COVID-19 vaccination status and motivators among Canadian health care workers: are they different from the general population?

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Inclusion in an NLM database does not imply endorsement of, or agreement with, the contents by NLM or the National Institutes of Health. Learn more: PMC Disclaimer | PMC Copyright Notice J Occup Health . 2026 Feb 11;68(1):uiag002. doi: 10.1093/joccuh/uiag002 Search in PMC Search in PubMed View in NLM Catalog Add to search COVID-19 vaccination status and motivators among Canadian health care workers: are they different from the general population? Camille Léger Camille Léger 1 Department of Psychology, Université du Québec à Montréal, Montréal, QC, Canada 2 Montreal Behavioural Medicine Centre, Centre Intégré Universitaire de Santé et Services Sociaux du Nord-de-l’Ile-de-Montréal (CIUSSS-NIM), Montréal, QC, Canada Find articles by Camille Léger 1, 2 , Vincent Gosselin Boucher Vincent Gosselin Boucher 3 Department of Physical Activity Sciences, Université du Québec à Montréal, Montréal, QC, Canada 4 Department of Innovation and Research, Ministère de la Santé et des Services Sociaux du Québec, Montréal, QC, Canada Find articles by Vincent Gosselin Boucher 3, 4 , Frédérique Deslauriers Frédérique Deslauriers 5 Department of Psychology, Université du Québec à Montréal, Montréal, QC, Canada 6 Montreal Behavioural Medicine Centre, Centre Intégré Universitaire de Santé et Services Sociaux du Nord-de-l’Ile-de-Montréal (CIUSSS-NIM), Montréal, QC, Canada Find articles by Frédérique Deslauriers 5, 6 , Samir Gupta Samir Gupta 7 Unity Health Toronto, Department of Medicine, Division of Respirology, St Michael’s Hospital, Toronto, ON M5B 1W8, Canada 8 Keenan Research Center, Li Ka Shing Knowledge Institute, St Michael’s Hospital, University of Toronto, Toronto, ON, Canada Find articles by Samir Gupta 7, 8 , Maximilien Vakambi Dialufuma Maximilien Vakambi Dialufuma 9 Montreal Behavioural Medicine Centre, Centre Intégré Universitaire de Santé et Services Sociaux du Nord-de-l’Ile-de-Montréal (CIUSSS-NIM), Montréal, QC, Canada Find articles by Maximilien Vakambi Dialufuma 9 , Michael Vallis Michael Vallis 10 Family Medicine, Adjunct Professor, Department of Psychology and Neuroscience, Dalhousie University, Halifax, NS, Canada Find articles by Michael Vallis 10 , Simon L Bacon Simon L Bacon 11 Montreal Behavioural Medicine Centre, Centre Intégré Universitaire de Santé et Services Sociaux du Nord-de-l’Ile-de-Montréal (CIUSSS-NIM), Montréal, QC, Canada 12 Department of Health, Kinesiology and Applied Physiology, Concordia University, Montréal, QC, Canada Find articles by Simon L Bacon 11, 12 , Kim L Lavoie Kim L Lavoie 13 Department of Psychology, Université du Québec à Montréal, Montréal, QC, Canada 14 Montreal Behavioural Medicine Centre, Centre Intégré Universitaire de Santé et Services Sociaux du Nord-de-l’Ile-de-Montréal (CIUSSS-NIM), Montréal, QC, Canada Find articles by Kim L Lavoie , on behalf of the iCARE Study team , on behalf of the iCARE Study team 13, 14, ✉ Author information Article notes Copyright and License information 1 Department of Psychology, Université du Québec à Montréal, Montréal, QC, Canada 2 Montreal Behavioural Medicine Centre, Centre Intégré Universitaire de Santé et Services Sociaux du Nord-de-l’Ile-de-Montréal (CIUSSS-NIM), Montréal, QC, Canada 3 Department of Physical Activity Sciences, Université du Québec à Montréal, Montréal, QC, Canada 4 Department of Innovation and Research, Ministère de la Santé et des Services Sociaux du Québec, Montréal, QC, Canada 5 Department of Psychology, Université du Québec à Montréal, Montréal, QC, Canada 6 Montreal Behavioural Medicine Centre, Centre Intégré Universitaire de Santé et Services Sociaux du Nord-de-l’Ile-de-Montréal (CIUSSS-NIM), Montréal, QC, Canada 7 Unity Health Toronto, Department of Medicine, Division of Respirology, St Michael’s Hospital, Toronto, ON M5B 1W8, Canada 8 Keenan Research Center, Li Ka Shing Knowledge Institute, St Michael’s Hospital, University of Toronto, Toronto, ON, Canada 9 Montreal Behavioural Medicine Centre, Centre Intégré Universitaire de Santé et Services Sociaux du Nord-de-l’Ile-de-Montréal (CIUSSS-NIM), Montréal, QC, Canada 10 Family Medicine, Adjunct Professor, Department of Psychology and Neuroscience, Dalhousie University, Halifax, NS, Canada 11 Montreal Behavioural Medicine Centre, Centre Intégré Universitaire de Santé et Services Sociaux du Nord-de-l’Ile-de-Montréal (CIUSSS-NIM), Montréal, QC, Canada 12 Department of Health, Kinesiology and Applied Physiology, Concordia University, Montréal, QC, Canada 13 Department of Psychology, Université du Québec à Montréal, Montréal, QC, Canada 14 Montreal Behavioural Medicine Centre, Centre Intégré Universitaire de Santé et Services Sociaux du Nord-de-l’Ile-de-Montréal (CIUSSS-NIM), Montréal, QC, Canada ✉ Corresponding author: Kim L. Lavoie, ( [email protected] ). Received 2025 Sep 6; Revised 2025 Dec 31; Accepted 2026 Jan 13; Collection date 2026 Jan-Dec. © The Author(s) 2026. Published by Oxford University Press on behalf of the Japan Society for Occupational Health. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence ( https://creativecommons.org/licenses/by-nc-nd/4.0/ ), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contact [email protected] for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact [email protected]. PMC Copyright notice PMCID: PMC13089536  PMID: 41608973 Abstract Objectives To determine the prevalence and correlates of COVID-19 vaccine hesitancy among Canadian health care workers (HCWs) and identify motivators for COVID-19 vaccination, compared with the general population (GPop). Methods As part of the iCARE study, 4 cross-sectional age-, sex-, and province-weighted population-based samples of 12 009 Canadians aged 18+ years were recruited between May 2021 and February 2022. Participants self-reported HCW and vaccine status. Results A total of 738 participants identified as HCWs, with 8.5% being vaccine hesitant, versus 12.6% of the GPop ( P = .005). In multivariate analyses, those with a chronic disease were less likely (HCW odds ratio [OR] = 0.34; GPop OR = 0.77) and parents with children <18 years of age in the household were more likely (HCW OR = 2.29; GPop OR = 1.39) to be vaccine hesitant. Needing only a single-dose vaccine (86%; 82.6%), and vaccine safety (46%; 42%) and effectiveness (38%; 37%) were most likely to motivate hesitant HCWs and GPop to get vaccinated. Conclusions Our findings highlight less vaccine hesitancy in HCWs compared with the GPop, despite demographic and motivator correlates being similar. In terms of policy implications, shared interventions emphasizing vaccine safety, reduced illness severity, shorter disease duration, and the advantages of single-dose options may benefit all groups. Keywords: Canadian health care workers, Covid-19 vaccination, motivators Key points What is already known on this topic: The COVID-19 pandemic severely strained health care systems in Canada, leading to high infection rates and absenteeism among health care workers (HCWs), making it crucial to understand vaccine hesitancy and motivators for vaccination among HCWs compared with the general population. What this study adds: This study demonstrates that vaccine hesitancy affects a substantial proportion of HCWs (8%), even after the introduction of mandatory vaccination; there was no prior such report examining Canadian HCWs. HCWs and members of the general population without a chronic disease, and/or who are parents with minors in the household are more likely to be vaccine hesitant. The top motivators for getting vaccinated were related to needing a single dose of the vaccine to be protected, along with confidence in the vaccine’s safety and effectiveness. How this study might affect research, practice, or policy: The findings may inform vaccine acceptance strategies emphasizing single-dose options alongside evidence of safety and effectiveness. Future research should assess the effectiveness of interventions addressing these key motivators. 1. Introduction Since its declaration by the World Health Organization (WHO) in March 2020, 1 the COVID-19 pandemic has caused notable morbidity and mortality as well as economic and social disruption across Canada and the rest of the world. 1 , 2 Health care systems were impacted dramatically by having to absorb the influx of COVID-19 patients in successive waves, manage institutional outbreaks and loss of staff due to quarantine and isolation, and adapt to temporary or permanent staff departures. 3 , 4 From May 2020 to January 2022, over 150 000 Canadian health care workers (HCWs) were infected with SARS-CoV-2 and over 45 died. 5 During this period, as the prevalence of COVID-19 grew, there was increased absenteeism from illness, isolation due to infection, and quarantine due to exposure (particularly among unvaccinated HCWs), which increased the risk of service failure. 3 , 4 , 6 According to Statistics Canada, the health care and social assistance sector experienced higher-than-average absences due to illness or disability in January 2022 (13.3%) compared with the average rate in January 2017, 2018, and 2019 (9.9%). 6 The spread of COVID-19 in health care settings was concerning due to hospitalized patients’ vulnerability to severe disease and death from infection. 3 , 4 The early stages of the COVID-19 pandemic focused on reducing infections through implementation of preventive behaviors and development of therapies and vaccines, which became available at the end of 2020. 7 , 8 Upon receipt of the first doses of vaccine, governments put in place specific immunization strategies that targeted priority populations. Across Canada, HCWs and residents of long-term care facilities were prioritized to receive the first doses of vaccine between December 2020 and May 2021, after which there was a general vaccine release. 9 Despite the widespread knowledge of the role and importance of vaccination among HCWs, many remained unvaccinated or partially vaccinated in the early phase of the COVID-19 pandemic. 10 This not only placed them and their patients at risk, but also may have undermined the public’s confidence in vaccines. It is therefore important to identify the characteristics of HCWs who were vaccine hesitant and what factors might have motivated them to accept vaccination, and to explore if these factors are any different to those in the general population. These data could have implications for future targeted interventions, including specific education and communication strategies designed to engage HCWs to get vaccinated. To address these issues, this study aimed to: (1) determine the prevalence and determinants of vaccine hesitancy among Canadian HCWs and the general population (GPop); and (2) identify HCWs’ primary motivators for vaccination compared with the GPop. 2. Methods 2.1. Study design This study is part of the iCARE Study ( www.icarestudy.com ), an ongoing, international, repeated, cross-sectional survey capturing data on public awareness and attitudes towards COVID-19 and related public health measures led by researchers at the Montreal Behavioural Medicine Centre (MBMC: https://mbmc-cmcm.ca/mbmc/ accessed on 10 March 2026). The protocol of the iCARE study has been published elsewhere, and the Checklist for Reporting Results of Internet E-Surveys (CHERRIES) can be found in Table S1 . 11 , 12 2.2. Study participants and recruitment We report data from 4 cross-sectional cohorts of age-, sex-, and province-weighted population-based samples of Canadians who completed online surveys after COVID-19 vaccines became available (Period 1: May 31-June 14, 2021; Period 2: September 10-20, 2021; Period 3: November 15-December 3, 2021; and Period 4: January 20-February 2, 2022). The services of the Léger Opinion© polling firm were retained to obtain representative Canadian samples. Léger recruited adults (18+) through its Leo panel ( https://legeropinion.com ), which includes over 400 000 Canadians. Respondents were invited by email to complete a voluntary, self-administered online survey via a unique link, ensuring single entry. Consent was obtained online before participation. The survey’s first page provided details on the iCARE Study’s purpose, investigators, eligibility, duration, data privacy, risks, ethical approval, and the right to skip questions or withdraw. No personal identifying information was collected. Participants received “points” from the polling firm, redeemable for gift cards. The research team provided no direct compensation. 11 Using data from Statistics Canada, results were weighted by age and sex within each province, then adjusted to reflect each province’s share of the Canadian population. 13 The study was approved by the Research Ethics Committee at the Centre Intégré Universitaire de Santé et de Services Sociaux du Nord-de-l’Île-de-Montréal (CIUSSS-NIM) (REB#: 2020-2099/03-25-2020). Our sample included a total of 12 009 respondents (survey 1, n = 3002; survey 2, n = 3004; survey 3, n = 3002; and survey 4, n = 3001). Response rates ranged between 11.4% (survey 4) and 13.2% (survey 2), which is average for online panels. 14 Of 12 009 participants, 2559 identified as essential workers, 4413 identified as nonessential workers, and 5037 responded with “I don’t know/prefer not to answer,” placing them in the GPop category. Essential workers were then asked whether they were HCWs; 772 responded “yes” and were classified as HCWs, whereas 1776 answered “no” and were placed in the GPop category. An additional 11 participants did not respond and were also placed in the GPop category. After categorizing participants by vaccination status and excluding those who did not answer this question (HCWs excluded, n = 34; GPop excluded, n = 124), 738 HCWs and 11 113 GPop remained (see Figure S1 ). 2.3. iCARE survey questionnaire The survey was designed by a multidisciplinary expert panel to measure constructs related to the Capability, Opportunity, Motivation-Behavior (COM-B) Model and the Health Belief Model of behavior. 15 , 16 It was then tested for usability and functionality with a small group of representative participants by Léger Opinion before deployment. The surveys included approximately 75 questions, took 15-20 minutes to complete, and were available online ( www.osf.io/nswcm ). Questions were presented in a fixed sequence, with randomized response options for multi-item questions to reduce bias. Conditional branching was used to shorten the survey. Although all questions were mandatory, most included an “I don’t know/prefer not to answer” option. Respondents could use a back button to review and modify their answers before submission. Survey questions assessed socio-demographics, physical/mental health, attitudes, and behavioral responses in relation to prevention measures (eg, hand washing, social distancing, wearing a mask), and vaccine intentions, status, and motivators. Details on how survey questions map onto theoretical behavior change constructs have been published elsewhere. 11 Participants self-reported being an HCW (or not) as well as their vaccine status. HCW status was determined using a 2-step question process. First, participants were asked, “Are you an essential worker?” with response options: “No,” “Yes,” or “I don’t know/I prefer not to answer.” Those who responded “No” were classified as part of the GPop. Those who responded “I don’t know/I prefer not to answer” were treated as missing values but were still included in the GPop. Participants who answered “Yes” were then asked, “Are you a healthcare worker?” with the options “No” (classified as GPop), “Yes” (classified as HCW), and “I don’t know/I prefer not to answer” (considered missing values and classified as GPop). Each group was then divided into 2 categories: vaccine hesitant (not vaccinated) or nonhesitant (partially or fully vaccinated). COVID-19 vaccine status was assessed using the question “Have you received the COVID-19 vaccine?” (possible responses: no [considered vaccine hesitant]; yes—partially [1 dose out of a 2-dose vaccine], yes—fully [2 out of 2 doses or 1 dose of a single-dose vaccine; considered nonhesitant]; or I don’t know/prefer not to answer [considered missing values and excluded]). Vaccination motivators were assessed by presenting a list of 17 potential motivators (informed by existing literature), 17 , 18 using the question: “To what extent did (or would) each of the following influence your decision to get vaccinated against COVID-19?” with response options: To a great extent; Somewhat; Very little; Not at all; or I don’t know/I prefer not to answer. Elements were considered motivators when respondents selected “To a great extent.” 2.4. Data analysis Descriptive statistics were calculated for socio-demographic characteristics. Pearson’s chi-square (χ 2 ) tests were used to compare individuals according to vaccine hesitancy status. We calculated univariate and multivariate logistic regression equations to assess the association between vaccine hesitancy (dependent variable) and multiple demographic and clinical factors (independent variables), including sex, age, education, average income, time period, chronic disease diagnosis (eg, cardiovascular disease, diabetes, obesity, cancer), and diagnosis of a depressive disorder or anxiety disorder. Vaccine motivators were reported as frequencies (proportions). We also performed a sensitivity analysis looking at differences between vaccine hesitancy in HCWs and the GPop as a function of time. The survey data, collected 4 times from a single national online panel (Leger© Opinion), portray trends in vaccine intentions over time but do not track the same individuals over time. All statistical tests were 2-sided, and a value of P < .05 was considered statistically significant. Statistical analyses were performed using SAS, version 9.4. 3. Results 3.1. HCWs and GPop characteristics HCWs were primarily nurses (20.5%), other allied health professionals (eg, nutritionists, occupational therapists, psychologists; 19.8%), orderlies (eg, cleaners, patient caregivers; 11.7%), administrators (eg, managers, receptionists; 15.6%), or fell into other categories (29.6%). The majority of HCWs were female (67.2%), with a mean (SD) age of 39.6 (10.4) years, had an income of $60 000 or more (62.1%), had a high school or less education (53%), and were not parents with minors in the household (64.6%). A total of 31.9% of HCWs had a chronic disease, 25% had an anxiety disorder (eg, panic disorder, generalized anxiety disorder), and 20.6% had a depressive disorder. Members of the GPop were just over 50% female (50.9%) with a mean (SD) age of 48.9 (17.5) years; most had an income of $60 000 or more (53.5%), had a high school or less education (73.3%), and were not parents with minors in the household (79.5%). Finally, 45.8% of the GPop had a chronic disease, 22.7% had an anxiety disorder, and 18.1% had a depressive disorder. 3.2. Vaccine status The results showed a significant difference in vaccine hesitancy between the GPop (12.6%; n = 1429) and HCWs (8.5%; n = 45) ( P = .005), with a phi coefficient of 0.03, suggesting a small difference. Only 1 of 15 participating physicians was hesitant. As shown in Table 1 , compared with nonhesitant HCWs, hesitant HCWs were younger (82% vs 76.4% aged 50 or under; P = .035), were less likely to have been diagnosed with a chronic disease (18.5% vs 33.1%, P = .043), and were more likely to be a parent with minors in the household (52.4% vs 33.9%, P = .016). Table 1. HCWs’ characteristics according to vaccine status. Variables Hesitant ( n = 45), n (%) Nonhesitant ( n = 479), n (%) P value a Sex Male 14 (31) 158 (32.9) .786 Female 31 (69.1) 321 (67.1) Age <25 years 1 (3.1) 72 (15) .035 26-50 years 36 (78.9) 296 (61.4) ≥51 years 8 (18) 114 (23.6) Average income $59 999 or less 16 (42) 169 (37.5) .585 $60 000 or more 22 (58) 281 (62.5) Education level High school or lower 29 (63.4) 250 (52.0) .142 Graduate or postgraduate degree 17 (36.6) 231 (48) Type of HCW Doctor 1 (1.9) 14 (2.9) .137 Nurse 12 (25.8) 95 (20) Other 32 (72.3) 365 (77.1) Chronic disease Yes 8 (18.5) 160 (33.1) .043 No 37 (81.5) 324 (66.9) Depressive disorder Yes 10 (21.9) 99 (20.5) .826 No 35 (78.1) 384 (79.5) Anxiety disorder Yes 13 (29.3) 119 (24.6) .491 No 32 (70.7) 364 (75.4) Parent of children <18 years in the household Yes 22 (52.4) 162 (33.9) .016 No 20 (47.6) 316 (66.1) Open in a new tab Abbreviation: HCW, health care worker. a Bold value denotes significance ( P < .05). As shown in Table 2 , compared with nonhesitant members of the GPop, hesitant members of the GPop were also younger (69.3% vs 48.1% of people were aged 50 or under; P < .001) and less educated (79.5% vs 72.5% had a high school or less education; P < .001). Those in the GPop who were hesitant were also more likely to report an average income of $59 999 or less (which is below the poverty line) compared with those who were nonhesitant (55.4% vs 45.3%; P < .001). Those in the GPop who were hesitant were also significantly less likely to have been diagnosed with chronic disease (39.2% vs 46.7%; P < .001) but more likely to be a parent with minors in the household (29.5% vs 19.3%; P < .001) than those who were nonhesitant. Hesitant members of the GPop were also significantly more likely to report having been diagnosed with an anxiety disorder (27.8% vs 21.9%; P < .001) or a depressive disorder (21.6% vs 17.7%; P < .001) than the nonhesitant GPop. Table 2. GPop characteristics according to vaccine status. Variables Hesitant ( n = 1164), n (%) Nonhesitant ( n = 9949), n (%) P value a Sex Male 664 (50) 4604 (49) .488 Female 665 (50) 4802 (51.1) Age <25 years 165 (12.4) 1138 (12.1) <.001 26-50 years 759 (57) 3378 (36) ≥51 years 409 (30.7) 4870 (51.9) Average income $59 999 or less 667 (55.4) 3864 (45.3) <.001 $60 000 or more 538 (44.6) 4674 (54.7) Education level High school or lower 1070 (79.5) 6854 (72.5) <.001 Graduate or postgraduate degree 275 (20.5) 2604 (27.6) Chronic disease Yes 527 (39.2) 4416 (46.7) <.001 No 819 (60.8) 5042 (53.3) Depressive disorder Yes 291 (21.6) 1669 (17.7) <.001 No 1055 (78.4) 7789 (82.4) Anxiety disorder Yes 374 (27.8) 2075 (21.9) <.001 No 972 (72.2) 7384 (78) Parent of children <18 years in the household Yes 383 (29.5) 1797 (19.3) <.001 No 915 (70.5) 7533 (80.8) Open in a new tab Abbreviation: GPop, general population. a Bold value denotes significance ( P < .05). 3.3. Correlates of vaccine hesitancy among HCWs and GPop Multivariate analyses revealed that HCWs (odds ratio [OR] = 0.34; 95% CI, 0.13-0.87) and members of the GPop (OR = 0.77; 95% CI, 0.63-0.94) with a chronic disease were nearly 66% and 23% less likely, respectively, to be hesitant. On the other hand, HCWs (OR = 2.29; 95% CI, 1.01-5.19) and members of the GPop (OR = 1.39; 95% CI, 1.08-1.78) who were parents with minors in the household were more likely to be hesitant. Multivariate analyses revealed that GPop members who were younger (OR = 2.38; 95% CI, 1.87-3.03), less educated (OR = 1.65; 95% CI, 1.39-1.96), and had a lower average income (OR = 1.65; 95% CI, 1.34-2.02) were more likely to be hesitant (see Tables 3 and 4 ). Table 3. Univariate and multivariate analysis examining predictors of vaccine hesitancy among the HCWs. HCWs nonhesitant (ref.: HCWs hesitant) a Univariate analysis Multivariate analysis b Variables Reference OR 95% CI OR 95% CI Sex: woman Man 1.11 0.46 2.64 1.46 0.44 4.88 Age: 26-50 years 51 years or more 1.7 0.68 4.25 1.27 0.45 3.62 Education: high school or lower Graduate or postgraduate degree 1.6 0.83 3.09 1.67 0.69 4.06 Average income: <$59 999/year >$60 000/year 1.22 0.54 2.8 1.16 0.44 3.01 Period 2 c Period 1 c 0.39 0.13 1.14 0.28 0.09 0.83 Period 3 c Period 1 0.29 0.09 0.95 0.3 0.09 1.08 Period 4 c Period 1 0.8 0.33 1.95 0.61 0.25 1.48 Being diagnosed with a chronic disease: Yes No 0.47 0.2 1.09 0.34 0.13 0.87 Depression disorder: Yes No 1.12 0.46 2.7 1.35 0.45 4.02 Anxiety disorder: Yes No 1.3 0.59 2.84 1.92 0.85 4.34 Parent of children <18 years in the household: Yes No 2.18 1.01 4.72 2.29 1.01 5.19 Open in a new tab Abbreviations: HCW, health care worker; OR, odds ratio. a Bold value denotes significance ( P < .05). b Adjusted for: sex, age, education, average income, period, diagnosis of chronic disease, depressive disorder, anxiety disorder, and weighted. c Period 1: May 31-June 14, 2021; Period 2: September 10-20, 2021; Period 3: November 15-December 3, 2021; Period 4: January 20-February 2, 2022. Table 4. Univariate and multivariate analysis examining predictors of vaccine hesitancy among the GPop. GPop nonhesitant (ref.: GPop hesitant) a Univariate analysis Multivariate analysis b Variables Reference OR 95% CI OR 95% CI Sex: woman Man 0.96 0.81 1.14 0.92 0.78 1.13 Age: 26-50 years 51 years or more 2.68 2.22 3.22 2.38 1.87 3.03 Education: high school or lower Graduate or postgraduate degree 1.48 1.29 1.69 1.65 1.39 1.96 Average income: <$59 999/year >$60 000/year 1.50 1.25 1.8 1.65 1.34 2.02 Period 2 c Period 1 c 0.53 0.42 0.67 0.49 0.38 0.63 Period 3 c Period 1 0.42 0.33 0.53 0.36 0.27 0.47 Period 4 c Period 1 0.5 0.4 0.63 0.46 0.36 0.59 Being diagnosed with a chronic disease: Yes No 0.74 0.62 0.87 0.77 0.63 0.94 Depressive disorder: Yes No 1.29 1.03 1.61 0.98 0.73 1.31 Anxiety disorder: Yes No 1.37 1.12 1.67 1.11 0.85 1.44 Parent of children <18 years in the household: Yes No 1.75 1.44 2.13 1.39 1.08 1.78 Open in a new tab Abbreviations: GPop, general population; OR, odds ratio. a Bold value denotes significance ( P < .05). b Adjusted for: sex, age, education, average income, period, diagnosis of chronic disease, depressive disorder, anxiety disorder, and weighted. c Period 1: May 31-June 14, 2021; Period 2: September 10-20, 2021; Period 3: November 15-December 3, 2021; Period 4: January 20-February 2, 2022. 3.4. Vaccine hesitancy over time We observed changes in hesitancy trends over the 3 survey periods (P) (Period 2: September 10-20, 2021; Period 3: November 15-December 3, 2021; and Period 4: January 20-February 2, 2022) in both HCWs and the GPop compared with Period 1 (Period 1: May 31-June 14, 2021). Hesitancy was less common in HCWs compared with the GPop across all survey periods (see Figure 1 ). In GPop, hesitancy dropped from 19.1% (P1) to 9.0% (P3) before rising to 10.5% (P4). In HCWs, it fell from 13.0% (P1) to 4.1% (P3), then increased to 10.4% (P4) in the last period. Multivariate analyses in the HCW group showed that HCWs polled in Period 2 were 72.0% less likely to be hesitant compared with those polled in Period 1 (OR = 0.28; 95% CI, 0.09-0.83) ( Table 2 ). Multivariate analyses in the GPop group also showed that GPop members polled in Periods 2, 3, and 4 were 51% (OR = 0.49; 95% CI, 0.38-0.63), 64% (OR = 0.36; 95% CI, 0.27-0.47), and 54% (OR = 0.46; 95% CI, 0.36-0.59) less likely to be hesitant compared with those polled in Period 1 ( Table 4 ). Figure 1. Open in a new tab Vaccine hesitancy over time. The trend in hesitancy over the first 3 periods in both HCWs and the general population. Data were drawn from 4 separate cohorts of online panels, so data reflect trends in vaccine intentions over time but not in the same individuals. a Represents the percentage of hesitants in each group (ie, HCWs or GPop). b Implementation of mandatory vaccination was introduced (with varying levels of enforcement), between October 12 and November 13, 2021, by the majority of governments (ie, by 10 of the 13 Canadian provinces). GPop, general population; HCW, health care worker. Sensitivity analyses looking at the difference in vaccine hesitancy between HCWs and GPop indicated a significant main effect of group (HCWs or GPop, χ 2 (1) = 6.7; P = .01) with HCWs showing lower vaccine hesitancy than the GPop overall. There was also a significant main effect of period (1, 2, or 3, χ 2 (3) = 14.7; P = .002), suggesting that levels of hesitancy varied across time points, regardless of group. However, the interaction effect between group and period was not significant (χ 2 (3) = 2.79; P = .425). Trends reflect population-level changes over time, not within individuals. 3.5. Motivators of COVID-19 vaccination We compared potential motivators to get vaccinated in hesitant HCWs and the GPop, finding the same 3 most reported: (1) only needing one dose of the vaccine to be protected (HCW: 86.0% and GPop: 82.6%); (2) having information that the vaccine is safe and unlikely to have major long-term side effects (HCW: 46.2% and GPop: 42.4%); and (3) having information that the vaccine is effective (HCW: 37.5% and GPop: 37.1%) (see Figure 2 ). Figure 2. Open in a new tab Motivators of COVID-19 vaccination. 4. Discussion Overall, the absolute level of vaccine hesitancy was marginally lower among HCWs than the GPop. This difference may be explained by the fact that HCWs have a higher risk of exposure to the disease (workplace exposures), a heightened awareness of the potential seriousness of the disease (witnessing illness among patients in health care settings), an inherent sense of responsibility to reduce the chances of triggering workplace outbreaks and infecting vulnerable patients, and possibly earlier access to the initial vaccine doses. 3 , 4 , 9 It may also have been related to mandatory COVID-19 vaccination policies for HCWs as a condition of employment that were introduced with varying levels of enforcement. The mandatory period pertained solely to data from Period 3, whereas the findings were observed across all periods. 19 , 20 These findings are consistent with a 2022 study conducted across 23 countries, which reported that vaccine hesitancy among HCWs decreased from 8.1% in 2021 to 4.6% in 2022 but was significantly lower than for non-HCWs (4.6% vs 9.4%). 21 In terms of socio-demographic correlates of vaccine hesitancy, being younger was associated with a greater likelihood of being hesitant to get vaccinated in both HCWs and GPop. This is consistent with published literature on COVID-19 and previous pandemics and is likely related to the fact that younger people have a substantially lower risk of morbidity and mortality from COVID-19. 10 , 22 A similar argument likely applies to our finding that HCWs and GPop who were not considered “high risk” for COVID-19 complications (ie, who were not living with a chronic disease) were also more likely to be hesitant, possibly pointing to low-risk self-perceptions as a potential determinant of hesitancy. 10 , 23 We also found that HCWs and GPop who were parents with minors in the household were more likely to be hesitant, which was somewhat unexpected. What is unique about parents is that they are faced with the decision of vaccinating themselves and their children. Early messaging that COVID-19 is mild in children and concerns about side effects related to rapidly developed vaccines and the new mRNA platform may have fueled parental hesitancy. 24 , 25 Members of the GPop with lower incomes also showed a higher probability of being vaccine hesitant. Lower income groups are at increased risk of contracting the virus, as well as suffering greater direct and indirect negative consequences from COVID-19, 26 and these negative outcomes may be related to lower rates of vaccination. Income was not a correlate for HCWs, likely due to the fact that a larger proportion had incomes greater than $60 000 (62.1% compared with 53.9% in the GPop). This suggests that communication strategies to increase vaccine uptake in the GPop should highlight economic benefits, such as avoiding lost wages from illness. Members of the GPop with a lower education level showed a higher probability of being vaccine hesitant, which was not observed among HCWs. This may be attributed to lower health literacy in the GPop compared with HCWs, who likely received greater and specific education in relation to health prevention behaviors and vaccination as part of their job training. 17 , 27 We also observed a trend indicating decreases in rates of vaccine hesitancy over time, between May 31 and December 3, 2021 (the first 3 periods), in both HCWs and the GPop. The drop in hesitancy between Period 1 (May 31-June 14, 2021) and Period 2 (September 10-20, 2021) may be explained by growing confidence in vaccines owing to growing anecdotal and observational data supporting vaccine efficacy and safety. 8 , 27 The drop between Periods 2 and 3 may have been further bolstered by vaccine mandates (eg, introduction of vaccine “passports” to access many public spaces, mandatory vaccination for HCWs), which were enacted between October 12 and November 13, 2021 by most (10/13) provincial governments. Although requiring proof of vaccination was viewed by some as being coercive, 28 this aligns with prior studies showing that these types of policies increase vaccination uptake and have net population benefits. 19 The increase in vaccine hesitancy in Period 4 may reflect the long-term effects of coercive strategies, pandemic fatigue, and/or complacency. Finally, our results indicated that the strongest motivators to getting vaccinated were similar in both hesitant HCWs and GPop, including confidence in the vaccine’s safety and efficacy, as well as the need to receive only a single dose for protection. Despite differences in education, income, and vaccine conditions for HCWs during the pandemic (ie, being the first population to be vaccinated, and many facing workplace vaccine mandates), this finding suggests that future education and communication strategies may not require specific messaging for HCWs compared with the GPop. Overall, a wealth of literature suggests that vaccination decisions may depend on individual and community perceptions of risk. 29 This is consistent with the Health Belief and COM-B models, which posit that a person’s belief in the efficacy and importance of the health behavior can influence both intention and the adoption of preventive measures, such as vaccination. These results demonstrate that communications (messaging) should emphasize vaccine safety, efficacy, and convenience. This study has certain limitations. First, despite including large national samples of Canadians with representation across age, sex, and province, the number of HCWs was low and included few physicians, limiting generalizability. Because physicians and nurses were underrepresented compared with other HCWs in our sample, and may exhibit different vaccination behaviors, our findings likely reflect the behaviors of the more represented group (ie, other HCWs). Second, data were self-reported and may be subject to response or social desirability bias. Third, voluntary participation from a polling panel may introduce selection bias. Fourth, we defined “vaccine hesitancy” as nonacceptance of a single dose of vaccine, whereas many people have also demonstrated a hesitancy to receive a second dose of a 2-dose schedule vaccine, and particularly a hesitancy to receive booster doses. Finally, although this study presents data depicting vaccine intentions over time, it was drawn from 4 separate cohorts of online panels, so data reflect trends in vaccine intentions over time but not in the same individuals. Given that the data are fully anonymous it is not possible to identify repeated respondents through the waves. Despite these limitations, the study has several notable strengths. Data were collected during key phases of the vaccine rollout, including the introduction of vaccine passports. The survey assessed over 10 evidence-based motivators, enhancing precision. It also included a large, demographically representative sample and analyses adjusted for key confounders. Finally, the design was informed by behavioral theories, supporting deeper insight into vaccine attitudes and informing future interventions. In conclusion, this study demonstrates that vaccine hesitancy is lower among HCWs than the general population, but similar factors influence both groups. This suggests that shared intervention strategies focusing on education regarding the relative safety of vaccines compared with COVID-19 infection, how vaccination reduces disease severity/duration, and benefits of single-dose options could be effective across populations. Future research should replicate these findings and evaluate targeted interventions. Supplementary Material supplementary_materials_uiag002 supplementary_materials_uiag002.docx (517.3KB, docx) Contributor Information Camille Léger, Department of Psychology, Université du Québec à Montréal, Montréal, QC, Canada; Montreal Behavioural Medicine Centre, Centre Intégré Universitaire de Santé et Services Sociaux du Nord-de-l’Ile-de-Montréal (CIUSSS-NIM), Montréal, QC, Canada. Vincent Gosselin Boucher, Department of Physical Activity Sciences, Université du Québec à Montréal, Montréal, QC, Canada; Department of Innovation and Research, Ministère de la Santé et des Services Sociaux du Québec, Montréal, QC, Canada. Frédérique Deslauriers, Department of Psychology, Université du Québec à Montréal, Montréal, QC, Canada; Montreal Behavioural Medicine Centre, Centre Intégré Universitaire de Santé et Services Sociaux du Nord-de-l’Ile-de-Montréal (CIUSSS-NIM), Montréal, QC, Canada. Samir Gupta, Unity Health Toronto, Department of Medicine, Division of Respirology, St Michael’s Hospital, Toronto, ON M5B 1W8, Canada; Keenan Research Center, Li Ka Shing Knowledge Institute, St Michael’s Hospital, University of Toronto, Toronto, ON, Canada. Maximilien Vakambi Dialufuma, Montreal Behavioural Medicine Centre, Centre Intégré Universitaire de Santé et Services Sociaux du Nord-de-l’Ile-de-Montréal (CIUSSS-NIM), Montréal, QC, Canada. Michael Vallis, Family Medicine, Adjunct Professor, Department of Psychology and Neuroscience, Dalhousie University, Halifax, NS, Canada. Simon L Bacon, Montreal Behavioural Medicine Centre, Centre Intégré Universitaire de Santé et Services Sociaux du Nord-de-l’Ile-de-Montréal (CIUSSS-NIM), Montréal, QC, Canada; Department of Health, Kinesiology and Applied Physiology, Concordia University, Montréal, QC, Canada. Kim L Lavoie, Department of Psychology, Université du Québec à Montréal, Montréal, QC, Canada; Montreal Behavioural Medicine Centre, Centre Intégré Universitaire de Santé et Services Sociaux du Nord-de-l’Ile-de-Montréal (CIUSSS-NIM), Montréal, QC, Canada. Acknowledgments The iCARE team Lead investigators: Kim L. Lavoie, PhD, University of Quebec at Montreal (UQAM) and CIUSSS-NIM, CANADA; Simon L. Bacon, PhD, Concordia University and CIUSSS-NIM, CANADA. Collaborators (in alphabetical order of country): ARGENTINA: Nora Granana, PhD, Hospital Durand. AUSTRALIA: Jacqueline Boyle, PhD, Monash University; Margie Danchin, PhD, Melbourne Medical School; Joanne Enticott, PhD, Monash University; Jessica Kaufman, PhD, Murdoch Children’s Research Institute. AUSTRIA: Alexandra Kautzky-Willer, MD, Medizinische Universität Wien; BRAZIL: Eduardo Caputo, PhD, Universidade Federal de Pelotas. CANADA: Mohamad Baydoun, PhD, University of Regina; Andrea Gershon, PhD, Sunnybrook Research Institute; Ariane Bélanger-Gravel, PhD, Université Laval; Tavis Campbell, PhD, University of Calgary; Linda Carlson, PhD, University of Calgary; Kim Corace, PhD, University of Ottawa; Rubee Dev, PhD, University of British Colombia; Olivier Drouin, MD, CHU Sainte-Justine/Université de Montréal; Gary Garber, PhD, University of Ottawa/Public Health Ontario; Samir Gupta, MD, University of Toronto; Catherine Herba PhD, UQAM; Jack Jedwab, PhD, Canadian Institute for Identities and Migration and the Association for Canadian Studies; Keven Joyal-Desmarais, PhD, Concordia University; Joanne Liu, PhD, McGill University; Sandra Pelaez, PhD, Université de Montréal; Paul Poirier, MD, Université Laval; Justin Presseau, PhD, University of Ottawa; Eli Puterman, PhD, University of British Columbia; Joshua Rash, PhD, Memorial University; Johanne Saint-Charles, PhD, UQAM; Jovana Stojanovic, PhD, Concordia University; Michael Spivock, PhD, Shared Services Canada; Geneviève Szczepanik, PhD, MBMC; Michael Vallis, PhD, Dalhousie University; Vincent Gosselin Boucher, PhD, The University of British Columbia, Faculty of Education, School of Kinesiology; Claudia Trudel-Fitzgerald, PhD, Department of Psychology, Université du Québec à Trois-Rivières; Tamara Cohen, PhD, University of British Colombia; Alysha Deslippe, PhD, University of British Colombia; Nazeem Muhajarine, PhD, University of Saskatchewan; Rachel Burns, PhD, Carleton University; Tristan Renaud, BSc, Carleton University; Sean Locke, PhD, Brock University. COLOMBIA: Mariantonia Lemos-Hoyos, PhD, Universidad EAFIT. CYPRUS: Angelos Kassianos, PhD, University of Cyprus; Mauricio Hincapié Montoya, PhD/ MD, Universidad EAFIT; Biviana Marcela Suárez Sierra, PhD, Universidad EAFIT. FRANCE: Gregory Ninot, PhD, Université de Montpellier; Mathieu Beraneck, PhD, Université Paris Cité, CNRS. GERMANY: Beate Ditzen, PhD, Heidelberg University. GREECE: Theodora Skoura, PhD, Aretaieio Hospital Athens University. HUNGARY: Beatrix Oroszi, PhD, Semmelweis University; Annamária Ferenczi, MSc, Semmelweis University. INDIA: Delfin Lovelina Francis MDS (PhD) Saveetha Dental College and Hospitals, SIMATS. IRELAND: Hannah Durand, PhD, University of Stirling; Oonagh Meade, PhD, University of Galway; Gerry Molloy, PhD, University of Galway; Chris Noone, PhD, University of Galway. ITALY: Stefania Paduano, PhD, University of Modena and Reggio Emilia; Valeria Raparelli, MD PhD, University of Ferrara. KENYA: Hildah Oburu, PhD, University of Nairobi. NEPAL: Niroj Bhandari, MBBS, Institute for Implementation Science and Health. SAUDI ARABIA: Abu Zeeshan Bari, PhD, Taibah University. SLOVAKIA: Iveta Nagyova, PhD, PJ Safarik University—UPJS. SWITZERLAND: Susanne Fischer, PhD, University of Zurich. TURKEY: Ceprail Şimşek, MD, Health Science University. UNITED KINGDOM: Joanne Hart, PhD, Manchester University; Lucie Byrne-Davis, PhD, University of Manchester; Nicola Paine, PhD, Loughborough University; Susan Michie, PhD, University College London. UNITED STATES: Michele Okun, PhD, University of Colorado; Sherri Sheinfeld Gorin, PhD, University of Michigan; Johannes Thrul, PhD, Johns Hopkins University; Abebaw Yohannes, PhD, Azusa Pacific University. Students (in alphabetical order of country): AUSTRALIA: Shrinkhala Dawadi, MSc, Monash University; Kushan Ranakombu, PhD, Monash University. BRAZIL: Daisuke Hayashi Neto, MSc, Unicamp. CANADA: Frédérique Deslauriers, BA, UQAM and CIUSSS-NIM; Amandine Gagnon-Hébert, BA, UQAM and CIUSSS-NIM; Mahrukh Jamil, BA, Concordia University and CIUSSS-NIM; Camille Léger, BSc, UQAM and CIUSSS-NIM; Callum MacLeay, BA, UQAM and CIUSSS-NIM; Ariany Marques Vieira, MSc, Concordia University and CIUSSS-NIM; Sarah O’Connor, BA, Université Laval; Zackary van Allen, PhD, University of Ottawa. COLOMBIA: Susana Torres, MSc, Universidad EAFIT. Community participants: CANADA: Sophie Duval, MSc; Johanne O’Malley; Katherine Séguin, BA; Kyle Warkentin. INDIA: Sarah Tanishka Nethan. Author contributions All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Camille Léger, Vincent Gosselin Boucher, Samir Gupta, Michael Vallis, Frédérique Deslauriers, Simon L. Bacon, Maximilien Vakambi Dialufuma, and Kim L. Lavoie. The first draft of the manuscript was written by Camille Léger, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Funding iCARE is supported by the Canadian Institutes of Health Research (CIHR: MM1-174903; MS3-173099; SMC-151518; PJT-479128), the Canada Research Chairs Program (950-232 522, chair holder: K.L.L.), the Fonds de Recherche du Québec-Santé (FRQ-S: 251618 and 34 757), the Fonds de Recherche du Québec—Société et Culture (FRQSC: 2019-SE1- 252541), and the Ministère de l’Économie et de l’Innovation du Québec (2020-2022-COVID-19- PSOv2a-51 754). C.L. is supported by the CIHR (FBD-203340). F.D. is supported by the FRQS (BF2 - 332 012). V.G.B. is supported by the CRSH (2025-01247). S.G. is supported by the University of Toronto Michael Locke Term Chair in Knowledge Translation and Rare Lung Disease Research. The study sponsors had no role in the design of the study, data collection, or analyses. Conflicts of interest K.L. is a member of the Canadian COVID-19 Expert Advisory Panel (Health Canada). She has served on the advisory board or as a consultant for Schering-Plough, Takeda, AbbVie, Almirall, Janssen, GlaxoSmithKline (GSK), Novartis, Boehringer Ingelheim (BI), Respiplus, and Sojecci Inc, has received sponsorship for investigator-generated research grants from GSK and AbbVie, speaker fees from GSK, Astra-Zeneca, Astellas, Novartis, Takeda, AbbVie, Merck, BI, Bayer, Pfizer, Xfacto, Respiplus, and Air Liquide, and has received support for educational materials from Merck, none of which are related to the current article. S.L.B. is a member of the Health Canada COVID Alert Application Working Group. He has served on the advisory board for Bayer and Sanofi, has received sponsorship for investigator-generated research grants from GSK, Moderna, and AbbVie, consultation fees from Schering-Plough, Merck, Astra Zeneca, Sygesa, Bayer, Sanofi, Lucilab, and Respiplus, and speaker’s fees from Novartis, Respiplus, and Janssen, none of which are related to the current article. S.G. has received funding from the Public Health Agency of Canada for COVID-19 vaccine education and from the Canadian Institutes of Health Research (CIHR) for COVID-related research. M.V. served on advisory boards and/or consults to AbbVie, Abbott, Bausch Health, Boehringher Ingelheim, Lifescan, Novo Nordisk, Roche Diabetes, and Sanofi, investigator-driven research funding from Abbott, Bausch, and Novo Nordisk, and speaking fees from AbbVie, Abbott, Bausch Health, Boehringher Ingelheim, Lifescan, Novo Nordisk, Roche Diabetes, and Sanofi. The remaining authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results. Data availability The iCARE study data are available on request via the process identified here: https://icare.mbmc-cmcm.ca/researcher-area/access-to-study-data/ (accessed on September 5, 2025). All analysis was performed in SAS version 9.4. The codes are available on request by contacting the corresponding author. References 1. WHO . WHO Director-General’s opening remarks at the media briefing on COVID-19: 11 March 2020. 2020. Accessed March 10, 2026. https://www.who.int/news-room/speeches/item/who-director-general-s-opening-remarks-at-the-media-briefing-on-covid-19---11-march-2020 2. Msemburi  W, Karlinsky  A, Knutson  V, Aleshin-Guendel  S, Chatterji  S, Wakefield  J. The WHO estimates of excess mortality associated with the COVID-19 pandemic. 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