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Behavioral responses of mandatory masking within social interactions

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Abstract

Social distance is known to impact interpersonal behaviors. We examine the potential consequences of mandated masking, which increases social distance, on social behavior. A controlled laboratory experiment was conducted to systematically impose a mask mandate in the treatment group, and to measure how this mandate affected other-regarding behavior within various social interactions. We find that behavior in the mandatory masking condition is less other-regarding compared to the control group with zero mask wearing. Particularly, we document less altruism, more sabotaging, and less cooperation. Our result suggests that mandatory masking has the potential to have broad behavioral consequences in the form of people generally becoming more selfish. Our results are found to be more pronounced among females than males.

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Notes

  1. We note that this is not intended to serve as an exhaustive set of references relating to the effectiveness of masking. The current volume of research related to COVID-19 and its various domains is vast. We refer readers to the following research repositories for a more comprehensive review of the current COVID-19 research: https://www.ncbi.nlm.nih.gov/research/coronavirus/ or https://collections.plos.org/collection/covid-19/.

  2. Masking has also been linked to changes in individual-level behaviors. For example, Griggs et al. (2021) and Yan et al. (2021) document a substitution effect where masking is linked to increased incidences of other risky behaviors. Lu et al. (2022) document robust empirical evidence that mask-wearing reduced deviant behavior by heightening moral awareness.

  3. This experimental study was approved by the Texas Tech University Institutional Review Board (IRB2021-933).

  4. Participants were recruited from an organized student research participation program run through the Rawls College of Business. As part of this program, participants also receive a fixed amount of “research credits”, which are based on the length of the study, that count toward fulfilling participation requirements for various classes they are enrolled in. In a way, these research credits serve as an additional form of fixed compensation for showing up to participate, akin to the $5 monetary show-up payment that was provided.

  5. After being reminded of the date and time they had signed up, participants saw the following message in the email: “Because of proximity in the lab, we are requiring you to wear a face mask during the entire study tomorrow. You are welcome to bring your own. If you don't have one, we will provide you with one.” We acknowledge this can induce some selection effects because of potential dropout from the study. However, this was unavoidable because of the voluntary nature of all such human subject’s research. In particular, the alternative would have been to surprise subjects at the time of show-up about the requirement to wear a mask. But, even in this case, the participants could have voluntarily dropped out of the study at this point, which essentially results in the same potential selection issue. In collaborating with the IRB, it was determined that giving them some minimal notice to make this decision would be perceived as less coercive than having them face this decision after making the investment to come into the lab. Moreover, the results from a balance test presented in Sect. 3 show no significant differences in the sample across observed characteristics between the Mask and NO-Mask conditions.

  6. Note, in the Optional Mask Condition participants were not prohibited from wearing a mask and, hence, were free to mask voluntarily. However, there was zero voluntary masking in this condition, so for interpretive clarity, we refer to this as the NO-Mask condition throughout the remainder of the paper.

  7. We are not claiming that order effects are ruled out completely. Rather, because we are not revealing information about outcomes between games, there is no scope for behavior in later games to be shaped by outcomes in earlier games. As such, there is essentially no scope for belief updating about others because no information is revealed between games to condition such beliefs. Similarly, there is little concern that behavior in later games is shaped by possible hedging or risk shifting from revealed outcomes in earlier games. Lastly, while there might be a small possibility that the game order shapes preferences (e.g., Carlsson et al., 2012), it seems unlikely that this would systematically interact with the masking condition; hence, the relative treatment effects are unlikely to be impacted by the fixed ordering of the games.

  8. Charness & Gneezy (2008) show that just providing the name of the interacting other can influence dictator behavior.

  9. For robustness, we also test for differences in means using a Mann–Whitney U test, the non-parametric equivalent of the two-sample t-test. These test results are also reported in Table 3. Generally, these tests yield similar qualitative conclusions regarding our main treatment effects.

  10. Power tests suggest that all else equal, an n = 351 would lead to significant results at the .05 level for the sabotage game for the pooled sample.

  11. Power tests suggest that all else equal, an n = 348 and n = 296 would lead to significant results at the .05 level for the public goods game for the pooled sample and female sample, respectively.

  12. While only speculation, the lack of behavioral differences in the trust game between the Mask and NO-mask condition, could be (at least in part) a function of how the game was implemented – binary choice and the strategy method. These features were chosen, ex-ante, to facilitate implementation within our experimental protocol. However, the binary choice nature of the game (trust vs. no trust) resulted in very high levels of trust across both conditions and didn’t allow for the identification of possibly small differences in trusting behavior. In light of the smaller magnitude of the behavior differences we documented in the prior games, it is quite possible that we would have documented a similarly consistent pattern in the trust game—Player As sending less in the Mask condition—had we allowed Player A participants to send any integer amount to Player B.

  13. Murtazashvili and Zhou (2023) discuss how externalities arise amid pandemics, and how this motivated the use of government regulation (e.g., mask mandates).

  14. Chakraborti and Roberts (2023) present a recent example of unintended consequences of COVID-19 era regulation, where they document evidence that states that enacted/activated price-gouging regulations also had more social contact within the population in commercial spaces, thus undermining social distancing measures.

  15. Note, even at the time of drafting this article, Los Angeles County, which is one of the largest counties in the country, was strongly considering re-imposing a mask mandate (https://www.yahoo.com/gma/los-angeles-county-mask-mandate-170951475.html). More recently, in the summer of 2023, in response to new COVID variants some businesses, schools, and hospitals were implementing short-term mask mandates (https://www.npr.org/2023/08/31/1196943567/covid-cases-surge-mask-mandates).

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Author notes

  1. Eric Cardella, Briggs Depew and Ryan B. Williams have contributed equally.

Authors and Affiliations

  1. Rawls College of Business, Texas Tech University, Lubbock, TX, 79409, USA

    Eric Cardella

  2. Jon M. Huntsman School of Business, Utah State University, Logan, UT, 84322, USA

    Briggs Depew

  3. TTU School of Veterinary Medicine, Texas Tech University, Amarillo, TX, 79106, USA

    Ryan B. Williams

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Cardella, E., Depew, B. & Williams, R.B. Behavioral responses of mandatory masking within social interactions. Public Choice (2024). https://doi.org/10.1007/s11127-024-01166-0

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