707243
research-article2017
SGOXXX10.1177/2158244017707243SAGE OpenVan Swol and Drury-Grogan
Article
The Effects of Shared Opinions on Nonverbal Mimicry
SAGE Open April-June 2017: 1–11 © The Author(s) 2017 https://doi.org/10.1177/2158244017707243 DOI: 10.1177/2158244017707243 journals.sagepub.com/home/sgo
Lyn M. Van Swol1 and Meghann L. Drury-Grogan2
Abstract People often mimic each other. Research has examined the positive social benefits of mimicry and factors that lead to increased mimicry. Two studies examine whether a participant is more likely to mimic nonverbal behavior of someone who shares the same opinion as the participant than someone who does not. The participant made a decision between two vacation destinations and discussed the choice in a three-person group. The two other group members were confederates. One agreed with the participant’s choice and one disagreed. Each confederate emitted a different nonverbal behavior consistently throughout discussion. Results offer some support to the hypothesis that the participant would be more likely to mimic nonverbal behavior of the confederate who is in agreement with the participant. Keywords mimicry, chameleon effect, nonverbal imitation, mirroring People tend to automatically mimic others. This tendency is so compelling that people will mimic the behavior of a nearby stranger with whom they are not even interacting (Chartrand & Bargh, 1999), and people are generally unaware that they are engaging in mimicry (Bavelas, Black, Lemery, & Mullett, 1986; Chartrand & Bargh, 1999). Much research has found that mimicry has many socially useful functions that help strengthen interpersonal bonds, such as increasing rapport, liking, empathy, and prosocial behavior (for review, see Chartrand & Lakin, 2013). Chartrand and Lakin (2013) highlight two recent themes in the mimicry literature: moderators that lead to more or less mimicry in a given situation, for example, social, motivational, and emotional factors; and downstream consequences of mimicry, for example, prosocial behavior, attitudes, and consumer preferences. Other research has examined what factors may increase mimicry of another person (see Chartrand & Bargh, 1999; Chartrand, Maddux, & Lakin, 2005; Guéguen, 2012; Guéguen & Martin, 2009; Sanchez-Burks, 2002; van Swol, 2003). This study explores how sharing the same opinion with another person may increase a participant’s behavioral mimicry of that person. Researchers have found that people imitate each other on a wide range of behaviors (for review, see Chartrand & Lakin, 2013; Dijksterhuis, Chartrand, & Aarts, 2007). For example, both infants and adults imitate the facial expressions of others (Meltzoff & Moore, 1977, 1983; Zajonc, Adelmann, Murphy, & Niedenthal, 1987). People tend to mimic each other’s speech (Giles, Coupland, & Coupland, 1991; Neumann & Strack, 2000; Webb, 1969, 1972),
linguistic style (Ireland & Pennebaker, 2010), yawning (Provine, 1986), and laughter (Young & Frye, 1966). People also mimic the posture and nonverbal body movements of their interaction partners (LaFrance, 1979, 1982; Lakin, Chartrand, & Arkin, 2008; Stel & Vonk, 2010). For example, Chartrand and Bargh (1999) found that when a confederate engaged in a specific nonverbal behavior, participants were more likely to display that nonverbal behavior when interacting with the confederate. Finally, in dyadic interactions, partners often synchronize their speech rhythms (Cappella & Planalp, 1981; Dittmann & Llewellyn, 1968, 1969). Mimicry is so prevalent in interaction because it serves many useful social functions that increase interpersonal bonds (Lakin, Jefferis, Cheng, & Chartrand, 2003). Chartrand et al. (2005) propose that mimicry was adaptive in our evolutionary past and continues to serve an adaptive function by increasing empathy, liking, rapport, and affiliation in interactions. Chartrand and Bargh (1999) found that confederates who mimicked participants were liked more than confederates who did not engage in mimicry. Other research has found that mimicry can increase rapport and empathy in an interaction (Bavelas et al., 1986; Charney, 1966; LaFrance, 1979; LaFrance & Broadbent, 1976; Ramanathan & McGill, 1
University of Wisconsin–Madison, USA Fordham University, New York, NY, USA
2
Corresponding Author: Lyn M. Van Swol, Department of Communication Arts, University of Wisconsin–Madison, 821 University Avenue, Madison, WI 53706, USA. Email:
[email protected]
Creative Commons CC BY: This article is distributed under the terms of the Creative Commons Attribution 3.0 License (http://www.creativecommons.org/licenses/by/3.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
2 2008; Tickle-Degnen & Rosenthal, 1987) and prosocial behavior (Kirschner & Tomasello, 2010; Valdesolo & DeSteno, 2011; van Baaren, Holland, Steenaert, & van Knippenberg, 2003; Wiltermuth & Heath, 2009). van Baaren, Holland, Kawakami, and van Knippenberg (2004) found that people who had been mimicked were more prosocial even to someone other than the person who mimicked them. Thus, the positive relational effects of mimicry extend beyond the interacting partners to include those who are not involved in the interaction. Finally, researchers (Bailenson & Yee, 2005; Herrmann, Rossberg, Huber, Landwehr, & Henkel, 2011; Jacob, Guéguen, Martin, & Boulbry, 2011; van Swol, 2003) have found that mimickers are rated as more persuasive than nonmimickers and more successful in a negotiation (Swaab, Maddux, & Sinaceur, 2011) and a mediation if mimicry occurs over an extensive interaction (Fischer-Lokou et al., 2014). Mimicry, therefore, serves a useful purpose in propagating relationships and prosocial behaviors, even to strangers. However, while research has long established the social benefits of mimicry, researchers have also been examining what factors may lead to more mimicry. Some researchers have found cultural differences in the tendency to engage in mimicry. Sanchez-Burks, Lee, Choi, Nisbett, Zhao, and Koo (2003) proposed that less attention is paid to indirect, relational communication in the workplace in the United States than in other countries because of the United States’s history of a Protestant relational ideology that emphasizes the importance of limiting interpersonal concerns in the workplace and separating the domains of work and leisure. Therefore, there is less emphasis on relational communication such as nonverbal mimicry in U.S. workplaces than in workplaces in other countries, and people in the United States raised in traditions of Calvinist Protestantism are less likely to engage in nonverbal mimicry in the workplace (Sanchez-Burks, 2002). Furthermore, researchers have examined how several variables can increase mimicry, including perspective taking, high self-monitoring, similarity, context dependence, interdependent self-construal, goals of affiliation, and rapport (for review, see Chartrand & Lakin, 2013). For example, incidental similarity, such as sharing the same name or major, can increase mimicry (Guéguen, 2012; Guéguen & Martin, 2009). Given the important social benefits of mimicry, understanding how mimicry may be increased is an important avenue toward increasing positive interactions in interpersonal exchanges, and similarity may be an important means toward increasing mimicry. Other research has confirmed the importance of similarity and examined how sharing the same opinion on an issue could lead to more mimicry, particularly how sharing the same viewpoint with someone may increase mimicry of that person (LaFrance, 1982; Navarre & Emihovich, 1978; Scheflen, 1964). For example, LaFrance (1982) argued that nonverbal mimicry could be the result of shared viewpoints, and Cheng and Chartrand (2003) demonstrated that
SAGE Open among high self-monitors, mimicry increases as a function of perceived self–other similarity. Van Swol (2003) had participants discuss an issue in a group with two other people who were actually confederates. One confederate agreed with the participant and one disagreed. Furthermore, each confederate elicited a different nonverbal behavior throughout the discussion. The data showed a trend toward participants mimicking the nonverbal behavior of the confederate who agreed with them more than the confederate who disagreed, but the results were not significant. The author suggested that low power could underlie the lack of significant results, and suggested that further research examining shared viewpoints and mimicry use a sample size larger than their 38 participants (van Swol, 2003). A workplace task for the group discussion was also used, and given that in the United States, nonverbal mimicry may be inhibited in work settings due to the Protestant relational ideology (Sanchez-Burks, 2002), use of a different type of task to test the relationship between shared viewpoints and nonverbal mimicry is important. Therefore, the two experiments in this article add to van Swol (2003) by using larger sample sizes and a less workoriented group discussion task to test the hypothesis that participants will be more likely to imitate a nonverbal behavior when that behavior is emitted by a confederate who agrees with the participant than a confederate who disagrees. Because nonverbal mimicry is strongly related to increased rapport, empathy, and liking (Chartrand & Lakin, 2013), a relationship between agreement and increased mimicry could indicate how mimicry may mediate a relationship between agreement and liking or strengthen the tendency to like and empathize with those who agree with us. Given that similarity can be established even through incidental means such as names and birthdays (Guéguen, 2012; Guéguen & Martin, 2009), similarity could be an especially easy way to improve social interactions through mimicry. Furthermore, given that mimicry may be sensitive to task (Sanchez-Burks, 2002), it is important to examine mimicry and its consequences in a variety of tasks.
Experiment 1 Method Participants and design. There were 69 participants who completed the experiment for partial credit in a communication studies class at a large Midwestern university in the United States. Participants were randomly assigned to conditions. Six participants were excluded from analysis because they indicated suspicion in the posttask questionnaire or noticed the nonverbal behavior of the confederates. One participant was excluded due to camera difficulties. Data from 62 participants were used; the agreeing confederate either shook their foot (n = 34) or touched their face (n = 28).
Van Swol and Drury-Grogan Procedure. When the participant arrived, he or she was brought to a room where one of the confederates was already waiting with a signed consent form, and the participant was given informed consent. Then the second confederate arrived and was given informed consent. After informed consent, the experimenter explained that the purpose of the experiment was to study how discussing one’s preference in a group affects one’s decision and behavior. Thus, it was explained that after making an individual decision alone, participants would be discussing their decision in a group. Participants were asked to pretend they won a trip in a student contest, and they could choose between two vacation destinations in the Caribbean. The participant and confederates were given a written description of the contest and information about each fictitious Caribbean island and then given a sheet to record their initial, individual decision and rate their confidence in their decision from 1 (very confident) to 9 (not at all confident). They were instructed to individually read through the information and make a decision about which island they wanted to visit. The experimenter then escorted the confederates out of the room, stating that everyone would work in separate rooms. After 8 to 10 minutes, the experimenter checked the progress of the participant. When the participant had made a decision, the experimenter collected his or her decision sheet and said that she wanted to check the camera. At this point, the experimenter turned the camera on to record a baseline of the participant’s behavior when alone. A baseline was collected to obtain a measure of how much the participants engaged in the measured nonverbal behaviors naturally without a confederate emitting them. In 10 of the trials, the participant moved out of the camera’s angle or the experimenter forgot to turn the camera on early. A baseline was recorded for 52 trials. The average baseline was 1.70 min (SD = 1.58 min). After turning the camera on, the experimenter stated that she would check the progress of the other two participants. After waiting about 2 min to record a baseline, the confederates were both brought back into the main experimental room. The three group members sat facing each other. There was no obstruction between them so the participant had a full body view of both confederates. The experimenter read the following instructions: Now I want you to discuss your choice with the other participants. If you picked a different vacation than someone else, please explain your choice to the other two participants telling them why you picked that vacation. Also, if another participant picked a different vacation than you, please listen to their information. You do not have to stick to your original preference if you learn new information that changes your mind. You will not make a group decision, but you will be asked to make an individual decision after the group discussion.
The experimenter asked whether anyone had any questions and then told the group that she would check back in 10
3 minutes but if they finished before, they should come get her in the next room. The participant and confederates kept their information sheet during the discussion to provide a loose script of information for the confederates to discuss. The participant was videotaped throughout the whole group discussion, although the camera was positioned so that it appeared as if the whole group was being taped. One confederate agreed with the participant’s choice of vacation destination and one disagreed. Furthermore, one confederate shook his or her foot throughout and one repeatedly touched his or her face. Confederates were blind to the experimental hypotheses. The use of a triad methodology in a mimicry study, pioneered by Dabbs (1969), allows the nontarget confederate to serve as a control within the same interaction. We counterbalanced whether the agreeing confederate touched his or her face or shook his or her foot. Furthermore, four different confederates were used for the experiment, and we counterbalanced whether they shook their foot or touched their face and whether they agreed with the participant or disagreed. Thus, each confederate alternated between agreement or disagreement and between shaking his or her foot or touching his or her face. For touching the face, the confederate was instructed to put a couple of fingers or part of their hand for a few seconds on any part of the face from the forehead to the chin and then shift the hand away. They were instructed to touch the face for approximately 50% to 70% of the time during the trial. For shaking the foot, the confederates could either cross their legs and shake their foot from the ankle or the knee or set the lower part of one leg across the knee of the other leg and shake their ankle. They were instructed to shake their leg during 50% to 70% of the trial. When shaking their leg, the confederates were instructed to have a steady, but not too vigorous, movement of the leg from the ankle and/or knee. Other than the specific nonverbal behavior, both confederates were instructed to act similarly in both the agreement and disagreement conditions. The group discussion lasted for a mean of 6.18 minutes (SD = 2.18 min, range = 2.38-13.48 min). After the discussion, the experimenter collected the information sheets, passed out a posttask questionnaire, and escorted the confederates out of the room. The questionnaire asked participants to again pick a vacation destination and rate their confidence. Participants were also asked, “What do you think the purpose of this research is?”, “What did you notice most about the other two participants?”, “Did any of the other two participants engage in any noticeable mannerisms during the experiment?”, and “Was there anything about the other two participants’ behavior that made you feel awkward or uncomfortable?” Five participants were excluded from data analysis because their answers indicated that they knew the experiment was staged. One other participant was excluded from analysis because he wrote that he noticed one of the staged nonverbal behaviors. Upon completion of the questionnaire, participants were thanked and asked to provide an
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SAGE Open
Table 1. Means and Frequencies of Nonverbal Behavior in Both Experiments. M
SD
3.82 4.75 2.69
6.39 15.17 4.59
1.95
3.62
8.42
11.97
3.93
4.93
1.40 6.19 2.30
3.21 7.02 3.53
0.88
1.01
9.58
13.80
4.53
6.19
Experiment 1 Baseline face touches Baseline foot shakes Face touches when agreeing confederate touched face Face touches when disagreeing confederate touched face Foot shakes when agreeing confederate shook foot Foot shakes when disagreeing confederate shook foot Experiment 2 Baseline face touches Baseline foot shakes Face touches when agreeing confederate touched face Face touches when disagreeing confederate touched face Foot shakes when agreeing confederate shook foot Foot shakes when disagreeing confederate shook foot
address if they wished to be debriefed upon completion of data collection. Because of the use of confederates, participants were not immediately debriefed. Coding. Three independent coders unaware of any hypotheses coded the trials. One coder was used as the primary coder and coded all trials, and the other two were secondary coders. The secondary coders split up the trials and each coded about half of them. Coders were instructed to count any up and down or back and forth movement of the leg and foot originating from the ankle or knee as an instance of “shaking the foot.” Crossing and uncrossing the legs did not count. The coder counted each time a participant moved his or her foot back and forth as one instance of “shaking the foot.” Coders were instructed to count any time the participant’s hand touched the face and moved away as an instance of “touching the face.” Touching the hair, neck, and ears did not count as an instance, nor did covering one’s mouth to sneeze or cough. If a participant put his or her hand on the face and kept it there, then the coders were instructed to count every 5 seconds that the hand rested on the face as one instance of “touching the face.” Coders counted the instances of nonverbal behavior both in the baseline and main experiment. The main coder’s count of touching the face in the baseline and experiment correlated with both the first (baseline: intraclass correlation [ICC] = .86, p < .0001; experiment: ICC = .84, p < .0001)
and second (baseline: ICC = .71, p < .0001; experiment: ICC = .84, p < .0001) secondary coders. The main coder’s count of shaking the foot also correlated with the first (baseline: ICC = .99, p < .0001; experiment: ICC = .82, p < .0001) and second (baseline: ICC = .93, p < .0001; experiment: ICC = .65, p < .0001) secondary coders. The main coder’s numbers were used for the analyses.
Results No participant changed his or her choice of vacation destination after meeting in the group with the two confederates. Thirty-six (58%) participants chose one vacation option, and 26 (42%) chose the other. This difference was not significant, χ2 = 1.61, p = .20. But participants’ confidence in their decision (before: M = 3.98, SD = 1.79; after: M = 3.33, SD = 2.32) did increase after meeting in the group, F(1, 60) = 8.75, η2 = .13, p = .004. Note that lower numbers represent higher confidence. The total number of foot shakes and face touches was divided by the minutes of discussion for each trial to determine an average number of shakes or touches per minute. Table 1 reports the number of face touches and foot shakes per minute in the main experiment and baseline. The number of face touches and foot shakes per minute in the baseline was compared in a paired samples t test. The difference was not significant, t(51) = 0.42, Cohen’s d = . 08, p = .68. Therefore, in the baseline, the participants were not more likely to elicit one nonverbal behavior more than the other. The number of face touches and foot shakes per minute in the main experiment also was compared in a paired samples t test. This difference was significant, t(61) = 3.15, Cohen’s d = . 66, p = .003. Thus, participants were more likely to shake their foot than touch their face during the main experiment. Neither did participants’ foot shakes in the baseline correlate with their foot shakes during the experiment, r = .14, p = .31, nor did their face touching in the baseline correlate with face touching during the main experiment, r = .23, p = .10. The participants’ amount of leg shakes and face touching during the experiment did not correlate with each other, r = .06, p = .66. A mixed model ANOVA with the within-subjects variable of type of movement (foot shakes, face touches) and the between-subjects variable of which behavior the agreeing confederate emitted tested for differences. There was a significant interaction between type of movement and which behavior the agreeing confederate emitted, F(1, 60) = 4.20,η2 = .07, p = .045. Participants were more likely (Cohen’s d = . 49) to shake their foot in the condition in which the agreeing confederate shook his or her foot (M = 8.42, SD = 11.97) than when the disagreeing confederate shook their foot (M = 3.93, SD = 4.93), and participants were more likely (Cohen’s d = .18) to touch their face when the agreeing confederate also touched his or her face (M = 2.69, SD = 4.59) than in the condition in which the disagreeing confederate touched his
Van Swol and Drury-Grogan or her face (M = 1.95, SD = 3.62). For the 52 trials with a baseline, the number of foot shakes per minute and number of face touches per minute in the baseline were included as covariates in an ANCOVA. Although the participant was more likely (Cohen’s d = . 40) to shake his or her foot in the condition in which the agreeing confederate shook his or her foot (M = 7.90, SD = 10.73) than when the disagreeing confederate shook his or her foot (M = 4.52, SD = 5.23) and was more likely (Cohen’s d = .24) to touch his or her face in the condition in which the agreeing confederate touched his or her face (M = 3.20, SD = 4.94) than when the disagreeing confederate touched his or her face (M = 2.13, SD = 3.88), the interaction between type of movement and which behavior the agreeing confederate emitted was not significant, F(1, 48) = 3.17, η2 = .06, p = .08.
Discussion The results lend some support for the hypothesis. Participants shook their foot more when the agreeing confederate shook his or her foot than when the disagreeing confederate shook his or her foot, and they touched their face more when the agreeing confederate touched his or her face than when the disagreeing confederate touched his or her face. These results suggest that people are more likely to mimic the nonverbal behavior of someone who agrees with them than someone who disagrees. However, when the baseline was used as a covariate to account for participants’ behavior when alone, the results approached, but no longer reached, significance. The first experiment had some problems that may account for the lack of strong significant results and that we try to correct in the second experiment. First, the baseline used may not have been appropriate. An individual’s nonverbal behavior alone may differ considerably from an individual’s nonverbal behavior when interacting with other people (Kraut & Johnston, 1979). The lack of correlation between participants’ baseline behavior and their nonverbal behavior in the experiment suggests that their nonverbal behavior alone was very different from their behavior in the presence of others. Also, we did not have a baseline for 10 people, which lowered the power of the test when including the baseline as a covariate. Furthermore, in Experiment 1, the effect sizes of the test without a covariate and the ANCOVA were very similar so adding the covariate of baseline behavior did very little toward controlling the variance. The fact that the test for leg shakes had a significant difference between the agreement and disagreement conditions but the ANCOVA was not significant is more likely explained by a drop in power in the ANCOVA due to the use of a smaller sample size. Therefore, Experiment 2 uses a more appropriate baseline in which the participant interacts with the confederates during the baseline. Also, Experiment 1 had no manipulation check on confederates. Although confederates were blind to the experimental hypotheses, they could have easily guessed that
5 agreement with the participant could affect the participant’s behavior differently than disagreement. Furthermore, confederates may have enjoyed agreeing with the participant more and may have acted more enthusiastically or smiled more when in agreement. This offers an alternative hypothesis for why there was a tendency for participants to imitate the confederates’ leg shaking more in the agreement condition. Therefore, we included a manipulation check on the confederates’ behavior in the second experiment to try to rule out this alternative hypothesis. Experiment 1 also did not check whether confederates were, in fact, engaging in their assigned behavior and at what rate, and, therefore, this is examined in Experiment 2 as well. Although there was not a significant difference between the number of foot shakes and face touches in the baseline, participants were more likely to shake their foot during the experiment. This suggests that, in general, people may be more likely to mimic foot shaking behavior than face touching. In other words, when alone, people may be just as likely to shake their foot as touch their face, but when interacting with others, foot shaking may be more contagious than touching one’s face. We used these two nonverbal behaviors because they have been used in previous research (Chartrand & Bargh, 1999; van Swol, 2003). It is possible that face touching is more controllable than foot shaking or that some participants may have been more reluctant to touch their face due to the use of makeup or presence of facial hair. Therefore, we use arm touching instead of face touching as a nonverbal behavior in the second experiment. Another reason participants may have been less likely to touch their face is that they were holding their information sheets during the interaction. This may have kept their hands occupied. Furthermore, some participants avoided eye contact with the confederates by looking at their information sheets, and this may have diminished their attention to the confederates’ nonverbal behavior. Therefore, in the second experiment, the experimenter collected the information sheets before the discussion, and participants discussed the information from memory and had no paper to hold during the discussion. The discussion time in Experiment 1 was short. By allowing the participants and confederates to get the experimenter when the group discussion seemed to be ending, the confederates were often misjudging the time and ending the discussion after only 5 min. Therefore, in the second experiment, confederates were instructed to keep the discussion going until the experimenter came to check on the group’s progress. A longer discussion time may allow the participant to observe the confederates’ nonverbal behavior more and possibly establish a better rapport with the confederates. This may ensure stronger results. Finally, Experiment 1 used a main coder rather than taking the mean of two or three coders. Although reliability between the main coder and secondary coders was acceptable, Experiment 2 takes the mean of the coders rather than relying on one coder.
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Experiment 2 Method Participants and design. There were 57 participants who completed the experiment for partial credit in a communication studies class at a large Midwestern university. Two participants were excluded from analysis. One changed their opinion after the group discussion and was excluded because we could not tell which confederate was agreed with during the discussion. The second excluded participant suspected the use of confederates. Data from 55 participants were used. Participants were randomly assigned to conditions of either the agreeing confederate shaking his or her foot (n = 27) or the agreeing confederate touching his or her arm (n = 28). Procedure. Experiment 2 used the same vacation destination task as Experiment 1. Participants received informed consent and made an individual decision according to the same procedure as Experiment 1. After the participant made an individual decision alone, the experimenter collected his or her decision sheet and information sheet. Neither the participant nor the confederates kept their information sheet during the discussion to avoid distractions. The experimenter then brought both confederates back into the main experimental room. The experimenter told the group to engage in talk to “get acquainted” for 2 min. They were to introduce themselves and not talk about the vacation destination task yet. The confederates were instructed to not engage in their designated nonverbal behavior during this 2-min baseline. This was to record a baseline of the participant’s nonverbal behavior when talking to the group members. There were two cameras in the room. One recorded the behavior of the participant, and the second camera was used to record the confederates for 30 of the trials to provide a manipulation check on the confederates’ behavior. For the other trials in which the confederates were not recorded, the second camera was still in the room and the experimenter pretended to turn it on. After turning the cameras on, the experimenter stated that she would return in approximately 2 min to explain the next steps of the experiment. A baseline was recorded for all trials. The average baseline was 2.04 min (SD = 0.33 min). After 2 min, the experimenter returned and read the same instructions to the group as in Experiment 1. The experimenter asked whether anyone had any questions and then told the group that she would check back in 8 to 10 minutes. Even if they felt they were finished, the group was instructed to continue talking about the vacation destinations until the experimenter returned. The group discussion lasted for a mean of 8.41 min (SD = 0.72 min, range = 6.809.60 min). When the experimenter returned, she asked whether the group was finished. All indicated that they were. One confederate agreed with the participant’s choice of vacation destination and one disagreed. One confederate
SAGE Open shook his or her foot throughout and one repeatedly touched his or her arms. It was counterbalanced whether the agreeing confederate touched his or her arms or shook his or her foot. Furthermore, four different confederates were used for the experiment, and it was counterbalanced whether they shook their foot or touched their arms and whether they agreed or disagreed. For touching the arms, the confederate was instructed to put a couple of fingers or part of their hand for a few seconds on any part of the arms from the shoulder to the top of the hand just above the knuckles and then shift the hand away. They could also cross their arms, rub their arms, or scratch their arms. They were instructed to touch their arms for approximately 50% to 70% of the time. For shaking the foot, the confederates were given the same instruction as Experiment 1. In addition to training the confederates to engage in the nonverbal behaviors, confederates were instructed to make mistakes in phrasing that would be expected in natural compared with scripted conversation. In Experiment 1, some of the participants who suspected the use of confederates stated that the confederates seemed to know the information too well. Therefore, confederates were trained to pause or stumble over words, slightly misremember a couple of pieces of information, and state some pieces of information in a simpler format. After the discussion, the experimenter passed out a posttask questionnaire and escorted the confederates out of the room, so that everyone allegedly could work on the questionnaire individually. The questionnaire asked participants to again pick a vacation destination and rate their confidence. The questionnaire also asked, “What do you think the purpose of this research is?”, “What did you notice most about the other two participants?”, and “Did any of the other two participants engage in any noticeable mannerisms during the experiment?” One participant was excluded from data analysis because his or her answers indicated that he or she knew the experiment was staged. Upon completion of the questionnaire, participants were thanked and debriefed according to the same procedure as Experiment 1. Coding. Two coders, unaware of the experimental hypothesis, coded all 55 of the trials for foot shaking and arm touching. The same coding scheme as Experiment 1 was used for foot shaking. For arm touching, the coders counted as an instance of arm touching any time the participant touched and pulled away with their hand or other arm any part of the arm from above the knuckles to the shoulder. Touching the fingers together or clasping hands together did not count. If participants continuously touched their arm by, for example, having their arms crossed or resting a hand on the other arm, then the coders counted every 5 seconds as an instance of arm touching. The first coder’s count of touching the arm in the baseline and experiment correlated with the second coder (baseline:
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Van Swol and Drury-Grogan Table 2. Coder Means for Ratings of Confederates’ Characteristics.
Characteristics Eye contact Smiling Friendliness Appearance of liking Persuasiveness Talkativeness
Disagreement
Agreement
M
SD
M
SD
4.55 3.43 3.83 3.65 3.03 4.05
0.95 1.36 1.17 1.25 1.41 0.63
4.35 3.25 3.58 3.42 3.63 4.22
0.59 0.80 0.81 0.77 1.18 0.47
ICC = .78, p < .0001; experiment: ICC = .94, p < .0001). The first coder’s count of shaking the foot also correlated with the second coder (baseline: ICC = .88, p < .0001; experiment: ICC = .98, p < .0001). The mean of both coders’ ratings for each nonverbal behavior was used as the dependent variable in the analyses. For 30 of the trials, the two different confederates also were videotaped so that the behavior of the agreeing and disagreeing confederate could be compared. Two coders, unaware of the experimental hypothesis, rated the confederates on a six-point scale from low to high for the following characteristics: amount of eye contact, amount of smiling, friendliness, degree to which the confederate appeared to like the participant, persuasiveness, and talkativeness. The two coders’ ratings significantly correlated for all measures: amount of eye contact (ICC = .72, p < .0001), amount of smiling (ICC = .85, p < .0001), friendliness (ICC = .96, p < .0001); degree to which the confederate appeared to like participant (ICC = .93, p < .0001), persuasiveness (ICC = .90, p < .0001), and talkativeness (ICC = .70, p < .001). The mean of the two coders’ rating for each scale for the two confederates was analyzed in a paired samples t test (disagreement − agreement). There were no significant differences between the rating of the agreeing and disagreeing confederates for (see Table 2 for means) amount of eye contact, t(29) = 1.21, Cohen’s d = . 21, p = .24; amount of smiling, t(29) = 0.81, Cohen’s d = .11, p = .42; friendliness, t(29) = 1.38, Cohen’s d = .09, p = .18; degree to which the confederate appeared to like participant, t(29) = 1.20, Cohen’s d = .12, p = .24; and talkativeness, t(29) = −1.72, Cohen’s d = −.19, p = .10. However, the agreeing confederate was rated higher in persuasiveness than the disagreeing confederate, t(29) = −2.59, Cohen’s d = −.46, p = .02. Possibly, the coders perceived this confederate’s agreement with the participant as a sign of persuasiveness. Therefore, the agreeing and disagreeing confederates were rated as behaving similarly on all measures except ratings of persuasiveness. In addition, two coders watched the recordings of confederates with a stop watch application on the computer to try to assess how much each coder engaged in their assigned behavior. They pressed a button to activate the stop watch
when the coder engaged in their assigned behavior and pressed the button again to stop the stop watch when the confederate discontinued. The coder watched the video twice and only coded one confederate per view. The two coders’ ratings correlated for amount of time spent touching their arm (ICC = .65, p = .003) and amount of time spent foot shaking (ICC = .83, p < .0001). We took the mean of the two coders’ ratings and divided the amount each coder recorded by the amount of time of the interaction. On average, confederates assigned to engage in foot shaking were shaking their feet during 53% of the interaction (M = 0.53, SD = 0.10), and confederates assigned to arm touching were touching their arms during 48% of the interaction (M = 0.48, SD = 0.07).
Results Twenty-nine (53%) participants chose one vacation option, and 26 (47%) chose the other. This difference was not significant, χ2 = 0.16, p = .69. Participants’ confidence in their decision did not significantly increase after the group discussion (before: M = 3.36, SD = 1.96; after: M = 3.15, SD = 1.79), F(1, 54) = 2.65, η2 = .05, p = .11. The total number of foot shakes and arm touches was divided by the minutes of discussion for each trial to determine an average number of shakes or touches per minute. The number of arm touches (M = 1.40, SD = 3.21) and foot shakes (M = 6.19, SD = 7.02) per minute in the baseline was compared in a paired samples t test (arm − foot). Participants had significantly more foot shakes than arm touches, t(54) = −4.61, Cohen’s d = −.88, p < .0001. The number of arm touches (M = 1.60, SD = 2.69) and foot shakes (M = 7.01, SD = 10.83) per minute in the main experiment also was compared in a paired samples t test (foot − arm). This difference was significant, t(54) = 3.60, Cohen’s d = .68, p < .001. Thus, participants were more likely to shake their foot than touch their arm. Participants’ foot shakes in the baseline correlated with their foot shakes during the experiment, r = .69, p < .0001, and participants arm touching in the baseline correlated with arm touching during the main experiment, r = .59, p < .0001. The participants’ amount of leg shakes and arm touching during the experiment did not correlate with each other, r = .05, p = .71. We analyzed the number of foot shakes per minute between conditions. There was a nonsignificant trend (Cohen’s d = .47) for participants to shake their foot more in the condition in which the agreeing confederate shook his or her foot (M = 9.58, SD = 13.80) than in the condition in which the disagreeing confederate shook his or her foot (M = 4.53, SD = 6.19), F(1, 53) = 3.10, η2 = 0.06, p = .08. However, in support of the hypothesis, when the baseline of participants’ foot shakes was included as a covariate, there was a significant difference between the condition in which the agreeing confederate shook his or her foot and the condition in which the disagreeing confederate shook his or her foot, F(1, 52) = 6.48, η2 = .11, p = .01.
8 We also analyzed the number of arm touches per minute between conditions. In support of the hypothesis, participants were significantly more (Cohen’s d = .55) likely to touch their arm when the agreeing confederate also touched his or her arm (M = 2.30, SD = 3.53) than when the disagreeing confederate touched his or her arm (M = 0.88, SD = 1.01), F(1, 53) = 4.04, η2 = .07, p = .05. However, when the baseline of arm touching was included as a covariate, the difference was no longer significant, F(1, 52) = 2.41, η2 = .04, p = .13.
Discussion The results for mimicking foot shakes and arm touches lend partial support to the hypothesis that participants would be more likely to mimic the nonverbal behavior of someone who agrees with them than someone who disagrees. However, the results for foot shakes were only significant when the baseline was included as a covariate, and the results for arm touches were only significant when the covariate was not included. Thus, the results were not conclusively significant. However, Experiment 2 did lend stronger support with stronger effect sizes for the hypothesis than Experiment 1. Possibly, the changes in methodology from Experiment 1 to Experiment 2 strengthened the effect. The manipulation check on confederates’ behavior in Experiment 2 could not completely rule out that the confederates were not acting differently. In particular, the agreeing confederate was rated as more persuasive. Because the coders were unaware of the experimental hypothesis, it is possible that the coders assumed the agreeing confederate was more persuasive because the participant agreed with him or her. However, it may be that the agreeing confederate was indeed acting more persuasive, and this offers an alternative hypothesis for our results that we cannot rule out. In addition, coding of the confederates’ assigned behavior confirmed that confederates were engaging in their assigned behavior during about half of the interaction.
General Discussion These two experiments examined whether shared viewpoints between two group members lead to increased mimicry. For foot shakes and arm touches, there was partial support that participants mimic the behavior of the confederate who agreed with them. However, for the nonverbal behavior of face touching, the results were not significant. Therefore, the results lend mixed support to the hypothesis; when significant, the effects sizes were small to moderate. This study used the social task of going on vacation to try to address a problem found in previous research (van Swol, 2003) that participants may be less likely to mimic others’ nonverbal behavior on a nonsocial task. People in the United States pay less attention to indirect, relational communication in workplace settings (Sanchez-Burks et al., 2003) than in settings involving leisure. However, this study did not find
SAGE Open unequivocal support that people mimic those who agree with them in social, leisure settings. However, future research should do a direct comparison and manipulate type of setting as an independent variable. A similar process to perspective taking may underlie the tendency of people with shared views to mimic one another. People may be more likely to direct their attention in a conversation to a person who is in agreement with them than a person who is in disagreement. Chartrand and Bargh (1999) argued that mimicry is caused by an automatic perception– behavior link such that simply perceiving a behavior is enough to elicit mimicry of the behavior, usually nonconsciously, from the perceiver. Other researchers (LaFrance & Broadbent, 1976; Tickle-Degnen & Rosenthal, 1987) also suggested that posture mimicry reflects the attention of the perceiver toward the person they are mimicking. Thus, people may be more susceptible to mimicry of a person who is in agreement with them because more of their perception and attention is directed toward that person’s behavior than a person who is in disagreement with them. People are more likely to gaze at faces that are similar to themselves (Hungr & Hunt, 2012) and gaze at people and objects they like (Schotter, 2010; Ulloa, Marchetti, Taffou, & George, 2015); however, future research may want to examine the moderating role of attention more directly, possibly by measuring participants’ eye gaze toward each confederate to establish that participants are directing more of their attention toward the confederate in agreement with them. For example, research has found that pictures of emotional content received more participant eye gazes and for longer durations than neutral content, and even more so if the emotional content was pleasant rather than nonpleasant (Nummenmaa, Hyönä, & Calvo, 2006). Perhaps like emotional pictures, participants might make more eye contact with a confederate who agrees with them. Likewise, averting eye gaze leads to participants feeling ostracized and showing related effects of lowered satisfaction of basic human needs, lowered experience of relational evaluation, more negative moods, lowered self-esteem, enhanced temptations to act aggressively, and an increased feeling that the relationship or interaction was low in value (Wirth, Sacco, Hugenberg, & Williams, 2010). Thus, if confederates avoid eye gaze, participants could feel more ostracized in the conversation and be less likely to mimic them or change their own opinion. Another reason people may be more likely to mimic someone in agreement with them is that mimicry is a form of communication (Bavelas et al., 1986; Chartrand & Lakin, 2013) that helps to communicate the empathetic message “‘I am with you’ or ‘I am like you’” (Bavelas, Black, Chovil, Lemery, & Mullett, 1988, p. 278). Thus, mimicry helps communicate that the perceiver shares the same feelings as the person they are mimicking. People may be more willing or likely to communicate such a nonverbal message to someone they perceive as more similar to themselves. Previous research has found that people are more willing to mimic
9
Van Swol and Drury-Grogan someone who has incidental similarity with them (Guéguen, 2012; Guéguen & Martin, 2009), which suggests that similarity could be driving the mimicry in the results. In addition, research on empathy has found that people are more likely to display empathy toward similar others (Baston et al., 1995; Krebs, 1975; Stotland, 1969). Therefore, participants may have increased empathy for others who share similar opinions as themselves and may be more likely to mimic their behavior as communication of that empathy. Future research should explore other factors that may lead to increased mimicry between two people. People are more likely to mimic someone who is more similar to themselves in other ways besides sharing the same opinion (Cheng & Chartrand, 2003; Guéguen, 2012; Guéguen & Martin, 2009). Other research should examine how variables such as “liking” mediate or moderate the relationship between similarity and mimicry. For example, it is already known that similarity increases liking and attraction (Byrne, 1971) and that people who like each other tend to mimic each other’s postures and mannerisms more than those who do not like each other (Bernieri, 1988; LaFrance, 1982), but the relationship between mimicry, liking, and attitudinal similarity can be tested in a mediation analysis. Overall, the two experiments and other work (van Swol, 2003) show that the effects of agreement on mimicry are subtle, inconsistent, and not particularly strong. These findings are in line with other nonconscious phenomenon (Klein et al., 2014) like priming where results can be inconsistent. Given the attentional nature of mimicry, results depend on participants paying attention to other members, and participants’ focus could have varied widely. Furthermore, tendency toward mimicry could depend on how strongly participants held their prediscussion opinion. In a fictitious laboratory task, participants may not have been that invested in agreeing with a certain option. This study also had several limitations. First, confederates were engaging in the nonverbal behavior about 50% of the time in our coded interactions and were instructed to engage in the behavior 50% to 70% of the time. This may have been too high an amount of mimicry and led to several participants noticing the behavior. The mimicry may have been obvious to several participants, and this may have reduced our ability to measure nonconscious, automatic mimicry. Second, low power still may have been an issue with these studies. Although this study had increased sample size than van Swol’s (2003), cell sizes were about 30 per cell after accounting for suspicious participants. Third, the coding comparing foot shaking with face touches was problematic with regard to the creation of rates per minute of face touching. Specifically, if participants touched their face for an extended period of time, every 5 seconds was counted as a face touch, but if a participant shook their leg for an extended period of time, every leg shake was counted as one leg shake. This may have lowered the amount of face touches in comparison with leg shakes. Finally, although intercoder reliability was acceptable on all measures,
sometimes reliability was much higher than others. For example, in Experiment 2, eye contact and talkativeness had lower reliability than ratings of friendliness and liking. Friendliness and liking were general impressions the coders made, whereas eye contact and talkativeness may have required more attentive coding to frequency that was more difficult for the coders. In conclusion, this study used a larger sample size and different task than van Swol’s (2003) study and lent some support for the hypothesis that people are more likely to mimic the nonverbal behavior of someone who shares the same opinion as them than the nonverbal behavior of someone who holds a different opinion. Authors’ Note The results of this article were presented as a talk at the 2006 International Communication Association conference in Dresden, Germany.
Acknowledgments Special thanks to Joseph Gulotti, Alex Glaser, Alice Kim, Nicole Orillac, Jon Greer, Darby Gaynor, Emily Glatzer, Birju Shah, Brad Weinstock, Lacey Connoley, and Stephanie Paul for serving as confederates and coders.
Declaration of Conflicting Interests The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding The author(s) received no financial support for the research, authorship, and/or publication of this article.
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Author Biographies Lyn M. Van Swol is a professor of Communication Science in the Department of Communication Arts at the University of WisconsinMadison. Her research focuses on information sharing in groups, utilization of advice, and deception in negotiations. She has received numerous awards for her research, which is published extensively internationally. Meghann L. Drury-Grogan is an assistant professor of Communication & Media Management in the Gabelli School of Business at Fordham University. Her research focuses on business communication, project management, and decision making. She has taught international academic and practitioner audiences, published in leading international journals and conferences, and received numerous academic and industry awards for her research.