Role of COVID-19 Caller Tune and Intention to Get Vaccinated: An Application of the Health Belief Model

Abstract

This study examined the persuasive healthcare communication of COVID-19 vaccination using mobile phone caller tunes as cues to action in intention to get vaccinated. Results indicate that caller tunes have a significant impact on only two constructs of the health belief model (HBM)—perceived benefits and self-efficacy—which can lead to getting vaccinated. However, the individual’s perception of barriers, severity and susceptibility was not found to be influenced by the caller tunes. The study was conducted with a sample of 334 drawn from India who were in the process of getting vaccinated at the time of the data collection. Our analysis reveals that a well-designed caller tune message by incorporating aspects of all constructs of HBM may have a bigger impact in such an unprecedented crisis. There is a dearth of research focussing on the relevance of cues to action in public health communication, and our study is an attempt to address this gap.

Keywords

Healthcare communication health belief model cues to action caller tunes self-efficacy COVID-19 pandemic

Introduction

The scale and magnitude of disturbance caused by the COVID-19 pandemic since its emergence in December 2019 have been a matter of international concern. Health, economic and social systems have been severely impacted (Kataria et al., 2021). The pandemic knows no borders, and COVID-19 has disrupted the countries’ healthcare systems across the globe, irrespective of their economic status. Vaccine intervention is the most efficient preventive measure to restrict the spread of transmittable diseases (Puri et al., 2020). The way to control the circulation of the disease is to get the maximum number of people vaccinated (Alagoz et al., 2021). However, hesitancy in the willingness to get vaccinated has been a significant challenge confronted by the public health institutions worldwide involved in administering vaccines to control the pandemic (Dhama et al., 2021). The only way to overcome the reluctance among people to get vaccinated is to improve awareness about the benefits of vaccination. An effective way to create awareness among people about vaccination is through public health campaigns. To gain people’s trust, governments must share the advantages of vaccination and distribute the vaccines. Mass media and social media have played an essential role in conducting healthcare campaigns (Wakefield et al., 2010).

Various governments initiated a range of healthcare communication to create awareness. Coordinated healthcare communication is a critical enabler in educating people about the severity of the infection. A novel approach by the Government of India in aiding the uptake of COVID-19 vaccines was through mobile phone caller tunes. The caller tunes were produced in several local languages, which proved to be a cost-effective as well as time-effective strategy for promoting vaccination (Appiah et al., 2021). The typical caller tune is replaced by a message promoting the vaccination in this context. The nationwide COVID-19 vaccination drive in India has been the world’s most extensive vaccination programme both in scale and reach. India bears an overwhelming 17.7% (1.39 billion) of the world’s population, and vaccination has therefore been a challenge (Choudhary et al., 2021). As the nation with the second-highest population, vaccine hesitancy among a small percentage of the population would translate to millions of unvaccinated individuals which could overwhelm the healthcare system in India (Sheikh et al., 2021). Mistrust and misinformation fuel vaccine hesitancy (Solis Arce et al., 2021), and a well-executed healthcare campaign can reinforce trust.

The quick spread of this infection globally became a source of public worry and ambiguity, creating panic. This resulted in urgency among people to gather more health information and apply it. Further, it led to the adaptation of preventive behaviour at a fast pace (Elgzar et al., 2020; Paakkari & Okan, 2020). To formulate comprehensive and effective strategies that encourage the adoption of COVID-19 vaccines, it is crucial to recognise the factors influencing people’s intention to get vaccinated. The health belief model (HBM) was developed in the early 1950s by the U.S. Public Health Service to recognise the resistance of people to accept disease prevention approaches and take preliminary tests for early diagnosis. This has been one of the most extensively employed theories in understanding health and illness behaviours. According to the HBM, the chances of an individual adopting the intended behaviour depend on the belief in a personal threat from illness and the success of the recommended behaviour for mitigating the threat. The constructs involved in the HBM include perceived susceptibility, perceived severity, perceived benefits and perceived barriers (Rosenstock, 1974). Many researchers have modified the original HBM involving four primary variables over the years in different contexts. Subsequently, two more factors, that is, cues to action and self-efficacy, were included (Rosenstock et al., 1988).

Cues to action is a factor that prompts individuals to engage in the desired health behaviour. It is the least-studied, rarely measured or researched construct in the HBM. It varies from experiencing symptoms (internal cues to action) to receiving signals from the media, friends, family members or a healthcare provider (external cues to action) (Gerend & Shepherd, 2012). According to Mercadante and Law (2021), the external ‘cues to action’ impact individuals’ preventive health behaviour. Having identified this research gap and the absence of such related studies in the country, this study was conceived to assess the impact of mobile caller tunes on COVID-19 preventive health behaviour. The present study explores the role of external cues to action, that is, mobile caller tunes, in this case, to spread the awareness of vaccine uptake during the COVID-19 pandemic. The main objective of this paper is to explain how the constructs of the HBM can be used to motivate people to get vaccinated. It was hypothesised that a mobile caller tune as a cue to action has a significant impact on the HBM constructs: perceived benefits, perceived severity, perceived barriers, perceived susceptibility and self-efficacy, leading to vaccination.

India is one of the few countries which used mobile caller tunes as a tool for awareness of preventive behaviour during the pandemic. For this study, a questionnaire was circulated for data collection among 500 people in India. Proper responses were obtained from 334 people who were still in the process of getting vaccinated. Our research suggests that a caller tune that is transparent, accurate and timely goes a long way in eliminating misconceptions, myths and misinformation. The caller tunes can be enhanced to significantly highlight the other HBM constructs to impact vaccination drive acceptance. It aids in boosting the individual’s confidence in such an unprecedented situation.

In this research paper, the relevant literature about the critical characteristics of HBM and cues to action is presented. This is followed by the methodology used in this research study, data analysis, discussion and theoretical as well as practical implications.

Literature Review

Health Belief Model

The HBM is a conceptual framework that can direct initiatives for disease avoidance, wellness promotion and disease prevention programmes. The HBM is one of the first theories developed exclusively for explaining and predicting an individual’s changes in health-related behaviours (Glanz et al., 2002). It is considered as the basis of organised and concept-based research in the field of health-related behaviour (Chen & Land, 1986; Hochbaum et al., 1992; Kharrazi et al., 2009). Since its development, HBM has been employed in various public health settings. HBM has been used in contexts such as undertaking Pap-test for screening of cervical cancer (Hay et al., 2003), undergoing mammography for screening of breast cancer (Simon & Das, 1984), examination of oneself (Umeh & Rogan-Gibson, 2001), quitting smoking (Li et al., 2003), usage of contraceptives (Lowe & Radius, 1987), eating a healthy diet (Deshpande et al., 2009), flu vaccine (Shahrabani et al., 2009) and COVID-19 vaccine (Alobaidi, 2021; Tao et al., 2021). Numerous domains and a wide range of people have verified the model’s capacity to explain and predict a variety of health-related behaviours (Carpenter, 2010; Janz & Becker, 1984). The approach has also been applied to the creation of numerous effective health mediations (Loke et al., 2015; Skinner et al., 2015). Ideally, the result of the HBM is to develop and provide community-based support to positively affect health behaviours and health outcomes (Houlden et al. 2021).

The HBM was created during the 1950s (Rosenstock, 1974). It is an expectancy-value model that has been implemented in various public health situations over the years. According to the HBM, an individual’s perceived risk from a disease is determined by the vulnerability to the disease and its seriousness. People will most probably take preventive action if they perceive that the danger of health risk is serious and feel they are personally prone to it. Preventive action will have a more considerable impact when there are more benefits to engaging in it than barriers (Champion & Skinner 2008; Rosenstock, 1974). According to the framework by Rosenstock, the likelihood of an individual involved in a health-related behaviour is established by their perception of four variables: perceived susceptibility, perceived severity, perceived benefit and perceived barrier. A person’s perception of their sensitivity to a certain medical condition is known as perceived susceptibility. A person is more likely to undertake a particular health-related behaviour to reduce risk the more they perceive they are at considerable risk. One’s perception of the severity of the medical illness and its unfavourable effects is characterised as perceived severity. A person’s view of the challenges preventing them from engaging in a particular health-related behaviour is referred to as perceived barriers. The idea that a particular health habit can have a favourable impact on outcomes is known as perceived benefits. Cues to action are precise cues required to initiate healthy activity (Mattson, 1999). Extended HBM (EHBM) (Bylund et al., 2012) includes the traditional four HBM variables, cues to action and self-efficacy. Rosenstock et al. (1988) have added self-efficacy to HBM, and it is defined as the individual’s perception that they can execute the advocated behaviour. It is a push that makes people try to achieve a goal with confidence in their ability to do so, even in difficult situations.

Cues to Action

Demographic characteristics and cues to action have an impact on the HBM constructs (Bish et al., 2011). According to HBM, it is assumed that cues initiate the entire motivation process for appropriate health behaviour to action (Norman & Conner, 2005). Cues to action, which assist in raising awareness of the health concern, can be internal like symptoms or external like messages (Janz & Becker, 1984). Perceptions, social cognition and physical indications regarding one’s own health are examples of internal cues (Mattson, 1999). In order to produce the desired action, external cues in healthcare communication use interpersonal interaction and the media (McGuire, 1984). Cues to action are generally contemplated as a superficial aspect of the HBM (Weinstein, 1988). However, researchers need to pay attention to cues to action since it can influence an individual’s beliefs and perceptions about their health. The authors conducted a detailed review of studies published in the last three years, exploring the various contexts in which cues to action was used in the HBM during the COVID-19 pandemic to understand the topic. A total of 34 articles appeared during our search in the Scopus database. However, 19 research papers that are in line with our study are considered for representation in a review of the literature. Table 1 summarises the literature on HBM in the context of COVID-19.

Table 1.

Literature on Health Belief Model (HBM) in the Context of COVID-19.

Author (Year)	Objective	Finding	Country
Carico et al. (2021)	To explain how pharmacists can use constructs of HBM to guide patients’ behaviour in limiting the spread of COVID-19.	Cues to action can be deployed to combat misinformation, limit behaviour, and select healthy behaviour.	USA
Jose et al. (2021)	To understand preparedness measures adopted towards various Governmental activities using HBM.	Cues for action brought in behavioural change. Primary health care approach by the government influenced perceptions of the community and behavioural change as revealed in HBM	India
Shahnazi et al. (2020)	To determine the preventive behaviours based on HBM	Cues to action had significant effects on preventive behaviours	Iran
Mahindarathne (2021)	To identify factors that affect preventive behaviour	Cues to action taken to prevent COVID-19 are influenced positively by perceived benefits, self-efficacy, and general health motivation but barriers have a negative relationship.	Sri Lanka
Tadesse et al. (2020)	To investigate the predictors of COVID-19 prevention practices using the HBM among employees in Addis Ababa, Ethiopia	Factors positively associated with the prevention practices of COVID-19 are cues to action, self-efficacy, income, and perceived barriers.	Ethiopia
Karimy et al. (2021)	To explore preventive health behaviours during the COVID-19 pandemic in Khuzestan using the Health Belief Model	Internal/external cues to action, adoption of preventive behaviours by mass media, social responsibility promote COVID-19 preventive behaviours	Iran
Wang and Lu (2022)	To examine which constructs in the HBM were related to audiences	Popular HBM constructs were barriers, benefits, susceptibility, cues to action, severity, and self-efficacy for vaccination promotion in the audience.	UK
Caple et al. (2022)	To find out the COVID-19 vaccine intent among the people	Motivation, cues to action and external cues to action were important for medical interventions and disease prevention behaviour	Philippines
Youssef Id et al. (2022)	To assess the acceptance and determinants of the COVID-19 vaccine among healthcare workers	Recommendations by health authorities and health facilities positively impacted vaccine acceptance.	Lebanon
Khan et al. (2022)	To explore how the COVID-19 passport is being discussed and perceived on Twitter	Most tweeters had a favourable attitude towards the COVID-19 passports. Unfavourable attitudes were due to a lack of common standard, consensus, and personal freedoms and human rights	Multiple regions: North America, the Middle East, Europe, and Asia
An et al. (2021)	To assess the willingness to get vaccinated using the HBM and the theory of planned behaviour (TPB)	More acceptance of the vaccination rose from higher cues to action and self-efficacy and lower perceived barriers	Vietnam
Kakra Twum et al. (2021)	To examine intention to vaccinate against COVID-19 using the TPB and HBM	Predictors of COVID-19 vaccination intention are attitude, social norm, perceived behavioural control, perceived susceptibility, and cues to action	Ghana
Al-Hasan et al. (2021)	To determine factors that impact willingness to vaccinate based on HBM, sources of information, media usage, knowledge of treatment, government’s efforts for mitigation.	Knowledge of COVID-19 treatment positively influences vaccine intent as seen on social media platforms (e.g., Twitter, LinkedIn) as against WhatsApp, Instagram, and YouTube, which have a negative influence.	Multiple regions: North America, the Middle East, Europe, and Asia
Al-Metwali et al. (2021)	(1) to assess: the perceptions of healthcare workers (HCWs) and the general population, (2) to evaluate factors influencing the acceptance of vaccination using the HBM, (3) to explore the suggested intervention strategies to promote the vaccination qualitatively	The eight factors associated with the willingness to receive COVID-19 vaccine: Preventive measures, perceived benefit, perceived barriers, cue to Action, subjective norm, are supportive of vaccination in general	Iraq
Yan et al. (2021)	To explore the rate of vaccination intention and its predictors using the HBM in Hong Kong during the pandemic	Susceptibility, self-efficacy, cues to action, and acceptance of governmental preventive measures related to COVID-19 reported intention to vaccinate. Low intention to vaccinate needs effective vaccination promotion campaigns with the predictors identified in this study.	Hong Kong
Shmueli (2021)	To explore the intentions, motivators and barriers to vaccinate against COVID-19, using both the HBM and the TPB model	Participants were more likely to be willing to get vaccinated if they reported higher levels of perceived benefits of the vaccine, perceived severity of infection and cues to action, according to HBM, and if they reported higher levels of subjective norms and self-efficacy.	Israel
Wong et al. (2021)	To examine factors associated with acceptance of vaccines based on (1) constructs of the HBM, (2) trust in the healthcare system, new vaccine platforms and manufacturers, and (3) self-reported health outcomes.	Perceived severity, perceived benefits of the vaccine, cues to action, self-reported health outcomes, and trust in the healthcare system or vaccine manufacturers and recommendation from the government were positive correlations of acceptance, while perceived access barriers and harm were negative correlations.	Hong Kong
Le An et al. (2021)	To determine factors related to the intention to vaccinate based on the HBM and the TPB model in Ho Chi Minh City.	Knowledge, perception of benefits, cues to action, behavioural control, and attitudes toward the vaccine were positive predictive factors though acceptability of vaccines differed within the education year.	Vietnam

The literature review recognises the HBM constructs as an essential predictor of COVID-19 vaccination. Therefore, studying significant HBM constructs that impact COVID-19 vaccination is necessary for customised interventions to boost the approval of the vaccine among people. The literature study reveals that cues to action have a significant impact on the individual’s behaviour and have been deployed to help reinforce preventive behaviour (Carico et al., 2021a, 2021b; Jose et al., 2021).

Proposed Framework

One of the critical initiatives of the Government of India in spreading awareness about vaccine uptake was the use of mobile phone caller tunes. While many studies (Jose et al., 2021; Tao et al., 2021) used the HBM model to predict the intention of individuals for preventive behaviour during COVID-19, very few studies focused on the relevance of cues to action, specifically mobile caller tunes. The outcomes of this research study will be required for health professionals, educationists, public health officers and practitioners, in terms of their obligation to reduce a public health crisis. The interpretation of HBM constructs for the current study is summarised in Table 2.

Table 2.

Interpretation of the HBM Constructs in the Study.

HBM Constructs	Interpretation of the Construct in the Study
Perceived benefits	An individual’s belief that the outcomes of COVID-19 vaccination will affect them positively
Perceived barriers	An individual’s belief about the difficulties to get COVID-19 vaccination
Perceived susceptibility	An individual’s chances of being infected with COVID-19 disease
Perceived severity	An individual’s belief that COVID-19 disease will lead to serious consequences
Self-efficacy	An individual’s confidence about their capability to get vaccinated
Cues to action	COVID-19 caller tunes to create awareness about particular health behaviour

For this study, the HBM model is adapted to predict the impact of cues to action on the HBM constructs—perceived susceptibility, perceived severity, perceived benefits, perceived barriers and self-efficacy—which leads to action. The classic HBM (Rosenstock, 1974) was initially framed to model the acceptance of precautionary health behaviours, but it has been successfully improved to fit various social and interesting contexts (Griffin, 2012; Scarinci et al., 2012). Cues to action are frequently incorporated in extant literature as independent predictors. As per Jones et al. (2015), communication researchers are expected to hypothesise external cues like campaign exposures, mobile caller tunes, mass media, etc. In this context, the authors have used one such major external cues to action, that is, caller tunes. The proposed theoretical model is given in Figure 1.

Figure 1.

Proposed Theoretical Model.

Thus, we propose the following hypotheses:

H₁: Cues to action have a significant relationship with perceived benefits.

H₂: Cues to action have a significant relationship with perceived barriers.

H₃: Cues to action have a significant relationship with perceived susceptibility.

H₄: Cues to action have a significant relationship with perceived severity.

H₅: Cues to action have a significant relationship with self-efficacy.

H₆: Perceived benefits have a significant relationship with the intention to get vaccinated.

H₇: Perceived barriers have a significant relationship with the intention to get vaccinated.

H₈: Perceived susceptibility has a significant relationship with the intention to get vaccinated.

H₉: Perceived severity has a significant relationship with the intention to get vaccinated.

H₁₀: Self-efficacy has a significant relationship with the intention to get vaccinated.

Research Methodology

This is a descriptive and cross-sectional study that attempts to identify the relationship between cues to action like caller tune and preventive health behaviour that is, vaccination, in the context of COVID-19 and the HBM. A questionnaire was circulated for data collection among people in India who had heard the COVID-19 caller tune and were in the process of deciding whether to get vaccinated or not.

Sample

The constructs used in the study were identified from the previous literature (Raude et al., 2020; Smail et al, 2021). To improve the dependability, the measuring tool for the questionnaire’s variables was created from earlier research. The Likert scale was used to measure responses to the many variables associated with the respondent’s perception. The questionnaire items include demographic characteristics, perceived susceptibility, perceived severity, perceived benefits, perceived barriers, cues to action, self-efficacy and intention to get vaccinated. Data were collected by an online survey. A pilot study was conducted on 50 respondents, and Cronbach’s alpha value was significant, that is, more than 0.70 (Fornell & Larcker, 1981).

When calculating the sample size for the analysis, a significance level of 0.05, an effect size of 0.10, and a power of 0.85 were applied, as suggested by Cohen (1988); the required sample size was 300 people. The questionnaire was sent to 427 participants, out of which only 355 participants responded to the questionnaire. Of the 355 questionnaires recovered, 334 were analysed, excluding the 21 questionnaires which had insufficient responses. Snowball sampling was used to recruit the participants due to the COVID-19 pandemic regulations. Only those who voluntarily expressed their willingness to participate in the study after being informed about the purpose of the study were included.

Instrument Development

The scales used in this study were adopted from earlier studies (Mohamed et al., 2019). Each question item was rated on a five-point Likert scale, where 1 = disagree; 2 = slightly disagree; 3 = neither agree nor disagree; 4 = slightly agree; 5 = agree. The demographic variables in this study are age, gender, educational background, occupation, marital status, monthly income and chronic illness. Table 3 shows the measurement items.

Table 3.

Items of Constructs.

Construct	Indicators	Items	Source Literature
Perceived susceptibility (PSus)	PSus3 PSus4 PSus5 PSus6	I am healthy, so I won’t be affected by COVID-19. The likelihood of me getting infected with COVID-19 is high The likelihood of my family and relatives getting infected with COVID-19 is high I live in an environment where I can be exposed to the COVID-19 infection	Rosenstock (1974) Bish et al. (2011)
Perceived severity (PSev)	PSev3 PSev4 PSev5 PSev6	Contracting COVID-19 would be severe for me. Contracting COVID-19 is worrying for me. Contracting COVID-19 will cause significant suffering or complications Diseases caused by the COVID-19 infection have very serious consequences.	Rosenstock (1974) Guvenc et al. (2011)
Perceived barriers (PBar)	PBar3 PBar4 PBar6	I forget about getting vaccinated. I think I will fall sick if I get vaccinated. Getting vaccinated is a complex task.	Rosenstock (1974) Kim and Kim (2020)
Perceived benefits (PBen)	PBen2 PBen3 PBen4 PBen5	I believe that getting vaccinated will be beneficial to control the disease. If I get vaccinated, my family members will also be safe I believe getting vaccinated will prevent further infections by other new variants. I believe getting vaccinated will prevent significant suffering and complications of the disease	Rosenstock (1974) Kim and Kim (2020)
Self-efficacy (SEff)	SEff1 SEff2 SEff3 SEff4	I am confident that I can complete all the process of vaccination. I am sure that I can find time to take the vaccine I am physically fit to get vaccinated I can afford the expenses of getting vaccinated	Rosenstock (1974) Bandura (1977)
Cues to action (CA)	CA1 CA2 CA5	The COVID-19 caller tune reminded me to get vaccinated The COVID-19 caller tune was very informative I got vaccinated because of the COVID-19 caller tune	Rosenstock (1974) Bandura (1977) Schiman and Kanuk (2000)

Demographic Profile

The demographic profile of the respondents is given in Table 4. Most of the respondents are females belonging to the age group of 20–29 years, and all the respondents have some form of formal education. The respondents are predominantly single and have a monthly income of less than ₹10,000. Most of the respondents have no chronic illness.

Table 4.

Demographics of the Respondents.

Characteristics	Percentage
Gender
Male	38.3
Female	61.7
Age
Less than 20 years	10.2
20–29 years	50.3
30–39 years	9.0
40–49 years	17.4
50–59 years	4.8
Above 60 years	8.4
Education
School	9.0
Graduate	27.5
Post-graduate and above	63.5
Occupation
Government employee	4.2
Homemaker	7.2
Private employee	21.6
Retired	4.8
Self-employed	2.4
Student	59.9
Marital Status
Single	63.5
Married	36.5
Monthly Income
Less than–10,000	51.5
10,000–30,000	10.2
30,000–50,000	9.6
50,000–70,000	10.2
Above 70,000	18.6
Chronic Illness
Yes	9.0
No	86.2
May be	4.8

Results

The data collected were grouped into frequency distributions and applied factor analysis. Initially, the study used exploratory factor analysis for the data purification process. After analysing the results, the researcher decided whether to retain or delete any ill-fitting item. According to Hair et al. (2006), any item which had a factor loading less than 0.5 was removed since it did not measure any given construct.

The standardised coefficient for the indicators was determined, and the internal consistency was measured using Cronbach’s alpha. The values for the factors ranged from 0.754 to 0.917, which is greater than 0.70 (Henseler et al., 2009; Pallant & Bailey, 2005). The results given in Table 5 showed that all items meet the requirement. The reliability measure shows that all items have high reliability with a factor loading value greater than 0.50. According to Allen (2017), the composite reliability values of the constructs should be higher than 0.70. According to Netemeyer et al. (2003), all factor loadings of the measurement items must be significant and higher than 0.50. In order to verify the suggested model, confirmatory factor analysis (CFA) was used to evaluate the reliability, convergent validity and discriminant validity of measuring instruments. According to Byrne (2010), the results obtained are within the recommended threshold level. According to DeVellis et al. (2003), each construct’s average variance extracted (AVE) must be higher than 0.50. In the suggested model, discriminant validity examines how distinct the constructs are different from one another (Chan et al., 2007). Table 6 displays the values for discriminant validity.

Table 5.

Cronbach’s Alpha, Composite Reliability, AVE, Factor Loadings.

Construct	Indicators	Cronbach’s Alpha	Composite Reliability	MSV	Factor Loadings
Perceived susceptibility (PSus)	PSus3 PSus4 PSus5 PSus6	0.754	0.789	0.173	0.502 0.526 0.543 0.593
Perceived severity (PSev)	PSev3 PSev4 PSev5 PSev6	0.917	0.900	0.173	0.522 0.623 0.566 0.546
Perceived barriers (PBar)	PBar3 PBar4 PBar6	0.917	0.890	0.144	0.683 0.566 0.606
Perceived benefits (PBen)	PBen2 PBen3 PBen4 PBen5	0.909	0.899	0.551	0.564 0.628 0.561 0.706
Self-efficacy (SEff)	SEff1 SEff2 SEff3 SEff4	0.886	0.894	0.551	0.669 0.663 0.671 0.544
Cues to action (CA)	CA1 CA2 CA5	0.789	11.898	0.003	0.674 0.778 0.744

Source: AMOS Output.

Table 6.

Discriminant Validity Values.

	AVE	Variance Extracted Between Factors
	AVE	PSus	PSev	PBar	PBen	SEff	CA
PSus	0.559	0.748
PSev	0.693	0.416	0.832
PBar	0.731	0.380	0.127	0.855
PBen	0.691	0.202	0.074	0.096	0.832
SEff	0.681	0.165	0.049	0.284	0.742	0.825
CA	9.949	0.010	0.007	0.025	0.054	0.048	3.154

Source: AMOS Output.

The constructs’ internal consistency was evaluated using composite reliability, and it was found in the acceptable range of 0.789 to 11.898, which is above the cut-off value of 0.70 (Hair et al., 2017). The AVE for the constructs ranged from 0.559 to 9.949, which is above 0.50 (Hair et al., 2017), which implies convergent validity. According to Chin (1998), AVE evaluates discriminant validity. The indicators of the badness of the model were well within acceptable levels as RMR and RMSEA were 0.04 (<0.05) and 0.06 (<0.08), respectively, which were less than the threshold value (Hair et al., 2017). The overall results make it evident that the measurement model fits well and is eligible for the structural model.

The model fit for the CFA model was validated to be acceptable (Chi-square = 349.618; df = 218; CMIN/DF = 1.604, GFI = 0.902; NFI = 0.903; CFI = 0.944; PCFI = 0.813; RMSEA = 0.060; PNFI = 0.745). The Kaiser–Meyer–Olkin value was 0.844 (see Table 7) more than the suggested minimum value of 0.6 (Kaiser, 1970; Kaiser & Rice, 1974), and Bartlett’s test of sphericity (Bartlett, 1954) which has a statistical significance of p < .001 (Table 7).

Table 7.

KMO and Bartlett’s Test.

Kaiser–Meyer–Olkin measure of sampling adequacy.		0.844
Bartlett’s test of sphericity	Approx. Chi-square	2,677.697
Bartlett’s test of sphericity	df	300
	Sig.	0.000

Source: AMOS Output.

After checking the measurement model for reliability and validity, the structural model was analysed for hypotheses testing. Table 8 and Figure 2 show that six hypotheses were accepted, and four of ten hypotheses were rejected. The first hypothesis is supported since the analysis shows that cues to action (β = 0.602, p = .000, p < .05) has a positive relationship with perceived benefits. Cues to action (β = −0.261, p = .007, p < .05) has a significant negative association with perceived susceptibility, and hence hypothesis 3 is also accepted. Cues to action also has a significant relationship with self-efficacy (β = 0.315, p = .005, p < .05). So, hypothesis 5 is also accepted. Similarly, perceived benefits (β = 0.323, p = .000, p < .05) and self-efficacy (β = 0.521, p = .000, p < .05) have a significant association with the intention to get vaccinated. Perceived barriers (β = −0.253, p = .002, p < .05) have a significant negative relationship with the intention to get vaccinated. Hence, the sixth, seventh and tenth hypotheses are also accepted. Thus, six hypotheses of direct relationship (H₁, H₃, H₅, H₆, H₇ and H₁₀) were accepted. The finding also showed that cues to action has a negative relationship with perceived susceptibility, and perceived barriers has a significant negative association with the intention to get vaccinated.

Table 8.

Hypothesis Test Results.

Path	Estimate	S.E.	C.R.	P	Label
PBen ← CA	0.602	0.139	4.327	<.001	Accepted
PBar ← CA	–0.061	0.098	−0.623	.533	Rejected
PSus ← CA	−0.261	0.125	−2.088	.007	Accepted
PSev ← CA	−0.182	0.118	−1.546	.122	Rejected
SEff ← CA	0.315	0.113	2.779	.005	Accepted
Int2 ← PBen	0.323	0.082	3.931	<.001	Accepted
Int2 ← PBar	–0.253	0.083	−3.040	.002	Accepted
Int2 ← PSus	0.122	0.072	1.692	.091	Rejected
Int2 ← PSev	–0.006	0.070	−0.091	.927	Rejected
Int2 ← SEff	0.521	0.079	6.584	<.001	Accepted

Source: AMOS Output.

Figure 2.

Source: AMOS Output.

Cues to action was a strong driving force for the intention to get vaccinated. This was supported by Wong et al. (2021), who suggested that vaccine recommendation from the government was far more impactful than other sources like peer groups or family members. Our study shows that perceived benefits have a significant relationship with the intention to get vaccinated, which was also observed in the study which is similar to the finding by Hakim et al. (2011), Mercadante and Law (2021) and Garg et al. (2021). The data analysis also showed that cues to action have a significant relationship with self-efficacy, leading to intention to get vaccinated. This finding is supported by Shmueli (2021), who conducted a study in Israel, and Patwary et al. (2021) in Bangladesh. These observations provide evidence that vaccine promotion caller tunes should be tailored to the context of the population concerned.

Implications

Theoretical Implications

This paper contributes to the advancement of the HBM regarding preventive health behaviour in adversity. First, the present study took the existing literature on HBM a step further by studying the effect cues to action on individual beliefs. This research attempted to modify the HBM by considering cues to action as a precursor to individual beliefs. To the best of the authors’ knowledge, no single study proposed such a model. The research reveals that cues to action impacts individual beliefs and self-efficacy, resulting in intention to desired action. This implies that HBM constructs could function as a causal chain (Hayes, 2012). In this case, COVID-19 caller tunes will influence individuals’ beliefs and self-efficacy, which will predict behaviour (Jones et al., 2020).

Second, healthcare interventions that use mobile technology have recently increased (Kruse et al., 2021), although many of them focus on SMS text messages and direct calls. First, this study is one of the early attempts to explore the role of external cues to action, such as government-initiated mobile caller tune campaigns in healthcare communication. The findings of our study concur with those of Appiah et al. (2021), which was conducted with community pharmacists to understand the relevance of mobile caller tunes to promote COVID-19 vaccine uptake in low- and middle-income countries.

Third, understanding trust in the local context is the key to communicating about vaccination. Building trust by the government in various forms boosts confidence in preventive health behaviour. In this context, self-efficacy is the confidence in one’s ability to prevent disease by vaccination. The analysis reveals that a well-designed caller tune can enhance the individual’s self-efficacy by removing mistrust and misinformation and motivating the person.

Practical Implications

First, our findings imply that cues to action has a relationship with all the constructs except barriers and severity. The existing caller tunes for healthcare communication generally focus on highlighting the benefits of intended behaviours and ignore the other important factors of HBM. This was evident in our analysis of the COVID-19 caller tunes implemented in India. The government and other agencies that undertake such initiatives should enhance the content of the caller tunes by considering the right combination of the dimensions of HBM.

Second, the study reveals that caller tunes can be a very effective medium of healthcare communication in such a cataclysmic event in a country like India where mobile phone penetration is very high. A carefully designed caller tune can be crucial for healthcare communication in preventive behaviour.

Third, since cues to action has a significant association with self-efficacy, an efficacy-centred message could increase self-confidence to undertake the desired measures. Impactful campaigns can increase an individual’s self-efficacy, sense of control, self-self-assurance, and inspiration and is a critical means in extending the benefit.

Limitation and Scope of Future Research

This research study has some limitations. It was limited to the respondents in India, a developing nation with a huge population. The sample size considered is too small to generalise the findings in other contexts. This study can further be extended to other countries in different contexts and cultures. The model considered only one aspect of external cues to action when governments and other authorities have various campaigns and healthcare communication initiatives during COVID-19. There is limited literature available on the application of mobile caller tunes for impactful healthcare communication. Future researchers may undertake studies using other healthcare models.

Footnotes

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

The authors received no financial support for the research, authorship and/or publication of this article.

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