The COVID-19 virus reached pandemic status in March 2020. Since then, the virus has spread to more than 213 nations and territories, infected more than 186 million people, and resulted in more than 6 million deaths worldwide [
1]. As the world grappled with the political, social, economic, and human effects of the virus, a number of vaccines were trialled and developed to counter the virus. Within a year of the outbreak, numerous global companies successfully managed to negotiate clinical trials and received approval for vaccines [
2]. In mid-2021, vaccines began being administered throughout the world at varying rates to the public. In the lead up to, and then during the vaccine delivery, vaccine hesitancy/scepticism remains a consistent challenge [
3,
4]. for example in an analysis of 19 nations found COVID-19 vaccine acceptance rates varied from 55% in Russia, 90% in China and that 41% of Austrians are hesitant toward COVID-19 vaccines [
5,
6].
Methods
After ethical approval, a nationally representative sample survey of New Zealand adults was collected in April–May 2021. The survey was conducted by Qualtrics, a survey agency. Qualtrics panels are comparable to other populations in published research [
48]. Participants for this study included 1852 New Zealanders, a response rate of 35% of individuals contacted. Participants completed the Vaccine Hesitancy Scale [
9], the Patient Advocacy Scale [
10], demographic questions, a question asking if they are able to receive the COVID-19 vaccination, and a follow-up question (if unable to receive the vaccination) asking them why they are unable to receive the vaccination. Table
1 presents the full demographic information for all participants. Confirmatory factor analyses (CFAs) were conducted on all measures. Established criteria were followed [
49]. See Table
2 for means, standard deviations, and alphas associated with the study variables.
Table 1
Demographic information
Age | | 42.41 | 16.79 |
Can you get vaccinated? |
Yes | 1412 (76.2%) | | |
No | 440 (23.8%) | | |
Why Can’t you get vaccinated? |
Guillian-Barre Syndrome | 3 (.7%) | | |
Liver Disease | 61 (13.9%) | | |
Asthma | 78 (17.7%) | | |
Kidney Disease | 33 (7.5%) | | |
Lyme Disease | 18 (4.1%) | | |
Pregnant or Trying to be | 106 (24.1%) | | |
Doctor Said I can’t | 21 (4.8%) | | |
Religious Leader said I can’t | 41 (9.3%) | | |
Miscellaneous Cancer | 30 (6.8%) | | |
Didn’t Provide Reason | 49 (11.1%) | | |
Sex |
Male | 830 (44.8%) | | |
Female | 1021 (55.1) | | |
Other | 1 (.1%) | | |
Do you Have Private Health Insurance |
Yes | 632 (34.1%) | | |
No | 1220 (65.9% | | |
Race |
Pākehā (White) | 926 (50%) | | |
Māori | 557 (30.1%) | | |
Pacific/Islander | 224 (12.1%) | | |
Other | 145 (7.8%) | | |
Highest Educational Level |
High School | 719 (38.8%) | | |
2-year degree/University | 313 (16.9%) | | |
University degree | 706 (38.1%) | | |
Post Graduate Degree | 114 (6.1%) | | |
Political Affiliation |
National | 487 (26.3%) | | |
Labour | 797 (43%) | | |
Green | 115 (6.2%) | | |
Māori | 37 (2%) | | |
Other | 59 (3.2%) | | |
No Affiliation | 357 (19.3%) | | |
Table 2
Means, standard deviations, reliability coefficients, and correlations
| Combined Sample n = 1852 |
Variable |
M
|
SD
|
α
| (1) | (2) | (3) | (4) |
(1) Confidence in Vaccines | 4.90 | 1.94 | .97 | - | | | |
(2) Info Seeking | 2.99 | .85 | .78 | .21** | - | | |
(3) Assertiveness | 2.87 | .75 | .74 | .11** | .67** | - | |
(4) Mindful Noncompliance | 2.84 | .90 | .86 | -.13** | .39** | .52** | - |
| Not able to Vaccinate Sample n = 440 |
Variable |
M
|
SD
|
α
| (1) | (2) | (3) | (4) |
(1) Confidence in Vaccines | 2.31 | 1.50 | - | - | | | |
(2) Info Seeking | 2.59 | .94 | - | .15** | - | | |
(3) Assertiveness | 2.58 | .89 | - | .18** | .71** | - | |
(4) Mindful Noncompliance | 2.69 | .96 | - | .06 | .45** | .58** | - |
| Able to Vaccinate Sample n = 1412 |
Variable |
M
|
SD
|
α
| (1) | (2) | (3) | (4) |
(1) Confidence in Vaccines | 5.71 | 1.22 | - | - | | | |
(2) Info Seeking | 3.12 | .78 | - | -.05 | - | | |
(3) Assertiveness | 2.96 | .68 | - | -.20** | .62** | - | |
(4) Mindful Noncompliance | 2.89 | .88 | - | -.45** | .35** | .49** | - |
Vaccine Hesitancy Scale
The 14-item Vaccine Hesitancy Scale (VHS) was adopted to assess vaccine hesitancy [
9]. The VHS is a 5-point Likert-type scale ranging from s
trongly disagree to
strongly agree.The VHS has two factors: confidence and risk perception. Sample items include, “Vaccines are effective,” “New vaccines carry more risks than older vaccines,” “I feel comfortable getting vaccinated,” and “Governments over hype the need for vaccines.” Reliabilities have ranged from 0.80 to 0.95 [
9]. In this study the two factor-solution did not fit the data: χ2(19) = 684.03,
p < 0.0001, CFI = 0.88, RMSEA = 0.15, GFI = 0.92. However, a one-factor solution with confidence in vaccines was a valid solution: χ2(9) = 597.62,
p < 0.001, CFI = 0.96, GFI = 0.95, SRMR = 0.05. Thus, a higher score on VHS indicates higher confidence in vaccines. Therefore, for the purpose of data interpretation, the variable “vaccine hesitancy” will be labelled “vaccine confidence”.
Patient Self-Advocacy Scale
The 18 item Patient Self Advocacy scale was adopted [
10]. This scale assesses patient self-advocacy across three dimensions: increased illness and treatment education, increased assertiveness in health care interactions, and increased potential for nonadherence. The scale is on a 5-point Likert-type scale ranging from
strongly disagree to
strongly agree.Sample items include: “Sometimes there are good reasons not to follow the advice of a physician,” and “I actively seek out information on my illness.” Reliabilities for the measure have ranged from 0.70 to 0.92 [
10,
50]. CFA confirmed a three-factor solution after deleting five items (1, 2, 7, 10, and 17): χ2(62) = 909.36,
p < 0.001, CFI = 0.95, GFI = 0.95, RMSEA = 0.05.
Statistical analysis
To address the research questions, various statistical approaches were employed. To answer RQ1, a simple frequency analysis was conducted. To answer RQ2, an independent samples t-test was conducted comparing those who identify as able and unable to receive a COVID-19 vaccination. To answer RQ3, multiple regression was used. Vaccine confidence was entered as the predictor variable. The following predictor variables were entered: ability to get a vaccine, age, sex, race, highest educational level, political affiliation, does the participant have private medical insurance, and a dimension of patient self-advocacy (Info Seeking, Assertiveness, and Mindful Noncompliance). Dummy variables were created for race and political affiliation, with Pākehā and the Labour Party serving as reference groups. Cross-product terms were created to test for interaction effects.
Results
Ability to get vaccinated
The first research explored the extent to which New Zealanders identify as able to receive a COVID-19 vaccine. Of the 1852 participants, 440 identified as not being able to receive a COVID-19 vaccination, 23.75%. Of those particiants, individuals who identified themselves as having Guillain-Barré Syndrome (GBS), Liver disease, kidney disease, and cancer meet the criteria set by groups such as the CDC (28.9% of the 23.75% of unable to receive vaccine participants). Those individuals who stated they could not receive the vaccination due to asthma, Lyme Disease, pregnancy or trying to get pregnant, and/or doctor said I can’t made up 50.7% of the unable to receive vaccination group. These reasons fall within a grey area as per CDC and other association guidelines [
47].
Vaccine hesitancy
Independent samples t-test compared those who identify as able and unable to receive a COVID-19 vaccination on vaccine hesitancy (RQ2). Those who identify as medically able to be vaccinated expressed significantly higher confidence (M = 5.71, SD = 1.22) in the vaccine than those who identified as unable to be vaccinated (M = 2.31, SD = 1.50); t(1850) = -48.09, p < 0.001.
To answer RQ3, multiple regression was used. In model 1, ability to get a vaccine was entered (
R2= 0.55). In model 2, age, sex, race, educational level, political affiliation, and if a participant has private medical insurance were entered. This model was a significant improvement over model 1 (
R2= 0.60;
ΔF = 16.45,
p < 0.001). In model 3, Info Seeking, Assertiveness, and Mindful Noncompliance (patient self-advocacy) were entered. This model was a significant improvement over model 2 (
R2= 0.64;
ΔF = 71.41,
p < 0.001). In model 4, cross-products of ability to get vaccinated and patient self-advocacy were entered to determine the effects of ability to get a vaccination and patient self-advocacy on vaccine confidence/hesitancy. This model was a significant improvement over model 3 (
R2= 0.66;
ΔF = 29.21,
p < 0.001), suggesting a significant interaction effect. Model 4 was retained for final analysis. Regression results are presented in Table
3.
Table 3
Regression model for confidence in COVID-19 vaccine
Intercept | -1.08 | .13 | -.96 | .21 | -.33 | .22 | -3.42 | .44 |
Vaccine Possible | .75** | .07 | .64** | .09 | .65** | .09 | 1.07** | .25 |
Age | | | .19** | .01 | .16** | .01 | .15** | .01 |
Female | | | .04* | .06 | .05* | .06 | .05** | .06 |
Māori | | | -.01 | .07 | -.01 | .07 | -.02 | .06 |
Pacific/Islander | | | -.01 | .10 | -.01 | .09 | -.01 | .09 |
Other Race | | | .02 | .11 | .01 | .11 | .01 | .10 |
National Party | | | -.08** | .08 | -.07** | .07 | -.08** | .07 |
Green Party | | | .02 | .13 | .04* | .12 | .03 | .12 |
Māori Party | | | .01 | .21 | .01 | .20 | .01 | .19 |
Other Political Party.01 | | | .21 | .01 | .16 | .01 | .16 | |
No Political Affiliation | | | .03 | .08 | .03* | .08 | .03* | .07 |
Private Insurance-.09** | | | .06 | -.09** | .06 | -.08* | .06 | |
Highest Educational Level | | | .06** | .03 | .06** | .03 | .05** | .03 |
Info Seeking | | | | | .10** | .04 | -.03 | .17 |
Assertiveness | | | | | .01 | .05 | .26** | .20 |
Mindful Noncompliance | | | | | -.23** | .04 | .15* | .15 |
Info Seeking*Vaccine Possible | | | | | | | .18 | .10 |
Assertiveness*Vaccine Possible | | | | | | | -.38** | .11 |
Mindful Noncompliance*Vaccine Possible | | | | | | | -.50** | .08 |
F
| 2312.89*** | 210.93*** | 204.47** | 184.74** |
ΔF
| | 16.45** | 71.41** | 29.21** |
R2
| .55 | .60 | .64 | .66 |
R2adj
| .55 | .60 | .64 | .65 |
As model 4 in Table
3 depicts, there are multiple main and interaction effects in predicting vaccine confidence. Assertiveness (
b = 0.26) and Mindful non-compliance (
b = 0.15) both have positive effects on confidence. Individuals who identify as being able to be vaccinated tend be more confident, and thus have less hesitancy (
b = 1.07). Age (
b = 0.15) and educational level (
b = 0.05) have positive effects on vaccine confidence. Women were higher in confidence (
b = 0.05) than men. Regarding political affiliation, individuals who did not identify with a political party had higher levels of confidence (
b = 0.03), while National voters (
b = -0.08) were lower in confidence when compared to Labour party voters. Not having private insurance had a negative effect on vaccine confidence (
b = -0.08).
Regarding the interaction effects, the following results were found. First, assertiveness among individuals who are able to be vaccinated had less of an effect on vaccine confidence compared to those who are unable to be vaccinated (b = -0.38). Assertiveness is seen as a demand for autonomy in health care decisions. Therefore, those individuals who are able to be vaccinated are less likely to demand autonomy or to assert independence in vaccine decisions. Similarly, mindful noncompliance among individuals who are able to be vaccinated also had less of a negative effect on vaccine confidence (b = -0.50) compared to those who are unable to be vaccinated. The tendency to reject medical treatments and not-comply is not as strong among the group able to receive vaccines.
Discussion and conclusion
Research suggests for New Zealand to have any chance of achieving herd immunity against new COVID-19 variants, in particular the delta or omicron variants, vaccination rates will need to be well over 90% [
51]. Therefore, it is imperative to understand the factors that influence peoples’ willingness to get vaccinated. The current study adds to the knowledge of vaccine hesitancy by understanding the reasons given for not being able to have a vaccine and also the differing vaccine attitudes between those who report being able to have vaccines and those who do not.
Our model predicts up to 65% of COVID-19 vaccine hesitancy. Those who were more confident or had higher levels of self-efficacy were more likely to be willing to receive COVID-19 vaccines and this is similar to previous research into vaccine uptake [
52]. Women were more confident than men in New Zealand, but interestingly, this result differs from recent research which has found men are more confident than women in relation to COVID-19 vaccines [
53,
54]. These differing results could be attributed to the nature and form of the New Zealand government’s vaccine rollout campaign, the centralised messaging during the pandemic, and/or a variety of other health messaging related issues. More research should explore why women in New Zealand are more confident than men in vaccines.
The decreased confidence in COVID-19 vaccines among those identifying as National party voters, a conservative party, is similar to overseas research finding conservatives were less likely to intend to vaccinate [
55]. While not directly related to COVID-19 vaccines, research has found political conservatism related to a lower level of trust in science, which indirectly and negatively affected willingness to comply with COVID-19 safety measures [
56]. Whether political conservatives in New Zealand follow the same trend is an area for further research.
Nearly 25% of those surveyed for this study, reported they were unable to receive a vaccine. However, of that 25% of the total sample, nearly 75% of this group did not meet criteria considered legitimate by the CDC for not receiving a vaccination. This group either fell into a medically grey area, gave religious reasons, or no reason at all. It is this latter group that is of concern if New Zealand or other countries are to achieve herd immunity. The biggest group in the medically grey area were women who identified themselves as pregnant or trying to become pregnant (24.1%) of the 25% who said they could not get vaccinated. A number of previous studies have found pregnant women are more likely to be vaccine hesitant [
57]. Given previous research showing the reactions of pregnant women to vaccines, it appears to follow that women trying to get pregnant may be concerned that vaccines harm their chances of becoming pregnant. However, all advice from the New Zealand Ministry of Health (MoH) and the CDC state women who are pregnant, trying to get pregnant and breastfeeding can safely have the COVID-19 vaccine [
47,
58]. The next largest group in the medical grey area stated they could not receive a vaccine because they had asthma (17.7%). Given COVID-19 has serious effects on the respiratory system it is argued this would be a group being encouraged to receive the vaccine. Indeed the New Zealand Government’s Unite against COVID-19 website, encourages all those who have underlying health conditions, including asthma, to get a COVID-19 vaccine [
59]. These results concerning pregnancy and asthma suggest MoH messaging is not being clearly received by some of those eligible to receive the COVID-19 vaccine. This is of concern as women who contract COVID-19 during pregnancy and those with asthma can become seriously ill. More targeted communication may be needed for these two groups concerning the benefits of and their ability to have COVID-19 vaccines. Previous research has illustrated, in addition to public health campaigns, insuring that frontline medical staff, physicians, midwives and nurses, have factually based responses to frequently asked questions or misinformation about the COVID-19 and other vaccines, can alleviate fears among women who are pregnant or wishing to become pregnant [
57,
60,
61]. Such information may also be able to be used to alleviate the fears of those with conditions such as asthma [
57]. Therefore, in addition to the current public health messaging, New Zealand should invest in training frontline medical staff to insure they have the required information so they can feel confident when confronted with concerns and objections.
For the last group in the medically grey area, those identifying with Lymes disease (4.1%), the picture is less clear. There is no clear consensus on if Lyme disease sufferers are unable to get vaccinations [
47]. Many of the symptoms of Lyme disease and long-haul COVID-19 are similar [
62] and so more medical research may be required to definitively answer whether or not Lyme disease sufferers can received COVID-19 vaccines.
Just over two percent of those surveyed stated they could not get a COVID-19 vaccine because their religious leader told them not to get a vaccine. This percentage is similar to the U.S. where those seeking non-medical exemptions rose from 1.48% to 2.2% between 2004–2011 [
63]. While this does not seem to be a high figure overall it does not take into account that those who seek such exemptions seem to cluster geographically. Such geographic clustering also occurs in New Zealand with the West Coast District Health Board suggesting several religious groups who did not believe in immunisation meant the Board would never reach its immunisation targets [
64]. This means these areas may remain susceptible to COVID-19 and could be a source of infection for the rest of the country unless properly managed. Religious objections to vaccines have been present since the first vaccines were produced [
13]. However, ‘religious reasons’ to refuse vaccines are often not theologically based, rather they reflect the safety concerns of a faith based social network of people [
65]. Therefore, further research in the New Zealand context may be beneficial to investigate whether religious reasons arise from inherently close social networks or from particular beliefs. In some cases these religious objections may be overcome by frontline medical staff pointing out that high profile religious leaders like the Pope have encouraged vaccination.
58. These high profile messages could also be repeated in public health campaigns.
Of more concern are those that did not provide a reason for their inability to have a vaccine. Without an understanding of this group’s inability to receive a vaccine it is impossible to construct any meaningful communication strategies to deal with any concerns this group might have about Covid-19 vaccines. This is an area for more in-depth research.
Health communication research demonstrates that patients who are more involved in their treatments and medical decisions tend to seek out more information, evaluate treatments based on their effectiveness and communicate with providers with more assertiveness [
66,
67]. The results of the current study reveal that seeking out information, even if one is “unable” to get a vaccine, is linked with increased confidence in vaccines. This link demonstrates the importance of information provision in reducing vaccine hesitancy. As individuals seek out information, their confidence usually increases, decreasing hesitancy. In addition, the need for autonomy (assertiveness) increases hesitancy in those “unable” to be vaccinated. For those able to be vaccinated, the need for autonomy and mindful non-compliance both decrease confidence in vaccines/increased hesitancy. These results demonstrate the importance of considering patient self-advocacy behaviours when examining vaccine hesitancy. As the results show, an individual’s level of involvement in their own treatment or medical decision-making has a significant impact on their level of hesitancy or confidence in vaccines.
The results of the current study underscore the importance of health and vaccine literacy which are essential to permit patients to both obtain and evaluate health/vaccine information, and to respond to (mis)information about vaccines. Thus, it is critical for governments to develop informative campaigns that confront public concerns directly [
68].
While this study is a national sample of the New Zealand public, the study is cross-sectional in its design. Thus, the study is not able to measure vaccine hesitancy, confidence, nor patient self-advocacy longitudinally. The data for this study were collected in April–May 2021, and it is highly likely that attitudes toward vaccines will shift as the vaccine rollout intensifies in New Zealand. Future research should explore these trends longitudinally. Second, while the study was drawn from national databases held by Qualtrics, the sample is not fully representative of the New Zealand population. For example, less than 1% of this sample identified as an other sex/gender, while more than 1% of the population identify as such. Future research could further strive for an even more representative sample, Third, while the sample closely resembled the demographics of New Zealand, we did not track participant geographic location. New Zealand is a largely rural country of five million people. The country has one urban area of over 1 million people (Auckland) and two other areas of 200,000 + people (Christchurch and Wellington). Future research should examine vaccine hesitancy among rural versus urban dwellers, particularly as journalists and researchers in New Zealand have alluded to differences in the perceptions between the two groups on vaccines [
69].
This research investigated vaccine hesitancy in New Zealand by examining the scale and causes of hesitancy and related behavioural characteristics. The research has generated a model that predicts up to 65 percent of COVID-19 vaccine hesitancy in New Zealand. There are three notable findings: first that many people incorrectly identify themselves as “unable” to receive the vaccine. Second, autonomy in health care choices increases hesitancy in those who identify themselves as “unable” to be vaccinated. Third, the behaviour of “seeking out information” about vaccines, is significantly linked with increased confidence in vaccines. Together, these findings are relevant in assisting the New Zealand Government in public health communication messages to reduce hesitancy as the vaccine roll-out intensifies. In particular, it would be beneficial for the New Zealand Government to redirect communication strategies towards addressing balanced evaluative information to the New Zealand public through trusted routes. In particular, the hesitancy of pregnant and hoping to become pregnant women is an area requiring a focused communication plan. Similarly communication to New Zealanders with health conditions such as asthma requires focused attention as this group are a sizeable minority who are both hesitant and at greater risk.
More specifically, communication strategies and health practitioner training which focus on generating patient self-advocacy, information seeking behaviour, and culturally literate engagements are medium to long-term strategies that will help with hesitancy issues. This investment in fundamental change to the practitioner-patient communication exchange seems justified given that COVID-19 will persist as an endemic disease requiring regular seasonal vaccination and also reflects the fact that even pre-COVID, public health strategies were increasingly blighted by vaccine hesitancy and patients’ non-adherent behaviours.
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