Vaccine 42 (2024) 126236
Contents lists available at ScienceDirect
Vaccine
journal homepage: www.elsevier.com/locate/vaccine
Confidence and barriers: Analysis of factors associated with timely routine
childhood vaccination in Canada during the COVID-19 pandemic
Harry MacKay a,b, Jeremy D. Gretton a, Sandra Chyderiotis c , Stephanie Elliott c , Ana Howarth d,
Catherine Guo a, Angela Mastroianni a,b , Christine Kormos b, Jessica Leifer b, Lauryn Conway b ,
Mark D. Morrissey a,*
a
Behavioural Science Office, Centre for Surveillance, Integrated Insights, and Risk Assessment, Data, Surveillance and Foresight Branch, Public Health Agency of Canada,
Canada
Impact Canada, Impact & Innovation Unit, Privy Council Office, Canada
c
Vaccination Behaviour and Confidence, Centre for Immunization Surveillance and Programs, Infectious Diseases and Vaccination Programs Branch, Public Health
Agency of Canada, Canada
d
Infectious Diseases and Vaccination Programs Branch, Public Health Agency of Canada, Canada
b
A R T I C L E I N F O
A B S T R A C T
Keywords:
Vaccine uptake
Health behaviour
Vaccine hesitancy
Barriers
Vaccine timeliness
Vaccine confidence
Routine childhood vaccination is a crucial component of public health in Canada and worldwide. To facilitate
catch-up from the global decline in routine vaccination caused by the COVID-19 pandemic, and toward the
ongoing pursuit of coverage goals, vaccination programs must understand barriers to vaccine access imposed or
exacerbated by the pandemic. We conducted a regionally representative online survey in January 2023 including
2036 Canadian parents with children under the age of 18. We used the COM-B model of behaviour to examine
factors influencing vaccination timeliness during the pandemic. We assessed Capability with measures of vaccine
understanding and decision difficulty, and Motivation with a measure of vaccine confidence. Opportunity was
assessed through parents’ self-reported experience with barriers to vaccination. Twenty-four percent of surveyed
parents reported having missed or delayed one of their children’s scheduled routine vaccinations since the
beginning of the pandemic, though most parents reported having either caught up or the intention to catch up
soon. In the absence of opportunity barriers, motivation was associated with timely vaccination for children aged
0–4 years (aOR = 1.81, 95 % CI: 1.14–2.84). However, experience with one or more opportunity barriers,
particularly clinic closures and difficulties getting an appointment, eliminated this relationship, suggesting
perennial and new pandemic-associated barriers are a critical challenge to vaccine coverage goals in Canada.
1. Introduction
Routine childhood vaccination is responsible for reducing the
occurrence and impact of vaccine-preventable diseases [1]. Beginning in
March 2020, the COVID-19 pandemic brought widespread disruptions
to healthcare services, including routine vaccinations. While interna­
tional and national-level health authorities urged the maintenance of
routine childhood vaccination programs, the pandemic saw the largest
sustained decline in worldwide childhood immunization rates in 30
years [2]. In Canada, childhood vaccination coverage rates for a variety
of diseases fell early in the pandemic [3–6], with, for example, the
overall up-to-date rate for children in Ontario dropping by 5.7 % from a
baseline of 71 % in the time period immediately following March 14,
2020 [6]. In Canada, childhood vaccines are typically delivered during
routine check-ups or in schools, and may or may not be mandatory for
school entry, depending on the province. Vaccines typically delivered in
Canadian schools, such as those against HPV, HepB, and meningococcal
disease, saw more sustained declines than those delivered in clinics
[7,8]. Parents experience a range of barriers to vaccination, many of
which were exacerbated by the pandemic. These included school and
clinic closures, along with demand-side issues such as difficulties with
appointment scheduling [5,7,9]. Parents of two-year-olds who reported
experience with COVID-19 related barriers to vaccinating their children,
or who had delayed their child’s vaccine by >30 days reported signifi­
cantly lower coverage rates for a variety of vaccines [10]. For example,
diphtheria, pertussis, and tetanus (≥4 doses) coverage dropped from
* Corresponding author.
E-mail address: mark.morrissey@phac-aspc.gc.ca (M.D. Morrissey).
https://doi.org/10.1016/j.vaccine.2024.126236
Received 29 February 2024; Received in revised form 9 August 2024; Accepted 14 August 2024
Available online 31 August 2024
0264-410X/Crown Copyright © 2024 Published by Elsevier Ltd.
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H. MacKay et al.
Vaccine 42 (2024) 126236
81.2 % to 64.6 % among parents who reported experiencing pandemicrelated barriers [10]. These challenges further strain Canada’s effort to
reach its immunization coverage goals [10]. While catch-up programs
are underway in Canada and globally, their success hinges on identifying
and addressing the reasons people missed their scheduled vaccinations
in the first place.
The effectiveness and continuity of routine vaccination programs
depend on their availability and accessibility, as well as the public’s
confidence in their efficacy and safety [11]. Outside of the context of the
pandemic, numerous frameworks exist to understand the factors influ­
encing vaccine uptake [12–15]. Alongside these vaccination-specific
frameworks, general behaviour models including the Capability, Op­
portunity, and Motivation framework for Behaviour (COM-B) and others
have been applied to the question of vaccination behaviour and routine
childhood immunization [9,16,17]. COM-B [18] provides a compre­
hensive yet parsimonious model for understanding vaccination behav­
iour, suggesting that it stems from the interaction between Capability
(psychological and physical capacity), Opportunity (external factors
including physical and social environments), and Motivation (cognitive
and emotional drivers) [19].
Confidence in vaccination among the general public may have
declined or become polarized over the course of the COVID-19 pandemic
[20]. The COVID-19 vaccine rollout increased the visibility of vaccines
and vaccine policy. Public expressions of hesitancy toward the COVID19 vaccine in Canada, notably demonstrated by the 2022 Freedom
Convoy, encompassed themes consistent with those seen in other set­
tings [21]. These themes included doubts about vaccine safety and ef­
ficacy, questions about the rapid pace of vaccine development,
skepticism toward the pharmaceutical industry, and opposition to gov­
ernment vaccine mandates [21–24]. Among these objections, many ef­
forts were directed at undermining (or expressing a lack of) confidence
in vaccines, further intensified by concerns regarding personal auton­
omy and freedom. Confidence in both routine and COVID-19 vaccines
remains generally high among Canadian parents and the general public
[10,25], with strong majorities in 2021 agreeing that in general
“childhood vaccines are safe” (97 %) and “childhood vaccines are
effective” (97.9 %) [10]. However, relative to 2019 significantly more
parents in 2021 agreed that “In general, a vaccine can give you a serious
case of the very same disease it was meant to prevent” (23.5 % vs. 20.8 %
in 2019) and that “In general, the use of alternative practices, such as
homeopathy and naturopathy, can eliminate the need for vaccination”
(14.9 % vs. 11.3 % in 2019) [10]. There is also evidence from other
jurisdictions that vaccine confidence has declined relative to before the
pandemic [26–28], although this is not observed universally [29]. At
present, many studies of vaccine confidence during and after the
pandemic focus on the population in general, and so determining
whether there has been a sustained change in parental vaccine confi­
dence awaits further research. The best available national data are from
2021 [10], but in light of the prominent expressions of hesitancy seen in
2022, however, the state of vaccine confidence could be in flux. The
near-universal experience of having to make decisions about the COVID19 vaccine exposed a wide range of parents to arguments against
vaccination, raising the possibility that this controversy may have
generalized to routine vaccines [30]. It is therefore crucial to survey
confidence in routine childhood vaccines and its influence on vaccine
uptake in the unique context presented by the various stages of the
pandemic.
Routine vaccination thus faces the dual threats of novel, pandemicinduced barriers to access limiting the opportunity to receive vaccines,
and an invigorated opposition movement that may undermine parental
motivation to seek vaccines for their child. To understand this situation
in Canada, we designed the Routine Childhood Immunization during the
COVID-19 Pandemic (RChIP) survey, which explored a national sample
of parents’ self-reported access to routine vaccines, barriers faced, and
factors influencing their capability and motivation to seek vaccines for
their children.
2. Methods
2.1. Data collection
The survey was administered in English and French using Qualtrics
online market research panels to a non-probability sample of Canadian
parents or guardians of children under 18 who reported being involved
in making decisions about their child’s vaccinations. Data were collected
from January 10th to January 30th, 2023. Quality control of survey
responses was performed on an ongoing basis by Qualtrics, removing
respondents flagged as bots or duplicates, or whose survey duration was
more than two standard deviations longer or shorter than the median.
2.2. Survey instrument
The RChIP survey comprised 142 questions designed to collect in­
formation on missed and delayed vaccinations, vaccine confidence, at­
titudes and beliefs about vaccination, and a range of other cognitive and
socio-demographic factors that may contribute to vaccine uptake. Re­
spondents completed a mean of 112 questions, with differences due to
variation in number of children and survey branch logic. Respondents
took an average of 25.4 min to complete the survey. A copy of the full
survey instrument is available in the supplementary materials.
2.3. Primary dependent variable: Reported timely vaccination
We asked participants about the number of children they had, using
three age groups (0–4, 5–11, and 12–17 years of age). We chose to ask
parents about their experience missing or delaying appointments to
have their child vaccinated to avoid potential confusion around which
vaccines the child was to receive, and where the vaccination was sup­
posed to take place. This is because at different ages, children may
receive vaccines at a routine checkup, in school, or some other sched­
uled event (i.e. community centre, pharmacist visit, etc.). To assist in
recalling any missed appointments, we presented participants with a
schematic of the routine childhood vaccination schedule in their prov­
ince or territory (Fig. 1A). The vaccination timeliness question asked:
“To the best of your knowledge, have any of your child(ren) aged [0–4 /
5–11 / 12–17] years old missed or delayed by more than 30 days one or
more of the vaccine appointments shown above since the start of the
COVID-19 pandemic in March 2020? You may answer from memory, or
refer to your child’s immunization records to answer this question.” The
age group presented was based on the reported age of the participant’s
child(ren), and parents with children in multiple age bins were asked
this question once per age bin. Parents with children in multiple age
groups are included in the analyses for each age group. Parents with
multiple children in the same age bin were asked this question only
once.
Participants could respond “Yes, they have missed or delayed one or
more appointments”, “No, they have not missed or delayed any”, “My
child was not due for a vaccine during this time”, “Never planned to
have my child vaccinated”, or “Not sure”.
We coded timely vaccination as a binary variable with “Yes, they
have missed or delayed one or more appointments” coded as 0, and “No,
they have not missed or delayed any” coded as 1. For this study, other
responses were excluded from the analysis.
2.4. COM-B variables
Following [19], we classified groups of questions into measures of
Capability, Motivation, and Opportunity (Supplementary Table 3). For
statistical analysis, we created five composite variables using the meancentred and standardized average of each group of survey questions.
Details on individual questions, their inclusion in composite variables,
Cronbach’s alpha, and unadjusted odds ratios for association with timely
vaccination are given in Supplementary Table 3. Only groups used in the
2
H. MacKay et al.
Vaccine 42 (2024) 126236
Fig. 1. Missed vaccinations and catch-up intentions since March 2020.
A: Example schematic of routine childhood immunization schedule for Ontario, provided to survey participants as a visual aid to facilitate recall of missed or delayed
vaccine appointments. B: Bar graph showing parents’ estimates of vaccine timeliness since the onset of the COVID-19 pandemic segmented by age group. C: Bar graph
showing catch-up intention among the subset of parents who reported missing or delaying a child’s routine vaccination. Percentages are calculated within each age
group. Values at the base of bars represent counts (n).
final model are discussed here.
recommended routine immunizations on time as estimated by the
participant).
2.5. Capability
Psychological capability. One’s perceived psychological capability
to have one’s child vaccinated was assessed using two composite vari­
ables recoded from 5-point Likert scale items: Vaccine Understanding (7
items; α = 0.91; sample item: “I have a good understanding of which
routine vaccines my child needs”) and Decision Difficulty (7 items, α =
0.95, sample item: “I felt overwhelmed by the decision”).
2.7. Motivation
Reflective motivation. To assess general vaccine confidence, we
asked nine questions derived from Canada’s Childhood National Im­
munization Coverage Survey (cNICS; [10,31]). On the basis of common
factor loading (>0.7 on a minimum residual factor analysis with oblimin
rotation) and conceptual grounds, we reduced this scale to four items
assessing confidence in routine childhood vaccines for inclusion in lo­
gistic regression analyses. These remaining items (sample item: “In
general, vaccines help to protect my child’s health”) had high internal
reliability (α = 0.94). Although we had included additional questions
that might be considered automatic motivation by virtue of their
emotionality (e.g., “When I think about my child getting a routine
vaccine, it feels… (risky/safe)”), they did not appear to offer substantial
improvements to model fit beyond the four vaccine confidence questions
ultimately included.
2.6. Opportunity
Physical opportunity. Participants were asked the following ques­
tion: “Since the start of the pandemic, have you experienced any diffi­
culties getting your children a routine vaccine? Select all that apply” and
were provided a list of barriers. Barriers were coded as “opportunity
barriers” if they reflected factors that prevent or discourage vaccination
because of a lack of environmental or social support [18]. Barriers were
classified into 15 opportunity barriers (e.g., “My child was sick on the
day of their appointment”; “My doctor’s office/clinic was closed”), as
well as five non-opportunity barriers (e.g., “Not sure where/how to
make an appointment”). The experience of opportunity barriers was
dummy coded (1 = experience with one or more opportunity barriers, 0
= none reported).
Social opportunity. In the context of vaccination, social opportu­
nity has been defined as the extent to which one’s social environment is
supportive of vaccination [19]. Here, we used the participant’s meancentred, standardized estimate of peer routine vaccine uptake (i.e., the
percentage of children in that child’s age group that had received all
2.8. Sociodemographic variables
We collected a range of sociodemographic data. Household gross
income (eight levels with reference category of $80,000–$100,000,
approximating the median for Canadian households) and place of birth
(born in Canada/born outside of Canada) were recoded as dummy
variables. Others, including those not included in the final analysis, are
detailed in Table 1.
3
H. MacKay et al.
Vaccine 42 (2024) 126236
Table 1
Demographic characteristics of survey sample.
Table 1 (continued )
N (%)
N (%)
Region
Alberta/Northwest Territories
Nova Scotia, New Brunswick, Newfoundland, Prince Edward Island
British Columbia
Manitoba, Saskatchewan, Nunavut
Ontario
Québec
Age
18–34 years
35–54 years
55 years and older
Sex
Female
Male
Gender
Female
Male
Other
Education level
High school or less
College/trades
University / post-graduate
Employment status
Employed full-time (working 35 or more hours per week)
Employed part-time (working <35 h per week)
Leave of absence (i.e. maternity, parental, short-term disability, etc.,)
Not in the workforce and not looking for work (full-time homemaker,
unemployed)
Retired
Self-employed
Student attending school full-time or part-time
Student employed full-time
Student employed part-time
Student looking for work
Student self-employed
Unemployed, but looking for work
Household income
Under $20,000
$20,000 to just under $40,000
$40,000 to just under $60,000
$60,000 to just under $80,000
$80,000 to just under $100,000
$100,000 to just under $150,000
$150,000 to just under $200,000
$200,000 to just under $250,000
$250,000 and above
Born in Canada
181 (9 %)
235 (12
%)
236 (12
%)
238 (12
%)
626 (31
%)
520 (26
%)
Born outside Canada
Ethnicity
Black (African, Afro-Caribbean, African descent)
East/Southeast Asian (e.g. Chinese, Korean, Japanese, Taiwanese,
Filipino, Vietnamese, Cambodian, Thai, Indonesian, other East/
Southeast Asian descent)
Indigenous (First Nations, Métis and/or Inuk/Inuit)
Latino/Latina (e.g. Latin American, Hispanic descent)
Middle Eastern and North African (e.g. Arab, Algerian, Egyptian, West
Asian descent (e.g. Iranian, Israeli, Lebanese, Turkish, Kurdish, etc.)
Mixed
Mixed Indigenous
South Asian (e.g., Afghan, Indian, Pakistani, Bangladeshi, Sri Lankan,
etc.)
656 (32
%)
1275 (63
%)
105 (5 %)
White European
1461 (72
%)
573 (28
%)
98 (5 %)
247 (13
%)
60 (3 %)
50 (3 %)
68 (4 %)
48 (3 %)
36 (2 %)
152 (8 %)
1130 (60
%)
2.9. Intentionally missed or delayed vaccination
1284 (63
%)
752 (37
%)
Parents were asked “Have you ever decided to delay your [0–4 /
5–11 / 12–17] year old child’s routine vaccine by more than 30 days?”
and “Have you ever decided to not immunize your [0–4 / 5–11 / 12–17]
year old child with a routine vaccine?”. Those that responded “Yes” were
presented with a follow-up question asking them to select, from a
multiple-choice list, their reasons for having done so.
1265 (62
%)
739 (36
%)
32 (2 %)
2.10. Statistical analyses
372 (18
%)
497 (25
%)
1156 (57
%)
We performed descriptive analyses of Capability (Vaccine Under­
standing, Decision Difficulty) and Motivation variables, focusing on the
rate of net agreement (agree or strongly agree) across the entire group of
questions. For analyses using logistic regression, single or composite
scales were treated as continuous variables across the full range of re­
sponses. We used logistic regression to generate unadjusted odds ratios
for timely vaccination for the individual questions comprising compos­
ite variables. The association between timely vaccination and experi­
ence with opportunity barriers or other barriers was assessed using
simple logistic regressions with p-values adjusted using the BenjaminiHochberg procedure. For ease of interpretation, results for barriers are
presented as relative odds of missing/delaying a vaccine given that one
experienced that barrier.
We used multivariable binomial logistic regressions to apply the
COM-B model [18] to the question of timely vaccination in children,
using the composite variables and dummy-coded opportunity barrier
variable in the model. We ran separate sets of regression models for each
age group of children. Our analyses began with a comprehensive model
that included a total of nine variables under the Capability, Opportunity,
and Motivation constructs (Supplementary Table 4), as well as an
additional seven sociodemographic factors. Two-way interactions be­
tween Capability, Opportunity, and Motivation variables were also
included in the model. Given the coding of the Barriers variable and its
inclusion in interaction terms in the model (e.g., Barriers x Confidence),
certain main effects (e.g., Confidence) are simple effects estimated for
Barriers = 0 (e.g., the effect of Confidence if no barriers were reported).
Beginning with the comprehensive model, we employed a theoreticallyinformed approach to variable selection, whereby subsequent model
iterations excluded variables based on redundancy, lack of conceptual
relevance, or non-significant or unstable associations with timely
vaccination. We evaluated each model iteration using the Akaike In­
formation Criterion (AIC), McFadden’s pseudo-R2, and the HosmerLemeshow goodness of fit test with the intent of achieving a balance
between model parsimony and fit. We assessed out-of-sample
1278 (64
%)
183 (9 %)
61 (3 %)
194 (10
%)
26 (1 %)
98 (5 %)
26 (1 %)
9 (0 %)
6 (0 %)
2 (0 %)
5 (0 %)
108 (5 %)
96 (5 %)
229 (12
%)
288 (15
%)
292 (15
%)
343 (18
%)
443 (23
%)
184 (9 %)
44 (2 %)
37 (2 %)
Immigration status
4
H. MacKay et al.
Vaccine 42 (2024) 126236
performance using area under the Receiver Operating Characteristic
curve (AUC) and sensitivity/specificity estimates derived from 10-fold
cross-validation. Each reduced model was also compared to both the
initial comprehensive model and the immediately preceding model
using the Likelihood Ratio (LR) test to ensure that enhancements to
predictive power did not significantly detract from the overall fit of the
model. To ensure that coefficient directionality and magnitude were
stable across different models, we performed a sensitivity analysis
(Supplementary Tables 5–7). To address potential multicollinearity, we
evaluated the Variance Inflation Factor (VIF) in models consisting only
of main effects [32], ensuring VIF values remained below 2. We ulti­
mately arrived at a reduced model which included five COM-B variables
and an additional two sociodemographic variables. This model was
defined as follows:
(
)
P(Timely vaccination = 1)
log
1 − P(Timely vaccination = 1)
3. Results
Data from 2036 parents were retained for analysis. There were a total
of 769, 982, and 864 parents of children 0–4, 5–11, and 12–17 years of
age, respectively. Because some parents have children in multiple age
bins, these numbers sum to >2036. Demographic information on the
sample is given in Table 1.
3.1. Reported timely vaccination
Twenty-five percent of parents of children aged 0 to 4 years (n = 190)
reported having missed or delayed a routine vaccination appointment
since the beginning of the COVID-19 pandemic in March 2020 (Fig. 1B).
The corresponding figures for the 5–11 and 12–17 age bins were 19 % (n
= 191) and 23 % (n = 199), respectively. Among those who reported
missed or delayed appointments, the majority had either caught up or
intended to do so (Fig. 1C). However, a minority (4–6 %, n = 8–11) did
not intend to catch up.
= β0 + (β1 Understanding + β2 Difficulty) + (β3 Barriers + β4 Uptake) +
(β5 Confidence) + (β6 Income + β7 Immigration) + (β1 Understanding*β3 Barriers) + (β2 Difficulty*β3 Barriers)
+ (β5 Confidence*β3 Barriers) + (β1 Understanding*β5 Confidence) + (β2 Difficulty*β5 Confidence)
3.2. Explaining self-reported timely vaccination using COM-B
Additional details on parameters and fit metrics for the models can
be found in Supplementary Table 4.
Statistical analyses were conducted using R 4.3.
To understand the behavioural and cognitive factors associated with
timely vaccination, we developed multivariable logistic regression
models incorporating measures of Capability, Opportunity, and Moti­
vation. These models included a total of 634, 743, and 703 complete
responses for children aged 0–4, 5–11, and 12–17, respectively.
Motivation, as measured by confidence in childhood vaccines,
showed a significant main effect on timely vaccination in 0–4-year-olds
(aOR = 1.81, 95 % CI: 1.14–2.84; Table 2, Fig. 2A) and this trend was
also observed for children aged 5–11 (Table 2, Supplementary Fig. 1A).
Opportunity, particularly the experience of opportunity barriers, was
significantly negatively associated with timely vaccination in 0–4-yearolds (aOR = 0.21, 95 % CI: 0.13–0.33, Table 2), and this association was
similar in older children as well (Table 2). For 0–4-year-olds, our anal­
ysis showed that neither Capability factor had a significant association
2.11. Ethical approval
Informed consent was collected prior to the start of data collection.
All study materials were reviewed and approved by Health Canada and
the Public Health Agency of Canada’s Research Ethics Board for research
studies involving human participants (December 21, 2022; REB 2022037P).
Table 2
Adjusted odds ratios (aOR) and 95 % confidence intervals for timely vaccination across three children age groups.
Variable
Motivation
Capability
Opportunity (physical)
Opportunity (social)
Sociodemographic variables
Interactions
(Intercept)
Vaccine confidence
Vaccine Understanding
Decision Difficulty
Opportunity barrier (experienced one or more)
Peer uptake estimate
Place of birth (outside Canada)
Household income (relative to $80,000 to just under $100,000)
Under $20,000
$20,000 to just under $40,000
$40,000 to just under $60,000
$60,000 to just under $80,000
$100,000 to just under $150,000
$150,000 to just under $200,000
$200,000 to just under $250,000
Vaccine confidence * Opportunity barrier (experienced one or more)
Vaccine understanding * Opportunity barrier (experienced one or more)
Decision difficulty * Opportunity barrier (experienced one or more)
Vaccine confidence * Vaccine understanding
Vaccine confidence * Decision difficulty
Notes: * p < 0.05, ** p < 0.01, *** p < 0.001.
5
0–4 years
5–11 years
12–17 years
9.68 (5.47–17.8)***
1.81 (1.14–2.84)*
1.45 (0.92–2.24)
0.76 (0.48–1.2)
0.21 (0.13–0.33)***
1.27 (1.02–1.58)*
1.57 (1.01–2.46)*
13.13 (7.23–25.12)***
1.58 (1.13–2.17)**
0.67 (0.43–1.02)
0.63 (0.45–0.89)**
0.23 (0.14–0.34)***
1.1 (0.9–1.33)
2.08 (1.37–3.22)***
3.88 (2.45–6.27)***
0.88 (0.59–1.26)
1.31 (0.98–1.73)
0.92 (0.66–1.31)
0.28 (0.19–0.41)***
1.36 (1.12–1.65)**
1.22 (0.81–1.88)
1.37 (0.46–4.7)
0.75 (0.36–1.56)
0.43 (0.22–0.84)*
0.67 (0.35–1.27)
0.47 (0.26–0.86)*
2.18 (0.9–5.91)
0.95 (0.32–3.05)
0.51 (0.29–0.87)*
0.63 (0.38–1.06)
1 (0.59–1.68)
0.9 (0.73–1.11)
1.2 (0.93–1.59)
0.66 (0.26–1.73)
0.44 (0.21–0.91)*
0.41 (0.21–0.8)**
0.56 (0.28–1.12)
0.48 (0.26–0.88)*
0.8 (0.35–1.86)
0.3 (0.11–0.84)*
0.52 (0.33–0.79)**
1.66 (1.03–2.74)*
1.37 (0.91–2.06)
0.86 (0.74–1.01)
0.92 (0.75–1.12)
2.22 (0.77–7.45)
1.3 (0.68–2.51)
1.32 (0.7–2.54)
1.42 (0.8–2.54)
1.91 (1.08–3.41)*
1.19 (0.61–2.37)
1.18 (0.48–3.13)
1.1 (0.71–1.75)
0.68 (0.47–0.98)*
1.28 (0.84–1.94)
1.02 (0.87–1.21)
1.15 (0.96–1.39)
H. MacKay et al.
Vaccine 42 (2024) 126236
Fig. 2. Opportunity barriers to routine vaccination overwhelm the positive influence of vaccine confidence on the probability of timely vaccination in children 0–4
years old.
A: Scatterplot showing the relationship between parental composite vaccine confidence score (see Fig. 3A) and the predicted probability of timely vaccination. B:
Scatterplot showing the relationship between parental composite vaccine understanding (see Fig. 4A) and timely vaccination. C: Scatterplot showing the relationship
between parental estimates of peer vaccination rate for children 0–4 years old and the predicted probability of timely vaccination.
with timely vaccination (aOR = 1.45, 95 % CI: 0.92–2.24 for vaccine
understanding and aOR = 0.76, 95 % CI: 0.48–1.20 for decision diffi­
culty; Table 2, Fig. 2B). Estimates of vaccine uptake among other 0–4
year olds (social opportunity) were significantly associated with timely
vaccination (aOR = 1.27, 95 % CI: 1.02–1.58; Table 2, Fig. 2C), and this
relationship also held for children aged 12 to 17 (aOR = 1.36, 95 % CI:
1.12–1.65; Table 2, Supplemental Fig. 2C). Vaccine confidence inter­
acted with opportunity barriers (aOR = 0.51, 95 % CI: 0.29–0.87). In the
absence of opportunity barriers, greater vaccine confidence was asso­
ciated with timely vaccination (aOR = 1.79, 95 % CI: 1.20–2.80), but
this relationship was negated in the presence of opportunity barriers
(aOR = 0.90, 95 % CI: 0.63–1.27; Fig. 2A). A similar relationship was
observed for 5–11-year-olds, but not 12–17-year-olds (Supplementary
Figs. 1A, 2A). The relationship between vaccine understanding and
barrier experience was similar but did not reach statistical significance
in 0–4-year-olds (aOR = 0.63, 95 % CI: 0.38–1.06; Fig. 2B), though it did
in older children (Table 2, Supplementary Figs. 1B, 2B).
It is possible that the interactions between motivation and oppor­
tunity could be influenced by an increased tendency among those with
high levels of vaccine confidence or understanding to identify and report
barriers after having missed/delayed a child’s vaccination. To investi­
gate this, we examined the correlation between motivation and capa­
bility factors and barrier load, the number of opportunity barriers
reported among parents reporting a missed/delayed vaccination. We
found no correlation between vaccine confidence and barrier load (r
(175) = 0.11, p = 0.16; r(180) = 0.11, p = 0.16; r(184) = − 0.07, p =
0.48 for children 0–4, 5–11, and 12–17 years of age, respectively).
Similarly, we did not observe a correlation between understanding and
barrier load (r(175) = 0.07, p = 0.38; r(180) = − 0.07, p = 0.52; r(184)
= 0.0008, p = 0.99). These results suggest that parents with higher levels
of motivation or capability are not more likely to report barriers if they
have missed a child’s routine vaccine.
As for sociodemographic variables, individuals born outside Canada
were slightly more likely to report that their 0–4- and 5–11-year-old
child(ren) had not missed or delayed a vaccination (aOR = 1.57, 95 %
CI: 1.01–2.46 and aOR = 2.08, 95 % CI: 1.37–3.22, respectively)
compared to those born in Canada. The relationship between household
income and timely vaccination was complex. Relative to families earn­
ing the approximate median Canadian household pre-tax income of
$80,000–$100,000, those with incomes of $40,000–$60,000 were
significantly less likely to report timely vaccination for their 0–4- and
5–11-year-old child(ren) (aOR = 0.43, 95 % CI: 0.22–0.84, aOR = 0.41,
95 % CI: 0.21–0.80). Higher household income did not necessarily
predict increased levels of vaccine timeliness: households earning
$100,000–$150,000 were also less likely to report timely vaccination for
their 0–4- and 5–11-year-olds (aOR = 0.47, 95 % CI: 0.26–0.86, aOR =
0.48, 95 % CI: 0.26–0.88).
The association between vaccine confidence and timely vaccination,
as well as its interaction with opportunity barriers, remained significant
among parents of 5–11-year-olds, but not for parents of 12–17-year-olds.
On the other hand, vaccine decision difficulty only showed a significant
negative association with timely vaccination among parents of 5–11year-olds (aOR = 0.63, 95 % CI: 0.45–0.89). While decision difficulty
did not interact with opportunity barriers, we did observe a significant
interaction between vaccine understanding and opportunity barriers
among parents of children aged 5–11 and 12–17 (aOR = 1.66, 95 % CI:
1.03–2.74 and aOR = 0.68, 95 % CI: 0.47–0.98, respectively; Supple­
mentary Figs. 1B, 2B). For children aged 5–11, in the absence of op­
portunity barriers, there was a trend toward a negative association
between vaccine understanding and timely vaccination (aOR = 0.66, 95
% CI: 0.43–1.02), while when opportunity barriers were present, this
was not the case (aOR = 1.10, 95 % CI: 0.88–1.36). For children aged
6
H. MacKay et al.
Vaccine 42 (2024) 126236
Table 3
Barriers to vaccination reported by parents, classified as Opportunity barriers or Other barriers.
0–4-year-olds
Opportunity barriers
Difficulty getting an appointment (e.g. no
appointments available, or scheduling
conflicts)
Fear of contracting COVID-19
My child is afraid of needles
My doctor’s office/clinic was closed
My child was sick on the day of their
appointment
Difficulty to book time off work/school for a
vaccine appointment
Lack of access to primary care physician
School closures
Difficulty obtaining childcare during
appointments
My child changed to a new preschool/daycare
Live in a remote area (limited transportation)
My child changed to a new school
Cost of the vaccine
Concerns about racism or discrimination
within the healthcare system
Language barrier
Other barriers
Uncertainty about which vaccines were
needed
Not sure about where/how to make an
appointment
It is difficult to remember when my
appointments are
Not sure where to get vaccinated
I don’t intend to have my child vaccinated
5–11-year-olds
12–17-year-olds
Barrier
frequency
OR of missed/delayed
vaccine (95 % CI)
Barrier
frequency
OR of missed/delayed
vaccine (95 % CI)
Barrier
frequency
OR of missed/delayed
vaccine (95 % CI)
19 %
2.53*** (1.7–3.78)
15 %
2.84*** (1.89–4.26)
15 %
2.49*** (1.63–3.78)
14 %
13 %
12 %
1.54 (0.97–2.42)
1.7* (1.06–2.7)
2.61*** (1.61–4.23)
14 %
16 %
10 %
1.15 (0.72–1.79)
1.33 (0.87–2.02)
1.98* (1.19–3.24)
12 %
10 %
8%
1.31 (0.8–2.09)
1.97* (1.2–3.18)
1.98* (1.15–3.37)
10 %
3.66*** (2.19–6.16)
9%
4.16*** (2.55–6.81)
6%
2.17* (1.14–4.08)
10 %
2.09* (1.23–3.51)
9%
2.58** (1.54–4.3)
7%
1.94* (1.09–3.4)
7%
7%
2.43** (1.34–4.37)
2.16* (1.16–3.98)
8%
10 %
2.16* (1.27–3.61)
1.93* (1.18–3.1)
9%
13 %
2.17* (1.27–3.65)
1.64 (1.04–2.56)
6%
2.59** (1.36–4.92)
6%
2.55* (1.36–4.73)
3%
5.9*** (2.55–14.77)
4%
4%
3%
3%
5.52*** (2.49–13.11)
4.06** (1.81–9.5)
2.42 (1.03–5.61)
6.27*** (2.63–16.54)
3%
4%
4%
3%
3.07* (1.4–6.68)
2.1 (0.94–4.52)
2.46* (1.12–5.26)
2.16 (0.93–4.84)
3%
2%
3%
3%
2.55 (1–6.42)
1.39 (0.48–3.63)
4.19** (1.78–10.3)
1.95 (0.79–4.59)
2%
2.62 (0.95–7.21)
2%
3.64* (1.45–9.3)
2%
1.67 (0.56–4.57)
2%
6.67** (2.2–24.55)
2%
2.25 (0.81–5.95)
2%
2.4 (0.76–7.32)
5%
1.99 (0.98–3.95)
6%
2.23* (1.22–4)
7%
2* (1.09–3.6)
5%
2.35* (1.14–4.83)
6%
1.47 (0.76–2.72)
6%
1.76 (0.9–3.31)
5%
1.35 (0.62–2.81)
5%
3.08** (1.63–5.79)
4%
1.95 (0.86–4.23)
4%
2%
1.59 (0.71–3.39)
2.62 (0.95–7.21)
3%
3%
2.02 (0.87–4.48)
2.32 (0.98–5.28)
4%
1%
1.4 (0.64–2.88)
2.33 (0.66–7.81)
Notes: Parents were asked: “Since the start of the pandemic, have you experienced any difficulties getting your child(ren) a routine vaccine? Select all that apply”. Odds
ratios (OR) reflect unadjusted odds of missing/delaying a routine vaccine given experience with that barrier. Barriers are sorted by frequency reported by parents of
0–4 year olds. * p < 0.05, **p < 0.01, ***p < 0.001.
12–17, greater vaccine understanding showed a trend toward positive
association with timely vaccination (aOR = 1.31, 95 % CI: 0.99–1.73),
but this was negated by experience with opportunity barriers (aOR =
0.89, 95 % CI: 0.70–1.13).
the pandemic. While 21 %–23 % of respondents reported increased
agreement with vaccine-favourable statements, 21 %–34 % reported
that they now believed more strongly in vaccine-opposed statements
(Fig. 3B). Depending on the statement, between 33 % and 53 % of re­
spondents reported a change toward either greater or less belief since
the pandemic began.
3.3. COM-B: Descriptive and univariable analyses
3.3.3. Vaccine understanding and decision difficulty (capability)
The majority of participants felt well-informed about various aspects
of childhood vaccinations, with most feeling confident in their knowl­
edge of where and how to get vaccines (94 %), the diseases protected
against (92 %), and how to schedule an appointment (92 %; Fig. 4A). In
contrast, we noted a moderate level of difficulty making vaccinationrelated decisions, with 38 % of parents agreeing that it was difficult to
keep all the relevant information together and 32 % expressing uncer­
tainty and stress around decision making (Fig. 4B).
3.3.1. Barriers associated with missed/delayed vaccinations (opportunity)
In general, opportunity barriers were strongly associated with
missing/delaying a child’s vaccination, with “difficulty getting an
appointment” having the strongest association (Table 3). Parents of 0–4year-olds reporting this barrier were 2.53 (95 % CI: 1.70–3.78) times as
likely to have missed or delayed their child’s vaccination compared with
those who did not report this barrier. This association remained signif­
icant for children aged 5–11 and 12–17 with ORs of 2.84 (95 % CI:
1.89–4.26) and 2.45 (95 % CI: 1.63–3.78), respectively. Doctor’s office/
clinic closures were also significantly associated with missed/delayed
vaccination at all three ages, while school closures were significant only
for children under 12 (Table 3). Fear of contracting COVID-19 was re­
ported by 12–14 % of parents, but was not significantly associated with
missed/delayed vaccination.
3.3.4. History of intentionally missing/delaying routine vaccines
13 % of parents reported having decided to not immunize their child
with a routine vaccine, and 16 % reported having decided to delay a
child’s routine vaccine by >30 days. The top reasons given for doing so
were related to concerns about the safety and efficacy of vaccines (re­
ported by 50–63 % of parents depending on age), interactions between
routine vaccines and the COVID-19 vaccine (reported by 36–41 % of
parents depending on age) and contracting COVID-19 during the
appointment (reported by 32–39 % of parents who had delayed; Sup­
plementary Tables 1, 2).
3.3.2. Vaccine confidence (motivation)
When asked about vaccine confidence, most parents (≥ 90 %) agreed
with affirmative statements regarding vaccine safety and efficacy.
However, we found relatively high rates of agreement with negative
statements regarding vaccination, with 58 % of parents reporting
concern with potential vaccine side effects (Fig. 3A). We also assessed
participants’ perceived changes in their attitudes toward vaccines since
7
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Vaccine 42 (2024) 126236
Fig. 3. Vaccine confidence and perceived changes in attitude.
A: Bar graph depicting the rate of net agreement (strongly agree and somewhat agree) among parents with general vaccine confidence statements. B: Perceived
change in attitudes with respect to vaccines. Parents were asked “Compared to before the pandemic, have your views on the following changed?”
Fig. 4. Capability: Vaccine Understanding and Decision Difficulty.
A: Bar graph illustrating the rate of net agreement (strongly agree and somewhat agree) among parents with statements related to understanding of various aspects of
routine childhood vaccination. B: Bar graph depicting the extent of net agreement (strongly agree and somewhat agree) with statements related to vaccine decision
difficulty experienced by parents.
4. Discussion
appointment since the pandemic began in March 2020, with rates for
parents of children aged 5–11 and 12–17 at 19 % and 23 %, respectively.
Even temporary delays amount to periods of under-vaccination, during
which children may be at risk for vaccine-preventable diseases.
Furthermore, intentional delay of vaccination is associated with an
increased risk of not receiving all recommended vaccine doses [33],
raising the possibility that delay induced by the pandemic may
The COVID-19 pandemic has posed unprecedented challenges to the
delivery and uptake of routine childhood vaccines. Our study reveals
significant perturbations to routine vaccination across different age
groups in Canada. Approximately 25 % of parents with children aged
0–4 years reported having missed or delayed a routine vaccine
8
H. MacKay et al.
Vaccine 42 (2024) 126236
jeopardize long-term coverage goals. While most parents have caught up
or plan to catch up soon, 4–6 % of those behind on their child’s vacci­
nation did not intend to. This is in addition to the 2–4 % of all parents
who did not plan on having their child vaccinated in the first place. This
figure is similar to rates of non-vaccination previously reported [10], but
our data show that new, COVID-related reasons are among the top
selected by parents who have intentionally delayed or missed their
child’s vaccination, suggesting that the pandemic may have exacerbated
this trend.
In this study, we applied the COM-B model to examine factors
associated with missing or delaying a child’s routine vaccine appoint­
ment during the COVID-19 pandemic. Our results indicate that oppor­
tunity, particularly experience with opportunity barriers, was the most
significant predictor of timely vaccination. This finding is consistent
with previous studies identifying barriers/enablers as a key determinant
of vaccine uptake [11,34,35], as well the observation that coverage rates
for a range of vaccines were lower among two-year-old children of
parents who reported experiencing pandemic-related barriers [10]. In
addition, both motivation (e.g., vaccine confidence) and capability
factors (e.g., vaccine understanding) had a stronger association with
timely vaccination among parents who did not encounter opportunity
barriers compared with those who did. This finding is consistent with
implementations of the COM-B model where opportunity influences the
relationship between motivation (or capability) and behaviour [36], as
well as the Behavioural and Social Drivers (BeSD) framework [15],
which suggests that practical issues can influence whether motivation/
intention translates into vaccination.
The relative association of capability, opportunity, and motivation
factors with timely vaccination also varied with the child’s age. The
association with social opportunity factors became increasingly pro­
nounced in older children, particularly those aged 12–17. Simulta­
neously, decision difficulty became a dominant psychological capability
factor in these older age groups. These findings highlight the need for
age-appropriate public health strategies. For younger children,
addressing opportunity barriers and boosting parental confidence is
crucial. Older children, particularly those in marginalized communities,
tend to have less contact with the medical system [37], and for them,
simplifying the delivery of key information to parents and leveraging the
influence of vaccination as a social norm may be more important.
While opportunity barriers were treated as a single category in our
COM-B model, specific barriers within this set had unique and agespecific univariable associations with timely vaccination. For example,
while difficulty getting an appointment was a strong barrier for all age
groups, clinic closures were particularly disruptive for parents of
younger children. The association between opportunity barriers and
vaccination timeliness diminished for older children, but remained
significant.
Aside from opportunity barriers and perceived norms, the behav­
ioural factors we measured did not show significant associations with
timely vaccination in children aged 12–17. These children typically
receive fewer vaccines and often receive them at school, therefore the
pace and context of vaccination differs compared to younger children.
The increased autonomy for children aged 12–17 may diminish the in­
fluence of the parent’s own motivation and capability. In addition,
although we provided vaccination schedules to participants, these par­
ents might still primarily think of younger children’s vaccines (e.g.,
MMR) when asked about “childhood vaccination”. This could lead some
predictors (e.g., routine childhood vaccination confidence) to be weaker
for parents of 12–17-year-olds compared with other age groups.
Despite barriers to vaccination, we observed generally strong vaccine
confidence, with 90 % or more affirming the efficacy and safety of
routine childhood vaccines. However, we noted a marked increase in
agreement with vaccine-opposed statements (e.g., “Natural immunity is
more protective than vaccines”) compared to responses reported in
cNICS, a national-level survey of vaccine coverage and attitudes toward
vaccination in 2019 [10,31]. While differences in sampling
methodology preclude formal comparisons between our survey and
cNICS, this observation, along with our data on self-reported attitude
change, suggest that at least subjectively, many people believe their
attitudes have become more negative since the pandemic. Measures of
perceived attitude change must be interpreted with caution, however, as
current attitudes can bias the recall of past attitudes [38–40].
Our study has some limitations that must be acknowledged. Vaccine
timeliness as we have defined it is naturally a less precise measure than
those that examine children’s vaccine records or corresponding
administrative data, leaving open the possibility that parents may have
forgotten or have been unaware of a missed vaccination, or perhaps even
forgotten having caught up. Moreover, as with any observational, crosssectional study, the relationship between our predictors and timely
vaccination is correlational. Because of this, there remains uncertainty
as to which factors lie upstream of timely vaccination, and may therefore
be good targets for intervention, and which ones constitute post hoc
rationalizations for missing a vaccination. There is evidence that vaccine
hesitancy is associated with vaccine intent prior to birth and with actual
postnatal uptake, suggesting that attitudes toward vaccination generally
precede vaccination behaviour [41], although associations between
hesitancy and subsequent vaccination have not been observed univer­
sally [42], making it difficult to rule out post hoc rationalization.
In the context of the COVID-19 pandemic, accurate measurement of
changes in vaccine timeliness, vaccine confidence, understanding, and
other such measures relative to before the pandemic would enhance our
confidence in the pandemic having a causal role. This information
would also be useful in contextualizing our primary dependent variable
of vaccine timeliness, because in Canada, delays in vaccination have
been a persistent issue even before the pandemic [43,44]. Absence of
pre-pandemic data with the current survey measures precludes direct
comparison with baseline levels. However, Lee et al. found a significant
drop in on-time vaccinations in Canada post-pandemic, from 81.8 % to
62.1 %, with an increased median delay length, especially in children
over six months [45]. Similarly, few longitudinal studies of routine
vaccine confidence exist, and while pre- and post-pandemic longitudinal
data would be invaluable, anticipating such a need was not possible
prior to March 2020. However, longitudinal data within the pandemic
do exist. Humble et al. conducted a longitudinal study through two
national surveys (December 2020 and October/November 2021) and
found an increase in positive perceptions and acceptance of routine
childhood vaccines among Canadian parents [46]. It is likely, however,
that this sentiment continued to shift during later stages of the
pandemic, as declines in confidence have been observed in studies that
focus on these later stages [27].
Our study differs from others on routine vaccination during the
pandemic because of its focus on the interplay of behavioural, cognitive,
and opportunity factors in influencing timely vaccination. Owing
perhaps to the strong associations between the outcome and these fac­
tors, household income and immigration status emerged as the only
significant sociodemographic variables in our final models. While lower
rates of timely vaccination have been previously observed in lowerincome households, the relationship between income, immigration sta­
tus, and vaccine uptake in Canada is inconsistent across studies. Gilbert
et al. [47] and Chen et al. [48], using data from the 2013 and 2019
cNICS, respectively, both found that lower-income households had
higher rates of incomplete vaccination and vaccine hesitancy. In
contrast, O’Donnell et al. found that lower household income was
associated with improved vaccine timeliness [44]. Our finding of a
higher probability of timely vaccination among individuals born outside
of Canada has been observed previously [49], and may relate to dif­
ferences in trust in institutions, as well as in sources of information used
in making decisions around vaccines [50]. Each of these demographic
variables represents a substantial flattening of meaningful interindi­
vidual variation and does not capture the range of challenges associated
with being new to a country or having a low household income.
Accordingly, an important topic for future research is how these
9
H. MacKay et al.
Vaccine 42 (2024) 126236
variables interact with the cognitive and behavioural factors to influ­
ence vaccine uptake.
Overall, our data spotlight a vulnerable state of affairs for routine
childhood vaccination during the pandemic, with as many as 25 % of
parents reporting missed or delayed routine vaccinations for their chil­
dren, and many reporting that their attitudes toward vaccines have
become more negative since before the pandemic. Barriers such as dif­
ficulties scheduling an appointment, clinic closures, and school closures,
all of which limit a parent’s opportunity to have their child vaccinated,
are negatively associated with vaccine timeliness. These barriers negate
the normally positive effects of vaccine confidence and understanding.
The rapid change of the COVID-19 pandemic context in Canada,
from the emergency phase in early 2020 to the winding down of the
public health response in 2022, has presented a unique and evolving
landscape for vaccination. Each phase of the pandemic represents a
distinct snapshot of the vaccination landscape, suggesting that a
comprehensive understanding of its impact on routine vaccination re­
quires data from as many stages as possible. Such an approach ac­
knowledges that, while short-term disruptions and challenges to vaccine
confidence pose risks, they also present opportunities for enhancing
public health strategies. Our research underscores the critical role of
opportunity barriers and their interaction with motivation and capa­
bility in determining uptake of routine vaccination. By enhancing our
understanding of these factors, it will be possible to bolster the resilience
of vaccination programs against future disruptions, ultimately helping
Canada reach its immunization coverage goals.
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Funding
No funding was received for the design of the study and collection,
analysis and interpretation of data and in writing the manuscript.
CRediT authorship contribution statement
Harry MacKay: Writing – review & editing, Writing – original draft,
Visualization, Investigation, Formal analysis, Data curation, Conceptu­
alization. Jeremy D. Gretton: Writing – review & editing, Writing –
original draft, Supervision, Project administration, Formal analysis.
Sandra Chyderiotis: Writing – review & editing, Methodology,
Conceptualization. Stephanie Elliott: Writing – review & editing,
Methodology, Investigation, Conceptualization. Ana Howarth: Writing
– review & editing, Methodology, Conceptualization. Catherine Guo:
Writing – review & editing, Resources, Project administration. Angela
Mastroianni: Writing – review & editing, Visualization, Formal anal­
ysis, Data curation. Christine Kormos: Writing – review & editing,
Supervision, Project administration, Conceptualization. Jessica Leifer:
Writing – review & editing, Supervision, Project administration,
Conceptualization. Lauryn Conway: Writing – review & editing, Su­
pervision, Project administration, Conceptualization. Mark D. Morris­
sey: Writing – review & editing, Supervision, Project administration,
Methodology, Investigation, Conceptualization.
Declaration of competing interest
The authors declare that they have no known competing financial
interests or personal relationships that could have appeared to influence
the work reported in this paper.
Data availability
The authors do not have permission to share data.
Appendix A. Supplementary data
Supplementary data to this article can be found online at https://doi.
org/10.1016/j.vaccine.2024.126236.
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H. MacKay et al.
Vaccine 42 (2024) 126236
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