# COVID-19 vaccine hesitancy and perceived post-vaccination adverse event: Findings from a cross-sectional survey

Maude Dionne, Chantal Sauvageau, Jeremy Ward, Jérémie Sylvain-Morneau, Fátima Gauna, Radhouene Doggui, Ève Dubé

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Maude Dionne, Chantal Sauvageau, Jeremy Ward, Jérémie Sylvain-Morneau, Fátima Gauna, et al. COVID-19 vaccine hesitancy and perceived post-vaccination adverse event: Findings from a cross-sectional survey. Vaccine, 2025, 62, pp.127529. 10.1016/j.vaccine.2025.127529. hal-05199950

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# COVID-19 vaccine hesitancy and perceived post-vaccination adverse event: Findings from a cross-sectional survey

Maude Dionne<sup>a</sup>, Chantal Sauvageau<sup>a,b,c</sup>, Jeremy K. Ward<sup>d</sup>, Jérémie Sylvain-Morneau<sup>a</sup>, Fátima Gauna<sup>d,e</sup>, Radhouene Doggui<sup>a</sup>, Éve Dubé<sup>b,d,*</sup>

## ARTICLE INFO

**Keywords:**

Vaccine hesitancy
SARS-CoV-2
COVID-19
Adverse events
Nocebo effect
AEFI

## ABSTRACT

**Introduction:** In Quebec, COVID-19 vaccine uptake among adults was high for the first two doses but decreased for the subsequent booster doses. This study assesses the relationships between attitudes towards vaccination and self-reported experience and severity of adverse events following immunization (AEFIs).

**Methods:** A web survey of Quebec adults who received at least one dose of the COVID-19 vaccine was conducted in September 2023. Participants share their level of vaccine hesitancy before vaccination and their experience with AEFIs after receiving a dose. Participants were asked to note the severity of the symptoms they believed were due to vaccination. Intention to receive other vaccines in the future was questioned. Two coders performed a qualitative content analysis on reported AEFIs (N = 3808). Descriptive and multivariate logistic regression analyses were performed.

**Results:** Among the 8419 vaccinated respondents, 46.7 % reported having experienced AEFIs. Fatigue or malaise (20.7 %), injection site disorder (17.3 %), musculoskeletal pain (11.2 %), headache (11.0 %), and fever (10.6 %) were the most commonly reported, respectively. Respondents who were very hesitant before the COVID-19 vaccine reported more frequently having a severe AEFI compared to those who were not hesitant (25.0 % vs 3.4 % =, *p* < 0.001). This affirmation stays true when all severity of adverse events are considered (68.7 % vs 36.9 %) (*p* < 0.001). Younger age (aOR = 0.98), being a female (aOR = 1.31), a higher education level (University degree aOR = 1.56 vs high school or less), being vaccine-hesitant in general (aOR = 1.69 vs non or less hesitant) were significantly associated (*p* < 0.001) with self-reported AEFIs in multivariate analysis. Self-reported AEFIs that prevented doing activities (aOR = 4.87) and being vaccine-hesitant in general (aOR = 4.94) were significantly associated with reduced intention to receive other vaccines in the future.

**Conclusion:** Vaccine hesitancy could influence self-reported AEFIs and their perceived severity. Transparent and tailored communication explaining AEFIs while emphasizing strategies to mitigate these effects could helpful. Our findings also have implications for pharmacovigilance.
301 mots.

## 1. Introduction

During the COVID-19 pandemic, the availability of safe and effective vaccines was a breakthrough in controlling the situation. In Canada, COVID-19 vaccine uptake was above 90 % among Canadian adults for the first two doses but decreased for the subsequent booster doses [1]. The same observation was made in the province of Quebec as vaccine

hesitancy increased among those who had received two or more doses, indicating a shift of change in the perception of vaccination in a fast-moving context (i.e., new variants and preventive measures) [2].

Before the pandemic, vaccine hesitancy (i.e., delay in vaccine acceptance or vaccine refusal despite the availability of vaccination services [3]) was identified by the WHO as a significant threat to population health [4]. During the COVID-19 pandemic, coercive (e.g.,

<footnote><sup>a</sup> Institut national de santé publique du Québec, Québec, Canada</footnote>

<footnote><sup>b</sup> Centre de recherche du CHU de Québec-Université Laval, Québec, Canada</footnote>

<footnote><sup>c</sup> Université Laval, Québec, Canada</footnote>

<footnote><sup>d</sup> CERMES3 (INSERM, CNRS, EHESS), Université de Paris, France</footnote>

<footnote><sup>e</sup> EHESP, CNRS, Inserm, Arènes—UMR 6051, RSMS (Recherche sur les Services et Management en Santé), U 1309, Université de Rennes, France</footnote>

<footnote>* Corresponding author at: Pavillon Charles-De Koninck, 1030 Avenue des Sciences Humaines, Bureau 3433, Québec G1V 0A6, Canada.
E-mail address: eve.dube@ant.ulaval.ca (È. Dubé).</footnote>
vaccine passport, travel bans) and non-coercive (e.g., vaccine lottery, mass educational and promotional campaigns) interventions were implemented in Quebec and may have led vaccine-hesitant individuals to accept vaccination [5].

Vaccine safety concerns are among the main reasons for vaccine hesitancy [3], including COVID-19 vaccine hesitancy [6]. The vaccine safety concerns can be amplified by social contexts (for example, knowing someone who has reported side effects) and the nocebo effects [7,8]. The nocebo effect is defined by the induction or the worsening of symptoms induced by sham or active therapies, such as vaccines [9]. A systematic review and meta-analysis concluded that approximately one-third of placebo recipients in COVID-19 vaccine randomized clinical trials reported at least one systemic adverse event following immunization (AEFI), mainly headache and fatigue, after the first and the second dose [10]. After the first dose of the COVID-19 vaccine, 76 % of systemic AEFIs were classified as nocebo; this proportion was 52 % after the second dose [10].

An increasing number of studies are exploring the relationship between vaccine hesitancy and AEFIs, and this was accelerated during the COVID-19 pandemic [11]. We reproduce and expand on Khouri and al. work in the Quebec context to facilitate comparison and build on it [12]. We explored the relationship between attitudes towards vaccination and Quebecers' perceived onset, severity, and characteristics of AEFIs after COVID-19 vaccination.

# 2. Method

## 2.1. Design and recruitment

Since May 2023, bi-weekly online cross-sectional surveys have been conducted in Quebec to monitor infectious diseases [13]. A population-based database (Clic Santé), including around 6 million Quebecers who had at least taken an appointment for the COVID-19 vaccine, was used to select a probabilistic sample.

Eight sampling strata were created using the sex at birth and age (18–34 y., 35–54 y., 55–64 y., and 65 y. and more) to account for the variations in response rates. A two-stage sampling procedure was performed within each stratum: First, sorting the sampling frame by health region of residence and age of respondents; Second, the systematic selection of adults. The expected sample size was 60,000 for each cycle of data collection.

The questionnaire was designed for surveillance purposes and included 39 items that cover three main sections: 1) COVID-19 infection; 2) Quebecers' perceptions of COVID-19 risks, attitudes, beliefs, knowledge about the pandemic and preventive measures, and behaviours regarding recommended measures; as well as 3) lifestyle and mental health. Data was collected fortnightly (every two weeks) for section 1 and monthly for sections 2 and 3 (alternating). After filling out the survey, participants do not receive further invitations within the next 8 weeks. All responses were anonymous; each participant had a unique link available for 7 days to answer the survey. More details about the survey methodology are available elsewhere [13].

Age, sex at birth, and areas of residency were available through the 'Fichier d'inscription des personnes assurées' database. This database comprises insured persons who are or have been entitled to benefits under the health and drug insurance plans and other programs entrusted to the 'Régie d'assurance maladie.' Vaccination status was available through the provincial vaccination registry. The health insurance number was used to link the 'Clic Santé' database to those databases.

For the following study, the data was collected between September 17th and 23rd, 2023.

## 2.2. Measures

### 2.2.1. Primary outcomes

Participants were asked about their experience of AEFIs after

receiving the vaccination against COVID-19 through the following question: "Have you experienced any side effects that you suspect are associated with vaccination against COVID-19?". Response options ranged from 0 (No, none) to 4 (Yes, they were strong), where higher scores reflect the severity of these sides' effects. An open-ended question allowed participants to note any symptoms they believed were due to vaccination.

Participants were asked about their intention to receive other routine vaccines in the future, and possible responses ranged from 1 ('strongly Agree') to 4 ('strongly Disagree').

For both primary outcomes, two supplementary response options were provided for these questions, namely 'I don't know' and 'I prefer not to answer,' to improve the data quality and response rate.

Analyses using this question are presented in Table and Fig. 2.

### 2.2.2. Exposure variables

Participants were asked to recall their level of vaccine hesitancy before vaccination: 'In general, do you consider yourself hesitant or fearful about vaccination?'. Responses ranged from 1 ('not at all hesitant or fearful') to 4 ('very hesitant or fearful'). Two supplementary response options were provided for these questions: 'I don't know' and 'I prefer not to answer.'

Vaccinated participants were asked to note the severity of the symptoms using the following question: 'Have these side effects affected your daily activities (e.g. work, daily chores, social activities)?'. Response options ranged from 1 ('No, these side effects had no impact on my daily activities') to 3 ('Yes, these side effects prevented me from doing my daily activities (for example, you stayed in bed)'.

Vaccine hesitancy was assessed by the following question: 'In general, do you consider yourself hesitant or fearful about vaccination?' responses included four categories and ranged from 1 ('not at all hesitant or fearful') to 4 ('very hesitant or fearful').

All items included in the analyses are detailed in Supplemental files 1. The complete survey questionnaire is available online [14].

### 2.2.3. Covariates

In addition to age, sex at birth, and area of residency, other covariates have been collected, namely level of education (6 categories: from 'less than secondary (high) school graduation' to 'university diploma') and household size (1 to 5 or more), COVID-19 vaccines are efficient to prevent the disease (Ref.: No), and worried about spreading the COVID-19 (Ref.: No).

Areas of residence were grouped into four categories: census metropolitan areas (CMA) of Montreal, others CMA, cities >10,000 inhabitants, and small towns/rural areas).

### 2.2.4. Data analysis

#### 2.2.4.1. Qualitative.
Under the supervision of the research team, two medical students analyzed qualitative data of all reported AEFIs (N = 3808) by codifying and categorizing them in Microsoft Excel. AEFI categories were defined based on the 100 first responses, the Medical Dictionary for Regulatory Activities (MedDRA) classification, and those from the French study [12,15]. Experts in immunization, public health, and medicine from the Institut national de santé publique du Québec (INSPQ) reviewed the categories that have been developed. A total of 21 categories were proposed. The inter-judge agreement was measured in 20 % of the responses (n = 742). The global Kappa was 0.86, indicating an excellent level of agreement [16]. Two reviewers (medical students) independently categorized the remaining responses, and discrepancies were resolved through discussion between the team and the supervisor.

After performing statistical analyses, categories were reduced to 12, as some categories were merged (ex., ORL and ocular symptoms), and many were incorporated into the "others" category as the rate was too low for further analyses (Supplemental files 2).
**2.2.4.2. Quantitative.** A method was used to calibrate the margins, enabling the weighting of the respondents' sample based on different characteristics of the population (sex, age group (18–34 years, 35–54 years, 55–64 years and 65 years and over), grouping of socio-health regions in four categories,<fnref n="1" /> level of education and living alone) [14]. A quality check was performed to ensure an adequate weighting procedure [14]. All proportions and tests presented in this article are weighted, except the multivariate logistic regressions, which are already adjusted for the variables used to calibrate the model.

Chi-squared tests were used to compare the frequency of AEFIs and their severity for responders who were very hesitant to COVID-19 vaccination with those who weren't hesitant (Figs. 1 and 2). Following a Bonferroni correction to consider the number of AEFI categories, statistical significance was established when the *p*-value was smaller than 0.004 (0.05 / 12).

A complete case analysis was realized, and then categories of ‘I don’t know’ or ‘I prefer not to answer’ were excluded. Multivariate logistic regressions were performed to identify predictors associated with reporting AEFIs after COVID-19 vaccination and those associated with a decrease in intention to receive other vaccines in the future after the occurrence of an AEFI. When the outcome was self-reported, experienced any AEFIs after the COVID-19 vaccination or intention to receive other vaccines in the future, adjustment was made in one set for age, sex at birth (ref. male), education (Ref.: High school or less), prior infection (ref. never), COVID-19 Vaccine doubts (Ref.: not at all/not really), worried about catching the COVID-19 (Ref.: No), Region (Ref. small region and rural area) household (Ref. single person), perceived efficacy of preventive measure (Ref. useless), adherence to hand washing and physical distancing (ref. not always), Vaccine hesitancy (Ref.: not at all/ not really), and AEFIs impacted my daily activities (Ref.: No) [12,17,18].

We used the variance Inflation Factor (VIF) to assess multicollinearity between the different predictors in both models [19]. All VIF values were less than 10 units, indicating the absence of multicollinearity and no impact on the precision of the regression coefficients.

Alpha error was set at a 5 % level.

All statistical analyses were carried out using SAS Software (version 9.4) (SAS Institute Inc. SAS and all other SAS Institute Inc., Cary, NC, USA).

## 2.3. Ethics approval

The Chief Medical Officer legally mandated this study under the Quebec Public Health Act as part of the 2020 COVID-19 investigation. This project was thus not subject to ethics board review. As we were operating under the legal mandate of the National Director of Public Health of Quebec under the Public Health Act, participant consent and approval were automatically waived by the national director. All methods were carried out in accordance with relevant guidelines and regulations.

## 3. Results

A total of 8419 participants responded to the questionnaire, which corresponds to a response rate of 14 %. All the respondents received at least one dose of COVID-19 vaccine. One-third of respondents were 25–44 y/o (32 %) or 60 y/o or more (32 %). Half (51 %) lived in the census metropolitan area CMA of Montreal. Most answered the survey in

French (88 %). Half (51 %) had received 4 doses or more of the COVID-19 vaccine, with an increased number of doses by age. Most (73 %) received their last dose in 2022 (Table 1).

Almost half of respondents (46.7 %, n = 3805) reported having experienced at least one AEFI. The most commonly reported AEFIs were fatigue or malaise (20.7 %), injection site disorder (17.3 %), headache (11.0 %), fever (10.6 %), and musculoskeletal pain (11.2 %) (data not shown). The mean number of reported AEFIs reported by a respondent was around 0.9. It ranged from 0.7 to 1.4.

Respondents who were very vaccine-hesitant were proportionally more likely to report adverse events (68.7 %) than those who were not vaccine-hesitant (36.9 %) (*p* < 0.001). This affirmation stays true when only severe adverse events are considered (25.0 % vs 3.4 %) (*p* < 0.001) (Table 2).

The distribution of the 12 types of AEFIs according to vaccine hesitancy for respondents who indicated they experienced adverse events they think are associated with the COVID-19 vaccine is presented in Fig. 2. A higher proportion of respondents who were very hesitant about the COVID-19 vaccine reported severe adverse events after their COVID-19 vaccination compared with those who were not hesitant about the vaccine (*p* < 0.004).

The type of AEFIs reported also varied according to respondents' level of hesitancy before receiving the COVID-19 vaccine (Fig. 1).

Table 3 presents the multivariate analysis of factors associated with reporting AEFIs after COVID-19 vaccination. Younger age, higher education level, being female, and being hesitant about the COVID-19 vaccine were the most statistically significant predictors of self-reported AEFIs.

Among the 46.7 % of respondents who reported adverse events after vaccination, 27.6 % reported a lower intention to accept routine vaccines in the future. Table 4 presents the results of the multivariate analysis designed to identify factors associated with a decrease in intention to receive other vaccines in the future after the occurrence of an AEFI. Having doubts and being hesitant about the COVID-19 vaccine, not believing that the vaccine is effective in preventing the disease, always adhering to hand washing and social distancing, and having experienced AEFIs that prevented the performance of daily activities were the most statistically significant predictors of reduced intention to receive other vaccines in the future.

## 4. Discussion

Few studies have focused on the link between COVID-19 vaccine hesitancy and the perception of AEFIs. A research team based in France conducted a project to explore the relationship between vaccine hesitancy and the onset, severity, and characteristics of self-reported AEFIs [12]. This study replicated and expanded one survey conducted in France in 2021 [12] in the Quebec context. The main differences between our study and the French survey are that the number of participants in Quebec was larger, and the sampling was probability-based (N = 8419 vs N = 1593). The participation rate was also higher in Quebec (14 % vs 4 %). Despite these differences, our conclusions are aligned.

First, we identified similar reported adverse events (injection site pain, fatigue, pyrexia and headache). The AEFIs reported by the respondents are also similar to those recorded in Quebec's passive surveillance system that monitors vaccine safety since 1990 [7]. The Public Health Act governs this program, and health professionals are legally obliged to report any undesirable or unusual effects that may occur following vaccine administration [7]. The program can detect changes in unusual clinical manifestations, but it does not determine whether there is a causal relationship between the event and vaccination [7]. In Quebec, between December 14, 2020, and May 31, 2022, the passive surveillance program for unusual clinical manifestations after COVID-19 vaccination received 12,494 reports which corresponds to an overall reporting rate of 61 per 100,000 doses administered [7]. An analysis of these declarations concluded that the COVID-19 vaccines administered

<footnote n="1">¹ Four categories: Montréal, North and South shore of Montréal (Montérégie, Lanaudière, Laurentides, Laval), other urban regions (Capitale-Nationale, Mauricie-Centre-du-Québec, Estrie, Outaouais, Chaudières-Appalaches, Saguenay-Lac-St-Jean) and small/rural regions (Bas-St-Laurent, Abitibi-Témiscamingue, Côte-Nord, Nord-du-Québec, Gaspésie-Îles-de-la-Madeleine, Terres-Cries-de-la-Baie-James et Nunavik).</footnote>
<figure><img src="image_3.png" /><figcaption>**Fig. 1.** Type of AEFIs reported by COVID-19 vaccine hesitancy level. <sup>a</sup> Menstrual cycle disorders category was analyzed only for women. * Significant differences between respondents who were not vaccine-hesitant compared to those who were very vaccine-hesitant before COVID-19 vaccination (chi-squared, *p* < 0.004).</figcaption></figure>

<figure><img src="image_4.png" /><figcaption>**Fig. 2.** Proportion (%<sup>a</sup>) of respondents reporting severe AEFIs by COVID-19 vaccine hesitancy level. *Significant differences between respondents with no reluctance and very hesitant to get the COVID-19 vaccine (chi-squared, *p* < 0.004).<sup>a</sup> weighted proportion.</figcaption></figure>

in Quebec appear more reactogenic than the other vaccines in the Quebec immunization program or those against pandemic influenza A (H1N1) [7]. Among the main reported manifestations were injection site reactions, general events, allergic manifestations, dermatological disorders, disorders of the cardiac system, nervous system disorders, hematological and vascular diseases, and menstrual cycle disturbances [7].

Second, similar to the study conducted in France, our findings showed that the more respondents were vaccine-hesitant respondents the more likely they were to report AEFIs and to rate them as severe.

This association was also observed in other COVID-19 studies [20,21], even if the characteristics and factors leading to vaccine hesitancy usually differ across different settings [22]. Hoffman and al. concluded that negative attitudes towards the vaccine predicted a meaningful proportion of COVID-19 vaccine adverse events and that there was a psychosomatic component in vaccinated individuals [18]. Finally, findings of two other studies also indicated that the risk for more severe adverse effects was higher when people were expecting a lower benefit of vaccination [20,24].
<table><caption>**Table 1**
Sociodemographic characteristics of respondents (n=8,419)</caption><thead><tr><th>Variables</th><th>Categories</th><th>N</th><th>%<sup>a</sup></th></tr></thead><tbody><tr><td rowspan="3">Sex at birth</td><td>Male</td><td>3973</td><td>49</td></tr><tr><td>Female</td><td>4446</td><td>51</td></tr><tr><td>18-24</td><td>440</td><td>10</td></tr><tr><td rowspan="3">Age</td><td>25-44</td><td>2561</td><td>32</td></tr><tr><td>45-59</td><td>2341</td><td>26</td></tr><tr><td>≥60</td><td>3077</td><td>32</td></tr><tr><td rowspan="2">Household size</td><td>Person living alone</td><td>2110</td><td>18</td></tr><tr><td>2 persons</td><td>3037</td><td>38</td></tr><tr><td rowspan="3">Education</td><td>3-4 persons</td><td>2562</td><td>34</td></tr><tr><td>5 or more persons</td><td>710</td><td>10</td></tr><tr><td>Highschool or less</td><td>1635</td><td>39</td></tr><tr><td rowspan="5">Geographical area of residence</td><td>College</td><td>2620</td><td>32</td></tr><tr><td>University</td><td>4164</td><td>29</td></tr><tr><td>CMA<sup>b</sup> of Montréal</td><td>4218</td><td>51</td></tr><tr><td>Other CMA</td><td>1983</td><td>22</td></tr><tr><td>Cities of 10,000 to 100,000 residents</td><td>761</td><td>10</td></tr><tr><td rowspan="3">Language of survey completion</td><td>Small towns/rural areas</td><td>1296</td><td>17</td></tr><tr><td>French</td><td>7459</td><td>88</td></tr><tr><td>English</td><td>960</td><td>12</td></tr><tr><td rowspan="3">Vaccinal status</td><td>1 dose</td><td>65</td><td>1</td></tr><tr><td>2 doses</td><td>1296</td><td>20</td></tr><tr><td>3 doses</td><td>2235</td><td>28</td></tr><tr><td rowspan="3">Last COVID-19 vaccine received</td><td>4 doses or more</td><td>4823</td><td>51</td></tr><tr><td>2021</td><td>1552</td><td>23</td></tr><tr><td>2022</td><td>6497</td><td>73</td></tr><tr><td></td><td>2023</td><td>370</td><td>4</td></tr></tbody></table>

<sup>a</sup> weighted proportion.

<sup>b</sup> census metropolitan areas.

<table><caption>**Table 2**
Proportion (%<sup>a</sup>) of AEFIs and severe AEFIs reported by responders according to their level of vaccine hesitancy.</caption><thead><tr><th>Vaccine hesitancy</th><th>n (8,033)*</th><th>The proportion of adverse events reported by responders (%)</th><th>The proportion of severe adverse events reported by responders (%)</th></tr></thead><tbody><tr><td>Not at all hesitant</td><td>3828</td><td>36.9</td><td>3.4</td></tr><tr><td>Not hesitant</td><td>1995</td><td>48.6</td><td>3.9</td></tr><tr><td>A little hesitant</td><td>1566</td><td>55.1</td><td>7.2</td></tr><tr><td>Very hesitant</td><td>644</td><td>68.7</td><td>25.0</td></tr></tbody></table>

<sup>a</sup> weighted proportion.

<sup>*</sup> Excluded participants who answered “I don’t know” or “Prefer not to answer” to the question about vaccine hesitancy (n = 386).

Third, younger age and female gender were significantly associated with higher reporting of AEFIs, as in this study and the French study [12]. In the literature, younger age, being a female, and the level of education were associated with vaccine hesitancy [2]. Being a woman and younger age were also associated with reporting symptoms after the first COVID-19 vaccine in a study conducted in the UK [18]. A study conducted in Australia reported those who experienced an AEFI reported significantly higher levels of injection anxiety than those who did not. In addition, participants were significantly less likely to receive a COVID-19 vaccine if they reported indirect exposure to an uncommon or rare AEFI and indirect exposure to a scientifically unsupported AEFI compared with other AEFIs [23]. As discussed by Khoury and al., it is possible that the perception of an AEFI may reinforce negative personal expectations and concerns about vaccine safety, leading to refusal of further vaccination and increasing the likelihood of experiencing further nocebo effects [12].

Finally, findings of our multivariate regression analysis showed that

<table><caption>**Table 3**
Individual-level factors associated with the self-reported experience of any AEFIs after the COVID-19 vaccination (multivariate analysis; n = 6628).</caption><thead><tr><th>Variable</th><th>Categories</th><th>Odds ratio (CI 95 %)</th></tr></thead><tbody><tr><td><strong>Age</strong><br>(continuous variable)</td><td>NA</td><td><strong>0.98</strong><br>(0.98-0.98)</td></tr><tr><td><strong>Sex</strong><br>(Ref.: Male)</td><td>Female</td><td><strong>1.31</strong><br>(1.18-1.45)</td></tr><tr><td><strong>Region</strong><br>(ref.: small regions)</td><td>Other urban regions</td><td>1.19<br>(0.94-1.51)</td></tr><tr><td></td><td>Metropolitan area of Montreal</td><td>1.17<br>(0.93-1.50)</td></tr><tr><td></td><td>Montréal</td><td>1.19<br>(0.93-1.53)</td></tr><tr><td><strong>Education</strong><br>(Ref.: Highschool or less)</td><td>Community College</td><td><strong>1.28</strong><br>(1.10-1.50)</td></tr><tr><td></td><td>University</td><td><strong>1.56</strong><br>(1.35-1.80)</td></tr><tr><td>Household<br>(Ref.: Single person)</td><td>2 persons</td><td>1.01<br>(0.89-1.16)</td></tr><tr><td></td><td>3 or 4 persons</td><td>0.87<br>(0.75-1.00)</td></tr><tr><td></td><td>5 persons or more</td><td>0.90<br>(0.73-1.11)</td></tr><tr><td>Had the COVID-19<br>(Ref.: never)</td><td>Once or more</td><td><strong>1.19</strong><br>(1.06-1.34)</td></tr><tr><td><strong>COVID-19 Vaccine doubts</strong><br>(Ref.: not at all/not really)</td><td>Very/a little</td><td><strong>1.42</strong><br>(1.23-1.64)</td></tr><tr><td>I consider myself to be at high risk of contracting COVID-19<br>(Ref.: No)</td><td>Yes</td><td>1.09<br>(0.96-1.23)</td></tr><tr><td>COVID-19 will be dangerous for my health<br>(Ref.: No)</td><td>Yes</td><td>1.04<br>(0.91-1.19)</td></tr><tr><td>Worried about catching the COVID-19<br>(Ref.: No)</td><td>Yes</td><td><strong>1.22</strong><br>(1.07-1.38)</td></tr><tr><td>Worried about losing a loved one to COVID-19<br>(Ref.: No)</td><td>Yes</td><td>0.96<br>(0.85-1.08)</td></tr><tr><td>My body will be able to fight off the COVID-19 easily<br>(Ref.: No)</td><td>Yes</td><td><strong>0.87</strong><br>(0.75-1.00)</td></tr><tr><td>Worried about spreading the COVID-19<br>(Ref.: No)</td><td>Yes</td><td><strong>1.20</strong><br>(1.05-1.37)</td></tr><tr><td>Low perceived risk of catching or spreading COVID-19<br>(Ref.: No)</td><td>Yes</td><td>0.91<br>(0.82-1.02)</td></tr><tr><td><strong>Adheres to hand washing and physical distancing</strong><br>(Ref.: Not always)</td><td>Always</td><td>0.94<br>(0.77-1.15)</td></tr><tr><td>Vaccines are efficient in preventing COVID-19<br>(Ref.: No)</td><td>Yes</td><td><strong>0.76</strong><br>(0.60-0.95)</td></tr><tr><td>Hand washing is efficient in preventing COVID-19<br>(Ref.: No)</td><td>Yes</td><td>1.08<br>(0.84-1.41)</td></tr><tr><td>Wearing a mask is efficient in preventing COVID-19<br>(Ref.: No)</td><td>Yes</td><td>1.08<br>(0.89-1.31)</td></tr><tr><td>Social distancing is efficient in preventing COVID-19<br>(Ref.: No)</td><td>Yes</td><td>0.96<br>(0.80-1.14)</td></tr><tr><td><strong>Vaccine hesitancy</strong><br>(Ref.: not at all/not really)</td><td>Very/a little</td><td><strong>1.69</strong><br>(1.43-2.00)</td></tr></tbody></table>

Bolded aOR indicates significance (p < 0.05).

vaccine hesitancy, perceived lack of effectiveness of the COVID-19 vaccine, compliance with preventive measures, and having experienced AEFIs that prevented the performance of daily activities were associated with a lower intention to receive other vaccines in the future. Studies conducted in different settings indicated that people who experienced AEFIs after the COVID-19 vaccination were less likely to get
<caption>**Table 4**</caption>

Individual-level factors associated with reduced intention to receive other vaccines in the future after having experienced any AEFIs following the COVID-19 vaccine (multivariate analysis; *n* = 3029).

<table><thead><tr><th>Variable</th><th>Categories</th><th>Odds ratio (CI 95 %)</th></tr></thead><tbody><tr><td>Age<br>(continuous variable)</td><td>NA</td><td><strong>0.99</strong><br>(0.98-1.0)</td></tr><tr><td><strong>Sex</strong><br>(Ref.: Male)</td><td>Female</td><td>0.93<br>(0.73-1.19)</td></tr><tr><td><strong>Region</strong><br>(ref.: small regions)</td><td>Other urban regions</td><td>1.13<br>(0.62-2.07)</td></tr><tr><td></td><td>Metropolitan area of Montreal</td><td>1.05<br>(0.58-1.91)</td></tr><tr><td></td><td>Montréal</td><td>1.01<br>(0.54-1.88)</td></tr><tr><td>Education level<br>(Ref.: Highschool or less)</td><td>Community College</td><td>0.84<br>(0.58-1.20)</td></tr><tr><td></td><td>University</td><td><strong>0.66</strong><br>(0.46-0.93)</td></tr><tr><td>Household<br>(Ref.: Single person)</td><td>2 persons</td><td>1.07<br>(0.77-1.48)</td></tr><tr><td></td><td>3 or 4 persons</td><td>1.14<br>(0.82-1.58)</td></tr><tr><td></td><td>5 persons or more</td><td>1.12<br>(0.71-1.77)</td></tr><tr><td>Had the COVID-19<br>(Ref.: never)</td><td>Once or more</td><td>0.94<br>(0.72-1.23)</td></tr><tr><td><strong>COVID-19 Vaccine doubts</strong><br>(Ref.: not at all/not really)</td><td>Very/a little</td><td><strong>3.56</strong><br>(2.74-4.64)</td></tr><tr><td>I consider myself to be at high risk<br>of contracting COVID-19 (Ref.: No)</td><td>Yes</td><td><strong>1.01</strong><br>(0.76-1.34)</td></tr><tr><td>COVID-19 will be dangerous for<br>my health<br>(Ref.: No)</td><td>Yes</td><td>1.02<br>(0.75-1.39)</td></tr><tr><td>Worried about catching the<br>COVID-19<br>(Ref.: No)</td><td>Yes</td><td>0.79<br>(0.58-1.07)</td></tr><tr><td>Worried about spreading the<br>COVID-19<br>(Ref.: No)</td><td>Yes</td><td>0.78<br>(0.57-1.06)</td></tr><tr><td>Worried about losing a loved one<br>to COVID-19<br>(Ref.: No)</td><td>Yes</td><td>1.20<br>(0.91-1.57)</td></tr><tr><td>My body will be able to fight off<br>the COVID-19 easily<br>(Ref.: No)</td><td>Yes</td><td>1.20<br>(0.86-1.67)</td></tr><tr><td>Low perceived risk of catching or<br>spreading COVID-19<br>(Ref.: No)</td><td>Yes</td><td>1.03<br>(0.80-1.34)</td></tr><tr><td><strong>Adheres to hand washing<br>and physical distancing</strong><br>(Ref.: Not always)</td><td>Always</td><td><strong>2.46</strong><br>(1.62-3.73)</td></tr><tr><td>Hand washing is efficient in<br>preventing COVID-19<br>(Ref.: No)</td><td>Yes</td><td>1.19<br>(0.67-2.13)</td></tr><tr><td>Vaccines are efficient in<br>preventing COVID-19<br>(Ref.: No)</td><td>Yes</td><td><strong>0.26</strong><br>(0.18-0.37)</td></tr><tr><td>Wearing a mask in public areas is<br>efficient<br>in preventing COVID-19<br>(Ref.: No)</td><td>Yes</td><td>0.65<br>(0.45-0.93)</td></tr><tr><td>Social distancing is efficient in<br>preventing COVID-19<br>(Ref.: No)</td><td>Yes</td><td>0.99<br>(0.70-1.41)</td></tr><tr><td><strong>Vaccine hesitancy</strong><br>(Ref.: not at all/not really)</td><td>Very/a little</td><td><strong>4.94</strong><br>(3.81-6.40)</td></tr><tr><td><strong>AEFIs impacted my<br>daily activities</strong><br>(Ref.: No)</td><td>Yes, and it prevented the<br>responder from doing them</td><td><strong>4.87</strong><br>(3.55-6.68)</td></tr><tr><td></td><td>Yes, and it didn't prevent<br>the responder from doing<br>them</td><td><strong>2.22</strong><br>(1.66-2.95)</td></tr></tbody></table>

Bolded aOR indicates significance (*p* < 0.05).

another dose [21,24-26]. The perception of the effectiveness of the COVID-19 vaccine as a factor influencing the intention to get a booster dose was observed in a study conducted in the UK and Australia [26]. Many other studies reported that those worrying about COVID-19 were more likely to comply with preventive measures like vaccination [25-27].

Negative expectations regarding adverse effects after vaccination can trigger vaccine hesitancy and decrease willingness to receive recommended vaccines, but this can be addressed [25]. Hoffman et al. suggest tailoring public health messaging about the psychosomatic dimensions of the nocebo effects [18]. A study evaluating a comprehensive communication strategy to minimize expectations of nocebo effects compared information about COVID-19 or influenza vaccination using either standard side-effect messaging or messaging enriched with proven elements of expectation-optimizing framing [17]. The results of this randomized experiment showed that positive framing significantly decreased AEFI expectations in the COVID-19 information group. However, their moderation analysis revealed that the framed side-effect communication lowered the expected COVID-19 vaccination uptake willingness in individuals with strong vaccine-hesitant attitudes [17]. An Australian study concluded that empathic recognition, at the community level, of real and perceived AEFI experience and incorporating stories of positive vaccination experiences into interventions to combat vaccine hesitancy could positively impact people who experienced AEFIs' willingness to accept other vaccines [23]. Our findings suggest that public health policies could consider including a measure of attitudes in vaccine safety monitoring systems and strategies. Our short questionnaire could be reused in future pharmacovigilance studies to capture how psychosocial factors shape the reporting and perception of vaccine side effects.

## 4.1. Study strengths and limitations

First, very few studies have looked at a link between vaccine hesitancy and self-reported adverse events after vaccination. Strengths of this study include the large number of respondents and probabilistic sampling to be representative of the Quebec population. However, even with a probabilistic approach and weighting of the estimates, our study might not capture some subgroups of the population (e.g., newcomers, low-income people, First Nations and Inuit). Also, the 'I don't Know' and 'I prefer not to answer' responses have been excluded and treated as missing data. The former category might be associated with lower health literacy and socioeconomic status [28,29]. This could undermine the generalizability of findings and the potential to overlook significant associations. Desirability bias and the inherent subjectivity of self-reported AEFIs could not be excluded, as with any survey. However, this bias should be minimized since the questionnaire was confidential and filled out by the respondents themselves without the help of an interviewer. As most of the respondents received the COVID-19 vaccines more than six months ago, there is a risk of recall bias for example regarding the perception of vaccine hesitancy especially among those that reported AEFIs. However, the particular context of the pandemic and COVID-19 vaccination campaigns is likely to have reduced this bias. The relatively low response rate (14 %) may introduce a selection bias, potentially limiting the generalizability of our findings as well. To mitigate this potential issue, we applied weighting adjustments based on key socio-demographic variables, thereby enhancing the representativeness of our estimates to the target population [29]. Finally, although our findings showed a correlation between some respondents' characteristics and reporting AEFIs or lower intention to receive another vaccine in the future, given the transversal nature of our survey, it is impossible to conclude on causality. However, our findings corroborate the conclusions of other studies conducted in various countries and are aligned with data collected through Quebec's passive pharmacovigilance system, which increases our confidence in their reliability.
# 5. Conclusion

Vaccine hesitancy appears to influence the experience and perceived severity of after COVID-19 vaccination. This finding is important to inform the development of strategies to address vaccine hesitancy, enhance vaccine confidence, and contextualize pharmacovigilance studies' conclusions. Vaccine providers could provide tailored counseling on adverse events management after vaccination. Active surveillance of adverse events after vaccination should also include questions on vaccine attitudes. Future prospective studies could be implemented to untangle the relationship between attitudes and experiences of AEFIs.

Our analyses have revealed an association between vaccine hesitancy and reported AEFIs after COVID-19 vaccination. Our study also highlighted that the perceived severity of AEFIs was higher among vaccine-hesitant respondents. Targeted communication that emphasizes anticipated adverse events and promotes accurate risk perception while focusing on the safety, effectiveness, and benefits of vaccines are needed. Given the nocebo effects, these interventions need to be carefully designed and pre-tested. As it is more difficult to change the attitude of a person who is very hesitant to vaccinate, a patient-centred approach is crucial to build trust and enhance vaccine confidence.

## Authors' contribution

All authors contributed to the project equally.

## CRediT authorship contribution statement

**Maude Dionne:** Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Methodology, Formal analysis, Data curation, Conceptualization. **Chantal Sauvageau:** Writing – review & editing, Writing – original draft, Validation, Supervision, Methodology, Investigation, Formal analysis, Conceptualization. **Jeremy K. Ward:** Writing – review & editing, Writing – original draft, Validation, Methodology, Investigation, Conceptualization. **Jérémie Sylvain-Morneau:** Writing – review & editing, Writing – original draft, Visualization, Validation, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. **Fátima Gauna:** Writing – review & editing, Writing – original draft, Visualization, Validation, Investigation, Conceptualization. **Radhouene Doggui:** Writing – review & editing, Writing – original draft, Validation, Supervision, Project administration, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. **Ève Dubé:** Writing – review & editing, Writing – original draft, Validation, Supervision, Methodology, Investigation, Conceptualization.

## Funding

This project was funded by the Ministère de la Santé et des services sociaux du Québec (2022).

## Declaration of competing interest

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Dre Chantal Sauvageau has research grants paid to the organization (INSPQ or CRCHU de Québec-Université Laval) for clinical trials and epidemiological studies funded by non-profit organizations (MSSS, CIHR, Bill & Melinda Gates Foundation, and Michael Smith Foundation). Dre Sauvageau is an active member of the Comité sur l'immunization du Québec and the National Advisory Committee on Immunization (NACI) HPV Working Group. J.K.W. is a member of the Commission Technique des Vaccinations at the Haute Autorité de la Santé. Other authors have nothing to declare.

## Acknowledgements

We thank the Ministère de la Santé et des services sociaux du Québec for funding this project. We also thank Anais Lachance and Élisabeth Lapointe, two medical students from Laval University, who helped with the qualitative analysis during their public health rotation.

# Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.vaccine.2025.127529.

## Data availability

The data that has been used is confidential.

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