of reliable public info		3.21	1.11
Brand_Side-effect	.709	3.52	1.01
Side effects of vaccine		3.41	1.02
Vaccine brand importance		3.63	1.00
Brand influencers	.827	3.13	1.11
Family		3.36	1.16
Friends		3.06	1.08
Doctors		3.2	1.11
Own Decision		3.84	1.03
Celebrity/Influencers/Politicians		2.70	1.11
Brand false news		2.63	1.13
Uptake influencers	.789	3.54	1.06
Family		3.68	1.10
Friends		3.42	1.08
Doctors		3.43	1.12
Own Decision		4.31	0.79
Celebrity/Influencers/Politicians		2.81	1.18
Media		3.6	1.08
Future vaccine uptake	.705	3.46	1.11
Willing to pay for vaccine		3.03	1.17
Willing to take future shots		3.88	1.06

Note. Items stated in simple sentences.

Trust comprised six items with examples including trust in government, COVID-19 vaccine, religious compatibility, reliable information pertaining to vaccine etc. (Rusgis et al., 2022; Silver et al., 2022). A high α-score of .844 indicates these six items to have good reliability, whereas a mean score of 3.87 generally shows that the majority of the respondents are agreeable to these items. Vaccine Concerns comprised four concerns with regards to COVID-19 vaccines (Gregory et al., 2022; Soares et al., 2021; Rusgis et al., 2022), and a high α-score of 0.816. Similar observations were noted whereby most of the respondents were found to be agreeable to these items.

Uptake and Brand Influencers were both measured using six items, both with high α-scores of .789 and .827, respectively. These factors specifically focused on entities that affect an individual’s decision to be vaccinated and the choice of the COVID-19 vaccine brand (Quinn et al., 2017; Stout et al., 2020). One item (i.e., media) was rephrased to “brand misinformation on media” for Brand Influencers. Unreliable Entities had four items targeting misinformation, lack of public information, etc. (Lee et al., 2022; Leng et al., 2021), whilst Brand_Side-effect had two items (Lee et al., 2022). The items used to assess these factors were also reliable based on their α-scores (i.e., >.70). Finally, two items were used to measure the dependent variable, that is, willingness to pay for vaccines in the future (Freeman et al., 2022; Gregory et al., 2022) and willingness to take future shots. The α-score of more than .70 establishes these two items to be reliable.

The overall Cronbach’s α for the scale was .859 (i.e., with all the items included), hence indicating good internal reliability.

Study Protocol

This cross-sectional online survey study was conducted from November 15 to December 12, 2022—a period where COVID-19 cases were on the rise and the Malaysian government was planning to roll out second dosage of booster shots. The study adopted the convenience sampling approach. The survey links were hosted on the Google Forms platform and disseminated mainly through social media such as Facebook, Instagram and WhatsApp. This was mainly done with the students sharing the links on their personal social media walls and through their personal WhatsApp groups and contacts. In some cases, the target respondents also assisted by forwarding the links to their contacts. We targeted Malaysians aged 18 and above. Respondents’ participation was voluntary, free, and anonymous. The questionnaire survey was ethically approved by the Universiti Malaya Research Committee.

Study Respondents

Using a calculator based on Cochran’s (1963) equation, the appropriate sample size given the specified combination of precision (±5%), confidence (95%) and variability (0.5) was 385. This study focused on Malaysians aged 18 and 50 years old, resulting in 698 respondents (i.e., seven aged more than 51 were removed). All the respondents were vaccinated; that is, they have received at least one dose of the COVID-19 vaccine. The respondents (M_age = 23.5; SD_age = 7.31) comprised 281 (40.3%) males and 417 (59.7%) females. Table 2 depicts the summary of their sociodemographic details.

Table 2.

Sociodemographic Profiles of Study Participants (n—698).

Characteristics	Categories	n (%)
Ethnicity	Malay	429 (61.5)
	Chinese	198 (28.4)
	Indian	45 (6.4)
	Others	26 (3.7)
Status	Tertiary	541 (77.5)
	Working	155 (22.2)
	Housewives	2 (0.3)
Education	Primary	13 (1.9)
	Secondary	51 (7.3)
	Tertiary	634 (90.8)
Hours Check News (daily)	Less than 1	301 (43.1)
	Between 1 and 5	313 (44.8)
	More than 5	84 (12.0)
Hours social media (daily)	Less than 1	41 (5.9)
	Between 1 and 5	330 (47.3)
	More than 5	327 (46.8)
Information source	Internet	146 (20.9)
	Family/friends	39 (5.6)
	Social media	488 (69.9)
	Printed News	12 (1.7)
	Radio/Tv	13 (1.9)
Vaccine misinformation	Yes	590 (84.5)
	No	34 (5.7)
	Unsure	70 (10.0)
Technology literacy	Beginner	23 (3.3)
	Intermediate	262 (37.5)
	Advanced	413 (59.2)
Fact check literacy	Beginner	113 (16.2)
	Intermediate	354 (50.7)
	Advanced	231 (33.1)
Misinformation literacy	Beginner	67 (9.6)
	Intermediate	383 (54.9)
	Advanced	248 (35.5)
Brand	Pfizer	516
	Sinovac	242
	AstraZeneca	229
	Johnson & Johnson	41
# of vaccine dose(s)	1	7 (0.01)
	2	211 (30.2)
	3	476 (68.1)
	4	4 (0.01)

Malaysia is a multi-ethnic country and the ethnicity makeup of the respondents is in line with the general population whereby the majority were Malays (61.5%), followed by Chinese (28.4%), Indians (6.4%) and Others (3.7%). Respondent status was skewed in the sense that most of them were tertiary students (77.5%), followed by working adults (22.2%). The pattern tallies with education levels whereby almost 90% of the respondents had tertiary education as opposed to primary and secondary. The sample is also considered active on social media, as many spent more than an hour daily (94.1%) and mostly cited social media as the main source of information (69.9%). Only 12% spent more than 5 hr daily checking news. Approximately 85% of the respondents claimed to have received fake news related to the COVID-19 vaccine, whilst 10% were unsure. In terms of literacy levels, the majority considered themselves as advanced (59.2%) followed by intermediate (37.5%) for technology. As for the ability to identify fake news and fact-checker literacy, the majority identified themselves as intermediate, followed by advanced. In general, it can be surmised that our sample is well-versed with regard to their literacy. Finally, Pfizer emerged as the most popular brand (n = 516), followed by Sinovac (n = 242) and AstraZeneca (n = 229). These figures were tabulated based on the number of shots (i.e., dose one, two etc.), and thus do not tally to 698. Looking at the number of vaccine shots received, more than half of the sample is fully vaccinated (i.e., three shots; 68.1%), although a large number of them have received only the primary dose (30.2%) and single shot (n = 7). This figure tallies with the statistics reported in the country showing a low uptake of the second booster shot (i.e., 2.1%) despite the increasing cases of COVID-19 (Basyir, 2023; The Malaysian Reserve, 2023).

Data Analysis

All the statistical analyses were performed using SPSS 28.0. The sample was described using frequency, percentage, mean (M), and standard deviations (SD). Kolgomorov-Smirnov test revealed our data not to be normally distributed (p < .05). Therefore, inferential statistics were performed using non-parametric tests. Specifically, the Mann-Whitney U was used to compare differences between two groups (i.e., gender), whilst Kruskal-Wallis was used in instances with at least three groups (e.g., status, hours spent daily on social media, etc.). The Spearman correlation was used to examine the relationship between two variables, a test that shows the strength of a relationship based on the rho-values that range from −1 to +1. A zero indicates no relationship whereas a value of ±1 indicates a perfect degree of association between the two variables (Schober et al., 2018).

Finally, hierarchical linear regressions were conducted to identify the significant predictors for intention to uptake vaccine. Two blocks or models were used: the first contained the sociodemographic variables and the second contained the underlying motives. Linear regressions yield the impact of each predictor based on their weights (i.e., β coefficients), with larger weights indicating a larger impact on the target variable (i.e., Future Vaccine Uptake; Siegel & Wagner, 2022). We used a statistical significance p;< .05 for all the tests above (i.e., any p-value more than .05 is considered insignificant).

Results

Age and Hesitancy Motives and Future Uptake

To answer RQ1a and RQ1b, Spearman Correlation tests were executed. Results showed age to be significantly and negatively correlated with Trust (rho = −0.107; p;= .005), Uptake Influencers (rho = −0.158; p;< .001) and Future Vaccine Uptake (rho = −0.094; p;= .013), indicating that individuals who are older tend to have lower Trust, Uptake Influencers and lower intention to receive the vaccine in the future.

Sociodemographic Impact on Hesitancy Motives and Future Uptake

Table 3 shows the results of the Kruskal-Wallis tests (RQ 2). No significant differences were noted for Gender based on Mann-Whitney. Ethnicity was found to be significant for all the factors except for Brand Influencers. The median ranks show that there is a higher level of Vaccine Concerns among the Chinese, whereas the Indians reported lower Trust, higher Unreliable Entities and brand side effects. Respondents’ education levels were significant for Trust and Future Vaccine Uptake - those with higher education reported higher scores. A similar pattern was observed for Status whereby tertiary students reported a higher Future Vaccine Uptake than working adults. Additionally, they also scored higher ranks for Vaccine Concerns and Uptake Influencers.

Table 3.

Sociodemographic Correlates for COVID-19 Vaccine Hesitancy and Future Vaccine Uptake.

	Kruskal-Wallis (H; p-value)
Factors	Ethnicity	Education	Status	Tech literacy	Fake news lit.	Fact-check lit.	Check news	Social media
Future vaccine uptake	9.75 (.004)	7.94 (.019)	6.52 (.011)	31.15 (<.001)	10.17 (.006)	10.05 (.007)	NS (.479)	NS (.394)
Vaccine concerns	13.58 (<.001)	NS (.133)	4.41 (.036)	27.15 (<.001)	11.00 (.004)	6.76 (.034)	NS (.104)	NS (.289)
Unreliable entity	11.77 (.003)	NS (.120)	NS (.712)	NS (.155)	NS (.446)	8.58 (.014)	NS (.413)	NS (.181)
Trust	12.76 (.002)	9.74 (.008)	NS (.416)	52.17 (<.001)	24.16 (< .001)	14.622 (< .001)	14.39 (<.001)	NS (.186)
Brand_Side-effect	15.92 (<.001)	NS (.144)	NS (.072)	NS (.799)	8.60 (.014)	NS (.139)	NS (.269)	6.38 (.04)
Uptake influencers	9.46 (.009)	NS (.506)	14.68 (<.001)	14.00 (<.001)	NS (.094)	6.50 (.039)	NS (.266)	11.87 (.003)
Brand influencers	NS (.39)	NS (.419)	NS (.058)	NS (.14)	NS (.387)	7.54 (.023)	NS (.135)	NS (.164)

Note. Only significant results are shown. NS = not significant; Gender = all insignificant based on Mann-Whitney test.

Literacy revealed consistent patterns whereby individuals with advanced levels of technology, fake news identification and fact-checking literacy significantly reported higher Future Vaccine Uptake, Trust and Vaccine Concerns than intermediate and beginners. As for Unreliable Entities, only fact-checking literacy was significant with advanced and intermediate respondents reporting more concerns for unreliable information and sources than beginners. Significant differences were also observed for Uptake and Brand Influencers whereby advanced respondents scored higher for these two motives than intermediate users. As for fake news identification literacy, significant observations were noted whereby beginners had higher scores for Brand_Side-effect than the others, showing that those with low levels of fake news identification skills are more influenced by vaccine brands and their side effects. Individuals who spent less time checking news daily had more Trust whereas those who spent more time on social media were significantly influenced by others (i.e., Uptake Influencers) than those who don’t.

Predictors for Motives and Intention to Uptake Vaccine

Finally, hierarchical linear regressions were performed to answer RQ 3. This was done by including all the sociodemographic variables in Block 1 and then controlling them for the underlying motives in Block 2. In both cases, Future Vaccine Uptake was the dependent variable.

Results shown in Table 4 indicate Model 1 to be significant (F(9, 688) = 3.48, p;< .001, R² = .031), with ethnicity (β = −.082; t = −2.132; p;= .033) and technology literacy (β = .027; t = 0.679; p;= .023) significantly predicting Future Vaccine Uptake. The second model with all the underlying motives was also significant (F(15, 682) = 18.74, p;< .001, R² = .29), with a significant improvement from Model 1, that is, ?F(6,682) = 39.86, p;< .001, ?R² = .25.

Table 4.

Hierarchical Regressions for Future Vaccine Uptake.

	Model 1			Model 2			Hypothesis
Factors	β	t-value	p-Value	β	t-value	p-Value	-
Ethnicity	−.082	−2.132	.033	-	-	-	-
Technology literacy	.027	0.679	.023	-	-	-	-
Vaccine concerns	-	-	-	−.084	−2.161	.031	H₃ supported
Trust	-	-	-	.450	11.014	<.001	H₁ supported
Uptake influencers	-	-	-	.173	3.687	<.001	H_2a supported
Brand_Side-effect	-	-	-	−.225	−5.955	<.001	H₅ supported

Vaccine Concerns, Trust, Uptake Influencers and Brand_Side-effect significantly predicted Future Vaccine Uptake, with Trust emerging as the strongest predictor (β = .450; t = 11.104; p;< .001), followed by Brand_Side-effect (β = −.225; t = −5.955; p ;< .001), Uptake Influencers (β = .173; t = 3.687; p;< .001), and Vaccine Concerns (β = −.084; t = −2.161; p;= .031). The positive relationships show that the higher the Trust and Influence, the higher the intention to be vaccinated. Contrarily, the lower the Vaccine Concerns and perceptions related to vaccine brand and side-effects, the higher the intention to receive vaccination.

Discussion

This study sought to identify the underlying motives for vaccine hesitancy and future COVID-19 vaccine uptake intention. Using data collected from 698 vaccinated Malaysian adults, the findings show Trust, Vaccine Concerns, Uptake Influencers, brand side-effect, ethnicity, and technology literacy had significant effects on Future Vaccine Uptake. Further, significant negative relationships were found between age and vaccine hesitancy motives and intention to receive vaccines in the future.

Trust emerged to be the strongest positive predictor—concurring with previous COVID-19 vaccine studies (Silver et al., 2022; Szilagyi et al., 2021; Tan et al., 2022; Zimmerman et al., 2023). One of the items used to measure Trust in this study was religious beliefs or compatibility, and the majority of the respondents agreed that receiving vaccines is compatible with their religion (Table 1). This is interesting considering the nation is considered to be “conservative” and previous studies have often cited religion to be a potential barrier to vaccine acceptance (Corcoran et al., 2021; Olagoke et al., 2020), including those conducted in Malaysia (Syed Alwi et al., 2021; Wong et al., 2020). The latter studies however, examined religion as a sociodemographic variable (i.e., Muslim, Christian, Hindu etc.) instead of an item assessed through an individual’s perception, therefore our finding provides a truer indication of religiosity and its impact on Future Vaccine Uptake. Moreover, we also argue that the majority of our respondents are well-educated (i.e., tertiary) urbanites, hence they may be more receptive toward vaccination. This may also be the reason for the higher agreeability in believing that vaccines are important for health and are effective in protecting one’s health as well, a finding that aligns with previous studies (El-Elimat et al., 2021; Gregory et al., 2022; Szilagyi et al., 2021).

Brand_Side-effect was a strong predictor as well, hence affirming reports on (true and/or false) link between certain COVID-19 brands and their deleterious side-effects (Beatty et al., 2021; Lee et al., 2022; Pillay et al., 2022). It is, therefore, unsurprising that many people emphasize vaccine brands as they believe that brands such as Pfizer are “safer” than others, including AstraZeneca and Sinovac. This is especially true in the Malaysian context as the government introduced the non-Sinovac vaccine as a booster shot to those who received two primary doses of Sinovac, amid growing concerns about its low efficacy as reported in several countries (Bangkok Post, 2022; BBC News, 2022; Ng et al., 2022; Premikha et al., 2022; Radio Free Asia, 2022). Although the link between brand and side effects was not investigated, other studies worldwide have reported similar preferences for Pfizer among the samples (El-Elimat et al., 2021 in Jordan; Ong et al., 2022 in the Philippines).

Respondents were also concerned about COVID-19 vaccines’ short- and long-term impacts and availability as well as their effectiveness in general (i.e., Vaccine Concerns). This shows that despite being aware of the importance of vaccines in protecting themselves, negative perceptions about vaccines still exist, and these need to be better managed by the healthcare authorities to ensure such concerns do not prevent an individual from receiving vaccines in the future. This discrepancy was also reported in other studies (Asadi Faezi et al., 2021; El-Elimat et al., 2021), and could be attributed to several factors including concerns about the adverse short- and long-term impacts. This can be addressed by promoting clinical studies on the short- and long-term effects as evidence exists indicating that nations with more confidence in the accuracy of side-effects reports are more likely to receive vaccination (Larson et al., 2014).

Our results also show that social contacts such as family members, friends, and doctors, as well as making own decisions (Uptake Influencers), have a positive effect on Future Vaccine Uptake, in line with previous studies showing the impact of social norms on health behaviours and attitudes (Pelegrín-Borondo et al., 2021; Quinn et al., 2017; Silver et al., 2022; Stout et al., 2020). This can be mainly attributed to the importance of the opinion of individuals we consider important to receive vaccines, including doctors and reliable media. Our finding is in agreement with studies that reported healthcare professionals, including physicians, to be the most trusted source of COVID-19 vaccine information (El-Elimat et al., 2021; Malik et al., 2020). This also suggests that people can motivate each other to counter “fear” against COVID-19 vaccines and reduce vaccine hesitancy rate. A community that works collectively to reach out to people about the benefits of vaccines helps as well. As social contacts can shape peoples’ acceptance/refusal of COVID-19 vaccines, gaining an understanding of trusted and influential resources is critical for the success of any future national vaccination campaign.

Both ethnicity and technology literacy were found to be significant predictors as well, whereas age significantly (and negatively) correlated with Future Vaccine Uptake. Similar observations were made in studies that have investigated race/ethnicity, with findings suggesting that other factors, such as lack of access to reliable information, one’s community and its beliefs, etc., may explain the varying impact vaccine uptake based on ethnicity (Dai et al., 2022; Silver et al., 2022). Further investigations are warranted to examine these results, also considering our ethnicity segregation in the sample is imbalanced. As for age, our findings are in congruence with previous studies that reported young(er) people are more likely to accept the COVID-19 vaccine (El-Elimat et al., 2021) and contrary to some who reported a higher acceptance among older age groups (Al-Mohaithef & Padhi, 2020; Lazarus et al., 2021). This, too, could be attributed to the skewed sample in our study, comprising mostly young people (Mage = 23.5; SDage = 7.31) with high literacy levels—an issue that was observed in most studies soliciting data through online surveys (El-Elimat et al., 2021). Therefore, this finding warrants further investigation.

This study has a few limitations. First, although online-based surveys enable efficient and cost-effective ways of data collection, this resulted in a skewed sample whereby the majority of the respondents were from the younger cohort (M_age = 23.5; SD_age = 7.31), urbanites and well-educated (i.e., 90% with tertiary education), and thus this could have affected the results as the respondents have a more positive attitude toward vaccination. The findings, therefore, may not fully reflect the general attitudes and perceptions of the population, hence they should be interpreted cautiously. Future studies could expand the study by including more respondents from older cohorts as well as those from the lower socio-economy status (SES) and rural areas to gain better insights into vaccine hesitancy and uptake. Further, themes like mis(information) were only assessed through two items, hence unlikely to capture the true extent of the issue. Previous studies have shown misinformation to increase vaccine hesitancy (Abbasi, 2022; Lee et al., 2022). Hence, more items specifically targeting this should be included and investigated to get a clearer picture of its impact on vaccine hesitancy and uptake.

Conclusion

Trust, Vaccine Concerns, Uptake Influencers, Brand_Side-effect, ethnicity and technology literacy had significant effects on Future Vaccine Uptake. Relevant authorities, including healthcare practitioners, state/local public health officials and the government, need to strategize programs to improve the COVID-19 vaccine acceptance rate by leveraging these motives, particularly when the cases are on the rise again. As the majority of the respondents were still concerned about the vaccine’s safety and reliability, interventions in the form of educational and awareness campaigns should be prioritized to reduce vaccine hesitancy. Such campaigns should be promoted through various medium including social media to spread reliable and transparent information related to COVID-19 vaccines’ safety and efficacy. Public health authorities should identify and establish trusted sources of information to provide more reliable information on vaccine efficacy, safety and materials/technology used in producing vaccines to increase future uptake of the booster shots.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Ethics Declaration

Ethics approval was obtained from the Universiti Malaya Research Committee - UM.TNC2/UMREC_2378

ORCID iDs

Vimala Balakrishnan

Saadat M. Alhashmi

Research Data Availability

The data will be made available based upon a reasonable request.

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COVID-19 Vaccine Hesitancy and Uptake Among Vaccinated Population in Malaysia

Abstract

Plain Language Summary

Keywords

Introduction

Theoretical Framework and Hypotheses

Materials and Methods

Instrument

Study Protocol

Study Respondents

Data Analysis

Results

Age and Hesitancy Motives and Future Uptake

Sociodemographic Impact on Hesitancy Motives and Future Uptake

Predictors for Motives and Intention to Uptake Vaccine

Discussion

Conclusion

Footnotes

Declaration of Conflicting Interests

Funding

Ethics Declaration

ORCID iDs

Research Data Availability

References