Exploring vaccine hesitancy and acceptance in the general population of Pakistan: Insights into COVID-19-related distress, risk perception, and stigma

ABSTRACT

The coronavirus disease 2019 (COVID-19) caused several impacts. Focusing on 360 participants (178 males, 182 females), this study explored the association between COVID-19 related distress, risk perception, stigma, and vaccine hesitancy and acceptance in the general population. Measures used included the Hospital Anxiety and Depression Scale (HADS) and COVID Stress Scale (CSS) to evaluate anxiety, depression, and COVID-19 related distress, the COVID-19 Risk Perception Scale and COVID-19 Stigma Discrimination Scale to assess risk perception and stigma, and the Oxford COVID-19 Vaccine Hesitancy Scale and Vaccine Acceptance Instrument to measure vaccine hesitancy and acceptance. The findings revealed that 66.9% of participants exhibited vaccine hesitancy, and stress and risk perception were significant predictors of both vaccine hesitancy and acceptance, even after controlling for demographic factors. This study highlights the importance of understanding the factors mentioned above that will contribute to vaccine hesitancy and acceptance, which will contribute to promoting vaccine acceptance.

KEYWORDS:

• vaccination
• Vaccine hesitancy
• vaccine acceptance
• COVID-19 relatedstress
• anxiety
• depression
• risk-perception
• stigma
• COVID-19 pandemic
• coronavirus
• immunization
• Pakistan

Introduction

The entire globe faced a significant and unprecedented challenge with the emergence of the coronavirus disease 2019 (COVID-19) pandemic. This public health crisis represented a substantial challenge, unprecedented in recent history, and resulted in notable impacts across the world. Ali¹ posits that the COVID-19 outbreak resulted in various pandemics, encompassing medical, economic, social, structural, emotional/psychological, and even a political pandemic. This is because the pandemic affected individual, communities, countries and continents. No one was spared from its critical implications. The pandemic caused multiple waves of infections and effects. Since the declaration of the pandemic, relevant scientists became engaged in the development of vaccines for dealing with these infections and effects. The initiation of the vaccination trials took place in late December 2020. On the one hand, it was the development of vaccine, and on the other hand, it was emergence of various competing narratives regarding the vaccine development, leading to a wide range of emotions and perspectives among people worldwide, both prior to and following their creation. Numerous unique factors exist that contribute to individuals’ choices in receiving the COVID-19 vaccine.

In the realm of logic, it is imperative to acknowledge that occurrences seldom transpire in a state of isolation. The intricacies of interconnectivity and interdependence characterize the fabric of events and phenomena, highlighting the profound influence exerted by contextual factors. This recognition illuminates the significance to consider the broader milieu in the analysis and interpretation of any given subject matter, as the interplay of diverse elements invariably contributes to the multifaceted nature of observed phenomena. The same is the case with vaccine choices. Hence, vaccine decision-making should be examined within a broader socio-cultural, economic and (geo-)political contexts, as indicated by previous research in the field of social sciences.^2–4 Vaccination is considered to be a part of a “larger social environment,”⁵ which implies that various factors, such as previous experiences with medical services, personal histories, feelings of control, and conversations with friends, can influence an individual’s decisions regarding vaccination choice. Receiving a vaccine is one of the many decisions that parents are confronted with, in addition to other daily concerns, such as child nutrition and health, may occasionally take priority or influence the willingness to vaccinate.⁶

Although the primary target population for vaccinations is children and young adults, a significant amount of research has focused on investigating the factors that influence vaccine acceptability among parents. Given the varying purposes and objectives of these studies, drawing definitive conclusions about the primary factors influencing vaccine acceptance or refusal proved to be unattainable. As mentioned earlier, personal decisions regarding vaccination are influenced by various factors, including the socio-cultural environment, social conditions, and personal knowledge. Despite these differences, there are certain shared factors that contribute to individuals either accepting or rejecting vaccines. In addition, the expenses associated with obtaining medical services, both directly and indirectly, have been found to have a negative impact on the uptake of vaccines, which is considered to be less than desirable.⁷

Brewer and colleagues revealed extensive evidence indicating perceptions of risks as determinants of adolescent immunization actions in a meta-analyses.⁸ Risk perceptions in the context of health are often assessed from two dimensions. First, perceived susceptibility that refers to the perceived likelihood of experiencing harm in the absence of any action, and second, outcome variables that pertain to the severity of the consequences if damage occurs.⁹ The evaluation of these risks is conducted in relation to the expected costs and benefits associated with taking measures to prevent potential harm. Risk perception can have a significant influence on the decision-making process regarding vaccine choices, manifesting in two distinct manners. The perception of risks associated with vaccine-preventable diseases can serve as a motivating factor for individuals to opt for vaccination. Conversely, the perception of risks associated with vaccines themselves can result in vaccine hesitancy.

Additionally, the perceived risks associated with vaccines, whether real or imagined, are more apparent than the individual benefits that vaccines may provide. In contrast to the opposite, the decision to refrain from vaccination can be reversed. Indeed, a plethora of studies have consistently demonstrated that individuals exhibit a greater level of apprehension toward the potential risks associated with taking action, such as receiving a vaccine that is perceived as “unsafe,” as opposed to the risks associated with inaction, such as contracting a preventable disease for which a vaccine is available. The phenomenon described in this context is commonly known as “omission bias.”¹⁰

Conisdering this discourse, the primary objective of this study was to explore the different conceptions and social stigma surrounding the COVID-19 vaccine in Pakistan. The country belongs to the category of those countries where different competing conceptions have become associated with the COVID-19 vaccine. These narratives have also affected individuals with higher education to exhibit hesitancy toward the vaccine. The other purpose regarding conducting this study was to provide an example of the impact of the polio vaccine in what is called the “culture of vaccine acceptability or rejectability.”¹¹

Pakistan remains one of the two countries that have not yet achieved polio-free status. The persistence of polio in the country can be attributed to the prevalence of various competing narratives surrounding the polio vaccine. These rumors have led to a reluctance among parents to vaccinate their children. Likewise, Ali and colleagues¹² found out in their study conducted in a small village in Pakistan’s Sindh province, where local people refused the routine polio vaccine whilst linking it to the conspiracy theories around COVID-19. The authors show how old and new narratives were weaved together. It happened when the temporarily haled vaccination program due to the pandemic was resumed in July 2020. They harbored suspicions that both the vaccine and COVID-19 were part of a “Western plot.”¹² The emergence of conspiracy theories, is also associated with specific geopolitics, thus has led to increased doubts, outright rejection of vaccines, and even the targeted killings of some vaccinators.¹³ Situating within this landscape, the present study emphasized the psychological and social factors that contribute to vaccine hesitancy and vaccine acceptance among the general population. The study aimed to examine the psychological determinants of vaccine hesitancy and acceptance, taking into account the previous review of the literature and theoretical framework.

Methods and materials

Research design

The current cross-sectional study examined the correlation between COVID-19 related distress, risk perception, and stigma, and their impact on vaccine hesitancy and acceptance among the general population. Data were gathered from Islamabad and Rawalpindi, Pakistan. It is necessary to briefly mention sampling strategy. Primarily, the sample for this study was estimated using Raosoft software, which takes the population size estimate, confidence interval (95%), and margin of error into account (5%t). The estimated size of the population was 370–420 adults from Rawalpindi and Islamabad, ranging in age from 19 years to 65 years. However, 360 individuals participated in this study. The Raosoft calculator used the following formula to calculate the sample size:

$\mathrm{X}=\mathrm{Z}\left(\mathrm{c}/100\right)2\mathrm{r}\left(100-\mathrm{r}\right)$

$\mathrm{n}=\mathrm{Nx}/\left(\left(\mathrm{N}-1\right)\mathrm{E}2+\mathrm{x}\right)$

$\mathrm{E}=\mathrm{Sqrt}\left[\left(\mathrm{N}-\mathrm{n}\right)\mathrm{x}/\mathrm{n}\left(\mathrm{N}-1\right)\right]$

Here, N represents the size of the population, r measures the proportion of reactions that you are interested in, Z(c/100) represents the level of significance for the confidence interval c, n represents the sample size, and E indicates the error rate.

Throughout the current study, a convenient sampling strategy was adopted, with each participant who met the required inclusion and exclusion criteria and agreed to participate being recruited as a study sample. As a result, the current study included 360 people (178 males and 182 females). Since this study was conducted during the pandemic, when standardized operating protocols (SoPs) such as lockdown were put in place, it was neither possible nor permissible to collect data in person. Convenient sampling appeared to be a more feasible sampling strategy, allowing the induction of participants for this research. However, inclusion criteria were applied, ensuring that only those individuals who had not received the COVID-19 vaccine participated. To reach the target population, we created an online questionnaire that was distributed on various social media platforms, including Facebook and WhatsApp. It is important to acknowledge that this method represents one of the limitations of our research.

The researchers obtained informed consent from the participants prior to conducting the study. The age range of the participants in the study spanned from 19 years to 65 years. The inclusion criteria for participants were as follows: The study included participants who were 19–65 years from the general population. Only individuals who were not vaccinated were included. The study utilized the following instruments.

COVID stress scale (CSS)

Taylor and colleagues (2020) developed the CSS to assess and identify distress related to the pandemic.¹⁴ Many individuals experienced stressors and anxious reactions during pandemics, such as worrying about becoming infected, fear of coming into contact with contaminated surfaces and equipment, fear of immigrants who may be carrying the virus, concerns about the socio-economic impact of the pandemic, and engaging in obsessive checking behaviors (e.g., nightmares, intrusive thoughts). The scale consisted of five subscales, which included: (1) fears of danger and contamination, (2) fears about economic consequences, (3) xenophobia, (4) compulsive checking and seeking reassurance, and (5) traumatic stress symptoms related to COVID-19.The responses were rated on a 5-point scale from 0 (not at all) to 4 (extremely).¹⁴

Hospital anxiety and depression scale (HADS)

The Hospital Anxiety and Depression Scale (HADS), developed by Zigmond and Snaith, (1983) and is a widely used tool for doctors to assess levels of depression and anxiety in individuals.¹⁵ The HADS is a fourteen-item scale that measures anxiety and depression. It consists of seven items for each component. Zigmond and Snaith developed this outcome measure specifically to reduce reliance on symptoms that are common to both these disorders and physical illnesses, such as fatigue, insomnia, or hypersomnia. The responses ranged from 0 to 3, with a maximum score of 21 and a minimum score of 0.The scoring for both depression and anxiety was categorized as normal (8–10), borderline abnormal (11–14), and abnormal (15–21).¹⁵

Risk percept COVID-19 scale

The Risk Percept COVID-19 questionnaire, developed by Jahangiry and colleagues (2020), aims to comprehend how people perceive, interpret, and respond to information about the risks associated with COVID-19.¹⁶ After screening, 29 questions were selected and classified into four factors with corresponding item numbers: perceived response efficacy (2, 3, 4, 5, 6, 7, and 15), defensive response (18, 19, 20, 21, 22, 23, 24, and 25), perceived self-efficacy (8, 9, 11, 12, 13, and 14), and perceived threats (10, 16, 17, 26, 27, 28, 29). The items were rated on a scale from 1 (strongly disagree) to 5 (strongly agree).¹⁶

COVID-19 stigma discrimination scale

The questionnaire consisted of 11 items with binary responses of ‘yes’ or ‘no’, seven of which were developed from the scale of stigma toward such tuberculosis,¹⁷ and four additional features designed by Cassiani-Miranda and colleagues (2021), which symbolized more particular elements of COVID-19 virus and its infectious disease complexities.¹⁸ This scale showed good alpha reliability i.e., .86 which shows this instrument to be reliable.¹⁸

Oxford covid-19 vaccine hesitancy scale

It was a seven-item scale developed by Freeman and colleagues (2021) also based on a study of 5,114 people from United Kingdom who were quota sampled to match the population for age, gender, ethnicity, income, and geography.¹⁹ Item-specific response options were used, coded from 1 to 5. There was also a ‘Don’t know’ option, which was not scored. Higher scores indicated a greater level of vaccine hesitancy.¹⁹

Vaccine acceptance instrument

The scale, consisting of 20 items, was developed by Sarathchandra and colleagues in 2018.²⁰ The current study utilized a shortened version of the instrument, consisting of 10 items.²⁰ The first two sub-scales, “perceived vaccine safety” (items 1–2) and “perceived vaccine effectiveness and necessity” (items 3–4), focus on the key concerns of vaccine safety and efficacy. The third sub-scale, “acceptance of vaccine selection and scheduling” (items 5–6), examines attitudes and concerns regarding the quantity and timing of vaccines. This can lead to various justifications and political implications. The fourth sub-scale, “positive values and affect towards vaccines” (items 7–8), explores the emotional and moral factors that may influence individuals’ decision to get vaccinated, regardless of the specific safety, effectiveness, and scheduling aspects. The fifth sub-scale, “perceived legitimacy of authorities to require vaccinations” (items 9–10), explores attitudes toward immunization that are relevant to public policy and have recently become a subject of political contention. The instrument used a 7-point Likert scale, ranging from 1 (strongly agree) to 7 (strongly disagree).²⁰

Ethical considerations

Before conducting the current research investigation, the American Psychological Association (2019) ethical requirements were followed. Permission was given by the institutional research and ethical board of Fatima Jinnah Women University in Rawalpindi.

Results

Data were analyzed using SPSS. Descriptive information was used to explain the socio-demographic characteristics of the research participants. Correlational analysis was used to examine the relationship between vaccine hesitancy, vaccine acceptability, and sociodemographic and psychological variables. Multiple hierarchical regressions were used to identify the main psycho-social predictor (COVID-19 related distress, risk perception, and stigma) of vaccine hesitancy and acceptance in the general population during the pandemic, after controlling for demographic variables. The study used an independent sample t-test to identify differences in vaccine hesitancy and acceptance levels between male and female participants.

The Table 1 represents relevant demographic data within the context of our study. The distribution of male and female participants is effectively delineated, with males comprising 49.4% (n = 178/360) and females accounting for 50.6% (n = 182/360) of the total sample size. Furthermore, this table provides information on the educational qualifications of the participants, which cover a wide range of categories. The study population encompasses individuals with qualifications ranging from matriculation (n = 29/360, 8.1%) to intermediate (n = 79/360, 21.9%), graduates (n = 117/360, 32.5%), and post-graduates (n = 135/360, 37.5%).The table also provides information about the marital status of the participants. It shows that both married individuals (n = 177/360, 49.2%) and unmarried individuals (n = 183/360, 50.8%) actively participated in the research. Additionally, it provides insight into the age distribution of the participants, categorizing them into distinct life stages: young adults (n = 182/360, 50.5%), middle adults (n = 108/360, 30.01%), and older adults (n = 70/360, 19.4%). This tabulation includes the family income levels of the study participants. The income categories are as follows: less than 50,000 (n = 144/360, 40%), 51000 to 1 lac (n = 110/360, 30.5%), 1 lac to 1.5 lac (n = 32/360, 8.8%), and more than 2 lacs (n = 14/360, 3.8%).

Table 1. Participants’ demographic details, frequencies and percentages (N = 360).

Variables	Classification	F	%
Gender	Male	178	49.4
	Female	182	50.6
Education level	Matric	29	8.1
	Intermediate	79	21.9
	Graduation	117	32.5
	Post-graduation	135	37.5
Marital status	Married	177	49.2
	Un-Married	183	50.8
Age	Young adult (19–35)	182	50.5
	Middle Adult (36–54)	108	30.1
	Older Adult (55–above)	70	19.4
Family income	Less than 50k	144	40.0
	51000 to 1 lac	110	30.5
	1 lac to 1.5 lac	60	16.6
	1.5 lac to 2 lac	32	8.88
	More than 2 lac	14	3.88

N = Total Participants, f = frequency, % = percentage.

The Table 2 shows that a higher number of participants, specifically 250 individuals, experienced severe levels of COVID-related stress. Additionally, 63 individuals reported high levels of stress, accounting for 69.4% and 17.5% respectively. The study found that anxiety levels were higher among 190 individuals, with 52.8% reporting high anxiety, compared to only 24.4% of the 88 individuals surveyed. On the depression scale, 51.1% of individuals were classified as abnormal (184 individuals), 23.3% as borderline abnormal (92 individuals), and 25.6% as normal (92 individuals).

Table 2. Levels of depression, anxiety and stress among the Respondents’ frequencies and percentages (N = 360).

Scales	Classification	F	%
COVID-related Stress	Low	7	1.9
	Mild	3	0.8
	Average	37	10.3
	High	63	17.5
	Severe	250	69.4
Anxiety	Normal	88	24.4
	Borderline abnormal	82	22.8
	Abnormal	190	52.8
Depression	Normal	92	25.6
	Borderline abnormal	84	23.3
	Abnormal	184	51.1

N = Total Study’s Participants, f = frequency, % = percentage.

The Table 3 gives insights into the attitudes and perceptions of study participants regarding vaccines, risk perception, and COVID-related stigma. Data within the table highlight certain noteworthy trends. These data indicate a substantial degree of vaccine hesitancy, with a sample size of 241 individuals. Out of this group, a significant majority (66.9%) showed a higher level of vaccine hesitancy, while the remaining 33.1% expressed lower levels of hesitancy toward vaccination. In contrast, when it comes to vaccine acceptance, a different pattern emerges. Out of the 360 participants, 210 individuals, accounting for 58.3% of the sample, showed a significantly high level of acceptance toward vaccines. In contrast, 41.7% of the participants (150 individuals) reported lower levels of acceptance. Data indicate that 188 individuals, or 52.2% of the sample, had a higher level of risk perception, while 172 individuals (47.8%) had lower levels of risk perception. The data provides insights into the prevalence of COVID-related stigma. Out of the study participants, 173 individuals (51.9% of the cohort) experienced a higher level of stigma associated with COVID-19. Conversely, 187 individuals, accounting for 48.1% of the sample, demonstrated a comparatively lower level of COVID-related stigma. This table encapsulates key findings pertaining to attitudes and perceptions within the study population, thereby offering valuable insights for further analysis and exploration within the context of our research.

Table 3. Levels of vaccine hesitancy, vaccine acceptance, risk perception and COVID stigma discrimination among the Respondents’ frequencies and percentages (N = 360).

Variables	Category	f	%
Vaccine hesitancy	Low	119	33.1
	High	241	66.9
Vaccine acceptance	Low	150	41.7
	High	210	58.3
Risk perception	Low	172	47.8
	high	188	52.2
COVID Stigma discrimination	Low	187	51.9
	High	173	48.1

N = Total Study’s Participants, f = frequency, % = percentage.

The Table 4 unveils a comprehensive matrix of correlation coefficients between various psychological and sociological factors, revealing their intricate interplay with vaccine hesitancy and acceptance. These correlations underscore pivotal associations within the study’s context, bearing implications for our understanding of public health behavior. First and foremost, it is evident that vaccine hesitancy exhibits a strong inverse association with several key variables. Notably, a significant negative relationship is observed between vaccine hesitancy and COVID stress danger (r = −.59, **p < .01), COVID stress socioeconomic status (r = −.58, **p < .01), Xenophobia (r = −.62, **p < .01), COVID stress contamination (r = −.64, **p < .01), COVID stress trauma (r = −.70, **p < .01), COVID stress compulsive checking (r = −.70, **p < .01), anxiety (r = −.54, **p < .01), depression (r = −.57, **p < .01), risk perception response efficacy (r = −.57, **p < .01), risk perception self-efficacy (r = −.62, **p < .01), and risk perception threats (r = −.24, **p < .01).This suggests that individuals who have lower levels of anxiety, stress, depression, and risk perception are more likely to be hesitant about getting vaccinated. In contrast, a positive link emerges between COVID stigma discrimination and vaccine hesitancy (r = .54, **p < .01).This suggests that vaccine hesitancy is positively associated with experiencing COVID-related stigma. It indicates that individuals who are hesitant to receive the vaccine may also bear the burden of elevated stigma.

Table 4. Relationship between COVID distress, risk perception, COVID stigma, vaccine hesitancy and vaccine acceptance.

	Variable	i	ii	iii	iv	v	vi	vii	viii	ix	x	xi	xii	xiii	xiv	xv
i	COVID stress (danger)	1	.72**	.62**	.67**	.66**	.66**	.48**	.47**	−.53**	−.20**	−.60**	−.29**	−.58**	−.59**	.51**
ii	COVID stress (socioeconomic consequences)
			1	.66**	.74**	.68**	.68**	.53**	.55**	−.51**	−.16**	−.55**	−.29**	−.59**	−.58**	.55**
iii	COVID stress (xenophobia)			1	.78**	.76**	.72**	.59**	.57**	−.50**	−.14**	−.53**	−.23**	−.64**	−.62**	.64**
iv	COVID stress (contamination)				1	.81**	.77**	.61**	.58**	−.58**	−.17**	−.61**	−.31**	−.66**	−.64**	.64**
v	COVID stress (trauma)					1	.84**	.63**	.64**	−.59**	−.20**	−.62**	−.32**	−.60**	−.70**	.70**
vi	COVID stress (compulsive checking)						1	.61**	.65**	−.55**	−.21**	−.62**	−.28**	−.61**	−.70**	.66**
vii	Anxiety (HADS)							1	.83**	−.61**	−.29**	−.55**	−.44**	−.50**	−.54**	.54**
viii	Depression (HADS)								1	−.64**	−.26**	−.59**	−.42**	−.46**	−.57**	.59**
ix	Risk Perception (response efficacy)									1	.47**	.82**	.63**	.50**	−.57**	.51**
x	Risk Perception (defensive response)										1	.54**	.83**	.072	−.09	.40**
xi	Risk Perception (self-efficacy)											1	.69**	.51**	−.62**	.73**
xii	Risk Perception (threats)												1	.18**	−.24**	.49**
xiii	COVID stigma discrimination													1	.54**	−.52**
xiv	Vaccine hesitancy														1	−.74**
xv	Vaccine acceptance															1

Conversely, examining the relationship with vaccine acceptance reveals an opposing pattern. Vaccine acceptance is positively correlated with several variables, including COVID stress danger (r = .51, **p < .01), COVID stress socioeconomic status (r = .55, **p < .01), Xenophobia (r = .64, **p < .01), COVID stress contamination (r = .64, **p < .01), COVID stress trauma (r = .70, **p < .01), COVID stress compulsive checking (r = .66, **p < .01), anxiety (r = .54, **p < .01), depression (r = .59, **p < .01), risk perception response efficacy (r = .51, **p < .01), risk perception self-efficacy (r = .73, **p < .01), risk perception defensive response (r = .40, **p < .01), and risk perception threats (r = .49, **p < .01).This indicates that individuals who have greater concerns about the threat of the virus and are more willing to get vaccinated tend to have higher vaccine acceptance.

A contrasting inverse relationship is observed between COVID stigma discrimination and vaccine acceptance (r = −.52, **p < .01). This suggests that individuals who experience COVID-related stigma are less likely to accept the vaccine, potentially due to fears or apprehensions associated with vaccination. It is worth noting that vaccine hesitancy and acceptance are also intricately related (r = −.74, **p < .01), emphasizing that higher levels of hesitancy are associated with lower levels of acceptance of vaccines. This nuanced web of connections highlights the multifaceted nature of public health decision-making and emphasizes the significance of considering psychological and sociological factors in vaccination campaigns.

The Table 5 illustrates a strong positive correlation between vaccine acceptance and gender. The results indicated a significant positive relationship between gender and vaccine acceptance selection schedule (r = .78, **p < .01), vaccine acceptance perceived safety (r = .76, **p < .01), vaccine acceptance perceived effectiveness (r = .79, **p < .01), vaccine acceptance positive values (r = .63, **p < .01), and vaccine acceptance perceived legitimation (r = .85, **p < .01). The study also found significant positive associations between education and vaccine acceptance selection schedule (r = .60, **p < .01), vaccine acceptance perceived safety (r = .59, **p < .01), vaccine acceptance perceived effectiveness (r = .58, **p < .01), and vaccine acceptance positive values (r = .49, **p < .01). Additionally, vaccine hesitancy was found to be significantly associated with the gender, education, and marital status of the study participants.

Table 5. Relationship between vaccine acceptance, vaccine hesitancy and sociodemographic variables.

	Variable	i	ii	iii	iv	v	vi	vii	viii	ix	x	xi	xii
i	age	1	−.30**	.05	−.05	−.70**	−.14**	−.25**	−.11*	−.15**	−.28**	−.24**	.28**
ii	gender		1	.16**	−.09	.17**	.24**	.25**	.28**	.15**	.30**	.32**	−.27**
iii	education			1	−.07	−.07	.35**	.16**	.34**	.15**	.35**	.36**	−.28**
iv	income				1	.06	−.03	−.06	−.00	−.09	−.06	−.06	.02
v	marital status					1	.00	.15**	.10	.18**	.19**	.16**	−.19**
vi	vaccine acceptance (selection schedule)						1	.47**	.53**	.34**	.60**	.78**	−.64**
vii	vaccine acceptance (perceived safety)							1	.50**	.35**	.59**	.76**	−.53**
viii	vaccine acceptance (perceived effectiveness)								1	.34**	.58**	.79**	−.49**
ix	vaccine acceptance (positive value)									1	.49**	.63**	−.47**
x	vaccine acceptance (perceived legitimation)										1	.85**	−.72**
xi	vaccine acceptance											1	−.74**
xii	vaccine hesitancy												1

*p < .05, **p < .01.

In the initial step of our analysis, we introduced four crucial demographic variables into the model to assess their impact on vaccine hesitancy: age, gender, income, and education (see Table 6). The outcome of this modeling endeavor elucidated that these demographic factors collectively accounted for 27% of the variability observed in the dependent variable. The overall model exhibited a remarkable level of statistical significance in predicting vaccine hesitancy, with an F-statistic of F (5,348) = 16.98, p < .001, and an associated R² of .28.Notably, within this preliminary model, gender (β = .20; p < .01) and education (β = −0.22; p < .01) were found to be the most significant predictors of vaccine hesitancy.

Table 6. Hierarchical multiple regression for variables predicting vaccine hesitancy (N = 360).

Variables	R	R^2	Δ R^2	B	SE	β	t	Sig
Step 1	.54	.27	.27
(Constant)				23.2	3.676		6.32	<0.01
Age				.179	.057	.209	3.14	.049
Gender				−1.49	.755	−.098	−1.97	<0.01
Education				−1.77	.380	−.222	−4.66	.000
Income				−1.97	.000	−.034	−.728	.467
Step 2	.75	.56	.55
(Constant)				17.3	4.54	.029	3.83	<0.01
Age				.105	.046	.123	2.30	.022
Gender				.702	.609	.046	1.15	<0.01
Education				−.150	.325	−.019	−.463	.644
Income				7.56	.000	.013	.344	.731
Marital Status				−.314	.785	−.021	−.400	.690
Stress				.114	.017	.479	6.80	<0.01
Anxiety (HADS)				−.102	.110	−.066	−.927	.355
Depression (HADS)				.493	.116	.299	4.26	.300
Risk Perception				.041	.040	.044	1.03	<0.01
COVID Stigma Discrimination				−.316	.154	−.107	−2.04	.041

R = Correlation, R² = Variance, Δ R² = Change in R², β = Standardized Coefficient, B = Unstandardized Coefficient, SE = Standard Error.

**p < .01***p < .001.

In the second step of our analysis, we maintained the demographic variables as controlled factors and introduced COVID-19 related distress, risk perception, and stigma to the model. The expanded model significantly improved our ability to explain vaccine hesitancy, accounting for 56% of the total variance. This heightened explanatory power was notably significant, as indicated by an F-statistic of F (5,343) = 42.90, p < .001, with an associated R² of .55.The inclusion of these variables significantly contributed to explaining an additional 29% of the variation in vaccine hesitancy, beyond the influence of socio-demographic factors.

Within this augmented model, it was revealed that stress (β = .47; p < .01) and risk perception (β = 0.044; p < .01) emerged as the most salient indicators of vaccine hesitancy. These findings underscore the pivotal role played by psychological and perceptual factors in shaping individuals’ attitudes toward vaccination. Gender remained a significant predictor of vaccine hesitancy, even when considering other influential variables.

Our modeling approach provides a comprehensive understanding of vaccine hesitancy, showing how socio-demographic and psychological factors are interconnected. These findings not only improve our understanding of vaccination behavior but also underscore the enduring relevance of certain demographic variables, particularly gender, in influencing individuals’ vaccination decisions.

The four socio-demographic variables (age, gender, income and education) were included in the model to observe their influence in the step one (see Table 7). The model’s result explained 33% of the alteration in the dependent variable and this model statistically significantly predicted vaccine acceptance, F (5,348) = 22.44, p < .0001, R² = .33. In addition, gender (β = 0.17; p < .001) and education (β = 0.26; p < .001) was found to be the most substantial predictor of vaccine acceptance.

Table 7. Hierarchical multiple analysis for variables predicting vaccine acceptance (N = 360).

Variables	R	R^2	Δ R^2	B	SE	Β	t	Sig
Step 1	.57	.33	.31
(Constant)				28.17	4.069		6.92	<0.01
Age				−.148	.063	−.152	−2.35	.019
Gender				2.975	.835	.171	3.56	<0.01
Education				2.432	.420	.267	5.78	<0.01
Income				1.74	.000	.003	.058	.954
Step 2	.80	.63	.62
(Constant)				26.65	4.719		5.64	<0.01
Age				−.019	.048	−.019	−.393	.695
Gender				1.474	.633	.085	2.32	<0.01
Education				.404	.338	.044	1.19	<0.01
Income				−1.23	.000	−.018	−.538	.591
Marital Status				.563	.816	.032	.691	.490
Stress				−.159	.017	−.589	−9.15	<0.01
Anxiety (HADS)				.183	.115	.103	1.59	.112
Depression (HADS)				−.240	.120	−.128	−1.99	.047
Risk Perception				.275	.041	.258	6.65	<0.01
COVID Stigma Discrimination				.257	.160	.076	1.60	.109

** p < .01, ***p < .001.

In the second step, demographic variable was controlled and COVID-19 related distress, risk perception and stigma were added which described about 63% for the total variance and this model was significant at, F (5,343) = 62.20, p < .01, R² = .63. This model explained that addition of these variable accounted for extra 30% variance occurred for vaccine acceptance after controlling the socio demographic variables. Moreover, stress (β = -.58; p < .01) and risk perception (β = 0.25; p < .01) were found to be the most significant predictors of vaccine acceptance.

The Table 8 describes that there is significant gender difference existed for vaccine hesitancy among gender, such as mean for females was (M = 29.27, SD = 6.38), for males (M = 25.01, SD = 8.17) which was significant as the t = 5.50** as p value was smaller than .05, which indicated females’ participants showed higher vaccine hesitancy as compared to males. Cohen’s d value for vaccine hesitancy i.e. 58 also specified medium effect size between groups of males and females.

Table 8. Independent T-Test for vaccine hesitancy and vaccine acceptance within male and female participants (N = 360).

Scales	Female n = 182		Male n = 178				0.95% CI for Mean Difference
	M	SD	M	SD	t	p	L	U	Cohen’s d
Vaccine hesitancy	29.27	6.38	25.01	8.17	5.507	.000	2.742	5.787	0.58
Vaccine acceptance	26.52	7.73	32.18	8.60	−6.561	.000	−7.355	−3.962	0.69
Vaccine Acceptance (Perceived safety)	5.27	2.23	6.45	2.22	−4.999	.000	−1.637	−.7129	0.53
Vaccine Acceptance (Perceived Effectiveness)	5.79	2.29	7.22	2.60	−5.520	.000	−1.936	−.9189	0.50
Vaccine Acceptance (Selection Schedule)	5.23	2.25	6.39	2.29	−4.833	.000	−1.631	−.6878	0.048
Vaccine Acceptance (Positive Values)	6.55	1.67	7.15	2.08	−3.027	.003	−.9952	−.2113	0.31
Vaccine Acceptance (Perceived Legitimation)	3.67	1.79	4.96	2.22	−6.051	.000	−1.713	−.8726	0.63

N = Total Study’s Participants, f = frequency, % = percentage, SD = Standard deviation.

Above table also indicated that the vaccine acceptance was less in female as compare to males as the mean value of females was (M = 26.52, SD = 7.73), and for males it was (M = 32.18, SD = 8.60) which was significant as t = −6.56** and less than .05. Cohen’s d value for vaccine acceptance i.e., .69 also indicated medium effect size between groups of males and females. Furthermore, the means of subscales of vaccine acceptance also exhibited that males had higher vaccine acceptance than females and females had higher vaccine hesitancy than males.

Discussion

Exerting aglobal influence, the impacts of the COVID-19 pandemic transcended individual experiences, specific national boundaries, and continental demarcations. In order to systematically assess the diverse manifestations of its effects within the context of Pakistan, the present cross-sectional study concentrated on individuals within the age range of 19 to 65 years residing in Rawalpindi and Islamabad. The delineation of the study parameters reflects a deliberate effort to discern the nuanced impact of the pandemic on this specific demographic cohort within the designated geographical locales.

This was a general population that was formally educated and some of them were receiving further education, while others were either employed or retired from the services. The present study focused on the interrelationships among COVID-19-related distress, risk perception, stigma, and the dynamic phenomena of vaccine hesitancy and acceptance within the broader spectrum of the general population.

Our study yielded significant findings regarding the associations between different factors and vaccine hesitancy, particularly in the context of the COVID-19 pandemic. The results showed that vaccine hesitancy was negatively associated with various factors, such as COVID stress danger, COVID stress socioeconomic status, xenophobia, COVID stress contamination, COVID stress trauma, COVID stress compulsive checking, anxiety, depression, risk perception response efficacy, risk perception self-efficacy, risk perception threats, and a positive association with COVID stigma discrimination. These findings align with prior research, reinforcing the interconnectedness of these factors. For example, previous studies have shown that individuals with a heightened perception of risk during outbreaks, such as the SARS outbreak, are more likely to experience worry and negative emotional reactions.²¹

Furthermore, the study identified a positive association between risk perception and individuals’ unwillingness to get vaccinated, consistent with previous research that established links between previous flu vaccinations and acceptance of pandemic vaccines. Having received the flu shot in the past was identified as a strong predictor of pandemic vaccine acceptance.^22,23 It is noteworthy that influenza vaccination rates remain low on a global scale, with only around 36% of adults aged 18 to 64 in the United States receiving the vaccine during the 2018–19 season.²⁴

Gender disparities were observed in the study, with females showing greater vaccine hesitancy compared to males, while males demonstrated higher level of vaccine acceptance. These findings were consistent with existing literature, which consistently shows that males have higher vaccine acceptance rates compared to females. For instance, one study reported that 72% of males were more likely to receive the COVID-19 vaccine compared to 28% of females.²⁵

Moreover, the study’s multivariate hierarchical regression analysis (MHR) confirmed the significance of education, gender, COVID-related stress, and risk perception as key predictors of vaccine acceptance and hesitancy, even after controlling for demographic variables. This aligns with prior research conducted in Turkey, the United Kingdom, and France, which found that greater risk perception and anxiety were associated with higher vaccine acceptance rates. Anxiety was identified as a constructive fear that can drive compliance with public health measures, although discrepancies exist that warrant further investigation into the role of fear and anxiety in vaccination behavior.²⁶ Another study conducted in Italy also indicated that higher risk perception increased the likelihood of vaccine acceptance.²⁷

A global survey conducted in June 2020 found that 71.5% of participants were willing to take a COVID-19 vaccine, with 48.1% open to their employer’s recommendation, and acceptance rates varied across countries, being highest in China (around 90%) and lowest in Russia (less than 55%), with trust in government sources influencing vaccine acceptance.²⁸

The people’s perception of the severity of the COVID-19 pandemic is linked to their understanding of the risks, which motivates them to participate more actively in disease preventive efforts.^29,30 This may be validated by examining vaccines during the Swine flu epidemic and the basic plan of precautionary measures, which corresponds to the conceptual perspective of risk and response evaluations in the usage of a person’s well-being models.^31,32

After people become more aware of the severity of COVID-19, their willingness to use precautionary measures also increased.^33,34 Based on this approach, one study found that fear of contracting COVID-19 and the perceived severity of COVID-19 were both positively and significantly associated with the acceptance of vaccines.³⁵

In Taiwan, a study aimed to assess COVID-19 vaccine acceptability as well as the impact of perceived risks on vaccination acceptance and individual health-protective actions.³⁶ A comprehensive cross-sectional survey of 1020 individuals was conducted. In total, more than half of the respondents were interested in receiving the COVID-19 vaccine, around 63% thought COVID-19 was “not important,” and almost 40% were concerned about contracting COVID-19. Participants who perceived COVID-19 as more severe had a higher likelihood of resisting the vaccine, and those who were worried about the virus had a reduced likelihood of adopting health prevention strategies. The reasons behind vaccine refusal included concerns about unknown side effects and a lack of trust in pharmaceutical companies. Some individuals who had previously refused other vaccines were 2.44 times more likely to reject the COVID-19 shots.³⁶

COVID-19 vaccination acceptability was influenced by participants’ age. In general, vaccine acceptability in Taiwan was lower than in other economically comparable regions. Participants over the age of 65 and those with a bachelor’s degree or above who had previously refused immunizations were less willing to receive the COVID-19 vaccine. Individual health preventive measures were positively correlated with risk perception; however, COVID-19 vaccination acceptance was negatively associated.³⁶

Previous research has established a link between prior flu vaccines and pandemic immunizations, with having received the flu shot in the past being the strongest predictor of pandemic vaccine uptake.^22,23 It’s worth mentioning that global vaccination acceptance for seasonal influenza is relatively low. In the United States, for example, the percentage of influenza vaccination among adults aged 18 to 64 years was around 36% for the 2018-19 season.²⁴ Similarly, vaccination rates are still low in Italy: During the 2018-19 season, 53.1% of people over the age of 65 received the seasonal vaccine, compared to only 15.8% of the total population.³⁷ In this context, the observations that COVID-19 is perceived similarly to influenza, particularly in the early stages of an outbreak, along with the findings that the strongest indicator of immunization against a disease outbreak is prior influenza vaccine experience,^22,23 may lead one to believe that the limited acceptance observed for flu vaccines could also affect people’s willingness to get vaccinated against coronavirus. Experts believe that this finding is particularly concerning because it is anticipated that 75–80% vaccine coverage is required to end the COVID-19 pandemic.^38,39

According to one survey conducted in the United States in the begining of 2020, less than half a percent of citizens were committed to acquiring the SARS-CoV-2 vaccination.⁴⁰ Acceptance percentages were also reported to have declined from 55% in May to 46% in July, indicating a downward trend over time. Meanwhile, similar data was collected in Italy, revealing that only 25% of the population was expected to be immunized for SARS-COVID-2 in May.⁴¹

To maintain a relatively higher vaccination rate, it’s crucial to consider that there may be some anti-vaccine sentiment during the previous epidemic.^22,42,43 Additionally, despite the availability of an H1N1 flu vaccine near the start of the second phase of the epidemic in 2009, vaccination rates were lower than expected, ranging from 0.4 to 59% in twenty-two nations.⁴⁴ Instead of flu inoculation, doubts about the efficacy of vaccines, a lower perception of risk, and fear of adverse reactions remained the most common reasons for refusal.⁴⁵ Several additional studies have found that the perception of risk plays a crucial role in deciding whether or not to get vaccinated^42,43,46,47 and it also influences behavior regarding vaccination.^8,48

Another study explored how perceptions of risk, risk exposures related to COVID-19 (i.e., severity, perceived vulnerability, and fear of COVID-19), and negative attitudes toward general immunization were associated with COVID vaccine acceptance among 1062 college students based on online survey data in South Carolina.⁴⁹ The findings revealed that vaccine acceptance was positively correlated with perceived COVID-19 severity and fear of the coronavirus, while lower vaccine acceptance was associated with higher levels of risk exposure (such as workplace exposures) and negative attitudes toward general immunization. The study’s findings suggested that customized educational messages for students are needed to emphasize the seriousness of COVID-19, especially potential long-term health concerns, address concerns about the side effects of general vaccines by dispelling misconceptions, and target the most vulnerable subgroups who reported higher levels of risk exposure and vulnerability but exhibited low intent to get vaccinated.⁵⁰ Perceptions of risk were found to be negatively associated with vaccination acceptance, suggesting that children exposed to higher levels of risk had a harder time accepting the COVID-19 vaccine.⁵⁰

Furthermore, vaccination as a whole in Pakistan is a highly contested phenomenon as it is related to various sociocultural, economic and geopolitical factors.^12,13,51 Due to these reasons parents become anxious not to choose to vaccinate their children, which results in a critical number of unvaccinated children as well as prevalence of different infectious but vaccine-preventable diseases (VPDs) such as polio and measles.^11,52, Despite a significant attention of government and WHO, polio vaccine appears in a critical state as many parents relate it with “Western plot” to sterilize women to control population.^12,13 That means, right from the beginning of the Expanded Programme on Immunization in 1978, the program received resistance from the general public while relating it to the family planning of Pakistan that was launched in 1953.^11-13,52 People perceived the EPI as the governmental move to replace family planning.

Nevertheless, it is important to acknowledge certain limitations of this study when interpreting and generalizing its findings. Firstly, the research was conducted online via Google Meet sessions, potentially excluding vulnerable populations with limited internet access. Secondly, the overrepresentation of respondents from specific geographic areas may impact the generalizability of the survey. Expanding the sample to include participants from diverse socio-economic backgrounds and ethnicities is recommended. Thirdly, the study’s exclusion of individuals with low education levels, who may not understand English, raises concerns about the representativeness of the sample.Future research should aim to include individuals from diverse backgrounds and provide protocols in both national and local languages.

Notably, this study contributes to the global discourse on vaccine hesitancy by examining the stigma associated with it in the Pakistani context, an area that has received limited attention in the literature. This uniqueness underscores the importance of studying vaccine hesitancy and acceptance from a sociocultural perspective.

Conclusions

Vaccination stands as one of the most triumphant strategies in averting life-threatening, communicable diseases. Indeed, the impact of vaccines has been transformative, markedly diminishing the incidence of several diseases, such as the eradication of poliomyelitis and smallpox in numerous countries. In the aftermath of the COVID-19 pandemic, which has lasted for over two years, and the introduction of COVID-19 vaccines in 2021, countries faced the lingering specter of vaccine hesitancy. This phenomenon is a pivotal and contentious issue in many countires, which has been amplified by conspiracy theories that question the effectiveness of vaccines and make critical claims about their composition, including the potential to cause infertility. Similarly, Pakistan is caught in this web of COVID-19 vaccine skepticism.

Focusing on this skepticism, the current study was devised to examine the interplay between COVID-19-related distress, risk perception, stigma, and the intricate dynamics of vaccine hesitancy and acceptance. Our findings highlight the significant role of stress and risk perception in shaping patterns of vaccine hesitancy and acceptance. Gender disparities exerted a discernible influence, with females exhibiting a more pronounced inclination toward hesitancy, while males displayed a greater propensity to embrace vaccination. Furthermore, educational attainment was found to be a significant factor in vaccine acceptance. This study underscores a positive correlation between COVID-19-related distress, risk perception, and the stigma surrounding vaccine hesitancy, elucidating that individuals grappling with depression, anxiety, and stress are more likely to exhibit hesitancy toward vaccination. The pervasive presence of vaccine-related conspiracy theories contributes to the prevailing uncertainty surrounding vaccine uptake. The problem of vaccine hesitancy in Pakistan highlights the significant impact of psychological factors, including stress, risk perception, and the fear of stigma. Gender and educational disparities, along with the persistent vaccine-related conspiracy theories, further complicate the situation. In addressing this multifaceted challenge, it is crucial to design interventions that target both the logistical aspects of vaccine distribution and the nuanced sociocultural as well as psychological dimensions that shape individuals’ decisions regarding vaccination.

Moving forward, it is suggested that future research should employ a more comprehensive mixed-method approach, including structured in-depth interviews, to explore deeper into the reasons behind low vaccine uptake rates in Pakistan. Longitudinal studies with larger and more diverse participant samples, including both urban and rural areas, should be conducted outside of lockdown periods to provide a more comprehensive understanding of vaccine hesitancy. Finally, conducting cross-cultural studies across different provinces in Pakistan would provide insights into regional variations in vaccine hesitancy and contribute to more targeted public health interventions.

Recommendations

To effectively combat vaccine hesitancy in Pakistan, a multifaceted approach is imperative. First, comprehensive public health education campaigns must be developed to highlight the vital role of vaccines in preventing these infectious diseases. Campaigns should deal with vaccine-related rumors and conspiracy theories through clear, evidence-based messaging with tailored messages to different demographics while considering gender disparities is essential to reach a wider audience.

Community engagement initiatives should be fostered by involving local leaders, religious figures, and community members to establish trust in vaccines and vaccine givers.

It is also necessary to recognize the influence of psychological factors such as stress, depression, and anxiety on vaccine hesitancy.

Gender disparities in vaccine acceptance need to be thoroughly explored to design specific interventions to empower women with accurate information about vaccines. Education initiatives should promote vaccine awareness within the educational system by involving students and parents through schools and colleges.

Cultural sensitivity must be a priority, with messaging and materials tailored to resonate with the local population and aligned with cultural norms. Transparency in the vaccine distribution process is paramount for building trust and requires open communication regarding safety, efficacy, and side effects.

Healthcare workers should be adequately trained to address vaccine hesitancy concerns empathetically and with science-based information. Ongoing monitoring of vaccine acceptance rates and reasons for hesitancy are essential for adapting strategies in real time.

Partnerships and collaborations with international health organizations, local NGOs, and community-based organizations should be established to pool resources and expertise. Ensuring equitable vaccine access, especially in remote or underserved areas, requires addressing logistical challenges and considering incentives to encourage vaccination.

These recommendations should be integrated into a comprehensive strategy to address vaccine hesitancy in Pakistan, considering the intricate interplay of social, psychological, and cultural factors identified in this study.

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Additional information

Funding

The author(s) reported there is no funding associated with the work featured in this article.