Factors That May Affect the Difficulty of Uncovering ...

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Group Processes & Intergroup Relations 2003 Vol 6(3) 285–304

Factors That May Affect the Difficulty of Uncovering Hidden Profiles Lyn M. Van Swol Northwestern University

Lucia Savadori University of Trento

Janet A. Sniezek University of Illinois at Urbana-Champaign

Three experiments examined three factors that may impede the discovery of hidden profiles: commitment to initial decision, reiteration effect, and ownership bias. Experiment 1 examined whether groups in which members are not asked to make an initial decision before group discussion are more likely to uncover hidden profiles than groups in which members are asked to make an initial decision. Experiment 2 examined this commitment to an initial decision and also the repetition of information for individuals. Experiment 3 explored the reiteration effect in groups and examined whether information that is usually repeated more in groups is viewed as more truthful. Experiments 1 and 2 found no support for the commitment to initial decision hypothesis for uncovering hidden profiles. Experiment 2 found that repetition of ‘common’ information significantly reduced individuals’ ability to uncover hidden profiles. Experiment 3 found that information individuals owned (both common and unique) before discussion was rated as more valid than other information. Experiment 3 did not find that common information, which is generally repeated more, was rated as more valid than unique information. Limitations of the current studies and suggestions for future research are discussed.

keywords common information bias, hidden profile, information sampling, reiteration effect R E S E A R C H E R S have found that group members tend to discuss information that they hold in common (common information) much more than information that each individual member alone holds (unique information) (for a review, see Wittenbaum & Stasser, 1996). Wittenbaum

Author’s note Address correspondence to: Lyn M. Van Swol, Department of Communication Studies, Northwestern University, 2240 Campus Drive, Evanston, IL 60208, USA [email: [email protected]]

Copyright © 2003 SAGE Publications (London, Thousand Oaks, CA and New Delhi) [1368-4302(200307)6:3; 285–304; 033837]

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and Stasser (1996) call this the common information sampling bias. The finding that groups tend to focus on common information has intrigued and concerned researchers because groups are often used to make decisions precisely because it is assumed that members’ unique contributions will lead to a better decision than any one individual would make alone (Gruenfeld, Mannix, Williams, & Neale, 1996; Wittenbaum, 1998). A number of studies (Hollingshead, 1996a; Savadori, Van Swol, & Sniezek, 2001; Stasser & Stewart, 1992; Stasser, Stewart, & Wittenbaum 1995; Stasser & Titus, 1985) have demonstrated groups’ inability to adequately discuss unique information through the use of hidden profiles. In a hidden profile information is distributed such that the sum total of information that the group collectively holds favors a superior alternative, but each individual member’s distribution of information favors another, inferior alternative. Each member alone cannot identify the superior alternative because they hold only a portion of the information that supports it. With a hidden profile much of the common information favors the inferior alternative, and much of the unique information favors the superior alternative. In this way, the superior alternative is ‘hidden’ in the unique information. If group members are unable to consider most of the unique information, they are likely to choose the inferior alternative. Groups usually fail to discover hidden profiles (Stasser & Stewart, 1992; Stasser, et al., 1995; Stasser & Titus, 1985). Groups need to mention and discuss the unique information to uncover hidden profiles (Hollingshead, 1996b; Stasser & Stewart, 1992; Stasser et al., 1995). Stasser and Stewart (1992, p. 427) state, ‘the discovery of a hidden profile depends on consideration of unique information during discussion’. However, even if each group member mentioned their unique information at least once so that the group has access to all the information, would they uncover the hidden profile? Factors other than the failure to mention unique information can work against uncovering hidden profiles. Before meeting in a group, members often

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make an individual decision that may bias how they view the information that is discussed in the group. Also, common information is often repeated more than unique information. This might increase its impact on the group decision. Therefore, sharing of all information in discussion may be necessary for groups to discover hidden profiles, but due to other processes, it may not be sufficient. The present research consists of three experiments designed to examine the roles of initial decisions and repetition of information on decision making with hidden profiles.

The effects of the initial decision Commitment to an initial decision may cause group members to discount new information they receive if it contradicts their initial individual decision. Staw (1997) describes the outcome of decision making as a process of self-justification in which information processing is biased in the direction of consistency between future information and the past decision. Much research in psychology has attested to the power of initial judgments biasing later individual information processing. For example, Petty and Cacioppo (1986) have found that information that supports one’s decision is more thoroughly processed. Lord, Ross, and Lepper (1979) report that people tend to focus on information that supports their initial preference and discount information that opposes their preference. In a study by Echabe and Rovira (1989), people were found to selectively remember information supporting their pre-existing beliefs and distort new information so that it reinforced their pre-existing beliefs. Other research has found that groups are also subject to the power of initial judgments. Schultz-Hardt, Frey, Luthgens, and Moscovici (2000) found that groups in which all members hold similar attitudes have a confirmation bias toward searching for information that supports the group’s consensus. Research with the Common Knowledge Effect (Gigone & Hastie, 1993) supports the power of individual


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pre-discussion preferences in determining the group response. Gigone and Hastie (1993) report that members’ individual pre-discussion decisions were the best predictor of a group’s decision, and that information discussed by groups impacted group decisions only indirectly through group members’ pre-discussion decision. Other work indicates that social psychological processes unique to groups inhibit the discover y of hidden profiles. Stasser and Stewart (1992) stated that ‘strong commitment to initial preferences’ may interfere with the pooling of unique information in groups. Stasser and Titus (1985, 1987) suggested several reasons why group members’ commitment to an initial decision may bias group discussion. First, group members will be more likely to mention information that supports what the majority of other group members support. If a particular viewpoint predominates in a group, group members may tailor the information they mention toward that viewpoint (Stasser & Titus, 1985, 1987). With a hidden profile, the majority of the group members enter the group discussion supporting the inferior alternative because the information they are initially given before group discussion supports the inferior alternative. Therefore, unique information supporting the superior alternative is unlikely to be mentioned because it does not favor the initial consensus of the group members. Further, group members are more likely to recall preferenceconsistent information during group discussion. Finally, even if preference-inconsistent information is recalled by a group member, group members are likely to adopt an advocacy role and mention information supporting their viewpoint, so that ‘discussion tends to favor the most popular position in the group’ (Stasser & Titus, 1987, p. 83). Group members usually defend their initial decision during group discussion, and with a hidden profile this would cause them to mention the common information, which tends to support their initial decision, more than the unique information (Stasser & Titus, 1985, 1987). Stasser (1988) examined the effects of advocacy or non-

difficulty uncovering hidden profiles

advocacy of a prior individual opinion on the group’s decision via computer simulation. In the nonadvocacy condition, members were equally likely to mention information that supported either choice. In contrast, members in the advocacy condition were biased toward mentioning information that supported one of the choice alternatives. However, using the same information distributions as Stasser and Titus (1985), Stasser found that common information dominated discussion in both the advocacy and nonadvocacy conditions and that both conditions failed to uncover hidden profiles. These results suggest that prior advocacy of an opinion is not a sufficient factor preventing discovery of hidden profiles. Still, minorities who were given more information supporting the superior alternative were shown to be more effective in facilitating the uncovering of hidden profiles in the nonadvocacy condition than the advocacy condition. Concluding, the difficulty uncovering hidden profiles may be partially explained by a commitment by group members to their initial individual opinions. Experiment 1 tests this ‘commitment to initial decision’ hypothesis by comparing choices of groups whose members are asked to make an individual choice before entering the discussion to groups whose members are not asked. In the first condition, individuals were expected to build their opinion during the individual phase, but in the second condition, individuals were expected to build their opinion during group discussion. Theoretically, there is a distinction between biased information processing in individuals and social processes involving justification or advocacy to other group members. Although empirical studies have demonstrated the potency of initial decisions with individuals and with groups, few studies (for exception see, Schulz-Hardt et al., 2000) have examined commitment to initial decision at both the individual and group levels under comparable, controlled conditions. We do this by manipulating the initial decision for individuals in Experiment 2 under conditions comparable to those for groups in Experiment 1.

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Experiment 1 Method Participants Ninety-six undergraduates at a large midwestern university participated in the experiment in partial fulfillment of course credit. Participants were assigned to time slots according to class schedules and were randomly assigned to three-person groups, for a total of 32 groups. Of these, 18 groups were assigned to the ‘no initial decision’ or one decision condition and 14 groups were assigned to the ‘initial decision’ or two decision condition. Decision task The task was based on previous work by Karau (1994). The problem was to decide which of two cholesterol-lowering drugs to market. To select information for the task, pretest ratings from Karau (1994) were used. Each piece of information was previously rated according to its desirability and importance. The pieces of information were selected so that a piece of negative information for drug 1 would be about the same in terms of negative valence as a piece of negative information for drug 2, and a piece of positive information for drug 1 would be the same in terms of positive valence as a piece of positive information for drug 2. Examples of positive information were: ‘The sales potential of drug 1 is 40% greater than any other drug now being produced by the company’, and ‘A three-month study of 22 human patients showed that total cholesterol levels decreased by 10% and high density lipoprotein levels increased by 32% for drug 2’. Examples of negative information were: ‘Several of the short term human studies conducted on drug 1 that showed it was effective have been criticized for poor methodology’, and ‘Drug 2 interacts with a wide variety of other prescription drugs, often in undesirable ways’. An example of neutral information was: ‘Drug 1 would probably be delivered to distribution sites from the main factories by truck or train’. Sixty-six percent of the information that each individual received was common to all three group members and 33% was unique. Each individual was given 18 pieces of

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information for each drug. Information was distributed to create a hidden profile so that individually participants had more positive information for drug 2, but collectively the total information for the group favored drug 1. Collectively there were 16 pieces of information that were positive for drug 1 and 11 pieces that were negative, and collectively there were 11 pieces of information that were positive for drug 2 and 16 pieces that were negative. The distribution of information between the group members is presented in Table 1. Procedure Participants met in a large room at the beginning of the session and received informed consent forms explaining the experiment. Participants were given preliminar y instructions describing the general research topic and a booklet of experimental materials. The booklet began with instructions varying by condition. Participants in the initial decision condition were asked to play the role of a manager in a pharmaceutical company and decide which drug to market to help save the company from a possible bankruptcy. Medical information on heart disease and its relationship to high cholesterol levels and drugs meant to reduce cholesterol was provided along with the participant’s 36 pieces of information about the two drugs. Participants received a sheet labelled drug 1 containing information on drug 1 and another sheet labelled drug 2. Common and unique and positive, negative, and neutral information were randomly mixed together, and common and unique information was not identified to participants as such. To avoid order effects, the order of information presentation was reversed for half the participants. In the no initial decision condition, participants were asked to play the role of a manager in a pharmaceutical company and read over information about two cholesterollowering drugs. They also were given the medical information on high cholesterol and the 36 pieces of information. Participants individually read through the experimental booklet. Upon finishing, those in the initial decision condition were asked to make a tentative decision prior to meeting in


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Table 1. Division of positive and negative information for drug 1 and drug 2 Information Drug 1

Drug 2

Member 1

12 common (8 negative, 1 positive, 3 neutral) 6 unique (5 positive, 1 negative)

12 common (8 positive, 1 negative, 3 neutral) 6 unique (5 negative, 1 positive)

Member 2



Member 3



Total group



their group. After the individual instructions and decision, if any, participants were moved to smaller group rooms to begin their discussion. All groups were asked to play the role of managers in a pharmaceutical company and decide which drug to market to help save the company from a possible bankruptcy. They were told that they had up to 25 minutes to discuss the material, but had to discuss it for at least a minimum of 15 minutes. If they were still discussing the information after 25 minutes, they were told to finish and were given a few extra minutes to finish their discussion. Before discussion, participants in both conditions were told that the information given to each member might not be entirely identical to the information received by another group member. Therefore their information might not be complete, and another group member might have information of which the participant is unaware. Participants were allowed to keep the information sheets during the group discussion. This was done for two reasons. The first was to represent the reality that members of managerial groups bring notes to meetings to manage a large amount of information, and

second, to avoid the effects of selective memory on the decision task. To enhance communication between the group members, participants also were told that while they could discuss any information on their sheets during discussion, they could not show their information sheet to other group members. All three members sat around a table during the discussion. After the group made a decision, the members returned to the large room where they had been originally. After explaining that they would not return to their groups, everyone was asked to make the decision again as an individual. Finally, they were thanked and debriefed. Dependent variables Two variables were measured in this experiment. First, participants were asked to choose one of the two drugs. Then, the confidence in the decision was measured with a 7-point rating scale from 1 = completely confident to 7 = completely unconfident.

Results Decision Table 2 shows the distribution of groups’ choices in the two conditions: initial

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decision and no initial decision. Contrary to the ‘commitment to initial decision’ hypothesis, the interaction between choice and condition was not significant (2(1, 32) = 0.62, p = .43). The hidden profile was rarely uncovered in either condition. Drug 2, the inferior alternative, was preferred over drug 1 both if the group members were asked to make an initial decision (2(1, 18) = 8.00, p < .001) and if they were not (2(1, 14) = 10.29, p < .001), resulting in an overall preference of the whole sample for drug 2(2(1, 32) = 11.80, p < .001). Of the 42 individuals assigned to the initial decision condition, 36 chose the inferior drug (drug 2) at the first individual decision and confirmed their choice at the second group decision, which gave a nonsignificant McNemar test for matched pairs (p = 1.00). Of the remaining six individuals, three switched from the superior drug (drug 1) to the inferior drug (drug 2), one stayed with the superior choice, and only two individuals switched to the superior alternative. Confidence in choice A marginally significant difference was found in the degree of decision confidence between the groups. Those that were asked to make an initial decision were marginally more confident (M = 5.71, SD = 0.61) than those who were not asked (M = 5.11, SD = 1.18) (t(26,6) = –1.87, d = 0.64, p = .07). Also, groups that chose drug 1 were marginally less confident (M = 4.25, SD = 0.96) than those who chose drug 2 (M = 5.53, SD = 0.92) (t(3,8) = –2.52, d = 1.37, p = .07).

Discussion Results from the groups’ decisions in Experiment 1 found no support for the commitment Table 2. Distribution of group decisions in the two conditions of experiment 1 Condition Drug 1 Drug 2

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No initial decision (one decision)

Initial decision (two decisions)

3 (16.7%) 15 (83.3%) n = 18

1 (7.1%) 4 13 (92.9%) 28 n = 14 n = 32

to initial decision hypothesis. Groups in which members were not asked to make an initial decision before meeting in the group were not significantly more likely to uncover the hidden profile. However, groups that made an initial decision were slightly more confident. All but one group in the initial decision condition picked drug 2, supporting the drug the majority of group members had picked before they entered the group. This consistency between individuals’ decision and the groups’ decision may have resulted in the groups having marginally higher confidence in the initial decision condition than the no initial decision condition. Although group members may have entered the discussion with tendencies toward drug 2 in the no initial decision condition, they were not asked to commit to a particular drug. Therefore, although the group discussion may have confirmed their original feelings about drug 2, there may have been less of a feeling of consistency between their individual choice and the group choice or there may have been less of a feeling of strong group consensus. Research has found that consensus in a group increases confidence about the choice ( Julian, Regula, & Hollander, 1968; Sniezek, 1992). However, the confidence results were only marginally significant, and how committed participants in the no initial decision condition were to drug 2 before entering the group discussion and how much stronger group consensus was cannot be known. There are several explanations for the null results for the commitment to initial decision hypothesis. First, whether or not participants make an initial decision before the group discussion may not significantly affect the group’s ability to uncover a hidden profile. This would support Stasser’s (1988) computer simulation study. However, another explanation is that the commitment to initial decision hypothesis may be an accurate description of group processes, but Experiment 1 may not have been designed properly to test the hypothesis. First, participants in the no initial decision condition may have been making a judgment without instructions to do so. Hastie and Park (1986) make a distinction between memory-based judgment,


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in which a judgment is made from the recollection of facts from memor y, and on-line judgment, in which a judgment is made as one encounters the information. Woehr and Feldman (1993) found that judgment biases memory when participants are given instructions to make an on-line judgment. Similarly, we had hypothesized that instructing participants to make an on-line judgment may bias a group’s ability to uncover a hidden profile. However, Hastie and Park (1986) found that on some tasks participants make on-line judgments whether or not they are asked to do so. Specially, participants automatically made on-line judgments about gender and personality characteristics. It is likely that participants may have made on-line judgments in the no initial decision condition. Although not asked to make a judgment, participants received an information sheet labeled drug 1 and another labeled drug 2, and it may have been natural to compare the two drugs. To prevent participants from making comparisons, they could have been assigned a task to divert their attention from making judgments. For example, participants could have been asked to read the information for an upcoming recall task or to read and evaluate the grammatic structure of the sentences describing the information (Hastie & Park, 1986). Alternatively, group discussions could be analyzed to examine if participants are spontaneously making judgments in the no initial decision condition. Coders could determine how often and how early participants commit to a position in a group. If there are no differences between the conditions, then it is likely that participants in the no initial decision condition were making on-line judgments. Unfortunately, videotapes of group discussions are not available for Experiment 1, but future research may want to test this possibility. A second problem with the design of Experiment 1 is the amount of information for the group to process. Collectively, there were 60 pieces of information in the group, and each individual group member had received 36 pieces of information. Although groups were given up to 25 minutes to discuss the information, the large amount of information may


have overloaded the group and inhibited group discussion. Stasser and Titus (1987) found that increasing information load decreased group members’ recall of unique information not given to them before group discussion, suggesting that high information load reduces a group’s discussion and processing of unique information. Therefore, it is unlikely that groups in Experiment 1 were able to effectively process the large amount of information. Even if there was a tendency to discuss more unique information when group members were not asked to make an initial decision, the large amount of information may have made it too difficult to uncover the hidden profile. Future research may want to test the commitment to initial decision hypothesis under conditions of low information load. Future research also should videotape group discussions to examine the type of information that is discussed for groups that are asked and not asked to make an initial decision. Although groups not asked to make an initial decision were not more likely to uncover the hidden profile, they still could have mentioned more unique information. However, only tapes of the group discussion could test this. Other research could manipulate the publicness of the initial decision. Participants could be asked to make an anonymous, private decision that they do not have to announce to other group members, or they could be asked to make a public decision in front of their group members at the beginning of the group discussion. Deutsch and Gerard (1955) found that when presented with new information suggesting that their initial opinion was incorrect, participants were more likely to refuse to change their initial opinion when they had announced it publicly than when they had written it down anonymously. Further, participants who were not asked for an initial opinion at all were the most open to new information. In Experiment 1, participants were asked to make a private decision in the initial decision condition and were under no instructions to announce their decision to the group. Making the decision public could intensify the effects of advocacy and commitment to the decision and increase consensus pressures

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if the majority of group members announce that they support the same position. The low frequency of discovery of hidden profiles was nevertheless intriguing and raises the possibility that some other factor was simply strong enough to inhibit discovery. Experiment 2 was conducted to examine another factor that may inhibit the discovery of hidden profiles. Experiment 2 was designed to address two issues. The first was how the manipulation of the initial decision affects individuals working alone on a hidden profile task. This allows a second test of the commitment to initial decision hypothesis, but as an individual not a group process. The second goal is to examine another factor implicated in the failure to uncover hidden profiles, the repetition of information. Experiment 2 examines if the repetition of ‘common’ information decreases the likelihood of uncovering the hidden profile and increases recall of ‘common’ information.

Experiment 2 A second factor affecting groups’ inability to uncover hidden profiles is based on the ‘information reiteration’ effect. Research has found that groups tend to repeat common information more than unique information after it has been first mentioned in discussion (Larson, Christensen, Abbott, & Franz, 1996; Larson, Foster-Fishman, & Keys, 1994; Savadori et al., 2001; Stasser & Stewart, 1992; Stasser, Taylor, & Hanna, 1989; Stasser et al., 1995; Wittenbaum, 1998). We hypothesize that the redundancy of the common information prevents participants from uncovering hidden profiles. With hidden profiles common information is redundant because it is given to all group members, but unique information is nonredundant because it is given only to one group member. When common information is first mentioned in discussion it is a repetition for everyone. However, when a group member first mentions a piece of unique information, it is not a repetition for other group members. Also, once mentioned, common information tends to be repeated by group members more than unique information due to mutual enhance-

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ment and consensual validation (Postmes, Spears, & Cihangir, 2001; Wittenbaum, Hubbell, & Zuckerman, 1999). When common information is mentioned, it reinforces what the other group members know and gives them a sense of increased importance of their information since other members deem it worth mentioning. Because group members enjoy having their information validated by other group members, they react to the contributor of common information with encouragement and positive evaluations, enhancing the contributor’s appraisal of his or her task knowledge. This reinforcement from mutual enhancement that arises from contributing common information increases the tendency to repeat common information (Wittenbaum et al., 1999). Also, common information tends to support the initial decision of the majority of group members. Therefore, common information is repeated more to facilitate consensus (Postmes et al., 2001; Stasser & Stewart, 1992). The greater repetition of common information is likely to lead participants to view the common information as more true, valid, and reliable. In a study of individuals, Hasher, Goldstein, and Toppino (1977) demonstrated that repetition of information increases one’s belief and confidence that the information is true, valid and reliable; and this increase in belief strength occurs independently of the underlying truth of the information. Research has called this the ‘reiteration effect’ (Hertwig, Gigerenzer, & Hoffrage, 1997) or the ‘validity effect’ (H. L. Arkes, 1993; Boehm, 1994). In fact, when there are no hints as to whether a piece of information is true, people decide on its truthfulness based on the frequency with which they have encountered the piece of information. This process is relatively automatic, using few cognitive resources (Alba, Chromiak, Hasher, Attig, 1980; Hasher & Chromiak, 1977; Hasher & Zacks, 1984; Hasher et al., 1977). H. R. Arkes, Hackett, and Boehm (1989) hypothesized that one mechanism underlying the reiteration effect is familiarity. Repetition increases familiarity, and statements that are perceived as familiar are rated as more valid.


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H. R. Arkes, Boehm, and Xu (1991) found further support for familiarity underlying the ‘reiteration effect’. While they found an effect of familiarity on the perceived validity of a statement, they also found a direct effect of repetition on validity without the mediating variable of familiarity. However, Boehm (1994) found that if familiarity is statistically controlled, the effects of repetition are eliminated. Experiment 2 examines the effect of repetition. In this experiment, individuals were given certain pieces of information either three times or once, and the effect of repetition on their decision and their recall of information was examined. Experiment 2 investigates the role of individual-level processes in hidden profiles by simulating the distribution of information in a group within an individual task. The aim was to investigate two factors hypothesized to impede the uncovering of hidden profiles in group decision-making situations: a commitment to initial decision and the reiteration effect.

Method Participants and design Ninety-one undergraduate students from a large, public midwestern university participated in the experiment in exchange for class credit. The experimental design was 2 2: individual decision (one decision vs. two decisions) and reiteration of the information (no repetition of the ‘common’ information vs. ‘common’ information repeated three times). Both factors were between-subjects. The design is shown in Table 3 and distribution of information is shown in Table 1.


Task and procedure Participants were given the same medical information about cholesterol as in Experiment 1, followed by information about the two drugs. The superior alternative was drug 1 and the inferior alternative was drug 2, and most of the common information favored drug 2 and most of the unique information favored drug 1. Participants received the 24 pieces of information that were ‘common’ in Experiment 1 and the 36 pieces of information that were ‘unique’. In all conditions, participants received all 60 pieces of information. In the one decision, no repetition condition, participants received a list of information about drug 1 and another list for drug 2. Common and unique information was mixed randomly together and was not identified to participants as such. Order of presentation of information was counterbalanced. After reading the information, participants were asked to pick a drug and rate their confidence. In the repetition conditions, participants received three profiles of information. Each profile contained the 24 pieces of common information and 12 of the 36 pieces of unique information. The three profiles of information were the same profiles that group members received in Experiment 1 before they met in the group. Each profile had a sheet of information for drug 1 and another sheet for drug 2. Again, common and unique information was mixed together randomly and was not identified to participants as common or unique. Order of presentation of the profiles was counterbalanced. In the two decision, repetition condition, participants received one of

Table 3. The information given in each condition of experiment 2 Two decisions

No repetition

Repetition

One decision

First decision

24 Common pieces 36 Unique pieces [N = 23]

24 Common 12 Unique

24 Common (3) 36 Unique (1) [N = 23]

24 Common 12 Unique

Second decision 24 unique [N = 24] 24common (2) 24 unique (1) [N = 21]

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the three profiles and made an initial decision, and then they received the other two profiles of information and made a final decision. In the one decision, repetition condition, participants received the three profiles at once and made one decision. Finally, in the two decision, no repetition condition, participants received the 24 pieces of common information mixed randomly with 12 pieces of unique information and were asked to make a decision after reading through the information. This would be the same type of profile received by the participant before the first decision in the two decision, repetition condition. After the initial decision, participants received the remaining 24 pieces of unique information and made a final decision. The presentation of the unique information was counterbalanced, so that no set of 12 pieces of unique information was always presented first. Table 3 shows the order in which participants were given information for each condition. After making their decision(s), participants filled out a free recall task and were then thanked and debriefed. The free recall task asked participants, ‘Now try to consider all the information you were given. List all the information you can remember in the order it arises in your mind and indicate with a number (1 or 2) to which drug it refers’. Dependent variables Participants’ drug choice and confidence were measured as they were in Experiment 1. Also, participants’ free recall was coded into several categories. Two independent coders, who were unaware of the hypotheses, coded the free recall. Coders were given a list with all the pieces of information used in the task, along with information about what drug the piece of information described, whether the information was positive, negative, or neutral toward the drug, and whether the information was common or unique. Coders were instructed to code each piece of recalled information according to what drug it described, its valence (positive, negative, or neutral), and whether it was common or unique. An item-byitem comparison of the coded information across all the recall sheets revealed that the two

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coders agreed on average 87% of the time. Any discrepancies between the two coders were resolved by the first author of the paper.

Results Decision The individuals’ final decision (see Table 4) was analyzed in a 2 (decision: one or two decisions) 2 (information repetition: repeated or not repeated) 2 (drug choice: drug 1 or drug 2) log linear model. The best fitting model was the drug choice by information repetition model (G 2 = 4.63, df = 4, p = .32), which confirms the hypothesis that the superior alternative (drug 1) was uncovered more often when there was no repetition of ‘common information’ (2(1, 91) = 12.11, p < .001). The drug choice by decision model had to be rejected (G 2 = 16.19, df = 4, p = .003), confirmed also by the nonsignificant interaction effect (2(1, 91) = 0.62, p = .43). This suggests that the initial decision did not affect the results. When the full saturated model was tested, the interaction between decision information repetition drug choice gave a marginally significant effect (2(1, 91) = 3.60, p = .058), suggesting that the repetition effect is stronger, although not reaching significance, in the two decision condition. Focusing on the two decision condition, we analyzed the frequency of participants who switched to the superior drug on the second decision when ‘common information’ was or was not repeated. The McNemar’s test for matched pairs (before and after the manipulation) indicated that the probability of switching to the superior drug was significant in the no repetition condition (p < .0001) (see Table 5(a)), but there was no significant difference between the first and second decision in the repetition condition (see Table 5(b)). Most of the participants (n = 14) switched to the superior drug when common information was not repeated, while most participants stayed with their previous inferior decision (n = 16) when common information was repeated. These later numbers are comparable to those found in the first experiment for individuals making two decisions, with the last decision in a group setting. This lends support to the reiteration


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Table 4. Frequencies of choices in the four conditions Two decisions (N = 45)

One and final decision (N = 46)

Initial decision*

Final decision

Totals *

No repetition of common information Drug 1 Drug 2

12 (52.2%) 11 (47.8%)

5 (20.8%) 19 (79.2%)

19 (79.2%) 5 (20.8%)

31 (66.0%) 16 (34.0%)

Repetition of common information Drug 1 Drug 2

8 (34.8%) 15 (65.2%)

2 (9.5%) 19 (90.5%)

5 (23.8%) 16 (76.2%)

13 (29.5%) 31 (70.5%)

* In the initial decision condition, the distinction between ‘no repetition’ and ‘repetition’ of information is just nominal, since the repetition of common information is done after the initial decision. The initial decision data are reported to allow a before–after the manipulation comparison. For this reason ‘Totals’ do not include the initial decision condition. Table 5. Frequency of choices at the first and second decision when common information was not repeated (a) and when it was repeated (b) (a)

Initial Decision

Final decision

Drug 1 Drug 2

Drug 1

Drug 2

5 14

0 5

hypothesis, that uncovering a hidden profile is more difficult when common information is repeated. Confidence A 2 (decision) 2 (repetition) analysis of variance (ANOVA) on the perceived confidence in the individuals’ decisions found no significant effect of either factor (all F s < 1), nor interaction (F(1,87) = 1.38, 2 = 0.16, p = .24). Individuals’ mean confidence was 5.08 (SD = 1.11). In the two decision condition, confidence judgments did not change between the first and the second decision, as shown by the nonsignificant F values of a 2 (repetition) 2 (decision time: first or second decision) ANOVA with repeated measures on the last factor. Neither repetition (F(1,43) = 1.08, 2 = 0.02, p = .31), nor the decision time (F(1,43) = 2.34, 2 = 0.05, p = .13), nor the interaction of these factors was significant (F(1,43) = 0.06, 2 = 0.01, p = .80).

(b)

Initial Decision

Final decision

Drug 1 Drug 2

Drug 1

Drug 2

2 3

0 16

Recall Information recalled after the final decision was divided into ‘unique’ information (given only once) and ‘common’ information (repeated three times in repetition condition). Because different amounts of common and unique information were given to participants, the recall data were analyzed in proportions. Proportions were computed by dividing the amount of unique information by 36 and the amount of common information by 24. The two types of information were analyzed in a 2 (decision: one or two decisions) 2 (repetition or no repetition) 2 (information type: unique or common) ANOVA with the last factor within-participants. The repetition factor interacted significantly with information type (F(1,82) = 92.29, 2 = 0.53, p < .0001). This interaction was further analyzed through oneway ANOVAs and paired samples t tests. Analyses showed that a larger proportion of common information (M = 0.41, SD = 0.17) was

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recalled than unique information (M = 0.22, SD = 0.12) in the repetition condition (t(38) = –8.41, d = 1.29, p < .0001); but a larger proportion of unique information (M = 0.30, SD = 0.12) was recalled than common information (M = 0.23, SD = 0.14) in the no repetition condition (t(46) = 4.04, d = 0.54, p < .0001). Also, more common information was recalled in the repetition condition than the no repetition condition (F(1,84) = 28.92, 2 = 0.26, p < .0001), and more unique information was recalled in the no repetition condition than the repetition condition (F(1,84) = 10.55, 2 = 0.11, p < .005). Nothing else was significant. Interestingly, those in the repetition condition did not recall more information than those in the nonrepetition condition (F(1,82) = 0.54, 2 = 0.01, p = .46) (M = 16.95 items recalled, SD = 7.10), but their recall differed significantly in the type of information recalled. Overall, those in the repetition condition were more likely to recall the information that was repeated (‘common’ information), but those in the nonrepetition condition were more likely to recall ‘unique’ information, which tended to support drug 1.

Discussion Experiment 2 found that repetition of ‘common’ information in a hidden profile reduced participants’ ability to uncover the hidden profile. However, Experiment 2 found no support for the commitment to initial decision hypothesis. In fact, without repetition participants were quite willing to change their decision after encountering more information supporting drug 1. Also, recall data confirmed that participants in the repetition condition were more likely to process and recall the repeated ‘common’ information, which favored drug 2. Finally, the confidence data did not support Hertwig et al’s. (1997) proposition that repetition increases one’s confidence. Overall, repetition of the common information diminished individuals’ ability to uncover the hidden profiles. However, the factor mediating between repetition of common information and the reduction in uncovering hidden profiles is unclear from the results of Experiment 2. In line with

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the reiteration or validity effect, repeated information may be perceived as more valid, and therefore, given more weight in the decision process. This would support extensive previous research on the effects of repetition (H. L. Arkes, 1993; Boehm, 1994; Hertwig et al., 1997). However, repetition of information is confounded with cognitive load. Therefore, it may be the increased cognitive load caused by the repeated information that diminished participants’ performance in the repetition condition. Participants in the repetition condition had an additional 48 pieces of information to read. Although this information was not new, it may have increased their load and distracted participants from being able to effectively process the new, unique information they were given. In fact, recall results support this. With the repetition of common information, participants recalled more common information, at the expense of unique information. Similarly, Stasser and Titus (1987) found that increasing the amount of information a group has to discuss in a hidden profile reduced group members’ ability to process new, unique information. However, Stasser and Titus manipulated cognitive load by giving a group more new information, not repeating the old common information. Nevertheless, a similar effect of cognitive load may be at work in both experiments. Whether or not repetition of already encountered information increases cognitive load should be studied in future research. Contrary to previous research with reiteration (Hertwig et al., 1997), participants’ confidence in their decision did not increase with the repetition of common information. If cognitive load is partially responsible for the diminished performance due to repetition, it may offer an explanation for the confidence results. Participants in the repetition condition may have been aware that they were unable to process the large amount of information they were given. This perception of increased load may have prevented them from feeling more confident when they were presented with repeated information. However, future research should try to disentangle the effects of repetition from cognitive load.


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Experiment 2 lacked the consensual validation and mutual enhancement (Clark & Stephenson, 1989; Postmes et al., 2001; Wittenbaum & Stasser, 1996; Wittenbaum et al., 1999) that often comes with repetition of information in a group discussion. It also lacked conformity pressures that may be implied in group discussion when common information favoring one alternative is repeated more in discussion or when there are group norms toward consensus that lead groups to favor common information (Postmes et al., 2001). Also, repetition of information may be more powerful when it is attributed to several human sources (H. R. Arkes et al., 1991) rather than just one source, as Experiment 2 used. Therefore, because a group discussion has social dynamics like consensual validation, mutual enhancement, group norms, conformity, and several sources of information, the effect of repetition by group members may be stronger than the effect obtained in this experiment using individuals reading information off a sheet of paper. Experiment 2 did not test whether or not repeated information was perceived as more valid, as would be predicted by the reiteration or validity effect. Also, Experiment 2 used individuals to investigate how individual level cognitive processes affect the ability to uncover hidden profiles. Experiment 2 was able to strictly control whether information was repeated because information was presented in written format to individuals. However, Experiment 3 was designed to extend research on repetition to a group situation. Whether or not information is repeated cannot be controlled in a natural group discussion; therefore, repetition is not controlled in Experiment 3. Also, unlike Experiment 2 participants rate the validity of information in Experiment 3.

Experiment 3 Although Experiment 2 found that individuals were less likely to uncover the hidden profile when ‘common’ information was repeated, the experiment offered few data to explain why repetition of ‘common’ information had this


effect. Research has found (Hasher et al., 1977; Hertwig et al., 1997) that simple repetition increases the validity of information with individuals. However, there are no comparable data that test if information repeated in group discussion increases in validity. Experiment 3 was conducted to test the reiteration hypothesis in groups. That is, we seek to determine if common information is perceived as more truthful than unique information following group discussion. Experiment 3 follows a similar procedure as Experiment 1, except that after meeting as a group, participants were asked to assess the truthfulness and familiarity of the information. It is expected that common information will be rated as more truthful than unique information. Although repetition of common information was not manipulated or measured in Experiment 3, based on overwhelming evidence from previous research that measured repetition of common and unique information in group discussion, it will be assumed that groups repeated more common than unique information (Larson et al., 1994, 1996; Savadori et al., 2001; Stasser & Stewart, 1992; Stasser et al., 1989, 1995; Wittenbaum, 1998). Experiment 3 also distinguishes between unique information the individual was given before group discussion (unique owned) and unique information that was given to other group members that may or may not have been discussed during the group discussion (unique not owned). Chernyshenko, Miner, Baumann, and Sniezek (2003) found a difference in how participants viewed unique information that was discussed depending on whether it was owned by the participants before group discussion or whether is was received from other group members during discussion. Unique owned information that was discussed was rated as more important than unique information added by other group members. Therefore, a difference between how common and unique information is perceived may be due to the fact that common information is completely owned by the participant before group discussion, whereas only part of the unique information is owned.

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This ownership bias that participants have for their own information underlies the effects of mutual enhancement. Because participants have an ownership bias toward their information, they react positively toward another group member who mentions their information and negatively toward another group member who mentions information that is unknown to them (Wittenbaum et al., 1999). As previously discussed, this positive reinforcement and mutual enhancement leads group members to repeat more common information than unique information. Experiment 3 splits unique information into unique owned and unique not owned to account for the ownership bias. If we find that common information is rated as more valid than both unique owned and unique not owned, this will support the reiteration hypothesis. However, if we find that common information is rated as valid as unique owned information, then the results will support the ownership hypothesis. In line with the reiteration effect, we predict that common information will be rated as most valid, followed by unique owned, then unique not owned, and the control information will be rated as the least valid. Because perceptions of validity have been found to be partially mediated by familiarity, we predict the same results for ratings of familiarity.

Method Participants Sixty undergraduates at a large, public midwestern university participated in the experiment in partial fulfillment of course credit. They were divided into 20 three-person groups. Decision task A shortened form of the decision task used in Experiments 1 and 2 was used in this experiment to accelerate experimental procedures to ensure that participants had time to complete the ratings within the experimental hour. There were 40 pieces of information. Each individual was given 11 pieces of common information (8 positive and 3 neutral) and 3 pieces of unique information (2 negative and 1 positive) for drug 1 and 11

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pieces of common information (8 negative and 3 neutral) and 3 of unique information (1 negative and 2 positive) for drug 2. The task was not meant to be a hidden profile; therefore, there was not a superior alternative. Negative and positive information was distributed equally within common (8 positive and 8 negative pieces) and unique (9 positive and 9 negative pieces) information. The control information (see next section for definition) included 10 pieces of information, 5 describing drug 1 and 5 describing drug 2. Procedure Participants met in a large room and received the same preliminary instructions describing the general research topic and booklet of experimental materials as in Experiment 1. After reading the materials and their information, participants were asked to make an individual decision before meeting in the group. Next, participants were put into threeperson groups and moved to separate rooms to discuss the information and make a group decision. The same procedure as in Experiment 1 was followed for the groups. After making a group decision, individuals were brought back into the large room. They were asked to make a decision again as an individual. Next, they were given a questionnaire that asked them to rate the pieces of information for validity on a 7-point scale from definitely true (1) to definitely false (7) and rate the information for familiarity on a 7-point scale from definitely have seen this item before (1) to definitely have NOT seen this item before (7). To assess that participants were attentively filling out the questionnaire, 10 control items were added that were not in any individual members’ original information. These distractor items were similar in content to the other items, but they just contained ‘new’ information. This was a manipulation check to ensure that participants had not simply randomly circled responses on the questionnaire. It also provided a baseline for comparing ratings. The order of information (n = 50) in the rating questionnaire was randomized and counterbalanced to prevent order effects. Afterwards, participants were thanked and debriefed.


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Results Validity A repeated measures ANOVA with one factor ‘type of information’ at four levels was computed on the validity judgments of common information, unique owned information, unique not owned information, and control information. The within-factor was significant (F(3,177) = 412.24, 2 = 0.88, p < .0001). Simple contrasts were used to test our hypotheses. Contrary to the reiteration hypothesis, unique owned information (M = 1.59, SD = 0.61) was judged as true as common information (M = 1.58, SD = 0.49) (F(1,59) = 0.00, 2 = 0.00, p = .96). Unique information not owned (M = 3.64, SD = 0.70) was judged less true than common information (M = 1.58, SD = 0.49) (F(1,59) = 576.87, 2 = 0.91, p < .0001). Also, unique information owned was judged more true than unique information not owned (F(1,59) = 575.61, 2 = 0.91, p < .0001). Unique not owned information was judged more true (M = 3.64, SD = 0.70) than control information (M = 3.83, SD = 0.71) (F(1,59) = 5.50, 2 = 0.85, p < .05), confirming that unique not owned information was not confused with false information. Due to dependence among group members the same analysis was conducted at the group level. A repeated measures ANOVA with one factor (type of information: common vs. unique vs. control) was computed on the perceived validity. The factor was significant (F(2,38) = 432.19, 2 = 0.96, p < .0001). Contrasts found that common information (M = 1.58, SD = 0.30) was perceived more true than unique information (M = 2.96, SD = 0.36) (F(1,19) = 432.60; 2 = 0.96, p < .0001); and unique information was perceived more true than control information (M = 3.83, SD = 0.44) (F(1,19) = 431.98, 2 = 0.86, p < .0001). Familiarity A repeated measures ANOVA with one within-factor ‘type of information’ at four levels was computed on the familiarity ratings. The ‘type of information’ factor was significant across levels (F(3,177) = 551.69, 2 = 0.90, p < .0001). Simple contrasts confirmed that common information (M = 1.65, SD = 0.47) was judged more familiar than unique information


not owned (M = 5.72, SD = 0.93) (F(1,59) = 812.25, 2 = 0.93, p < .0001), but similar to the validity judgments, common information was judged as familiar as unique owned information (M = 1.69, SD = 0.77) (F(1,59) = 0.12, 2 = 0.00, p = .73). Interestingly, unique not owned information was judged to be as unfamiliar as the control items of information (M = 5.59, SD = 0.93) (F(1,59) = 1.88, 2 = 0.03, p = .18). The same analysis was conducted at the group level. A repeated measures ANOVA with one factor (type of information: common vs. unique vs. control) was computed on perceived familiarity. The factor was significant (F(2,38) = 500.27, 2 = 0.96, p < .0001). Contrasts showed that common information was perceived as more familiar (M = 1.65, SD = 0.29) than unique information (M = 4.37, SD = 0.42) (F(1,19) = 611.87, 2 = 0.97, p < .0001); and unique information was perceived as more familiar than control information (M = 5.59, SD = 0.57) (F(1,19) = 133.49, 2 = 0.87, p < .0001).

Discussion This experiment was designed to test whether common information is judged as more valid and more familiar than unique information. We hypothesized that common information would be rated as more valid and familiar because common information tends to be repeated more in discussion. However, the results did not support this conclusion. Participants rated common information as valid as the unique information they had been given before the group discussion. These results suggest that ownership of information is more important in affecting how participants view information. This supports previous research by Chernyshenko et al. (2003) that found that participants rated unique owned information that had been discussed as important as common information. One reason common information was not rated as more valid than unique owned information may have been that the group size was too small to repeat common information a significant number of times. Chernyshenko et al. (2003) predicted that as a group’s size increases common information is

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seen as more important because increased social validation and mutual enhancement lead to more repetition of the common information. With a larger group, more members will react positively to the common information and negatively to unique information that is mentioned in discussion. Thus, mutual enhancement should increase with group size. Chernyshenko et al. (2003) predicted that in a three-person group unique owned information that is discussed would be judged as important as common information because the lack of agreement about the unique information among members is smaller and there is less social validation of common information. Although we did not measure importance of information, our results with three-person groups for validity and familiarity of information were in line with their predictions. With a three-person group, common information may not be validated and repeated enough to set it apart from one’s own unique information. However, in a larger group where more group members may repeat and validate common information, the reiteration effect may have more impact on how information is rated. Therefore, both ownership of information and repetition of information may contribute to how valid a piece of information is perceived to be. In future, experiments may test for the reiteration effect in a larger group of five members. Other future research should record group discussions and assess if information that is repeated the most is rated as the most valid. Experiment 3 assumed that common information was repeated more based on results of past research. This is a weakness because it could not be measured if common information was repeated significantly more than unique information. A more precise experiment should correlate amount of repetition in group discussion with ratings of validity for each piece of information. Unique information should be divided into whether or not it was discussed in group discussion to identify whether other group members had access to that information during group discussion. Experiment 3 did not distinguish between whether a piece of unique

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not owned information was discussed or not discussed, and this reduced the precision of the experimental results. An even more ambitious study could use confederates in group discussion and manipulate whether or not the confederates repeat more common or unique information. The effect of repetition of common or unique information in a hidden profile task on the participants’ post-group decision could then be assessed. Also, the effect of ownership of information in group discussion needs more research. Chernyshenko et al. (2003) was one of the first studies to split unique information according to its ownership, and more studies, especially with group sizes larger than three, are needed to confirm these results.

General discussion and conclusions Stasser (1988, p. 401) wrote that, ‘the reason why groups are not able to uncover hidden profiles is because unique information tends to be omitted from discussion’. Research on information sampling in groups attributed the inability of groups to uncover hidden profiles to groups’ lack of thorough discussion of the unique information that could enable the group to discover the superior alternative. According to this, the relevant literature on information sampling in groups attempted to create the conditions to increase the unique information discussed in groups (Hollingshead, 1996a, 1996b; Stasser & Stewart, 1992; Stasser et al., 1995; Stewart, Billings, & Stasser, 1998). This paper examined three factors that may affect a group’s ability to uncover a hidden profile: initial decision, repetition, and ownership of information. Experiments 1 and 2 found no support for the ‘commitment to an initial decision’ hypothesis in groups’ and individuals’ decisions. Experiment 1 found that groups in which members were not asked to make a pre-discussion decision were not significantly more likely to uncover hidden profiles. However, participants could have made a decision without being asked, and Experiment 1 is unable to test whether or not participants


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did so. Research on on-line memory (Hastie & Park, 1986) does find that people often do make spontaneous judgments. Experiment 2 found that participants were quite able to change from their first decision when given more information, suggesting the participants do not always anchor on their first decision and can integrate new information. Experiment 2 found that even if individuals were given all the information, repetition of the common information significantly reduced participants’ ability to uncover hidden profiles. Repetition of the common information may increase its validity to participants, and therefore, increase its importance in the decision. This would support previous research with the reiteration effect. However, an alternative explanation is that repetition of information increases cognitive load and reduces the ability of participants to process the new, unique information needed to improve decision making. Regardless of the mediating process, the repetition of the common information can be potentially sufficient to mask the superior alternative. A key factor therefore is not having access to all the information, but the fact that common information has a higher chance to be redundant. Experiment 3 examined if common information, which tends to be repeated more, is perceived as more valid and familiar than unique information. However, Experiment 3 found that participants rated information they had been given (both common and unique) as more valid than information other group members had been given. Ownership of information was the determining factor in how valid participants perceived information. Therefore, the low quality decisions of groups are not attributable only to group interaction or social dynamic variables, such as conformity pressures, mutual enhancement, group norms, or cohesion, but also to cognitive factors that affect how information is coded. Increased judgments of validity for repeated information is an automatic, cognitive response (Alba et al., 1980; Hasher & Chromiak, 1977; Hasher et al., 1977; Hasher & Zacks, 1984). Also, increased judgments of validity for some-


thing one has been given over something another has been given is a common finding (Alicke, Klotz, Breitenbecher, Yurak, & Vredenburg, 1995; Kahneman, Knetsch, & Thaler, 1991). However, ownership of information and repetition of information interact with and are created by social dynamic variables. The ownership bias underlies participants’ preference for hearing others mention common information and the resulting process of mutual enhancement. In turn, the positive reinforcement of mutual enhancement increases the repetition of common information during group discussion. This increased repetition may then increase participants’ ratings of validity for the repeated information. Individuals’ cognitive judgments of information and group dynamic variables are intertwined. To uncover hidden profiles it is not sufficient that group members share all the relevant information, but it is necessary that individuals avoid repeating common information and overcome their ownership bias. In other words, it is not sufficient for unique information to be mentioned once. Vinokur and Burnstein (1974) thought that already known information would have little impact when it was mentioned during discussion because everyone already knew it and that new, unshared information brought up by another group member would be the most persuasive and have the biggest impact on people’s judgments and decisions. However, Vinokur and Burnstein (1974) underestimated the impact of the repetition and ownership of information. One way to increase a group’s focus on unique information is to try to instill group norms to overcome the ownership bias. A group norm favoring new information could try to be instilled in the group. Similarly, group members could be trained to react positively to unique information when it is mentioned so that unique information is positively reinforced. If other group members react positively when a group member contributes a piece of his or her unique information, this may lead to more repetition of unique information among group members. When looking for explanations for the

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common information bias, individual and group level processes need to be distinguished, although both contribute to the bias. This study examined how individuals may weigh information differently when it is repeated or owned and how this might affect groups’ inability to uncover hidden profiles. Other factors at the group level that we did not address also help explain a group’s susceptibility to the common information bias and may magnify any individual processes. For example, any individual bias toward weighting repeated information more than unrepeated information is likely to be magnified when the repeated information is also socially validated by other group members or mutually enhanced by nonverbal behavior or when the individual feels pressure to agree to the common information because other group members are discussing it. Considering that individual and group level processes reinforce each other in the discussion of common information, helping groups focus more on unique information poses a great challenge to researchers and practitioners. In conclusion, group discussion is a complicated process and many factors at both the group level and individual level affect how information is discussed and viewed by group members. This paper examined three factors that may affect group discussion and decision making: repetition of information, ownership of information, and commitment to an initial decision. In Experiment 2 repetition of common information was found to reduce individuals’ ability to discover hidden profiles, and in Experiment 3 ownership of information increased participants’ judgments of the information’s validity. How these two factors interact with other factors to impede the discovery of hidden profiles provides a fruitful area for future research.

Acknowledgments Special thanks to Jason Cordini, Patrick Wadlington, Jonathan Ronk, Beth Gottfried, Robert Klimek, Cara Ludutsky, and Vivian Dzokoto for assistance with data collection. Part of this paper was presented as a

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poster at the Judgment and Decision-Making conference in Dallas, Texas (November, 1998).

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Biographical notes received her PhD at University of Illinois at Urbana-Champaign in the Department

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of Psychology in the Personality-SocialOrganizational division. She is currently an Assistant Professor in the Department of Communication Studies at Northwestern University. Her research interests include information sharing in groups, trust in the communication of reputation and advice, trust in on-line auctions, and non-verbal imitation in groups. Her work has been published in Organizational Behavior and Human Decision Processes and Communication Research. received her PhD in social psychology from the University of Padua, Italy in 1999. Currently, she is a research scientist at the Cognitive Science Laboratory of the University of Trento, Italy. Her research interests include information sharing in groups, reasoning and decision making, and risk perception.

L U C I A S AVA D O R I

received her PhD from Purdue University. She is an Associate Professor in the University of Illinois at Urbana-Champaign in the Department of Psychology in the PersonalitySocial-Organizational division. Her research interests include judgment and choice: relation between accuracy and confidence, influences on subjective uncertainty, the connections among choice and behavior. Judgmental forecasting: comparisons of techniques for prediction, estimation of future performance, social influences on forecasting. Social decision systems: judgment and choice processes of multiple persons, the role of advice, especially in organizations.

JANET SNIEZEK