Determinants of the Attitude to COVID-19 Vaccine in Lima-Peru: Path Analysis and Structural Regression

Abstract

Introduction

Research on the effects of COVID-19 has shown that a favorable attitude toward the COVID-19 vaccine would help reduce the pandemic's sequelae and avoid lethal variants.

Objective

A theoretical model was tested through the strategy of path analysis and structural equation modeling, seeking to evaluate the direct effect of neuroticism and the indirect effects of risk-avoidance and rule-following behaviors, mediated by attitudes toward science.

Methods

A total of 459 adults, mostly women (61%), mean age 28.51 (SD = 10.36), living in Lima (Peru), participated. The scales of neuroticism, risk avoidance behavior (RAB), norm following (NF), attitudes toward science, and attitudes toward vaccination were administered.

Results

The path analysis explained 36% of the variance in vaccine attitude, whereas the latent structural regression model achieved a 54% explanation; according to this model attitude toward science (β=.70, p < .01) and neuroticism (β=-.16, p < .01) are significant predictors of vaccine attitude. Likewise, risk avoidance behavior and rule-following have indirect effects on attitudes toward vaccination.

Conclusion

Low neuroticism and a positive attitude toward the science that mediates the effects of RAB and NF directly condition the possibility of vaccination against COVID-19 in the adult population.

Keywords

attitude COVID-19 vaccine science norms risk neuroticism

Introduction/Background

It is recognized that to reduce the risks of SARS-CoV-2 effects, vaccination is necessary (Alhowaymel et al., 2022; Klugar et al., 2021). Immunization through vaccination is a procedure that has demonstrated efficacy in controlling many deadly diseases (Kwok et al., 2021). Rejection of the vaccine could lead to the continuation of the health crisis since mortality would continue among the unvaccinated and the risk of the emergence of new lethal strains of coronavirus (Nguyen et al., 2022).

Refusals are based on various reasons, and it is a trend that is also of concern in other latitudes. According to Ullah et al. (2021) vaccine refusal in the population may be based on a lack of knowledge, religious beliefs, or misinformation about vaccination. But this rejection may also be due to a lack of guidance to people about the side effects of vaccination (Alhowaymel et al., 2022), or distrust of vaccines or the government (Nguyen et al., 2022).

The acceptance of the vaccine, by the Spanish public, would be influenced by the perception of efficacy, social influence, and income level (Sánchez et al., 2021). In China, Zhang et al. (2021) of 2053 workers found that 67% had a good attitude toward receiving the vaccine. Such a positive attitude was related to perceived social support, behavioral control, and exposure to positive vaccine information.

In France, out of 1554 health care workers, 77% accepted vaccination against COVID-19. Older age, male sex, fear of COVID-19, perceived individual risk, and influenza vaccination during the previous season was associated with hypothesized acceptance of COVID-19 vaccination (Gagneux-Brunon et al., 2021).

In Italy, Caserotti et al. (2021) evaluated how risk perception and some factors associated with the decision to comply with vaccination modulated vaccine acceptance for COVID-19.

In the United States by the end of December 2021, there was a 25% unvaccinated population by free choice (Cohn et al., 2022); as of July 2022, approximately 10% of the adult population had not received any vaccine doses and 23% of the adult population had not received all three doses, and nearly 50% of the adult population had not received any booster doses (Nguyen et al., 2022).

In Peru, an August 2020 national urban survey conducted by IPSOS Opinión y Mercados S. A. (2020) showed that 22% of respondents would not be vaccinated. Among the reasons for refusal, they highlighted non-belief in the efficacy of vaccines, that the vaccine could cause other diseases, and that vaccines would have microchips to track people. Asked whether the vaccine should be mandatory, 48% indicated that it should be voluntary. The proportion of refuseniks increased as one moved from the highest socioeconomic level (A) to the lowest (E).

In this regard, the presence of a large percentage of the unvaccinated population against COVID-19 that exceeds 10% constitutes a threat to public health (DeRoo et al., 2020) because the risks of not being vaccinated can result in death or a sequela of health problems in vulnerable populations or those with fewer resources. The emergence of variants with greater contagiousness and the subsequent collapse of the health care system make the need for a positive attitude to the application of the vaccine more evident.

Review of Literature

Therefore, it is imperative to explain the negative attitude toward the vaccine. If this explanation were achieved, we would have a greater probability of reducing the unvaccinated population and, consequently, reducing the possibility of infection and death from COVID-19. As a theoretical hypothesis, it is postulated in the present study that the attitude toward vaccination (dependent variable) could be mediated by attitudes toward science, which then has an endogenous variable function, while neuroticism, avoidance of risk behaviors, and following norms are exogenous variables (independent variables).

The theory underpinning our hypothesis corresponds to behavioral analysis within the field of psychology (Piña et al., 2011; Ribes, 1990). Under this theoretical perspective, it is conceived that health problems are correlated with the psychological, i.e., health problems such as catching COVID-19 are linked to dispositional factors of tendency (such as personality), propensities and inclinations (such as attitudes), and behavioral competencies (such as risk avoidance behaviors).

One definition of attitude toward science (and its products) is conceived as "emotional responses toward the scientific, i.e., toward science in general and scientific disciplines, careers, or subjects" (Toma, 2020, p. 145). A positive attitude toward science would make vaccine acceptance more likely, based on the achievements of vaccines to other diseases and confidence that scientific products are proven. Conversely, a negative attitude, based on coincidences, rumors, and ideas of conspiracies, would make acceptance less likely.

On the other hand, the neuroticism dimension of the personality model proposed by Eysenck (1967) is still valid due to its strong empirical basis. There is strong evidence that neuroticism is related to physical and psychological health problems (Liu et al., 2021; Turunen et al., 2022; Watson, 2021). The refusal of anti-COVID-19 vaccination is likely a strong emotional reaction to the near event (MacDougall & McCann, 2020).

Risk avoidance behaviors can be defined as any type of behavior that avoids or reduces physical and/or psychological harm, in the short or long term, to the subject that emits it (Madan et al., 2021). This variable covers a wide spectrum of behavioral and health areas, but for the specific case of anti-COVID-19 vaccination, it is clear that it is related to the behaviors recommended to avoid contagion (Kroencke et al., 2020).

Following group norms is conceived as the process of acceding to the requests or demands of others. One factor influencing compliance is authority. Populations unwilling to follow them or those who for some reason cannot follow them will be at higher risk of contagion (Hsiang et al., 2020) and constitute a group that negatively affects public health efforts (Buturoiu et al., 2021).

The present study, from a theoretical point of view, seeks to test the explanatory model. From a social and psychological point of view, it offers an alternative to understanding the attitude of rejection of the only reliable solution to the COVID-19 pandemic, vaccination. Specifically, it should be noted that the study is novel because it broadens the possibility of explaining the attitude adopted by individuals toward vaccination against COVID-19 based on variables not yet contemplated in previous studies.

Therefore, the central aim of the study is to assess the direct effect of neuroticism and the indirect effects of risk avoidance and rule-following behaviors, mediated by attitudes toward science, on attitudes toward anti-COVID-19 vaccination.

Methods

Design

A non-experimental cross-sectional design was used. Due to the nature of the causal relationships between the variables, it corresponds to a multivariate study.

Research Questions

In accordance with the formulated objective, the study answers the following research questions:

Can attitude towards the anti-COVID-19 vaccine be predicted from attitude toward science, neuroticism, risk avoidance behavior and norm following?

How is the relationship between neuroticism and attitude toward the vaccine?

Is risk avoidance behavior an exogenous factor of indirect effects on attitude toward the vaccine and is this relationship mediated by attitude toward science?

Is norm following an exogenous factor of indirect effects on vaccine attitude and is this relationship mediated by attitude toward science?

Sample

The participants were adults between 18 and 65 years of age of Peruvian nationality, and residents of Metropolitan Lima.

A total of 459 people responded to the online form: 178 males (37%; mean age = 28.68, SD = 10.44) and 281 females (61%; mean age = 28.49, SD = 10.79); 232 with completed high school, 55 with completed technical education and 164 with completed higher education.

Data Collection

The sample recruitment process was carried out between August and October 2021 in the city of Lima. For this purpose, an online form designed in MS form and Google form was used, which was disseminated through social networks such as WhatsApp, Facebook, Instagram, Twitter, and Telegram. Students were assisted by students who disseminated it among their contacts.

Measures

Data were collected using five self-reports, for which evidence of validity and reliability was estimated.

Neuroticism Scale

Revised and abbreviated version (EPQR-A) of Sandín et al. (2002), composed of 6 items and a dichotomous response format (yes = 1 and no = 0), was administered. For the present study, Cronbach's alpha and McDonald's ω reliability indices were estimated, which are at the standards of 0.783 and 0.786, respectively; confirmatory factor analysis (CFA) indicated that the model fit data are optimal, as shown in Table 1.

Table 1.

Fit Index for the Confirmatory Factor Analysis from the 5 Scales of the Predictive Model in Attitude Toward the COVID-19 Vaccine.

Scales	χ²	df	CFI	TLI	RMSEA [90% CI]	SRMR
Neuroticism	58.3	8	0.981	0.964	0.114 [0.08, 0.14]	0.076
Risk avoidance behavior	350.9	52	0.987	0.984	0.069 [0.06, 0.07]	0.061
Norm following	161.3	35	0.989	0.986	0.060 [0.05, 0.07]	0.054
Attitudes toward science	313.0	35	0.985	0.980	0.071 [0.06, 0.07]	0.060
Attitude toward the vaccine	664.1	53	.0993	0.991	0.061 [0.05, 0.08]	0.052

Risk Avoidance Behavior Scale

It is a self-report of 12 items, designed ad hoc, with graduated responses of 5 alternatives from never (1) to always (5). In the psychometric review, good reliability coefficients were obtained, Cronbach's alpha of 0.898 and McDonald's ω of 0.90; likewise, the adjustment indexes for validity by CFA are satisfactory.

Scale for Following the Norms

Self-report prepared ad hoc, consisting of 10 items, with a graduated response format from never (1) to always (5). In the psychometric review, optimal reliability coefficients were obtained: Cronbach's alpha of 0.836 and McDonald's omega of 0.838; on the other hand, the fit indices obtained with CFA were also optimal (see Table 1).

Scale of Attitudes Toward Science

This ad hoc self-report consists of 10 items and a four-anchor Likert response format ranging from strongly disagree (1) to strongly agree (4). In the psychometric evaluation, excellent reliability indices were obtained, Cronbach's alpha of 0.834 and McDonald's omega of 0.832. Table 1 shows the fit indices of the CFA for evidence of construct validity.

Scale of Attitude Toward Vaccination

Self-report elaborated ad hoc with the purpose of evaluating attitude toward the COVID-19 vaccine (6 items) as well as attitude toward vaccination (6 items), made up in total by 12 items, with 4 response options graduated from totally disagree (1) to totally agree (4). The evaluation showed excellent reliability indices with Cronbach's alpha and McDonald's omega of .917 and .918, respectively.

Ethical Considerations

The research protocol was approved by the Ethics Committee of the Faculty of Psychology of the University where the researchers work. Likewise, the ethical principles of the Declaration of Helsinki were taken into consideration.

Statistical Analysis

Three multiple linear regression analyses and one simple linear regression analysis were performed to construct the path analysis model and evaluate the influences of the exogenous and endogenous variables. All these analyses were performed with the SPSS package version 25. To calculate the significance of the indirect effects of the path analysis, the Aroian test (Preacher & Leonardelli, 2021) was applied.

The confirmatory factor analyses and the structural equation model (SEM) were run with R software version 4.2.1. WLSMV (Weighted Least Squares Mean and Variance) was used as an estimator for the confirmatory models and the latent structural model given the categorical nature of the items; the goodness-of-fit indices for the evaluation of the models examined were the Chi-square goodness-of-fit test (good fit is considered when its p-value is greater than 0. 05), CFI and TLI which are valued as adequate fit indexes when they are greater than 0.90 and very good fit if they are ≥ 0.95 (Hu & Bentler, 1999) and the RMSEA and SRMR indexes which are considered adequate fit when they are ≤ 0.08 and very good fit when they are between 0.06 and 0.00 (Hu & Bentler, 1999).

Results

Prediction of Attitude Toward COVID-19 Vaccine Using Multiple Linear Regression Strategies

The results of correlation and linear regressions that allowed the incorporation of the coefficients (r and β) in the path analysis model presented in Figure 1 are shown.

Figure 1.

Path Model for Vaccine Attitude with Regression Indices.

Flat Multiple Linear Regression Analysis

Table 2 shows that all correlations between variables are significant which may justify the model. The correlations between the exogenous variables neuroticism and norm following as well as between neuroticism and risk avoidance behavior are both negative and with a significance for small effect size (r > 0.10). The correlations between risk avoidance behavior and norm following, as well as between attitudes toward science and attitudes toward vaccination, are positive and with practical significance indicating a large effect size relationship (r > 0.50).

Table 2.

Correlations Between Variables in the Multiple Linear Regression Model with Attitudes Toward the Vaccine.

Scales	Attitude toward the vaccine	Attitudes toward science	Neuroticism	Risk avoidance behavior
Attitudes toward science	0.555***
Neuroticism	−0.116*	−0.116**
Risk avoidance behavior	0.350***	0.257***	−0.175***
Norm following	0.357***	0.265***	−0.127**	0.664***

Note: * p < 0.05, ** p < 0.01, *** p < 0.001.

The summary of the multiple flat regression model explains 36% of the variance in attitude toward the vaccine (Table 3). The effect size is 0.56, a large effect, and a test power of 1.00.

Table 3.

Summaries of the Regression Models for the Predictive Model of Attitude Toward Vaccine.

Regression	R	R²	R² adjusted	Standard error from estimation	Statistics of change
Regression	R	R²	R² adjusted	Standard error from estimation	R²	F	gl1	gl2	p
Flat Regression	0.604^a	0.365	0.359	4.562	0.365	63.423	4	441	0.000
Regression 1	0.604^a	0.365	0.361	4.558	0.365	84.628	3	442	0.000
Regression 2	0.286^a	0.082	0.078	4.156	0.082	19.734	2	443	0.000
Simple Regression	0.116^a	0.013	0.011	5.667	0.013	6.020	1	444	0.015

Flat Regression a. Predictors: (Constant), Norm following, Neuroticism, Attitude toward science, Risk avoidance behavior.

Regression 1 a. Predictors: (Constant), Norm following, Attitude toward science, Risk avoidance behavior.

Regression 2 a. Predictors: (Constant), Norm following, Risk avoidance behavior.

Simple regression a. Predictors: (Constant), Neuroticism.

Table 4 shows the coefficients associated with each predictor. The variables attitude toward science (β = 0.482, p < 0.001), risk avoidance behavior (β = 0.129, p < 0.05), and norm following (β = 0.141, p < 0.01) were statistically significant in predicting attitudes toward vaccination.

Table 4.

Coefficients of Multiple Flat and Multiple Regression Analyses for Predictive Model Testing.

Regression	Model	Coefficients			t	p	Correlations
Regression	Model	Not St.B	Error Desv.	St. B	t	p	Zero Order	Partial	Part
Flat R	(Constant)	8.305	2.352		3.530	0.000
	Attitudes toward science	0.635	0.052	0.482	12.147	0.000	0.555	0.501	0.461
	Neuroticism	−0.055	0.111	−0.019	−0.493	0.622	−0.116	−0.023	−0.019
	Risk avoidance behavior	0.101	0.040	0.129	2.508	0.013	0.350	0.119	0.095
	Norm Following	0.160	0.058	0.141	2.755	0.006	0.357	0.130	0.105
R1	(Constant)	7.988	2.261		3.533	0.000
	Attitudes toward science	0.637	0.052	0.484	12.228	0.000	0.555	0.503	0.464
	Risk avoidance behavior	0.104	0.040	0.132	2.582	0.010	0.350	0.122	0.098
	Norm Following	0.160	0.058	0.141	2.760	0.006	0.357	0.130	0.105
R2	(Constant)	21.825	1.782		12.247	0.000
	Risk avoidance behavior	0.086	0.036	0.144	2.372	0.018	0.257	0.112	0.108
	Norm following	0.146	0.052	0.169	2.775	0.006	0.265	0.131	0.126
SR	(Constant)	42.019	0.424		99.068	0.000
SR	Neuroticism	−0.334	0.136	−0.116	−2.453	0.015	−0.116	−0.116	−0.116

Flat R: Flat Regression a. Dependent variable: Vaccine attitudes scores.

R 1: Regression 1 a. Dependent variable: Attitudes toward the vaccine.

R 2: Regression 2 a. Dependent variable: Attitude toward science.

S R: Simple Regression a. Dependent variable: Attitude toward science.

Multiple Regression 1

Table 3 shows that norm following, attitude toward science and risk avoidance behaviors predict 36.1% of the variance in attitude toward vaccination. The Table 4 shows that attitude toward science, risk avoidance behavior, and norm following are significant (p < 0.01). The standardized coefficients (β) associated with attitude toward science, risk avoidance behavior and norm following were 0.484, 0.132, and 0.141, respectively. With the three predictors we have an effect size of 0.56, a large effect, and a test power of 1.00.

Multiple Regression 2

For the endogenous variable, attitudes toward science, the regression was run with risk avoidance behavior and norm following as predictors. Table 3 shows that the predictors explain only 7.8% of the variance in attitude toward science. Both risk avoidance behavior and norm following were significant (p < 0.05). The effect size with two predictors is 0.084, which corresponds to a small effect (greater than the critical value of ƒ² = 0.02) and a test power of 0.99. The standardized coefficients (β) taken to the path model are shown in Table 4.

Simple Linear Regression

To complete the calculation of the path analysis model coefficients, a simple linear regression was run where the dependent variable (DV) was the attitude toward vaccination and the independent variable (IV), was neuroticism. Table 3 shows that only 2% of the variance of attitude toward vaccination is explained by neuroticism. The standardized coefficient (β) of −0.116 (p < 0.05) was significant (Table 4).

Testing the Validity of the Predictive Model of Attitude Toward Vaccines

With all the coefficients (r and β) found, the path analysis model is presented with the values incorporated and the R². Figure 1 shows the model, which explains 36% of the variance of attitude toward vaccination from the exogenous and endogenous variables.

Testing the Importance of Neuroticism in Attitudes Toward Vaccines

Tables 3 and 4 show the results of the simple linear regression in which the adjusted R² is 0.011, thus explaining 1% of the variance in vaccine attitude.

Testing the Significance of the Risk Avoidance Behavior Pathway Mediated by Attitudes to Science on Attitude to Vaccination

To test the statistical significance of the indirect effects, the Aroian formula (MacKinnon et al., 1995) presented by Preacher and Leonardelli (2021) was used. The Aroian equation is as follows:

z - valor = \frac{a * b}{\sqrt{(b^{2} * S_{a}^{2} + a^{2} * S_{b}^{2} + S_{a}^{2} * S_{b}^{2}}}

Where:

a = crude regression coefficient for the association between IV and mediator.

b = crude coefficient for the association between the mediator and DV (when IV is also a predictor of DV)

sa = standard error of a.

sb = standard error of b.

The path risk avoidance behavior on vaccine attitude mediated by attitudes to science according to the Aroian z-test has a value of 5.24 and p = 0.00000016 < 0.001. This result indicates that the indirect effect of risk avoidance behavior on vaccine attitude is statistically significant.

Testing the Significance of the Norm-Following Path Mediated by Attitudes to Science on Attitudes to Vaccination

The norm-following path on vaccine attitude mediated by attitudes to science according to the Aroian z-test yielded a value of 5.38 and p = 0.00000007 < 0.001. This result indicates that the indirect effect of norm following on vaccine attitude is statistically significant.

Prediction of Attitude Towards Anti-COVID-19 Vaccine Using Latent variable SEM Strategy

The predictor model (Figure 2) configured from latent variables evidence empirical validity since both the overall goodness-of-fit indices of the model and the estimated parameters for the structural relationships are satisfactory: χ2 (1164) = 2096.9, p = 0.000; CFI = 0.956; TLI = 0.953; RMSEA = 0.042 [.040, .045]; SRMR = 0. 068; that is, the results indicate that the SEM model presents an adequate measure of parsimony (χ2/gl = 1.80), incremental measures of very good fit (CFI and TLI), as well as the absolute fit indices such as RMSEA and SRMR by presenting good fits indicate that there is a minimal presence of error in the reproduction of the empirical model.

Figure 2.

Latent predictive model of attitude toward COVID-19 vaccine.

According to the estimated parameters, Figure 2 shows that low values of neuroticism have an inverse effect on the attitude to vaccination, while a favorable attitude to science has a positive impact on the attitude to vaccination; the combined impact of the two latent variables on the attitude to vaccination is 54%; Likewise, behaviors based on risk avoidance and rule-following have a direct impact of 19% on attitudes to science, the latter variable, in turn, being a mediator for the indirect effects of risk avoidance and rule-following behavior on attitudes to vaccination. Among the covariances, it is observed that the lower the neuroticism (greater emotional stability), the greater the risk avoidance behavior and rule following, as well as a strong positive correlation between the last two variables, indicated.

When comparing the attitude to science according to the educational level of the participants, significant differences are observed for a power greater than the minimum expected (1-β = 0.80). Likewise, effect sizes (ƒ > 0.10, ω² > 0.01) denote practical differences of small significance between groups (see Table 5).

Table 5.

Analysis of variance for attitude toward science according to educational level.

	S	Mean	ED	F	p	ƒ	ω²	1-β
Primary	8	28.88	2.949	4.446	0.004	0.17	0.023	0.868
Secondary	235	32.45	4.382
Technical	49	32.04	4.518
Superior	154	33.47	4.086

According to the post hoc LSD (Least Significant Difference) test, a difference in means between subjects in primary education with those in secondary (Δ means = −3.572, p = 0.021), technical (Δ means = −3.166, p = 0. 050) and higher (Δ means = −4.593, p = 0.003); those in secondary with those in higher education (Δ means = −1.021, p = 0.022); finally, those in technical education with those in higher education (Δ means = −1.427, p = 0.043).

Discussion

The willingness to be vaccinated against coronavirus is a necessary attitude to reduce contagion, and reduce mortality, that is, at the level of individual and social health, but the benefits and impact of this willingness go beyond society, the impacts on the economic recovery of Peru as in other countries, the recovery of employment are factors that will make feel the welfare that was enjoyed before the pandemic due to COVID-19.

To understand the variables that would explain the favorable attitude to be vaccinated, a model with exogenous variables (neuroticism, avoidance of risk behaviors, and compliance with group norms) and endogenous variables (attitude toward science) of direct and indirect effects was proposed (Figure 1 and 2). The solution to the problem was approached using two strategies: path analysis and latent variable structural regression modeling (SEM). The path model, estimated from the linear regression analyses, overall explains 36% of the variance of total vaccination attitude, with a large effect size of 0.56 and a test power of 1.00, making the model an important model for explaining vaccine attitude. The structural equation modeling analysis not only reaffirms the findings but unlike the path analysis—by estimating the empirical model from latent variables—it offers a greater explanation (54%) of the total variance of the attitude toward vaccination.

In contrast to what was found with the path analysis (β = −0.02, p = 0.62), the personality variable, neuroticism, according to the structural equation modeling analysis presents a direct inverse effect on the criterion variable (β = −0.158, p = 0.004). This means that low levels of neuroticism (high emotional stability) would be explained in a certain way by the adoption of favorable attitudes toward vaccination against COVID-19. This finding is reinforced by Singh (2022) who reported that individuals with high neuroticism and low conscientiousness did not take care in the face of risks. In the same direction, Liu et al. (2020) found that high neuroticism scores are related to maladaptive strategies. The scientific community to explain the resistance or rejection of preventive public health measures such as vaccination against COVID-19 has postulated and accumulated evidence on conspiracy theories associated with psychological variables such as anxiety, depression, uncertainty, irrational beliefs, critical thinking, etc. (for example De Coninck et al., 2021; Sallam et al., 2021; Yang et al., 2021), to this effort to understand what kind of people are more prone to accept and spread these conspiracy theories our research contributes with a variable such as neuroticism.

The path composed of risk avoidance behavior and attitude toward vaccination mediated by attitude toward science was satisfactorily validated in path analysis (β = 0.09, p < 0.05; β = 0.64, p < 0.001) like in the analysis of latent relationships of the structural equation modeling (β = 0.19, p < 0.05; β = 0.70, p < 0.001). It follows from this finding that behavioral practices of avoiding risks that may affect health is an important factor in making a favorable attitude toward vaccination feasible, this relationship is mediated by a positive attitude toward science further magnifies the likelihood of vaccination against COVID-19. Although there are no previous studies on attitude toward science as a mediator between risk avoidance behavior and attitude toward vaccination, our findings are consistent in the three analyses performed (path regression analysis, the Aroian test for mediation effects, and the SEM model).

Also the path composed by the causal relationship between norm following and attitude toward vaccination mediated by attitude toward science is valid because it has empirical support both by the findings with path analysis (β = 0.09, p < 0.05; β = 0.64, p < 0.001) and by structural equation modeling (β = 0.19, p < 0.05; β = 0.70, p < 0.001), as well as in the evaluation of the mediation effect with the Aroian test (p < 0.001). It is inferred from these findings that the variable attitude to science plays a powerful mediating role between norm following and favorable disposition for vaccination in the young-adult population of Lima. In the absence of similar studies examining this indirect relationship, it is possible to support the relationships observed from bivariate studies and direct relationships, in the sense that Cavazos-Arroyo and Pérez (2020) confirmed that social norms are good predictors of the intention to be vaccinated against COVID-19. Insofar as social norms are standard prescriptions that regulate citizen behavior, in situations where public health is vulnerated as in the context of COVID-19, it is consistent to argue that social norms favor the adoption of positive attitudes to comply with preventive or protective measures such as vaccination. In the context of health disease, compliance with social norms is established or enhanced when supported by scientific evidence, for example, measures adopted such as social isolation, social and physical distancing, hand washing, and use of masks, among others, have been translated into effective measures with the dissemination of scientific evidence (Lurie et al., 2020).

Of interest is the finding of the negative relationship between neuroticism with risk avoidance behavior and norm following. In both the path analysis and like in the analysis of latent relationships with structural equation modeling the findings reveal the same direction of the covariances. Some studies have been found that support the findings because they report that there is a regularly significant correlation between neuroticism and norm following, and also with risk behavior avoidance (Lahey, 2009; Madan et al., 2021; Shokrkon & Nicoladis, 2021). These relationships should be understood in terms of the presence of low scores on neuroticism (which in turn means the presence of high levels of emotional stability) corresponding with high scores on risk avoidance behaviors and behaviors based on norm following.

As for the strong positive correlation between risk avoidance behavior and norm following in a pandemic situation, it means that it would not be the result of a nervous or fearful reaction, but, rather, a rational response and an adaptive citizenship response to society. A finding that reinforces this approach is the result of the comparative analysis of the attitude to science because according to the proposed model, risk avoidance behavior and norm following are two factors that regulate the attitude toward science. The data found evidence of the existence of significant and practical differences in the attitude toward science according to the level of education. This means that the practices of risk avoidance behavior and norm following are cultural variables that depend on education, and therefore, the higher the level of education, the higher the appreciation of science.

Strengths and Limitations

This research is perhaps one of the few studies that offer the possibility of explaining the attitude toward vaccination against COVID-19 as a function of social (risk prevention behavior, norm following, attitude toward science) and psychological (neuroticism) behaviors. From the knowledge gained, the possibility is generated for public health managers to implement intervention strategies aimed at modifying and reversing the psychosocial variables that regulate the negative attitude toward vaccination against COVID-19 and thus reduce the unvaccinated population, and consequently, reduce the possibility of contagion and deaths due to COVID-19.

Regarding the sources of internal validity, which sustains the validity of the predictive model, we have good control of instrumentation problems with good to optimal validity and reliability characteristics, the absence of mortality, and, for the statistical conclusion, alpha error levels less than 0.05 (type I error), while for power (1- β) greater than 0.80 (type II error).

External validity may be a weakness of this research since non-probability sampling was performed; therefore, generalization should be cautious. Despite this limitation, the results of the present study are valuable due to the knowledge gap, which can generate a basis for future research for critical situations such as a pandemic, in which it would be necessary to know how to overcome the resistance of those who show negative attitudes to receive a vaccine that could save their own and other people's lives.

Implications for Practice

The practical implications for directing the behavior of individuals in the pandemic are related to information management. This should appeal to the rationality of the presence of medical and behavioral scientists to address the population, in addition to continuing to regulate individual and societal behavior based on scientific principles.

Conclusions

The presence of personality characterized by adequate and high emotional stability is a necessary condition to adopt adaptive strategies in favor of health such as vaccination against COVID-19, on the contrary, the presence of neuroticism is characterized by insecurity, anxiety, and irrational beliefs, among other maladaptive behaviors, is a negative factor that conditions the reluctance or rejection of vaccination.

Adherence to risk avoidance behaviors has indirect effects on the willingness to accept or refuse vaccination against COVID-19, this relationship is mediated importantly by the attitude toward science.

Norm following aimed at containing the transmission and spread of SARS-CoV-2 is a factor that is enhanced by the mediation of attitude toward science and indirectly regulates the possibility of vaccination.

Both the path model (based on manifest variables) and regression models with structural equations (based on latent variables) show that a negative or favorable attitude toward vaccination is directly regulated by neuroticism and indirectly by risk avoidance behaviors and compliance with norms, the latter variables being mediated by the attitude toward science.

Footnotes

Declaration of Conflicting Interests

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

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iDs

Edmundo Hervias-Guerra

Walter Capa-Luque

Aldo Bazán-Ramírez

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