1 Introduction

Vaccine hesitancy has been recognized as one of the global health problems. It may undermine the establishment or sustainability of herd immunity, which necessitates vaccinating a significant fraction of the overall population. An important issue related to vaccination hesitancy and inadequate herd immunity is that people who are not vaccinated might serve as reservoirs for the virus [1]. They have the potential to trigger further waves of infection, impeding the progress in limiting the transmission of a virus to the whole populace [2]. Models have predicted significant negative impact of the vaccine hesitancy on the mortality due to COVID-19 pandemic [3]. Various tools measure vaccine hesitancy and confidence among different population groups [4]. However, the literature on vaccine hesitancy in low-middle-income countries like India is limited and depends on parents' perception of child vaccination [5, 6]. This may be because adult vaccination, apart from the Tetanus diphtheria (Td) given for pregnant women, is not under a universal immunization program or widespread. Anti-rabies and Td vaccines are currently provided to the prescribed adults under the public health systems. The Hepatitis B vaccine (HBV) is being recommended for persons employed in high-risk areas such as healthcare delivery settings. Human Papilloma Virus (HPV) vaccine is being piloted and advocated for adoption in the Indian setting to prevent cervical cancer [7]. With the advent of COVID-19 and the COVID-19 vaccines, the scenario in adult vaccination has changed. Universal COVID-19 vaccination is being done in public and private healthcare settings. In addition to the lack of awareness, affordability and availability [8, 9], vaccine hesitancy has been proposed as one of the potential reasons for poor adult vaccination uptake in India [10, 11]. The hesitancy toward the COVID-19 vaccine has been expressed in countries like USA [12]. In India, Jain et al., reported a vaccine hesitancy of 10.6% for COVID-19 vaccines among medical students [13]. Kumari et al. used a validated questionnaire, which evaluated the knowledge, attitude and determinants of COVID-19 vaccination, among urban dwellers and the younger population who raised concerns about taking the COVID-19 vaccine [14, 15]. Panda et al. attempted to assess the COVID-19 vaccine acceptance and concerns for safety among the adults of Odisha [16]. However, these studies had the following limitations: The tools used were not validated in Indian settings [13, 16], the tool was in the English language, and data was collected through google forms, thus limiting the validity among the population who are not aware of such technological aspects [13, 15, 16]. Though, the number of people speaking English is on the rise in India, English is not the common language in India, and it has a strong affiliation with privileges such as higher socio-economic status, age and urbanized society in India [17]. Hence, the results of these studies have limited internal and external validity. Hindi has been one of the languages of the masses and the scheduled language in India, spoken by 528 million [18]. The majority of the Hindi speakers reside in northern India. However, no validated tool is available to assess vaccine hesitancy among the Hindi-speaking population of India. In this background, to enable accurate and easy assessment of vaccine hesitancy among adults, validation of the Hindi vaccine hesitancy questionnaire, encompassing multiple sub-domains of vaccine hesitancy, is a pre-requisite. Hence, we conducted the following study to translate and determine the reliability, content, construct and concurrent validity of the Hindi Adult Vaccine Hesitancy scale (5C) among adults in Northern India.

2 Materials and methods

2.1 Study design

The present study follows a cross-sectional study design. It is a validation study conducted during October 2021-March 2022.

2.2 Study area

Indira Colony (IC), Manimajra, Chandigarh (Union Territory), India. It caters to a population of 23,204. Primary health care services are provided to the population through an Urban Health Training Centre. This specific area and population were chosen, since it was the field practice area of our department, which had the official memorandum of understanding with the local health authorities to undertake research and deliver healthcare services.

2.3 Study tool

5C questionnaire is a tool to assess vaccine hesitancy that has been psychometrically validated among adults speaking English and Germany. It is a 15-item questionnaire spread across five factors known as 5Cs. The 5C scale expands the scope of available measures and covers the broader theoretical conceptualization of vaccine hesitancy & acceptance, and the said tool is freely available on the online repository of the ‘Open Science Framework’ [19]. It measures vaccine hesitancy under the following five sub-domains: confidence (C1), complacency (C2), constraints (C3), calculation (C4) and collective responsibility (C5). Each of the domains had three items. Each item is answered on a Likert scale ranging from 1 to 7.

2.4 Methodology

The present study was conducted in sequential steps: Translation to Hindi, cognitive interviews using the translated tool, content validation by the experts, construct validation and concurrent validation. (Fig. 1).

  • A. Translation to Hindi [20]

Fig. 1
figure 1

Steps followed in validating the Hindi 5C vaccine hesitancy tool. *Expert committee members- The translators involved in forward and back translations and two of the investigators

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The English 5C questionnaire was translated to, and back translated from Hindi by two different sets of translators. The forward translation was done by two independent translators (One medical expert- MET 1 and one translator with non-medical background- NMT-1) who were bilingual in Hindi & English, with Hindi as their mother tongue. The translations were collated, and the discrepancies found were discussed with the forward translators and adjudicated by one of the investigators (TK). The consensus version of the Hindi translation of the questionnaire was sent to a different set of translators (One medical expert- MET 2 and one translator with non-medical background- NMT-2). They were bilingual in Hindi & English, with English as the medium of education from the primary level till their post-graduation. The forward and back-translated versions of the questionnaires were compared with the tool's original version in the source language (SL), English. The identified discrepancies were discussed by the expert committee comprising the translators involved in the process (MET 1 & 2, NMT 1 & 2) and one of the investigators (TK). The consensus arrived had been taken as the final Hindi version of the 5C tool, post-translation exercise (Fig. 1).

  • B. Cognitive interviews among target population

  • i) Study population

Adult patients (aged ≥ 18 years) and attenders visiting the health centre in the study area. Individuals who did not consent, did not know Hindi and were not the residents (who were migratory), were excluded.

  • ii) Cognitive interviews

The items, responses and instructions of the translated Hindi tool were pre-tested among 10 eligible participants by cognitive interviews under the aspects of comprehension and relevancy. Comprehension of each item, instructions and the responses were scored on a scale of 1–3 as ‘highly clear’, ‘somewhat clear’, ‘not clear’. The participants were asked to answer the items they understood clearly, and the same was scored ‘highly clear’. If they did not understand the item, they were asked to mark the question and move on without answering it, which was scored as not clear. If they understood the item but had doubts or were not able to understand certain words/phrases in the item, they were asked to mark the specific words/phrases, and this was scored as ‘somewhat clear’. Once the participants completed the tool, a cognitive interview was conducted with them by discussing each item of the tool. Questions were posed on what they understood by that item, and verified whether their understanding is in line with the content of that item in the 5C tool. If the participants found a particular item to be ‘not clear/somewhat clear’ or their understanding was different from that of the intended purpose of the item, then they were explained in detail the intended meaning of the item by the interviewer. Following this, the participants were asked to give suggestions and better words/phrases that would convey the intended meaning in a way their peers from the community could understand. The relevance of the items was assessed on a scale of 1–3 as ‘relevant’, ‘somewhat relevant’, and ‘irrelevant’ during the cognitive interviews. The relevance was explained to the participants as ‘whether they believed that that specific item was related or can contribute towards identifying/assessing the concept of vaccine hesitancy for them in specific, and their community in general’. The participants' qualitative comments were written down and recorded in audio after obtaining their verbal consent [20]. At the end of the cognitive interview, the item(s) which have been flagged as unclear (not clear/somewhat clear) and irrelevant (irrelevant/somewhat relevant) by more than 20% of the participants were re-phrased based on the analysis of the qualitative inputs of the participants and re-evaluated among another set of 10 participants from the study population [20]. Three rounds of such cognitive interviews were conducted by taking in the inputs from the participants of the initial rounds till we achieved a sufficient proportion (> 80%) of participants that had exhibited comprehension and relevancy for all items [20].

  • C. Content validation

At the end of the cognitive interviews, we obtained the pre-tested questionnaire, which was sent for content validation to the expert panel of 10 members. Content validity is defined as the "ability of the selected items to reflect the variables of the construct in the measure" [21]. The panel had a mix of medical and paramedical experts and professionals working in public health and vaccines, with Hindi as their mother tongue. The content validation panel comprised two community physicians, one community medicine specialist, one family medicine cum community medicine specialist, two community medicine faculty, two public health professionals, one gynecologist and one public health nursing specialist. The content was evaluated for relevance and comprehension. To establish relevance, the items on the scale were rated on a scale of 1–4 as ‘Highly relevant’, ‘quite relevant’, ‘somewhat relevant’, ‘not relevant’. For assessing the comprehension of each item, instructions and the responses were rated on a scale of 1–4 as ‘Highly clear’, ‘quite clear’, ‘somewhat clear’, ‘not clear’, and the comprehensiveness of the whole tool. The experts' suggestions and inputs on the unclear (scored 1,2) and irrelevant (scored 1,2) questions were obtained using qualitative comments in the text [20]. Content Validity Index was calculated based on the scoring of the relevancy- Item wise CVIs (I-CVI) and full-scale CVI (S-CVI). Item-wise, CVI was calculated using two methods: The proportion of experts who scored the particular item as relevant [22], and the Kappa statistics to eliminate any agreement by chance between the panelists. An I-CVI was ≥ 0.78 was considered adequate content validity for the items [22]. Evaluation criteria for kappa are the values above 0.74, between 0.60 and 0.74, and the ones between 0.40 and 0.59, which are considered excellent, good, and fair, respectively [23]. S-CVI was assessed by S-CVI/Ave (Average method), a standard approach for calculating the S-CVI [22]. An S-CVI/Ave value of ≥ 0.90 was considered to have excellent content validation [22].

  • D. Confirmatory factor analysis and construct validity

  • i) Sample size and sampling technique

Based on the previous literature, taking a subject: item ratio of 10:1, a sample size of 150 was taken [24]. Our study tool had 15 items. It has been reported that previous studies have taken this study subjects to item ratio ranging from as low as 2:1 (two study subjects per item) to 20:1 (20 study subjects per item). It has also been reported that while conducting confirmatory factor analysis (CFA), the recommended minimum sample size is 150 [24]. Hence, considering the above guidelines from the previous literature on validation studies and our resources, we took 150 (10 study subjects per item 10:1) as the minimum sample size required for our study. Consecutive enrollment of all the eligible and consenting persons was done till the sample size was achieved.

  • ii) Statistical analysis for establishing internal consistency and construct validity:

The content-validated questionnaire was administered among the 150 eligible participants [20, 25]. The participants were the consecutively selected consenting individuals attending the OPD. Since the health centre, where the study was undertaken provided specific services on certain days of a week, in order to ensure that we covered adults visiting all clinics and services, we distributed the data collection period all through the week. A maximum of 10 participants per day were included in the study. These were done to ensure adequate representation of all kinds of adults attending the health centre for availing various services. A trained interviewer administered the questionnaire to the participants. The investigators (AG & RG) trained the interviewers on each item of the scale and the method of conducting the interviews. The investigators debriefed the interviewers at the end of each day's data collection. The construct validation process, which measures the degree to which the particular measure is consistent with theoretical evidence [26], was carried out by employing the CFA method using IBM SPSS Amos version 23.0 [27]. Usage of CFA for assessment of construct validity is not only helpful in adding a statistical precision to the instrument/tool, but also confirms the different domains of the tool (5C tool in this study) through the evaluation of convergent and discriminant validity [27].

The convergent validity was examined using the Average Variance Extracted (AVE) to verify if the items of a particular factor were related to that factor. Values above the cut-off value of 0.50 indicated good convergent validity [28]. The discriminant validity was analyzed to understand the level of distinction between factors. As per the prescribed guidelines, the AVE should be greater than the square of the latent variable correlations [28]. (AVE should be ≥ r2) for the establishment of discriminant validity. The reliability of each domain of the scale was assessed by employing internal consistency through the Composite Reliability values (CR ≥ 0.70) [28].

  • iii) Goodness of fit measures

In order to determine whether the model had a good fit, the following goodness of fit indices, which are usually calculated while employing CFA were examined [29]; the Goodness of fit (GFI) and its adjusted measure; the Root Mean Square Residual (RMR), Tucker-Lewis Fit Index (TLI) especially used for relatively low sample size (less than 300); the Comparative Fit Index (CFI) were employed, We used ≥ 0.90 as cut off for GFI, AGFI, TLI and CFI measures, while the cut off values ≤ 0.08 was used for RMR [29, 30]. Additionally, for the final model comparison, the Parsimony Comparative Fit Index (PCFI) was used, where an index value between 0.60 and 0.80 suggests a good model fit, and an index value above 0.80 suggests a very good model fit [29].

  • E. Concurrent validity

Concurrent validity was assessed by asking the participant whether they would take the vaccine if their physician recommended it. The response was coded on a scale of 1–5, from “definitely no” to “definitely yes”. The score was then correlated against the domain scores of the 5C tool. Spearman correlation coefficients were calculated.

2.5 Ethical considerations

Ethical approval to conduct the study was obtained from the Institute Ethics Committee, PGIMER, Chandigarh (Reference No: NK/7149/Study/212) approved on March 12, 2021. After assuring the confidentiality of the data, written informed consent was obtained from all the participants. All the procedures adhered to the ethical guidelines of the Helsinki Declaration. The STROBE statement check list is included in the Additional file 1.

3 Results

The summary outcomes of the forward and back translation results and cognitive interviews are tabulated (Additional file 2: Table S1). In terms of content validity, the I-CVI and kappa statistics of all items of the tool ranged from 0.8 to 1.0. The S-CVI/Ave was calculated to be 0.97. The above findings revealed a sufficient content validity of the individual items and the overall 5C tool among the Hindi-speaking population of our study.

The median age of the study participants included for the construct validity was 33 years. Females formed the majority (75.3%) of the participants. The majority of the study participants were homemakers (61.3%), married (88%) and literate (79.3%). (Table 1) The median (Interquartile range) per capita income was Rs 2500 (1666.7,3333.3).

Table 1 Socio-demographic profile of the participants in construct validity
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Construct validity and reliability coefficients revealed through confirmatory factor analysis are presented in Table 2. The composite reliability (CR ≥ 0.70) and convergent validity (AVE ≥ 0.50) coefficients are found to be greater than their cut-off values. Similarly, the AVE of the latent variables was found to be greater than the squared values of the latent variable correlations. These indicate that the 5C tool has good construct validity (reflected by convergent and discriminant validity) along with composite reliability.

Table 2 Measures of internal consistency and construct validity of the 5C tool extracted through the process of confirmatory factor analysis
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The goodness of fit indices for the CFA analysis of the 5C tool is presented in Additional file 2: Table S2. The values of all the required fit measures, i.e., RMR, TLI, CFI, PCFI are well above their required threshold levels [29]. This indicates that the overall construct validity and reliability of the 5C tool in the Indian setting has a good fit as established through confirmatory factor analysis. However, both the GFI (0.803) and AGFI (0.738) values are marginally below the threshold value (0.9), but GFI and AGFI are upward biased based on the sample size [31]. Therefore, subjecting the 5C tool to a similar larger Indian setting would ultimately lead to an increase in the GFI and AGFI values. The coefficients for the full model are presented in Fig. 2.

Fig. 2
figure 2

Standardized individual parameters as per results of Confirmatory factor analysis. C1-Confidence; C2- Complacency; C3- Constraints; C4- Calculation. C5- Collective responsibility

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To summarize the key findings of the results, the I-CVI and Kappa statistics of all tool items ranged from 0.8 to 1.0. The S-CVI/AVE also came out to be 0.97, which are well above their prescribed recommended values, thereby indicating good content validity. The composite reliability (CR ≥ 0.70) and convergent validity (AVE ≥ 0.50) coefficients were also found to be adequate. The AVE of the latent variables was greater than the squared values of the latent variable correlations, indicating adequate discriminant validity. The validity and reliability parameters were in line with predefined cut-off values in most of the goodness of fit indices values, thereby reflecting that 5C tool in the Indian setting demonstrated a ‘good fit’ established through confirmatory factor analysis.

3.1 Concurrent validity

There was a significant positive correlation of the willingness to take recommended vaccines with the confidence, calculation and collective responsibility domains. In contrast, a negative correlation was found with the complacency and constraint domains of the 5C tool (Table 3).

Table 3 Concurrent Validity reflecting the correlation between the 5C domains and the willingness to take recommended vaccines
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4 Discussion

The pattern and impact of vaccine hesitancy are context and case-specific in each country, thus making it largely unpredictable and subjecting it to extrapolation between countries and populations will not give an accurate picture [32].

The present study translated and validated the Hindi version of the 5C vaccine hesitancy questionnaire for adults in an Indian setting. Hindi, the official language prescribed in the Indian constitution, is widely spoken and understood by the Indian population. This is the first adult vaccine hesitancy tool to be validated in the Hindi language in India and a validated tool from low-middle-income settings. Vaccine hesitancy is being taken beyond the domains of confidence and safety through the 5C tool [19]. The forward and backward translation of the 5C tool in Hindi was an essential and intensive task. Some technical words were translated into simpler expressions, and in some instances, the long sentences were broken down into short simpler local Hindi words for maximum comprehensibility by the target population, which had a sizable illiterate (20.8%) group, or studied largely up to middle school level (32%). Several rounds of translations followed by cognitive interviewing were done to ensure that the integrity and the content of the translated questions remained consistent with the original English version of the 5C questionnaire.

The Arabic version of the 5C tool also showed validity and reliability outcomes, similar to our study [33]. However, the Arabic study used Cronbach's alpha to test the reliability, while we applied the composite reliability coefficient. This was because we applied ‘Confirmatory Factor Analysis' (CFA), a more elaborative and robust technique for establishing the construct validity and composite reliability [34]. CFA results indicated reasonable levels of reliability and validity of the Hindi version of the 5C tool in the Indian setting. One major methodological difference between the validation of the English version and the current study is that we administered the tool through the interviewer while they used the self-administration technique. The investigators consciously adopted this change in methodology since India has around ≈27% of the illiterate population [35]. The interviewer's administration of the translated 5C tool assured accurate responses from our study population, who was considerably illiterate and less educated, as discussed above. Kumari et al. validated a self-administered English language questionnaire in India for COVID-19 vaccine concerns among adults in India, but the tool was restricted to a small group of a sophisticated population [14]. The direction of correlation in the concurrent validity of individual domains was in line with that of the expected measures [25]. The constraint domain had the maximum correlation with vaccination willingness in the current settings. Further, it was observed that comparatively the composite reliability value for 5th domain (C5) is slightly less than the values for other domains. It might be due to the nature of the domain (‘collective responsibility’), which primarily is more subjective as it depends largely on the personality characteristics and attitude of the individual towards collective and community good. Therefore, the composite reliability values have differed for C5 domain in comparison to other domains. Nevertheless, it is still above the predefined cut off value of 0.70, thereby indicating good composite reliability for this domain as well.

Our study is not without limitations. Since, it was a cross-sectional study, predictive validity could not be elicited. The domains of 5C correlate differently with different individual vaccines [19]. The varied correlation of the domains of the 5C tool with individual vaccines was not assessed in the present study, which needs to be considered in future studies. There are multiple other languages in India that are spoken by crores of people for whom the current validation is not applicable. Even though several rounds of translations were undertaken, there may be a slight possibility of translation not being simple enough for the target population owing to the presence of some technical words in the original English version of the 5C tool. This is because sometimes there is a lack of exact words in the local/Hindi language which can best describe the content of that English word in the original tool. The comprehensibility of the word then rests upon the substitute word and the interviewer's expertise in communicating it to the respondents. Another limitation is that, only the participants who were visiting the healthcare facility were included, hence a selection bias might be there in the study.

The present study is a maiden attempt to validate the translated Hindi version of the 5C vaccine hesitancy tool for adults in a North Indian setting. The validity values can increase with a large sample size with a considerably more literate population. The study leaves scope for future research in translating and validating the Hindi tool in a broader population with different social factors since many dialects of Hindi are spoken across the Indian subcontinent. Also, it provides a window of opportunities to translate the English version into many different languages that are spoken in India for a broad cross-cultural adaptation and validation.

5 Conclusion

The present study has validated the Hindi version of the 5C scale in North Indian city of Chandigarh, which can be used to assess vaccine hesitancy among the Hindi-speaking population of India as well. The tool can be adopted in the routine and research settings to identify the overall as well as individual domains of vaccine hesitancy which need to be worked upon in the local settings. Further follow-up studies need to be conducted to elicit the predictive validity in the current settings and the appropriateness of the tool's validity in other Indian settings.