Exploring vaccine hesitancy: the twofold role of critical thinking

Abstract

With the progress of the vaccination campaign against the SARS-COV-2, we are ever closer to reaching that part of the population that refuses or is hesitant about vaccination. This study investigated the association between critical thinking motivation factors (i.e., intrinsic value of critical thinking and expectancy of one’s critical thinking ability), conspiracy mentality, intolerance of uncertainty and hesitancy toward vaccination. A sample of 390 participants completed an online survey during April 2021. Across participants, results indicate that conspiracy mentality and expectancy about personal ability as a critical thinker positively predict vaccine hesitancy. On the contrary, the intrinsic value attributed to critical thinking, intolerance of uncertainty, and education are negatively associated with hesitancy. While the findings confirm existing evidence, particularly on the detrimental role of conspiracy mentality on vaccine acceptance, they also shed light on the double-faced role exercised by critical thinking. Practical implications and future directions are discussed.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12144-022-04165-w.

Introduction

From the first clinical trial for a COVID-19 vaccine in March 2020, we have witnessed a growing development of different vaccine solutions and a simultaneous diffusion of the vaccine among the population in the last few months. While during the first pandemic phase, as vaccine availability was limited, much attention has been paid to investigate possible solutions to manage COVID-19 vaccine allocation priority (e.g. Ceccato, Di Crosta, et al., 2021; Ceccato, Palumbo, et al., 2021), nowadays national governments are concentrating their efforts on accelerating the vaccination campaign, as clinical and socio-economic benefits are linked to a high vaccination coverage. However, a portion of the population reports to be skeptics and/or shows hesitancy toward the vaccination. Vaccine hesitancy refers to “delay in acceptance or refusal of vaccines despite availability of vaccination services” (MacDonald, 2015). For example, related to the COVID-19 vaccination, in a recent survey across European countries 27% of Europeans were found to be vaccine hesitant (Ahrendt et al., 2021). As the vaccination campaign progresses, this could be a crucial point as we are getting closer and closer to this resistant part of the population (Feleszko et al., 2021).

To date, several psychological factors and processes have been explored in relation to vaccine hesitancy. For example, the lack of trust in authorized members of society (e.g., scientists, pharmaceutical companies, or governments in general) have been associated with negative attitudes towards vaccines (e.g. Kennedy, 2019; Mesch & Schwirian, 2015). More recently, regarding the COVID-19 pandemic, conspiracy-related variables (both generic conspiracy beliefs and specific COVID-19 related conspiracy beliefs) have been largely confirmed as negative predictor of compliance with preventive measures (e.g. Pavela Banai et al., 2021) and as a positive predictors of vaccine hesitancy across different populations and during different stages of the pandemic (Allington et al., 2021; Bertin et al., 2020; Murphy et al., 2021). It should be noted that conspiracy beliefs have been sometimes related to intolerance of uncertainty, as their formation is supposed to be due to an individual’s perceived necessity to find a causal explanation to a situation with a high level of uncertainty (Douglas et al., 2019). Given the social and epidemiological relevance of the hesitancy phenomenon, researchers are urged to identify which variables may reduce or modulate the hesitancy toward vaccination. For example, critical/analytical thinking skills have been suggested as “protective” factors against general vaccine hesitancy (Arede et al., 2019). Some studies also reported that analytic thinking is associated with reduced endorsement of conspiracy theories (Pytlik et al., 2020). It should be noted that, as critical/analytical thinking is cognitively demanding and usually produces longer processing of information, some scholars argued that when assessing this ability, motivation towards this ability “activation” should be considered as well (Valenzuela et al., 2011).

Overall, the current study adopted an integrative approach to fill previous gaps in the literature by analyzing at once conspiracy mentality, intolerance of uncertainty, and critical thinking motivation, examining their separate role on people’s hesitancy toward COVID-19 vaccination. Furthermore, for the first time, critical thinking was analyzed not as a cognitive skill, but as an attitudinal and motivational factor able to orient decisions and health behaviors.

Theorical background

Conspiracy mentality and intolerance of uncertainty

In the last few years, a topic that has increasingly caught scholars’ attention is the investigation of psychological drivers and consequences of individuals’ tendency to believe in conspiracy theories (Douglas et al., 2017). According to the most recent literature, the expression “conspiracy theories” identifies the “attempts to explain the ultimate causes of significant social and political events and circumstances with claims of secret plots by two or more powerful actors” (Douglas et al., 2019). Another widely shared definition was proposed by Swami and colleagues (Swami et al., 2014), who suggested that conspiracy theories can be defined as “a subset of false beliefs in which the ultimate cause of an event is believed to be due to a plot by multiple actors working together with a clear goal in mind, often unlawfully and in secret” (Swami et al., 2014; Swami & Furnham, 2014). One of the first psychological contributions on this topic supported the hypothesis that conspiracy beliefs are defined by a “monological functioning”, as believing in one conspiracy theory is associated with believing in all conspiracy theories (Goertzel, 1994). While more recent evidence suggested that sometimes conspiracy beliefs can also be associated with a singular topic (Sutton & Douglas, 2014), some studies highlighted that a person who believes in a specific conspiracy theory is more likely to trust all other conspiracy theories even if not related to the first one (Swami et al., 2010; Wood et al., 2012). This evidence led to the conceptualization of a more general thinking style, usually referred to as “conspiracy mentality” or “conspiracy mindset” (Dagnall et al., 2015). According to the available literature, this “style” may arise from different factors. For example, schizotypy, a personality style associated with magical thinking and distorted odds beliefs, has been systematically found to be a strong predictor of beliefs in conspiracy theories (Barron et al., 2018; Barron et al., 2014). Moreover, conspiracy mentality has been associated with greater proneness to specific cognitive biases, such as the Bias Against Disconfirmatory Evidence (Buchy et al., 2007; Georgiou et al., 2021). Also, other factors, such as low level of education (Georgiou et al., 2019; Van Prooijen & Jostmann, 2013) and extreme political orientation (Van Prooijen & Acker, 2015), have been identified as positive predictors of conspiracy beliefs. Taken together, available evidence suggests a role of three possible unmet psychological needs in people’s proneness to believe in conspiracy theories (Douglas et al., 2019; Stojanov et al., 2021). First, on a social level, when people feel that their need to maintain a positive self-image (Fairfield et al., 2015; Lantian et al., 2017) or a positive image of their ingroup (Cichocka et al., 2016) is threatened, they are more likely to adopt conspiracy beliefs. Second, conspiracy beliefs may arise when existential needs are activated and people need to feel safe and in control, such as when feeling powerless (Abalakina-Paap et al., 1999; Zebrowitz et al., 2015); this explanation was further supported by evidence of a reduction in conspiracy beliefs when the individual regained control (Van Prooijen & Acker, 2015). At last, as conspiracy beliefs may be seen as hypothesized causal explanations of the relationship between different events that might satisfy unsolved epistemic needs. Specifically, conspiracy beliefs can reduce uncertainty by engaging in mental sense-making processes that make the world understandable and predictable. This enhanced cognitive activity works as a coping strategy to restore a feeling of control (Park, 2010). Intolerance of uncertainty can be defined as “an individual’s dispositional incapacity to endure the aversive response triggered by the perceived absence of salient, key, or sufficient information, and sustained by the associated perception of uncertainty” (Carleton, 2016). Results on the relationship between intolerance of uncertainty and conspiracy theories’ endorsement are mixed, with some findings suggesting no relationship (Maftei & Holman 2022; Moulding et al., 2016) and others reporting a positive association between the two variables (Mari et al., 2022). By the way, for what concerns the direct influence of intolerance of uncertainty on COVID-19 vaccine hesitancy, more recent evidence suggests no significant role of this variable (Nazlı et al., 2021).

Regardless of the origin of a conspiracy mindset and its relationship with intolerance of uncertainty, several studies have reported an influence of this variable on the propensity to vaccinate. For example, in a cross-country study, Hornsey and colleagues reported conspirative thinking as the strongest predictor of anti-vaccine attitudes in general (Hornsey et al., 2018). The relationship between conspiracy beliefs and vaccine hesitancy has also been reported as related to specific diseases such as Polio (Murakami et al., 2014) or a particular type of vaccination such as MMR (McHale et al., 2016). Based on the available literature, we hypothesized that conspiracy mentality and intolerance of uncertainty positively predict vaccine hesitancy.

Critical thinking motivation and conspiracy mentality

Thinking style preferences, particularly for critical/analytical thinking, have been investigated as a possible protective factor against the endorsement of conspiracy theories (Pytlik et al., 2020). For instance, analytic thinking is associated with reduced beliefs in conspiracy theories and, in line with that, experimentally eliciting analytic thinking produces a reduction in conspiracies ideation (Swami et al., 2014). Generally speaking, out of the different measures and constructs used in literature to assess this variable, a more intuitive vs. deliberative thinking style has been consistently reported as a predictor of conspiracy mentality (Denovan et al., 2020). As related to the COVID-19 pandemic and related behaviors, Stanley and colleagues recently showed that lower engagement in analytic thinking is a predictor of both the tendency to believe that the pandemic is a hoax and the lack of respect for social distancing measures (Stanley et al., 2021). For what strictly regards vaccine hesitancy and refusal, an influence of parents’ analytical thinking has been proposed as a relevant variable in children’s vaccine uptake (Bertoncello et al., 2020; Tomljenovic et al., 2020). It should be noted that most of the contributions investigating the relationship between thinking style and vaccine-related behaviors have focused on analytic/critical thinking in its skill-based component. Nevertheless, no evidence is available for what concerns analytic/critical thinking motivation. Theoreticians of critical thinking, indeed, argued in favor of a bifactorial structure in the development of this style of thinking: on the one hand, the skill factor as a cognitive component, and on the other hand the disposition/motivation to put this style of thinking into practice (Elder & Paul, 2020). According to this approach, both components are required for critical thinking to be exercised. Moreover, critical thinking is a deliberative process, it is not automatically activated and presents activation costs. Therefore, the disposition/motivation component has been proposed as a prerequisite for activating and executing critical thinking skills (Faccione et al., 2000; Di Domenico et al., 2016). Thus, the literature investigating disposition/motivation toward critical thinking, by representing critical thinking as a task that requires resources to be performed, suggested that this variable depends on two different elements: first, the value that the individual assigns to critical thinking; and second, the expectation of a positive outcome as a consequence of the application of critical thinking (Eccles & Wigfield, 2002). Valenzuela and colleagues followed this line of reasoning and proposed a model and an associated measurement instrument for critical thinking motivation based on the value/expectation dichotomy. In this model, the value dimension reflects the positive intrinsic merit attributed to the critical thinking activity. In contrast, the dimension of expectation is defined as the individual self-evaluation of being a good critical thinker (Valenzuela et al., 2011). According to this model, both value and expectancy dimensions are required to be motivated to use one’s critical thinking skills. Therefore, this motivational component led to the activation of critical thinking skills (the cognitive component).

For the current work, given that critical thinking motivation is expected to be positively associated with critical thinking skill itself and that this skill has been proposed as a protective factor against vaccine hesitancy and refusal (Anderson, 2015), we hypothesized that both expectancy and value dimensions of critical thinking motivation negatively predicts vaccine hesitancy.

Methods

Sample

A total of 400 participants (39% male; mean age = 39.2 ± 13, mean years of education 14.2 ± 3.8) were recruited for this study using a snowball method. Students were recruited during faculty classes. When they completed the survey, they were invited to share the link to the survey with friends. Therefore, the final sample included both college students and adults from the general population (age range: 21–64). Participants provided written informed consent in accordance with the Declaration of Helsinki’s ethical standards. Data were collected via Qualtrics online platform (qualtrics.com) in three days during April 2021, when the national vaccine campaign in Italy had already started for a portion of the population and the first vaccination wave was just started. All participants were Italian speakers who physically resided in Italy during the pandemic. The research protocol was approved by the Institutional Review Board of Psychology (IRBP).

Measures

To ensure that participants had no previous history of psychiatric disorders or mental health conditions in general, as this can represent an influencing factor for study variables, the survey included a screening question on mental health. As based on this question, 10 participants were excluded from the dataset. Therefore, we obtained a final sample of 390 participants (38% male; mean age = 41 ± 13 years, mean years of education = 13.9 ± 3.7). The survey also included demographic questions about age, gender, years of education, political orientation, and a screening question to exclude potential respondents that had already received the vaccine because belonging to one of the groups that have accessed vaccination before the rest of the population in Italy at the moment of data collection (i.e., over 80 years old, some professionals and people with specific medical conditions). No participant was excluded after this question. Further, participants answered the vaccine hesitancy question “When it becomes available to you, how likely or unlikely is it that you will decide to get the vaccine?“ by using a 0 to 100 rating scale (from 0 = very likely to 100 = very unlikely). Thus, we obtain a score for which the higher the value, the higher respondent’s hesitancy. The survey also included the Italian version of the Intolerance of Uncertainty Scale (IUS-12) (Bottesi et al., 2015; Lauriola et al., 2016), the Italian adaptation of the Conspiracy Mentality Scale (Stojanov & Halberstadt, 2019) and the Italian adaptation of the Critical Thinking Motivational Scale (Valenzuela et al., 2011).

Intolerance of uncertainty (IUS-12)

The short form of the Intolerance of uncertainty scale (IUS-12) (Lauriola et al., 2016) was administered to assess this factor. The scale includes 12 items measuring two independent scores, prospective and inhibitory intolerance, and a general score (example item: “Unforeseen events upset me greatly”). Participants are required to answer using a 5-points Likert scale (from 1 = not at all characteristic of me to 5 = entirely characteristic of me). For the current study, we computed the general score for which the higher the score, the more the respondent feels intolerant toward uncertainty. The scale showed excellent reliability in the current sample, Cronbach’s α = 0.90.

Conspiracy mentality scale (CMS)

This scale includes 11 items measuring conspiracy mentality by asking participants to express their agreement with each item statement (example item: “Events throughout history are carefully planned and orchestrated by individuals for their betterment”) using a 7 points Likert scale (from 1 = completely disagree to 7 = completely agree) (Stojanov & Halberstadt, 2019). The original scale allows computing two scores (skepticism and conspiracy theories) and a total composite score reflecting conspiracy mentality. Higher scores are associated with a more conspiratorial mindset. Given our interest in measuring a conspiracy mentality in its whole and the lack of a priori hypothesis on the role of each subfactor, for the subsequent analyses we focused on the total composite score, including all 11 items (in the present study Cronbach’s α = 0.91) as suggested by previous literature (Stojanov & Halberstadt, 2019). It should be noted that none of the items in the CMS refers to specific conspiracy beliefs/theories about COVID-19 (more details on the Italian adaptation of the scale are provided in the Supplementary Material).

Critical thinking motivational scale (CTMS)

The critical thinking motivation scale (CTMS) (Valenzuela et al., 2011) contains 19 items measuring two factors: the intrinsic value of critical thinking (Value) and the expectations about one’s skills as a critical thinker (Expectancy) through a Likert scale (from 1 = completely agree to 6 = completely disagree). The Value factor of critical thinking is assessed via items such as: “Critical thinking will be useful for my future” (in the present study Cronbach’s α = 0.90). An example for the Expectancy factor is: “Concerning reasoning correctly, I am better than most of my peers” (in the present study Cronbach’s α = 0.75). To the aim of the current study, the independent influence of Value and Expectancy factors of critical thinking on vaccine hesitancy was assessed (see the Supplementary Material for details on the Italian adaptation of the scale).

Results

Distribution of vaccine hesitancy

Across participants, vaccine hesitancy ranging from 0 (very likely to get the vaccine) to 100 (very unlikely to get the vaccine), was found to be moderate (M = 45.9, SD = 38.8). Mean vaccine hesitancy scores for each considered demographic variable are reported in Table 1.

Table 1.

Participants’ vaccine hesitancy on a scale from 0 (very likely to get the vaccine) to 100 (very unlikely to get the vaccine)

		M (SD)
Gender	Female	45.6 (37.8)
	Male	46.3 (40.5)
Educational Level	Elementary School	63 (40.3)
	Middle School	56.3 (36.9)
	High School	44.9 (40.1)
	College/University (1st level)	44.0 (36.6)
	College/University (2nd level)	38.1 (40.9)
	PhD or more	40.2 (43.3)
Political Orientation	Extreme right	0 (0)
	Right	60.9 (42.7)
	Center-Right	40.9 (43.3)
	Center	53.8 (45.0)
	Center-Left	38.6 (40.0)
	Left	39.3 (38.0)
	Extreme Left	78.6 (35.9)
	Prefer not to answer	47.3 (36.2)

Note. For descriptive purposes, years of education were converted into six educational levels.

Pearson correlation coefficients were computed to assess the relationships between intolerance of uncertainty, conspiracy mentality, and the two dimensions of critical thinking (i.e., expectancy and value) (Table 2). Intolerance of uncertainty was positively correlated with conspiracy mentality, p < .001. On the contrary, there was a negative correlation between conspiracy mentality and both value of critical thinking, p = .002, and expectancy of critical thinking, p < .001. Moreover, a negative correlation between intolerance of uncertainty and expectancy of critical thinking was found, p < .001.

Table 2.

Means (M), Standard Deviations (SD) and Pearson correlations (r) between variables

Variable	M	SD	1	2	3	4
1. Intolerance of Uncertainty	20.7	17.7	-
2. Conspiracy Mentality	4.05	1.0	0.231**	-
3. Value CTMS	5.1	0.64	− 0.062	− 0.146*	-
4. Expectancy CTMS	4.3	0.98	− 0.312**	− 0.172**	0.497**	-
5. Vaccine Hesitancy	45.9	38.8	− 0.709**	− 0.064	− 0.009	0.264**

Note. CTMS = Critical thinking motivational scale. ^*p < .01. ^**p < .001.

At last, a hierarchical multiple regression model was carried out to investigate whether conspiracy mentality, intolerance of uncertainty, value, and expectancy scores from the CTMS could significantly predict participants’ vaccine hesitancy while controlling for the potential role of demographic characteristics (gender, age, and years of education). Therefore, in the first step, we entered gender, age, and education. In the second step, conspiracy mentality, intolerance of uncertainty, value, and expectancy of CTMS were added. All the assumptions were met. The result indicated that the overall model explained a significant variance of vaccine hesitancy, 53%, F(4, 382) = 104.2, p < .001. Results revealed that education was the only significant demographic predictor, while age and gender did not exhibit significant relationship with hesitancy. Specifically, higher levels of education intolerance of uncertainty and value of CTMS, predicted lower levels of vaccine hesitancy. On the contrary, conspiracy mentality and expectancy of CTMS were found to be positive predictors of hesitancy. Therefore, vaccine hesitancy increases by about 3% for each unit increase in conspiracy mentality and 4.4% for each unit increase critical thinking expectancy. On the contrary, vaccine hesitancy decreases by about 5% for each unit increase in critical thinking value, about 1.5% for each increase in intolerance of uncertainty unit, and about 3.7% for education. Therefore, results revealed that, while conspiracy mentality and one’s expectation as a critical thinker positively predict vaccine hesitancy, education, intolerance of uncertainty and value attributed to critical thinking were negative predictors of vaccine hesitancy (see Table 3).

Table 3.

Results for the hierarchical regression predicting vaccine hesitancy

	Predictor	B	SE	β	t	p	95% CI LL	95% CI UL
Model 1  F(3,386) = 2.38 p > .05	Intercept	73.93	14.34		5.15	0.000	45.74	102.13
	Gender	− 0.25	4.24	− 0.00	− 0.05	0.953	-8.60	8.09
	Age	− 0.20	0.16	− 0.07	-1.21	0.225	− 0.53	0.12
	Years of Education	-5.57	2.07	− 0.14	-2.68	0.007	-9.65	-1.49
Model 2  F(7,382) = 61.63 p < .001	Intercept	81.34	16.95		4.79	0.000	48.01	114.68
	Gender	2.50	2.96	0.03	0.84	0.399	-3.31	8.33
	Age	− 0.04	0.11	− 0.01	− 0.33	0.73	− 0.27	0.19
	Years of Education	-3.68	1.50	− 0.09	-2.45	0.015	-6.64	− 0.73
	Intolerance of Uncertainty	-1.52	0.08	− 0.69	-18.22	0.000	-1.68	-1.35
	Conspiracy Mentality	3.01	1.47	0.08	2.07	0.038	0.17	5.96
	Expectancy CTMS	4.41	1.69	0.11	2.60	0.010	1.08	7.75
	Value CTMS	-4.99	2.48	− 0.08	-2.00	0.045	-9.88	− 0.10

Note. SE = Standard Error. 95% CI = Confidence Interval at 95% for the estimated coefficient, LL = lower level, and UP = upper level. N = 390.

The described analysis did not include political orientation as a predictor because about half of the participants answered “Prefer not to answer” on this question. Therefore, we replicated the same regression analysis described above by admitting only those participants who had reported their political orientation, adding political orientation into the first step. No significant association between vaccine hesitancy and political orientation was detected. For model 2 an R² = 0.62, F(4, 186) = 74.13, p < .001 was obtained. Detailed results are reported in Table 4.

Table 4.

Results for the hierarchical regression predicting vaccine hesitancy (including political orientation)

	Predictor	B	SE	β	t	p	95% CI LL	95% CI UL
Model 1 F(4,190) = 1.55 p > .05	Intercept	83.86	22.70		3.69	0.000	39.07	128.65
	Gender	0.42	6.45	0.00	0.06	0.947	-12.29	13.15
	Age	− 0.19	0.24	− 0.06	− 0.78	0.433	− 0.68	0.29
	Years of Education	-7.23	3.09	− 0.18	-2.33	0.020	-13.33	-1.13
	Political Orientation	-1.37	2.01	− 0.05	− 0.68	0.494	-5.34	2.58
Model 2  F(8,186) = 39.04 p < .001	Intercept	101.96	24.94		4.08	0.000	52.75	151.16
	Gender	2.91	4.09	0.03	0.71	0.478	-5.16	10.98
	Age	− 0.09	0.15	− 0.03	− 0.59	0.556	− 0.404	0.21
	Years of Education	-3.67	2.01	− 0.09	-1.82	0.070	-7.66	0.30
	Political Orientation	− 0.77	1.27	− 0.02	− 0.60	0.544	-3.30	1.74
	Intolerance of Uncertainty	-1.69	0.11	− 0.73	-14.87	0.000	-1.91	-1.46
	Conspiracy Mentality	4.68	1.97	0.11	2.37	0.019	0.79	8.58
	Expectancy CTMS	5.54	2.32	0.13	2.38	0.018	0.96	10.12
	Value CTMS	-9.57	3.78	− 0.13	-2.52	0.012	-17.04	-2.10

Note. SE = Standard Error. 95% CI = Confidence Interval at 95% for the estimated coefficient, LL = lower level, and UP = upper level. N = 195.

Discussion

Going forward with vaccinations, nations are increasingly clashing with that portion of the population that has avoided vaccinating up to now. As current predictions suggest that we will need to continue vaccinating, it is helpful to understand which individual factors influence vaccine hesitancy we may have to continue to struggle with during the vaccination campaigns.

Our results highlighted a significant negative influence of education on vaccine hesitancy, similarly to what was reported by other studies (Bertoncello et al., 2020; Reno et al., 2021). On the other side, we found no relationship between political orientation and vaccine hesitancy, contrary to what was described in previous contributions (Fridman et al., 2021), possibly due to differences in the nationality of the involved participants. Regarding gender, we found no statistical differences contrary to some previous evidence which suggested more vaccine hesitancy in the female sample (Liu, 2021). Similarly, not significant role of age was detected in the present sample, while, for example, other evidence supported a higher hesitancy in the 35–54 years sample (Reno et al., 2021).

Results contribute to the investigation of this topic in two ways. First, from a theoretical point of view, present findings help clarify the association between intolerance of uncertainty and conspiracy beliefs. While a positive correlation between the two was detected, they intriguingly exerted an opposite influence of vaccine hesitancy. Indeed, while conspiracy mentality was found to positively predict hesitancy, as expected based on the literature, intolerance of uncertainty was a negative predictor of hesitancy. Overall, these findings supported the hypothesis of an association between intolerance towards uncertainty and a conspiratorial mentality and the influence of both factors on the propensity to receive the vaccination. Importantly, our results align with a recent study in the context of COVID-19 (Maftei & Holman, 2022), reporting a similar pattern of findings. Other authors investigated the predictors of compliance with the lockdown rules and found a small positive correlation between intolerance of uncertainty and conspiracy mentality and an opposite influence exerted by the two on the dependent variable (Maftei & Holman, 2022). A possible interpretation for our results stems from the hypothetical comparison of potential consequences to get (or not) vaccinated made by the individuals. Indeed, participants with high intolerance of uncertainty may have evaluated the effects of being vaccinated as less uncertain (more tolerable) than the consequences of not being vaccinated.

Second, our results suggest a dual role of critical thinking motivation in influencing hesitation about the vaccine. While, on the one hand, beliefs about oneself as a good critical thinker seem to promote hesitation, beliefs about the positive intrinsic value of critical thinking itself seem to work as a protective factor against hesitation. In other words, people who believe to be very able to reason systematically and rationally (i.e., expectancy) were also less prone to get vaccinated. On the contrary, people who believe that thinking in a critical and analytical way is a relevant skill and an important personal goal were less hesitant toward the vaccination. From a more practical point of view, this result is particularly interesting for what concerns policy-making efforts to promote vaccination among the hesitant population. In this regard, our results confirm the relevant role played by critical thinking as they suggest that attributing a high value to critical thinking is associated with less vaccine hesitancy, thus supporting those accounts that sustain the need for specific health and media literacy training (Dib et al., 2021; Pisl et al., 2021). It is important to acknowledge that the supplementary analysis on the construct validity of the CTMS questionnaire suggested substantial room for improvement. However, to date, this is the only instrument available in the literature to measure critical thinking motivation. Future studies are needed to confirm present findings and to delve into the topic, examining additional aspects and operationalizations of critical thinking attitude.

Following the line of reasoning delineated so far, promoting a culture of critical thinking and attention toward accuracy (Pennycook et el., 2021) would help the population navigate a world full of information that every day requires the ability to distinguish the truth from fake information (Arede et al., 2019; Mammarella et al., 2012). On the other side, our findings indicate that perceiving oneself as a good critical thinker increases the hesitation towards the vaccine, suggests being cautious of those training programs, social initiatives, or intervention protocols that aim to increase (or that cause an increase as an indirect consequence of other programs) critical thinking, without taking into account the possible negative consequences or without equipping individuals of any instrument to manage this effect.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Author contribution

LC conceived the experiment. AB, ADC, and PLM prepared tasks and conducted the experiment. LC and IC performed the statistical analyses. LC, IC, ROP, ADD, and RIP prepared the draft manuscript. All authors discussed, reviewed, and approved the final manuscript.

Funding

The authors received no specific funding for this work.

Data Availability

The datasets generated during and/or analyzed the current study are available in the Open Science Framework repository: [https://osf.io/83mzb/?view_only=d6763991d8df45aba49cbd93860c85a1]

Declarations

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.