To provide initial evidence for the joint effects of agency and communion on socially induced emotions, we manipulated the senders’ agentic and communal traits and then exposed participants to the senders’ displays of happiness, sadness, and anger. We expected that happy and sad expressions would evoke congruent emotional responses (that is, participants’ emotions would correspond to emotions expressed by the senders). We also hypothesized that these congruent responses would be promoted by high communion and weakened by low communion. Finally, we expected that high agency would intensify the effects of communion on participants’ responses to happiness and sadness, whereas low agency would lessen these effects. As previously mentioned, we did not formulate any specific hypotheses concerning anger-related responses.
Participants and design
We used G*Power (Faul et al., 2007) and the results of the previous study on the effect of agency and communion on emotional contagion (Wróbel et al., 2020), to calculate the sample size.Footnote 1 The analysis indicated that n = 58 was required to detect an effect size of f = .20 with 95% power and alpha level of .05. We recruited 72 undergraduates (52 women) but based on predetermined exclusion criteria we excluded participants who guessed the hypotheses (n = 2) or declared that they had not watched the videos carefully (n = 8). Our final sample included 62 participants (41 women; Mage = 21.74, years, SD = 4.21). We used a 3 (senders’ emotional display: happiness, sadness, anger) × 2 (senders’ communal traits: high communion, low communion) × 2 (senders’ agentic traits: high agency, low agency) within-participants design.
Procedure and materials
Participants were scheduled for individual sessions. To divert their attention from the real aim of the research, they were informed that the study would be about the relationship between memory and first impressions. After signing the informed consent, each participant was seated at a computer and asked to follow the instructions on the screen.
First, participants saw profiles of four senders (two men and two women) shown in random order. Each profile was presented on a separate page and consisted of a picture of a sender showing a neutral facial expression and eight adjectives (each of them in a separate line). Four adjectives referred to the sender’s communal traits, while the other four referred to his/her agentic traits. The images were taken from the Warsaw Set of Emotional Facial Expression Pictures (Olszanowski et al., 2015), whereas the traits were taken from Wojciszke et al. (2009, Study 3). Depending on the experimental condition, the traits represented high vs. low communion (envious, malicious, stingy, unfair vs. helpful, kind, non-egoistic, selfless) and high vs. low agency (competent, educated, hard-working, well-organized vs. disorganized, inert, passive, undependable), which resulted in four possible combinations of traits. The allocation of the four combinations to the four senders as well as the order of the traits in each combination were random. To make the profiles more credible, participants were led to believe that the four individuals presented in the pictures had been anonymously assessed by other people and that the traits below each picture had been most often mentioned in these assessments. Participants were also asked to memorize the profiles for later recall tasks and thus, the presentation time was not limited (i.e., participants moved to the next profile once they felt ready).
To ensure that participants associated the profiles with the right senders, we administered the first recall task. The images of the senders were shown once again and participants were asked whether each person was described by communal (friendly, nice, rSB = .91) and agentic (efficient, competent, rSB = .74) characteristics. Ratings were made on a 7-point scale ranging from definitely no to definitely yes.
Next, participants were exposed to twelve 35-s videos presenting the senders expressing happiness, sadness, and anger (4 senders × 3 displayed emotions).Footnote 2 The videos were presented in random order and showed dynamic facial displays created by morphing the images we used at the beginning of the study (i.e., neutral faces of the senders) with the images of anger, sadness, and happiness displayed by the same four senders (Olszanowski et al., 2020). The frame rate in each video was 29 frames per second. Each video started with a 2-s still image of a neutral face that within 3 s changed gradually to a full emotional display (apex). After reaching the apex, the face returned within the next 3 s to a blended expression (half-neutral, half-emotional), and then, after 3 s, it reached the apex again. The transformations were repeated four times. The video finished with a still image of a blended expression.
After each video participants rated the extent to which they felt happiness (happy, cheerful, delighted; ω = .92), sadness (sad, downhearted, blue; ω = .87), anger (angry, irritated, mad, ω = .82) and fear (anxious, fearful, tense, ω = .81) on a scale ranging from 1 (not at all) to 7 (extremely). The items were taken from a modified Polish version of the Differential Emotion Scale (DES; Izard et al., 1974) and presented in random order. We decided to measure fear in addition to the emotions that directly corresponded to the senders’ emotional displays, because as already mentioned, expressed anger often elicits reactive anger and fear rather than mimicry/contagion (see also Dimberg & Thunberg, 2012; Wróbel & Olszanowski, 2019). The identification of reactive responses to anger is important because, their occurrence suggests that the angry senders’ intents are perceived as non-affiliative and thus, the possibility of sharing the senders’ expressed emotions (via mimicry and/or contagion) decreases (Hess & Fischer, 2013; Wróbel & Imbir, 2019). However, as we did not have any predictions concerning participants’ responses to anger, we did not have any hypotheses not only for self-reported anger, but also for self-reported fear.
Having watched the videos, participants performed the second recall task (rSBcommunion = .75; rSBagency = .74). Lastly, they were asked about their assumptions regarding the goals of the study and whether they had watched the videos carefully.
Results and discussion
Planned contrasts confirmed that the trait manipulation was successful. The high-communion senders were rated as more communal (M = 5.86, SD = 0.96) than the low-communion senders (M = 1.94, SD = 0.84), F(1,61) = 394.82, p < .001, ηp2 = .87 [.80, .90] and the high-agency senders as much more agentic (M = 6.05, SD = 0.99) than the low-agency senders (M = 2.16, SD = 1.02), F(1,61) = 312.90, p < .001, ηp2 = .84 [.76, .88]. Means and standard deviations for all conditions are given in the Supplementary Table S2.
Next, we assessed the influence of the senders’ emotional displays and traits on happiness contagion, using a 3 (senders’ emotional display: happiness, anger, sadness) × 2 (senders’ communal traits: high communion, low communion) × 2 (senders’ agentic traits: high agency, low agency) repeated measures ANOVA, with self-reported happiness as a dependent variable. The analysis showed the expected three-way interaction, F(2,122) = 4.44; p = .014; ηp2 = .07 [.003, .16] (see Fig. 2, Panel A). We then run a series of planned contrasts consistent with our hypotheses. Contrast weights are given in Table 1. The first contrast compared happiness levels following exposure to the happy senders (M = 4.86, SD = 1.26) with happiness levels following exposure to the sad and angry senders (M = 1.87, SD = 1.01). The contrast was significant, F(1,61) = 187.09; p < .001; ηp2 = .75 [.64; .82], indicating that we observed the induction of convergent emotion (happiness contagion). The second contrast tested whether happiness contagion was moderated by the senders’ communion. This contrast was also significant, F(1,61) = 8.43; p = .005; ηp2 = .12 [.01; .28], indicating that participants reported being significantly more happy after seeing the happy senders high in communion (M = 5.09, SD = 1.28) than after seeing the happy senders low in communion (M = 4.62, SD = 1.54). The effect of communion on happiness contagion was further modulated by the senders’ agency, as indicated by the last two contrasts. Specifically, for the senders high in agency, communion affected happiness contagion, such that high communion was associated with more happiness (M = 5.20, SD = 1.42) than low communion (M = 4.45, SD = 1.78), F(1,61) = 13.38, p < .001, ηp2 = .18 [.04, .34]; for the senders low in agency, communion did not influence happiness contagion (high communion: M = 4.98, SD = 1.65 vs. low communion: M = 4.78, SD = 1.75), F(1,61) = 0.62, p = .434, ηp2 = .01 [0, .11].
Taken together, these findings are consistent with the Dual Perspective Model of Agency and Communion, by showing that the effect of communion on happiness contagion was cushioned by the senders’ low agency. Possibly the combination of happiness, high communion and low agency resulted in ambivalent social judgements, that is, the senders were seen as having affiliative intents (due to happy expression and high communion) but also as lacking competence required to act according to these intents (due to low agency). This, in turn, might have eliminated the effect of communion on happiness contagion for the low-agency senders.
An analogous analysis for self-reported sadness did not support the predicted three-way interaction, F(2,122) = .07; p = .937; ηp2 = .001 [0, .02] (Fig. 2, Panel B). Only the first contrast was significant indicating that participants reported higher levels of sadness after seeing the sad senders (M = 3.84, SD = 1.49) than after seeing the happy and angry senders (M = 1.71, SD = 0.79), F(1,61) = 128.26; p < .001; ηp2 = .68 [.53, .76]. The remaining contrasts testing the role of agency and communion on sadness contagion were not significant (Fs < 0.05, ps > .827). Put differently, we observed sadness contagion, but contrary to our hypotheses, participants shared the senders’ sadness regardless of agentic and communal traits.
Importantly, the pattern suggesting that agency and communion moderated happiness contagion but did not influence sadness contagion replicates the study by Wróbel et al. (2020). One reason might be that affiliative signals sent by sadness override the information provided by the traits. Sadness, as mentioned above, communicates the need for support (Fischer & Manstead, 2008) and thus, arouses compassion and triggers the intention to offer social support (Van Kleef et al., 2011). Thus, it is likely that this unique social meaning of sadness counteracts the effects of the senders’ non-affiliative traits on sadness contagion. This reasoning is consistent with other studies showing that sad faces often elicit congruent emotions regardless of the sender’s characteristics (e.g., Wróbel & Królewiak, 2017). Still, it is important to note that these studies, similar to the current study, often rely on self-reports. Thus, even though we tried to reduce the impact of social demands by using a different design than Wróbel et al. (2020), it is possible that participants might have been reluctant to admit that they were insensitive to other people’s sadness. This interpretation is indirectly supported by studies on empathy which show that self-report measures of empathic responses often do not indicate how people actually feel but rather reflect their knowledge of how they are expected to feel (Zhou et al., 2003). Therefore, the null effects of agency and communion on sadness contagion should be treated with caution.
We then analyzed participants’ responses to anger focusing on self-reported anger and fear, that is, two emotions typically evoked by angry expressions. As this analysis was driven not by specific directional predictions but by research questions that corresponded to the hypotheses we formulated for self-reported happiness and sadness, we did not analyze all possible effects in a completely exploratory manner but focused on the magnitude of the effects corresponding to these questions.
For self-reported anger, the analysis revealed a three-way interaction with a medium effect size (ηp2 = .06 [.001, .15]) (Fig. 2, Panel C). Participants reported being more angry following exposure to anger displays (M = 3.32, SD = 1.41) than following exposure to happiness and sadness displays (M = 1.77, SD = 0.75), as evidenced by a large effect size of this comparison (ηp2 = .58 [.41, .68]). We also observed a small-to-medium effect showing that participants responded with less anger to the high-communion angry senders (M = 3.17, SD = 1.49) than to the low-communion angry senders (M = 3.47, SD = 1.61), ηp2 = .05 [0, .19]. This effect, however, was more pronounced for the high-agency angry senders (high communion: M = 2.95, SD = 1.57 vs. low communion: M = 3.49, SD = 1.78; ηp2 = .09 [.003, .24]), whereas for the low-agency angry senders, the effect of communion was small to non-existent (high communion: M = 3.40, SD = 1.73 vs. low communion: M = 3.45, SD = 1.87; ηp2 < .001 [0, .06]). Overall, these results show that high agency strengthened the effect of communion on participants’ self-reported anger following exposure to anger displays, but this effect was opposite to that found for self-reported happiness following exposure to happy displays (that is, the low-communion angry senders evoked more anger than the high-communion angry senders). On the one hand, this result may seem surprising, given that the combination of high communion and high agency suggests that the senders have affiliative characteristics and thus their anger should be less antagonistic and more “contagious” than anger expressed by the senders characterized by other combinations of traits. On the other hand, as previously mentioned, non-affiliative expressions often evoke reactive rather than imitative responses (Fischer & Hess, 2017). Although such responses are difficult to differentiate from contagion, it seems that in the current study, anger probably elicited such responses, because, when agency was high, participants reported more anger following exposure to the low-communion than to the high-communion angry senders. In the case of contagion, the pattern would have been reversed (i.e., participants would have reported more anger following exposure to the high-communion than to the low-communion angry senders), because contagion is more likely to occur when the sender’s intents are perceived as affiliative (Wróbel & Imbir, 2019).
The analyses for self-reported fear align with the idea that anger expressions evoked reactive responses (Fig. 2, Panel D). Specifically, participants reported higher levels of fear after exposure to anger displays (M = 3.41, SD = 1.41) than after exposure to happiness and sadness displays (M = 2.34, SD = 0.89), as indicated by the large effect size of this comparison (ηp2 = .50 [.31, .62]). All other effects, including the three-way interaction were small (ηp2 < .05), which suggests that reactive fear in response to anger occurred regardless of the senders’ traits.
Summing up, Study 1 provided initial support for the notion that emotional contagion is controlled by agency and communion, but the pattern of results differed substantially across emotions. Specifically, this pattern supported our hypotheses when the senders expressed happiness, but we found no impact of agency or communion on participants’ emotional responses when the senders expressed sadness. Moreover, when the senders expressed anger, we probably observed reactive rather than imitative responses.
Two limitations of this study should be noted. First, as already mentioned, due to the use of self-reports, some participants might have been reluctant to admit that they were insensitive to other people’s sadness. Second, during the post-session debriefing, some participants mentioned that they found it difficult to focus on the videos, because the session was quite long. Although we excluded those who declared that they had not watched the videos carefully, we cannot be sure whether the remaining participants were fully engaged throughout the study. This seems important because the influence of social factors on emotional contagion may be based on top-down reflective processes (Wróbel & Imbir, 2019). Accordingly, the lengthy nature of the study might have made participants’ less attentive to the senders’ characteristics and, in consequence, reduced the impact of agency or communion on participants’ responses (see also Sachisthal et al., 2016). We addressed these limitations in Study 2.