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10.1371/journal.pone.0310761
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Influenza vaccine hesitancy among healthcare workers in a Northeastern province in Thailand: Findings of a cross-sectional survey
Healthcare worker influenza vaccine hesitancy in Thailand
Shrestha Manash Conceptualization Data curation Formal analysis Investigation Methodology Project administration Visualization Writing – original draft Writing – review & editing 1
Sherer Penchan Pradubmook Conceptualization Investigation Methodology Supervision Validation Writing – review & editing 1
https://orcid.org/0000-0002-9483-5572
Paek Seung Chun Conceptualization Formal analysis Investigation Methodology Supervision Validation Visualization Writing – review & editing 1
Prasert Kriengkrai Data curation Formal analysis Project administration Resources Writing – review & editing 2 3
Chawalchitiporn Sutthinan Data curation Project administration Writing – review & editing 4
https://orcid.org/0000-0003-4593-0247
Praphasiri Prabda Conceptualization Investigation Methodology Resources Supervision Visualization Writing – review & editing 3 *
1 Department of Society and Health, Faculty of Social Sciences and Humanities, Mahidol University, Nakhon Pathom, Thailand
2 Nakhon Phanom Hospital, Nakhon Phanom, Thailand
3 Faculty of Public Health, Kasetsart University, Sakon Nakhon, Thailand
4 Epidemiology Department, Faculty of Medicine, Thammasat University, Bangkok, Thailand
Ahmed Sirwan Khalid Editor
Ministry of Health, General Health Directorate of Raparin and University of Raparin, IRAQ
Competing Interests: The authors have declared that no competing interests exist.

* E-mail: marxprabda2510@gmail.com, Prabda.p@ku.ac.th
19 9 2024
2024
19 9 e031076120 3 2024
5 9 2024
© 2024 Shrestha et al
2024
Shrestha et al
https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Background

Healthcare workers (HCWs) are an important target group for influenza vaccination due to their increased risk of infection. However, their uptake remains a challenge. This study aimed to identify and measure influenza vaccine hesitancy among HCWs in Nakhon Phanom province, Thailand.

Methods

A representative cross-sectional survey was conducted during August–September 2020, among 350 HCWs at six hospitals in the province selected by a two-stage cluster sampling using a self-administered questionnaire. HCWs who either delayed getting influenza vaccines, accepted the vaccines but were unsure, or refused the vaccine with doubts were categorized as hesitant. HCWs who accepted the influenza vaccine without any doubts were classified as non-hesitant. Determinants of vaccine hesitancy were identified by a multivariable logistic regression analysis.

Results

A total of 338 participants (97%) filled the questionnaires. The mean age of the participants was 37.2 years. Most participants were female (280; 83%), nurses (136; 40%), working at district hospitals (238; 71%), with bachelor’s degree (223; 66%), and without any pre-existing chronic medical conditions (264; 78%). Influenza vaccine hesitancy was evident among nearly 60% of the participants (197/338), who had varying patterns of hesitancy. Significant factors of influenza vaccine hesitancy were found to be age above 50 years (adjusted odds ratio [aOR] 3.2, 95% CI 1.3–8.5), fair knowledge of influenza and vaccination (aOR 0.4, 95% CI 0.2–0.8), and negative influence of other HCW (High level–aOR 2.3, 95% CI 1.1–4.8; Moderate level- aOR 2.1, 95% CI 1.1–4.4).

Conclusion

Influenza vaccine hesitancy was highly prevalent among the Thai HCWs in Nakhon Phanom province. Imparting updated information to the HCW, in combination with positive guidance from influential HCWs in the hospital, may help reduce hesitancy. These data may be useful to the National Immunization Program to design appropriate approaches to target hesitant HCWs in Thailand to improve influenza vaccine coverage.

The author(s) received no specific funding for this work. Data AvailabilityAll relevant data are within the manuscript and its Supporting Information files.
Data Availability

All relevant data are within the manuscript and its Supporting Information files.
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pmcIntroduction

Healthcare workers (HCWs) are recommended for seasonal influenza vaccines as they are at a higher risk of contracting influenza and inadvertently transmitting the virus to high-risk and vulnerable patients who may develop severe complications [1–5]. However, despite several recommendations, influenza vaccine uptake among HCWs has remained a challenge globally [6–8]. Many studies indicate that despite vaccine availability, some HCWs may be hesitant about vaccines, especially influenza vaccines, including when considering the vaccines for their children or their patients [9–11].

While the anti-vaccination movement is not a recent development [12], more people are becoming skeptical of vaccines, such that vaccine hesitancy is now considered a major threat to global health [13]. As HCW recommendations are highly influential for patients [14, 15], acceptance of vaccination by HCWs themselves is, therefore, also an important determinant of influenza vaccine uptake in the populations that they serve [16, 17]. Addressing the concerns of HCWs may be strategically beneficial in reducing vaccine hesitancy among the general public as well [18].

Defined as “a delay in acceptance or refusal of vaccines despite availability of vaccination services” by the World Health Organization (WHO)’s Strategic Advisory Group of Experts (SAGE), vaccine hesitancy is a behavioral phenomenon that broadens the scope of study of vaccination decision-making [19]. Vaccine-hesitant people are seen in a spectrum between those who accept vaccination without any doubts and those who reject vaccination at all costs. People may either accept vaccines without hesitation, accept them with hesitation, or reject them with or without hesitation [20]. Vaccine-hesitant individuals might receive all recommended vaccines on time but still harbor significant doubts [21]. Thus, vaccine hesitancy is better understood as a state of indecision and reluctance [22]. This view frames vaccine hesitancy as involving ’doubts’, ’concerns’, and ’reluctance’ about vaccination. Many scholars similarly argue that vaccine hesitancy is more a psychological state than a behavioral one [20, 23–25].

In their “3C” model, SAGE identified “complacency”, “inconvenience in accessing vaccines”, and “lack of confidence” as three key reasons for this hesitancy [19]. However, this phenomenon is dependent on the context and specific to vaccines. For example, the hesitancy to influenza vaccine may be different than to other vaccines. Therefore, SAGE supplemented the “3C” model with a vaccine hesitancy determinant matrix that included contextual, individual and group, and vaccine/vaccination-specific influences [19]. Although Paterson et al. adapted this matrix for HCW and added a few more determinants [16], it has been informed largely by research from high-income countries. Evidence from middle-income countries like Thailand has remained minimal.

In Thailand, HCWs were the first group to be recommended for yearly influenza vaccination by the Ministry of Public Health (MOPH) since 2004 [26]. Vaccination rates among Thai HCWs were self-reported to be as high as 89% in 2009 [27]. However, in 2018, regional reports showed that HCW influenza vaccine coverage had plummeted to below 30% in some regions (Department of Medical Services [DMS], MOPH) (S1 File). Although little is known about Thai HCW’s attitudes towards influenza vaccines, there are some disconcerting pieces of evidence. A study revealed that only 60% of Thai HCWs were willing to receive the pandemic influenza A(H1N1) vaccine [28]. In 2013, more than one-third of the Thai physicians working in ante-natal care clinics were found to have doubts about influenza vaccine’s safety and effectiveness, and only 25% of them routinely recommended influenza vaccines to pregnant women [29]. Another study reported that the seasonal influenza vaccine acceptance rate among medical professionals at a tertiary hospital in Bangkok was 65.4% [30]. Being the most informed group of people about the benefits of vaccines and having more access to vaccine than others, moderate acceptance and lower recommendations of influenza vaccines by Thai HCW may indicate deeper-lying cultural or personal concerns that might relate to vaccine hesitancy.

Despite being the study site of many influenza vaccine-related research in Thailand in the recent past that have actively partnered with local HCWs [31–33], the HCW uptake rate in Nakhon Phanom province was only 28% in 2018 (S1 File). Low uptake of influenza vaccines among HCWs is particularly remarkable in this border northeastern province as it is considered a “model” province for influenza vaccine research in Thailand, where vaccination rates are supposed to be higher. As Thailand’s influenza vaccination policies were largely shaped by the active surveillance data from this province [34–36], we found it important to evaluate if the HCWs in the province were themselves hesitant to influenza vaccines. Therefore, the objectives of this cross-sectional survey were to identify and measure influenza vaccine hesitancy among HCWs in Nakhon Phanom province.

Materials and methods

Study design and setting

This cross-sectional survey was part of a mixed-methods study on influenza vaccine hesitancy among healthcare workers in Nakhon Phanom province, which is located in the plateau region of northeastern Thailand, approximately 735 km from Bangkok. The province borders Lao PDR and has a total area of 5,528.88 sq. km. The province consists of 12 districts, with Muang district as the capital, along with 97 sub-districts and 1,123 villages [34]. There are 14 public hospitals in the province: one provincial general hospital, 11 community hospitals, a psychiatric hospital, and a military hospital. From 2003 to 2015, there was active surveillance of respiratory illnesses in the public hospitals of this province [34–36].

Study population

Thai HCWs of Nakhon Phanom province were the targeted population of the study. Although the WHO defines HCW as “all people engaged in actions whose primary intent is to enhance health” [37], we limited HCW’s definition to those who were currently working in public hospital settings in Nakhon Phanom for operational feasibility. As per a report of DMS, 1,863 registered HCWs were working in the province in 2018 (DMS, MOPH). The HCWs were broadly categorized into two groups according to the amount of patients’ contact/exposure and as grouped by WHO [38]: a) Health service providers who delivered health services and came in direct contact with patients and substances such as patients’ blood and other specimens, and b) Health management and support staff who assisted in the functioning of the health system without directly providing health services and as such may or may not have had direct contact with the patients. According to the nature of their work, health service providers were further sub-categorized into six groups—medical doctors, dentists, nurses, pharmacists, public health officers, and other service providers [38].

Participant selection criteria

Thai HCWs of both sexes (male and female) aged above 18 years, having a good command of the written and spoken Thai language, and currently working at a public hospital in Nakhon Phanom province were included in the study. HCWs who were not present in the hospital at the time of data collection and who were not willing to participate in the study voluntarily were excluded.

Sample size and sampling technique

As there was no prior estimate of influenza vaccine hesitancy among Thai HCWs, a conservative proportion of 50% was taken to calculate the sample size for the survey. A sample size of 350 was calculated using the single proportion formula and a finite population correction factor in OpenEpi (www.openepi.com), assuming a Type I error of 5%, absolute precision of 7.5 percentage points, and a design effect of 2 given the cluster sampling used for the population size of 1,863 HCW in Nakhon Phanom after inflating 10% for refusal and absences.

HCWs were recruited in the survey using a two-stage cluster sampling. In the first stage, hospitals were selected as clusters to recruit 50 HCWs in each cluster (i.e., seven clusters in total). The hospitals were chosen by a systematic random sampling using probability proportional to size (PPS) of the number of HCWs. As Nakhon Phanom Provincial hospital was a large hospital, it got selected twice. Therefore, 100 HCWs were recruited from that particular hospital, and 50 HCWs were selected from five other hospitals. In the second stage, HCWs were chosen using stratified random sampling according to their professional categories and proportional distribution in each hospital. Microsoft Excel sheets were used to generate the random numbers for the sampling in both stages, as described above.

Survey instrument and data collection

The survey questions were modified from the sample questions of SAGE’s vaccine hesitancy determinant matrix for the Thai context to measure influenza vaccine hesitancy and its three broad determinants: contextual or sociocultural, individual/group, and influenza vaccine-specific influences [16, 39]. Clear and concise language was used for ease of understanding and questions that were related were grouped to avoid jumping between unrelated topics. The participants were asked to indicate their level of agreement or disagreement with the items of the constructs on a 5-point Likert scale, with ‘1’ meaning strongly disagree and ‘5’ strongly agree. The questionnaire took around 30–35 minutes to complete. The study instrument was validated for use in the Thai context by another research project which used qualitative methods in the development of the questionnaire and had rigorous steps such as pilot testing (n = 30) for assessing feasibility, acceptability, and face validity, and a larger survey among a nationally representative sample of healthcare workers (n = 2352) for evaluating construct validity and reliability [40].

In this survey, the questionnaire was self-administered to the HCWs who were approached through designated focal points at the six hospitals in the province, identified by the sampling technique, from 1st August to 30th September 2020. A total of 350 questionnaires were distributed to the participants. The participants were assured that their responses would remain anonymous and confidential to reduce the pressure to conform to socially desirable responses. Clear instructions were provided on how to answer the questions, emphasizing the importance of honest and accurate responses.

Variables and measurement

The dependent variable of the study, influenza vaccine hesitancy, was defined as either delaying getting influenza vaccines, accepting the vaccines but being unsure, or refusing the vaccine despite seeing its value. It was measured as a binary variable (yes/no). “Yes” meant those HCWs who displayed some form of hesitancy, and “No” meant HCWs who accepted the influenza vaccine without any doubts.

The independent variables included demographic and work characteristics. Participant’s age and years of experience as HCW were first measured as continuous variables and then converted to appropriate categories. Categorical variables were sex (binary—male/female), religion, level of the hospital (Provincial/District), HCW type (Health service providers/Health management and support staff), daily exposure to patients (<1 meter/≥1 meter/no contact), education level, and self-reported presence of any pre-existing medical conditions (yes/no). Participants’ knowledge of influenza and vaccination was assessed using seven items that were adopted as a subset of a questionnaire from a previous study among Thai physicians [29], and then grouped into three categories using a modification of Bloom’s original cut-off points, such that six or more correct answers (i.e. ≥80%) represented “good knowledge”, four to five correct answers (i.e. 60–79%) meant “fair knowledge” and three or less correct answers (i.e. <60%) were considered as “needed improvement”.

The determinants of vaccine hesitancy were measured as constructs (i.e., composite variables). Contextual factors included the negative influence of media/social media (2 items), politics/policies (2 items), pharmaceutical industry influences (2 items), and the level of trust in the health system (2 items). Individual/group influences contained constructs of experience with past vaccination (3 items), beliefs and attitudes about influenza and vaccination (3 items), vaccination as a social norm (3 items), and influence of other healthcare professionals (2 items). Influenza vaccine/vaccination-specific issues included constructs of risk/benefit (perceived, heuristic) (4 items), risk of adverse events due to vaccination (3 items), fear of painful injections (2 items), and access to vaccines in the hospital (4 items) (S1 Table). Both positively and negatively worded statements were used, and the direction of negatively worded questions was reversed for data analysis. Items under each construct were averaged to create aggregated mean scores for the construct. The average scores were case-ranked and then used to divide the construct into three categories–high, moderate, and low.

Data analysis

Descriptive statistics were first employed to provide a summary of the selected variables and study samples. The mean scores of vaccine hesitancy determinants were compared between hesitant and non-hesitant HCWs using independent t-tests. The associated factors of influenza vaccine hesitancy were identified by a series of binary logistic regression models. As the dependent variable (influenza vaccine hesitancy) was categorical, the logistic regression analysis was performed using non-hesitant HCW as the reference category. All variables showing at least some evidence of association (Type III p values <0.1 in the binary logistic regression models) were entered into a multivariable logistic regression model, adjusting hospital locations to account for clustering. Variables with significant adjusted odds ratio (aOR) in the final model were recognized as associated factors (p-value <0.05). All data analysis was conducted using SPSS version 20 (IBM Corp., Armonk, NY).

Ethical considerations

Written informed consent was obtained from each participant before data collection. The study protocols and all related study documents were reviewed and approved by the Mahidol University—Central Institutional Review Board (MU-CIRB) (Protocol number MU-CIRB 2020/138.1606). Permission for data collection was also received from the Provincial Chief Medical Officer, Nakhon Phanom Provincial Public Health Office (ref no. 78.02/ 06115).

Results

Response rate

Out of the total 350 survey questionnaires distributed, 338 filled questionnaires were received back from the participants, implying a response rate of 96.6% (Fig 1). The response rates varied at different hospitals, ranging from 80–100% (S2 Table).

10.1371/journal.pone.0310761.g001 Fig 1 Study flow and influenza vaccine hesitancy among healthcare workers in Nakhon Phanom Province, Thailand.

Participant characteristics

Of those 338 participants, the mean age of the participants was 37.2±9.7 years, with a minimum of 20 years and a maximum of 60 years. Almost all participants were Buddhists (333; 98.5%). A majority of the participants were female (280; 82.8%), nurses (136; 40.2%), from district hospitals (238; 70.7%), with bachelor’s degree (223; 65.9%), and without any pre-existing chronic medical conditions (264; 78.1%) (Table 1). The participants had a mean work experience of 13.8±9.8 years as HCW, and around half of them reported having high daily exposure with patients in the proximity of less than 1 meter (172; 50.9%).

10.1371/journal.pone.0310761.t001 Table 1 Participant characteristics (n = 338).

Characteristic	Number	Percentage	
Age group			
    ≤30 years	102	30.2	
    31–40 years	121	35.8	
    41–50 years	72	21.3	
    >50 years	43	12.7	
Mean (SD): 37.2 years (9.7); Min: 20, Max: 60			
Sex			
    Female	280	82.8	
    Male	58	17.2	
Religion			
    Buddhism	333	98.5	
    Christianity	5	1.5	
Level of hospital			
    Provincial	100	29.6	
    District	238	70.4	
HCW type			
    Health service providers	295	87.3	
        Nurse	136	40.2	
        Pharmacist	19	5.6	
        Public health officer	19	5.6	
        Medical doctor	16	4.7	
        Dentist	6	1.8	
        Other medical personnel	99	29.3	
            Hospital assistant staff	55	16.3	
            Patient assistants	27	8.0	
            Emergency medical technicians (EMT)/paramedic	7	2.1	
            Laboratory staff	7	2.1	
            Nurse aids	3	0.9	
    Health management and support staff	43	12.7	
Average daily exposure with patients			
    High (<1 meter)	172	50.9	
    Moderate (1 meter or more)	106	31.4	
    Low (no direct patient contact)	60	17.8	
Work experience as HCW			
    ≤5 years	74	21.9	
    >5 years to <20 years	166	49.1	
    ≥20 years	98	29.0	
Mean (SD): 13.8 years (9.8); Min:1, Max: 37			
Highest educational attainment			
    High school or below	36	10.7	
    Diploma or vocational college	43	12.7	
    Bachelor’s degree	223	65.9	
    Master’s degree or higher	36	10.7	
Pre-existing chronic medical condition			
    Yes	74	21.9	
    No	264	78.1	
Abbreviations: SD, Standard deviation; Min, Minimum; Max, Maximum

Knowledge about influenza and vaccination

A high majority of HCWs were aware of the MOPH recommendation of influenza vaccination for them (302; 89.3%). However, most participants were misinformed about the influenza vaccines as only 52% correctly identified that the influenza vaccine may not work if it contained the wrong virus strains than the circulating ones, and only 30% firmly believed that the influenza vaccine does not itself cause some people to get influenza (Table 2). Overall, only a quarter of the participants had a good knowledge regarding influenza and vaccination (85; 25.1%) (Table 2).

10.1371/journal.pone.0310761.t002 Table 2 Participants’ correct responses to each item of knowledge on influenza and vaccination (n = 338).

Knowledge items	Correct response	Number	%	
     1. Healthcare workers are recommended for influenza vaccination in Thailand by the MOPH	True	302	89.3	
     2. Thailand has a national policy to provide free vaccine to high-risk groups	True	273	80.8	
     3. Influenza can lead to serious complications, including pneumonia	True	240	71.0	
     4. HCWs are less susceptible to influenza infections than other people	False	219	64.8	
     5. Influenza vaccination may not work if the vaccine contains the wrong mix of viruses	True	176	52.1	
     6. Influenza vaccination does not work in some persons, even if the vaccine has the right mix of viruses	True	140	41.4	
     7. Influenza vaccine may cause some people to get influenza	False	102	30.2	
Overall knowledge categories				
     Need improvement (Overall score <60%)	0–3	104	30.8	
     Fair (Overall score 60–79%)	4–5	149	44.1	
     Good (Overall score ≥80%)	6–7	85	25.1	

Influenza vaccine hesitancy among the participants

A majority of the participants reported some degree of hesitancy towards influenza vaccines (197; 58.3%), and 7 HCWs (2.1%) were outright refusers of influenza vaccines who were not hesitant in their refusal (Fig 1). On closer inspection, most of the hesitant HCWs were “hesitant compliers” who had doubts about the influenza vaccines but still accepted them (172; 87.3%). Only 3 (1.5%) refused the vaccine while being considerate of its benefits, and 22 (11.2%) delayed receiving the vaccine for themselves (Fig 2). More than 60% of the health management staff, other medical professionals (paramedics), and nurses reported vaccine hesitancy, while other HCW types had less hesitancy than the sample prevalence of 58.3%; the least hesitancy was seen among pharmacists (31.6%) (Fig 3).

10.1371/journal.pone.0310761.g002 Fig 2 Types of hesitant HCW among the participants.

10.1371/journal.pone.0310761.g003 Fig 3 Influenza vaccine hesitancy levels among different HCW types.

Vaccine hesitancy determinants

Removing the seven HCWs who refused influenza vaccines left with an analytical sample of 331 HCWs. The aggregated mean scores and standard deviations of the vaccine hesitancy determinants are presented in Table 3. The mean scores are on a scale of 1–5, where higher scores signify higher hesitancy or more negative sentiment towards the construct. Overall, the participants reported the highest negative perceptions towards pharmaceutical industry influences (mean score 2.8, SD 1.0) and influence of media/ social media (mean score 2.7, SD 0.8) (Table 3). When the mean scores were compared, HCW with influenza vaccine hesitancy were more likely to have a higher lack of trust in the health system (2.7 vs 2.3; p-value 0.008), negative past experience of vaccination (2.4 vs 2.1; p-value 0.017), negative perception of vaccination as a social norm (2.3 vs 2.0; p-value 0.011), negative influence of other HCW (2.2 vs 1.9; p-value 0.006), higher perceived risk and lack of benefit of influenza vaccine (2.4 vs 2.1; p-value 0.001), risk of adverse events due to vaccination (2.7 vs 2.3; p-value 0.001), fear of painful injections (2.5 vs 2.2; p-value 0.007), and lack of access to vaccines (2.5 vs 2.2; p-value <0.001) (Table 3).

10.1371/journal.pone.0310761.t003 Table 3 Influenza vaccine hesitancy determinants aggregated mean scores (n = 331).

Determinant	Total Mean (SD)	Influenza vaccine hesitancy	p-value*	
Yes (n = 197)	No (n = 134)	
Mean	SD	Mean	SD	
Contextual factors							
    Negative influence of media/ social media	2.7 (0.8)	2.6	0.8	2.8	0.9	0.154	
    Negative perception of politics/policies	1.9 (0.9)	1.9	0.8	1.8	0.9	0.057	
    Negative perception of pharmaceutical industry	2.8 (1.0)	2.8	0.9	2.7	1.1	0.435	
    Lack of trust in health system	2.5 (1.0)	2.7	0.7	2.3	1.1	0.008	
Individual/Group influences							
    Negative past experience of vaccination	2.3 (1.1)	2.4	1.1	2.1	1.0	0.017	
    Negative beliefs, attitudes about influenza and vaccination	2.2 (0.9)	2.2	0.8	2.1	1.0	0.614	
    Negative perception of vaccination as a social norm	2.2 (0.9)	2.3	0.8	2.0	0.9	0.011	
    Negative influence of other HCW	2.0 (1.0)	2.2	0.9	1.9	1.0	0.006	
Influenza vaccine specific factors							
    Perceived risk of influenza infection and lack of benefit of vaccination	2.2 (0.7)	2.4	0.6	2.1	0.7	0.001	
    Risk of adverse events due to vaccination	2.5 (0.9)	2.7	0.9	2.3	1.0	0.001	
    Fear of painful injections	2.4 (0.7)	2.5	0.8	2.2	0.8	0.007	
Access to vaccines in the hospital	2.4 (0.7)	2.5	0.7	2.2	0.7	<0.001	
Abbreviations: SD, Standard deviation; Min, Minimum; Max, Maximum.

*p-value obtained from independent t-test.

Factors associated with influenza vaccine hesitancy

In a series of univariable logistic regression analyses, different variables were found to be significantly associated with influenza vaccine hesitancy (Table 4). Compared to young HCWs (aged 30 years and below), HCWs aged above 50 years were nearly three times more likely to be vaccine-hesitant (OR 2.8; 95% CI 1.2–6.3). Similarly, HCWs with 20 years or more work experience were more than two times more likely to be vaccine-hesitant than HCWs with experience of 5 years or less (OR 2.2; 95% CI 1.2–4.2). In contrast, HCWs having fair knowledge of influenza and vaccines were less likely to be hesitant compared to HCWs with less knowledge (OR 0.5; 95% CI 0.3–0.8).

10.1371/journal.pone.0310761.t004 Table 4 Factors associated with vaccine hesitancy among HCW (n = 331).

Factor	Influenza vaccine hesitancy	Crude OR	95% CI	Adjusted ORa	95% CI	
Yes (n = 197)	No (n = 134)	
n (%)	n (%)	
Age-groups (in years)							
    ≤30	55 (53.9)	47 (46.1)	Ref		Ref		
    31–40	65 (55.1)	53 (44.9)	1.0	0.6–1.8	1.1	0.6–2.1	
    41–50	44 (64.7)	24 (35.3)	1.6	0.8–2.9	1.9	0.9–4.1	
    >50	33 (76.7)	10 (23.3)	2.8	1.2–6.3*	3.2	1.3–8.5*	
Sex							
    Male	34 (59.6)	23 (40.4)	Ref				
    Female	163 (59.5)	111 (40.5)	0.9	0.6–1.8			
Level of hospital							
    Provincial	54 (55.7)	43 (44.3)	Ref				
    District	143 (61.1)	91 (38.9)	1.2	0.8–2.0			
HCW type							
    Health service providers	169 (58.3)	121 (41.7)	0.6	0.3–1.3			
    Health management and support staff	28 (68.3)	13 (31.7)	Ref				
Average daily patient exposure							
    High	96 (56.8)	73 (43.2)	0.8	0.4–1.5			
    Moderate	65 (63.1)	38 (36.9)	1.1	0.6–2.1			
    Low	36 (61.0)	23 (39.0)	Ref				
Work experience							
    ≤5 years	37 (50.0)	37 (50.0)	Ref				
    >5 years to <20 years	95 (58.3)	68 (41.7)	1.4	0.8–2.4			
    ≥20 years	65 (69.1)	29 (30.9)	2.2	1.2–4.2*			
Highest educational attainment							
    High school or below	25 (69.4)	11 (30.6)	Ref				
    Diploma/ vocational college	31 (72.1)	12 (27.9)	1.1	0.4–3.0			
    Bachelor’s degree	122 (56.2)	95 (43.8)	0.6	0.3–1.2			
    Master’s degree or higher	19 (54.3)	16 (45.7)	0.5	0.2–1.4			
Pre-existing chronic condition							
    Yes	44 (60.3)	29 (29.7)	1.0	0.6–1.8			
    No	153 (59.3)	105 (40.7)	Ref				
Knowledge of influenza and vaccination							
    Need improvement	71 (69.6)	31 (30.4)	Ref		Ref		
    Fair	74 (51.4)	70 (48.6)	0.5	0.3–0.8*	0.4	0.2–0.8*	
    Good	52 (61.2)	33 (38.8)	0.7	0.4–1.3	0.9	0.5–2.0	
Contextual factors							
Negative influence of media/ social media							
    High	41 (57.7)	30 (42.3)	0.7	0.4–1.4			
    Moderate	93 (57.1)	70 (42.9)	0.7	0.4–1.2			
    Low	63 (64.9)	34 (35.1)	Ref				
Negative perception of politics/policies							
    High	76 (69.1)	34 (30.9)	2.6	1.5–4.7*	1.8	0.8–4.0	
    Moderate	78 (61.4)	49 (38.6)	1.9	1.1–3.2*	1.2	0.6–2.3	
    Low	43 (45.7)	51 (54.3)	Ref		Ref		
Negative perception of pharmaceutical industry							
    High	58 (65.9)	30 (34.1)	1.6	0.9–2.9			
    Moderate	89 (58.6)	63 (41.4)	1.1	0.7–1.9			
    Low	50 (54.9)	41 (45.1)	Ref				
Lack of trust in health system							
    High	52 (69.3)	23 (30.7)	2.6	1.3–4.9*	1.3	0.5–3.5	
    Moderate	106 (61.3)	67 (38.7)	1.8	1.1–3.0*	1.2	0.6–2.4	
    Low	39 (47.0)	44 (53.0)	Ref		Ref		
Individual/group factors							
Negative past experience of vaccination							
    High	65 (67.0)	32 (33.0)	2.1	1.2–3.7*	1.4	0.6–3.2	
    Moderate	80 (62.5)	48 (37.5)	1.7	1.0–2.9*	1.2	0.6–2.5	
    Low	52 (49.1)	54 (50.9)	Ref		Ref		
Negative beliefs, attitudes about influenza and vaccination							
    High	62 (59.0)	43 (41.0)	1.4	0.8–2.5	0.7	0.3–1.5	
    Moderate	86 (67.2)	42 (32.8)	2.0	1.2–3.5*	1.4	0.7–2.7	
    Low	49 (50.0)	49 (50.0)	Ref		Ref		
Negative perception of vaccination as a social norm							
    High	78 (68.4)	36 (31.6)	2.2	1.3–3.9*	0.9	0.4–2.3	
    Moderate	70 (59.3)	48 (40.7)	1.5	0.9–2.5	1.1	0.5–2.2	
    Low	49 (49.5)	50 (50.5)	Ref		Ref		
Negative influence of other HCW							
    High	92 (70.2)	39 (29.8)	3.3	1.9–5.7*	2.3	1.1–4.8*	
    Moderate	60 (65.9)	31 (34.1)	2.7	1.5–4.9*	2.1	1.1–4.4*	
    Low	45 (41.3)	64 (58.7)	Ref		Ref		
Influenza vaccination specific factors							
Perceived risk of influenza infection and lack of benefit of vaccination							
    Low	73 (68.2)	34 (31.8)	2.5	1.4–4.5*	1.0	0.4–2.5	
    Moderate	82 (61.7)	51 (38.3)	1.9	1.1–3.2*	0.9	0.4–1.8	
    High	42 (46.2)	49 (53.8)	Ref		Ref		
Risk of adverse events due to vaccination							
    High	55 (73.3)	20 (26.7)	2.8	1.5–5.3*	1.6	0.6–4.1	
    Moderate	84 (60.9)	54 (39.1)	1.6	0.9–2.6	0.9	0.5–1.9	
    Low	58 (49.2)	60 (50.8)	Ref		Ref		
Fear of painful injections							
    High	104 (63.8)	59 (36.2)	1.7	1.1–2.7*	0.9	0.5–1.6	
    Moderate	28 (70.0)	12 (30.0)	2.3	1.0–4.8*	1.8	0.7–4.5	
    Low	65 (50.8)	63 (49.2)	Ref		Ref		
Access to vaccines in the hospital							
    Low	64 (66.0)	33 (34.0)	2.0	1.2–3.5*	1.3	0.6–2.8	
    Moderate	71 (66.4)	36 (33.6)	2.1	1.2–3.5*	1.4	0.7–2.8	
    High	62 (48.8)	65 (51.2)	Ref		Ref		
Abbreviations: OR, Odds Ratio; CI, Confidence Interval

aAdjusted OR and 95% CI, and p-values calculated using multivariable logistic regression, controlling for hospital locations to account for clustering

Among the contextual factors, HCWs with negative perceptions of politics/policies and lack of trust in the health system had significant odds of being vaccine-hesitant compared to HCWs with positive perceptions (Table 4). Similarly, in the individual/group influences, significant determinants of hesitancy were negative past experience of vaccination (High—OR 2.1, 95% CI 1.2–3.7; Moderate–OR 1.7, 95% CI 1.0–2.9), moderate level of negative beliefs (OR 2.0, 95% CI 1.2–3.5), high negative perception of vaccination as a social norm (OR 2.2, 95% CI 1.3–3.9), and negative influence of other HCW (High–OR 3.3, 95% CI 1.9–5.7; Moderate—OR 2.7, 95% CI 1.5–4.9). Among the factors specific to influenza vaccines, low perceived risk (Low—OR 2.5, 95% CI 1.4–4.45; Moderate–OR 1.9, 95% CI 1.1–3.2), high risk of adverse events after vaccination (OR 2.8, 95% CI 1.5–5.3), fear of painful injections (High–OR 1.7, 95% CI 1.1–2.7; Moderate—OR 2.3, 95% CI 1.0–4.8), and reduced access to vaccines in the hospital (Low–OR 2.0, 95% CI 1.2–3.5; Moderate–OR 2.1, 95% CI 1.2–3.5) were significantly associated with the hesitancy.

However, in the multivariable model, only age (above 50 years–aOR 3.2, 95% CI 1.3–8.5), fair knowledge (aOR 0.4, 95% CI 0.2–0.8), and negative influence of other HCW (High–aOR 2.3, 95% CI 1.1–4.8; Moderate—aOR 2.1, 95% CI 1.1–4.4) remained significant factors of influenza vaccine hesitancy (Table 4). Work experience was not entered in the final model as it showed a high correlation with age.

Discussion

Influenza vaccine hesitancy was highly prevalent among the Thai HCWs in this study, as nearly 60% of the survey participants reported having some degree of hesitancy. Older age and the role of other HCWs were associated with increased hesitancy, while fair knowledge of influenza and vaccination was indicated to reduce hesitancy. The findings of this study can be used to improve local influenza vaccination policy in Thailand.

Since vaccine hesitancy studies are in their nascent stage in Thailand, there are no prior estimates of the prevalence of influenza vaccine hesitancy among the HCWs. Therefore, the proportion of 58.3% found in this study can function as a baseline figure of influenza vaccine hesitancy among Thai HCWs for future reference. Nevertheless, comparisons can be made with past Thai studies regarding the HCW doubts of the influenza vaccines. Nearly 50% of HCWs had some doubts about the influenza vaccine in this current study, which is higher than the 30% reported among Thai physicians in 2017 [29]. In a similar vein, the vaccine acceptance rate in this study was lower than the 65.4% reported among HCWs in a Bangkok hospital [30]. Although these comparisons are limited due to differences in vaccine hesitancy conception, study sites, and the HCW definition, which was expanded to include all types of HCW working in the hospital in this study as opposed to only doctors or medical service providers in the past studies [29, 30], they indicate that HCW in Nakhon Phanom may be more hesitant towards influenza vaccines than normally expected. Our result can be comparable to the 65% influenza vaccine hesitancy reported among community health workers in Southwest China, where, similar to our study, older and complacent HCWs were more likely to be vaccine-hesitant [41]. Nonetheless, similar studies from other countries, such as Egypt, Hong Kong, and South Africa, report influenza vaccine hesitancy among HCWs to be below 50% [42–45].

While the proportion of hesitant HCWs in this study is alarming, the proportion of HCWs who actively delayed and refused vaccination was only around 11%. Most of the hesitant HCWs were those who were skeptical of the influenza vaccine but still received the vaccination. A possible explanation for this phenomenon may be that although there isn’t a mandatory vaccination for HCWs and there is a notion of HCW’s choice, in reality, the HCWs often end up taking the influenza vaccines as an obligation, particularly as Nakhon Phanom is a “model” province for influenza vaccine research in Thailand where vaccination rates are supposed to be higher.

In this study, the role of other HCWs, such as the medical doctor, vaccinator nurses, or senior staff, was a significant predictor of influenza vaccine hesitancy. This is an important finding as it suggests that HCW vaccine hesitancy can be potentially reduced when HCWs, such as medical doctors and supervisors, provide positive feedback and peer support to their fellow HCWs. Medical doctors have a higher social class [46], and along with vaccinator nurses, senior HCWs have more social capital to be influential in social interactions with other HCWs in hospital settings [47]. As many studies indicate, the acceptance of influenza vaccination among this group is likely to be transferred to their HCW colleagues. For example, supervisor and physician encouragement has been found to be a key predictor of HCW vaccination [48]. The strategy of using influential HCWs and senior staff was found to improve HCW vaccination in research conducted in countries such as Spain and Canada [49, 50]. Similarly, in Israel, a randomized controlled trial showed that an intervention comprising of a lecture from a family physician, in addition to e-mail reminders, and a personal approach from a key local staff (doctor or nurse), was able to increase the odds of influenza vaccination among HCW by 3.51 (95% CI 2.03–6.09) compared to the control group [51]. Our study also provides supportive evidence that increasing knowledge of influenza disease and vaccine may help to reduce hesitancy to a certain extent, particularly when combined with support from an influential senior HCW.

The social capital of senior HCWs (i.e., the capital derived from one’s social position and status) may explain why the vaccine-hesitant HCWs were more likely to be older than 50 years in our study. Using Bourdieu’s concept of social capital [52], it can be hypothesized that when this group of experienced and senior HCWs becomes influenza vaccine-hesitant, they can exert their power to either resist (i.e., refuse) or negotiate (i.e., delay) taking vaccines. Hesitant HCWs of this group may have more options instead of being confined to the government vaccines and thus have more power to choose. In previous research, vaccine hesitancy was viewed as a form of symbolic capital that helped to understand and elaborate on the social processes, uncertainties, and difficulties in various vaccine-related journeys [53]. While in this study, the older HCW’s accrued social capital with the virtue of their seniority and social networks built in the hospital for many years may have provided them with more power to resist the vaccination policy and the approaches of junior vaccinators. The higher social standing of the older HCWs may be the reason why they could overtly display their hesitancy, while the younger HCWs may have had to keep it hidden. This hypothesis, however, needs to be further explored and corroborated by other studies.

Overall, this study contributes to the growing literature on vaccine hesitancy and presents the situation of HCWs in a rural northeastern province in Thailand. This study has been reported here in accordance with the STROBE statement on cross-sectional studies (S3 Table). Nevertheless, there are some limitations in the study. First, the research was conducted after the first wave of coronavirus disease 2019 (COVID-19) in Thailand. This presented different logistic hurdles and time delays in conducting the survey. More importantly, the emergence of COVID-19 might have affected some HCWs’ influenza vaccine decision-making, which was not captured in the survey data as the questionnaire was designed in the pre-COVID period. Second, there may have been a potential selection bias as the data was collected exclusively in the daytime, and the HCWs working night shifts were unable to be included. Although stratified random sampling was used in the survey, which accounted for all staff working in the hospital and gave the HCW working at night time an equal probability to get enrolled, cross-sectional data collection in the daytime may have limited their participation. Finally, a small number of samples in some HCW categories reduced the statistical power of the survey to draw valid comparisons between the HCW types. Nonetheless, the survey provided a representative sample of HCWs of the province selected by a multistage cluster sampling using probability proportional to HCW size in the hospitals.

In conclusion, a high proportion of HCWs had some form of hesitancy towards influenza vaccines. The findings of this study can be used as a baseline to monitor the changes in the level of vaccine hesitancy of Thai HCWs in future studies. Public health strategies and interventions informed by the study findings may be more effective in reducing influenza vaccine hesitancy among Thai HCW.

Supporting information

S1 Table HCW influenza vaccine hesitancy determinant items (5 point Likert scale).

(PDF)

S2 Table Response rates from each of the study hospitals.

(PDF)

S3 Table STROBE statement—Checklist of items that should be included in reports of cross-sectional studies.

(PDF)

S1 File Influenza vaccine coverage by province.

(XLSX)

We are grateful to the HCWs who participated in the study and the focal points at the six hospitals who helped in conducting the survey.

10.1371/journal.pone.0310761.r001
Decision Letter 0
Aljamaan Fadi Academic Editor
© 2024 Fadi Aljamaan
2024
Fadi Aljamaan
https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Submission Version0
1 May 2024

PONE-D-24-10541Influenza vaccine hesitancy among healthcare workers in a Northeastern province in Thailand: Findings of a cross-sectional surveyPLOS ONE

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Please respond to the comments of reviewer 2 who raised many major points in methodology and results interpretation before we progress to second cycle of revision, regarding reviewer 1 I am contacting him whether he meant rejection or no as he did not mention clear reasons of rejection.

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Reviewer #1: Yes

Reviewer #2: Partly

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Reviewer #1: thank you for submitting this work titled Influenza vaccine hesitancy among healthcare workers in a Northeastern province in Thailand: Findings of a cross-sectional survey which Background: Healthcare workers (HCWs) are an important target group for influenza

36 vaccination due to their increased risk of infection. However, their uptake remains a challenge.

37 This study aimed to identify and measure influenza vaccine hesitancy among HCWs in Nakhon

38 Phanom province, Thailand.

39

40 Methods: A representative cross-sectional survey was conducted during August – September

41 2020, among 350 HCWs at six hospitals in the province selected by a two-stage cluster

42 sampling using a self-administered questionnaire. HCWs who either delayed getting influenza

43 vaccines, accepted the vaccines but were unsure, or refused the vaccine with doubts were

44 categorized as hesitant. HCWs who accepted the influenza vaccine without any doubts were

45 classified as non-hesitant. Determinants of vaccine hesitancy were identified by a multivariable

46 logistic regression analysis.

47

48 Results: A total of 338 participants (97%) filled the questionnaires. The mean age of the

49 participants was 37.2 years. Most participants were female (280; 83%), nurses (136; 40%),

50 working at district hospitals (238; 71%), with bachelor’s degree (223; 66%), and without any

51 pre-existing chronic medical conditions (264; 78%). Influenza vaccine hesitancy was evident

52 among nearly 60% of the participants (197/338), who had varying patterns of hesitancy.

53 Significant factors of influenza vaccine hesitancy were found to be age above 50 years

54 (adjusted odds ratio [aOR] 3.2, 95% CI 1.3-8.5), fair knowledge of influenza and vaccination

55 (aOR 0.4, 95% CI 0.2-0.8), and negative influence of other HCW (High level– aOR 2.3, 95%

56 CI 1.1-4.8; Moderate level- aOR 2.1, 95% CI 1.1-4.4).

57

58 Conclusion: Influenza vaccine hesitancy was highly prevalent among the Thai HCWs in

59 Nakhon Phanom province. Imparting updated information to the HCW, in combination with

60 positive guidance from influential HCWs in the hospital, may help reduce hesitancy. These

61 data may be useful to the National Immunization Program to design appropriate approaches to

Reviewer #2: Thank you for this important work. Please, find my comments below

1. On what basis did the authors include those who “accepted the vaccines but were unsure” as HESITANTS. Can you cite any reference/guideline/consensus statement for this? And what is the actual number of the study participants who fall into this category? Lumping those who indicated acceptance but were unsure cannot be accurate since the concept of vaccine acceptance/hesitancy itself is dynamic being determined by many other external influences. And I think this may be the reason why only 3 factors were significantly associated with hesitancy in the final adjusted model, with the age factor being an odd finding with respect to the overwhelming findings of previous studies.

2. Can the authors specifically define what they mean by “acceptance”, whether, for example, the term includes those already vaccinated plus unvaccinated who are willing to be vaccinated, or whether the term refers only to unvaccinated who are willing to be vaccinated?

3. Can the authors provide a reference for their affirmative statement “…acceptance of vaccination by HCWs themselves is, therefore, also an important determinant of influenza vaccine uptake in the populations that they serve”

4. Please cite the webpage/URL for your statement in line 101-103, “However, in 2018, regional reports showed that HCW influenza vaccine coverage had plummeted to below 30% in some regions (Department of Medical Services [DMS], MOPH)”.

5. If the “mixed-methods study”, which the present study is said to be part of by the authors has been published, please cite it were you said this.

6. Why would the authors say “As there was no prior estimate of influenza vaccine hesitancy among Thai HCWs” in line 160 under Methods section, while in line of the introduction, they wrote “A study 105 revealed that only 60% of Thai HCWs were willing to receive the pandemic influenza (H1N1) vaccine [21]”? Isn’t this a self-contradiction?

7. In your methods, please describe the tool used to assessed knowledge, specify whether it is adapted or adopted and whether it has been validated.

8. In the analysis, have the authors evaluated model fitness? If so, please state which were used, and if not, please explain why.

9. Given that this study was conducted during the early phase of the COVID-19 pandemic, a period that has saw an unprecedented levels of rise in vaccine hesitancy and antagonism, have the authors considered a spillover of this COVID-19 vaccine-related hesitancy into influenza vaccine and all other vaccines?

10. In your Discussion section, please clarify why you would say that there are “no prior estimates of the prevalence of influenza vaccine hesitancy among the HCWs” despite citing acceptance rates of the same vaccine among the same study population in the same country. Note subtracting these reported acceptance rates gives you the hesitancy rates, right?

11. The probable reason(s) for higher odds of hesitancy in HCWs age >50years (who at higher risk of the infection than those below) need to be better hypothesized in your Discussion. I think this finding may be related to the inaccurate analysis that lumps “those who accept but were unsure” as hesitants.

I look forward to reading the revised version of this manuscript.

Best

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Reviewer #1: No

Reviewer #2: Yes: Dr. Sahabi Kabir Sulaiman

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10.1371/journal.pone.0310761.r002
Author response to Decision Letter 0
Submission Version1
14 Jun 2024

A rebuttal letter in the form of a response to reviewers has been submitted as a Word file, and appropriate changes have been made to the manuscript.

Attachment Submitted filename: Response to Reviewers.docx

10.1371/journal.pone.0310761.r003
Decision Letter 1
Ahmed Sirwan Khalid Academic Editor
© 2024 Sirwan Khalid Ahmed
2024
Sirwan Khalid Ahmed
https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Submission Version1
27 Aug 2024

PONE-D-24-10541R1Influenza vaccine hesitancy among healthcare workers in a Northeastern province in Thailand: Findings of a cross-sectional surveyPLOS ONE

Dear Dr. Praphasiri,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

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Reviewer #2: All comments have been addressed

Reviewer #3: (No Response)

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Reviewer #2: Thank you for revising this work. I have gone through the revision and its supporting responses and I agree with them. I have no new comments. Looking forward to seeing the published work online.

Best

Reviewer #3: 2. How the author makes sure that the participants were not biased towards specific answer

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10.1371/journal.pone.0310761.r004
Author response to Decision Letter 1
Submission Version2
4 Sep 2024

The rebuttal letter has been added in the attached files as "Response to Reviewers".

Attachment Submitted filename: Response to Reviewers.docx

10.1371/journal.pone.0310761.r005
Decision Letter 2
Ahmed Sirwan Khalid Academic Editor
© 2024 Sirwan Khalid Ahmed
2024
Sirwan Khalid Ahmed
https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Submission Version2
6 Sep 2024

Influenza vaccine hesitancy among healthcare workers in a Northeastern province in Thailand: Findings of a cross-sectional survey

PONE-D-24-10541R2

Dear Dr. Praphasiri,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

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PLOS ONE

Additional Editor Comments (optional):

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10.1371/journal.pone.0310761.r006
Acceptance letter
Ahmed Sirwan Khalid Academic Editor
© 2024 Sirwan Khalid Ahmed
2024
Sirwan Khalid Ahmed
https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
11 Sep 2024

PONE-D-24-10541R2

PLOS ONE

Dear Dr. Praphasiri,

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now being handed over to our production team.

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on behalf of

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Academic Editor

PLOS ONE
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