Effect of attribution on the emotions and behavioral intentions of third-party observers toward intergroup discriminators during the COVID-19 pandemic

Abstract

The global outbreak of novel coronavirus disease COVID-19 has caused intergroup discrimination associated with the disease to become increasingly prominent. Research demonstrates that the attitudes and behaviors of third-party observers significantly impact the progression of discrimination incidents. This study tested a parallel mediating model in which the attribution tendencies of observers influence their behavioral intentions through the mediating effect of the emotions of anger and contempt. The first two studies confirmed the proposed model with discrimination incidents reported against “returnees from Wuhan” and “returning workers from Hubei.” Study 3 further manipulated the attribution tendencies of observers, providing empirical evidence for the causality from attribution tendencies to emotions, confirming the validity of the model. These findings enrich the cognitive (attribution)–emotion–action model, further enhancing our understanding of the role of third parties in intergroup conflicts, with implications for the management of people’s emotions and behaviors in social crises.

Keywords

attribution cognition (attribution)–emotion–action model COVID-19 intergroup discrimination third-party observer

The global outbreak of novel coronavirus disease COVID-19 has profoundly threatened the mental and physical health of people worldwide. The COVID-19 pandemic continues to exhibit a trend of sporadic outbreaks, affecting people’s daily lives (World Health Organization [WHO], 2021). With the development of the pandemic, intergroup discrimination associated with the disease has become increasingly prominent (Zuo & Wen, 2020). For instance, during the outbreak, there were numerous media reports about discrimination against people from Wuhan and Hubei, such as the leaking of personal information of “returnees from Wuhan,” and refusing to let “workers from Hubei” enter their destination cities.

These discrimination incidents have undoubtedly caused great distress to the individuals involved. Although third parties did not directly participate in the incidents, the pandemic context and high level of coverage of such incidents by the media ensured a certain degree of involvement of the population. Previous studies have shown that the attitudes and behaviors of third parties in intergroup discrimination have an important impact on the progression of the incident, which helps to punish offenders and maintain social norms (Fehr & Fischbacher, 2004). Hence, investigating the mental and behavioral responses of third-party observers in incidents of intergroup discrimination during the COVID-19 pandemic has significant practical implications for intergroup conflict intervention during public health emergencies.

Aggressive and Avoidant Responses of Third-Party Observers in Intergroup Discrimination

Established theories have provided an enlightening perspective for understanding the reactions of “third-party observers” in intergroup discrimination. According to the Deontic justice theory proposed by Folger (2001), although the observers are not parties to the discrimination incident, they will experience similar pain and injustice as the victims. Further, based on the moral assumption, observing or hearing behaviors that violate social norms will trigger individuals’ emotional reactions, which in turn will cause them to act to punish the offenders and help restore social justice (O’Reilly & Aquino, 2011; Xu et al., 2020). Collectively, these theories indicate that the cognitive, emotional, and behavioral tendencies of third-party observers in intergroup conflicts can never be overlooked, for they are an essential element for the maintenance of social norms and group cooperation (Buckholtz & Marois, 2012; Fehr & Fischbacher, 2004). The third-party observers investigated in the current study refer to individuals who were not directly involved in the discrimination incidents but were indirectly informed of the events (Xu et al., 2020), representing the most common form of third parties in the context of a social lockdown. Therefore, an in-depth exploration of their psychological and behavioral patterns is of great significance to better understand and manage the side effects of intergroup discrimination in a social crisis.

The behaviors from intergroup affect and stereotypes (BIAS) map developed from the stereotype content model (SCM) suggests that an individual’s cognition of others based on warmth and competence dimensions can effectively predict their subsequent behavioral intentions. Several lines of evidence suggest that people tend to show aggressive behaviors toward individuals with low warmth, while adopting avoidant strategies toward those with low competence (Cuddy et al., 2007; Ufkes et al., 2012; Zuo et al., 2006). Aggression and avoidance in the BIAS map model are consistent with the two main negative behavioral reactions of “confrontation and attack” and “avoidance and separation” found in intergroup contact research (Alston et al., 2020). Meanwhile, they also conform to the behaviorist view of positive and negative punishment: aggression indicates imposing a negative stimulus on the target, while avoidance means the deprivation of social resources (Malouff et al., 2009). Hence, the present study mainly focuses on the behavioral intentions of aggression and avoidance of third-party observers toward the discriminator.

Unlike the everyday intergroup discrimination incidents explored in previous studies, the COVID-19 pandemic placed observers in the same social crisis context as the parties directly involved, which may make them more engaged in the discriminatory situation and thus develop a stronger tendency to defend social norms. However, simultaneously, they may also have a higher motivation to safeguard their own interests and avoid losses under the high-threat and high-stress conditions of the pandemic (Bruni et al., 2008; Zhou & Xie, 2015; Zuo & Wen, 2020). This begs the question: under these two conflicting motivations, what pattern of behavioral tendencies will third-party observers show to the discriminators? This study aims to investigate this issue and hypothesizes that, under the combined effect of the motivation to maintain social norms and self-interest, third-party observers may show coexisting behavioral strategies of aggression and avoidance (H1).

Effect of Anger and Contempt on Aggression and Avoidance Behaviors

Emotions often play an important mediating role in the association between cognition and behaviors (Tomkins, 1962; Weiner et al., 1978, 1979). According to the appraisal theory of emotion, people’s emotions triggered by specific situations are essential determinants of their behavioral responses (Frijda et al., 1989). This study focuses on the two emotions of anger and contempt because they frequently occur in negative social interactions and are closely linked to the negative appraisal of others’ intentions (Fischer & Roseman, 2007; Kuppens et al., 2003). Meanwhile, based on the contempt, anger, and disgust hypothesis proposed by Rozin et al. (1999), these emotions provide the emotional basis for morality and are elicited by violations of three different moral domains. Anger in response to the violation of autonomy (rights and freedom of individuals); contempt in response to the violation of the ethic of community (respect and responsibility); and disgust in response to the violation of divine ethics (purity, beauty; Fischer & Roseman, 2007; Rozin et al., 1999). The incidents of intergroup discrimination explored in the current study are primarily related to the infringement of the social norms of autonomy and community. Hence, our focus on the emotions of anger and contempt is reasonable and meaningful.

Previous research has shown a strong association between the emotions of anger and contempt and the behavioral intentions of aggression and avoidance (Ufkes et al., 2012). Anger is generally regarded as a member of the attack emotion family. Empirical evidence regarding the emotion–behavior relationship demonstrates that there is a preferential association between anger and approach motivation (Carver & Harmon-Jones, 2009; Harmon-Jones & Peterson, 2008), as aggression is an important example of approaching behavior, and anger tends to elicit aggressive behaviors (Du, 2012; Wilkowski & Robinson, 2012). The emotion of contempt, however, is considered as belonging to the exclusion emotion family, which prompts people to exclude others from their social networks and to exhibit avoidance behaviors (Fischer & Roseman, 2007; Frijda et al., 1989; Hutcherson & Gross, 2011; Mackie et al., 2000).

Furthermore, considerable evidence indicates that anger leads to avoidance behaviors, whereas contempt leads to aggressive behaviors. Specifically, research supports the correlation between anger and avoidance motivation that further predicts avoidance behaviors (Balconi & Mazza, 2010; Stewart et al., 2010; Zinner et al., 2008). The intergroup affect and stereotypes map model also suggests that individuals’ contempt for targets with low warmth and competence has a crucial role in the development of subsequent aggressive behaviors, indicating the association between contempt and aggression (Cuddy et al., 2008). The diverse patterns of emotion–behavior associations are consistent with findings of the binary coexistence of emotional arousal and behavioral reactions to out-groups. For instance, it has been found that people show both active harm behaviors (i.e., aggression, attack) and passive harm behaviors (i.e., avoidance, rejection) in response to out-group members with low warmth and competence (Cuddy et al., 2008; Guan & Cheng, 2011). However, most studies in this field have only focused on the separate effect of anger or contempt, not on their combined effect as mediating variables. To address this research gap, the second aim of this study is to simultaneously examine the effects of the emotions of anger and contempt on behavioral intentions.

Further, based on the social functional view of emotion, self-involvement is an important factor influencing the association between emotions and behavioral responses (Hutcherson & Gross, 2011). On the one hand, third-party observers are not directly involved in the discrimination incidents; thus, their involvement is relatively lower compared to those directly involved. On the other hand, different from usual intergroup conflicts, the observers included in this study—both the discriminators and the discriminated—were operating in the context of the COVID-19 pandemic, which may make them more concerned about the events and thus more involved than observers of traditional intergroup conflicts (Wen et al., 2020). Consequently, it is worthwhile to further investigate how the emotions of observers connect with their behavioral intentions during the pandemic. Based on theoretical and empirical evidence, it is hypothesized that observers’ anger and contempt will predict subsequent aggression and avoidance behaviors and exhibit parallel mediated forms (H2).

Effect of Attribution Tendencies on Emotional and Behavioral Responses

According to the cognitive (attribution)–emotion–action model, individuals’ cognitive attribution of events is a decisive factor for their subsequent emotional and behavioral responses. It has been shown that cognitive attribution will first affect people’s emotions, which in turn impact the relevant behaviors (Tomkins, 1962; Weiner et al., 1978, 1979). Attribution is a cognitive process that allows people to identify causes of events through information-processing activities, including perception, thinking, and inferring based on known results (Liu, 2010). Attribution theory was first proposed by Heider (1958), who divided the causes of actions or events into “internal causes” and “external causes.” Internal attribution, also known as dispositional attribution, refers to the tendency to assign causes of events to inherent traits of actors, such as their personality, efforts, and ability, while external attribution, also known as situational attribution, refers to the tendency to attribute causes of events to situational influences, including environmental conditions, interference from others, and luck. In addition, it includes the underlying assumption that most people will act the same way in a certain situation (Heider, 1958; Teng et al., 2021).

Previous studies are limited to exploration of the influence of group identities or social situations on attribution, paying less attention to the after-effects of attribution. However, according to the cognitive (attribution)–emotion–action model, people’s emotional and behavioral responses to others vary greatly depending on their attribution tendencies (Vargas, 2021; Weiner, 1980). Data from several studies suggest that when internal attributions are made for negative behaviors, people will develop higher levels of anger and further produce avoidant or punitive behaviors toward the targets (Palazzolo & Roberto, 2011). Moreover, studies on intergroup conflict have also shown that hostile attributions to out-groups can effectively predict aggressive behaviors (Crick & Dodge, 1994; Li, 2017; Sun & Yang, 2013). It has also been reported that internal attribution of negative behaviors will lead to a greater tendency to believe that the occurrence of an event was controlled and intentional, which in turn will generate higher contempt and further promote avoidance behaviors (Fischer & Roseman, 2007; Weiner, 1980).

This poses the question of how third-party observers’ attribution of discriminatory behaviors in incidents of intergroup discrimination affects their behavioral intentions through emotions. The current study seeks to explore this issue. Based on the cognitive (attribution)–emotion–action model and empirical evidence, we hypothesize that individuals’ internal attribution tendencies will elicit higher levels of contempt and anger, which in turn will produce aggressive or avoidant behavioral responses.

The Present Study

Based on the perspective of third-party observers, the current research examined a parallel mediating model through three studies. In the first two studies, the parallel mediation model was used to test the influence of observers’ internal attribution tendencies on their behavioral intentions of aggression and avoidance through the mediating role of the emotions of anger and contempt. The model was tested using two real events: a private information leak of returnees from Wuhan and the rejection of returning workers from Hubei, both of which were gathered social attention and concern. Study 3 sought to validate the causal logical sequence whereby individuals’ attributional tendencies influence their emotions and behaviors, by manipulating their internal and external attributional tendencies. The present study hypothesizes that third-party observers’ internal attribution tendencies will cause higher intentions to enact aggressive and avoidant behaviors, with anger and contempt playing a mediating role.

Study 1: A Test Based on the Incident of Intergroup Discrimination Against Returnees From Wuhan

Study 1 aimed to conduct a preliminary test on the parallel mediation model. This study focused on intergroup discrimination against returnees from Wuhan, examining the influence of observers’ attribution tendencies on their aggressive and avoidant behavioral intentions, with the mediating effect of the emotions of anger and contempt.

Method

Participants

This cross-sectional study was conducted between March 23 and April 8, 2020. Due to the pandemic, this study was conducted through an online questionnaire platform (www.wjx.com), a commonly used channel for online surveys conducted in China. Moreover, we partially adopted the snowball sampling technique, which has been widely used in research conducted during the pandemic (e.g., Ogueji et al., 2021; Ozamiz-Etxebarria et al., 2020), to distribute questionnaires. Questionnaires were first distributed to the online subject pool (QQ or WeChat groups); participation was voluntary in this survey and participants were encouraged to distribute the questionnaires to others.

The final sample was collected according to the following inclusion criteria. (a) In order to ensure validity of the online questionnaires as well as participants’ conscientiousness in answering, based on the estimated time required to complete the survey (10 minutes), questionnaires with too short (indicating the participant was not answering seriously) or too long (indicating web page failure or distraction while answering) completion times were excluded (two participants who spent 3 SD longer than the average time were removed). (b) To prevent participants’ personal experience of the incident from interfering with their judgment as third-party observers, the question “Am I a returnee from Wuhan?” was included in the questionnaire (30 people were identified as returnees from Wuhan and their questionnaires were excluded).

The final sample consisted of 333 respondents: 80 (24.00%) were male, and 253 (76.00%) were female. Their ages ranged from 18 to 64 years (M = 28.44, SD = 11.00). The sample was sourced from 111 cities in 30 provinces across China: 35 (10.51%) participants were from Wuhan, 51 (15.32%) were from other cities in Hubei, and 247 (74.17%) were from other provinces or municipalities (see Table 1). Thus, the sample had relatively high representativeness.

Table 1.

Descriptive statistics of sociodemographic variables: Study 1.

Continuous variables		M	SD
Age		28.44	11.00
Socioeconomic status		4.90	1.67
Categorical variables		N	%
Gender	Male	80	24.00
	Female	253	76.00
Location	Wuhan	35	10.51
Location	Other regions in Hubei	51	15.32
	Other provinces and municipalities	247	74.17

Measures

Emotions and behaviors toward discriminators

Participants’ anger and contempt, as well as their avoidant and aggressive behavioral intentions toward discriminators, were measured in the study. To clarify to participants the targets of their emotions and behavioral intentions, the following item was included in the questionnaire: “For those people who leaked the private information of returnees from Wuhan, I would feel . . .” Two items (“I am angry with discriminators” and “I feel contempt for discriminators”) were adopted to measure emotions. In addition, two items (“I want to avoid discriminators” and “I want to attack discriminators”) were adopted to measure behavioral intentions. All four items used 7-point Likert scales (on the emotion scale: 1 = not at all, 7 = very strongly; on the behavioral intention scale: 1 = I completely disagree, 7 = I completely agree).

Attribution tendencies

We compiled the internal and external attribution scales to measure participants’ attribution tendencies. The Internal Attribution Scale included “knowledge,” “competence,” “morality,” “personal prejudice,” “inner fears,” “personality trait,” and “self-protection.” These items were measured using a 7-point Likert scale (1 = I completely disagree, 7 = I completely agree). Cronbach’s α for the scale was .85. Furthermore, the External Attribution Scale included “lack of communication,” “conformity,” “government management,” “epidemic control needs,” “prevention and control conditions,” “media propaganda influence,” and “competition between groups.” These items were measured using a 7-point Likert scale (1 = I completely disagree, 7 = I completely agree). Cronbach’s α for the scale was .81.

Procedures and materials

This study was conducted between March 23 and April 8, 2020. According to the statistics of the National Health Commission of the PRC, the cumulative number of confirmed COVID-19 cases in China was 81,439 by March 28, while the cumulative number of confirmed COVID-19 cases was 81,865 by April 8, indicating the ongoing critical period of COVID-19 pandemic prevention and control. First, news about discrimination incidents during the pandemic was collected, and the leakage of private information of returnees from Wuhan event was finally selected as our study material. According to an authoritative information source, this incident occurred around January 27, 2020, and since then it has attracted widespread attention and caused major social impact.

Participants engaged in the task through the online questionnaire platform. They were required to read the instructions and confirm that they had understood the requirements and contents of the study before beginning with the formal task. Participants were first provided with a description of the discrimination incident adapted from the real news: “Previously, the information of nearly 10,000 returnees from Wuhan was leaked, the private information was circulated indiscriminately on the Internet, thus causing a lot of trouble.” Participants were instructed to report their attributions (internal and external) of this incident, emotions, and behavioral intentions toward the discriminators based on the description they had read. Finally, they completed a demographic questionnaire that included gender, age, current location, and subjective socioeconomic status.

Results

Test for common method bias

Since the data on multiple variables in this study were provided by participants themselves via self-report questionnaires, there may be a common method bias effect. A Harman one-factor test was conducted to check for possible common method bias in the study (Hair et al., 1998); all the terms of the study variables were loaded on the same common factor. Results showed that the common factor explained 25.25% of the total variance. Thus, to some extent, there is no common method deviation in this study.

Descriptive statistics

The measure of individuals’ attribution in this study consisted of two dimensions: internal attribution and external attribution; hence, there may be a condition where both internal and external attributions are high, or both of them are low. Since our study focuses on the attribution tendency of observers and its impact on subsequent emotions and behavioral intentions, the difference between the scores of the internal and external attribution scales was used as indicator of the attribution tendency. That is, the higher the difference values, the more likely the participants are to make internal attributions. This operational method has been widely applied in the calculation of internal and external attribution. For example, Na et al. (2010) required participants to attribute the behaviors of target people, and the difference between external situational attribution and dispositional attribution was used as an indicator of attribution tendency (Na et al., 2010). Therefore, the calculation method of internal attribution tendencies in the current study is reasonable and can reflect individuals’ attribution of discriminators’ behavior.

Descriptive statistics and correlation analysis of internal attribution tendencies, emotions of anger and contempt, as well as avoidant and aggressive behavioral intentions are shown in Table 2. The results showed that anger was positively correlated with contempt, avoidant behavior, aggressive behavior, and internal attribution; contempt was positively correlated with avoidant behavior, aggressive behavior, and internal attribution tendency; and avoidant behavior was positively correlated with aggressive behavior and internal attribution tendency. There was also a significant positive correlation between aggressive behavior and internal attribution tendency.

Table 2.

Descriptive statistics and correlation analysis of anger, contempt, avoidance, and aggression: Study 1.

	M ± SD	Anger	Contempt	Avoidance behavior	Aggressive behavior	Internal attribution tendency
Anger	5.47 ± 1.50	1.00
Contempt	4.50 ± 1.86	.59**	1.00
Avoidance behavior	4.30 ± 1.83	.46**	.55**	1.00
Aggressive behavior	3.34 ± 1.86	.44**	.55**	.42**	1.00
Internal attribution tendency	3.93 ± 8.33	.29**	.24**	.20**	.19**	1.00

p < .05.**p < .01.***p < .001.

The predictive effect of internal attribution tendency on avoidant behavior: Test of the parallel mediation model of anger and contempt

The bias-corrected bootstrap method and PROCESS macro Model 4 were used to test for mediation effects (Hayes, 2013). Taking gender and age as control variables, 5,000 samples were randomly selected to estimate the 95% confidence interval of the mediating effect, in order to analyze the parallel mediating effect of anger and contempt between internal attribution tendency and avoidant behavior.

As shown in Table 3, an internal attributional tendency positively predicted avoidant behavior (B = 0.05, p < 0.001), anger (B = 0.05, p < 0.001), and contempt (B = 0.06, p < 0.001). In addition, both anger and contempt predicted avoidant behavior (B = 0.26, p < 0.001; B = 0.43, p < 0.001).

Table 3.

Regression analysis predicting avoidant behavior: Study 1.

Regression equation(N = 333)	Fit indices				Coefficient significance
Result variables	Predictors	R	R ²	F	B (β)	t
Avoidant behavior	Internal attribution tendency	.21	.04	5.06***	0.05	3.84***
Anger	Internal attribution tendency	.30	.09	11.00***	0.05	5.41***
Contempt	Internal attribution tendency	.26	.07	7.62***	0.06	4.72***
Avoidant behavior	Anger	.58	.34	32.90***	0.26	3.56***
	Contempt				0.43	7.40***
	Internal attribution tendency				0.01	0.93

p < .05.**p < .01.***p < .001.

Mediating effect analysis showed that anger played a mediating role in the influence of internal attribution tendency on avoidant behavior (see Figure 1). In addition, the point of the mediating effect equated to 0.013, accounting for 18% of the total effect, while the bootstrap 95% confidence interval of the indirect effect did not contain zero, indicating that the indirect effect is significant. Meanwhile, contempt played a mediating role in the influence of internal attribution tendency on avoidant behavior. The point of the mediating effect equated to 0.024, accounting for 95% of the total effect, and the bootstrap 95% confidence interval of the indirect effect did not contain zero, indicating that the indirect effect is significant. The analysis showed that the confidence interval of both the total effect and the indirect effect did not contain zero; however, the confidence interval of the direct effect did contain zero, indicating that there was a full mediating effect between internal attribution tendencies and avoidant behavior via anger and contempt.

Figure 1.

Multiple mediation test of the relationship between internal attribution tendency and avoidant behavior through the emotions of anger and contempt.

The predictive effect of internal attribution tendency on aggressive behavior: Test of the parallel mediation model of anger and contempt

As shown in Table 4, internal attribution tendency positively predicted aggressive behavior (B = 0.04, p < 0.001), anger (B = 0.05, p < 0.001), and contempt (B = 0.06, p < 0.001). In addition, anger, as well as contempt, also positively predicted aggressive behavior (B = 0.22, p < 0.001; B = 0.44, p < 0.001).

Table 4.

Regression analysis predicting aggressive behavior: Study 1.

Regression equation(N = 333)	Fit indices				Coefficient significance
Result variables	Predictors	R	R ²	F	B (β)	t
Aggressive behavior	Internal attribution tendency	.20	.04	4.70**	0.04	3.44***
Anger	Internal attribution tendency	.30	.09	11.00***	0.05	5.41***
Contempt	Internal attribution tendency	.26	.07	7.62***	0.06	4.72***
Aggressive behavior	Anger	.57	.33	31.76***	0.22	3.05**
	Contempt				0.44	7.66***
	Internal attribution tendency				0.01	0.55

p < .05.**p < .01.***p < .001.

Mediating effect analysis showed that anger played a mediating role in the influence of internal attribution tendency on aggressive behavior (see Figure 2). In addition, the point of the mediating effect equated to 0.011, accounting for 26% of the total effect, and the bootstrap 95% confidence interval of the indirect effect did not contain zero, indicating that the indirect effect is significant. Furthermore, contempt played a mediating role in the influence of internal attribution tendency on aggressive behavior. In addition, the point of the mediating effect equated to 0.025, accounting for 60% of the total effect, and the bootstrap 95% confidence interval of the indirect effect did not contain zero, indicating that the indirect effect is significant. The analysis showed that the confidence intervals of the total effect and the indirect effect did not contain zero; however, the confidence interval of the direct effect did contain zero, indicating that there was a full mediating effect between internal attribution tendency and the aggressive behaviors via anger and contempt.

Figure 2.

Multiple mediation test of the relationship between internal attribution tendency and aggressive behavior through the emotions of anger and contempt.

Discussion

Study 1 examined the parallel mediating effect of contempt and anger on the association between the attribution tendency of third-party observers and their behavioral intentions of aggression and avoidance, using the discrimination incident against returnees from Wuhan. The results supported our hypotheses and are consistent with the cognition (attribution)–emotion–action model, that is, both anger and contempt play a parallel and complete mediating role between internal attribution tendency and aggressive or avoidant behaviors. Specifically, the model suggests that an increase in internal attribution will promote feelings of both anger and contempt, thus leading to an increase in aggressive or avoidant responses, which is consistent with the trends observed in previous studies. In addition, the results also indicate that the association between emotions and behavioral intentions of observers exhibits a pattern of “binary coexistence.” That is, from the perspective of observers, the emotions of anger and contempt exhibit parallel mediating effects that simultaneously predict behavioral intentions of aggression and avoidance.

Study 2: A Test Based on the Incident of Intergroup Discrimination Against Returning Workers From Hubei

Study 2 aimed to further investigate the parallel mediating role of anger and contempt in the relationship between attribution tendency and aggressive/avoidant behavioral intention of third-party observers, based on the incident of intergroup discrimination against returning workers from Hubei.

Method

Participants

This cross-sectional study was conducted between March 23 and April 8, 2020 through an online questionnaire platform (www.wjx.com). Questionnaires were first distributed to the online subject pool; participants voluntarily engaged in this task and were encouraged to pass on the questionnaires to others.

Based on the estimated time required to complete the survey (10 minutes), three participants who spent 3 SD longer than the average time were excluded. In order to avoid interference of participants’ personal experience of the incident, the question “Am I a returning worker from Hubei?” was included in this questionnaire. Eventually, 19 people were identified as returning workers from Hubei, and their questionnaires were excluded.

The final sample consisted of 346 respondents: 74 (21.40%) were male, and 272 (78.60%) were female. Their ages ranged from 18 to 64 years old (M = 27.97, SD = 10.82). The sample was sourced from 122 cities in 30 provinces across China: 88 (25.43%) participants were from Hubei, and 258 (74.57%) participants were from other provinces or municipalities (see Table 5). Thus, the sample had relatively high representativeness.

Table 5.

Descriptive statistics of sociodemographic variables: Study 2.

Continuous variables		M	SD
Age		27.97	10.82
Socioeconomic status		4.93	1.64
Categorical variables		N	%
Gender	Male	74	21.40
	Female	272	78.60
Location	Hubei	88	25.43
Location	Other provinces and municipalities	258	74.57

Measures

Emotions and behavioral responses toward discriminators

We used the same measurements as in Study 1 for observers’ emotions of anger and contempt and aggression and avoidance behaviors. The following item was included in the questionnaire: “For those people who prevented returning workers from Hubei from entering their cities, I would feel . . .”

Attribution tendencies

Participants’ attribution tendencies were measured using the same internal and external attribution scales as in Study 1. Both internal and external attribution scales obtained high internal consistency reliability, with Cronbach’s α of .85 and .81, respectively.

Procedure and measurement

This study was conducted between March 23 and April 8, 2020; according to the statistics of the National Health Commission of the PRC, the cumulative COVID-19 cases still showed an upward trend. News about discrimination incidents during the pandemic was collected, and the “rejection of returning workers from Hubei” event was selected as the material for Study 2. According to an authoritative information source, this incident occurred between March 18 and 19, 2020, attracting widespread social attention.

Participants engaged in the task through the online questionnaire platform. Before starting with the formal task, they were required to read the instructions and confirm that they had understood the requirements and contents of the study. Participants were first provided with a description of the discrimination incident adapted from the real news: “Recently, several buses carrying returning workers from Hubei were rejected when they arrived at their destination; they were waiting late into the night, and some of them had to return to Hubei.” Then, participants were instructed to report their attributions (internal and external) of this incident, emotions, and behavioral intentions toward the discriminators based on the description they had just read. Consistent with Study 1, a demographic questionnaire that included gender, age, current location, and participants’ subjective socioeconomic status was completed.

Results

Test for common method bias

A Harman one-factor test was conducted to check for possible common method bias in the study; all the terms of the study variables were loaded on the same common factor. Results showed that the common factor explained 23.92% of the total variance. Thus, to some extent, there is no common method deviation in this study.

Descriptive statistics

As in Study 1, this study also used the difference between participants’ internal and external attribution scale scores to indicate their attribution tendency. The higher the score, the stronger the internal attribution tendency of the discriminator’s behavior.

Descriptive statistics and correlation analysis of internal attribution tendency, anger and contempt, as well as avoidant and aggressive behavioral intentions are shown in Table 6. The results showed that anger was positively correlated with internal attribution, avoidant behavior, aggressive behavior, and contempt; contempt was positively correlated with internal attribution, avoidant behavior, and aggressive behavior; and avoidant behavior was positively correlated with aggressive behavior and internal attribution. There was also a significant positive correlation between aggressive behavior and internal attribution tendency.

Table 6.

Descriptive statistics and correlation analysis of anger, contempt, avoidance and aggression: Study 2.

	M ± SD	Anger	Contempt	Avoidance behavior	Aggressive behavior	Internal attribution tendency
Anger	4.56 ± 1.67	1.00
Contempt	3.51 ± 1.81	.62**	1.00
Avoidance behavior	3.49 ± 1.76	.53**	.76**	1.00
Aggressive behavior	2.65 ± 1.70	.64**	.64**	.60**	1.00
Internal attribution tendency	−0.02 ± 7.51	.43**	.32**	.24**	.25**	1.00

p < .05.**p < .01.***p < .001.

The predictive effect of internal attribution tendency on avoidant behavior: Test of the parallel mediation model of anger and contempt

The bias-corrected bootstrap method and PROCESS macro Model 4 were used to test for mediation effects. Taking gender and age as control variables, 5,000 samples were randomly selected to estimate the 95% confidence interval of the mediating effect, in order to analyze the parallel mediating effect of anger and contempt between internal attribution tendency and avoidant behavior.

As shown in Table 7, internal attribution tendency positively predicted avoidant behavior (B = 0.06, p < 0.001), anger (B = 0.09, p < 0.001), and contempt (B = 0.08, p < 0.001). In addition, anger, as well as contempt, positively predicted avoidant behavior (B = 0.11, p < 0.001; B = 0.71, p < 0.001).

Table 7.

Regression analysis predicting avoidant behavior: Study 2.

Regression equation(N = 346)	Fit indices				Coefficient significance
Result variables	Predictors	R	R ²	F	B (β)	t
Avoidant behavior	Internal attribution tendency	.27	.07	8.71***	0.06	4.53***
Anger	Internal attribution tendency	.46	.21	30.09***	0.09	8.79***
Contempt	Internal attribution tendency	.40	.16	22.00***	0.08	6.21***
Avoidant behavior	Anger	.77	.60	100.04***	0.11	2.28*
	Contempt				0.71	16.28***
	Internal attribution tendency				−0.01	−0.86

p < .05.**p < .01.***p < .001.

Mediating effect analysis showed that anger played a mediating role in the relationship between internal attribution tendency and avoidant behavior (see Figure 3). Moreover, the point of the mediating effect equated to 0.01, accounting for 18% of the total effect. Furthermore, the bootstrap 95% confidence interval of the indirect effect did not contain zero, indicating that the indirect effect is significant. Meanwhile, contempt played a mediating role in the influence of internal attribution tendency on avoidant behavior. Moreover, the point of the mediating effect equated to 0.05, accounting for 95% of the total effect. Furthermore, the bootstrap 95% confidence interval of the indirect effect did not contain zero, indicating that the indirect effect is significant. The analysis showed that the confidence interval of both the total effect and the indirect effect did not contain zero; however, the confidence interval of the direct effect contained zero, indicating that there was a full mediating effect between internal attribution tendency and avoidant behaviors via anger and contempt.

Figure 3.

Multiple mediation test of the relationship between internal attribution tendency and avoidant behavior through the emotions of anger and contempt.

The predictive effect of internal attribution tendency on aggressive behavior: Test of the parallel mediation model of anger and contempt

The bias-corrected bootstrap method and PROCESS macro Model 4 were used in this study. Taking gender and age as control variables, 5,000 samples were randomly selected to estimate the 95% confidence interval of the mediating effect, in order to analyze the parallel mediating effect of anger and contempt between internal attribution tendency and aggressive behavior.

As shown in Table 8, internal attribution tendency positively predicted aggressive behavior (B = 0.06, p < 0.001), anger (B = 0.09, p < 0.001), and contempt (B = 0.08, p < 0.001). In addition, both anger and contempt positively predicted aggressive behavior (B = 0.16, p < 0.001; B = 0.50, p < 0.001).

Table 8.

Regression analysis predicting aggressive behavior: Study 2.

Regression equation(N = 346)	Fit indices				Coefficient significance
Result variables	Predictors	R	R ²	F	B (β)	t
Aggressive behavior	Internal attribution tendency	.29	.09	10.79***	0.06	4.75***
Anger	Internal attribution tendency	.46	.21	30.09***	0.09	8.79***
Contempt	Internal attribution tendency	.40	.16	22.00***	0.08	6.21***
Aggressive behavior	Anger	.65	.42	49.28***	0.16	2.88**
	Contempt				0.50	9.92***
	Internal attribution tendency				0.003	0.30

p < .05.**p < .01.***p < .001.

Mediating effect analysis showed that anger played a mediating role in the influence of internal attribution tendency on aggressive behavior (see Figure 4). Moreover, the point of the mediating effect equated to 0.02, accounting for 27% of the total effect. Furthermore, the bootstrap 95% confidence interval of the indirect effect did not contain zero, indicating that the indirect effect is significant. Meanwhile, contempt played a mediating role in the influence of internal attribution tendency on aggressive behavior. Moreover, the point of the mediating effect equated to 0.04, accounting for 66% of the total effect. Furthermore, the bootstrap 95% confidence interval of the indirect effect did not contain zero, indicating that the indirect effect is significant. The analysis showed that the confidence interval of both the total effect and the indirect effect did not contain zero, but the confidence interval of the direct effect did contain zero, indicating that there was a full mediating effect between internal attribution tendency and aggressive behaviors via anger and contempt.

Figure 4.

Multiple mediation test of the relationship between internal attribution tendency and aggressive behavior through the emotions of anger and contempt.

Discussion

Study 2 tested the parallel mediating model based on intergroup discrimination against returning workers from Hubei, aiming to further verify and expand the findings of Study 1. The results support our hypotheses, indicating that internal attribution of third-party observers can influence avoidant and aggressive behaviors through a parallel mediating effect of anger and contempt. In other words, consistent with the findings of Study 1, this study supports our model and provides evidence for the cognition (attribution)–emotion–action model from the perspective of third-party observers.

Study 3: A Causal Test of Attribution Tendencies on Third-Party Observers’ Emotions and Behavioral Intentions

The results of the first two studies support the parallel mediation model in which the internal attribution tendencies of third-party observers contribute to aggressive and avoidant behavioral intentions through the emotions of anger and contempt. To further verify the causal relationship between attribution tendencies and individuals’ emotions and behavioral intentions toward the discriminators, this study manipulated observers’ internal and external attributions, aiming to test whether the differences in individuals’ emotions and behavioral intentions under different attribution tendencies conformed to the mediation model.

Method

Participants

According to G*Power, to detect an effect size of 0.5, with a probability of 1 − β = .95, given an α value of .05, the minimum sample size should be N = 54 (G*Power 3.1.9.4; Faul et al., 2009). This cross-sectional study was conducted through an online questionnaire platform (www.wjx.com); all participants enrolled in the study voluntarily, with their informed consent obtained prior to the start.

Based on the estimated time required to complete the task (3 minutes), a total of 12 participants who took less than 1 minute to complete the questionnaire, or were not serious in their answers, were excluded. To avoid interference of participants’ personal experience of the incidents, the questions “Am I a returnee from Wuhan?” and “Am I a returning worker from Hubei during the COVID-19 pandemic in 2020?” were included in the questionnaire. Thirty people were identified as returnees from Wuhan or returning workers from Hubei, and their questionnaires were excluded.

The final sample consisted of 73 respondents: 28 (38.40%) were male, and 45 (61.60%) were female. Their ages ranged from 18 to 56 years old (M = 23.25, SD = 6.11). The sample included eight (10.96%) participants from Wuhan, three (4.11%) participants from other regions in Hubei, and 62 (84.93%) participants from other provinces or municipalities (see Table 9). Thus, the sample had relatively high representativeness.

Table 9.

Descriptive statistics of sociodemographic variables: Study 3.

Continuous variables		M	SD
Age		23.25	6.11
Socioeconomic status		5.12	1.86
Categorical variables		N	%
Gender	Male	28	38.40
	Female	45	61.60
Location	Wuhan	8	10.96
	Other regions in Hubei	3	4.11
	Other provinces and municipalities	62	84.93

Design

A within-subject design was applied in this study, with the manipulated attribution tendencies as the independent variable. The dependent variables were observers’ emotions of contempt and anger and behavioral intentions of aggression and avoidance toward the discriminators.

As the mediating models of the two incidents in previous studies were consistent, the discrimination incidents of returnees from Wuhan and returning workers from Hubei were simultaneously adopted in the current study.

Measures

Emotions and behaviors toward discriminators

Participants’ emotions, as well as behavioral intentions, toward discriminators were measured. The following items were included in the questionnaire: “For those people who leaked the private information of returnees from Wuhan, I would feel . . .” and “For those people who prevented returning workers from Hubei from entering their cities, I would feel . . .” In addition to anger and contempt, the negative emotions of sadness, tension, and the affection of calmness were also measured in this study. Items of behavioral intention were consistent with those used in previous studies. All items were answered on 7-point Likert scales (for the emotion scale: 1 = not at all, 7 = very strongly; for the behavioral intention scale: 1 = I completely disagree, 7 = I completely agree).

Procedure and materials

As this experiment was conducted in the late pandemic period in China, a retrospective priming paradigm was adopted whereby participants were guided to review the COVID-19 pandemic situation in 2020 by reading the following instruction: “Please imagine you are back in the outbreak stage of COVID-19 in 2020, the following is a real-life event extracted from the news. Please carefully read the information and answer the following questions.” The descriptions of the two discrimination incidents presented to the participants were the same as those used in Studies 1 and 2.

Subsequently, the attribution tendencies of participants were manipulated. In line with the previous two studies, the current one considered the participants as third-party observers. Hence, participants were first presented with a picture and were led to imagine that the person in it represented themselves; next, they were presented with the description of the attribution of the discrimination incident (see Figure 5): “I believe that this discrimination incident was caused by internal reasons, such as the knowledge, morality, personality, and values of the people who blocked the returning workers from Hubei” (internal attribution) or “I believe that this discrimination incident was caused by external reasons, such as government requirements, prevention and control conditions, and media influence” (external attribution). After reading the materials, participants were required to evaluate their emotions and behavioral intentions toward the discriminators.

Figure 5.

Attribution tendency material in Study 3.

Participants were instructed to read either kind of incident material twice, separately, followed by the priming of internal and external attribution. To avoid the interference of sequence effect, the order of internal and external attribution priming was counterbalanced among participants. After completing the task, participants answered the demographic questionnaire.

Results

Data were analyzed using IBM SPSS 23.0. This study adopted a within-subject design; thus, a paired-sample t test was conducted on individuals’ responses in two attribution conditions to evaluate whether there was a significant difference between emotions and behavioral intentions after internal and external attributions.

In terms of emotions, observers’ self-reported anger ratings toward discriminators in the internal attribution condition (M = 5.14, SD = 1.57) were 0.77 (95% CI [0.32, 1.21]) higher than those in the external attribution condition (M = 4.37, SD = 1.80); the difference was statistically significant, t(72) = 3.46, p = .001, d = 0.40. In addition, scores of contempt in the internal attribution condition (M = 4.26, SD = 1.81) were 0.63 (95% CI [0.17, 1.09]) higher than that in the external attribution condition (M = 3.63, SD = 1.78); the difference was also statistically significant, t(72) = 2.74, p = .008, d = 0.32. But for the negative emotions of sadness (p = .27), tension (p = .83), and the emotion of calmness (p = .43), the difference between internal and external attribution conditions was not significant (p > .05), which indicates that the effect was not widespread in all negative emotions.

In terms of behavioral intentions, observers’ self-reported rating of avoidant behavior toward discriminators in the internal attribution condition (M = 4.38, SD = 1.83) was 0.70 (95% CI [0.27, 1.13]) higher than that in the external attribution condition (M = 3.68, SD = 1.87); the difference was statistically significant, t(72) = 3.22, p = .002, d = 0.38. In addition, the score of aggressive behavior in the internal attribution condition (M = 3.67, SD = 1.73) was 0.53 (95% CI [0.11, 0.96]) higher than that in the external attribution condition (M = 3.14, SD = 1.77); the difference was also statistically significant, t(72) = 2.53, p = .014, d = 0.30. Overall, both aggressive and avoidant behavioral intentions were significantly higher in the internal attribution contexts than in the external attribution ones.

Discussion

Based on the findings of Studies 1 and 2, the current study experimentally manipulated observers’ internal and external attribution tendencies, aiming to provide empirical evidence for the proposed parallel mediating model. The emotions of anger, contempt, sadness, tension, and calmness were measured. Results indicated that, compared with external attribution, observers had higher levels of anger and contempt toward the discriminator when the causes of the incidents were attributed internally. However, there was no significant difference in sadness, tension, and calmness emotions between the two conditions, suggesting that this phenomenon is not a generalized negative emotion effect. In terms of behavioral intentions, results also demonstrated that observers showed a higher intention of aggression and avoidance when internal attributions were made.

General Discussion

Through three experiments, the present study examined a parallel mediation model in which the attribution tendencies of third-party observers influence their behavioral intentions of aggression and avoidance through the mediating effect of anger and contempt. The experiments adopted two intergroup discrimination events as study material, a private information leak of returnees from Wuhan and the rejection of returning workers from Hubei, both of which had caught public attention. The results of the first two studies support our hypothesis that third-party observers’ internal attribution tendencies will lead to higher levels of anger and contempt, as well as aggressive and avoidant behavioral intentions. Moreover, the model also indicated that emotions play a complete and parallel mediating role between observers’ cognitive attribution tendencies and their aggressive and avoidant behaviors toward the discriminators. Study 3 manipulated the attribution tendencies of observers, providing empirical evidence for the causal logic from attribution tendencies to emotions, and further confirming the validity of the parallel mediation model.

This study investigated the after-effects of cognitive attribution on emotions and behavioral intentions. The three studies confirmed that the attribution tendencies of third-party observers can influence their behavioral intentions through the mediating effect of emotions, which is in line with the cognitive (attribution)–emotion–action model. It suggests that individuals’ cognitive attribution tendencies of events can affect their emotions, which will affect their subsequent behavioral responses (Tomkins, 1962; Weiner et al., 1978, 1979). The parallel mediation model further shows that the higher the observer’s internal attribution tendency of discrimination events, the more anger and contempt they will experience toward the discriminator, which will further lead to either aggressive or avoidant behaviors.

Specifically, the association between internal attribution tendency and stronger emotions and behavioral intentions is consistent with the studies of Palazzolo and Roberto (2011) and Li (2017), which found that when negative actions are internally attributed, individuals experience stronger contempt or anger, which in turn affects their behavioral decisions. This may be because, in the intergroup discrimination events regarding Wuhan returnees and Hubei workers, when observers attributed the discriminatory behaviors to discriminators’ internal and dispositional factors such as “moral traits” or “ability and quality traits” rather than to environmental uncontrollable factors, individuals were more likely to believe that discriminators should be held accountable for the events; this resulted in stronger emotional and behavioral responses. Our results are also similar to those of previous research on the impact of attribution of responsibility on anger; that is, when individuals believe that the occurrence of a negative incident is due to the personal characteristics of a subject, it will lead to greater anger (Yang et al., 2017). In the current study, the discriminators’ behaviors mainly reflect the violation of social norms and human rights. Therefore, according to the contempt, anger, and disgust hypothesis, third-party observers’ internal attributions of an event would primarily elicit heightened anger and contempt (Fischer & Roseman, 2007; Rozin et al., 1999).

Furthermore, the parallel mediation model also shows that there is a generalized association between anger, contempt, aggression, and avoidance from the perspective of third-party observers. The results here differ from the specific one-to-one connections between emotions and behaviors of directly involved parties found in prior studies (Fischer & Roseman, 2007; Hutcherson & Gross, 2011). Previous research generally proposed that anger would induce approach motivation, with the aim to attack others to obtain favorable outcomes. Contempt, however, would induce avoidance motivation, which is aimed at reducing social contact and is therefore associated with avoidant behaviors (Frijda et al., 1989; Hutcherson & Gross, 2011; Mackie et al., 2000). However, there is also evidence for associations between contempt and aggression, and anger and avoidance. For instance, the BIAS map model suggests that individuals tend to show contempt for subjects rated as having “low warmth and competence,” which further leads to aggressive behavioral responses (Cuddy et al., 2008). Moreover, studies have found that anger is correlated with avoidance motivation, which predicts avoidant behaviors (Balconi & Mazza, 2010; Stewart et al., 2010; Watson, 2009; Zinner et al., 2008).

Unlike previous studies that focused on the perspective of directly involved parties (Ufkes et al., 2012; Zuo et al., 2018), the current research explored the cognitive attributions, emotions, and behavioral tendencies of third-party observers, that is, people who were not directly involved in the discrimination events but were indirectly informed about them. The aforementioned differences in the association between emotion and behavior may be related to the lower involvement of observers compared to that of directly involved parties (Hutcherson & Gross, 2011). Because observers are not directly involved in the events, they have to make judgments while lacking important contextual information; thus, it is difficult for them to make clear choices when judging behavioral tendencies. In addition, this result is consistent with the binary coexistence of emotional arousal and behavioral responses to out-groups found in previous studies, whereby anger and contempt, which are jointly associated with negative evaluations of others, will be equally relevant and will act together in subsequent aggressive and avoidant behaviors (Guan & Cheng, 2011).

Implications

The parallel mediation model on the relationship between observers’ attribution tendencies and emotional and behavioral responses makes both theoretical and practical contributions.

Theoretically, the parallel mediation model provides further empirical evidence for the mechanism by which cognitive attributions influence subsequent emotions and behavioral intentions, enriching the cognitive (attribution)–emotion–behavior model from the perspective of third-party observers. Moreover, the associations between anger and contempt and aggressive and avoidant behaviors provide support for the appraisal theory of emotion that indicates the deciding impact of emotions on behaviors. In the applied dimension, the results indicate that the internal attribution tendencies of third-party observers can elicit feelings of anger and contempt, which in turn will trigger avoidant and aggressive behavioral intentions. These results suggest that the media should try to provide more timely, comprehensive, and unbiased coverage of intergroup discrimination incidents. Doing so will prevent audiences from receiving limited, internally attributed information about such incidents that may lead to more widespread social conflicts and cyberviolence (Gilles et al., 2013; van Bavel et al., 2020). Moreover, these findings have another important implication in the context of a social crisis; attention needs to be directed to the psychological states of the parties involved as well as those of third-party observers who are not directly involved in the events but are informed about them. In general, this study sheds light on the management of people’s emotions and behaviors in sudden social incidents, and provides intervention strategies from the perspective of cognitive attribution.

Limitations and Future Directions

Several limitations of the present research need to be taken into account. First, this study did not consider the different relationships between third-party observers, discriminators, and people discriminated against. In the future, group relations between observers and the parties involved in a conflict can be manipulated to examine the model in different connection conditions. Second, it is confirmed that the specific feelings people have toward other groups depend on the specific threats they perceive. The observers in this study may have simultaneously perceived a health threat from the discriminated people from Hubei and Wuhan, as well as the threat of inequity from the discriminators. Therefore, future studies could directly measure individuals’ attitudes to COVID-19 and those who might be infected, to investigate the moderating effect of perceived threats in the mediation model. Third, we mainly adopted a self-report method to measure individuals’ emotions and behavioral intentions. In future studies, the model can be further examined with implicit tests, situational experiments, or cognitive neuroscience methods.

Conclusion

In summary, the results suggest that regarding incidents of intergroup discrimination during the COVID-19 pandemic, internal attribution tendencies of third-party observers will lead to the rise of aggressive and avoidant behavioral intentions toward the discriminators, with the parallel and complete mediating effect of the emotions of anger and contempt. In general, the model constructed from the perspective of third-party observers enriches the cognitive (attribution)–emotion–action model, further enhancing our understanding of the role of third parties in intergroup conflicts. Moreover, the model provides empirical evidence of the importance of attending to the psychological states of the general population during social crises.

Supplemental Material

sj-docx-1-gpi-10.1177_13684302211062367 – Supplemental material for Effect of attribution on the emotions and behavioral intentions of third-party observers toward intergroup discriminators during the COVID-19 pandemic

Supplemental material, sj-docx-1-gpi-10.1177_13684302211062367 for Effect of attribution on the emotions and behavioral intentions of third-party observers toward intergroup discriminators during the COVID-19 pandemic by Bin Zuo, Hanxue Ye, Fangfang Wen, Wenlin Ke, Huanrui Xiao and Jin Wang in Group Processes & Intergroup Relations

Footnotes

Data sharing and data accessibility

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Ethics approval statement

The authors declare that the research adheres to the APA code. The Ethics Committee of the Center for Studies of Social Psychology at Central China Normal University (CSSP-2020019) gave permission for this research.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Major Program of the National Fund of Philosophy and Social Science of China (CN; 18ZDA331), National Post-funded Projects of Philosophy and Social Sciences (20FSHB003), and Self-determined Research Funds of CCNU from the Colleges’ Basic Research and Operation of MOE Grants (CCNU19ZN021).

ORCID iD

Fangfang Wen

Patient consent statement

The authors declare that all participants enrolled in the studies voluntarily, with informed consent obtained prior to beginning.

Supplemental material

The supplementary material of this study is available from the OSF link:

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