ABSTRACT
COVID-19 vaccine hesitancy remains problematic among healthcare workers. Social network influences may shape vaccine decision-making, but few studies have examined this in this critical workforce. We assessed the relationship between friends’ COVID-19 vaccination attitudes and personal hesitancy among Chinese healthcare personnel. In December 2022–January 2023, a cross-sectional online survey was conducted at a tertiary hospital in China using WeChat. Of the 1832 healthcare personnel who were invited to answer the structured questionnaire, 613 (33.5%) samples had valid data for data analysis. Logistic regression examined the association between friends’ hesitancy and participants’ own hesitancy, adjusting for confounders. Of 613 healthcare workers included, 266 (43.4%) were hesitant. Those with hesitant friends had 6.34 times higher adjusted odds of hesitating themselves versus those without hesitant friends (95% CI 2.97–13.52). Strong associations persisted across subgroups. Chinese healthcare workers’ COVID-19 vaccination hesitancy was highly influenced by perceived friends’ attitudes. Fostering pro-vaccine social norms through trusted peer networks could help promote vaccine acceptance in this critical workforce.
Introduction
The most effective way to return to normal life is with the COVID-19 vaccine as it prevents disease, asymptomatic infections and transmission.Citation1 However Vaccine hesitancy has been identified as one of the top threats to global health, undermining progress made in tackling vaccine-preventable diseases.Citation2 Recent surveys have found concerning rates of hesitancy toward COVID-19 vaccines among healthcare workers, a critical population for vaccine promotion.Citation3 A study showed that the proportion of respondents who were hesitant about the vaccine who received the hypothetical booster dose was only 14.3%.Citation4 However, up to 40% of healthcare workers across 33 countries expressed reluctance to receive a COVID-19 vaccine during early rollout.Citation5 Such hesitancy risks undermining vaccine uptake and prolonging the public health crisis. This highlights the urgent need to understand factors driving COVID-19 vaccine decision-making. Beyond individual attitudes and demographics, acceptance of new vaccines can be shaped by social influences.Citation6 A study across 67 countries have demonstrated that perceived social norms and attitudes of friends/peers are strong predictors of individuals’ own vaccination behaviors, even stronger than confidence in health authorities.Citation7 A dose-response relationship has been observed where increasing proportions of vaccine-hesitant individuals within one’s social network corresponded to lower likelihoods of personal vaccine acceptance.Citation8
The concept of “social contagion” being applied to vaccine attitudes and behaviors can be grounded in Social Contagion Theory. Social Contagion Theory has been used to explain the spread of various health behaviors and conditions like obesity, smoking, depression, etc. within social circleg s.Citation9 Researchers have also applied it to understand the propagation of vaccine misinformation and hesitancy through social networks.Citation10,Citation11 The theory suggests that doubts or concerns about vaccines can be communicated and reinforced among connected individuals, leading to clustering of vaccine hesitancy attitudes. Medical staff represent a high priority population for COVID-19 vaccination given their critical role in care delivery and influence on broader vaccine uptake.Citation12,Citation13 However, studies show concerning rates of vaccine hesitancy in this group,Citation14 while their own attitudes and behaviors can sway acceptance among patients and communities.Citation15,Citation16 Thus the attitude of medical staff toward vaccination has a role to play in modeling and leading the acceptance of vaccines in the community as a whole. Despite this, few studies have examined the impact of social network factors on COVID-19 vaccine decision-making among healthcare workers specifically.
There is very clear evidence that levels of antibodies to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) decline over time.Citation17 A fourth dose of COVID-19 vaccination has been approved in Israel and Japan in May 2022, mainly for healthy adults who received the third vaccination more than five months ago.Citation8,Citation18 China is also considering initiating a fourth vaccination at an appropriate time in response to a COVID-19 pandemic.Citation19 The aim of this study was to assess the relationship between hesitancy and friends of Chinese healthcare workers regarding the fourth booster vaccination in the context of social reopening. We hypothesized friends’ attitudes would independently predict one’s own vaccine hesitancy even after accounting for demographic, medical history, COVID-19 knowledge and infection variables. Clarifying this social contagion effect around vaccine decision-making among medical staff can inform public health communication strategies targeting this important group.
Methods
Study design and data collection
A population-based online survey was conducted anonymously using the Wen-Juan-Xing platform (Changsha Ranxing Information Technology Co., Ltd, Hunan, China), the largest online survey platform in China. The questionnaire was created by the researcher on the Internet survey platform, and a URL link and QR code were generated. Upon receiving consent from the relevant institution, the researcher distributed the survey link or QR code to the hospital nursing department, medical department, and president’s office, which then disseminated it to the institution’s staff. The questionnaire was sent to all 1,832 medical staff at the hospital in December 2022 based on an internal contact list. Data collection occurred from December 17, 2022 to January 31, 2023. In total, 613 medical staff members completed the survey via WeChat. The study was approved by the institutional ethics committee and followed Helsinki Declaration guidelines.
Participant eligibility
We included all medical staff actively employed at the hospital during the study period who voluntarily opted to complete the online questionnaire. Exclusion criteria were: non-medical hospital employees, lack of access to the WeChat platform, declining participation, aborted or incomplete questionnaires, submission outside the timeframe, duplicated responses, or illogical/contradictory responses. Screening was done to filter out invalid or unreliable questionnaires based on completion time, substantial missing data, multiple submissions per person, and logical errors. Only eligible participants were included in the final analytic sample.
Questionnaire design and assessment of hesitancy
We developed a survey instrument to assess COVID-19 vaccination attitudes based on previously validated constructs from the literature.Citation20,Citation21 The questionnaire covered sociodemographic factors, medical history, COVID-19 knowledge and experiences, and social influences. The questionnaire covered sociodemographic factors, medical history, COVID-19 knowledge and experiences, and social influences. To evaluate vaccination hesitancy, we included the 4-item Vaccine Hesitancy Scale.Citation22 This uses a 5-point Likert scale assessing comfort with receiving the COVID-19 vaccine, serious side effect concerns, importance of vaccination, and willingness to get vaccinated. Higher scores indicate greater hesitancy. We defined hesitancy as a mean score ≥ 3, consistent with prior studies.Citation7,Citation22
Assessing friends’ hesitancy
To measure friends’ hesitancy toward the COVID-19 vaccine, we included the following item in the questionnaire, “How many of your close friends are hesitant about receiving the 4th dose/booster of the COVID-19 vaccine?” Participants responded by selecting one of the following options: 1) None of my close friends are hesitant; 2) A few of my close friends are hesitant; 3) About half of my close friends are hesitant; 4) Most of my close friends are hesitant; 5) All of my close friends are hesitant. For the analysis, we dichotomized this variable where responses 2) through 5) were classified as having “hesitant friends,” while response 1) was categorized as “no hesitant friends” (please see Appendix 1).
Quality control
Several steps were taken to ensure high quality questionnaire design and data collection: 1) The survey instrument was developed by a multidisciplinary team including epidemiologists, statisticians, physicians, psychologists, and public health experts to ensure appropriate constructs were measured. 2) The questionnaire was piloted among 20 medical staff members to evaluate understandability, length, flow, and feasibility. Ambiguous or problematic questions were revised based on feedback. 3) Logic and skip patterns were programmed into the online questionnaire to minimize erroneous or missing responses. Required answers and value range checks were built in for key items. 4) The online platform allowed tracking of survey completion rates and duration to identify issues. Reminder prompts were sent to non-responders to improve participation. 5) Data were exported regularly to check for anomalies, duplications, or incomplete surveys. Irreconcilable issues triggered a review of the online questionnaire. 6) All data were processed through validation rules, with exclusions applied for unreliable questionnaires as pre-specified. Logical consistency checks were conducted on the final dataset. 7)A random 10% sample was selected for dual entry and verification to assess data accuracy. Error rates informed the need for reentering subsets if above the 5% threshold.
Statistical analysis
Descriptive statistics including frequencies, percentages, means, and standard deviations were used to summarize sample characteristics. Bivariable analyzes using chi-square and t-tests compared differences between the hesitancy and non-hesitancy groups. Logistic regression models were constructed to examine the association between friends’ COVID-19 vaccination hesitancy and participants’ own hesitancy. Both unadjusted and adjusted models were fitted, with progressive adjustment for sociodemographic factors, medical history, COVID-19 variables, and other social influences. Odds ratios and 95% confidence intervals were calculated. Effect measure modification was assessed by including an interaction term between friends’ hesitancy and each potential effect modifier. Stratified analyzes were also conducted within subgroups defined by sex, age, parenthood, and allergy history. A forest plot displayed the results. Two-sided p-values < .05 were considered statistically significant for all analyzes. Missing data were minimal given the online survey design and managed through sample exclusions as pre-specified. All analyzes were conducted using R version 4.2.2 and figures were generated with ggplot2.
Results
Characteristics of the participants
A total of 2,234 individuals working at the hospital were assessed for eligibility. Of these, 402 were excluded for the following reasons: not currently employed as medical staff (n = 342), unable to use the WeChat mobile app (n = 41), and unwilling to participate in the online questionnaire (n = 19). The questionnaire was distributed to the remaining 1,832 medical staff via the WeChat platform. Of these, 1,219 were further excluded for the following reasons: no response to the questionnaire (n = 988), questionnaire submitted with too short completion time (n = 47), questionnaire with substantial missing responses (n = 127), duplicate or multiple questionnaire submissions (n = 43), and questionnaires submitted after data collection period ended (n = 14). After applying the exclusion criteria, 613 medical staff members with valid questionnaires were included in the final analysis (see the ). This represented 33.5% of the 1,832 medical staff invited to participate and 27.5% of the initial 2,234 hospital employees assessed for eligibility. The majority of exclusions were due to non-response on the WeChat platform. Other major reasons for exclusions were incomplete or duplicated questionnaire submissions. To assess non-response bias, we compared available demographic and medical data of respondents (n = 613) to non-respondents (n = 1219) using chi-square tests. No statistically significant differences were found in sex, age, residence, education, occupation, and annual frequency of colds (p > .05). These suggesting respondents were largely representative of the target population (please see Appendix 2).
Figure 1. The flow chart of the study.
summarizes the baseline characteristics of the study participants. The mean age was 35.2 ± 15.0 years. The majority were female (70.6%). The majority (92.3%) had friends who were infected with COVID-19, while only 10.1% had friends who hesitated to get the fourth dose vaccinated. Significant differences between the hesitated and non-hesitated groups were observed for sex, allergy history, COVID-19 infection history, vaccination knowledge, and friends’ hesitancy status (all p < .05).
Table 1. Baseline characteristics of medical staff stratified by hesitancy.
Multivariable regression analyses
Multiple logistic regression models were constructed to examine the association between having friends who hesitancy about COVID-19 vaccination and medical staff’s own hesitancy about the fourth vaccine dose. As shown in , having hesitant friends was significantly associated with increased odds of self-reported hesitancy in all models. In the unadjusted model (Model 1), those who had hesitant friends had 5.50 times higher odds of hesitating themselves compared to those without hesitant friends (95% CI: 2.66–11.36, p < .001). After adjusting for sociodemographic factors (Model 2), the odds ratio was similar at 5.57 (95% CI: 2.66–11.65, p < .001). Further adjusting for medical conditions (Model 3) also did not attenuate the association (OR 5.78, 95% CI: 2.74–12.16, p < .001). The association remained significant after additionally controlling for prior COVID-19 knowledge and infection history (Model 4) with an OR of 6.35 (95% CI: 2.98–13.54, p < .001). In the fully adjusted model including all potential confounders (Model 5), having hesitant friends continued to be a strong predictor of self-hesitancy, with a 6-fold higher odds compared to those without hesitant friends (OR 6.34, 95% CI: 2.97–13.52, p < .001). The multiple regression analyzes consistently demonstrated a significant association between friends’ COVID-19 vaccination hesitancy and medical staff’s own vaccination hesitancy that persisted after controlling for sociodemographics, medical history, prior COVID-19 factors, and other social influences. This suggests friends’ attitudes may independently influence one’s own vaccination decision-making.
Table 2. Association between friends’ hesitancy and medical staff’s hesitancy.
Subgroup analyses
Subgroup analyzes were conducted to evaluate whether the association between friends’ hesitancy and medical staffs’ own hesitancy varied across different demographic factors. As shown in the forest plot (), having hesitant friends strongly predicted one’s own hesitancy consistently across subgroups. In the overall adjusted model, those with hesitant friends had 6.34 times higher odds of hesitating themselves (95% CI: 2.97–13.52). This association remained significant when stratified by sex, with the odds ratio for males being 6.83 (95% CI: 1.66–28.09) and females being 6.53 (95% CI: 2.58–16.56; P-interaction = 0.750). When examined by age, the odds ratio was higher among younger participants ≤35 years (OR 10.68, 95% CI: 3.83–29.79) compared to those >35 years (OR 2.64, 95% CI: 0.78–8.89), though the interaction was not statistically significant (p = .085). Having hesitant friends strongly predicted one’s own hesitancy regardless of parenthood status, though the effect size was larger among those without children (OR 19.62, 95% CI: 4.06–94.84) versus those with children (OR 3.33, 95% CI: 1.34–8.27; P-interaction = 0.046). Among those with versus without an allergy history, the odds ratios were 8.10 (95% CI: 3.05–21.51) and 3.91 (95% CI: 0.86–17.85), respectively (P-interaction = 0.419). The association between friends’ hesitancy and medical staff’s own COVID-19 vaccination hesitancy persisted across all subgroups examined, though the magnitude of the effect varied. The relationship was strongest among younger and nulliparous individuals.
Figure 2. Subgroup analysis of between friends’ hesitancy and medical staffs’ hesitancy.
Discussion
Our results show a robust correlation whereby a friend’s vaccination hesitancy directly influences their own hesitancy.Those reporting hesitant friends had over 6 times higher odds of hesitating themselves in fully adjusted models. In this study, “social contagion” would refer to the spread of vaccine hesitancy among Chinese medical staff due to the influence of their social networks, where doubts or concerns about vaccines are communicated and shared, leading to a collective increase in vaccine hesitancy within this professional community.Citation11
Reporting biases are inherent to most survey research, but we took several steps to minimize their influence, such as protecting respondent anonymity and using validated, widely-accepted measurement scales. Reverse causality cannot be fully ruled out, but the hypothesized direction of friends influencing individuals aligns with established social contagion theory and prior empirical evidence.Citation11,Citation23,Citation24 Furthermore, we adjusted for a comprehensive set of potential confounding factors that could create omitted variable bias, including sociodemographics, medical histories, COVID-19 knowledge/experiences, and other social influences. The strong, persistent association despite these adjustments argues against trivial confounding.
While not establishing definitive causality, the sociological premise that individuals’ attitudes and behaviors are shaped by their social milieu has strong theoretical grounding across disciplines. The “social contagion” framing is perhaps an imperfect analogy, but it reflects established principles of conformity, social learning, and normative influences on health behaviors.Citation25 Even if our findings only capture clusters of hesitancy attitudes rather than their transmission process, delineating this social patterning remains important for designing effective public health communication strategies. The strong social contagion effect around COVID-19 vaccine attitudes highlights the importance of community confidence building and addressing collective concerns. Information interventions targeting influential peer groups and community leaders could help promote acceptance of COVID-19 vaccination among healthcare workers.Citation26 Beyond educating individuals, public health communication must focus on shaping social norms and perceptions of vaccination within key social circles and institutions.Citation15
At minimum, our results reveal a robust link between medical staff’s COVID-19 vaccination hesitancy and perceived hesitancy among their close social ties. This aligns with prior studies of social/peer effects on vaccine attitudes in the general population and suggests medical staff may be similarly influenced despite their healthcare expertise.Citation6 The present study found that the influence of friends on COVID-19 vaccination among young people is of interest. In fact, the influence of friends’ hesitation was most significant among young participants under 35 years of age. With the popularity of social media and the rapidity of information dissemination, the exchange of views and sharing of information among friends has become more convenient and frequent. As a result, when friends express doubts or opposing attitudes toward the COVID-19 vaccine on social media, such information can easily penetrate into young people’s social circles, which in turn affects their attitudes and decision-making about the vaccine. Younger adults likely have more dynamic social networks and may be more amenable to peer effects regarding new health behaviors like COVID-19 vaccination.Citation27,Citation28 Our results suggest peer-focused communication efforts could help boost vaccine uptake in this age group. While causal mechanisms require further investigation, these correlational findings already point to an important phenomenon with pragmatic implications that should not be disregarded due to design constraints.
In the subgroup analyzes, We also found that the hesitancy of health workers without children had a greater impact on vaccination intentions. Healthcare professionals with children may have access to diverse information from various channels, such as schools, children’s health management agencies, and parent groups. Those with children may have more varied information sources or exposure to pro-vaccine norms through school requirements that mitigate peer influence.Citation29
Moreover, our study highlights key hypotheses and provides foundational justification for future prospective studies with more robust socio-behavioral measurements and advanced causal modeling techniques. Overcoming the limitations of cross-sectional designs using longitudinal social network data, randomized interventions targeting peer influences, and inferential methods like social-based instrumental variables could yield more definitive insights into social contagion processes affecting COVID-19 vaccine decision-making in this critical population.
Individuals’ vaccination attitudes are likely influenced by those of their friends and peers. As false information spreads on social media, it can infiltrate an individual’s social circle.Citation11 If a trusted friend then shares misinformation about the COVID-19 vaccine within this circle, it can influence individual attitudes toward the vaccine. Consequently, in efforts to increase COVID-19 vaccination rates, it is important to consider how social influence, facilitated by the spread of misinformation, can impact attitudes toward the vaccine. COVID-19 vaccination hesitancy among friends strongly predicted one’s own hesitancy among Chinese medical staff. Harnessing trusted social networks and community leaders to promote vaccine-positive norms could be an impactful strategy for improving COVID-19 vaccine acceptance in this critical workforce. A nuanced understanding of the social dynamics shaping vaccine decision-making will be key to overcoming vaccine hesitancy and maximizing population protection.
Limitations
Our study had limitations including reliance on self-reported data which can be subject to recall bias. First, In this study, 33.5% of respondents provided effective responses, indicating the potential presence of non-response bias. Comparison of demographic and medical data between respondents and non-respondents revealed no statistically significant differences, suggesting some degree of representativeness. However, it remains possible that unmeasured factors related to COVID-19 vaccine attitudes and hesitancy may have influenced the differences between these two groups. Second, our pre-defined exclusion criteria necessitated the exclusion of participants with incomplete or missing data on key variables to uphold data quality standards. However, we cannot rule out that respondents may have systematically differed from non-respondents on unmeasured factors related to COVID-19 vaccine attitudes and hesitancy. Third, The cross-sectional design also prevents determining causality. Fourth, Sample size for some subgroup analyzes was modest, though the main association remained robust. Fifth, as this was a regional sample of Chinese medical staff, results may not fully generalize to other healthcare worker populations. Further large-scale, high-quality prospective longitudinal studies are needed to investigate the potential impact of being in the proximity of vaccine-hesitant friends on an individual’s likelihood of reducing their own vaccination uptake.
Conclusion
This study found Chinese medical staff COVID-19 vaccination hesitancy strongly associated with perceived hesitancy among friends. Harnessing trusted social networks to promote pro-vaccine norms may be an impactful strategy for improving COVID-19 vaccine acceptance in this critical workforce.
Author contributions
L.L.H. and W.W.H. conceived and designed the study. L.L.H. and W.W.H. collected the data. L.L.H., W.W.H., W.W.H., and Y.H.J. analyzed and interpreted the data. L.L.H. drafted the manuscript. W.W.H., W.W.H., and Y.H.J. critically revised the manuscript. All authors gave final approval and agree to be accountable for all aspects of the work.
Ethics approval and consent
This study was approved by the Ethics Committee of Taizhou First People’s Hospital, Zhejiang Province, China [approval 2023-KY079-01]. And performed in accordance with the Declaration of Helsinki principles. Participants were informed of the study objectives, confidentiality, anonymity, voluntary participation, and consented prior to participation.
Supplemental Material
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Download PDF (283.5 KB)Acknowledgments
The authors thank the medical staff who participated in the survey. We acknowledge the support provided by the Taizhou First People’s Hospital for facilitating data collection.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Data availability statement
The data that support the findings of this study are available on reasonable request from the corresponding author.
Supplementary material
Supplemental data for this article can be accessed on the publisher’s website at https://doi.org/10.1080/21645515.2024.2344290
Additional information
Funding
References
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