Public behavioral coping strategies model framework during the COVID-19 pandemic
More risk studies from social sciences have realized that the intervention of public behavior on risk is crucial [15]. Several behavioral theories have been established and extended. The theory of planned behavior (TPB) is an explanatory model widely applied in studies on behavioral intention [16]. Public behavior theory based on TPB revealed that attitude, perceived behavior control (PBC), and people’s knowledge significantly affect their behavior in reducing urban air pollution [17]. Other similar behavioral models, like the recycling behavior model based on TPB, were also reported [18]. Besides, people generate a cognition-affect-coping model when facing threats and pressure; that is, an individual’s cognition and judgment of risk stimuli produce a corresponding effect and then influence the individual’s response behavior [19]. A serial mediation model based on cognition-affect theory showed that scarcity aggravates panic buying, and this aggravation effect is serially mediated by perceived control and panic [20]. These findings provide essential enlightenment for guiding rational public behavior and managing public opinion during emergencies. Besides, an exploratory theoretical model of four public behaviors based on the combinations of the public-personal domains and mitigation-adaptation actions was suggested against the risk of particulate matter (PM, a small air pollutant) by focusing on the roles of risk perception, communication, and attribution factors [21]. These results provide some enlightenment effect on selecting public behavioral factors and classifying behavioral coping strategies in our research.
However, the previous theories and models (TPB, cognition-affect theory) lack specificity in the context of COVID-19 crisis, and the specific public behavior theories were rarely reported. Furthermore, traditional statistical methods, such as principal component analysis, linear regression model, and path analysis [17, 18, 20, 21], only clarify the quantitative correlation between the dependent and independent variables and cannot profoundly explain its further logical causality, which limits the theory’s explanatory power.
When facing the severity of the COVID-19 pandemic, the public can respond in different ways, varying from protective coping behavior (PCB) to excessive coping behavior (ECB).
On the one hand, people can take preventive actions to reduce their risk. A vaccination strategy is considered the best option for COVID-19 prevention, as the vaccine can protect public health and reduce transmission of the virus. Still, skepticism, hesitancy, and resistance remain [22,23,24]. Research shows that individual vaccination decisions are related to personal characteristics and rooted in their public health and home state’s political and economic contexts [25]. Safe and effective vaccines are undoubtedly groundbreaking. Nevertheless, the resurgence of the COVID-19 crisis occurred in many countries in the latter half of 2021 due to waning immunity from vaccination after the second dose [26].
Consequently, the public was recommended to continue wearing masks, washing their hands, ensuring good ventilation indoors, physically distancing, and avoiding crowds in the foreseeable future [27]. Social distancing is very effective in blocking short-distance infections. Mathematical modeling demonstrates that social distancing and public behavior changes had curbed the spread of COVID-19 [15]. Public behavior was deeply affected by local government regulations rather than the global pandemic situation [28]; there were noticeable regional differences in intent to follow key public health recommendations such as “stay home and keep social distancing” [29].
On the other hand, the public may also respond with excessive actions. Panic buying is a common phenomenon during public emergencies and has substantially undesirable social impacts [20]. The media must consider the effect of their messaging on public behavior, as even imagined food shortages can instigate excessive actions such as stockpiling and panic buying behavior, as observed during the COVID-19 pandemic [30].
As a critical link in the emergency response process, risk communication (RC) transmits real-time information, advice, and opinions between experts and people facing threats to their health, economic, or social well-being [31], which can profoundly affect public behaviors during the pandemic. An online randomized controlled trial demonstrated the importance of effective RC in reducing undesired public behavior during non-conventional terrorism crises [32]. The government could use relevant media as a crisis and risk communication strategy to intervene in pandemic-related public behavior [8]. Research suggests that vaccine efforts might need to go beyond communication campaigns correcting misinformation about COVID-19 vaccines and should focus on re-establishing public trust in government agencies [33]. Trust in science may positively affect individuals’ social distancing behavior by decreasing perceived media exaggeration about COVID-19 [34]. Trust is a critical factor that encourages people to comply with public health regulations. One online survey showed that higher trust in governmental organizations was related to greater compliance in adopting protective behaviors during the COVID-19 crisis [9].
The studies above indicate that the critical external factors, RC and degree of trust (DT), can profoundly affect pandemic-related public behavior. Their regulation by risk management departments may be effective in pandemic prevention and control. Furthermore, we noted that today, the public’s psychological factors are closely related to external factors and are becoming more critical in better targeted psychological pandemic-crisis interventions.
Public risk perception (RP) is defined as the subjective judgment people make about the characteristics and severity of risks [35], which is an essential consideration in public health emergencies and risk management decision-making [36]. A qualitative study revealed that people influenced by information and advice campaigns perceive a risk that has shaped their protective behavior [10]. Moreover, there is a dynamic relationship between RP and pandemic-related behavior [11]. Therefore, timely monitoring and regulating public RP can help the government predict public behavior and manage risk effectively. In addition to RP’s impact on behavior, emotion plays a central role. Higher RP concerning COVID-19 is notably associated with less favorable or more negative emotions (NE) [12]. Events during the public health crisis (like lockdown) increase the likelihood of public NE (worry, fear, and anxiety), which in turn prompt behaviors including excessive avoidance and blind obedience [37]. Hence, it is crucial to grasp the potential psychological effects of COVID-19 immediately.
In conclusion, public behavior is shaped by key external (RC and DT) and internal (RP and NE) influencing factors, and we constructed the behavioral framework hypothesis. Our previous study [14] verified the theory by path analysis (Fig. 1A). However, the asymmetry of causality in social problems and the correlation of multiple causes limit further interpretation of the results. From the configuration perspective, the influences of external factors and internal psychological conditions on public behavior response are not independent; still, they play a synergistic role through linkage and matching (Fig. 1B). Specifically, concurrent synergistic effects among multiple conditions may include mutual reinforcement through adaptation or cancellation through substitution. Therefore, from a configuration perspective, the study empirically explores how external–internal conditions can affect public behavior through mutual matching (adaptation/substitution).
The fuzzy set qualitative comparative analysis
Herein, we attempt to analyze the multiple driving mechanisms behind public behavior during the COVID-19 pandemic based on a configuration perspective, so we proposed using fsQCA to carry out an empirical test.
Ragin proposed the qualitative comparative analysis (QCA) method in the 1980s [38]. In QCA, researchers can determine the logical relationship between matching configurations of different conditions and outcomes through cross-case comparison, that is, “Which configurations of condition variables can lead to the appearance or disappearance of outcomes?” thereby further identifying the synergistic effects of multiple conditional variables under the premise of acknowledging causal complexity.
In delineating the social sciences approaches, it is conventional to distinguish between quantitative, variable-oriented analysis and qualitative, case-oriented analysis [38, 39]. The fundamental objective of variable-oriented research is the production of descriptive or explanatory inferences by hypothesis testing [39]. In contrast, case-oriented qualitative research is more valuable when implemented to spotlight each case’s distinctiveness and facilitate theory development [39]. By embracing both quantitative and qualitative methods’ aspects, comparative methods can circumvent some of both approaches’ limitations [38, 39]. Like case-oriented methods, comparative methods maintain cases’ integrity; like variable-oriented methods, comparative methods examine relationships’ patterns among variables. So, comparative methods, described as a ‘bridge’ between qualitative, case-oriented research and quantitative, variable-oriented research [40], could be applied for both hypothesis testing and theory development [38]. Unlike variable-oriented causal research methods, such as regression analysis or path analysis, that produce precise predictions of the likely effect of one variable upon another [41], comparative methods see the social world in terms of sets and set-theoretic relations [42], which emphasizes the search for highly consistent relationships linking combinations of causes to outcomes [40].
Rooted in set theory, QCA uses set algebra – also known as Boolean algebra – to analyze causal configurations [42, 43]. QCA has many advantages: on the one hand, researchers can identify conditional configurations with equivalent outcomes, which can help people understand the differential driving mechanisms that lead to outcomes in different scenarios, and further discuss the adaptation and substitution relationship between conditions. On the other hand, researchers can further compare the configuration of conditions that lead to the emergence and disappearance of outcomes and broaden their theoretical interpretation of specific research questions. Under the logical premise of causal asymmetry, the conditions that lead to the emergence of the outcomes may not be the same as those that lead to the disappearance of the outcomes. QCA includes three basic categories [13, 43]: a clear set qualitative comparative analysis (csQCA), fsQCA, and multi-valued set qualitative comparative analysis (mvQCA). Compared with the characteristics of csQCA and mvQCA, which are only suitable for dealing with category problems, fsQCA can further deal with the problem of degree change or partial membership [44].
Accordingly, based on the above theoretical model framework, our study attempts to analyze the multiple driving mechanisms behind public behavioral coping strategies during the COVID-19 pandemic from a configuration perspective. Therefore, fsQCA is proposed to conduct empirical tests.