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Influence of information sources on vaccine hesitancy and practices
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Original article
Influence of information sources on vaccine hesitancy and practices夽 Influence des sources d’information sur l’hésitation vaccinale et les pratiques vaccinales Jalal Charron ∗ , Arnaud Gautier , Christine Jestin Santé Publique France, 12, rue du Val d’Osne, 94410 Saint-Maurice, France
a r t i c l e
i n f o
Article history: Received 5 May 2019 Received in revised form 30 August 2019 Accepted 28 January 2020 Available online xxx Keywords: Vaccine hesitancy Social networks Vaccines Internet
a b s t r a c t Introduction. – Many factors influence vaccination practices and attitudes. This study aimed to identify vaccine information sources used by parents of children aged 1–15 years to get a better understanding of the relation between vaccine information sources, practices for two vaccines (MMR, HBV), vaccine acceptance, and vaccine hesitancy. Methods. – A total of 3938 parents, drawn by random sampling, were interviewed by telephone as part of the “2016 health barometer” survey. Vaccine information sources were described and analyzed according to socio-demographic variables. Multivariate logistic regression models were then built to explain vaccine information sources usage, vaccination practices and attitudes. Results. – Healthcare professionals (HCP), the Internet, and relatives were the three main vaccine information sources. Vaccination practices and acceptance were better when parents were getting information from HCPs compared with parents getting information from the Internet or relatives. Besides, getting information from the three different types of sources was associated with the highest rate of vaccine hesitancy: 70.9% (OR = 4.6; P < 0.0001) versus 34.6% among parents getting information from HCPs only. Conclusion. – Those results suggest an interest in providing quality information about vaccination on the Internet. The primary role of HCPs in vaccination decision is once again demonstrated. © 2020 Elsevier Masson SAS. All rights reserved.
r é s u m é Mots clés : Hésitation vaccinale Vaccins Réseaux sociaux Internet
Objectifs. – Les attitudes et pratiques vaccinales sont des processus complexes influencés par de nombreux facteurs. L’objectif de cette étude était d’identifier le recours à différentes sources d’information sur la vaccination chez les parents d’enfants de 1 à 15 ans afin de mieux comprendre les liens entre sources d’information, pratiques vaccinales déclarées pour deux vaccinations (ROR, VHB), adhésion et hésitation vaccinales. Patients et méthodes. – Un échantillon de 3938 parents d’enfants de 1 à 15 ans, construit par sondage aléatoire, a été interrogé par téléphone dans le cadre de l’enquête Baromètre Santé 2016. Dans un premier temps, les sources d’information ont été décrites et analysées selon différentes variables sociodémographiques. Dans un second temps, des modèles multivariés de régression logistique visant à expliquer l’usage des différentes sources, les pratiques vaccinales, l’adhésion et l’hésitation ont été construits. Résultats. – Les trois sources d’information principales chez les parents étaient les professionnels de santé, internet et l’entourage. Les pratiques (ROR, VHB) et l’adhésion à la vaccination étaient meilleures chez les parents qui s’informent chez un professionnel comparé à ceux qui s’informent sur internet ou auprès de leur entourage. Par ailleurs, le fait d’associer les trois types de sources étaient associé à l’hésitation la plus élevée: 70,9 % (OR = 4,6; p < 0,0001) contre 34,6 % chez ceux s’informant uniquement auprès de professionnels.
夽 The present work was presented at the 2018 Rencontres de Santé publique France. ∗ Corresponding author. E-mail address: [email protected] (J. Charron). https://doi.org/10.1016/j.medmal.2020.01.010 0399-077X/© 2020 Elsevier Masson SAS. All rights reserved.
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Conclusions. – Il existe un intérêt à apporter des informations de qualité sur la vaccination sur internet. Par ailleurs, le rôle primordial des professionnels de santé dans la décision vaccinale est une nouvelle fois souligné. ´ ´ © 2020 Elsevier Masson SAS. Tous droits reserv es.
1. Objectives Vaccination is one of the most efficient public health measures. According to the World Health Organization (WHO), vaccination prevents the death of two to three million individuals every year [1]. However, vaccination programs have always raised concerns and opposition among some population groups [2]. Mistrust in vaccination has become more evident over the past years in many countries. It may take the form of vaccine hesitancy, which is defined by the SAGE working group of the WHO as the delay in acceptance or refusal of vaccines despite availability of vaccination services [3]. Vaccination against H1N1 influenza sparked a polemic in France in 2009, which was largely covered by the media and social networks. This polemic highly contributed to reinforcing such hesitancy as vaccine acceptance declined from 90% in 2005 to 61% in 2010 among people aged 18-75 years living in metropolitan France [4]. Vaccine acceptance among the general population is a major challenge, as poor acceptance leads to suboptimal vaccine coverage and to the circulation of diseases that could be prevented. Vaccine acceptance is particularly important among parents. They are confronted with vaccination choices for their children, of which they must assess the determinants. Acceptance, hesitancy, and vaccination practices are indeed complex processes influenced by numerous factors [5–7], such as the level of knowledge and information on vaccination. Gautier et al. reported that the main information sources on vaccination for parents were the family physician, the Internet, and relatives. They also reported that looking for information only on the Internet was associated with poorer acceptance of the MMR vaccine [8]. However, associations between getting information from one’s relatives or from several information sources and vaccine practices have never been studied. We aimed to assess the use of various information sources on vaccination by parents of children aged 1–15 years living in metropolitan France. We also aimed to determine the relation between the use of such sources with: • declared practices for the MMR and HBV vaccines; • acceptance of vaccination; • vaccine hesitancy. Better understanding of such factors will guide promotional vaccine strategies and improve vaccination coverage.
2. Patients and methods 2.1. Health barometer The 2016 health barometer is a cross sectional phone survey based on two overlapping samples (two sampling frames were constituted for landlines and mobile phones; people owning both a landline and a mobile phone occurred in both sampling frames), and performed through random polling [9]. The survey was conducted during the first semester of 2016, with 15,216 people aged 15–75 years.
A large part of the questionnaire focused on vaccination. The aim was to obtain for the first time an estimate of vaccine hesitancy in France [10]. Questions on vaccine hesitancy and its determinants were asked to 3,938 parents of children aged 1-15 years. Vaccine information sources used by parents were assessed using the following open-ended question: “When wondering about a vaccine for your child, where do you look for information?”. Vaccine practices were assessed using the following questions: “Is your child vaccinated against HBV?” and “Is your child vaccinated against measles, mumps, and rubella? ”. Acceptance of vaccination was assessed with the following question: “Generally speaking, are you in favor of vaccination?” and vaccine hesitancy was assessed using a variable gathering answers to three questions: “Have you ever refused a vaccine for your child–that was recommended by his family physician–because you believed this vaccine to be dangerous or useless?”, “Have you ever decided to delay your child’s vaccination for a recommended vaccine because you were reluctant?”, and “Have you ever agreed to a vaccine for your child, even though you had doubts about its effectiveness?”. 2.2. Data analysis Answers to the question on information sources led to establishing three dichotomous variables through data clustering into three general types of sources: healthcare professionals and early childhood professionals, the Internet, and relatives. We also built a variable combining the three general types of sources identified and including eight categories (information from healthcare professionals alone; from the Internet alone; from relatives alone; from the Internet and relatives; from the Internet and healthcare professionals; from relatives and healthcare professionals; from the Internet, relatives, and healthcare professionals; none of the three sources of information). We first analyzed information sources, vaccination practices (MMR, HBV), vaccine acceptance and hesitancy depending on socio-demographic variables (sex, age, level of education, income by consumption unit defined by the OECD scale, management of the child by a physician practicing homeopathy or acupuncture, and living area). Comparisons were performed using Pearson’s Chi2 test. Two types of multivariate logistic regression models were then designed. The first model aimed to explain the use of the various types of information sources (healthcare professionals and early childhood professionals, the Internet, relatives, using at least three types of sources) and included the aforementioned sociodemographic variables as explicative variables. The second type of model aimed to explain the declared vaccine practices for the MMR and HBV vaccines, vaccine acceptance and hesitancy, and included sociodemographic variables and the combined use of sources of information as explicative variables to assess their joint effects. In these models, the reference category chosen for the variable “information sources” was getting information from healthcare professionals alone. Data was weighted to take into account probability of inclusion and was corrected for sex, age, living area, size of the urban area, level of education, and living on one’s own distributions (from
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Fig. 1. Vaccine information sources among parents of children aged 1-15 years (in percentage).
the 2014 employment survey published by INSEE). Analyses were performed using Stata software 13.1. 3. Results 3.1. Vaccine information sources When looking for vaccine information for their children, 83.6% of interviewed parents declared getting information from healthcare professionals or early childhood professionals, 37.4% from the Internet, and 20.1% from relatives (Fig. 1). Besides, 35.3% of parents declared using at least two of these three types of sources and 7.9% declared getting information on vaccination from these three types of sources. Use of these various information sources by parents varied by sociodemographic characteristics. Getting information from a healthcare professional was more frequent among women (adjusted odds ratio, aOR = 1.3; P < 0.05) and among people aged above 40 years (aOR = 1.5; P < 0.05). However, getting information from the Internet, from relatives, or from all these three types of information sources was more frequent among people aged below 30 years, people with a higher level of education, and people with the highest level of income (Table 1). Getting information from the Internet was also more frequent among parents living in a urban area of more than 100,000 inhabitants or in the Paris area. 3.2. Declared vaccine practices and information sources Vaccine practices (HBV and MMR) significantly varied by information sources (Table 2).
Overall, 94.6% of parents getting information from a healthcare professional, 84.9% of parents getting information from the Internet alone, and 83.5% of parents getting information from relatives alone declared that all their children were vaccinated against MMR (P < 0.001). The same percentage of parents getting information from healthcare professionals (47.1%) and from relatives alone (47.0%; NS) declared that their children were vaccinated against HBV. However, that figure is lower among parents getting information from the Internet alone (39.5%; P < 0.05). For both vaccines, when parents declared getting information from a healthcare professional and from relatives, vaccination practices were comparable to those of parents getting information from a healthcare professional alone. However, when combining the Internet and relatives, vaccination practices were lower − whether it be for the HBV vaccine (aOR = 0.6; P < 0.05) or for the MMR vaccine (aOR = 0.3; P < 0.01). Similarly, when combining all three types of information sources, vaccination practices declared by parents were significantly lower for the HBV (aOR = 0.6; P < 0.01) and MMR vaccines (aOR = 0.4; P < 0.001).
3.3. Vaccine acceptance and hesitancy, and information sources Even more than variables related to declared practices of some vaccines, variables assessing vaccine acceptance and hesitancy significantly varied by information sources (Table 3). Acceptance of vaccination as a whole was 82.8% when parents declared getting information from healthcare professionals alone versus 61.6% when looking on the Internet alone, and 62.4% when getting information from relatives alone (P < 0.001). Combining the various information sources was associated with different levels of
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Table 1 Sociodemographic factors associated with the use of vaccine information sources among parents of children aged 1-15 years. Caractéristiques sociodémographiques associées à l’utilisation de sources d’information chez les parents d’enfants de 1 à 15 ans.
Overall percentage Sex Male (ref.) Female Age 15/29 (ref.) 30/39 > 40 Level of education Lower than high school diploma (ref.) High school diploma or equivalent Higher than high school diploma Income/consumption unit (CU) (terciles)a 1st tercile (ref.) 2nd tercile 3rd tercile Don’t know/refusal Consulting a physician practicing homeopathy or acupuncture No (ref.) Yes Area of residence Rural (< 20000 inhabitants) 20,000 to 100,000 inhabitants More than 100,000 inhabitants Paris area * ** *** a
Healthcare and early childhood professionals
Internet
83.6
37.4
Relatives
20.0
Number
%
aOR
95% CI
%
aOR
95% CI
1656 2282
82.0 84.8
1 1.3*
[1.0-1.6]
38.3 36.7
1 0.9
[0.8-1.1]
281 1557 2100
80.3 82.7 84.9
1 1.2 1.5*
[0.8-1.8] [1.0-2.2]
1 0.7* 0.6**
[0.5-1.0] [0.5-0.9]
1048
84.6
1
42.9 38.7 35.3 *** 29.5
814
81.9
0.8
[0.6-1.1]
42.0
1.6***
2073
83.3
0.9
[0.7-1.2]
44.3
1.7***
83.1 85.4 80.9 90.5
1 1.3 0.9 1.9
[1.0-1.7] [0.7-1.2] [0.8-4.9]
3009 929
83.9 82.6
1 0.9
[0.7-1.2]
1242 1,107
85.0 84.9
1 1.0
988
82.2
601
81.6
7.9
%
aOR
95% CI
%
aOR
95% CI
19.6 20.3 * 26.3 20.2 18.6 *** 14.9
1 1.0
[0.8-1.2]
7.3 8.3
1 1.1
[0.8-1.6]
1 0.6** 0.5**
[0.4-0.8] [0.4-0.8]
11.8 7.4 7.5 *** 5.3
1 0.5** 0.5*
[0.3-0.8] [0.3-0.8]
[1.3-2.0]
20.1
1.3*
[1.0-1.8]
6.9
1.2
[0.8-1.9]
[1.4-2.1]
25.8
1.8***
[1.4-2.3]
11.4
2.0***
[1.4-2.9]
1
*** 1233 1616 1045 44
At least three types of information sources
1
***
1
***
32.5 38.2 47.2 18.8
1 1.1 1.4** 0.5*
[0.9-1.3] [1.1-1.8] [0.2-1.0]
16.5 20.3 27.2 10.5
1 1.1 1.4** 0.6
[0.8-1.4] [1.1-1.9] [0.2-1.9]
5.9 7.9 12.2 1.6
1 1.1 1.7** 0.3
[0.8-1.6] [1.1-2.4] [0.0-1.9]
1 1.1
[0.9-1.3]
19.9 20.3
1 1.0
[0.8-1.2]
7.7 8.4
1 1.1
[0.8-1.5]
[0.8-1.3]
36.7 39.7 * 34.3 35.3
1 1.1
[0.9-1.4]
19.2 18.7
1 1.0
[0.8-1.3]
7.6 6.8
1 0.9
[0.6-1.4]
0.8
[0.6-1.1]
38.9
1.3*
[1.0-1.5]
20.1
1.1
[0.8-1.3]
8.2
1.1
[0.8-1.5]
0.8
[0.6-1.1]
43.3
1.4**
[1.1-1.8]
23.4
1.2
[0.9-1.6]
9.6
1.1
[0.8-1.7]
P < 0.05. P < 0.01. P < 0.001. Terciles are cut off values allowing for splitting a variable distribution into three equal parts. The third tercile corresponds to the highest incomes.
acceptance: the lowest acceptance rate was observed among parents getting information from both the Internet and relatives (54.6%). Similar results were observed for vaccine hesitancy: rates were 70% when parents were getting information from the Internet and from relatives (aOR = 4.7, P < 0.001) or from the three sources of information (aOR = 4.7, P < 0.001); rates of vaccine hesitancy ranged from 50% to 60% when parents were getting information from the Internet or from relatives; a lower hesitancy rate was observed when parents were getting information from healthcare professionals alone (34.6%, P < 0.001). Other factors associated with higher hesitancy rates were being a woman (aOR = 1.5; P < 0.001), being aged above 40 years (aOR = 1.5; P < 0.05), high education level (aOR = 1.5; P < 0.001), and consulting a physician practicing acupuncture or homeopathy (aOR = 1.3; P < 0.01). These factors were associated with a hesitancy rate close to 50%. Conversely, living in a urban area of more than 100,000 inhabitants or in the Paris area was associated with a lower hesitancy rate. 4. Discussion Based on a large number of respondents (n = 3,938), the present study assessed the use and impact of various information sources on vaccination. To our knowledge this is the first study to assess the impact of the combined use of several information sources on vaccination attitudes and practices.
The main limitation of the study lies in the collection of data before the extension of mandatory vaccines on January 1, 2018 in France. Mandatory vaccination could indeed modify attitudes and practices related to the 11 mandatory vaccines, and could lower the relevance of our results, mainly for declared vaccination practices. However, the extension of mandatory vaccines may not modify the way people are getting informed on vaccination and may have little impact on factors associated with vaccine acceptance or hesitancy. It could be interesting to perform the same type of study with data collected after the application of the vaccine extension law to compare results and to confirm our hypothesis. Our results indicate that getting information from healthcare professionals is associated with better declared vaccine practices, better vaccine acceptance, and lower vaccine hesitancy rates. The vital role of family physicians–who are mentioned by the vast majority of parents as the reference healthcare professionals–is indeed largely documented in the vaccination decision process [11–13]. We should however moderate such observation as consulting a physician practicing homeopathy or acupuncture was in our study associated with a lower declared use of the MMR vaccine, a higher level of vaccine hesitancy, and a lower level of vaccine acceptance. This result is consistent with those of Verger et al. who observed the highest proportions of physicians practicing complementary medicine among the most reluctant physicians to vaccination [14]. Conversely, getting information from the Internet or relatives seemed to have a negative impact on declared vaccine
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Table 2 Factors associated with vaccine practices of parents of children aged 1-15 years for their children (MMR, HBV). Facteurs associés à la pratique déclarée de deux vaccins recommandés pour leurs enfants (ROR, VHB) chez les parents d’enfants de 1 à 15 ans.
Overall percentage Number Sex Male (ref.) Female Age 15/29 (ref.) 30/39 > 40 Level of education Lower than high school diploma (ref.) High school diploma or equivalent Higher than high school diploma Income/consumption unit (CU) (terciles)a 1st tercile (ref.) 2nd tercile 3rd tercile Don’t know/refusal Consulting a physician practicing homeopathy or acupuncture No (ref.) Yes Area of residence Rural (< 20,000 inhabitants) 20,000 to 100,000 inhabitants More than 100,000 inhabitants Paris area Vaccine information source Healthcare professionals alone (ref.) Internet alone Relatives alone Healthcare professionals and Internet Healthcare professionals and relatives Internet and relatives Healthcare professionals, Internet, and relatives None or other * ** *** a
All children vaccinated against MMR
All children vaccinated against HBV
91.3
44.8 aOR
95% CI
1 3.1***
[2.3-4.2]
281 1557 2100
% *** 87.0 94.6 ** 86.8 89.8 93.3
1 1.6 2.8***
[0.9-2.7] [1.6-4.7]
1048 814 2073
92.4 90.7 90.3
1 0.8 0.7
[0.6-1.3] [0.5-1.0]
1233 1616 1045 44
92.1 91.1 90.2 88.4 *** 92.2 88.0
1 1.1 1.2 0.5
[0.8-1.6] [0.8-1.8] [0.1-2.2]
1 0.6**
[0.5-0.9]
89.7 92.0 91.6 92.1 *** 94.6 84.9 83.5 89.4 93.0 84.8 86.7 83.8
1 1.3 1.3 1.4
[0.9-1.9] [0.9-1.9] [0.9-2.3]
1 0.3*** 0.3** 0.5*** 0.8 0.3** 0.4*** 0.3**
[0.2-0.6] [0.2-0.7] [0.3-0.7] [0.4-1.5] [0.2-0.6] [0.2-0.6] [0.1-0.7]
1656 2282
3009 929 1242 1107 988 601 1915 318 122 782 268 116 340 77
% *** 38.5 49.6 *** 56.7 46.9 40.8 * 46.9 44.9 42.1 ** 48.2 42.3 41.1 56.4
aOR
95% CI
1 1.5***
[1.3-1.8]
1 0.7* 0.6***
[0.5-1.0] [0.4-0.8]
1 0.9 0.9
[0.3-1.1] [0.7-1.1]
1 0.9 0.9 1.4
[0.7-1.1] [0.7-1.1] [0.6-2.9]
45.2 43.3 ** 40.3 44.0 46.1 50.9 * 47.1 39.5 47.0 45.3 45.0 37.1 36.4 31.3
1 0.9
[0.8-1.1]
1 1.1 1.3* 1.6**
[0.9-1.4] [1.0-1.6] [1.2-2.0]
1 0.7* 1.0 1.0 0.9 0.6* 0.6** 0.5*
[0.5-1.0] [0.6-1.5] [0.8-1.3] [0.6-1.2] [0.4-1.0] [0.5-0.8] [0.3-1.0]
P < 0.05. P < 0.01. P < 0.001. Terciles are cut off values allowing for splitting a variable distribution into three equal parts. The third tercile corresponds to the highest incomes.
practices, vaccine acceptance and hesitancy. The lowest results were observed among parents getting information both from the Internet and relatives. Such results are not much better when getting information also from healthcare professionals, i.e. from all three types of information sources. Getting information only from relatives was even associated with less favorable results than only looking for information online for the declared use of the MMR vaccine (83.5% versus 84.9%) or for vaccine hesitancy rate (59.5% versus 55.1%). Statistical associations between the respective roles of the Internet and relatives are worrying, but do not lead to establishing a causal link and to determining their meaning. One may assume that getting information from the Internet or from relatives leads to hearing more negative experiences on vaccination, thus influencing attitudes and practices. On the contrary, reluctant parents could prefer alternative sources of information that would provide them with information in line with their opinion. Ames et al. reported that parents find it difficult to assess whether a given source of information is trustworthy, and that their own attitudes towards vaccination influence their trust in such information sources [15]. Trust in the information source also influences the way parents are getting informed, perceive, understand, and assess the information. Information sources and attitudes towards vaccination might have mutual influence: reluctant people tend to get information from the Internet or relatives, and the information received strengthens their doubts.
Using two or three sources of information was most often associated with less favorable results in terms of practices and attitudes. Bults, Beaujan et al. had already observed during the H1N1 pandemic in the Netherlands that parents refusing vaccination for their child tended to more actively look for information [16]. These people are associated with a higher level of vaccine hesitancy. In our study we observed a higher rate of vaccine hesitancy among women than men (49.4% versus 40.8%). Paradoxically, women were more favorable to vaccination as a whole than men (77.5% versus 73.7%). This result could reflect the increased attention given to vaccine-related issues among mothers as they more often take care of their child’s health decisions than men [17]. The Internet is a difficult-to-comprehend information source because of its varied usage: institutional websites, anti-vaccine websites, online media, digital social networks, health blogs, youtube chains, etc. Numerous fake news are present online, especially in the field of health [18], and such news spread rapidly. Salathé demonstrated that anti-vaccine opinions more easily disseminated on digital social networks than pro-vaccine opinions [19]. The distinction between the Internet and relatives fades away with the use of social networks (Facebook, Twitter, Instagram, etc.). These networks are based on algorithms that select information likely to match the user’s interests based on their previous behaviors (likes, comments, friends with whom they interact the most, etc.).
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Table 3 Factors associated with vaccine acceptance and vaccine hesitancy in parents of children aged 1-15 years. Facteurs associés à l’adhésion et à l’hésitation vaccinale chez les parents d’enfants âgés de 1 à 15 ans.
Overall percentage Number Sex Male (ref.) Female Age 15/29 (ref.) 30/39 > 40 Level of education Lower than high school diploma (ref.) High school diploma or equivalent Higher than high school diploma Income/consumption unit (CU) (terciles)a 1st tercile (ref.) 2nd tercile 3rd tercile Don’t know/refusal Consulting a physician practicing homeopathy or acupuncture No (ref.) Yes Area of residence Rural (< 20,000 inhabitants) 20,000 to 100,000 inhabitants More than 100,000 inhabitants Paris area Information source on vaccination Healthcare professionals alone (ref.) Internet alone Relatives alone Healthcare professionals and Internet Healthcare professionals and relatives Internet and relatives Healthcare professionals, Internet, and relatives None or other * ** *** a
1656 2282 281 1557 2100 1048 814 2073 1233 1616 1045 44 3009 929 1242 1107 988 601 1915 318 122 782 268 116 340 77
Acceptance
Hesitancy
75.9
45.7
% * 73.7 77.5 ** 69.0 74.0 78.6 *** 74.6 71.1 79.7 * 73.2 75.8 81.3 77.4 ** 77.1 71.6
aOR
95% CI
1 1.3**
[1.1-1.6]
1 1.1 1.4
[0.7-1.6] [1.0-2.0]
1 0.9 1.3
[0.7-1.1] [1.0-1.6]
1 1.1 1.7*** 1.0
[0.9-1.5] [1.3-2.2] [0.4-2.9]
1 0.8*
[0.6-0.9]
75.7 75.0 76.1 77.2 *** 82.8 61.6 62.4 73.7 78.8 54.6 65.0 63.5
1 1.0 1.1 1.1
0.8-1.2 0.8-1.3 0.8-1.4
1 0.3*** 0.3*** 0.5*** 0.7 0.2*** 0.3*** 0.3**
[0.2-0.5] [0.2-0.5] [0.4-0.7] [0.5-1.1] [0.2-0.4] [0.2-0.5] [0.2-0.7]
% *** 40.8 49.4
aOR
95% CI
1 1.5***
[1.3-1.8]
43.1 44.2 47.3 *** 39.4 48.0 51.8
1 1.1 1.5*
[0.8-1.6] [1.1-2.1]
1 1.3* 1.5***
[1.0-1.6] [1.2-1.8]
44.1 47.1 47.3 32.5 ** 44.1 50.9
1 1.0 0.8 0.7
[0.8-1.2] [0.7-1.0] [0.4-1.5]
1 1.3**
[1.1-1.6]
49.5 44.6 44.1 44.3 *** 34.6 55.1 59.5 52.2 54.1 70.6 70.9 47.7
1 0.8 0.8* 0.7**
0.7-1.0 0.6-0.9 0.5-0.9
1 2.5*** 3.0*** 2.1*** 2.2*** 4.7*** 4.7*** 1.9
[1.8-3.3] [1.9-4.7] [1.7-2.6] [1.6-3.1] [2.9-7.7] [3.4-6.4] [0.9-3.7]
P < 0.05. P < 0.01. P < 0.001 Terciles are cut off values allowing for splitting a variable distribution into three equal parts. The third tercile corresponds to the highest incomes.
Such selection mechanisms lead to resonance chamber and filter bubble phenomena [20]: the user lives in a bubble where he is no longer exposed to dissenting opinions and where only opinions similar to his are presented. This “closed” environment acts as a resonance chamber for the user as his own opinions are reinforced and amplified. Such phenomena may add up and reinforce vaccine hesitancy feelings in already reluctant individuals or in people already opposed to vaccination. This could explain the observed results. The negative link observed between information found on the Internet and vaccine hesitancy strengthens the desire of public authorities to be present on the Internet when it comes to vaccination issues. As demonstrated by J.P. Stahl et al., although the Internet may be where fake information is disseminated and where polemics are sparked on vaccination, it may also provide new tools and means to fight against vaccine hesitancy [21]. Various initiatives have already been developed such as the production of two videos on vaccination produced by health youtubers as part of a partnership with the ministry for health [22] (300,000 and 500,000 views approximately in June 2018) or the creation of the “vaccination-info-service.fr” website by the French national agency for public health (Santé publique France) [23]. This website aims to become the reference on vaccination. Its referencing on search engines is favorable (more than 4 million connections the first year–Santé Publique France data). The present study is the first to assess the association between getting vaccine information from relatives and vaccination practices and attitudes in France. Just like for the Internet, the
association seems to be negative and is even more worrying that young people rather turn to their relatives to obtain information (26.3% of people aged below 30 years seek information from relatives versus 18.6% of people aged above 40 years). The role of relatives is complex. Besides their informative role, relatives may have social influence, defined as modifications of the perception, attitudes, or behavior of an individual after hearing other people’s perception, attitudes, and behaviors. Conformism is thus translated into the individual adopting the general opinion of a given group. Brunson et al. have for instance demonstrated that having relatives recommending non-compliance with vaccination (incomplete vaccinations, late vaccination, or no vaccination at all) was significantly associated with non-compliance with the vaccination calendar [24]. Social psychology and the network theory could shed additional light on the dissemination of anti-vaccine feelings among the population. Onnela et al. thus demonstrated that in Malegaon, India, households opposed to vaccination were socially and geographically connected. They formed clusters or pockets of resistance to vaccination [25]. Better knowledge of the socio-spatial distribution of vaccine hesitancy could lead to more targeted interventions to promote vaccination. The multiple-target strategies of vaccination campaigns also seem to be adapted considering the influence of relatives when it comes to vaccination. Such strategies rely on opinion leadership such as the grandparents or healthcare professionals and early childhood professionals.
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Family physicians play a crucial role, as they are the ones to perform vaccination, to check that their patients’ status is up to date, and to explain the role of vaccine in protecting from infectious diseases. Family physicians are indeed the first source of information for parents when it comes to vaccination, and 95.3% of parents trust their family physician [8]. Access to family physicians is however not homogeneous in France and can be limited in specific areas where medical density is lower (e.g., specific rural areas or underprivileged neighborhoods). One of the limitations of the study lies in the non-consideration of difficulties in having access to a family physician as a potential confounding factor. However, we observed in our study that living in large cities (> 100,000 inhabitants or Paris area) was associated with a more extensive use of the Internet, better vaccination practices, and lower vaccine hesitancy rates. 5. Conclusion Our study demonstrates the association between looking for vaccine information on the Internet and, for the very first time, from relatives and low levels of vaccination practice and acceptance. Initiatives such as the creation of the “vaccination-info-service.fr” website should therefore be continued, and their impact and use should be assessed, mainly among vaccine-hesitant people. Assistance and education should also be provided to people looking for reliable health-related information on the Internet. Authors’ contributions JC performed the literature analysis and statistical analysis, and wrote the article. CJ supervised the work and contributed to reviewing the article. AG provided the data, supervised the statistical analysis, and contributed to reviewing the article. Disclosure of interest The authors declare that they have no competing interest. References [1] OMS | Vaccination [Internet]. WHO. Available from: http://www.who. int/topics/immunization/fr/. Accessed on Mars 6, 2019. [2] Wolfe RM, Sharp LK. Anti-vaccinationists past and present. BMJ. Br Med J 2002;7361(8):430–2. [3] WHO SAGE. Vaccine Hesitancy Working Group report [Internet]; 2014 [Available from: https://www.who.int/immunization/sage/meetings/2014/october/ SAGE working group revised report vaccine hesitancy.pdf?ua=1. Accessed on July 18, 2019]. [4] Perception et adhésion à la vaccination en France [Internet]. Available from: https://professionnels.vaccination-info-service.fr/Aspects-sociologiques/ Perception-et-adhesion-a-la-vaccination/Perception-et-adhesion-a-lavaccination-en-France. Accessed on Mars 6, 2019 [Published on the 29.03.2018; updated on the 02.05.2018].
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[5] Dube E, Laberge C, Guay M, Bramadat P, Roy R, Bettinger J. Vaccine hesitancy: an overview. Hum Vaccines Immunother 2013;9(8):1763–73. [6] Larson HJ, Jarrett C, Eckersberger E, Smith DMD, Paterson P. Understanding vaccine hesitancy around vaccines and vaccination from a global perspective: a systematic review of published literature, 2007-2012. Vaccine 2014;32(19):2150–9. [7] Smith LE, Amlot R, Weinman J, Yiend J, Rubin GJ. A systematic review of factors affecting vaccine uptake in young children. Vaccine 2017;35(45):6059–69. [8] Gautier A, Verger P, Jestin C. Sources d’information, opinions et pratiques des parents en matière de vaccination en France en 2016. Vaccination des jeunes enfants: des données pour mieux comprendre l’action publique. Bull Epidemiol Hebd 2017:28–35. [9] Richard J, Gautier A. G R, L C, B F. Méthode d’enquête du Baromètre santé; 2014. p. 26. [10] Rey D, Fressard L, Cortaredona S, Bocquier A, Gautier A, Peretti-Watel P, et al. Vaccine hesitancy in the French population in 2016, and its association with vaccine uptake and perceived vaccine risk-benefit balance. Euro Surveill Bull Eur Sur Mal Transm Eur Commun Dis Bull 2018;23(17). [11] Gust DA, Darling N, Kennedy A, Schwartz B. Parents with doubts about vaccines: which vaccines and reasons why. Pediatrics 2018;4:718–25. [12] Gust DA, Kennedy A, Shui I, Smith PJ, Nowak G, Pickering LK. Parent attitudes toward immunizations and healthcare providers the role of information. Am J Prev Med 2005;29(2):105–12. [13] Mergler MJ, Omer SB, Pan WKY, Navar-Boggan AM, Orenstein W, Marcuse EK, et al. Association of vaccine-related attitudes and beliefs between parents and health care providers. Vaccine 2013;31(41):4591–5. [14] Verger P, Collange F, Fressard L, Bocquier A, Gautier A, Pulcini C, et al. Prevalence and correlates of vaccine hesitancy among general practitioners: a crosssectional telephone survey in France, April to July 2014. Euro Surveill Bull Eur Sur Mal Transm Eur Commun Dis Bull 2016;21(47). [15] Ames HM, Glenton C, Lewin S. Parents’ and informal caregivers’ views and experiences of communication about routine childhood vaccination: a synthesis of qualitative evidence. Cochrane Database Syst Rev 2017;2:CD011787. [16] Bults M, Beaujean DJMA, Richardus JH, van Steenbergen JE, Voeten HACM. Pandemic influenza A (H1N1) vaccination in The Netherlands: parental reasoning underlying child vaccination choices. Vaccine 2011;29(37):6226–35. [17] Cresson G, La production familiale de soins et de santé. La prise en compte tardive et inachevée d’une participation essentielle. Rech Fam 2006;(1):6–15. [18] Sushis, vaccins et viande humaine: le « palmarès » des fausses infos, 2017. Available from: https://www.lemonde.fr/le-blog-du-decodex/ article/2017/09/08/sushis-vaccins-et-viande-humaine-le-palmares-desfausses-infos 5182743 5095029.html. Accessed on Mars 6, 2019. [19] Salathé M, Vu DQ, Khandelwal S, Hunter DR. The dynamics of health behavior sentiments on a large online social network. EPJ Data Sci 2013;2(1):4. [20] Pariser E. The Filter Bubble: What The Internet Is Hiding From You. Penguin Books Limited; 2011. [21] Stahl J-P, Cohen R, Denis F, Gaudelus J, Martinot A, Lery T, et al. The impact of the web and social networks on vaccination. New challenges and opportunities offered to fight against vaccine hesitancy. Médecine Mal Infect 2016;46(3):117–22. London, UK. [22] DICOM, Jocelyne M. 11 vaccins obligatoires: des vidéos YouTube pour tout comprendre [Internet]. Ministère des Solidarités et de la Santé; 2019 [Available https://solidarites-sante.gouv.fr/actualites/presse/communiques-defrom: presse/article/11-vaccins-obligatoires-des-videos-youtube-pour-toutcomprendre. Accessed on Mars 6, 2019]. [23] Accueil [Internet]. Available from: https://vaccination-info-service.fr/. Accessed on Mars 6, 2019. [24] Brunson EK. The Impact of Social Networks on Parents. Vaccin Decis Pediatr 2013:131. [25] Onnela J-P, Landon BE, Kahn A-L, Ahmed D, Verma H, O’Malley AJ, et al. Polio vaccine hesitancy in the networks and neighborhoods of Malegaon, India. Soc Sci Med 1982 2016;153:99–106.
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Original article
Influence of information sources on vaccine hesitancy and practices夽 Influence des sources d’information sur l’hésitation vaccinale et les pratiques vaccinales Jalal Charron ∗ , Arnaud Gautier , Christine Jestin Santé Publique France, 12, rue du Val d’Osne, 94410 Saint-Maurice, France
a r t i c l e
i n f o
Article history: Received 5 May 2019 Received in revised form 30 August 2019 Accepted 28 January 2020 Available online xxx Keywords: Vaccine hesitancy Social networks Vaccines Internet
a b s t r a c t Introduction. – Many factors influence vaccination practices and attitudes. This study aimed to identify vaccine information sources used by parents of children aged 1–15 years to get a better understanding of the relation between vaccine information sources, practices for two vaccines (MMR, HBV), vaccine acceptance, and vaccine hesitancy. Methods. – A total of 3938 parents, drawn by random sampling, were interviewed by telephone as part of the “2016 health barometer” survey. Vaccine information sources were described and analyzed according to socio-demographic variables. Multivariate logistic regression models were then built to explain vaccine information sources usage, vaccination practices and attitudes. Results. – Healthcare professionals (HCP), the Internet, and relatives were the three main vaccine information sources. Vaccination practices and acceptance were better when parents were getting information from HCPs compared with parents getting information from the Internet or relatives. Besides, getting information from the three different types of sources was associated with the highest rate of vaccine hesitancy: 70.9% (OR = 4.6; P < 0.0001) versus 34.6% among parents getting information from HCPs only. Conclusion. – Those results suggest an interest in providing quality information about vaccination on the Internet. The primary role of HCPs in vaccination decision is once again demonstrated. © 2020 Elsevier Masson SAS. All rights reserved.
r é s u m é Mots clés : Hésitation vaccinale Vaccins Réseaux sociaux Internet
Objectifs. – Les attitudes et pratiques vaccinales sont des processus complexes influencés par de nombreux facteurs. L’objectif de cette étude était d’identifier le recours à différentes sources d’information sur la vaccination chez les parents d’enfants de 1 à 15 ans afin de mieux comprendre les liens entre sources d’information, pratiques vaccinales déclarées pour deux vaccinations (ROR, VHB), adhésion et hésitation vaccinales. Patients et méthodes. – Un échantillon de 3938 parents d’enfants de 1 à 15 ans, construit par sondage aléatoire, a été interrogé par téléphone dans le cadre de l’enquête Baromètre Santé 2016. Dans un premier temps, les sources d’information ont été décrites et analysées selon différentes variables sociodémographiques. Dans un second temps, des modèles multivariés de régression logistique visant à expliquer l’usage des différentes sources, les pratiques vaccinales, l’adhésion et l’hésitation ont été construits. Résultats. – Les trois sources d’information principales chez les parents étaient les professionnels de santé, internet et l’entourage. Les pratiques (ROR, VHB) et l’adhésion à la vaccination étaient meilleures chez les parents qui s’informent chez un professionnel comparé à ceux qui s’informent sur internet ou auprès de leur entourage. Par ailleurs, le fait d’associer les trois types de sources étaient associé à l’hésitation la plus élevée: 70,9 % (OR = 4,6; p < 0,0001) contre 34,6 % chez ceux s’informant uniquement auprès de professionnels.
夽 The present work was presented at the 2018 Rencontres de Santé publique France. ∗ Corresponding author. E-mail address: [email protected] (J. Charron). https://doi.org/10.1016/j.medmal.2020.01.010 0399-077X/© 2020 Elsevier Masson SAS. All rights reserved.
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Conclusions. – Il existe un intérêt à apporter des informations de qualité sur la vaccination sur internet. Par ailleurs, le rôle primordial des professionnels de santé dans la décision vaccinale est une nouvelle fois souligné. ´ ´ © 2020 Elsevier Masson SAS. Tous droits reserv es.
1. Objectives Vaccination is one of the most efficient public health measures. According to the World Health Organization (WHO), vaccination prevents the death of two to three million individuals every year [1]. However, vaccination programs have always raised concerns and opposition among some population groups [2]. Mistrust in vaccination has become more evident over the past years in many countries. It may take the form of vaccine hesitancy, which is defined by the SAGE working group of the WHO as the delay in acceptance or refusal of vaccines despite availability of vaccination services [3]. Vaccination against H1N1 influenza sparked a polemic in France in 2009, which was largely covered by the media and social networks. This polemic highly contributed to reinforcing such hesitancy as vaccine acceptance declined from 90% in 2005 to 61% in 2010 among people aged 18-75 years living in metropolitan France [4]. Vaccine acceptance among the general population is a major challenge, as poor acceptance leads to suboptimal vaccine coverage and to the circulation of diseases that could be prevented. Vaccine acceptance is particularly important among parents. They are confronted with vaccination choices for their children, of which they must assess the determinants. Acceptance, hesitancy, and vaccination practices are indeed complex processes influenced by numerous factors [5–7], such as the level of knowledge and information on vaccination. Gautier et al. reported that the main information sources on vaccination for parents were the family physician, the Internet, and relatives. They also reported that looking for information only on the Internet was associated with poorer acceptance of the MMR vaccine [8]. However, associations between getting information from one’s relatives or from several information sources and vaccine practices have never been studied. We aimed to assess the use of various information sources on vaccination by parents of children aged 1–15 years living in metropolitan France. We also aimed to determine the relation between the use of such sources with: • declared practices for the MMR and HBV vaccines; • acceptance of vaccination; • vaccine hesitancy. Better understanding of such factors will guide promotional vaccine strategies and improve vaccination coverage.
2. Patients and methods 2.1. Health barometer The 2016 health barometer is a cross sectional phone survey based on two overlapping samples (two sampling frames were constituted for landlines and mobile phones; people owning both a landline and a mobile phone occurred in both sampling frames), and performed through random polling [9]. The survey was conducted during the first semester of 2016, with 15,216 people aged 15–75 years.
A large part of the questionnaire focused on vaccination. The aim was to obtain for the first time an estimate of vaccine hesitancy in France [10]. Questions on vaccine hesitancy and its determinants were asked to 3,938 parents of children aged 1-15 years. Vaccine information sources used by parents were assessed using the following open-ended question: “When wondering about a vaccine for your child, where do you look for information?”. Vaccine practices were assessed using the following questions: “Is your child vaccinated against HBV?” and “Is your child vaccinated against measles, mumps, and rubella? ”. Acceptance of vaccination was assessed with the following question: “Generally speaking, are you in favor of vaccination?” and vaccine hesitancy was assessed using a variable gathering answers to three questions: “Have you ever refused a vaccine for your child–that was recommended by his family physician–because you believed this vaccine to be dangerous or useless?”, “Have you ever decided to delay your child’s vaccination for a recommended vaccine because you were reluctant?”, and “Have you ever agreed to a vaccine for your child, even though you had doubts about its effectiveness?”. 2.2. Data analysis Answers to the question on information sources led to establishing three dichotomous variables through data clustering into three general types of sources: healthcare professionals and early childhood professionals, the Internet, and relatives. We also built a variable combining the three general types of sources identified and including eight categories (information from healthcare professionals alone; from the Internet alone; from relatives alone; from the Internet and relatives; from the Internet and healthcare professionals; from relatives and healthcare professionals; from the Internet, relatives, and healthcare professionals; none of the three sources of information). We first analyzed information sources, vaccination practices (MMR, HBV), vaccine acceptance and hesitancy depending on socio-demographic variables (sex, age, level of education, income by consumption unit defined by the OECD scale, management of the child by a physician practicing homeopathy or acupuncture, and living area). Comparisons were performed using Pearson’s Chi2 test. Two types of multivariate logistic regression models were then designed. The first model aimed to explain the use of the various types of information sources (healthcare professionals and early childhood professionals, the Internet, relatives, using at least three types of sources) and included the aforementioned sociodemographic variables as explicative variables. The second type of model aimed to explain the declared vaccine practices for the MMR and HBV vaccines, vaccine acceptance and hesitancy, and included sociodemographic variables and the combined use of sources of information as explicative variables to assess their joint effects. In these models, the reference category chosen for the variable “information sources” was getting information from healthcare professionals alone. Data was weighted to take into account probability of inclusion and was corrected for sex, age, living area, size of the urban area, level of education, and living on one’s own distributions (from
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Fig. 1. Vaccine information sources among parents of children aged 1-15 years (in percentage).
the 2014 employment survey published by INSEE). Analyses were performed using Stata software 13.1. 3. Results 3.1. Vaccine information sources When looking for vaccine information for their children, 83.6% of interviewed parents declared getting information from healthcare professionals or early childhood professionals, 37.4% from the Internet, and 20.1% from relatives (Fig. 1). Besides, 35.3% of parents declared using at least two of these three types of sources and 7.9% declared getting information on vaccination from these three types of sources. Use of these various information sources by parents varied by sociodemographic characteristics. Getting information from a healthcare professional was more frequent among women (adjusted odds ratio, aOR = 1.3; P < 0.05) and among people aged above 40 years (aOR = 1.5; P < 0.05). However, getting information from the Internet, from relatives, or from all these three types of information sources was more frequent among people aged below 30 years, people with a higher level of education, and people with the highest level of income (Table 1). Getting information from the Internet was also more frequent among parents living in a urban area of more than 100,000 inhabitants or in the Paris area. 3.2. Declared vaccine practices and information sources Vaccine practices (HBV and MMR) significantly varied by information sources (Table 2).
Overall, 94.6% of parents getting information from a healthcare professional, 84.9% of parents getting information from the Internet alone, and 83.5% of parents getting information from relatives alone declared that all their children were vaccinated against MMR (P < 0.001). The same percentage of parents getting information from healthcare professionals (47.1%) and from relatives alone (47.0%; NS) declared that their children were vaccinated against HBV. However, that figure is lower among parents getting information from the Internet alone (39.5%; P < 0.05). For both vaccines, when parents declared getting information from a healthcare professional and from relatives, vaccination practices were comparable to those of parents getting information from a healthcare professional alone. However, when combining the Internet and relatives, vaccination practices were lower − whether it be for the HBV vaccine (aOR = 0.6; P < 0.05) or for the MMR vaccine (aOR = 0.3; P < 0.01). Similarly, when combining all three types of information sources, vaccination practices declared by parents were significantly lower for the HBV (aOR = 0.6; P < 0.01) and MMR vaccines (aOR = 0.4; P < 0.001).
3.3. Vaccine acceptance and hesitancy, and information sources Even more than variables related to declared practices of some vaccines, variables assessing vaccine acceptance and hesitancy significantly varied by information sources (Table 3). Acceptance of vaccination as a whole was 82.8% when parents declared getting information from healthcare professionals alone versus 61.6% when looking on the Internet alone, and 62.4% when getting information from relatives alone (P < 0.001). Combining the various information sources was associated with different levels of
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Table 1 Sociodemographic factors associated with the use of vaccine information sources among parents of children aged 1-15 years. Caractéristiques sociodémographiques associées à l’utilisation de sources d’information chez les parents d’enfants de 1 à 15 ans.
Overall percentage Sex Male (ref.) Female Age 15/29 (ref.) 30/39 > 40 Level of education Lower than high school diploma (ref.) High school diploma or equivalent Higher than high school diploma Income/consumption unit (CU) (terciles)a 1st tercile (ref.) 2nd tercile 3rd tercile Don’t know/refusal Consulting a physician practicing homeopathy or acupuncture No (ref.) Yes Area of residence Rural (< 20000 inhabitants) 20,000 to 100,000 inhabitants More than 100,000 inhabitants Paris area * ** *** a
Healthcare and early childhood professionals
Internet
83.6
37.4
Relatives
20.0
Number
%
aOR
95% CI
%
aOR
95% CI
1656 2282
82.0 84.8
1 1.3*
[1.0-1.6]
38.3 36.7
1 0.9
[0.8-1.1]
281 1557 2100
80.3 82.7 84.9
1 1.2 1.5*
[0.8-1.8] [1.0-2.2]
1 0.7* 0.6**
[0.5-1.0] [0.5-0.9]
1048
84.6
1
42.9 38.7 35.3 *** 29.5
814
81.9
0.8
[0.6-1.1]
42.0
1.6***
2073
83.3
0.9
[0.7-1.2]
44.3
1.7***
83.1 85.4 80.9 90.5
1 1.3 0.9 1.9
[1.0-1.7] [0.7-1.2] [0.8-4.9]
3009 929
83.9 82.6
1 0.9
[0.7-1.2]
1242 1,107
85.0 84.9
1 1.0
988
82.2
601
81.6
7.9
%
aOR
95% CI
%
aOR
95% CI
19.6 20.3 * 26.3 20.2 18.6 *** 14.9
1 1.0
[0.8-1.2]
7.3 8.3
1 1.1
[0.8-1.6]
1 0.6** 0.5**
[0.4-0.8] [0.4-0.8]
11.8 7.4 7.5 *** 5.3
1 0.5** 0.5*
[0.3-0.8] [0.3-0.8]
[1.3-2.0]
20.1
1.3*
[1.0-1.8]
6.9
1.2
[0.8-1.9]
[1.4-2.1]
25.8
1.8***
[1.4-2.3]
11.4
2.0***
[1.4-2.9]
1
*** 1233 1616 1045 44
At least three types of information sources
1
***
1
***
32.5 38.2 47.2 18.8
1 1.1 1.4** 0.5*
[0.9-1.3] [1.1-1.8] [0.2-1.0]
16.5 20.3 27.2 10.5
1 1.1 1.4** 0.6
[0.8-1.4] [1.1-1.9] [0.2-1.9]
5.9 7.9 12.2 1.6
1 1.1 1.7** 0.3
[0.8-1.6] [1.1-2.4] [0.0-1.9]
1 1.1
[0.9-1.3]
19.9 20.3
1 1.0
[0.8-1.2]
7.7 8.4
1 1.1
[0.8-1.5]
[0.8-1.3]
36.7 39.7 * 34.3 35.3
1 1.1
[0.9-1.4]
19.2 18.7
1 1.0
[0.8-1.3]
7.6 6.8
1 0.9
[0.6-1.4]
0.8
[0.6-1.1]
38.9
1.3*
[1.0-1.5]
20.1
1.1
[0.8-1.3]
8.2
1.1
[0.8-1.5]
0.8
[0.6-1.1]
43.3
1.4**
[1.1-1.8]
23.4
1.2
[0.9-1.6]
9.6
1.1
[0.8-1.7]
P < 0.05. P < 0.01. P < 0.001. Terciles are cut off values allowing for splitting a variable distribution into three equal parts. The third tercile corresponds to the highest incomes.
acceptance: the lowest acceptance rate was observed among parents getting information from both the Internet and relatives (54.6%). Similar results were observed for vaccine hesitancy: rates were 70% when parents were getting information from the Internet and from relatives (aOR = 4.7, P < 0.001) or from the three sources of information (aOR = 4.7, P < 0.001); rates of vaccine hesitancy ranged from 50% to 60% when parents were getting information from the Internet or from relatives; a lower hesitancy rate was observed when parents were getting information from healthcare professionals alone (34.6%, P < 0.001). Other factors associated with higher hesitancy rates were being a woman (aOR = 1.5; P < 0.001), being aged above 40 years (aOR = 1.5; P < 0.05), high education level (aOR = 1.5; P < 0.001), and consulting a physician practicing acupuncture or homeopathy (aOR = 1.3; P < 0.01). These factors were associated with a hesitancy rate close to 50%. Conversely, living in a urban area of more than 100,000 inhabitants or in the Paris area was associated with a lower hesitancy rate. 4. Discussion Based on a large number of respondents (n = 3,938), the present study assessed the use and impact of various information sources on vaccination. To our knowledge this is the first study to assess the impact of the combined use of several information sources on vaccination attitudes and practices.
The main limitation of the study lies in the collection of data before the extension of mandatory vaccines on January 1, 2018 in France. Mandatory vaccination could indeed modify attitudes and practices related to the 11 mandatory vaccines, and could lower the relevance of our results, mainly for declared vaccination practices. However, the extension of mandatory vaccines may not modify the way people are getting informed on vaccination and may have little impact on factors associated with vaccine acceptance or hesitancy. It could be interesting to perform the same type of study with data collected after the application of the vaccine extension law to compare results and to confirm our hypothesis. Our results indicate that getting information from healthcare professionals is associated with better declared vaccine practices, better vaccine acceptance, and lower vaccine hesitancy rates. The vital role of family physicians–who are mentioned by the vast majority of parents as the reference healthcare professionals–is indeed largely documented in the vaccination decision process [11–13]. We should however moderate such observation as consulting a physician practicing homeopathy or acupuncture was in our study associated with a lower declared use of the MMR vaccine, a higher level of vaccine hesitancy, and a lower level of vaccine acceptance. This result is consistent with those of Verger et al. who observed the highest proportions of physicians practicing complementary medicine among the most reluctant physicians to vaccination [14]. Conversely, getting information from the Internet or relatives seemed to have a negative impact on declared vaccine
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Table 2 Factors associated with vaccine practices of parents of children aged 1-15 years for their children (MMR, HBV). Facteurs associés à la pratique déclarée de deux vaccins recommandés pour leurs enfants (ROR, VHB) chez les parents d’enfants de 1 à 15 ans.
Overall percentage Number Sex Male (ref.) Female Age 15/29 (ref.) 30/39 > 40 Level of education Lower than high school diploma (ref.) High school diploma or equivalent Higher than high school diploma Income/consumption unit (CU) (terciles)a 1st tercile (ref.) 2nd tercile 3rd tercile Don’t know/refusal Consulting a physician practicing homeopathy or acupuncture No (ref.) Yes Area of residence Rural (< 20,000 inhabitants) 20,000 to 100,000 inhabitants More than 100,000 inhabitants Paris area Vaccine information source Healthcare professionals alone (ref.) Internet alone Relatives alone Healthcare professionals and Internet Healthcare professionals and relatives Internet and relatives Healthcare professionals, Internet, and relatives None or other * ** *** a
All children vaccinated against MMR
All children vaccinated against HBV
91.3
44.8 aOR
95% CI
1 3.1***
[2.3-4.2]
281 1557 2100
% *** 87.0 94.6 ** 86.8 89.8 93.3
1 1.6 2.8***
[0.9-2.7] [1.6-4.7]
1048 814 2073
92.4 90.7 90.3
1 0.8 0.7
[0.6-1.3] [0.5-1.0]
1233 1616 1045 44
92.1 91.1 90.2 88.4 *** 92.2 88.0
1 1.1 1.2 0.5
[0.8-1.6] [0.8-1.8] [0.1-2.2]
1 0.6**
[0.5-0.9]
89.7 92.0 91.6 92.1 *** 94.6 84.9 83.5 89.4 93.0 84.8 86.7 83.8
1 1.3 1.3 1.4
[0.9-1.9] [0.9-1.9] [0.9-2.3]
1 0.3*** 0.3** 0.5*** 0.8 0.3** 0.4*** 0.3**
[0.2-0.6] [0.2-0.7] [0.3-0.7] [0.4-1.5] [0.2-0.6] [0.2-0.6] [0.1-0.7]
1656 2282
3009 929 1242 1107 988 601 1915 318 122 782 268 116 340 77
% *** 38.5 49.6 *** 56.7 46.9 40.8 * 46.9 44.9 42.1 ** 48.2 42.3 41.1 56.4
aOR
95% CI
1 1.5***
[1.3-1.8]
1 0.7* 0.6***
[0.5-1.0] [0.4-0.8]
1 0.9 0.9
[0.3-1.1] [0.7-1.1]
1 0.9 0.9 1.4
[0.7-1.1] [0.7-1.1] [0.6-2.9]
45.2 43.3 ** 40.3 44.0 46.1 50.9 * 47.1 39.5 47.0 45.3 45.0 37.1 36.4 31.3
1 0.9
[0.8-1.1]
1 1.1 1.3* 1.6**
[0.9-1.4] [1.0-1.6] [1.2-2.0]
1 0.7* 1.0 1.0 0.9 0.6* 0.6** 0.5*
[0.5-1.0] [0.6-1.5] [0.8-1.3] [0.6-1.2] [0.4-1.0] [0.5-0.8] [0.3-1.0]
P < 0.05. P < 0.01. P < 0.001. Terciles are cut off values allowing for splitting a variable distribution into three equal parts. The third tercile corresponds to the highest incomes.
practices, vaccine acceptance and hesitancy. The lowest results were observed among parents getting information both from the Internet and relatives. Such results are not much better when getting information also from healthcare professionals, i.e. from all three types of information sources. Getting information only from relatives was even associated with less favorable results than only looking for information online for the declared use of the MMR vaccine (83.5% versus 84.9%) or for vaccine hesitancy rate (59.5% versus 55.1%). Statistical associations between the respective roles of the Internet and relatives are worrying, but do not lead to establishing a causal link and to determining their meaning. One may assume that getting information from the Internet or from relatives leads to hearing more negative experiences on vaccination, thus influencing attitudes and practices. On the contrary, reluctant parents could prefer alternative sources of information that would provide them with information in line with their opinion. Ames et al. reported that parents find it difficult to assess whether a given source of information is trustworthy, and that their own attitudes towards vaccination influence their trust in such information sources [15]. Trust in the information source also influences the way parents are getting informed, perceive, understand, and assess the information. Information sources and attitudes towards vaccination might have mutual influence: reluctant people tend to get information from the Internet or relatives, and the information received strengthens their doubts.
Using two or three sources of information was most often associated with less favorable results in terms of practices and attitudes. Bults, Beaujan et al. had already observed during the H1N1 pandemic in the Netherlands that parents refusing vaccination for their child tended to more actively look for information [16]. These people are associated with a higher level of vaccine hesitancy. In our study we observed a higher rate of vaccine hesitancy among women than men (49.4% versus 40.8%). Paradoxically, women were more favorable to vaccination as a whole than men (77.5% versus 73.7%). This result could reflect the increased attention given to vaccine-related issues among mothers as they more often take care of their child’s health decisions than men [17]. The Internet is a difficult-to-comprehend information source because of its varied usage: institutional websites, anti-vaccine websites, online media, digital social networks, health blogs, youtube chains, etc. Numerous fake news are present online, especially in the field of health [18], and such news spread rapidly. Salathé demonstrated that anti-vaccine opinions more easily disseminated on digital social networks than pro-vaccine opinions [19]. The distinction between the Internet and relatives fades away with the use of social networks (Facebook, Twitter, Instagram, etc.). These networks are based on algorithms that select information likely to match the user’s interests based on their previous behaviors (likes, comments, friends with whom they interact the most, etc.).
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Table 3 Factors associated with vaccine acceptance and vaccine hesitancy in parents of children aged 1-15 years. Facteurs associés à l’adhésion et à l’hésitation vaccinale chez les parents d’enfants âgés de 1 à 15 ans.
Overall percentage Number Sex Male (ref.) Female Age 15/29 (ref.) 30/39 > 40 Level of education Lower than high school diploma (ref.) High school diploma or equivalent Higher than high school diploma Income/consumption unit (CU) (terciles)a 1st tercile (ref.) 2nd tercile 3rd tercile Don’t know/refusal Consulting a physician practicing homeopathy or acupuncture No (ref.) Yes Area of residence Rural (< 20,000 inhabitants) 20,000 to 100,000 inhabitants More than 100,000 inhabitants Paris area Information source on vaccination Healthcare professionals alone (ref.) Internet alone Relatives alone Healthcare professionals and Internet Healthcare professionals and relatives Internet and relatives Healthcare professionals, Internet, and relatives None or other * ** *** a
1656 2282 281 1557 2100 1048 814 2073 1233 1616 1045 44 3009 929 1242 1107 988 601 1915 318 122 782 268 116 340 77
Acceptance
Hesitancy
75.9
45.7
% * 73.7 77.5 ** 69.0 74.0 78.6 *** 74.6 71.1 79.7 * 73.2 75.8 81.3 77.4 ** 77.1 71.6
aOR
95% CI
1 1.3**
[1.1-1.6]
1 1.1 1.4
[0.7-1.6] [1.0-2.0]
1 0.9 1.3
[0.7-1.1] [1.0-1.6]
1 1.1 1.7*** 1.0
[0.9-1.5] [1.3-2.2] [0.4-2.9]
1 0.8*
[0.6-0.9]
75.7 75.0 76.1 77.2 *** 82.8 61.6 62.4 73.7 78.8 54.6 65.0 63.5
1 1.0 1.1 1.1
0.8-1.2 0.8-1.3 0.8-1.4
1 0.3*** 0.3*** 0.5*** 0.7 0.2*** 0.3*** 0.3**
[0.2-0.5] [0.2-0.5] [0.4-0.7] [0.5-1.1] [0.2-0.4] [0.2-0.5] [0.2-0.7]
% *** 40.8 49.4
aOR
95% CI
1 1.5***
[1.3-1.8]
43.1 44.2 47.3 *** 39.4 48.0 51.8
1 1.1 1.5*
[0.8-1.6] [1.1-2.1]
1 1.3* 1.5***
[1.0-1.6] [1.2-1.8]
44.1 47.1 47.3 32.5 ** 44.1 50.9
1 1.0 0.8 0.7
[0.8-1.2] [0.7-1.0] [0.4-1.5]
1 1.3**
[1.1-1.6]
49.5 44.6 44.1 44.3 *** 34.6 55.1 59.5 52.2 54.1 70.6 70.9 47.7
1 0.8 0.8* 0.7**
0.7-1.0 0.6-0.9 0.5-0.9
1 2.5*** 3.0*** 2.1*** 2.2*** 4.7*** 4.7*** 1.9
[1.8-3.3] [1.9-4.7] [1.7-2.6] [1.6-3.1] [2.9-7.7] [3.4-6.4] [0.9-3.7]
P < 0.05. P < 0.01. P < 0.001 Terciles are cut off values allowing for splitting a variable distribution into three equal parts. The third tercile corresponds to the highest incomes.
Such selection mechanisms lead to resonance chamber and filter bubble phenomena [20]: the user lives in a bubble where he is no longer exposed to dissenting opinions and where only opinions similar to his are presented. This “closed” environment acts as a resonance chamber for the user as his own opinions are reinforced and amplified. Such phenomena may add up and reinforce vaccine hesitancy feelings in already reluctant individuals or in people already opposed to vaccination. This could explain the observed results. The negative link observed between information found on the Internet and vaccine hesitancy strengthens the desire of public authorities to be present on the Internet when it comes to vaccination issues. As demonstrated by J.P. Stahl et al., although the Internet may be where fake information is disseminated and where polemics are sparked on vaccination, it may also provide new tools and means to fight against vaccine hesitancy [21]. Various initiatives have already been developed such as the production of two videos on vaccination produced by health youtubers as part of a partnership with the ministry for health [22] (300,000 and 500,000 views approximately in June 2018) or the creation of the “vaccination-info-service.fr” website by the French national agency for public health (Santé publique France) [23]. This website aims to become the reference on vaccination. Its referencing on search engines is favorable (more than 4 million connections the first year–Santé Publique France data). The present study is the first to assess the association between getting vaccine information from relatives and vaccination practices and attitudes in France. Just like for the Internet, the
association seems to be negative and is even more worrying that young people rather turn to their relatives to obtain information (26.3% of people aged below 30 years seek information from relatives versus 18.6% of people aged above 40 years). The role of relatives is complex. Besides their informative role, relatives may have social influence, defined as modifications of the perception, attitudes, or behavior of an individual after hearing other people’s perception, attitudes, and behaviors. Conformism is thus translated into the individual adopting the general opinion of a given group. Brunson et al. have for instance demonstrated that having relatives recommending non-compliance with vaccination (incomplete vaccinations, late vaccination, or no vaccination at all) was significantly associated with non-compliance with the vaccination calendar [24]. Social psychology and the network theory could shed additional light on the dissemination of anti-vaccine feelings among the population. Onnela et al. thus demonstrated that in Malegaon, India, households opposed to vaccination were socially and geographically connected. They formed clusters or pockets of resistance to vaccination [25]. Better knowledge of the socio-spatial distribution of vaccine hesitancy could lead to more targeted interventions to promote vaccination. The multiple-target strategies of vaccination campaigns also seem to be adapted considering the influence of relatives when it comes to vaccination. Such strategies rely on opinion leadership such as the grandparents or healthcare professionals and early childhood professionals.
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Family physicians play a crucial role, as they are the ones to perform vaccination, to check that their patients’ status is up to date, and to explain the role of vaccine in protecting from infectious diseases. Family physicians are indeed the first source of information for parents when it comes to vaccination, and 95.3% of parents trust their family physician [8]. Access to family physicians is however not homogeneous in France and can be limited in specific areas where medical density is lower (e.g., specific rural areas or underprivileged neighborhoods). One of the limitations of the study lies in the non-consideration of difficulties in having access to a family physician as a potential confounding factor. However, we observed in our study that living in large cities (> 100,000 inhabitants or Paris area) was associated with a more extensive use of the Internet, better vaccination practices, and lower vaccine hesitancy rates. 5. Conclusion Our study demonstrates the association between looking for vaccine information on the Internet and, for the very first time, from relatives and low levels of vaccination practice and acceptance. Initiatives such as the creation of the “vaccination-info-service.fr” website should therefore be continued, and their impact and use should be assessed, mainly among vaccine-hesitant people. Assistance and education should also be provided to people looking for reliable health-related information on the Internet. Authors’ contributions JC performed the literature analysis and statistical analysis, and wrote the article. CJ supervised the work and contributed to reviewing the article. AG provided the data, supervised the statistical analysis, and contributed to reviewing the article. Disclosure of interest The authors declare that they have no competing interest. References [1] OMS | Vaccination [Internet]. WHO. Available from: http://www.who. int/topics/immunization/fr/. Accessed on Mars 6, 2019. [2] Wolfe RM, Sharp LK. Anti-vaccinationists past and present. BMJ. Br Med J 2002;7361(8):430–2. [3] WHO SAGE. Vaccine Hesitancy Working Group report [Internet]; 2014 [Available from: https://www.who.int/immunization/sage/meetings/2014/october/ SAGE working group revised report vaccine hesitancy.pdf?ua=1. Accessed on July 18, 2019]. [4] Perception et adhésion à la vaccination en France [Internet]. Available from: https://professionnels.vaccination-info-service.fr/Aspects-sociologiques/ Perception-et-adhesion-a-la-vaccination/Perception-et-adhesion-a-lavaccination-en-France. Accessed on Mars 6, 2019 [Published on the 29.03.2018; updated on the 02.05.2018].
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Please cite this article in press as: Charron J, et al. Influence of information sources on vaccine hesitancy and practices. Med Mal Infect (2020), https://doi.org/10.1016/j.medmal.2020.01.010