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Psychol Bull. Author manuscript; available in PMC 2016 Mar 18.
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PMCID: PMC4797953
NIHMSID: NIHMS454608
PMID: 19586162

Feeling Validated Versus Being Correct:A Meta-Analysis of Selective Exposure to Information

Abstract

A meta-analysis assessed whether exposure to information is guided by defense or accuracy motives. The studies examined information preferences in relation to attitudes, beliefs, and behaviors in situations that provided choices between congenial information, which supported participants' pre-existing attitudes, beliefs, or behaviors, and uncongenial information, which challenged these tendencies. Analyses indicated a moderate preference for congenial over uncongenial information (d. = 0.36). As predicted, this congeniality bias was moderated by variables that affect the strength of participants' defense motivation and accuracy motivation. In support of the importance of defense motivation, the congeniality bias was weaker when participants' attitudes, beliefs, or behaviors were supported prior to information selection, when participants' attitudes, beliefs, or behaviors were not relevant to their values or not held with conviction, when the available information was low in quality, when participants' closed-mindedness was low, and when their confidence in the attitude, belief, or behavior was high. In support of the importance of accuracy motivation, an uncongeniality bias emerged when uncongenial information was relevant to accomplishing a current goal.

The availability of diverse information in an environment does not guarantee that a person's views will be equally diverse. Former United States vice-president Dick Cheney, for example, reportedly requires the television set be tuned into a conservative news channel before he enters a hotel room (The Smoking Gun, 2006). Individuals strongly committed to certain religions often avoid contact with information or people that can tempt them away from their doctrine. For example, science teachers at a public school in Arkansas were prevented from discussing evolution after complaints from religious parents, teachers, and faculty (Wiles, 2006). But what is the extent of people's inclination to receive congenial information? Is there a predominance of exposure to information that confirms pre-existing views? And, if there is such a bias, is it mitigated by factors that highlight the benefits of reaching accurate conclusions? Research on information exposure, which is synthesized in this paper, can answer these questions.

Although recent research has carefully analyzed the role of motivated reasoning in creating positive illusions (e.g., Kunda, 1990; Molden & Higgins, 2005), processes that allow access to the truth are just as important. Receiving information that supports one's position on an issue allows people to conclude that their views are correct but may often obscure reality. In contrast, receiving information that contradicts one's view on an issue can make people feel misled or ignorant but may allow access to a valid representation of reality. Therefore, understanding how people strive to feel validated versus to be correct is critical to explicate how they select information about an issue when several alternatives are present. A meta-analysis of field and laboratory studies on information exposure was conducted to shed light on these issues.

The classic assumption in selective exposure research is that people are motivated to defend their attitudes, beliefs, and behaviors from challenges (e.g., Festinger, 1957; Olson & Stone, 2005). In attitude theory (e.g., Albarracín, Johnson, & Zanna, 2005; Eagly & Chaiken, 1993; Zanna & Rempel, 1988), attitude is defined as the individual's evaluation of an entity (an issue, person, event, object, or behavior; e.g., President Obama); belief as an association between an entity and an attribute or outcome (e.g., President Obama is honest); and behavior as an overt action performed in relation to an entity (e.g., voting for President Obama). Selective exposure enables people to defend their attitudes, beliefs, and behaviors by avoiding information likely to challenge them and seeking information likely to support them. Selectivity of this type has often been called a congeniality bias (e.g., Eagly & Chaiken, 1993, 1998, 2005), but has also been called a confirmation bias (e.g., Jonas, Schulz-Hardt, Frey, & Thelen, 2001). In this paper, we will use the term congeniality bias.

Although the idea that selective exposure typically takes the form of a congeniality bias has a history extending back to William James (1890) and even to Francis Bacon (1620/1960), the topic first attained prominence among social psychologists in the context of Festinger's (1957, 1964) theory of cognitive dissonance. According to dissonance theory, after people commit to an attitude, belief, or decision, they gather supportive information and neglect unsupportive information to avoid or eliminate the unpleasant state of post decisional conflict known as cognitive dissonance. Typically researchers have tested this congeniality principle in a laboratory paradigm in which participants select information from alternatives. Prior to this selection, participants make a decision (e.g., about the guilt of a defendant in a mock trial), form an attitude (e.g., toward a work of art), report an existing attitude (e.g., on abortion), or report a prior behavior (e.g., whether they have smoked). Then participants are given an opportunity to receive information about the same issue (e.g., abortion, smoking) from a list of options usually presented as titles or abstracts of available articles. Typically half of these options support the participant's attitude, belief, or behavior, and the other half contradict it. The researcher records the numbers of chosen articles that agree or disagree with each participant's attitude, belief, or behavior. Selection of more articles that agree and fewer that disagree indicates a congeniality bias. Selection of more articles that disagree and fewer that agree indicates an uncongeniality bias.

In one of the initial studies testing selective exposure (Adams, 1961), mothers reported their belief that child development was predominantly influenced by genetic or environmental factors and then could choose to hear a speech that advocated either position. Consistent with the congeniality principle, mothers overwhelmingly chose the speech that favored their view on the issue. More recent investigations have used more complex designs to identify the moderators of the congeniality principle. For example, in a study showing that people select more uncongenial information when it is viewed as easy to refute, participants were offered congenial and uncongenial information attributed to either expert or novice sources (Lowin, 1969). Moreover, many studies have included manipulations to study the effects of perceiving that a previously reported decision could be altered (Frey & Rosch, 1984; Lowe & Steiner, 1968) and of challenging initially-reported attitudes (Brodbeck, 1956; Frey, 1981b).

As the intensive study of moderators might suggest, Festinger's (1957) assumptions about selective exposure did not receive universal support. In fact, Freedman and Sears' (1965) narrative review revealed that selective exposure appears to be strong when people are exposed to information in natural settings because congenial information predominates in their environment (de facto selective exposure). In contrast, this review indicated that laboratory experiments in which people were free to choose the information were as likely to disconfirm as confirm the congeniality principle. However, in the mid-1980s, reviewers who took a fresh look at the available research concluded that considerable evidence supported Festinger's theory (Cotton, 1985; Frey, 1986). Specifically, these reviewers argued that selectivity in favor of attitudes, beliefs, and behaviors occurs more under some conditions than others, such as when people possess high (vs. low) commitment to their attitudes. Like Festinger (1957, 1964), they also maintained that a congeniality bias is not the only psychological principle regulating information selection. These additional principles, which need to be controlled in testing selective exposure, include preferences for information that is unfamiliar (e.g., Sears, 1965) and information that is useful for making decisions or performing upcoming tasks (e.g., Lowe & Steiner, 1968; for a discussion of these principles, see Wicklund & Brehm, 1976).

To date, only qualitative reviews have examined selective exposure research. Importantly, however, a meta-analysis is the best way to examine whether a congeniality bias exists, as well as its precise size and variability. Our meta-analysis corrects this omission and provides the most inclusive literature coverage to date. In the first available review, Freedman and Sears (1965) analyzed 14 research reports and found little support for the congeniality principle. In subsequent reviews, Cotton (1985) and Frey (1986) examined 29 and 34 research reports, respectively, and concluded that congeniality exists under a variety of circumstances consistent with dissonance theory. Although these past reviews were comprehensive, our meta-analysis includes 21 new research reports that have emerged since 1986. Given the additional research on this topic, it is important to re-examine the issue of selective exposure in light of the most recent evidence. Moreover, re-examining past conclusions is critical because many of the recent studies have assessed selective exposure using novel methods (e.g., Jonas, Greenberg, & Frey, 2003; Lundgren & Prislin, 1998). In conducting this reanalysis, we were also able to examine new moderators and estimate the contribution of motivational factors not examined in earlier reviews.

Given the acknowledged complexities of the determinants of selective exposure, we present a general framework, displayed in Figure 1, of the motivational forces that shape exposure decisions. These motivational forces and their empirical instantiations organize our meta-analysis of the direction, size, and variability of exposure biases. In this framework, information choices are meant to fulfill goals to defend attitudes, beliefs, and behaviors and to accurately appraise and represent reality (Chaiken, Liberman, & Eagly, 1989). By extending our analysis beyond the defense motivation principle central to cognitive dissonance theory (Cotton, 1985; Frey, 1986), we present a framework for understanding selective exposure that is broad enough to encompass most empirical findings. In addition to investigating whether defense and accuracy motivations guide selective exposure, our review furthers understanding by examining the relative strength of these motivations.

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The opposing motivations and their concrete instantiations influence exposure to congenial over uncongenial information (congeniality bias).

Defense and accuracy motives have proven to be popular in analyses of how people process attitude-relevant information (Chaiken, Wood, & Eagly, 1996; Eagly, Chen, Chaiken, & Shaw-Barnes, 1999; Johnson & Eagly, 1989; Prislin & Wood, 2005; Wyer & Albarracín, 2005). In one of the most prominent discussions of motivated information processing, Chaiken et al. (1989) distinguished between defense and accuracy motivation. Defense motivation is the desire to defend one's existing attitudes, beliefs, and behaviors; accuracy motivation is the desire to form accurate appraisals of stimuli. Although these theorists also proposed a third motive, impression motivation, the desire to form and maintain positive interpersonal relations, the research on this aspect of selective exposure does not offer sufficient evidence for a meta-analysis. Even though past research has varied the anonymity of attitudes and selection decisions, such manipulations are uninformative because the effect of anonymity on selective exposure should depend on characteristics of the audience that one intends to impress (Schlenker, 1980; e.g., the congeniality of the audience). In the absence of appropriate manipulations, our meta-analysis focused only on defense and accuracy motivations.

Defense Motivation

In dissonance theory, selective exposure to congenial information is a strategy to relieve or avoid cognitive dissonance, which is the discomfort arising from the heightened presence of dissonant cognitions (Festinger, 1957). This discomfort can arise from the mere presence of cognitive conflict (Beauvois & Joule, 1996; Harmon-Jones, 2000; Harmon-Jones et al., 1996) or from a self-threat, such as the perception one is poorly informed (Aronson, 1968; Greenwald & Ronis, 1978; Schlenker, 1980, 2003; Steele, 1988). Presumably, experiencing or anticipating cognitive dissonance motivates people to defend themselves by seeking more congenial than uncongenial information. Hence, factors that enhance the experience or anticipation of cognitive dissonance should strengthen defense motivation and in turn accentuate the congeniality bias.

Defense motivation should be stronger when people who just reported an attitude or belief, or engaged in a behavior, receive challenging (vs. supporting) information prior to information selection (Frey, 1986). If people encounter a challenge to recently expressed attitudes, beliefs, or behaviors, their effort to reduce the cognitive conflict may enhance the congeniality bias (Beauvois & Joule, 1996; Festinger, 1964). In one study (Frey, 1981b), participants made a decision about whether to extend the contract of a store manager. Afterwards, participants were asked to read congenial information, uncongenial information, both congenial and uncongenial information, or no information prior to selecting additional reading material. Results revealed that participants manifested an enhanced congeniality bias when they were asked to read uncongenial rather than congenial information prior to this selection.

Another consideration pertains to the quality of the information available for selection. Whereas the selection of high-quality uncongenial information has the potential to threaten individuals, the selection of low-quality uncongenial information does not. Hence, to the degree that defense motivation guides exposure decisions, the presence of apparently high-quality uncongenial information for selection may enhance the congeniality bias (i.e., people will be more likely to avoid such information). Correspondingly, whereas high-quality congenial information can potentially bolster one's pre-existing position, low-quality congenial information may threaten one's position. Hence, expectations of high-quality congenial information for selection may enhance selection of congenial information as a way of defending a prior view (Festinger, 1964). As a result, regardless of whether information supports or refutes one's own position, expecting high-quality information should enhance the congeniality bias, and expecting low-quality information should lessen it (Frey, 1986; Lowin, 1969).

Defense motivation is presumably also strengthened by individuals' commitment to the pre-existing attitude, belief, or behavior and by high relevance of the issue to enduring values. Personal commitment to an attitude, belief, or behavior is presumed to increase defense motivation because of the greater discomfort produced by holding an incorrect view on an important issue (Brehm & Cohen, 1962; Kiesler, 1971). Personal commitment is often conceptualized as feeling highly attached to a view (Kiesler, 1971) or contributing to feeling ownership for a view (i.e., belief possession; see Abelson, 1988). Several factors have been identified that might lead to commitment, such as sacrificing for the view (e.g., dedicating much time or effort to make a decision), freely choosing the view (e.g., forming an attitude without coercion) and explaining the view publicly or privately (e.g., defending a belief in a written essay; for reviews, see Olson & Stone, 2005; Harmon-Jones & Harmon-Jones, 2008). Accordingly, commitment has sometimes been assessed directly by having participants self-report their attachment or loyalty to a view (e.g., Jonas & Frey, 2003a). Moreover, commitment has also been manipulated by leading participants to (a) engage in a behavior under high or low choice conditions (e.g., Frey & Wicklund, 1978), (b) dedicate more or less time or effort to attitude-relevant behavior (e.g., Betsch, Haberstroh, Glöckner, Haar, & Fiedler, 2001), or (c) justify (e.g., Schwarz, Frey, & Kumpf, 1980) or anticipate having to justify their opinions to an audience (e.g., Canon, 1964; Lowin, 1969; Sears & Freedman, 1965).

Another factor that may affect the strength of defense motivation is the ability to reverse a prior attitude, belief, or behavior (reversibility). On the one hand, reversibility may reduce defense motivation by, for example, reducing attachment to a prior view that is seen as tentative due to its reversibility (Abelson, 1988; Kiesler, 1971). On the other hand, reversibility may increase defense motivation by, for example, increasing thoughts about reasons to change the view and thus increasing the number of dissonant cognitions. As a result, reversibility may either attenuate or accentuate the congeniality bias.

Similarly, defense motivation should be strengthened when attitudes, beliefs, or behaviors are linked to individuals' enduring values (e.g., on the issues of euthanasia or abortion) and therefore promote value-relevant involvement with the issue (Johnson & Eagly, 1989). Value-relevant involvement with an issue often produces resistance to persuasion and, more generally, defensive processing of issue-relevant information (Chaiken et al., 1996). Hence, tendencies to prefer congenial over uncongenial information should be amplified when issues are high (vs. low) in value relevance (e.g., Festinger, 1964; Johnson & Eagly, 1989).

Finally, personality differences may affect the extent to which people are motivated to defend their views and behaviors. Closed-minded individuals may view challenging information as threatening, whereas open-minded people may view it as interesting (Adorno, Frenkel-Brunswick, Levinson, & Sanford, 1950; Altemeyer, 1981; 1998). Consequently, individuals with trait closed-mindedness (i.e., high scores on measures of dogmatism or authoritarianism, and high scores on the repression end of the repression-sensitization scale; Byrne, 1964) should manifest a stronger congeniality bias. Furthermore, people who view themselves as incapable of refuting challenging information may be more motivated to proactively guard against such threats (e.g., Albarracín & Mitchell, 2004). If so, the congeniality bias should be more pronounced for individuals with lesser confidence in their attitude, belief, or behavior. Researchers have operationalized confidence by providing bogus positive (vs. negative) feedback about participants' ability to form accurate attitudes, beliefs, or decisions (e.g., Micucci, 1972; Thayer, 1969) or by assessing participants' (a) confidence in their attitude, belief, or behavior (e.g., Berkowitz, 1965; Brechan, 2002; Brodbeck, 1956), (b) chronic anxiety (Frey, Stahlberg & Fries, 1986), or (c) consistency (vs. inconsistency) among behaviors and beliefs (Feather, 1962).1

Accuracy Motivation

Accuracy motivation should promote tendencies to process information in an objective, open-minded fashion that fosters uncovering the truth (Chaiken et al., 1989; Kunda, 1990). One motivational variable linked to accuracy motivation is outcome-relevant involvement (Johnson & Eagly, 1989), which refers to attitudes, beliefs, and decisions linked to an important outcome. For example, in one study (Jonas & Frey, 2003b), participants made a decision assuming that they would (high outcomes relevance) or would not (low outcome relevance) receive a prize for a correct choice. Unlike value-relevant involvement, which heightens defense motivation, outcome-relevant involvement has been shown to foster accuracy concerns and objective processing of available evidence (Albarracín, 2002; Chaiken et al., 1996; Johnson, 1994; Johnson & Eagly, 1989; Petty & Wegener, 1998). Therefore, the congeniality bias may be weaker for information about issues with important personal outcomes (high outcome relevance) than issues without such outcomes (low outcome relevance).

Another factor linked to accuracy motivation is information utility, defined as the extent to which information can be used to facilitate good decisions. Accuracy motivation should direct individuals to information of the highest utility regardless of its congeniality and may therefore weaken the congeniality bias. Researchers have manipulated information utility by assigning participants either to debate an issue or to write an essay in support of their attitudes, beliefs, or behaviors (e.g., Canon, 1964; Freedman, 1965b). The expectation of participating in a debate enhances the selection of uncongenial information because accurate knowledge of the opposition's arguments is useful for planning a rebuttal (i.e., uncongenial information is higher in utility than congenial information; Canon, 1964). In contrast, the expectation of writing a supporting essay enhances the selection of congenial information because this information is useful for preparing an intelligent defense of a current view (i.e., congenial information is higher in utility than uncongenial information; Canon, 1964). Also, accuracy motivation, unlike defense motivation, should direct individuals to information that is of high quality regardless of its congeniality. Therefore, unlike defense motivation, accuracy motivation should reduce the congeniality bias when the uncongenial information is high (vs. low) in quality. But, similar to defense motivation, accuracy motivation should accentuate the congeniality bias when the congenial information is high (vs. low) in quality.

The Present Meta-analysis

Our focus is on the analysis of whether people prefer information that supports pre-existing attitudes, beliefs, and behaviors more than information that challenges pre-existing attitudes, beliefs, and behaviors. Hence, we included studies that measured information selection on the basis of a pre-existing attitude, belief, or behavior. Our search produced 67 eligible reports of selective exposure, which contained 91 studies incorporating 300 statistically-independent groups with a total of just under 8,000 participants. Our synthesis of the selective exposure research has two primary objectives. The first objective is to assess the average magnitude, direction, and variability of selection biases. The second objective is to examine whether moderators related to defense and accuracy motivation (see Figure 1) account for variability in information selection. In general, attempts to defend attitudes, beliefs, or behaviors from attack should accentuate the congeniality bias, whereas attempts to reach accurate conclusions might often attenuate this bias. Other variables were analyzed in an exploratory fashion, including year of publication, source of report, study country, and amount of congenial and uncongenial information available for selection.

Method

Sample of Studies

To locate studies, we first conducted a computerized search of PsycINFO, Medline, Educational Resources Information Center, Dissertation Abstracts International, Social Science Citation Index, the conference proceedings of the Association for Consumer Research, ComAbstracts (http://www.cios.org), the Foreign Doctoral Dissertations Database of the Center for Research Libraries (http://www.crl.edu), and the databases of the Institute of Psychology Information for the German-Speaking Countries (http://www.zpid.de). The keywords were selective exposure, confirmation bias, congeniality bias, information seeking, information avoidance, information preference, attitude selectivity, selective processing, post decision changes, exposure to information, post decision exposure, selectivity, and information seeking. Additional keywords were cognitive dissonance, cognitive consistency, consonant information, dissonant information, supportive information, nonsupportive information, supporting information, consistent information, inconsistent information, decision reversibility, and decision irreversibility.

To supplement these database searches, we examined the reference lists of numerous review articles, chapters, and books discussing selective exposure. Also, we examined the abstracts of all of the publications by authors of multiple articles on selective exposure. Finally, we contacted researchers to request unpublished data and sent requests to the email lists of the Society for Personality and Social Psychology and the Association for Consumer Research. Our search extended through February 2008.

Selection Criteria

Five criteria determined the selection of studies. These criteria yielded a relatively large set of studies that used a similar methodology.

  1. Studies were included if they assessed selective exposure on the basis of prior attitudes, beliefs, and behaviors (including decisions). Studies assessed attitudes and beliefs using self-report rating scales (e.g., agree vs. disagree). Behavior was usually operationalized by (a) a choice made in the session (e.g., choosing to extend a manager's contract; e.g., Frey, 1981b), (b) a self-report of past behavior (e.g., smoking; e.g., Feather, 1962), or (c) a behavior carried out in the experimental session (e.g., playing a computer game; e.g., Betsch et al., 2001). We excluded studies of exposure as a function of mood (e.g., studies of whether people who chronically suffer from a negative mood watch televised-news programs less than those who do not suffer from a negative mood; e.g., Anderson, Collins, Schmitt, & Jacobvitz, 1996), psychological disorders (e.g., studies of whether depressed vs. non-depressed people vary in exposure to comedy programs; e.g., Hammen, 1977; Potts & Sanchez, 1994; Raghunathan & Pham, 1999), biological factors (e.g., preferences for different television programs as a function of time of the menstrual cycle; e.g., Meadowcroft & Zillman, 1987; Potts, Dedman & Halford, 1996), demographic variables (e.g., gender differences in reading about achievement related topics; e.g., Dillman, Knobloch, & Zillman, 2003; Knobloch-Westerwick & Hastall, 2006) or personality (e.g., preferences for different types of music as a function of rebelliousness; e.g., Carpentier, Knobloch & Zillman, 2003).
  2. Studies were included if they assessed information selection or preference and excluded if they pertained to selective interpretation (e.g., Robinson, Keltner, Ward, & Ross, 1995), memory (e.g., Levine & Murphy, 1943), or liking of already viewed material (e.g., Boden & Baumeister, 1997). Typical assessments of selective exposure compared counts of participants' choices from a list of congenial and uncongenial alternatives (e.g., Fischer, Jonas, Frey, & Schulz-Hardt, 2005; Jonas, Graupmann, & Frey, 2006). In some studies, information selection was assessed by participants' ratings or rankings of their preferences for congenial and uncongenial information (e.g., Brannon, Tagler, & Eagly, 2007; Feather, 1963). Finally, selective exposure was sometimes assessed by the amount of time participants devoted to viewing congenial versus uncongenial information (e.g., Brock & Balloun, 1967; Olson & Zanna, 1979).
  3. Studies were included if they arranged choices between congenial and uncongenial information and excluded if they presented only one-sided information or only neutral information (fifteen articles; e.g., Behling, 1971; Edeani, 1979; Frey, 1981c; Otis, 1979; Sweeney & Gruber, 1984; Wellins & McGinnies, 1977). Note that a bias in information selection can only be diagnosed when choices are provided between consonant and dissonant information (Freedman & Sears, 1965). For example, finding that voters who supported Nixon (vs. did not) paid less attention to anti-Nixon information does not necessarily imply a congeniality bias if these same voters also pay less attention to the news in general (Sweeney & Gruber, 1984). Based on this criterion, we also excluded studies on positive hypothesis testing, which examine whether individuals tend to select more questions that are consistent than inconsistent with a prior belief (e.g., Johnston, 1996). For example, research in this tradition might ask participants to test whether someone is an extravert by selecting questions to ask to this person. Some of these questions might confirm the hypothesis (Do you enjoy parties?), whereas others might disconfirm it (Do you enjoy spending time alone?). Selecting more confirming than disconfirming questions has been termed positive hypothesis testing and is distinguished from the congeniality bias examined in research on selective exposure. Specifically, questions testing a hypothesis can sometimes provide disconfirming answers, thus departing from a direct choice of congenial or uncongenial information (Klayman & Ha, 1987).
  4. Studies were included if they focused on an individual's information seeking and excluded if they focused on a group's information seeking (Shulz-Hardt, Frey, Luthgens, & Moscovici, 2000).
  5. Finally, studies were excluded if they lacked adequate statistics (e.g., F-ratios, frequencies, and p-values) for calculating an effect size representing the difference in exposure to congenial and uncongenial information (seven articles; e.g., Donohew, Parker, & McDermott, 1972).

Partitioning of Studies, Calculation of Effect Sizes, and Analytical Considerations

Results were often partitioned into experimental conditions or samples of participants. Whenever possible, effect sizes were computed according to the conceptually-important moderators discussed by the researcher even when this partitioning did not reflect our hypothesized moderators (e.g., unlimited vs. limited choices of information to receive; Fischer et al., 2005). This procedure allowed us to analyze the overall sample of effect sizes without assuming equality in effect sizes across the levels of moderators that were of interest to the researcher (see Table 1).2

Table 1

All Included Studies, Effect Sizes, and Moderator Values (Levels)

Short reference for report and condition d Challenge or
support
Quality
congenial
Quality
uncongenial
CommitmentReversibilityValue
relevance
Closed-
mindedness
ConfidenceOutcome
relevance
Utility
Congenial
Utility
uncongenial
Relative
utility
Adams (1961)
  Heard congenial speech0.71SupportHHHReversibleHMHHNo goalNo goalEqual
  Heard uncongenial speech0.55ChallengeHHHReversibleHMHHNo goalNo goalEqual
Berkowitz (1965)
  Support−1.50SupportLLMIrreversibleHMHLNo goalNo goalEqual
  Moderate dissonance−0.85ChallengeLLMIrreversibleHMHLNo goalNo goalEqual
  Strong dissonance1.04ChallengeLLMIrreversibleHMLLNo goalNo goalEqual
Betsch et al. (2001)
  Strong routine, familiar task1.04NoMMHReversibleLMHLHHEqual
  Weak routine, familiar task0.61NoMMMReversibleLMHLHHEqual
  Strong routine, new task−0.28NoMMHReversibleLMMLHHEqual
  Weak routine, new task0.46NoMMMReversibleLMMLHHEqual
Bosotti (1984)
 Study 1
  Low quality information0.40NoLLMIrreversibleHMMLNo goalNo goalEqual
  High quality information0.38NoHHMIrreversibleHMMLNo goalNo goalEqual
 Study 2
  Low quality information−0.26NoLLMIrreversibleHMMLNo goalNo goalEqual
  High quality information0.70NoHHMIrreversibleHMMLNo goalNo goalEqual
Brannon et al. (2007)
  Study 1a0.72NoHHMIrreversibleHMMLNo goalNo goalEqual
  Study 1b0.73NoHHMIrreversibleHMMLNo goalNo goalEqual
  Study 20.49NoHHMIrreversibleHMMLNo goalNo goalEqual
Brechan (2002)
 Study 1
  High confidence1.72NoMMMIrreversibleHMHLNo goalNo goalEqual
  Low confidence1.07NoMMMIrreversibleHMLLNo goalNo goalEqual
 Study 2
  High confidence1.79NoMMMIrreversibleHMHLNo goalNo goalEqual
  Low confidence0.99NoMMMIrreversibleHMLLNo goalNo goalEqual
Brock (1965)
  Low commitment, smoker0.53NoMMHIrreversibleLMMHNo goalNo goalEqual
  Low commitment, non-smoker0.01NoMMMIrreversibleLMMLNo goalNo goalEqual
  High commitment, smoker3.32NoMMHIrreversibleLMMHNo goalNo goalEqual
  High commitment, non-smoker2.24NoMMMIrreversibleLMMLNo goalNo goalEqual
Brock et al. (1970)
  New information, high commitment0.81NoHHHIrreversibleLMMHNo goalNo goalEqual
  New information, less commitment−0.09NoHHMIrreversibleLMMHNo goalNo goalEqual
  Old information, high commitment−0.17NoHHHIrreversibleLMMHNo goalNo goalEqual
  Old information, less commitment0.30NoHHMIrreversibleLMMHNo goalNo goalEqual
Brock & Balloun (1967)
 Study 1
  Smoker0.74NoHHHIrreversibleLMMHHHEqual
  Non-smoker0.18NoHHMIrreversibleLMMLHHEqual
 Study 2
  Smoker0.86NoHHHIrreversibleLMMHHHEqual
  Non-smoker0.11NoHHMIrreversibleLMMLHHEqual
 Study 3
  Smoker0.99NoHHHIrreversibleLMMHHHEqual
  Non-smoker−0.06NoHHMIrreversibleLMMLHHEqual
 Study 4
  Smoker1.21NoHHHIrreversibleLMMHHHEqual
  Non-smoker0.42NoHHMIrreversibleLMMLHHEqual
Brodbeck (1956)
  Challenge, decrease in confidence−0.37ChallengeLLMIrreversibleHMLHNo goalNo goalEqual
  Challenge, no decrease in confidence−0.70ChallengeLLMIrreversibleHMHHNo goalNo goalEqual
  Support−0.97SupportLLMIrreversibleHMMHNo goalNo goalEqual
Canon (1964)
  Debate goal, high confidence−0.55NoMMHIrreversibleLMHLHHUncongenial
  Debate goal, low confidence0.23NoMMHIrreversibleLMLLHHUncongenial
  Expression goal, high confidence0.32NoMMHIrreversibleLMHLHHCongenial.
  Expression goal, low confidence1.14NoMMHIrreversibleLMLLHHCongenial.
Canon & Matthews (1972)
  Non-smoker, low concern for health (CH)0.16NoHHMIrreversibleLMMLNo goalNo goalEqual
  Non-smoker, high CH0.52NoHHMIrreversibleHMMLNo goalNo goalEqual
  Smoker, low CH−0.06NoHHHIrreversibleLMMHNo goalNo goalEqual
  Smoker, high CH0.89NoHHHIrreversibleHMMHNo goalNo goalEqual
Clarke & James (1967)
  Expect debate0.47NoMMMIrreversibleHMMLHHUncongenial
  Expect discussion0.31NoMMMIrreversibleHMMLHHEqual
Cotton & Hieser (1980)
  Low choice1.04NoMMMReversibleHMHLNo goalNo goalEqual
  High choice0.17NoMMLReversibleHMHLNo goalNo goalEqual
Ehrlich et al. (1957)
  New car owners0.95NoMMHIrreversibleLMMHNo goalNo goalEqual
  Old car owners0.63NoMMHIrreversibleLMHHNo goalNo goalEqual
Feather (1962)
  Smoker, congenial beliefs−0.78NoMMHIrreversibleLMHHNo goalNo goalEqual
  Smoker, uncongenial beliefs0.39NoMMHIrreversibleLMLHNo goalNo goalEqual
  Non-smoker, uncongenial beliefs−0.39NoMMMIrreversibleLMMLNo goalNo goalEqual
  Non-smoker, congenial beliefs0.26NoMMMIrreversibleLMHLNo goalNo goalEqual
Feather (1963)
  Smoker0.06NoMMHIrreversibleLMMHNo goalNo goalEqual
  Non-smoker−0.12NoMMMIrreversibleLMMLNo goalNo goalEqual
Feather (1969)
  High dogmatism, old information1.22NoHHMIrreversibleHHMLNo goalNo goalEqual
  High dogmatism, new information1.40NoHHMIrreversibleHHMLNo goalNo goalEqual
  Low dogmatism, old information0.41NoHHMIrreversibleHLMLNo goalNo goalEqual
  Low dogmatism, new information0.18NoHHMIrreversibleHLMLNo goalNo goalEqual
Fischer et al. (2005)
 Study 1
  No restrictions−0.20NoHHMReversibleLMMLHHEqual
  Lower limit restrictions−0.07NoHHMReversibleLMMLHHEqual
  Upper-limit restrictions1.00NoHHMReversibleLMMLHHEqual
  Specific restrictions1.65NoHHMReversibleLMMLHHEqual
 Study 2
  Restricted, no scarcity cue2.43NoHHMReversibleHMMHHHEqual
  Restricted, scarcity cue1.61NoHHMReversibleHMMHHHEqual
  Unrestricted, no scarcity cue0.66NoHHMReversibleHMMHHHEqual
  Unrestricted, scarcity cue1.77NoHHMReversibleHMMHHHEqual
 Study 3
  Restricted, load−0.34NoHHMReversibleLMMLHHEqual
  Restricted, no load2.22NoHHMReversibleLMMLHHEqual
  Unrestricted, no load−0.01NoHHMReversibleLMMLHHEqual
  Unrestricted, load0.08NoHHMReversibleLMMLHHEqual
 Study 4
  Restricted, before0.55NoHHMReversibleLMMLHHEqual
  Restricted, after0.71NoHHMReversibleLMMLHHEqual
  Unrestricted, before−0.07NoHHMReversibleLMMLHHEqual
  Unrestricted, after0.08NoHHMReversibleLMMLHHEqual
Fischer et al. (2008)
 Study 1
  2 pieces−0.39NoHHMIrreversibleLMMLNo goalNo goalEqual
  10 pieces0.46NoHHMIrreversibleLMMLNo goalNo goalEqual
 Study 2
  2 pieces−0.29NoMMHReversibleHMMHHHEqual
  4 pieces0.65NoMMHReversibleHMMHHHEqual
  10 pieces0.85NoMMHReversibleHMMHHHEqual
 Study 3
  2 pieces with content cues−0.41NoHHMReversibleLMMLHHEqual
  10 pieces with content cues1.06NoHHMReversibleLMMLHHEqual
  2 pieces no content cues−0.31NoHHMReversibleLMMLHHEqual
  10 pieces no content cues−0.01NoHHMReversibleLMMLHHEqual
 Study 4
  2 no focus−0.44NoHHMReversibleLMMLHHEqual
  10 no focus0.78NoHHMReversibleLMMLHHEqual
  2 quality focus0.48NoHHMReversibleLMMLHHEqual
  10 quality focus0.68NoHHMReversibleLMMLHHEqual
  2 direction focus−1.29NoHHMReversibleLMMLHHEqual
  10 direction focus−0.20NoHHMReversibleLMMLHHEqual
Freedman (1965a)
  Positive interview−1.49NoHHMIrreversibleLMHLNo goalNo goalEqual
  Negative interview−1.44NoHHMIrreversibleLMHLNo goalNo goalEqual
Freedman (1965b)
  Low confidence, expression goal0.35NoMMHIrreversibleLMLLHHCongenial
  Low confidence, debate goal−0.29NoMMHIrreversibleLMLLHHUncongenial
  Low confidence, no goal0.04NoMMMIrreversibleLMLLNo goalNo goalEqual
  High confidence, expression goal0.34NoMMHIrreversibleLMHLHHCongenial
  High confidence, debate goal−0.27NoMMHIrreversibleLMHLHHUncongenial
  High confidence, no goal0.04NoMMMIrreversibleLMHLNo goalNo goalEqual
Frey (1981a)
  Information costs, 70.14NoMMMReversibleHMLLNo goalNo goalEqual
  Information costs, 150.72NoMMMReversibleHMLLNo goalNo goalEqual
  Information costs, 250.64NoMMHReversibleHMLLNo goalNo goalEqual
  Information costs, 330.62NoMMHReversibleHMLLNo goalNo goalEqual
  Information free, 70.22NoMMMReversibleHMLLNo goalNo goalEqual
  Information free, 150.78NoMMMReversibleHMLLNo goalNo goalEqual
  Information free, 25−0.25NoMMHReversibleHMLLNo goalNo goalEqual
  Information free, 33−0.18NoMMHReversibleHMLLNo goalNo goalEqual
Frey (1981b)
 Study 1
  High quality congenial, high quality Uncongenial0.50NoHHHIrreversibleLMMLHLCongenial
  Low quality congenial, high quality Uncongenial−0.07NoLHHIrreversibleLMMLLLEqual
  High quality congenial, low quality Uncongenial0.23NoHLHIrreversibleLMMLHLCongenial
  Low quality congenial, low quality Uncongenial0.07NoLLHIrreversibleLMMLLLEqual
 Study 2
  High quality congenial, high quality Uncongenial0.58NoHHMIrreversibleHMMHHHEqual
  Low quality congenial, high quality Uncongenial−0.01NoLHMIrreversibleHMMHHHEqual
  High quality congenial, low quality Uncongenial0.69NoHLMIrreversibleHMMHHHEqual
  Low quality congenial, low quality Uncongenial0.24NoLLMIrreversibleHMMHHHEqual
 Study 3
  Unlimited, no information0.40NoHHMIrreversibleLMMLNo goalNo goalEqual
  Unlimited, uncongenial information0.54ChallengeHHMIrreversibleLMMLNo goalNo goalEqual
  Unlimited, congenial information−0.23SupportHHMIrreversibleLMMLNo goalNo goalEqual
  Unlimited, both0.21NoHHMIrreversibleLMMLNo goalNo goalEqual
  Limited, no information0.91NoHHMIrreversibleLMMLNo goalNo goalEqual
  Limited, uncongenial information0.44ChallengeHHMIrreversibleLMMLNo goalNo goalEqual
  Limited, congenial information−0.04SupportHHMIrreversibleLMMLNo goalNo goalEqual
  Limited, both0.36NoHHMIrreversibleLMMLNo goalNo goalEqual
Frey (1982)
  High gain0.74SupportMMHReversibleLMHHHHEqual
  Moderate gain0.76SupportMMHReversibleLMHHHHEqual
  Low gain1.26SupportMMHReversibleLMHHHHEqual
  Low loss0.72ChallengeMMHReversibleLMLHHHEqual
  Moderate loss−0.18ChallengeMMHReversibleLMLHHHEqual
  High loss−0.72ChallengeMMHReversibleLMLHHHEqual
Frey & Rosch (1984)
  Reversible, old information0.72NoHHLReversibleLMMLLLEqual
  Reversible, new information0.15NoHHLReversibleLMMLHHEqual
  Irreversible, old information0.73NoHHHIrreversibleLMMLLLEqual
  Irreversible, new information1.19NoHHHIrreversibleLMMLHHEqual
Frey & Stahlberg (1986; Study 1)
  Congenial information0.18SupportHHHIrreversibleHMHLNo goalNo goalEqual
  No information0.65NoHHHIrreversibleHMMLNo goalNo goalEqual
Frey et al. (1986)
  High anxiety, low score1.32NoHHHReversibleHHLLNo goalNo goalEqual
  High anxiety, high score−0.07NoHHHReversibleHHLLNo goalNo goalEqual
  Low anxiety, low score0.50NoHHHReversibleHHHLNo goalNo goalEqual
  Low anxiety, high score0.31NoHHHReversibleHHHLNo goalNo goalEqual
Frey & Wicklund (1978)
  No choice, restricted search−0.07NoHHLIrreversibleLMLLNo goalNo goalEqual
  No choice, restricted search0.47NoHHLIrreversibleLMLLNo goalNo goalEqual
  No choice, unrestricted search0.14NoHHLIrreversibleLMLLNo goalNo goalEqual
  No choice, restricted search−0.40NoHHLIrreversibleLMLLNo goalNo goalEqual
  Choice, restricted search0.72NoHHHIrreversibleLMLLNo goalNo goalEqual
  Choice, restricted search1.53NoHHHIrreversibleLMLLNo goalNo goalEqual
  Choice, unrestricted search0.50NoHHHIrreversibleLMLLNo goalNo goalEqual
  Choice, restricted search0.60NoHHHIrreversibleLMLLNo goalNo goalEqual
Hillis & Crano (1973)
  Strong pro-choice attitude, pro-choice talk1.12NoHHHIrreversibleHMHLHLCongenial
  Pro-choice attitude, pro-choice talk0.83NoHHMIrreversibleHMMLHLCongenial
  Strong pro-life attitude, pro-choice talk−0.51NoHHHIrreversibleHMHLLHUncongenial
  Pro-life attitude, pro-choice talk0.00NoHHMIrreversibleHMMLLHUncongenial
  Strong pro-life attitude, pro-life talk0.73NoHHHIrreversibleHMHLHLCongenial
  Pro-life attitude, pro-life talk0.73NoHHMIrreversibleHMMLHLCongenial
  Strong pro-choice attitude, pro-life talk−1.26NoHHHIrreversibleHMHLLHUncongenial
  Pro-choice attitude, pro-life talk−1.26NoHHMIrreversibleHMMLLHUncongenial
Holton & Pyszczynski (1989)
 Study 11.30NoHHHReversibleHMMLNo goalNo goalEqual
Janis & Rausch (1970)
  Refused to sign quickly−0.70NoMMMIrreversibleHMHHNo goalNo goalEqual
  Refused to sign−0.74NoMMMIrreversibleHMMHNo goalNo goalEqual
  Might sign0.30NoMMMIrreversibleHMLHNo goalNo goalEqual
  Have signed−0.14NoMMHIrreversibleHMHHNo goalNo goalEqual
Jecker (1964)
  Moderate commitment0.54NoHHMIrreversibleLMMHNo goalNo goalEqual
  Low commitment0.10NoHHLIrreversibleLMMHNo goalNo goalEqual
Jonas & Frey (2003a)
  Dm−0.25NoHHMIrreversibleLMMLNo goalNo goalEqual
  Euro0.35NoHHLIrreversibleLMLLNo goalNo goalEqual
Jonas & Frey (2003b)
 Study 1
  Personal, friendly atmosphere0.24NoHHHReversibleLMMLHHEqual
  Personal, business atmosphere0.63NoHHHReversibleLMMLHHEqual
  Advisor, friendly atmosphere−0.08NoHHHReversibleLMMHHHEqual
  Advisor, business atmosphere0.10NoHHHReversibleLMMHHHEqual
 Study 2
  Personal0.36NoHHMReversibleLMMLHHEqual
  Advisor−0.13NoHHMReversibleLMMHHHEqual
Jonas, Frey et al. (2001)
  Support, verbal justification0.35SupportHHHReversibleLMHLHHEqual
  Challenge, verbal justification0.11ChallengeHHHReversibleLMLLHHEqual
  Support and challenge, verbal justification0.40NoHHHReversibleLMMLHHEqual
  Support, no verbal justification−0.19SupportHHMReversibleLMHLHHEqual
  Challenge, no verbal justification0.32ChallengeHHMReversibleLMLLHHEqual
  Support and challenge, no verbal justification−1.16NoHHMReversibleLMMLHHEqual
Jonas, Graupmann et al. (2003)
  Low party awareness, low relevance0.57NoHHMIrreversibleLMMLNo goalNo goalEqual
  Low party awareness, high relevance2.18NoHHMIrreversibleHMMLNo goalNo goalEqual
  High party awareness, low relevance0.50NoHHMIrreversibleLMMLNo goalNo goalEqual
  High party awareness, high relevance0.82NoHHHIrreversibleHMMLNo goalNo goalEqual
Jonas et al. (2006)
 Study 1
  Positive mood−0.01NoHHHReversibleLMHLHHEqual
  Negative mood0.85NoHHHReversibleLMLLHHEqual
 Study 3
  Positive mood0.26NoHHHReversibleLMHLHHEqual
  Neutral mood0.64NoHHHReversibleLMMLHHEqual
  Negative mood0.89NoHHHReversibleLMLLHHEqual
Jonas, Greenberg et al. (2003)
  Mortality salience, worldview issue1.50NoHHHReversibleHMMHHHEqual
  Control, worldview issue0.73NoHHMReversibleHMMHHHEqual
  Mortality salience, fictitious issue−0.02NoHHMReversibleLMMLHHEqual
  Control, fictitious issue0.28NoHHMReversibleLMMLHHEqual
Jonas, Schulz-Hardt & Frey (2001)
  Sequential2.56NoHHHReversibleHMMHNo goalNo goalEqual
  Simultaneous1.28NoHHMReversibleHMMHNo goalNo goalEqual
Jonas et al. (2005)
 Study 1
  Decision-maker for self2.24NoMMMReversibleLMMHHHEqual
  Advisor as recommender (non-binding)0.76NoMMMReversibleLMMHHHEqual
  Advisor as decision-maker (binding)2.76NoMMHReversibleLMMHHHEqual
 Study 2
  No meeting, recommendation0.78NoMMMReversibleLMMHHHEqual
  Meeting, recommendation0.84NoMMHReversibleLMMHHHEqual
  No meeting, decision-maker−0.81NoMMMReversibleLMMHHHEqual
  Meeting, decision-maker1.14NoMMHReversibleLMMHHHEqual
Jonas, Schulz-Hardt, Frey, & Thelen (2001)
 Study 1
  Simultaneous search0.40NoHHMReversibleHMMHHHEqual
  Sequential search1.25NoHHHReversibleHMMHHHEqual
 Study 2
  Simultaneous-simultaneous focus0.56NoHHMReversibleHMMHHHEqual
  Simultaneous-sequential focus0.40NoHHMReversibleHMMHHHEqual
  Sequential-simultaneous focus0.90NoHHHReversibleHMMHHHEqual
  Sequential-sequential focus1.84NoHHHReversibleHMMHHHEqual
 Study 3
  Sequential search0.91NoHHHReversibleHMMHHHEqual
 Study 4
  Sequential-control focus1.40NoHHHReversibleHMMHHHEqual
  Simultaneous-control focus0.43NoHHMReversibleHMMHHHEqual
  Sequential-information focus0.46NoHHMReversibleHMMHHHEqual
  Simultaneous-information focus0.50NoHHMReversibleHMMHHHEqual
Kleck & Wheaton (1967)
 Study 10.47NoMMMIrreversibleHMMHNo goalNo goalEqual
Lavine et al. (2005)
  Control, high authoritarianism0.15NoMMMIrreversibleHHMLNo goalNo goalEqual
  Control, low authoritarianism0.06NoMMMIrreversibleHLMLNo goalNo goalEqual
  Mortality salience, high authoritarianism0.74NoMMHIrreversibleHHMLNo goalNo goalEqual
  Mortality salience, low authoritarianism0.00NoMMHIrreversibleHLMLNo goalNo goalEqual
Lavoie & Thompson (1972)
 Study 10.20NoMMMIrreversibleHMMLNo goalNo goalEqual
Lowe & Steiner (1968)
  Reversible, consequences−0.44NoMMLReversibleLMMHHHEqual
  Reversible, no consequences−0.25NoMMLReversibleLMMLHHEqual
  Irreversible, consequences−0.53NoMMHIrreversibleLMMHNo goalNo goalEqual
  Irreversible, no consequences0.28NoMMHIrreversibleLMMLNo goalNo goalEqual
Lowin (1969)
  High quality information, high confidence0.52NoHHHIrreversibleLMHLNo goalNo goalEqual
  High quality information, low confidence0.64NoHHHIrreversibleLMLLNo goalNo goalEqual
  Low quality information, high confidence−0.50NoLLHIrreversibleLMHLNo goalNo goalEqual
  Low quality information, low confidence−0.18NoLLHIrreversibleLMLLNo goalNo goalEqual
Lundgren & Prislin (1998)
 Study 1
  Accuracy motive−0.18NoLLMReversibleLMMLHHEqual
  Impression motive−0.51NoLLMReversibleLMMLLHUncongenial
  Defense motive0.42NoLLMReversibleLMMHHLCongenial
  Control−0.26NoLLMReversibleLMMLNo goalNo goalEqual
 Study 2
  Impression and accuracy motive0.16NoLLMReversibleLMMHHHUncongenial
  Defense and accuracy motive1.24NoLLMReversibleLMMHHHCongenial
  Defense and impression motive0.26NoLLMReversibleLMMHHHEqual
Maccoby et al. (1961)
  Support0.83SupportLLMReversibleHMMLHHEqual
  Challenge0.75ChallengeLLMReversibleHMMLHHEqual
McFarland & Warren (1992)
  Fundamentalist Christians1.54NoHHHIrreversibleHMMLNo goalNo goalEqual
Micucci (1972)
  Low self-esteem1.04NoMMMIrreversibleHMLLNo goalNo goalEqual
  Moderate self-esteem−0.29NoMMMIrreversibleHMMLNo goalNo goalEqual
  High self-esteem−0.30NoMMMIrreversibleHMHLNo goalNo goalEqual
Miller (1977)
  Immediate0.17NoMMMIrreversibleHMLHNo goalNo goalEqual
  4 minutes−0.57NoMMMIrreversibleHMLHNo goalNo goalEqual
  12 minutes0.82NoMMMIrreversibleHMLHNo goalNo goalEqual
Nemeth & Rogers (1996)
  High relevance, majority dissent0.56NoHHMReversibleHMMHHHEqual
  High relevance, minority dissent0.00SupportMMMIrreversibleLMMHNo goalNo goalEqual
  Low relevance, majority dissent0.77ChallengeMMMIrreversibleLMMLNo goalNo goalEqual
  Low relevance, minority dissent0.30SupportMMMIrreversibleLMMLNo goalNo goalEqual
Olson & Zanna (1979)
  Repressors, choice0.83NoN/AN/AMIrreversibleLHMLNo goalNo goalEqual
  Repressor, liking0.05NoN/AN/AMIrreversibleLHMLNo goalNo goalEqual
  Sensitizers, choice−0.21NoN/AN/AMIrreversibleLLMLNo goalNo goalEqual
  Sensitizers, liking0.16NoN/AN/AMIrreversibleLLMLNo goalNo goalEqual
Pyszczynski et al. (1985)
  Study 11.06NoHHHReversibleHMMLNo goalNo goalEqual
  Study 21.20NoHHHReversibleHMMLNo goalNo goalEqual
Rhine (1967)
  0–1 contradiction−0.61NoHHHIrreversibleHMHHNo goalNo goalEqual
  2 contradictions0.29ChallengeHHHIrreversibleHMMHNo goalNo goalEqual
  3 contradictions0.37ChallengeHHHIrreversibleHMMHNo goalNo goalEqual
  4 contradictions0.36ChallengeHHHIrreversibleHMLHNo goalNo goalEqual
  5–6 contradictions0.86ChallengeHHHIrreversibleHMLHNo goalNo goalEqual
  No contradictions0.35NoHHHIrreversibleHMHHNo goalNo goalEqual
Rosen (1961)
  Objective, high relevance0.65NoHHMIrreversibleLMMHNo goalNo goalEqual
  Objective, low relevance0.42NoHHMIrreversibleLMMLNo goalNo goalEqual
  Essay, high relevance0.87NoHHMIrreversibleLMMHNo goalNo goalEqual
  Essay, low relevance0.28NoHHMIrreversibleLMMLNo goalNo goalEqual
Rosenbaum & McGinnies (1973)
 Study 10.50NoHHMIrreversibleHMMLNo goalNo goalEqual
Schulman (1971)
  High primary support, low secondary support0.37NoMMMIrreversibleHMMHNo goalNo goalEqual
  High primary support, high secondary0.41NoMMMIrreversibleHMHHNo goalNo goalEqual
  Moderate primary support, low secondary support0.41NoMMMIrreversibleHMMHNo goalNo goalEqual
  Moderate primary support, high secondary support0.72NoMMMIrreversibleHMMHNo goalNo goalEqual
  Low primary support, low secondary support0.81NoMMMIrreversibleHMLHNo goalNo goalEqual
  Low primary support, high secondary support0.70NoMMMIrreversibleHMMHNo goalNo goalEqual
Schulz-Hardt et al. (2000)
 Study 11.01NoHHHIrreversibleLMMLHHEqual
Schwarz et al. (1980)
  Supportive essay, one-sided support0.25SupportHHHIrreversibleLMHHNo goalNo goalEqual
  Supportive essay, two-sided support−0.52SupportHHHIrreversibleLMMHNo goalNo goalEqual
  Supportive essay, one-sided challenge1.58ChallengeHHHIrreversibleLMLHNo goalNo goalEqual
  Supportive essay, two-sided challenge0.79ChallengeHHHIrreversibleLMMHNo goalNo goalEqual
  No essay, one-sided support0.64SupportHHMIrreversibleLMHHNo goalNo goalEqual
  No essay, two-sided support−0.38SupportHHMIrreversibleLMMHNo goalNo goalEqual
  No essay, one-sided challenge0.20ChallengeHHMIrreversibleLMLHNo goalNo goalEqual
  No essay, two-sided challenge−0.08ChallengeHHMIrreversibleLMMHNo goalNo goalEqual
Sears (1965)
  Old information−0.64NoHHMIrreversibleLMMLNo goalNo goalEqual
  New information−0.50NoHHMIrreversibleLMMLNo goalNo goalEqual
Sears (1966)
  No summation−0.18NoHHMIrreversibleLMMLNo goalNo goalEqual
  Agrees with summation−0.40SupportHHMIrreversibleLMHLNo goalNo goalEqual
  Disagrees with summation0.53ChallengeHHMIrreversibleLMLLNo goalNo goalEqual
  Two opposed summations−0.03NoHHMIrreversibleLMMLNo goalNo goalEqual
Sears & Freedman (1963)
  Low commitment, expression goal0.35NoHHLReversibleLMMLHHCongenial
  Low commitment, no goal0.35NoHHLReversibleLMMLNo goalNo goalEqual
  High commitment, expression goal0.11NoHHHIrreversibleLMMLHHCongenial
  High commitment, no goal0.17NoHHHIrreversibleLMMLNo goalNo goalEqual
Sears & Freedman (1965)
  Convict, new information−1.00NoHHHIrreversibleLMMLNo goalNo goalEqual
  Acquit, new information0.06NoHHHIrreversibleLMMLNo goalNo goalEqual
  Convict old information−0.31NoHHHIrreversibleLMMLNo goalNo goalEqual
  Acquit, old information−0.02NoHHHIrreversibleLMMLNo goalNo goalEqual
Smith et al. (2007)
 Study 1
  Expression goal0.87NoMMHIrreversibleHMMLHHCongenial
  No goal0.21NoMMMIrreversibleHMMLNo goalNo goalEqual
 Study 2
  Expression goal, time pressure0.99NoMMHIrreversibleHMMLHHCongenial
  Expression goal, no time pressure0.26NoMMHIrreversibleHMMLHHCongenial
  No goal, time pressure0.33NoMMMIrreversibleHMMLNo goalNo goalEqual
  No goal, no time pressure0.15NoMMMIrreversibleHMMLNo goalNo goalEqual
Thayer (1969)
  High confidence0.07NoMMMIrreversibleLMHLNo goalNo goalEqual
  Low confidence0.36NoMMMIrreversibleLMLLNo goalNo goalEqual

Note. The following abbreviations were used for the columns: H = High; L = Low; M = Moderate; No = No challenge or support.

After completing the coding, we calculated effect sizes (g) representing selective exposure from means and standard deviations, proportions or frequencies, F-ratios, t-tests, and correlations. When a report included means (e.g., ratings of interest in the information), we calculated g by subtracting the mean ratings of the uncongenial information from the mean ratings of the congenial information and dividing by the pooled standard deviation. From other documents, g was estimated from t-tests or F-ratios. For proportions, an odds or an odds ratio was calculated. When there was a mutually exclusive choice between congenial and uncongenial information (i.e., selecting a congenial article meant not selecting an uncongenial article), the odds of selecting congenial information was calculated by dividing the proportion of participants choosing congenial information by the proportion choosing uncongenial information. When there were independent choices of congenial and uncongenial information, we calculated separate odds and then an odds ratio by dividing the odds for congenial information by the odds for uncongenial information. To produce g, the log of the odds or the odds ratio was divided by 1.81 (Haddock, Rindskopf, & Shadish, 1998; Hasselblad & Hedges, 1995). All gs were converted to ds to correct for sample size bias (Hedges & Olkin, 1985). Positive ds indicate greater selection of congenial information, negative ds indicate greater selection of uncongenial information, and zero indicates the absence of bias.

We used Hedges and Olkin's (1985) procedures to calculate weighted mean effect sizes, effect sizes (d) and to estimate a homogeneity statistic (Q). Q has a distribution similar to a chi-square with k −1 degrees of freedom, where k is the number of effect sizes, and indicates whether the variance in effect sizes is no greater than sampling error. When a d implied a within-subjects comparison (e.g., between mean ratings of congenial and uncongenial information), the correlation between the two measures can be used to calculate the between-subjects variance in the statistic (Morris, 2000). We estimated this correlation (r = .27) using procedures suggested by Seignourel and Albarracín (2002) and then calculated the variance of the effect sizes using this imputed correlation.3 When d implied a between-subjects comparison, we used Hedges and Olkin's (1985) procedures to calculate the between-subjects variance in the statistic.

In the absence of homogeneity, we examined whether our moderators, entered alone and jointly with other moderators, accounted for variability among effect sizes using both fixed-effects and random-effects models.4, 5 In addition, we examined whether the effects of the moderators replicated using only effect sizes that derived from studies that measured or manipulated the moderator variable of interest. Because these analyses relied on a smaller number of cases, only univariate analyses using fixed- and random-effects models are presented. These analyses ensure that the effects of moderators are not due to uncontrolled differences across studies. We analyzed the effects of the moderators on selective exposure using analysis of variance. In this type of analysis, the inverse of the variance of the effect size being predicted is used as a weight and the significance of the moderators of interest are determined by examining the significance of the QB, which is a sums of squares comparable to an F-ratio but distributed similar to a chi-square with l −1 degrees of freedom, where l is the number of levels of the moderator. QBs were obtained to test for the main and simple effects of the moderator variable on selective exposure.

Moderators

Potential moderators were independently coded by two of the authors with adequate agreement (average kappa = .79; all kappas > .70). Disagreements were resolved by discussion with a third author.

For descriptive purposes, we recorded (a) year of publication; (b) publication form (journal article, unpublished dissertation or thesis, or other unpublished document); (c) participant population (university students, high school students, other, or mixed); (d) country where the study was conducted (United States and Canada, Germany, Australia, or Italy); (e) research setting (lab or field); (f) type of issue used in the study (e.g., politics, religion and morality, game play, betting and buying behavior, or personal health and development); (g) artificiality of issue (artificial, e.g., a hypothetical hiring decision, or real, e.g., abortion); (h) breadth of issue (broad, e.g., euthanasia, or narrow, e.g., decision about the guilt of a particular defendant); (i) exposure measure (choice of information to receive, rating of information preference, or ranking of information preference); (j) amount of congenial and uncongenial information offered for selection (number of congenial choices and number of uncongenial choices in the selection array); (k) psychological predictor used in the research (attitude, belief, or behavior); (l) the anonymity of the attitude, belief, and choice (anonymous or not anonymous); and (m) the novelty of the congenial and uncongenial information offered for selection (familiar or novel).

Coding of Potential Motivational Moderators

To examine the motivational determinants of selective exposure, we coded several variables with potential motivational properties (see Figure 1).

Defense motivation

In some studies participants' pre-existing attitudes, beliefs, and behaviors were challenged or supported prior to the information selection by learning that their decision was poor (vs. smart; e.g., Frey, 1982), hearing that their attitude was a minority (vs. majority) position (e.g., Nemeth & Rogers, 1996), and receiving more or less challenging (vs. supporting) information (e.g., Berkowitz, 1965). We coded challenge or support received prior to information selection as challenge (i.e., more uncongenial than congenial information received), no challenge or support (i.e., neither congenial nor uncongenial information received or equal amounts of congenial and uncongenial information received), or support (i.e., more congenial than uncongenial information received).

Also, we coded the quality of the available information presented for selection as high when the presumed source of the information was an expert on the topic (e.g., a scientist) and low when the presumed source was a novice or a peer (e.g., in a financial decision, high for an economics professor and low for a fifteen-year-old student or a passerby on the street; Frey, 1981b). When the source was neither clearly high nor low in expertise (e.g., a newspaper columnist or magazine writer), quality was coded as moderate.

We coded participants' commitment to their pre-existing attitude, belief, or behavior as high, moderate, or low. Commitment was high if the participants (a) justified (e.g., Jonas & Frey, 2003b; Schwarz et al., 1980) or anticipated having to justify (Canon, 1964; Janis & Rausch, 1970; Lowin, 1969) an attitude, belief, or behavior to an audience; (b) freely spent a relatively large amount of time or effort on a given behavior (e.g., playing a game; Betsch et al., 2001; smoking; Brock, 1965; writing random numbers, Frey & Wicklund, 1978); (c) engaged in sequential information searches (Jonas, Graupmann, & Fischer, 2003), which are known to enhance commitment to the decision (Jonas et al., 2001); (d) thought about their own death (Jonas, Greenberg, & Frey, 2003; Lavine, Lodge, & Freitas, 2005), which is known to enhance commitment to attitudes, beliefs, and behaviors that are tied to world views (review by Pyszczynski, Greenberg, Solomon, Arndt, & Schimel, 2004); or (f) reported that they held their attitude or belief with high commitment (Jonas & Frey, 2003a; Rhine, 1967) or viewed the belief as relevant to their self-worth (e.g., intelligence; Frey & Stahlberg, 1986; sociability, Holton & Pysczynski, 1989). Commitment to a pre-existing attitude, belief, or behavior was low when the participants freely engaged in attitude-inconsistent behavior (Cotton & Hieser, 1980), did not freely choose their behavior, attitude, or beliefs (e.g., behavior was assigned; Frey & Wicklund, 1978), or indicated a low amount of commitment to the choice (Jonas & Frey, 2003a). When commitment was not clearly high or low, it was coded as moderate. In addition, we coded for the reversibility of participants' reported attitudes, beliefs, or behaviors by noting whether, at the time of information selection, participants believed that they could (reversible) or could not (irreversible) change their attitudes, beliefs, or behaviors at a later time in the experiment (e.g., Frey & Rosch, 1984).

We also coded the value relevance of the issue. Value relevance was high if the issue was judged to be connected to the participants' enduring values (e.g., abortion, euthanasia, how to raise children); otherwise value relevance was low (e.g., a specific hiring decision, choosing among gifts). We also coded, whenever possible, participants' closed-mindedness as high or low as assessed by Rokeach's (1960) Dogmatism Scale, Altemeyer's (1996) Right Wing Authoritarianism Scale, and the Repression-Sensitization scale (Byrne, 1964). If the sample was not partitioned on closed-mindedness, this variable was coded as moderate.6 Participants' confidence in their attitude, belief, or behavior was registered as high, moderate, or low. Confidence was high (low) if participants reported high (low) confidence in their attitude, belief, or behavior (e.g., Adams, 1961; Brechan, 2002; Berkowitz, 1965; Brodbeck, 1956), reported beliefs that were consistent (inconsistent) with their behavior (Feather, 1962), received bogus positive (negative) feedback about their ability to form accurate attitudes, beliefs, or decisions (e.g., Thayer, 1969), were placed in a positive (negative) mood state after forming a decision (Jonas et al., 2006),7 were provided positive (negative) self-relevant feedback (Micucci, 1972), or possessed low (high) dispositional levels of anxiety (Frey et al., 1986). Without a confidence manipulation or partitioning of the sample, confidence was coded as moderate.

Accuracy motivation

We coded outcome relevance of the topic as high if the issue could have foreseeable effects on participants' outcomes in the near future (e.g., a choice of a gift, use of a type of exam, career choice) or distant future (e.g., developing cancer from smoking); otherwise, outcome relevance was coded as low. For example, manipulations of outcome relevance had participants select potential dates assuming that they would (high outcomes relevance) or would not (low outcome relevance) actually date the person (Lowe & Steiner, 1968).

We coded the utility of the available information presented for selection as high or low for fulfilling an experimental goal. Utility was high if the available information was high or moderate in quality and novel, and could facilitate accomplishing an immediate goal in the session (e.g., deciding whether to extend the contract of a manager, or writing an essay to justify their beliefs, attitudes or behaviors) or low if it was low quality and familiar, and could not facilitate accomplishing an immediate goal. When no such goal was present, utility was coded as no goal. We also coded the relative utility of the available congenial and uncongenial information presented for selection (congenial more useful; equally useful; uncongenial more useful). Conditions were coded as equally useful when there was no immediate goal in the session or the congenial and uncongenial information were judged equally likely to facilitate or hinder goal attainment. For example, the congenial and uncongenial information would be equally useful for preparing to select among gifts (Jonas et al., 2005). However, uncongenial information would be more useful for preparing to debate (e.g., Canon, 1964) or to write an uncongenial essay (Hillis & Crano, 1973). Congenial information would be more useful for planning to discuss one's opinion (Canon, 1964; Smith, Fabrigar, Powell, & Estrada, 2007) or to defend one's attitudes, beliefs, or behaviors (Frey, 1981b; Lundgren, & Prislin, 1998).

Results

Distribution of Effect Sizes

Our effect sizes are displayed in the stem-and-leaf plot in Figure 2. We first analyzed the distribution of effect sizes to check for potential biases in the study retrieval or publication. To estimate potential study retrieval and publication biases, we examined the funnel plot of effect sizes (see Figure 3) and the normality of the distribution under examination (see Figure 4). For Figure 3, if no bias is present, the plot should take the form of a funnel centered on the mean effect size, with smaller variability as the sample size increases. Instead, in the presence of publication bias, there is a distortion in the shape of the funnel. If the true effect size is zero and there is bias, the plot has a hollow middle. If the true effect size is not zero, the plot tends to be asymmetrical, having a large and empty section where the estimates from studies with small sample sizes and small effect sizes would be located in the absence of bias. Following these guidelines, an examination of the plot in Figure 3 suggests no retrieval or publication bias.

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Stem-and-leaf plot of effect sizes (ds).

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This funnel plot presents mean effect sizes on the Y-axis and sample sizes on the X-axis; a symmetric and inverted funnel shape suggests no publication bias

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Normal quantile plot. The line on the diagonal indicates normality; the lines around the diagonal represent the 95% confidence interval around the normality line.

In addition to examining the funnel plot, we used the normal-quantile plot method to uncover evidence of bias (Wang & Bushman, 1999). In a normal-quantile plot, the observed values of a variable are plotted against the expected values given normality. If the sample of effect sizes is from a normal distribution, data points cluster around the diagonal; if the sample of effect sizes is biased by publication practices or eligibility criteria, data points deviate from the diagonal (Wang & Bushman, 1999). As can be seen from Figure 4, the standardized effect sizes followed a straight line and generally fell within the 95% confidence intervals of the normality line.

Study Characteristics

Prior to testing our hypotheses, we examined some descriptive characteristics of the samples in our meta-analysis. As shown in Table 2, samples generally (a) were published in earlier decades, (b) appeared in journals, (c) included college students as participants, (d) took place in The United States and Canada, and (d) with the exception of a minority of field studies, took place in the laboratory. In terms of the issues, conditions generally used issues that were (a) political (e.g., scandals, campaign issues, war); (b) real (e.g., abortion) rather than artificial (e.g., a bogus hiring decision); and (c) specific in scope (e.g., extending the contract of a particular manager) rather than general (e.g., euthanasia). Choices of information to receive were most frequently assessed and most often made between two pieces of congenial information and two pieces of uncongenial information. Information choices were most often predicted from measures of prior behaviors and measures that were not anonymous in the experimental setting. The congenial and uncongenial information offered for selection was most often novel rather than familiar.

Table 2

Distribution of Descriptive Moderators

VariablesValue
Median publication year1981
Publication form
 Journal article279 (93%)
 Unpublished document8 (3%)
 Dissertation or master's thesis7 (2%)
 Book chapter6 (2%)
Participant population
 University students252 (84%)
 High school students35 (12%)
 Other or mixed13 (4%)
Country where study was conducted
 United States and Canada147 (49%)
 Germany139 (46%)
 Australia10 (3%)
 Italy4 (1%)
Research setting
 Lab257 (86%)
 Field43 (14%)
Issue type
 Politics72 (24%)
 Organization and business administration70 (23%)
 Personal development, personal health, self-related69 (23%)
 Religion and values51 (17%)
 Buying behavior, game play, or betting38 (13%)
Artificiality of issue
 Real219 (73%)
 Artificial or bogus81 (27%)
Generality of issue
 Specific169 (56%)
 General131 (44%)
Exposure measure
 Choice of information to receive197 (66%)
 Rating of information preference85 (28%)
 Ranking of information preference18 (6%)
Modal amount of congenial information offered2
Modal amount of uncongenial information offered2
Predictor
 Behavior194 (65%)
 Attitude63 (21%)
 Belief43 (14%)
Anonymity of attitude, belief, or behavior
 Not anonymous224 (75%)
 Anonymous76 (25%)
Novelty of congenial and uncongenial Information
 Familiar13 (4%)
 Novel287 (96%)

Note. Unless otherwise specified, values are number of conditions or samples, with percents in parentheses.

The distributions of other important descriptive characteristics appear in the third column of Table 3. For moderators relevant to defense motivation, typically (a) challenge or support of the pre-existing attitudes, beliefs, or behaviors was absent; (b) quality of the available congenial and uncongenial information for selection was high (vs. moderate or low); (c) commitment to the pre-existing attitude, belief, or behavior was moderate (vs. high or low); (d) reversibility of the pre-existing attitude, belief, or behavior was absent (irreversible; vs. present, reversible); (e) value relevance of the issues was low (vs. high); (f) closed-mindedness was high or low in the samples in which it was assessed; and (g) confidence in the pre-existing attitudes, beliefs, or behaviors was moderate (vs. low or high). For moderators relevant to accuracy motivation, a majority of the conditions pertained to issues that (a) were not outcome relevant and (b) did not provide an immediate goal in the session. In the conditions that did provide a goal, the available information presented for selection was generally high (vs. low) in utility. The correlations between the defense-motivation and accuracy-motivation moderators appear in Table 4. As one might expect, the quality of the congenial and uncongenial information intercorrelated highly, and the utility of the congenial and uncongenial information also intercorrelated highly. Although many of the other correlations were weak or non-significant, we used multiple-regression procedures to determine the independent contribution of each moderator.

Table 3

Moderator Analyses for All Included Studies

Moderator and leveld. k Fixed-effect QBFixed-adjusted effect QBRandom-effect QBRandom-adjusted effect QB
Challenge or support14.72***10.44**3.323.15
 Challenge0.27a24
 No challenge or support0.38a257
 Support0.16b19
Quality of available congenial information43.82***38.32***10.41**7.14*
 High0.41a173
 Moderate0.37a100
 Low0.00b23
Quality of available uncongenial information26.23***----7.64*----
 High0.40a173
 Moderate0.37a100
 Low0.01b23
Commitment to the attitude, belief, or behavior19.99***25.06***6.66*6.87*
 High0.42a117
 Moderate0.35b170
 Low0.13c13
Reversibility of the attitude, belief or behavior0.061.624.35*0.75
 Reversible0.37a114
 Irreversible0.36a186
Value relevance84.15***67.63***11.87***10.19**
 High0.51a120
 Low0.24b180
Closed-mindedness17.85***17.94***4.053.48
 High60.69a
 Moderate2880.36b
 Low60.11c
Confidence in attitude, belief, or behavior11.40**14.40***4.73#4.54
 High0.23a36
 Moderate0.37b224
 Low0.45 b40
Outcome relevance1.651.194.52*0.94
 High0.39a102
 Low0.35a198
Utility of congenial information31.59***0.4712.19**0.84
 High0.36a123
 No goal0.39a168
 Low−0.16c9
Utility of uncongenial information8.87**----1.26----
 High0.31a121
 No goal0.39b168
 Low0.51b11
Relative utility100.83***66.92***26.74***17.05***
 Congenial more useful0.54a17
 Both equally useful0.38b272
 Uncongenial more useful−0.39c11

Note; d. = weighted mean effect size; k = number of cases. QB = Homogeneity statistic distributed as a χ2 with degrees of freedom equal to the number of moderator levels minus one. Effect sizes (d.) were estimated using a fixed- and random-effects model. For d., positive numbers indicate approach to congenial information, whereas negative numbers indicated approach to uncongenial information. The fixed and random-effect QB reflect the between group effect of the moderator when entered independently into the respective model. To determine the significance of simple effects, a one-tailed criterion was used when a directional hypothesis was assessed; otherwise, a two-tailed criterion was used, d.s within columns not sharing subscripts are significantly different from each other at p < .05 when entered independently into the fixed-effect model. The fixed- and random-adjusted effect QB was estimated using the respective model with all (non-redundant) moderators in this table entered simultaneously into a regression equation.

#p < .10
*p < .05
**p < .01
***p < .001

Table 4

Inter-correlations between Moderators

Variable 1 2 3 4 5 6 7 8 9 10 11 12
Challenge or support (1)----−0.01−0.010.02−0.040.050.00−0.020.06−0.03−0.030.00
Quality congenial (2)----0.96**0.030.08−0.16**0.000.01−0.080.090.07−0.01
Quality uncongenial (3)----0.030.08−0.16**0.000.01−0.080.060.070.02
Commitment (4)----0.020.020.000.080.13*0.080.05−0.07
Reversibility (5)----−0.040.00−0.010.090.57**0.58**0.03
Value relevance (6)----0.000.010.16**−0.19**−0.17**0.01
Closed-mindedness (7)----0.000.000.000.000.00
Confidence (8)----0.020.060.060.00
Outcome relevance (9)0.12*0.12*0.03
Utility congenial (10)0.81**−0.25**
Utility uncongenial (11)0.16**
Relative utility (12)----

Note. Entries are Spearman's correlation coefficients. Levels of the moderators were coded as follows: challenge or support (1= support; 2 = no challenge or support; 3 = challenge), quality congenial and uncongenial (1 = low; 2 = moderate; 3 = high), commitment (1 = low; 2 = moderate; 3 = high), reversibility (1 = irreversible; 2 = reversible), value relevance (1 = low; 2 = high), closed-mindedness (1 = low; 2 = moderate; 3 = high), confidence (1 = low; 2 = moderate; 3 = high), outcome relevance (1 = low; 2 = high), utility congenial (1 = low; 2 = moderate; 3 = high), utility uncongenial (1 = low; 2 = moderate; 3 = high), relative utility (1 = congenial more useful; 2 = both equally useful; 3 = uncongenial more useful).

*p < .05
**p < .01

Average Exposure Effect Size and Between-Effect Variability

We first obtained a weighted-mean average of information preferences and tested for variability among effect sizes. The average effect was d. = 0.36 (95% CI = 0.34, 0.39) according to fixed-effects analysis, indicating a moderate congeniality bias, and d. = 0.38 (95% CI = 0.32, 0.44) according to the random-effects analysis, indicating a moderate congeniality bias as well. Both of these average effects were statistically different from zero, Q (299) = 611.57, p < .001 for the fixed-effects analysis and Q (299) = 132.02, p < .001 for the random-effects analysis, and were heterogeneous, Q (299) = 1,354.55, p < .001 for the fixed-effects analysis and Q (299) = 372.45, p < .001 for the random-effects analysis. Notably, the mean unweighted effect size of 0.38 was similar to both of these estimates.

Moderator Analyses

Because there was a large amount of variability between effect sizes, we tested whether our moderators accounted for a significant amount of this variability. Generally, the results from fixed- and random-effects models converged. Thus, we focus on the fixed-effects models, which are more powerful, and are summarized in columns four and five of Table 3 (but see the sixth and seventh column of Table 3 for random-effects results). Table 3 presents analyses of all conditions, which provide the most complete description of our synthesis. Table 5 presents analyses using only the effect sizes for which the levels of the moderator varied within a study; these analyses protect against different levels of a moderator being spuriously confounded with study characteristics. Therefore, the Table 3 analyses included all samples, whereas the Table 5 analyses relied on studies with manipulations or partitioning based on a particular moderator. Importantly, the patterns of cell means were generally similar across these two types of analyses.

Table 5

Moderator Analyses for Studies with Variability in the Levels of Moderators

Moderator and leveld. k Fixed-effect QBRandom-effect QB
Challenge or support2.211.07
 Challenge0.27a24
 No challenge or support0.15a11
 Support0.16a19
Quality of congenial information24.14***4.49*
 High0.55a8
 Low−0.01b8
Quality of uncongenial information4.53*1.33
 High0.38a8
 Low0.13b8
Commitment to the attitude, belief, or behavior21.80***7.97*
 High0.43a54
 Moderate0.24b57
 Low0.15b9
Reversibility of the attitude, belief or behavior0.410.24
 Reversible0.10a6
 Irreversible0.18a6
Value relevance10.58**4.24*
 High0.80a6
 Low0.33b6
Closed-mindedness17.82***4.02*
 High0.69a6
 Low0.11b6
Confidence in attitude, belief, or behavior18.87**5.82#
 High0.19a30
 Moderate0.29a16
 Low0.53b20
Outcome relevance0.671.58
 High0.22a25
 Low0.28a23
Utility of congenial information21.82***6.68*
 High0.32a21
 No goal0.13b10
 Low−0.17c9
Utility of uncongenial information25.59***9.25**
 High0.13a19
 No goal0.13a10
 Low0.74b7
Relative utility92.48***23.48***
 Congenial more useful0.54a17
 Both equally useful0.19b13
 Uncongenial more useful−0.39c11

Note. d. = weighted mean effect size; k = number of cases. QB = Homogeneity statistic distributed as a χ2 with degrees of freedom equal to moderator levels minus one. Effect sizes (d.) were estimated using a fixed- and random-effects model. For d., positive numbers indicate approach to congenial information, whereas negative numbers indicated approach to uncongenial information. The random effects QB reflect the between-group effect of the moderator when entered independently into the random-effects model. The fixed effects QB reflect the between-group effect of the moderator when entered independently into the fixed-effects model. To determine the significance of simple effects, a one-tailed criterion was used when a directional hypothesis was assessed; otherwise, a two-tailed criterion was used. d.s within columns not sharing subscripts are significantly different from each other at p < .05 according to the fixed-effect model.

#p < .10
*p < .05
**p < .01
***p < .001

Defense Motivation

Six of seven of our findings provided at least partial support for the hypothesis that defense motivation enhances the congeniality bias (see Figure 1). First, as anticipated, the congeniality bias was smaller when there was support rather than no challenge or support of the preexisting attitude, belief, or behavior prior to information selection. However, the congeniality bias was not larger when there was a challenge rather than no challenge or support prior to information selection. Second, as predicted, the congeniality bias was larger when the uncongenial or congenial information available for selection was high or moderate in quality (vs. low), although the high and moderate levels did not differ from one another. Third, as anticipated, the congeniality bias was larger for samples with high than moderate commitment to an attitude, belief, or behavior and smaller for samples with low than moderate commitment. Fourth, the congeniality bias was larger when the value relevance of the issue was high than low. Fifth, as expected, the congeniality bias was larger for samples high in closed-mindedness (vs. moderate) and smaller for samples low in closed-mindedness (vs. moderate). Sixth, the congeniality bias was smaller among samples with high (vs. moderate or low) confidence in the attitude, belief, or behavior. Although many of the findings supported the hypothesis that defense motivation enhanced the congeniality bias, one finding did not. Specifically, although the fixed-effects analysis showed that the congeniality bias was not influenced by whether the attitude, belief, or behavior was reversible, the random-effects analysis showed that the congeniality bias was larger when the attitude, belief, or behavior was reversible (vs. irreversible; d = 0.47 vs. 0.32).

Accuracy Motivation

Most of our major findings were consistent with the hypothesis that accuracy motivation can guide information selection (see Figure 1). First, as anticipated, the congeniality bias was larger when the congenial information was highly useful relative to when it was not useful or when there was no experimental goal. In fact, an uncongeniality bias appeared when the congenial information was not useful. Second, the congeniality bias was smaller when the uncongenial information was high than low in utility or when there was no goal. Third, as hypothesized, the congeniality bias was larger when the congenial information was more useful than the uncongenial information rather than when they were equally useful. In addition, the congeniality bias was smaller (and reversed) when the uncongenial information was more useful than the congenial information rather than when they were equally useful. Two findings were inconsistent with the hypothesis that accuracy motivation guides exposure decisions. First, although the fixed-effects analysis showed that the congeniality bias was not influenced by the outcome relevance of the issue, the random-effects analysis showed that the congeniality bias was larger when issues were high in outcome relevance (vs. low; d = 0.48 vs. 0.33). Second, the congeniality bias was larger when the uncongenial information was high or moderate in quality rather than low in quality. This latter finding, as mentioned earlier, supports defense motivation predictions more than accuracy motivation predictions.

Defense Motivation vs. Accuracy Motivation: Relative Contributions

To examine the relative influence of defense and accuracy motivations on the congeniality bias, we entered all seven non-redundant defense motivation moderators (i.e., challenge or support, quality of available congenial information, commitment, reversibility, value relevance, closed-mindedness, confidence) and the two accuracy motivation moderators (i.e., relative utility, outcome relevance) into a hierarchical regression analysis. Prior to entering these variables, they were dummy-coded with l - 1 dummy codes for each variable, where l represents the number of levels in the moderator. For example, challenge or support had two dummy codes. One dummy code represented a comparison between challenge and the other two groups (1 = challenge, 0 = support and no challenge or support), and the other dummy code represented a comparison between support and the other two groups (1 = support, 0 = challenge and no challenge or support). Note that when these two dummy codes are entered into a regression equation simultaneously, they completely account for the effect of the variable on congeniality (for more on dummy-coding see Keith, 2006).

The congeniality bias was predicted using a hierarchical-regression analysis with the defense-motivation moderators entered in the first step and the accuracy-motivation moderators entered in the second step. This analysis revealed that the defense-motivation moderators alone accounted for a significant amount of variance (13%; QR = 179.64, p < .001). Importantly, adding the accuracy-motivation moderators accounted for an additional 7% of the variance, which was significant (QR = 90.61, p < .001). Thus, it seems that both of these variables may contribute to selective exposure, but as the moderate-sized congeniality bias (d. = 0.36) would imply, defense motivation has a greater influence. Indeed, when we entered the accuracy-motivation moderators in the first step and defense-motivation moderators in the second step (i.e., reversed the order of entry), results were similar (accuracy accounted for 8% and defense accounted for 13% of the variance). Note that the individual effects of the moderators in this analysis are presented in the fifth column of Table 3.

Supplementary Analyses and Analyses of Descriptive Moderators

Comparing the analyses of the studies that varied the levels of the moderator (Table 5) with the analyses of all conditions (Table 3), we find a large amount of agreement. As can be gleaned from Table 5, the patterns of cell means were comparable for all nine of the moderator analyses that were significant according to both analyses. Challenge or support was the only moderator that failed to reach conventional levels of significance for this analytic approach but did for the analyses of all conditions.

Table 6 contains analyses for the descriptive moderators. Of the 16 descriptive moderators, 12 were significant predictors of information selection. The year the paper was published and the amount of congenial and uncongenial pieces of information in the selection array were each positively correlated with congeniality scores. In addition, congeniality biases were generally larger when reported in dissertations and theses, when the study concerned religion and values or politics, when the issues were real and general, when belief (vs. attitudes and behaviors) was the predictor, when participants ranked the information, and when the samples were not composed entirely of college and high school students. Possible interpretations of these findings appear in the general discussion.

Table 6

Descriptive Moderator Analyses

Moderator and level B k Fixed-effect QBFixed-effect adjusted QBRandom-effect QB
Publication year (Median = 1981)0.2030053.24***13.67**14 74***
Amount of congenial information (Mode = 2)0.082847.70**4.65*6.37*
Amount of uncongenial information (Mode = 2)0.082847.96**5.25*6.49*
d.
Publication form53.63***47.66***6.69
 Journal article0.35a279
 Book chapter0.25a6
 Dissertation or master's Thesis1.00b7
 Unpublished document0.28a8
Country where study was Conducted0.512.094.59
 United States and Canada0.37a147
 Germany0.37a139
 Australia0.34a10
 Italy0.29a4
Research setting0.010.330.06
 Laboratory0.36a257
 Field0.36a43
Issue type50.38***4.6712.59**
 Politics0.46a72
 Organization and business administration0.20b70
 Personal development, personal, health, self-related issues0.36c69
 Religion, and values0.48a51
 Buying behavior, game play, or betting0.27bc38
Artificiality of issue8.61**0.410.12
 Real0.39a219
 Artificial or bogus0.28b81
Generality of issue84.34***10.96***14.49***
 Specific0.23a169
 General0.50b131
Predictor34.41***11.43**0.39
 Behavior0.29a194
 Attitude0.42b63
 Belief0.53c43
Exposure measure: Choice of information to receive12.32***1.234.29*
 Yes0.41a186
 No0.30b114
Exposure measure: Rating of Preference25.00***33.56***12.24***
 Yes0.26a85
 No0.42b215
Exposure measure: Ranking of Preferences6.10*15.54***1.99
 Yes0.51a18
 No0.35b282
Participant population21.83***26.69***5.81#
 University students0.35a252
 High school students0.35a35
 Other or mixed0.66b13
Anonymity of attitude, belief, or behavior16.08***0.031.72
 Not anonymous0.32a224
 Anonymous0.45b76
Novelty of congenial and uncongenial information0.540.070.44
 Familiar0.3113
 Novel0.37287

Note. B = slope; d. = weighted mean effect size; k = number of cases. QB = Homogeneity statistic distributed as a χ2 with degrees of freedom equal to one minus the levels of the moderator. Effect sizes (d) were estimated using a fixed- and random-effects model. For d, positive numbers indicate approach to congenial information, whereas negative numbers indicated approach to uncongenial information. The fixed effect (random effect) QB reflects the between group effect of the variable when entered independently into the fixed effects (random-effects) model. The fixed-adjusted effect QB was estimated using the respective model with all (non-redundant) defense and accuracy moderators entered simultaneously into a regression equation. To determine the significance of simple effects, a two-tailed criterion was used, d.s within columns not sharing subscripts are significantly different from each other at p < .05 according to the fixed-effect model.

#p < .10,
*p < .05,
**p < .01,
***p < .001

GENERAL DISCUSSION

People's attitudes and behaviors are often inappropriate and inaccurate, as is the case when investors make a poor investment decision, physicians misdiagnose patients, and children persist in their belief in Santa Claus. Although information relevant to these attitudes and behaviors can provide opportunities for change, our review demonstrates biases in what information is selected for reception. People are almost two times (OR = 1.92, based on d. = 0.36) more likely to select information congenial rather than uncongenial to their pre-existing attitudes, beliefs, and behaviors. The moderate size of the bias is perhaps not surprising given that selective exposure is responsive to motivations that can occasionally exert opposing influences on selection preferences. As our analyses have shown, variables associated with defense motivation (e.g., commitment, value relevance, confidence, and challenge or support) uniformly increased the selection of congenial information. In contrast, information utility, a moderator associated with the accuracy motivation, increased or decreased the preference for congenial information, depending on whether the congenial or uncongenial information possessed a utility advantage. Selecting congenial information can facilitate feeling validated about one's view or even maintaining stable views of the world but may reduce accuracy and flexibility. Hence, the occasionally opposing influences of defense and accuracy motivation create a balance between defending prior views and obtaining realistic views of an object or issue.

Motivational Factors

Several theorists have proposed that accuracy and defense motivations guide human behavior (e.g., Chaiken et al., 1996; Jonas et al., 2005; Katz, 1960; Smith, Bruner, & White, 1956; Wyer & Albarracín, 2005). People are presumed to want to believe in the accuracy of their views (a result of defense motivation) but also attain views that are rooted in external reality (a result of accuracy motivation; for broader theories, see Baumeister, 2005; Schlenker, 1980). Consistent with this notion of human motivation (see Figure 1), our meta-analysis confirmed that exposure decisions are guided by defense and accuracy motivation.

Defense Motivation

The majority of our findings showed that a congeniality bias increases as a function of factors that presumably increase defense motivation. As expected, the congeniality bias was positively correlated with information quality, commitment, value-relevance, and closed-mindedness, but negatively correlated with confidence in or support given to one's pre-existing attitude, belief, or behavior. Although the majority of our findings suggested that defense motivation affects selective exposure, one finding did not. In particular, we predicted that irreversible decisions would promote a greater congeniality bias because people experience greater affective attachment to their irreversible decisions than their reversible ones (Kiesler, 1971; Schlenker, 1980). Although a fixed-effects analysis revealed that the ability to reverse a pre-existing attitude, belief or behavior had no effect on the congeniality bias, a random-effects analysis showed that the congeniality bias was larger when prior attitudes, beliefs, or behaviors could be reversed.

Another possible interpretation of the reversibility effect is that the ability to change one's position may enhance the experience of cognitive dissonance by prompting a consideration of reasons to change the position. For example, the possibility for change may automatically direct attention to why the unchosen position might be better than the chosen position. Consequently, dissonance arousal may be greater and congeniality more pronounced under reversible-decision conditions. Alternatively, the perceived ability to change one's position may enhance attempts to crystallize and defend this position (Dewey, 1938; Kruglanksi, 1990; Lewin, 1951; Pierce, 1877; Tajfel, 1969). Yet another possibility is that the perceived ability to change a decision enhances the congeniality bias by directly improving memory for the contents (e.g., beliefs) and decision-making strategies (e.g., congenial information searches) associated with that incomplete decision (Zeigarnik, 1927). Future work may disentangle these possibilities, perhaps as a function of individual differences in variables such as closed-mindedness (e.g., need for cognitive closure) and through assessments of memory. At present, the accumulated data are insufficient to explore these issues further.

Accuracy Motivation

Our meta-analysis revealed that participants selected information that best suited the goal they were pursuing in the session. Studies showed that selection favored congenial information when the congenial information was useful but favored uncongenial information when the uncongenial information was useful. Less supportive of the role of accuracy motivation in selective exposure were associations involving information quality and outcome relevance. The expected preference for high-quality congenial information was present, even though the expected preference for high-quality uncongenial information was absent. Importantly, this pattern was entirely consistent with the role of defense motivation but was only partially consistent with the role of accuracy motivation. Also, contrary to the possibility that outcome relevance negatively correlates with the congeniality bias, the random-effects analysis showed that the correlation was positive. However, closer inspection revealed that outcome relevance was correlated with value relevance (rs = .16, p = .005; see Table 4). In an analysis controlling for value relevance, outcome relevance no longer had a significant effect on congeniality (p > .10).

Effects of Descriptive Variables

Some of the effects of the descriptive variables on the congeniality bias (see Table 6) might reflect defense and accuracy motivation. For example, the findings that congeniality biases are enhanced for general issues, real issues, and belief-relevant topics may reflect enhanced defensiveness in these conditions. Real and belief-relevant issues are also more value relevant, and so value relevance should be responsible for these associations. Indeed, in analyses controlling for value relevance, neither variable significantly predicted the congeniality bias (ps > .10). Why general rather than specific issues (e.g., capital punishment vs. the guilt of a defendant) enhances the congeniality bias is less clear but might reflect the fact that general issues bring to mind many specific beliefs, attitudes, and behaviors. If so, disagreement on general issues may arouse more cognitive conflict than disagreement on specific issues.

Still other findings may support a cognitive mechanism affecting the congeniality bias. For example, the positive association between congeniality and the number of pieces of congenial and uncongenial information in the selection array might suggest that larger arrays make prior attitudes and behaviors more accessible as a basis for the selection. Alternatively, larger arrays may create a cognitive load and hence promote tendencies to rely on heuristics that promote congenial selections (e.g., “if it is (un)congenial, then it is probably (un)reliable”). We also found that congeniality biases were greater when information preferences were measured by rankings as opposed to ratings or yes/no selections. Perhaps ranking methods require more thought about the information and thereby aid retrieval of past views. Alternatively, ranking methods may force direct comparisons among the information in the array and therefore better highlight the congeniality or uncongeniality of each piece of information. Further, the finding that student samples exhibited a smaller congeniality bias than non-student or mixed samples may be due to more mature individuals' practice with selective exposure. Student samples are ordinarily younger than non-student samples and therefore have less experience with the selective exposure process and less developed views (Sears, 1986).

Additional findings may reflect publication practices or methodological changes over time. For example, the congeniality bias was larger in unpublished reports as opposed to published reports. Perhaps the controversial history of selective exposure led journal editors to publish various types of findings, including null ones (see review by Freedman & Sears, 1965). Also, the positive correlation between report year and congeniality may reflect improved methodologies through the years. Researchers now possess more refined experimental methods and a better grasp of the competing causes of information selection that must be controlled when studying this issue.

Our Review in the Context of the Past Reviews

More than two decades have passed since Frey's (1986) and Cotton's (1985) influential reviews of selective exposure. Guided at least in part by these reviews, many new research reports with innovative methods have emerged since 1986. This accumulation of new data created an ideal opportunity for a review that quantifies the congeniality bias and determines its variability. In doing so, this meta-analysis yielded some conclusions that support the earlier reviews and some that do not.

Our study strongly supported the earlier conclusion that defense motivation enhances the congeniality bias (Cotton, 1985; Frey, 1986). Some our findings, however, were not obtained in past reviews. For example, past reviews concluded that attitudinal confidence and congeniality are unrelated (Cotton, 1985; Freedman & Sears, 1965), but our results suggested that congeniality is weaker at high (vs. low or moderate) levels of confidence. Also, whereas Frey (1986) concluded that congeniality is stronger when decisions are irreversible than reversible (Frey, 1986), our results revealed that congeniality is stronger when decisions are reversible. Yet, Frey's conclusion was based on only two studies (Frey, 1981c; Frey & Rosch, 1984), the first of which presented only congenial information.

In addition to exploring defense motivation, which was the theoretical foundation for the reviews by Cotton (1985) and Frey (1986), our analysis highlighted the critical role of accuracy motivation. Our conclusions on accuracy motivation are reminiscent of Freedman and Sears' (1965) view that, although attitudinal selectivity can occur, utility may be a more important guide for information choices. Consistent with this notion, our study showed a moderate-size uncongeniality bias when the uncongenial information was clearly of higher utility than the congenial information. Our estimates suggested that both defense and accuracy motivations predict exposure decisions but, as the mean effect size signals a predominance of congeniality, defense is a stronger predictor.

Our review has greatly amplified understanding of the variability of selective exposure effects. Whereas past reviews have analyzed effects of moderators only within individual studies, our study examined their effects both between and within studies. Moreover, by coding all studies on all moderators, our conclusions regarding moderators are based on far more information than prior reviews. The new moderators we introduced also proved to be important. For example, we assessed the effect of value relevance on selective exposure and found greater congeniality for high (vs. low) value-relevant topics. All in all, our review advances the selective exposure literature well beyond past reviews.

Future Directions

Congeniality at Other Stages of Information Processing

Past research has examined whether congeniality biases exist at all stages of information processing—exposure, interpretation, and memory. To date, however, only congeniality biases at exposure and memory have been estimated meta-analytically. In this regard, the current review estimated the congeniality bias at exposure to be moderate in size (d. = 0.36) and influenced by accuracy and defense motivations. In contrast, the congeniality bias in memory was smaller (d. = 0.23, albeit artificially increased by methodological problems that were prevalent in earlier studies) and was also moderated by accuracy and defense motivations (Eagly et al., 1999). The variance of the overall size of congeniality bias across these two stages is interesting and might suggest that the strength of defense and accuracy motivation vary accordingly. Therefore, to get a clearer picture of congeniality biases, future research should explore the size and variability of the bias at information interpretation (Bargh, 1999; Bruner, 1957; Darley & Gross, 1983; Duncan, 1976; Hastorf & Cantril, 1954; Lord, Ross, & Lepper, 1979).

Cognitive Factors in Selective Exposure

Although motivational mechanisms appear to underlie selective exposure, cognitive mechanisms are also likely to be critical. For example, the congeniality bias might increase along with people's ability to retrieve past attitudes, beliefs, and behaviors (e.g., attitude accessibility). Attitudes, beliefs, and past behaviors may automatically influence information selection by making the selections consistent with the retrieved attitude, belief, or behavior (e.g., Chen & Bargh, 1999; Greenwald, McGhee, & Schwartz, 1998). In addition, the ability to retrieve these tendencies may make congenial information easier to process than uncongenial information and hence more attractive (Winkielman & Cacioppo, 2001). Such considerations were not amenable to testing within this meta-analysis, and they are prime candidates for future research. For example, studying the development of selective exposure may show that older children (who have greater resources to recall prior attitudes and behaviors) show an enhanced congeniality bias compared to younger children. In addition, examining factors that affect attitude retrieval may show that factors that impede retrieval of prior attitudes (e.g., distraction) decrease the congeniality bias.

Impression Motivation and Selective Exposure

The kind of information that people select can convey preferences and other personal attributes, leading them to attempt to strategically manage their selections to establish a desired identity. In our meta-analysis, a tendency towards trying to appear unbiased was revealed by a weaker congeniality bias when attitudes, behaviors, and beliefs were not anonymous relative to anonymous (see Table 6). Nonetheless, future research should investigate self-presentation issues in greater depth. For example, the presence of an audience may affect selective exposure by affecting the perceived desirability of appearing receptive versus resolute (Schlenker, 1980, 1985, 2003; see Jonas et al., 2005). In addition to manifesting strategic forms of impression management, people may select information to develop (or maintain) relationships and create a shared reality with likeable others (Higgins, 1992). For example, to maintain a relationship with an attractive group, an individual may select information consistent with its views (Lundgren & Prislin, 1998). In contrast, to cut ties from an unattractive group, an individual may select information inconsistent with its views.

Controlled and Automatic Processes Underlying Selective Exposure

A critical consideration for changing and alerting individuals about biases in information selection is whether the selective exposure process is controlled or automatic (e.g., Fiske & Taylor, 1991; Shiffrin & Schneider, 1977). Yet, little research has addressed this question to date. On the one hand, people may make a conscious decision to select congenial information. In this case, the process of selecting information is effortful and intentional, and it occurs with conscious awareness and may be intentionally interrupted. On the other hand, people may reduce dissonance without conscious awareness or intention. In a dramatic demonstration of this fact, patients who suffered from anterograde amnesia (i.e., a condition that prevents the formation of new memories) re-ranked a piece of artwork more positively when they had previously chosen it than when they had not (Lieberman, Ochsner, Gilbert, & Schacter, 2001, Study 1). By the same token, then, defense motivation (and possibly accuracy motivation) may be elicited automatically after retrieving an attitude or making a decision. In this situation, the effects of prior attitudes, beliefs, or behaviors on exposure could be effortless, unintentional, devoid of awareness, and uncontrollable.

To our knowledge, only Fischer et al. (2005, Study 3) have studied the automatic nature of selective exposure. In their study, participants were asked to decide whether to extend the contract of a fictitious manager and then were offered additional information about the manager in either distracting (cognitive load) or nondistracting (control) conditions. The congeniality bias was smaller (and nonsignificantly reversed) in the cognitive-load condition than in the control condition, suggesting a controlled process. Importantly, however, information selection may be more or less automatic depending on the nature of the pursued goals. Defense motivation may be easily satisfied by selecting congenial information, whereas accuracy motivation may require complex procedures that involve conscious monitoring. For example, satisfying defense motivation may require monitoring the direction and quality of the information in relation to a prior attitude, belief, or behavior. In contrast, satisfying accuracy motivation may require monitoring the direction and quality of the information as well as attending to and correcting for any systematic biases in exposure (e.g., Harkness, DeBono, & Borgida, 1985; McAllister, Mitchell, & Beach, 1979; Tetlock, 1983; Tetlock & Kim, 1987). Given these possibilities, future research might explore the automatic and controlled processes that influence information selection.

Increasing (or Decreasing) Exposure through Goal Accomplishment

The motivation to defend an attitude may lead to seeking more congenial than uncongenial information until defense motivation is satisfied, at which point this motive may become deactivated or inhibited (Zeigarnik, 1927). As a result, if defense or accuracy motivation is satisfied by means of behaviors other than selective exposure (e.g., self-affirmation; Steele, 1988), effects on exposure may be attenuated or possibly reversed. Performing mathematical calculations correctly, for example, may increase the congeniality bias if this behavior satisfies accuracy motivation. This prediction is counterintuitive because the calculations could potentially activate accuracy-related procedures, thus enhancing rather than reducing accuracy.

Another issue deserving of future research is whether satisfaction of defense or accuracy motivation in one information-search domain affects future information selection in other domains. For example, allowing an individual to satisfy defense motivation by selecting and reading congenial information on abortion may result in less defensiveness when selecting information on euthanasia. Such a possibility has important implications for daily life because people often search for information about more than one issue.

Practical Implications of Our Meta-Analysis

Although our study implemented a correlational method to assess the effects of various factors on the congeniality bias and hence possesses the weaknesses associated with this method, it is unlikely that unidentified differences across the studies and conditions could completely account for the effects of the moderators on the congeniality bias. For example, we found that the effects of the moderators generally replicated using only effect sizes from studies that measured or manipulated the moderator variable of interest. In addition, multiple regression analyses showed that the effects of the moderators generally remained significant even after controlling for the other moderators. Also, we employed various measures of the motivational processes that were of interest (see Figure 1), and the alternate measures generally had the same effect on the congeniality bias.

Health-Promotion Intervention Planning

Selective exposure can have implications for the health and well-being of a society. For example, a recent meta-analysis of intervention acceptance and attrition found that about a quarter of eligible participants turned down an opportunity to participate in an HIV-prevention program (Noguchi, Albarracin, Durantini, & Glasman, 2007). Even more unfortunate, people who rarely wear condoms and hence are most in need of prevention programs were more likely to turn down these programs than people who consistently wear condoms (Noguchi et al., 2007). Presumably, individuals in need of intervention programs are more likely to avoid them because they anticipate that the programs will challenge their behavior.

Despite this resistance, there may be several strategies for increasing participation among an unwilling audience. Individuals may be motivated to attend such programs when the intervention is perceived as facilitating the attainment of valued goals. For example, people may have an inherent need to help others, especially their children (Baumeister, 2005; Maslow, 1968) but not be aware of how this goal can be facilitated by taking part in an HIV intervention program. If a program is framed as facilitating the ability to provide important knowledge that can be transmitted to one's children and family, people may participate to that end. This approach seems plausible given our finding that people seek uncongenial information when the information facilitates achieving a current goal (i.e., helping others in this case). Furthermore, prevention programs may increase acceptance rates by minimizing cues that can trigger defense motivation. For example, people may be more willing to participate in a program called a “health discussion group” than an “HIV intervention group” or “HIV counseling group.” By implying an intention to produce change, such words as “intervention” and “counseling” may automatically strengthen defense motivation and increase tendencies to avoid the program (Albarracin et al, in press).

Democracy and Selective Exposure

Individual choice rather than governmental choice of information is characteristic of a democracy. Moreover, democracies rely on the ability of citizens to access a range of available information and make intelligent choices based on this information. Despite having relatively few governmental restrictions on information, citizens may select certain newspapers, televised-news programs, radio programs, and magazines that suit their political ideology. A 2004 survey by The Pew Research Center found that Republicans are about 1.5 times more likely to report watching Fox News regularly than Democrats (34% for Republicans and 20% of Democrats). In contrast, Democrats are 1.5 times more likely to report watching CNN regularly than Republicans (28% for Democrats vs. 19% of Republicans). Even more striking, Republicans are approximately five times more likely than Democrats to report watching “The O'Reilly Factor” regularly, and are seven times more likely to report watching “Rush Limbaugh” regularly.

Our review found a stronger congeniality bias for political issues than other issues (d = 0.46; see Table 6). Moreover, our review suggests strategies for increasing exposure to uncongenial political information among citizens. Individuals should be motivated to seek uncongenial political information when this information best suits their goals. For example, a strong motivation to debate an issue (vs. express one's view) may promote a search for uncongenial information with the objective of counterarguing it (e.g., Albarracín & Mitchell, 2004; Canon, 1964; see also Smith et al., 2007). In addition, citizens might be led to seek uncongenial information if political discussion is framed as an opportunity to build rapport (vs. establish interpersonal distance) with uncongenial audiences (see Lundgren & Prislin, 1998). These important issues deserve future research attention.

Closing Note

Although information selection could potentially proceed under the influence of the motivation to feel validated or the motivation to gain an accurate understanding of reality, our review suggests that both motivations are important. It seems likely that these often antagonistic tendencies may compensate for the potential dangers of seeking only self-validating or accurate information. Whereas defense motivation facilitates psychological stability and personal validation, accuracy motivation promotes accurate perceptions of reality. Given current evidence, however, it appears that tendencies toward congeniality prevail.

Acknowledgments

The research was funded by grants from the National Institutes of Health (K02-MH01861 and R01-NR08325). We thank the attitudes laboratories at the Psychology Departments of the University of Florida and the University of Illinois at Urbana-Champaign for discussion of the ideas reported in this paper. Also, we thank Shelly Chaiken, Blair Johnson, Tarcan Kumkale, and Moon-Ho Ringo Ho for their helpful comments on an earlier version of this paper and KyuHee Lee for her assistance in coding studies.

Footnotes

1Although confidence and commitment should exert opposite effects on selective exposure, they may, in practice, go hand-in-hand. Therefore, our predicted effect of confidence assumes that commitment is controlled at a moderate level and our predicted effect of commitment assumes that confidence is controlled at a moderate level.

2Partitioning studies in this way (versus only partitioning studies based on moderators of interest) allows a single study to contribute more than one effect size (e.g., each condition or sub-sample within a study contributes an effect size). Although such sub-samples within the studies of a meta-analysis are assumed to be statistically independent (e.g., Lipsey & Wislon, 2001; Raudenbush & Bryk, 2002), some researchers have suggested that sub-samples from the same study may share minor statistical dependencies even though the participants are different (see Wolf, 1990). For this reason, we re-analyzed our data after partitioning studies based on only the moderators of interest. Essentially, this procedure involved averaging effect sizes across moderators (not of interest) within a single study to reduce the number of effect sizes coming from that study (potential dependence). Of note, this change in partitioning procedure reduced the number of effect sizes to 211 (i.e., 70% of the original sample, 300). A majority of this decrease in the number of effect sizes (i.e., 89) can be attributed to only six papers (i.e., 40 effect sizes; or 45% of the decrease; Fischer et al., 2005, 2008; Frey, 1982; Frey, 1981a,b; Frey & Wicklund, 1978), in which moderators were not directly relevant to our theoretical framework (e.g., limited vs. unlimited searches), or had additional levels of one of our moderator of interest (e.g., high, moderate or low levels of challenge). This more conservative partitioning procedure did not alter the pattern of our reported results for the moderator analyses.

To directly verify that our liberal partitioning strategy did not reduce the statistical independence of the effect sizes, we estimated the sampling error (see Lipsey & Wilson, 2001) for the effect sizes partitioned on only the moderators of interest (211 effect sizes; conservative partitioning strategy) and then for the effect sizes partitioned on the basis of the moderators used in the studies (300 effect sizes; liberal partitioning strategy). If the sampling error for the 211 effect sizes is larger than the sampling error for the 300 effect sizes, then the liberal (vs. conservative) partitioning procedure may have introduced dependencies in the data. Contrary to this possibility, however, the sampling error estimates were almost identical and thus suggested similar statistical independence. In fact, the sampling error for the sample of 211 (vs. 300) effect sizes was estimated to be slightly smaller (compare vθ = 0.23 vs. 0.24).

3Due to a limited number of reports containing the statistics required to compute this correlation, we also calculated the variance of within-subject effect sizes using three different correlations between the preferences for congenial and uncongenial information to reflect extreme (r = .00 and r = .99) and moderate correlations (r = .50; see also Albarracín et al., 2003, 2005). Notably, the results were very similar across these various correlations, so we present only the ones with the imputed correlation (see also Albarracín et al., 2003, 2005).

4Although fixed-effects models are “mixed” models (Raudenbush & Bryk, 2002), we chose to retain traditional meta-analytic terminology.

5In the case of a fixed-effects model, one assumes a fixed population effect size and estimates its sampling variance, which is an inverse function of the sample size of each group. As a result, effects sizes generated from larger samples are considered to be more precise estimates of the fixed effect size and hence are weighted more heavily than effect sizes obtained from smaller samples. In contrast, random-effects models assume that effect sizes are sampled from a population of effect sizes. Hence, an effect size results from sampling an effect size at random (from a population of values) in addition to measurement error, which is an inverse function of the sample size. Because random-effects models account for these two sources of error in an effect size, they yield a larger error term and less statistical power than fixed-effects procedures. However, one of the benefits of the random-effects model (vs. the fixed-effects model) is the ability to generalize its results to a broader universe of studies.

6In addition to comparing the congeniality bias across three groups of closed-mindedness, we compared only groups coded as high and low (see Table 5).

7Past research indicates a fairly direct relation of confidence to positive and negative affect (see Erber, 1991; Forgas & Moylan, 1987; Johnson & Tversky, 1983; Salovey & Birnbaum, 1989). Hence, we coded positive mood as high confidence and negative mood as low confidence. Eliminating these conditions did not alter our results.

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