Influence of sense of power on epidemic control policy compliance

Main Article Content

Ping Yuan
Fanghui Ju
Yuan Cheng
Yanbin Liu
Cite this article:  Yuan, P., Ju, F., Cheng, Y., & Liu, Y. (2021). Influence of sense of power on epidemic control policy compliance. Social Behavior and Personality: An international journal, 49(9), e10555.


Abstract
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References
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Incidences of noncompliance with COVID-19 prevention and control policies have occurred worldwide, increasing the risk to public safety and making epidemic control more difficult. We applied the approach–inhibition theory of power perception to investigate the underlying mechanisms and boundary conditions of the relationship between individuals’ power perception and their prevention and control policy compliance. This study collected data from 303 participants in 45 counties (districts) spanning one province in China. Results show that individuals’ sense of power was negatively related to their prevention and control policy compliance, with risk perception mediating and group policy control moderating this relationship. The findings provide a reference for assessing the effectiveness and relevance of government epidemic prevention and control. Implications for research and practice are discussed.

During the COVID-19 outbreak, incidences of noncompliance with epidemic control policies have occurred worldwide (Boylan et al., 2021), increasing threats to public safety and making controlling the epidemic more difficult. Examples of noncompliance include ignoring lockdown policies, deliberately concealing a history of contact, and even refusing treatment after being diagnosed with the coronavirus infection. Previous studies have thoroughly explored the antecedent variables and mechanisms of individual compliance (e.g., Griffin & Hu, 2013; Griffin & Neal, 2000; Kark et al., 2015; Pilbeam et al., 2016). Among those, people’s sense of power has gained much attention (Guinote, 2017; Liu & Mattila, 2017; Magee et al., 2007; Seppälä et al., 2012).

However, some questions remain regarding the relationship between individuals’ sense of power and their compliance. First, sense of power has been widely discussed in different areas of social life (see, e.g., Morrison et al., 2015), but it has not been paid enough attention in specific social life contexts. For example, during the COVID-19 outbreak, people need to comply with government prevention and control policies, but they also have the motivation to pursue such personal conveniences as commuting for work, shopping, and meeting friends, thus leading to more complex behavioral decision patterns (Boylan et al., 2021). Second, previous studies have focused on the motivational role of power in shaping individuals’ behavior (see, e.g., Anderson & Kilduff, 2009), but behavior may also be the result of people’s perceptions (Xia et al., 2017). For example, in this pandemic, individuals with a high sense of power might underestimate the potential risk and likelihood of being infected, leading to more violations of epidemic control policies. Third, previous research has explored the mechanisms of the relationship between perceptions of power and individual behavior from a noncompulsory regulation perspective; for example, a positive organizational climate can reinforce the effect of a high sense of power on individual proactive behavior (Morrison et al., 2015). However, compulsory regulations can also shape one’s behaviors (Huang et al., 2003). In epidemic control, group policy regulation is a representation of social norms or guidelines that influence the behavior patterns of individuals with different senses of power (Clark et al., 2020). In this vein, it is worthwhile to investigate how social regulations impact on the association between individuals’ sense of power and their behavior.

In sum, we explored the mechanism and boundary conditions of individuals’ sense of power on their compliance with COVID-19 epidemic control policies. The main contributions of this study are as follows: First, we introduced sense of power into the literature on epidemic control and expanded the research context of previous theoretical studies related to sense of power (Morrison et al., 2015). Second, we applied the approach–inhibition theory of power (Keltner et al., 2003) to explore the mediating role of perceived risk in this association. Third, from the perspective of compulsory regulations, we applied group policy control as a moderator, thus building a cross-level moderated mediating effect model to fully understand the relationship of individuals’ sense of power and policy compliance. We hope this model will provide a reference for the effectiveness of governments’ epidemic prevention and control.

Literature Review and Hypotheses

The approach–inhibition theory of power (Keltner et al., 2003) indicates that a strong sense of power increases sensitivity to rewards or gains and encourages more promotive behavior, whereas a low sense of power is associated with sensitivity to loss and leads to more inhibitive behavior. Previous research has shown that individuals with a high sense of power are less sensitive to external threats and less concerned about the impact of their behavior on others. In contrast, low-power individuals are more likely to feel environmental constraints and control and are more concerned about the impact of their behavior (Keltner et al., 2003). In the process of epidemic prevention and control, compared to individuals with a low sense of power, those with a high sense of power might be less sensitive to the threat of COVID-19 and to punishments for violating prevention and control policies. Therefore, we applied the approach–inhibition theory of power to explain the underlying and boundary mechanism of the impact of individuals’ sense of power on epidemic prevention and control policy compliance. It is worth noting that although many researchers do not distinguish between individuals’ objective power and perceived sense of power (Anderson & Galinsky, 2006; Galinsky et al., 2008), some have argued that an individual’s objective power is shaped through their perceived power (e.g., Anderson et al., 2012; Duan & Huang, 2013).

Sense of Power and Policy Compliance

Sense of power influences individuals’ compliance with rules and regulations. People with a high sense of power tend to overestimate their control over outcomes (Huang et al., 2003), be optimistic about their behavior, and conduct risk-seeking behaviors (Anderson & Galinsky, 2006). On the other hand, people with a low sense of power tend to be sensitive to loss and punishment (Anderson et al., 2012), which, in turn, leads to avoidance and prohibitive behaviors (Keltner et al., 2003). We assumed that people with a high sense of power would perceive themselves as more capable of coping with the risks of the COVID-19 epidemic and would, therefore, tend to disregard epidemic control regulations, such as wearing masks and not participating in large gatherings. In contrast, people with a low sense of power would be more sensitive to the risks of the epidemic and would believe it is difficult to avoid the negative consequences of being infected, thereby increasing their likelihood of complying with control policies. Thus, we formed the following hypothesis:
Hypothesis 1: Individuals’ sense of power will be negatively correlated with their epidemic control policy compliance.

The Mediating Role of Risk Perception

Individuals’ sense of power can reduce their risk perception. Those with a high sense of power usually focus on the potential gains from risky behavior while ignoring the potential losses (Anderson & Galinsky, 2006; Maner et al., 2007). For example, they tend to underestimate the possibility and severity of negative events and have low risk perceptions (Anderson & Berdahl, 2002; Anderson & Galinsky, 2006). Thus, in the context of epidemic prevention and control, individuals with a high sense of power would be less sensitive to the threats of the epidemic, and would believe that the likelihood of becoming infected is low.

Risk perception can reinforce individuals’ security compliance behaviors. Individuals with a high risk perception tend to conduct risk-averse behaviors when faced with potential threats (Cooper & Faseruk, 2011), such as complying with policy regulations (Arezes & Miguel, 2008; Xia et al., 2017). In terms of prevention and control related to COVID-19, people with a high risk perception of the epidemic might believe that they have a higher tendency to become infected with the virus (Barrios & Hochberg, 2020). In contrast, individuals with a low risk-perception levels believe that they are less likely to become infected, and anticipate that even if they do catch the virus, there might be no serious consequences. Thus, they tend to act according to their own wishes and convenience, without caring about epidemic control policies. In sum, we formed the following hypothesis:
Hypothesis 2: Risk perception will mediate the relationship between individuals’ sense of power and their epidemic control policy compliance.

The Moderating Role of Group Policy Control

Group control policies usually convey information about what is important to obey and what is forbidden to do (Huang et al., 2003). When group control is strict, individuals might believe that ignoring group policies can have serious consequences, such as creating safety hazards or leading to accidents (Zhang & Liu, 2016); thus, going against the policies would lead to negative outcomes and increase individuals’ risk perception of their behavior. In the epidemic control process, strong group policy control sends the message to the public that it is dangerous to ignore instructions. In this context, regardless of their sense of power, individuals would feel that they should seek protection from the virus. In contrast, loose group policy control sends the message that it is acceptable for individuals to show low conformance (Zhang & Liu, 2016), such that individuals with both high and low power sensitivities might develop a low risk perception for the epidemic and feel that they can deal with the threat of the virus without protection. Previous studies have shown that when safety supervision is strong, individuals think that accidents are more likely to occur, so they perceive a higher level of risk (Huang et al., 2003). Thus, we formed the following hypothesis:
Hypothesis 3: Group policy control will negatively moderate the relationship between individuals’ sense of power and their risk perception. Specifically, when group control is strong, the relationship between individuals’ sense of power and their risk perception will be weaker.

Group policy control can also weaken the negative effect of sense of power on policy compliance through risk perception. When group control is strong, people perceive that it is difficult to cope with the threat of the epidemic; thus, they perceive a higher likelihood of becoming infected, and have a higher level of risk perception (e.g., Kaufman et al., 2020). To avoid becoming infected, they strictly follow the requirements of control policies. When group control is weak, however, people perceive a low level of threat of the epidemic and the possibility of becoming infected, so they have a lower level of risk perception and show lower policy compliance. Similarly, research has shown that positive security regulatory policies can enhance the perception of individual security risks (Clarke, 2006; Griffin & Hu, 2013). Thus, we formed the following hypothesis:
Hypothesis 4: Group policy control will regulate individuals’ sense of power and impact on the indirect effect of policy compliance through risk perception. Specifically, when group policy control is high, the indirect relationship between sense of power and policy compliance will be weaker when risk perception is high.

The theoretical model of this study is shown in Figure 1.

Table/Figure

Figure 1. The Hypothesized Model

Method

Participants and Procedure

As the epidemic situation varies quickly and is unpredictable, we conducted a cross-sectional study. The data were collected during one week in March 2020, when epidemic control measures were being widely performed in China. We targeted one province of Mainland China and recruited 303 participants from 45 counties and districts, ranging from 5 to 12 participants per county and district. There were 161 men (53.1%) and 142 women (46.9%) with an age range from 18 to 88 years (M = 42.3, SD = 17.9). Among the participants, 63.7% had a high school or lower level of education.

Participants were reached through convenience sampling and data were collected through face-to-face interviews. This study was approved by the Institutional Review Boards of the corresponding author’s university. Participants were informed that their information and responses were confidential and would be used for research purposes only, and that they could discontinue their participation at any moment. At the end of the study, participants were debriefed and thanked.

Measures

The measures used in this study were originally developed in English, so we translated these into Chinese through a back-translation process (Brislin, 1980). To reduce homologous method bias, the variables were measured on a 5-point Likert scale (1 = strongly disagree, 5 = strongly agree) except for group policy control, which was measured on a 7-point Likert scale (1 = strongly disagree, 7 = strongly agree).

Sense of Individual Power
We assessed sense of individual power with Anderson et al.’s (2012) eight-item questionnaire. A sample item is “In my daily life, I am listened to by people around me.” Cronbach’s alpha in this study was .83.

Risk Perception
We assessed risk perception with three items modified from Babcicky and Seebauer (2017): “I think that people are very likely to be infected with COVID-19,” “I think once people get infected with COVID-19, the consequences will be serious,” and “I am concerned about the potential threats caused by COVID-19”. Cronbach’s alpha in this study was .71.

Policy Compliance
Epidemic prevention and control policy compliance was measured using five items from Kark et al. (2015). A sample item is “I live, study, or work in a safe manner during the epidemic.” Cronbach’s alpha in this study was .92.

Group Policy Control
Group policy control was assessed with three items from Huang et al. (2003): “In our local area, if someone violates the epidemic prevention and control policy they will definitely be punished severely,” “I think if people in our local area violate the epidemic control policy they will be punished,” and “I think our government contributes toward creating a safe environment through epidemic control policy.” As group policy control is a group-level variable, it needed to be aggregated to the team level. The results of the analysis on the basis of within-group interrater agreement (rwg) and intraclass correlation coefficients (ICC) were as follows: rwg = .85, ICC(1) = .43, ICC(2) = .84, indicating that the construct of group policy control was suitable for aggregating to the group level (see, e.g., James et al., 1993).

Control Variables
Following the practice used in previous studies (Gonzaga et al., 2008), we controlled for individual demographic factors, including age, gender, and education level.

Results

The confirmatory factor analysis results show that the hypothetical model had a good fit to the data, chi square = 62.62, degrees of freedom = 48, comparative fit index = .99, Tucker–Lewis index = .99, root mean square error of approximation = .03, standardized root mean square residual = .04, and also fit significantly better than the other alternative models. The descriptive statistics and correlation results for the study variables are shown in Table 1.

Table 1. Descriptive Statistics and Correlation Results for Study Variables

Table/Figure

Note. N = 303. Cronbach’s alphas are shown in parentheses on the diagonal.
* p < .05 (two-tailed). ** p < .01 (two-tailed).

Mediating Effects Analysis

We used Mplus software (Muthén & Muthén, 2012) to test the proposed mediating effects, and the results in Table 2 show that the effect of people’s sense of power on their policy compliance was .14 (p < .05), and the bootstrapping analysis result with 1,000 resamples for the indirect effect of sense of power negatively affecting policy compliance through risk perception was −.03, 95% confidence interval (CI) [−0.054, 0.000]. Following the practice in previous research (Preacher & Selig, 2012), to enhance the reliability of our findings we conducted Monte Carlo simulations of the CIs for this indirect effect. The results with 20,000 resamples indicate that the 95% CI for the indirect effect did not contain zero, [−0.058, −0.004]. Thus, Hypotheses 1 and 2 were supported.

Table 2. Direct Effect and Indirect Effect Analyses

Table/Figure

Note. N = 300. Unstandardized coefficients are reported. CI = confidence interval. Confidence intervals were calculated from 20,000 bootstrapped resamples.
* p < .05 (two-tailed). ** p < .01 (two-tailed).

Tests for the Cross-Level Moderating Effects

Next, we tested the proposed cross-level moderating effects. The results show that for the group with stronger group policy control (M + 1 SD), the effect of individual power perception on risk perception was .14, 95% CI [−0.209, 0.485], and for the group with weaker group policy control (M − 1 SD), the effect of power perception on risk perception was −.50, 95% CI [−0.724, −0.267]. A comparison of the groups shows that the effect of individuals’ power perception on risk perception was significantly different, .63, 95% CI [0.186, 1.081]. Thus, Hypothesis 3 was supported.

For those with strong group policy control, the effect of individuals’ power perception on their policy compliance through risk perception was .02, 95% CI [0.038, 0.167], whereas for those with relatively weak group policy control, the indirect effect of individuals’ power perception on policy compliance was −.07, 95% CI [0.086, 0.268]. Comparing the groups with stronger versus weaker group policy control, the indirect effect of individuals’ power perception on policy compliance through risk perception was significant, −.09, 95% CI [0.150, 0.001].

The results of Monte Carlo simulations of the moderated mediating effects across levels show that, on the basis of a bootstrapping analysis with 20,000 resamples, for the group with strong group policy control the indirect effect of individual power perception → risk perception → policy compliance was not significant, 95% CI [−0.030, 0.040], whereas for the group with weak group policy control this indirect effect was significant, 95% CI [−0.102, −0.015]. The indirect effect of sense of power → risk perception → policy compliance was significantly different, 95% CI [−0.103, −0.014] for the groups with stronger versus weaker group policy control. Thus, Hypothesis 4 was supported.

Table 3. Moderated Mediation Effect of Team-Level Group Policy Control

Table/Figure

Note. PMX = the effect of sense of power on risk perception; PYM = the effect of risk perception on policy compliance; PMX × PYM = the indirect effect of sense of power on policy compliance. Confidence intervals were calculated from 20,000 bootstrapped resamples.

To visualize the moderating effect of the intensity of the epidemic prevention and control policies, we plotted the cross-level moderating effect of group policy control using the parameters of hierarchical linear modeling output (Raudenbush & Bryk, 2002). As shown in Figure 2, when group policy control was strong, the effect of risk perception was greatly weakened.

Table/Figure

Figure 2. Interactive Effects of Cross-Level Group Policy Control

Discussion

We applied the approach–inhibition theory of power to examine the mechanism and boundary conditions of the influence of individuals’ sense of power on their compliance with epidemic control policies. The findings suggest that people with a high sense of power experienced a lower level of risk perception about COVID-19; therefore, they tended to have lower levels of policy compliance, which led to them displaying more behaviors that were against the control policies. Group policy control negatively moderated this relationship, in that it had a negative influence on the indirect effect of individuals’ power perception on their policy compliance through risk perception. Thus, when group policy control is strict, no matter how strong is individuals’ sense of power, they tend to perceive more risk about COVID-19 and display greater policy compliance. In contrast, when group policy control is loose, individuals tend to perceive less risk and display less policy compliance.

Theoretical and Practical Contributions

This study makes several theoretical contributions. First, it introduces sense of power into the field of epidemic prevention and control. Previous studies have suggested that a higher sense of power weakens individuals’ perception of environmental opportunities and stimulates proximity-type behavior, whereas a weaker sense of power reinforces perceptions of environmental constraints and stimulates avoidance behavior (Gonzaga et al., 2008; Keltner et al., 2003). We applied a cognitive perspective to the context of epidemic prevention and control, and found that individuals with a high sense of power showed a lower level of epidemic prevention and control policy compliance. Thus, people with a stronger sense of power might be more confident about their control over the epidemic and their ability to handle the negative consequences of being infected.

Second, we used the approach–inhibition theory of power to examine the role of individuals’ sense of power in policy compliance. Previous research conducted from a motivational perspective found that sense of power motivates individuals’ self-efficacy (Ju et al., 2019), and, in turn, increases their risk-seeking behaviors (Fast et al., 2012). However, Leiter et al. (2009) showed that behavior may also be the result of individual cognition. In the context of epidemic prevention and control, from the cognitive perspective, this study introduced the mediating role of risk perception in the relationship between sense of power and epidemic policy compliance. Specifically, we found that individuals with high sense of power underestimated the likelihood and severity of virus infection and exhibited lower levels of policy compliance. Thus, this study deepens understanding of the mechanism by which sense of power influences individual compliance behavior.

Third, by introducing the concept of group policy regulation in our examination of epidemic prevention and control policy compliance, this study has validated the contextual mechanisms of individuals’ sense of power on policy compliance. Previous studies have explored the mechanisms and boundary conditions of the relationship between environmental factors and individual behavior through the lens of flexible measures, such as security climate (Clarke, 2006). However, it has been found that strict regulatory measures can also reinforce environmental factors in shaping individual behavior (Huang et al., 2003). From the perspective of compulsory regulations, this study found that stronger group policy control weakened the negative relationship between individuals’ power perception and risk perception, thus reducing the indirect effect of power perception. Therefore, this study has deepened the literature on the boundary conditions of the mechanism of individual compliance behavior.

This study also has practical implications. To increase people’s compliance with control regulation and protect the overall health and well-being of society, the mediating role of risk perception that we observed indicates relevant media should increase publicity of the severe and negative consequences of being infected, to enhance individuals’ awareness of the risk of COVID-19. In addition, the moderating role of group control suggests strict regulations from the government, for example, emphasizing control policy implementation and increasing law enforcement of pandemic control compliance, are still in needed for controlling the epidemic. Moreover, as the participants we recruited in this study were diverse and covered most cities and districts in one province in China, we believe our results shed light on the overall psychological mechanisms of compliance with control regulation in China.

Limitations and Directions for Future Studies

This study has some limitations. First, the cross-sectional research design means we could not effectively verify the causal relationships among variables. Future researchers could replicate the research using multiple methods, such as experiments or quasiexperiments (DeRue et al., 2012). Second, there are other possible explanatory mechanisms for the relationship between individuals’ power perception and control policy compliance that we did not examine. For example, according to the theory of planned behavior (Ajzen, 1991), individuals with a higher sense of power might believe they can control their external environment; thus, they will show less compliance with policies. Furthermore, the self-efficacy model indicates that individuals with a high sense of power might be more confident, leading to a lower level of policy compliance. We leave those assumptions for future studies to test.

Conclusion

We applied the approach–inhibition theory of power to explore the mechanism and boundary conditions of the influence of individuals’ sense of power on their epidemic control policy compliance through a district-population proportional sample of 303 participants from 45 counties (districts) in one province of Mainland China. This study found that (a) people’s individual sense of power was negatively related to their policy compliance; (b) individuals’ risk perception played a mediating role in this relationship; and (c) group policy control negatively moderated the relationship between people’s individual sense of power and risk perception, and the indirect effect of individuals’ sense of power and policy compliance through risk perception.

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Table/Figure

Figure 1. The Hypothesized Model


Table 1. Descriptive Statistics and Correlation Results for Study Variables

Table/Figure

Note. N = 303. Cronbach’s alphas are shown in parentheses on the diagonal.
* p < .05 (two-tailed). ** p < .01 (two-tailed).


Table 2. Direct Effect and Indirect Effect Analyses

Table/Figure

Note. N = 300. Unstandardized coefficients are reported. CI = confidence interval. Confidence intervals were calculated from 20,000 bootstrapped resamples.
* p < .05 (two-tailed). ** p < .01 (two-tailed).


Table 3. Moderated Mediation Effect of Team-Level Group Policy Control

Table/Figure

Note. PMX = the effect of sense of power on risk perception; PYM = the effect of risk perception on policy compliance; PMX × PYM = the indirect effect of sense of power on policy compliance. Confidence intervals were calculated from 20,000 bootstrapped resamples.


Table/Figure

Figure 2. Interactive Effects of Cross-Level Group Policy Control


This work was supported in part by grants from the Zhejiang Province Social Science Foundation (#19NDJC188YB)

the Zhejiang Soft Science Research Program (#2019C35104)

the Zhejiang Province Educational Science Planning Project (2021SCG347)

and the Achievements of Scientific Research and Innovation Team Project of Zhejiang Wanli University in 2021.

Fanghui Ju, Business School, NingboTech University, Qianhu South Road 1, Ningbo, 315100, People’s Republic of China. Email: [email protected]

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