Integrative Complexity,Participation,and Agreement in Group Discussions

Abstract

This study tested status-contingency theory and conversion theory on a task in which members made ordered judgments instead of dichotomous judgments. In groups, participants discussed whether “under God” should be in the pledge of allegiance and reached consensus on an ordered scale. Members’ contributions were scored for integrative complexity. In groups with more dispersion of opinion, members with opinions less discrepant from other group members did not have higher integrative complexity than members with more discrepancy of opinion, failing to support status-contingency theory for nondichotomous decisions. In support of conversion theory, members with more discrepant opinions were more influential when they had higher integrative complexity in their arguments. Replicating past research, groups with longer discussions had higher integrative complexity.

Keywords

integrative complexity minority majority dissent influence group communication

The presence of minority dissent increases divergent thinking, consideration of multiple solutions, and integrative complexity of arguments of those in the majority exposed to the dissent (De Dreu, 2002; De Dreu & West, 2001; Gruenfeld, 1995; Gruenfeld & Preston, 2000; Moscovici, 1980; Smith, Tindale, & Dugoni, 1996). Integrative complexity of thinking has been researched as an outcome of minority influence, but using the theoretical grounding of conversion theory, we argue that integrative complexity can also be a means by which minority members—or members with more discrepant opinions—persuade. Members with opinions more discrepant from other group members may be more influential when making more complex and nuanced statements. The presented experiment uses interacting groups to examine the influence of group members with more discrepant opinions on a real-world task with ordered alternatives, and rather than examining dissent as dichotomous (minority vs. majority), an individual-level measure of discrepancy from other group members is used. First, in line with status-contingency theory, we test whether exposure to more differences of opinion can increase the integrative complexity of less discrepant group members’ arguments. Second, we examine if more discrepant members with more integratively complex arguments are more persuasive, in support of conversion theory.

Integrative Complexity and Status-Contingency Theory

Researchers note that exposure to minority dissent increases the integrative complexity of the majority members’ arguments (Gruenfeld, 1995; Gruenfeld & Preston, 2000) or of the group as a whole (Curseu, Schruijer, & Boros, 2012). Integratively complex arguments are based on evidence from varied, novel, and/or conflicting perspectives on a particular issue. Integrative complexity refers to an individual’s differentiation, or recognition of multiple dimensions of and perspectives about an issue, and integration, an individual’s recognition of conceptual connections among the differentiated characteristics (Baker-Brown et al 1992; Gruenfeld, 1995; Tetlock, 1986). An individual high in cognitive differentiation recognizes multidimensional processes and effects at play in each decision-making scenario. For example, simplistically classifying a political policy in a unidimensional way—such as “good” or “bad”—based on a few salient items constitutes arguments with low differentiation (Gruenfeld, 1995; Tetlock, 1986). In contrast, with high differentiation, the decision-maker acknowledges a political policy might have varied effects on different levels—each of which should be considered in the judgment process. High levels of integration would then involve comparing the differentiated perspectives and outcomes with how they connect to other complex dimensions of policy judgments made by the decision-maker (e.g., Tetlock, 1981). High integrative complexity is linked to policy decision-maker behaviors where “the objective is to collaborate with the other side to reach an agreement in which all participants are satisfied” (Tetlock, 1985, p. 1567). Integrative complexity is not synonymous with simply acknowledging a two-sided argument; it involves assessing all levels, effects, and outcomes of said arguments. In addition to focusing on the complexities and connectedness of aspects of an argument, integrative complexity reflects more flexibility and less dogmatism; dogmatism has been shown to increase reliance on defensive bolstering and more justification of one’s opinion when one’s opinion is challenged (see Tetlock, Skitka, & Boettger, 1989).

According to status-contingency theory (Gruenfeld, 1995), the status of minority and majority members in groups affects the integrative complexity of their arguments. When minority members encounter dissent, and realize that their position lacks social support from others and is not likely to prevail in the group, they experience significant stress, uncertainty, and frustration. Due to this stress, minority members respond to majority dissent with convergent thinking in which they constrict their focus to the majority position and are motivated to conform to the majority to avoid rejection (Nemeth & Wachtler, 1983). Rather than thinking more systematically about the problem, minority members superficially focus on the majority position and on ways to avoid rejection (Nemeth, 1986). This convergent thinking lacks differentiation and integrative complexity (Gruenfeld, 1995). Although majority members have some stress from minority dissent, they experience less stress than minority members. According to Gruenfeld (1995), majority members have the ideal amount of stress that motivated them to process the arguments more thoroughly to understand the dissent but does not overwhelm them and impair their ability to systematically process arguments.

Exposure to minority dissent may lower majority members’ confidence levels, but it also leads to more systematic processing and reconceptualization of arguments as majority members try to resolve the dissent against their own viewpoint and desire for harmony in the group. The social validation from being in the majority can increase a majority member’s tolerance for questioning their own attitude in the face of minority dissent because the majority member is likely to assume their view is correct. As majority members reconceptualize their position and highlight new dimensions, their arguments increase in complexity and cognitive differentiation (De Dreu, 2002; Martin & Hewstone, 2001; Moscovici, 1980). Several studies have found that minority dissent increases the integrative complexity of majority members’ arguments. Gruenfeld (1995) analyzed Supreme Court decisions and found higher integrative complexity among the arguments at the subgroup level of the majority faction than among either the minority faction or unanimous group opinions, and Gruenfeld, Thomas-Hunt, and Kim (1998) found higher integrative complexity among majority members in interacting laboratory groups.

We seek to extend and generalize previous research beyond decisions in which members provide dichotomous decisions (i.e., pro/con). Several researchers have called for more research of group decision-making on judgments that are not dichotomous (e.g., Bonner, Gonzalez, & Sommer, 2004; Davis, 1996; Miller, 1989). Dichotomous choice tasks have real-world relevance (e.g., jury decision-making; Supreme Court decisions), but many consequential group decisions, such as budget negotiations, forecasting future demand, or determining agreed upon standards like fuel efficiency for cars, are made from ordered options on a continuum. There are theoretical reasons to suggest that group dynamics, especially minority/majority dynamics, change when groups work on a decision with ordered alternatives rather than a dichotomous decision.

With dichotomous choices, the group can only pick one option or the other, but with ordered alternatives, more compromise is possible because members can move closer to each other without necessarily conceding their position (Nemeth, 1986). Furthermore, the distinction between majority and minority can be hazy, as even group members on one side of an issue can differ on how extremely they rate their opinion (Miller, 1989). With ordered alternatives, there is not an explicit statement of a position that is different or in opposition to others, but rather differences are a matter of discrepancy and cognitive distance from others. Thus, we define members in a group in terms of discrepancy from other members based on their position on the ordered alternatives, rather than define members as taking the minority or majority viewpoint on a dichotomous task; group members can have discrepancy or cognitive distance from others in the group. Previous research on integrative complexity and minority dissent has used dichotomous tasks. However, disagreement is not as salient in a group with ordered alternatives because members with differences of opinion have more options for changing their opinion than having to switch sides. Therefore, concepts such as minority dissent are not as salient. For example, rather than move from for to against, a member could moderate their opinion. This could reduce the difference in stress and anxiety between being in the majority or having less discrepancy from other group members and being in the minority or having more discrepancy from other group members. This could affect whether having more dispersion of opinion in a group increases the integrative complexity of the contributions of less discrepant members. Therefore, we seek to determine if the benefits of dissent from more discrepant members in groups will replicate on tasks in which group members make a judgment on an ordered scale.

Research Question 1 (RQ1): With the presence of more dispersion of opinion in a group, will less discrepant group members state arguments with higher levels of integrative complexity than more discrepant group members?

Integrative Complexity and Conversion Theory

Status-contingency theory (Gruenfeld, 1995) highlights how the need to understand minority dissent coupled with the lower stress of being a majority member can increase both the motivation and ability for majority members to systematically process minority members’ arguments. This complements conversion theory’s explanation for how majority and minority members often persuade differently in groups. Per conversion theory (Levine & Prislin, 2013; Martin & Hewstone, 2001; Moscovici, 1980, 1985), majority members in a group exert their influence through social comparison in which other members conform without carefully examining majority members’ arguments because conforming to the majority is desirable and not conforming is stressful. Therefore, members concentrate more on majority members’ position instead of the reasoning behind majority members’ position. However, when encountering minority dissent, majority members try to understand the minority members’ thinking and examine the minority members’ reasoning and conclusions; a process called validation. To be influential, a minority member must present strong reasoning and systematic conclusions.

Initially, a minority viewpoint is rejected and considered wrong, but a consistent and nondogmatic minority can cause majority members to try to validate the minority position by considering its arguments more carefully. Moscovici and Personnaz stated (1980), “that a conflict of responses with the minority triggers an intense intellectual or perceptual effort to assess the relation of the minority’s judgment to reality” (p. 272). Majority members are influenced more by minority conversion than conformity, as conversion requires the majority to analyze minority members’ arguments more thoroughly. Furthermore, Wood et al.’s (1994) meta-analysis found that minority influence is also more private and indirect, in support of conversion theory. Because minority members’ arguments are scrutinized and processed more centrally, minority members’ arguments need to be consistent, present clear reasoning, be more flexible and nondogmatic (Mugny & Papastamou, 1980), and show commitment to the viewpoint (Moscovici & Personnaz, 1980).

This suggests another role that integrative complexity can play in minority influence. Conversion theory predicts greater scrutiny of minority members’ arguments and less scrutiny of majority members’ arguments. Because arguments with high levels of integrative complexity incorporate more cognitive connections, strengthen overall cognitive complexity, and reflect an acknowledgment of multiple sides of an issue and connections among several concepts, they should be more persuasive, especially when used by a group member whose arguments are being scrutinized more (Baker-Brown et al., 1992; Tetlock, 1986). We seek to generalize the results of conversion theory to groups making decisions with ordered alternatives. Therefore, we hypothesize that having more integratively complex arguments should be related to greater influence for more discrepant group members, but not related to greater influence for less discrepant members whose opinions are closer to other group members.

Status-contingency theory predicts that minority members have less integratively complex arguments than majority members, and we are not predicting otherwise. Rather, we predict that when members with more discrepant opinions do present arguments higher in integrative complexity, they will be more influential in the group. Whereas, integrative complexity will not be linked to increased influence for less discrepant members because, according to conversion theory, majority members influence through normative influence and their greater numbers, and less through informational influence (Deutsch & Gerard, 1955).

Hypothesis 1 (H1): For more discrepant members, higher integrative complexity should lead to more influence, but for less discrepant members, integrative complexity should not affect influence.

Finally, De Dreu and West (2001) found that dissent increased group-level innovation in organizational work teams under conditions of high participation, but not low participation. They reasoned that only with higher levels of participation are group members able to share and critically process information and develop a motivation to understand alternative viewpoints. High levels of participation increase the ability and motivation for a majority member to systematically process arguments when exposed to dissent. Wittenbaum and Park (2001) theorized that with information sharing in groups, initial group discussion is used to develop a common ground and psychological safety among group members by discussing shared information and interests. Only later are groups willing to discuss newer information and arguments that may be more critical and innovative. De Dreu and West conducted a field study and used survey items to measure dissent and perception of participation, and they advised that additional, future experiments needed to replicate their findings with actual behavioral measures rather than survey items assessing perception of participation and dissent. We try to generalize their results on innovation and participation to research on integrative complexity and to add to research using a behavioral measure of word count for participation and a behavioral measure of dispersion of opinions in the group to measure dissent in a group.

Hypothesis 2 (H2): In groups with higher levels of participation, members will state arguments with higher levels of integrative complexity than in groups with lower levels of participation, and this effect should be stronger in groups with higher amounts of dispersion of opinion.

Method¹

Participants and Design

Participants (males = 63, females = 167) were undergraduate students from a large, public Midwestern university in the United States receiving extra credit in a communication course for participation. Same-gender groups were used to avoid any status expectations linked with sex that could affect participation (Balkwell & Berger, 1996). Participants were randomly assigned to an experimental time based on their schedule. There were 29 four-person groups, 21 five-person groups, and 3 three-person groups. Although at least five participants were scheduled for each session, group size was dependent on the attendance rate for an experiment.

Procedure and Materials

To select a controversial topic, eight issues were pilot tested (e.g., use of performance enhancing drugs, euthanasia, legalization of prostitution, medical marijuana, keeping the words “under God” in the Pledge of Allegiance, etc.). Medical marijuana was universally popular in our sample and use of performance enhancing drugs was universally unpopular, so it would have been difficult to have diversity of opinions in the groups if they deliberated these topics. For this study, keeping “under God” in the U.S. Pledge of Allegiance was used because there was a strong range of opinions and strong feelings on the issue in our student sample.

Participants were given informed consent forms. Then, they filled out a form asking if they were U.S. citizens; non-U.S. citizens were excused from the experiment. Participants were told that the study was examining how people discuss controversial issues in groups and were asked to read a one-page sheet with background information about whether the words “under God” should remain in the Pledge of Allegiance. The information came from a nonpartisan website (http://undergod.procon.org) and was credited as such (see the appendix); the information was designed to be evenhanded. Participants were given a copy of the Pledge, and a large (3 feet × 5 feet) U.S. flag was hanging in the laboratory to highlight the issue.

After reading the information, participants were asked to individually rate their attitude toward the issue on a 9-point scale from 1 (I completely oppose the words “under God” appearing in the US Pledge of Allegiance) to 9 (I completely support the words “under God” appearing in the US Pledge of Allegiance), with a midpoint of 5 (unsure). Then, participants were brought together as a group. All sheets were collected, and each group member was randomly assigned to a spot at the table labeled with a large visible letter to help distinguish their contributions in the digital recording. Participants were told the following:

Now please discuss the issue as a group and make a group decision about the issue. We ask that you discuss the issue for at least ten minutes, but you may continue up to 30 minutes. After the group discussion, you will be asked to voluntarily say the Pledge of Allegiance either with or without the words “under God” based on your group’s decision. You are free to decline to say the Pledge for any reason, which you do not have to tell us. All interaction will be video recorded. Any questions?

After reading the instructions and answering questions, the experimenter put a group decision sheet in the middle of the table, instructed the group to reach a decision on the issue, and left the room. The sheet asked the group to record their decision on the same scale that participants filled out individually. When discussion was finished, they (voluntarily) faced the flag and recited the Pledge the way that their group had decided (with or without the words “under God”). Participants were not forced to say the Pledge of Allegiance, and some group members (n = 13) chose to say the Pledge differently than their group or not say the Pledge at all. Finally, participants were asked individually to rate their attitude about the Pledge of Allegiance on the same rating scale as pre-deliberation to examine if any immediate attitude change occurred. Participants were debriefed and thanked.

Integrative Complexity Coding

Digital recordings were transcribed verbatim by two graduate students who each transcribed one group’s interaction on tape. Their work was checked by the first author. Any problems were discussed before they transcribed the rest of their recordings. Recordings were split between the two transcribers. Two recordings had technical difficulties, leaving recorded discussions for 51 groups. Once the recordings were transcribed, each group transcript was split into individual files for each group member’s spoken contributions.

A senior undergraduate and graduate student coder were trained for assessing integrative complexity using the Conceptual/Integrative Complexity Scoring Manual (Baker-Brown et al., 1992). After training, coders completed the Integrative Complexity Scoring Tests I and II and were given feedback on their coding. Coders were instructed to score evidence of integration and differentiation for each individual group member’s transcribed contributions in half-page increments (see Baker-Brown et al., 1992, for the detailed coding instructions). Coders read each member’s contributions to the discussion individually without knowledge of the member’s level of agreement with others in the group. A score was provided for each half-page of contributions from each member. Differentiation and integration are represented on ordinal scales with low values (1-3) reflecting differentiation and high values (5-7) indicating conceptual integration. A score of 1 indicates no evidence of differentiation or integration. A score of 2 indicates implied but not detailed differentiation. A score of 3 indicates explicit differentiation but little integration is present. A score of 4 indicates implicit integration accompanied by high differentiation. A score of 5 indicates differentiation is present and the effects or trade-offs of varied perspectives are explored. A score of 6 indicates high differentiation with implicit or described integration. A score of 7 indicates high differentiation with the pros/cons of alternate perspectives being described in detail and/or complex ways, as well as the inclusion of effects or alternative paths that may not be previously discussed. For each individual member, their average integrative complexity score of the half-page increments served as their integrative complexity score in analysis.

The intraclass correlation between the coders, using two-way mixed effects model, was significant, ICC = .83, p < .0001, and the Krippendorff alpha (.69) was acceptable (Hayes & Krippendorff, 2007). Therefore, the reliability was acceptable. The average of the two coders was taken as a measure of integrative complexity. The average integrative complexity was 2.40 (SD = 0.93). Furthermore, 39.3% of average ratings were 2.0 or below.

Results

We operationalized individual-level difference of opinion as the average discrepancy the individual had from others in the group. For example, in a four-person group with member rated opinions of 8, 3, 9, and 5, the member that rated their opinion as 8 would have an average discrepancy from other members of 3 ([8 – 3] + [9 – 8] + [8 – 5]) / 3, and the member who rated their opinion as 3 would have an average discrepancy of 4.33. The group mean of individual level discrepancy was taken as a measure of dispersion of opinions in the group. We examined each group and classified it as a high-disagreement group if group members’ pre-deliberation opinions about leaving the words “under God” in the Pledge of Allegiance were rated on both sides of the midpoint (5). For example, a group with members’ pre-group opinions as 6, 7, 7, 4, and 2 was classified as a high-disagreement group. Groups in which all members were on one side of the scale—including the midpoint (e.g., 1 to 5 or 5 to 9)—were classified as low-disagreement group. There were no groups in which all members were unanimous. The group average of dispersion of opinion highly correlated with whether the group had been classified as high disagreement (1) or low disagreement (0), r = .74, p < .001. Hence, average dispersion is a good indicator of presence of disagreement of opinions.

RQ1 asked if in groups with more dispersion of opinions, the members with lower discrepancy scores would have higher integrative complexity scores for their arguments than members with higher discrepancy scores. Using hierarchical linear modeling (HLM), guided by H1, we predicted integrative complexity score with the Level 1 individual level variable of individual discrepancy and the Level 2 group-level variable of average dispersion of opinions in the group. Group size and gender of group were included as Level 2 variables as a control. Individual Level 1 variables were group mean centered, and group Level 2 variables, except for gender, were grand mean centered (Enders & Tofighi, 2007). For the Level 2 variable of dispersion of opinions in the group, there was no effect (γ₀₃ = .02, df = 206, SE = 0.10, p = .84). Therefore, there was no relationship between more dispersion of opinion in the group and amount of integrative complexity of arguments used. There was also not a main effect of individual-level discrepancy (γ₁₀ = .21, df = 206, SE = 0.50, p =.67), so members with more discrepant opinions did not have more or less use of integrative complexity in their arguments. Furthermore, the slope between individual discrepancy and dispersion of opinions in the group was not significant (γ₁₃ = .10, df = 206, SE = 0.09, p = .27). Therefore, in groups with more dispersion of opinion, less discrepant members did not have higher integrative complexity than more discrepant members did. To answer RQ1, more dispersion of opinion did not increase the integrative complexity of less discrepant members in comparison with more discrepant members.

H2 predicted higher integrative complexity of arguments with more participation, the effect being stronger with more dispersion of opinion in the group. Group word count ranged from a low of 671 words to a high of 5,347 words with an average of 2,118.97 (SD = 996.77). Through HLM, we used the group Level 2 standardized variable of group word count as a measure of participation, the group-level measure of dispersion of opinion, and the interaction between the two variables. Furthermore, we controlled for group size and gender by including them as Level 2 variables in the analysis. We found an effect of participation (γ₀₁ = .370, df = 45, SE = 0.139, p = .01). Groups with higher levels of participation, even after controlling for group size, had higher integrative complexity in members’ contributions, thus supporting H2. Although we used standardized word count as a continuous variable in the analyses, we present mean integrative complexity for groups in top half of word count (M = 2.83, SD = 1.00) and the bottom half (M = 2.10, SD = 0.74). Amount of participation did not interact with amount of dispersion of opinion in the group (γ₄₁ = −.032, df = 45, SE = 0.100, p = .75). Contrary to H2, the effect of groups having more integrative complexity with more discussion was not stronger in groups with more dispersion of opinion. Therefore, H2 was partially supported.

Agreement With Group Opinion

We examined how the integrative complexity of members’ arguments affected how close their opinion was to the group opinion. We had two measures of agreement (Van Swol, Braun, Acosta Lewis, Carlson, & Dimperio, 2018): comparative agreement and residual agreement. Comparative agreement took the absolute value of a member’s opinion before the group discussion minus the group opinion (|pre-group opinion – group opinion|) and subtracted from this the average absolute difference of the other group members from the group opinion. If a member had 6 as their pre-group opinion, the group opinion was 5, and the mean absolute difference from the group opinion for other group members is 2; then this member has a comparative agreement score of –1.00. Larger negative numbers indicate that a member’s pre-group opinion was closer to the group opinion than other members in the group (more agreement), and larger positive numbers indicate that their opinion was further from the group opinion than others (less agreement). Our second measure of agreement is residual agreement. The mean of group members’ pre-group opinion (pre-group mean) is used as the standard, and residual agreement calculates the amount the group opinion is from this standard in the direction of an individual member’s opinion. Residual agreement measures the potential ability an individual group member has to attract the group from the pre-group mean toward their own opinion. For residual agreement, higher positive numbers indicate more agreement, and it is represented by:

[(Group opinion – pre-group mean) × (Individual opinion – pre-group mean)] / pre-group mean.

Both measures try to control for group differences in dispersion of opinion by including the mean of other members’ pre-group opinions into the equation.

Using HLM, we predicted comparative and residual agreement measures (in two separate analyses) with Level 1 variables of integrative complexity score and discrepancy of member’s opinion from others, and interaction terms between discrepancy and integrative complexity. Group size and gender of group were included as Level 2 variables as a control. Individual Level 1 variables were group mean centered, and group Level 2 variables, except gender, were grand mean centered. For comparative agreement, the intercept was not significantly different from 0 (γ₀₀ = .09, SE = 0.26, p = .73), and there was no significant variation in this intercept value (U₀ = 0.00, p > .50). There was a significant effect of member status (γ₁₀ = 1.09, df = 155, SE = 0.47, p = .02). More discrepant members had less comparative agreement than less discrepant members; thus, the group decision was less in agreement with discrepant members’ initial opinions. There was a significant interaction between discrepancy of member opinion and integrative complexity (γ₃₀ = −0.02, df = 49, SE = 0.01, p = .05). This interaction, discussed in the next paragraph, is in conjunction with the interaction results of residual agreement.

For residual agreement, the intercept was not significantly different from 0 (γ₀₀ = −.06, SE = 0.10, p = .57), and there was no significant variation in this intercept value (U₀ = 0.00, p > .50). The main effect of discrepancy of opinion was not significant (γ₁₀ = .04, df = 155, SE = 0.11, p = .68). There was a significant interaction of discrepancy of opinion and integrative complexity (γ₃₀ = .01, SE = 0.00, p = .01). For more discrepant members, increases in integrative complexity led to both more comparative (negative numbers indicate more agreement) and residual agreement. However, for less discrepant members, there was no relationship between the integrative complexity of their arguments and how close the group opinion was to their initial opinion. This supports H1.

Discussion

To summarize the results, in groups with more dispersion of opinion, less discrepant members did not have higher integrative complexity than more discrepant members. Thus, using a task with ordered instead of dichotomous alternatives, we failed to replicate the finding that minority dissent increases the integrative complexity of the majority. Groups with longer discussions had higher integrative complexity among all members. Finally, more discrepant members with higher levels of integrative complexity were more likely to have the group opinion closer to their own initial opinion in comparison with other members, but integrative complexity was not related to agreement to the group opinion for less discrepant group members.

This research adds to research about integrative complexity and minority influence in several ways. First, this was the first study to test whether the findings of status-contingency theory generalize to group decisions made on a nondichotomous, ordered scale. Below, we discuss possible reasons why results did not generalize. Second, this was also the first study to examine integrative complexity as a means of influence rather than an outcome of minority influence. Results support conversion theory and suggest that future research should examine the relationship between integrative complexity and influence. Finally, researchers have called for more research examining the influence of minorities in dynamic interacting groups rather than minority dissent in a noninteraction paradigm, in which people are just made aware of the presence of minority dissent without the opportunity to interact with the dissenter (Curseu et al., 2012; Levine & Hoon-Seok, 2011; Smith et al., 1996). Below we discuss these results in more depth.

Integrative Complexity and Status-Contingency Theory

Scoring opinions on an ordered scale instead of dichotomously may have blurred the line between majority and minority members in groups. As reviewed in the introduction, Gruenfeld (1995) hypothesized that differences in integrative complexity between majority and minority group members were the result of stress levels. However, given that our study measured participants’ opinion on a continuum, the divisions between minority and majority members were not as clear-cut as previous research on integrative complexity. Because opinions were measured in terms of cognitive distance from each other and not in terms of opposition, members whose opinion were on the other side of the midpoint from the majority of the other members may not have even realized they were holding a minority opinion. Therefore, there may have been less variation in stress and arousal levels between group members, and this may have affected differences in integrative complexity among members. Furthermore, if lower integrative complexity of minority members in previous research (see Gruenfeld, 1995) is the result of convergent thinking, conformity, and a focus on the majority opinion as correct, then the fact that a highly discrepant member in this study could move toward the positions of other members on the one to nine scale without necessarily switching from yes to no may have diminished the focus on a united majority position.

Given the failure to replicate status contingency’s findings on integrative complexity and minority influence, this identifies a clear need for more research to identify the boundary conditions of the finding that minority members cause more integrative complexity among the majority. Our findings point to a clear direction for this future research. Ideally, the task should be manipulated directly (dichotomous vs. ordered task) to examine differences in the effect. Furthermore, the primary theoretical assumptions of status-contingency theory (Gruenfeld, 1995) need to be tested by measuring levels of stress for minority and majority members and testing for differences in stress levels and its effects on integrative complexity.

Integrative Complexity and Conversion Theory

The interaction between discrepancy of individual member opinion and integrative complexity of their arguments affected a member’s influence, as measured by agreement, in the group. More discrepant members’ initial opinions had more agreement with the group opinion when they used arguments higher in integrative complexity, whereas less discrepant members did not have more agreement with the group opinion in the presence of more integratively complex arguments. Although given that participants’ contributions were scored on the lower end of the integrative complexity scale, a fairer conceptualization of the results may be in terms of differentiation than integrative complexity because the majority of participants’ discourse did not reach the level of integrating concepts and the inclusion of alternative ways of thinking.

Our results support previous research on conversion theory that posits that minority members’ arguments and information are more systematically processed (Levine & Prislin, 2013; Martin & Hewstone, 2001; Moscovici, 1980, 1985). Past research has treated integrative complexity as an outcome of minority influence. We extended research in integrative complexity by examining the role between integrative complexity and influence for members in an interacting group. Whereas integratively simple thinkers tend to emphasize the usefulness of “simple rules of thumb” (Tetlock, Peterson, & Berry, 1993, p. 502), integratively complex individuals are less dogmatic and rigid. Research notes that minority group members are more persuasive when they are less dogmatic in general (Mugny & Papastamou, 1980; Nemeth, 1986), so discrepant members with higher integrative complexity should also be more influential.

One limitation of this finding is that our measures of influence were actually measuring how much a member’s initial opinion agreed with the group decision and not how much that member actually influenced the group. If the group opinion was close to or agreed with a group member’s initial opinion, this could reflect influence of that member, but it could also reflect other dynamics in the group like taking the average to reach consensus or could reflect the influence of another group member whose initial opinion was similar to the other member. Therefore, while we hypothesized about influence, our measure of influence more accurately reflected agreement with the group decision. A second limitation to this finding is that less discrepant members had less variance in their influence scores on the group. In general, less discrepant members were more influential, but they generally had a smaller range of influence scores. This may have limited the amount of variance that could be understood by integrative complexity.

Participation and Integrative Complexity

We also add to research by De Dreu and West (2001) who found that dissent increased group-level innovation only for groups with high levels of participation. De Dreu and West measured perception of participation and perception of dissent with survey items asking for members’ ratings. We extended their findings using behavioral measures of both participation and dissent rather than using survey items. We found that group-level discussion increased individual-level integrative complexity for all members; we did not find that amount of discussion interacted with amount of dispersion in the group to affect integrative complexity. This also adds to research by Curseu, Schalk, and Schruijer (2010) who found that groups needed time to establish more complex relationships between more differentiated and distal concepts than for concepts that were more similar conceptually. Longer discussions may have allowed for more critical examination of the information and arguments that could increase integrative complexity. Furthermore, initial group discussion may have been more devoted toward members becoming comfortable with each other and establishing credibility and common ground (Wittenbaum & Park, 2001). De Dreu, Nijstad, Bechtold, and Baas (2011) found minority dissent leads to more innovation in groups when there is an environment of psychological safety characterized by trust. Larson, Christensen, Abbott, and Franz (1996) found that groups discuss more unshared and unique information later in group discussion after group members have exhausted their discussion of shared information that the group members feel more comfortable discussing. Therefore, as the discussion progressed, members could have become more comfortable and their ability and motivation to present more integratively complex arguments increased. One limitation of this study is that length of discussion measured by word count may not have always reflected participation of all group members, especially if one group member dominated the discussion. Although all members were exposed to more arguments and deliberation with longer discussions, participation was not always equitable.

Conclusion and Future Research

Many important decisions are made from ordered options, so more research is needed about how group dynamics related to discrepancy and cognitive distance differ from group dynamics related to the minority versus majority dichotomy. As mentioned previously, future research should test why previous research on differences in integrative complexity between minority and majority members failed to replicate in this study, and also test whether underlying processes such as stress and arousal levels or convergent thinking are driving the results. More research should also test the effects of integrative complexity on influence in the group and try to generalize our findings of the effects of integrative complexity on influence to other tasks. In conclusion, we hope future research will test the boundary conditions of when discrepant or minority views increase the integrative complexity of other members’ thinking.

Footnotes

Appendix

Should the Words “Under God” Be in the U.S. Pledge of Allegiance?.

About this topic
The Pledge of Allegiance was first written in 1892 by Francis Bellamy, a Baptist Minister and Socialist, for the patriotic family magazine The Youth’s Companion. At that time it read “I Pledge Allegiance to my Flag and the Republic for which it stands; one nation indivisible, with liberty and justice for all.” The Pledge officially became part of the U.S. Flag Code in 1942. In 1954, the words “under God” were added to the Pledge by Congress with approval from President Dwight Eisenhower. A 2001 lawsuit, filed by Michael A. Newdow, contested the inclusion of the phrase “under God” in the Pledge of Allegiance, citing a violation of church-state separation principles. To clarify this multifaceted issue, here are pro and con responses to the central questions in the words of key proponents and opponents in the debate.
PRO under god	CON under god
PRO: Some proponents argue that the United States was created from the Christian principles of the Founding Fathers and as such the Pledge should respect the country’s heritage. Others say the U.S. Constitution protects freedom of religion and not freedom from religion. Many advocates of including “under God” in the Pledge point out that polls show at least 80% of Americans support it, that federal law already contains 22 references to “God,” and that Presidents swear an oath of office ending with “so help me God.” Many others claim the incorporation of religious language is a reflection of the U.S. civic culture and not a promotion of religion.	CON: Some opponents argue that church and state should be kept separate as the Founding Fathers intended. Others say the phrase “under God” in the Pledge places “undue coercion” on young children, thus violating the Establishment Clause of the First Amendment. They also declare that the US Constitution protects minority rights against majority will. Many advocates of removing “under God” point out that the phrase was not written into the original pledge and that the opposition to returning to the original pledge is proof that “under God” is a religious symbol and not merely a secular practice.

Acknowledgements

Thanks to Brennan Harris, Flannery Devine, and Riley Roehl for help with coding and running the experiment.

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.

Notes

Author Biographies

Lyn M. Van Swol (PhD, University of Illinois at Urbana–Champaign) is a professor in the Department of Communication Arts at University of Wisconsin–Madison, USA. Her research examines communication of advice, discourse and exchange of information in groups, and deception in negotiations.

Cassandra L. Carlson-Hill (PhD, Communication Arts, University of Wisconsin–Madison) is an assistant professor at Coastal Carolina University, USA. Her primary research interests lie at the intersection of social support and persuasion, namely examining advice communication in family contexts.

Emily Elizabeth Acosta Lewis (PhD, Communication Arts, University of Wisconsin–Madison, USA) is an assistant professor and faculty-in-residence at Sonoma State University, USA. Her primary interest is in the role of media and new media in shaping viewers’ perceptions of social reality via persuasion, communication, and psychology theories.

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Integrative Complexity,Participation,and Agreement in Group Discussions

Abstract

Keywords

Integrative Complexity and Status-Contingency Theory

Integrative Complexity and Conversion Theory

Method 1

Participants and Design

Procedure and Materials

Integrative Complexity Coding

Results

Agreement With Group Opinion

Discussion

Integrative Complexity and Status-Contingency Theory

Integrative Complexity and Conversion Theory

Participation and Integrative Complexity

Conclusion and Future Research

Footnotes

Appendix

Acknowledgements

Declaration of Conflicting Interests

Funding

Notes

Author Biographies

References

Method¹