6. Discussion
The goal of this study was to explore the role of social conformity in mask-wearing behavior. As far as we know, there has been no peer-reviewed or observational study that has focused on real mask-wearing behavior from this perspective and thus no research against which we can directly compare our results. This study also contributes to current knowledge by providing empirical evidence of real-life mask-wearing behavior in a unique context, i.e., the Czech Republic. The results are based on observations made in heavily frequented shopping venues.
Three factors (respiratory protection of employees, respiratory protection of customers, and estimated number of customers per m2) were operationalized to examine conformity and social pressure, which resulted in interesting statistical outputs. While the mask-wearing of fellow customers had a strong positive influence on a person's propensity to adhere to face mask regulations – thereby supporting the effect of conformity – we observed the opposite effect (negative relation) in relation to the estimated number of customers per m2. This conflicts with the assumption that the more customers per m2 (crowded stores), the stronger the influence will be on mask-wearing behavior in the same direction (e.g., due to the social pressure originating in the particular social group). This finding goes against Bir and Wildmar's [14] and Bryson's [44] recent studies that concluded that social pressure can be a significant motive to adopt social group behavior. Our counterintuitive finding can be attributed to free-riding behavior [23,45,46], as an adverse and unforeseen reaction to social pressure or even to inattention and mistakes made by other people. For example, customers entering a store with a high proportion of customers wearing masks may decide not to wear masks, as they perceive the store to be a safe area given that the rest are wearing masks. Hypothetically, free riders may pursue everybody to wear masks, but not to wear them themselves (similar logic may apply to vaccination skepticism [23]). They might even find another person not wearing a face mask, thus justifying their decision not to wear one. Additionally, the notion that social pressure has a negative effect on mask-wearing behavior may be partially interpreted as a rebellious (and unlawful) behavior toward authorities [47], or in our case accepted social and legal norms.
Another notable finding is that the respiratory protection of employees did not have a significant impact on mask-wearing behavior. Store employees (e.g., retail workers) are expected to behave in a manner that promotes and communicates the company's position and etiquette on certain issues (e.g., mask-wearing), thereby cascading the message and influencing the behavior of others. Still, we did not capture any statistically meaningful relationship between the mask-wearing behavior of employees and that of customers, which calls into question the aforementioned idea and seems a promising area for future research. This may be explained by the proposition that the influence of other customers' (in-group) mask-wearing behavior overruled the potential impact of employee behavior. This is similar to the situation of mass events, where individuals align primarily with the observed behaviors of their peers, largely ignoring their information base and other exogenous influences (e.g., the behavior of retail staff) [48], which leads to social herding [31]. This is a noteworthy premise that requires further research attention.
With regard to customer-level characteristics, the results revealed that older age categories are more inclined to wear masks. This is understandable given the scale and content of Czech communication campaigns that (primarily at the beginning of the COVID-19 pandemic) focused on the elderly, presenting them as one of the categories most vulnerable to the virus [49]. Moreover, our findings support those of Haischer et al. [50], who found that older people are more inclined to mask-wearing in comparison to young or middle-aged individuals. Conversely, these findings indicate that younger people are more unprotected and thus potentially more vulnerable in terms of contracting and spreading the virus, which is borne out by the high incidence of confirmed cases among this category [50]. This might also be considered as a consequence of the dominant and prevailing narrative from the beginning of the pandemic in which young people were presented as either immune to the virus or largely unaffected by it. In terms of sex, the propensity of women to use face masks was found to be higher than that of men [51]. This can be attributed to the women's higher health care awareness (e.g., 32, 33) and the more prevalent risk-taking behavior of men in terms of health issues [50]. This is in line with Moran and Del Valle [51], who concluded that women are more involved in so-called non-pharmaceutical behaviors (e.g., the use of disinfectant, hand washing, mask-wearing, etc.) than men. Moreover, our findings reflect the more empathetic altruistic, and prosocial behavior of women [52].
The time of the observation (morning, afternoon, or evening), whether a customer entered the store individually or as a member of a close group and the location of the store entrance did not have any statistically significant relation to mask-wearing behavior. Therefore, we found no empirical evidence that suggests these variables influence the wearing of masks.
It is necessary to mention several limitations of the study that may have influenced our findings. Firstly, although we provided structured and validated checklists for the observations and one-day training for the observers, and divided them into pairs to ensure consistent and independent data collection, observation, by its nature, tends to be subjective assessment. There is a risk of incorrect estimation due to the subjective evaluations of the observers (e.g., the age of customers, the proportion of customers with correct respiratory protection in a store or the identification of mask type may have been incorrectly estimated). Secondly, given the research design, we did not ask customers and employees if they perceived that their mask-wearing had been influenced by others in any way, and thus conformity behavior was investigated only indirectly. This presents a promising area of future research in which, for example, an experiment could be designed that would capture the causal relations. Although our variables measure real-life behavior (in contrast to previous studies that mostly relied on self-reported perceptions (e.g., 20, 32–38)), more insights are needed to fully understand mask-wearing behavior. Future studies could follow our research design and add a brief survey to triangulate the observed variables more precisely. Thirdly, we did not find a way of operationalizing whether someone had been vaccinated. Vaccination status may have an impact on a person's decision not to adhere to mask-wearing regulations, as those who are vaccinated may perceive themselves to be immune to the COVID-19 virus [53]. Moreover, the study could be repeated at various points in time to capture the longitudinal dynamic and changes in mask-wearing behavior. Also, we could not safeguard if individuals were not subjects of two or more observations at different stores. Similarly, our research design may be censored in a way that does not account for those that are made uncomfortable by the presence of mask/not-masking-wearing crowd in the store and decided to stay outside. The potential remedy would be to perform a photo-epidemiology study and rely on video surveillance data and focus on individuals having facemasks in their hands. These amendments would lead to an increase in the robustness of results at a population level [52]. Scholars should factor these limitations into future studies, given the existing risk of skewed and censored results. Lastly, the cultural background and broader contextual dynamics could have influenced the real-life mask-wearing behavior. Therefore, to fully comprehend the role of conformity in the wearing of masks, the study should be replicated in a cultural context distant from the Czech one. Thus, these are some issues that are worthy topics for further research.
There are several practical implications of our study. In order to promote the wearing of masks, strict social distancing measures need to be enforced and mask-wearing must be systematically and continuously monitored. The results of this study suggest that ensuring individuals wear masks would have a secondary or cumulative effect on others. More specifically, it would have a knock-on effect, whereby others would align their own behavior with the behavior they observe [54]. Moreover, given the surprising finding that the more crowded stores provoke more resistance to mask-wearing regulations among incoming customers, more emphasis should be placed on restricting the number of customers in stores and preventing mass gatherings. Furthermore, in terms of content, communication campaigns should focus not only on altruistic behavior with regard to categories vulnerable to the virus (e.g., the elderly [55]), but also portray all the categories as being affected by the virus in some way. Also, to increase the impact of communication campaigns, particular social categories (e.g., students, seniors, etc.) should be targeted and the required behavior within those categories should be promoted (e.g., students wear masks), in order to create an unconscious bond between peers. Public policies and communication campaigns should pay more attention to those categories that are inclined to resist the regulations (young people and men), regardless of the extent to which these categories are affected by the virus themselves [56], as their refusal to wear masks can influence others.
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