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Le Cognitif Par Michel Serres

October 12, 2011

Pukat UGM : Memaafkan Koruptor Itu Ide Bodoh

July 30, 2011
tags:

Sabtu, 30/07/2011 06:04 WIB

Jakarta – Ketua DPR, Marzuki Alie, mencetuskan ide agar para koruptor dipulangkan dan dimaafkan. Namun ide tersebut dinilai kurang cerdas, dan kurang tepat, karena Indonesia tengah serius memberantas korupsi.

“Itu ide bodoh, paling tidak dia tahulah, kalau kasus korupsi di negara kita ini masih besar,” ucap Peneliti Pusat Kajian Antikorupsi (Pukat) UGM, Hifdzil Alim, kepada detikcom, Jumat (29/7/2011).

Hifdzil juga menolak usulan Marzuki yang meminta KPK dibubarkan. Menurutnya bila KPK dibubarkan tidak ada yang bisa dipercaya publik untuk menangani kasus korupsi.

“KPK ini didirikan, karena ketidakberhasilan Polisi dan Kejaksaan dalam memberantas korupsi,” lanjutnya.

Hifdzil mengatakan, sebaiknya Marzuki memahami betul peranan penting lembaga penegak korupsi. dengan demikian, Marzuki tidak akan sembarangan mengeluarkan pernyataan.

“Saya rasa Pak Marzuki, tidak paham soal itu, makanya dia asal komentar saja,” tutupnya.

Sebelumnya, Ketua DPR yang juga Wakil Ketua Dewan Pembina Partai Demokrat Marzuki Alie mengajak semua rakyat Indonesia untuk memulai hidup baru. Memaafkan koruptor dan membenahi sistem baru transaksi keuangan serta hukuman mati bagi para koruptor.

“Seluruh koruptor dipanggil pulang suruh bawa uangnya masuk, kenakan pajak. Kita saling memaafkan seluruh Indonesia, memaafkan koruptor, semuanya dimaafkan. Tuhan saja memaafkan semua manusia. Tapi tidak boleh mengulangi lagi, kalau diulangi dihukum mati,” ujar Marzuki.
Sumber :

(her/her)

Illuminati et la pédophilie

February 12, 2011

L’assassinat de Martin Luther King

February 12, 2011

The JFK Assassination – the Last Shot

February 12, 2011

Dramatic video as thousands clash with Egypt riot police in Cairo

February 12, 2011

Assassination of Anwar Sadat

February 12, 2011

The Rise and Fall of Husni Mubarak

February 12, 2011

Gender Similarities and Differences in Children’s Social Behavior: Finding Personality in Contextualized Patterns of Adaptation

February 6, 2011
Gender Similarities and Differences in Children’s Social Behavior: Finding Personality in Contextualized Patterns of Adaptation.
Authors:
Zakriski, Audrey L., Department of Psychology, Connecticut College, New London, CT, US, alzak@conncoll.edu
Wright, Jack C., Department of Psychology, Brown University, Providence, RI, US
Underwood, Marion K., School of Behavior and Brain Sciences, University of Texas at Dallas, Dallas, TX, US
Address:
Zakriski, Audrey L., Department of Psychology, Connecticut College, 270 Mohegan Avenue, New London, CT, US, 06320, alzak@conncoll.edu
Source:
Journal of Personality and Social Psychology, Vol 88(5), May, 2005. pp. 844-855
Publisher:
US: American Psychological Association
ISSN:
0022-3514 (Print)
1939-1315 (Electronic)
Language:
English
Keywords:
gender similarities; gender differences; children’s social behavior; personality; adaptation; social context
Abstract:
This research examined how a contextualist approach to personality can reveal social interactional patterns that are obscured by gender comparisons of overall behavior rates. For some behaviors (verbal aggression), girls and boys differed both in their responses to social events and in how often they encountered them, yet they did not differ in overall behavior rates. For other behaviors (prosocial), gender differences in overall rates were observed, yet girls and boys differed more in their social environments than in their responses to events. The results question the assumption that meaningful personality differences must be manifested in overall act trends and illustrate how gender differences in personality can be conceptualized as patterns of social adaptation that are complex and context specific. (PsycINFO Database Record (c) 2010 APA, all rights reserved) (from the journal abstract)
Subjects:
*Adjustment; *Human Sex Differences; *Individual Differences; *Personality; *Social Behavior; Childhood Development; Social Environments
Classification:
Psychosocial & Personality Development (2840)
Population:
Human (10)
Male (30)
Female (40)
Location:
US
Age Group:
Childhood (birth-12 yrs) (100)
Adolescence (13-17 yrs) (200)
Adulthood (18 yrs & older) (300)
Tests & Measures:
Wechsler Intelligence Scale for Children
Methodology:
Empirical Study; Longitudinal Study; Quantitative Study
Format Availability:
Electronic; Print
Format Covered:
Electronic
Publication Type:
Journal; Peer Reviewed Journal
Document Type:
Journal Article
Publication History:
Accepted Date: Dec 29, 2004; Revised Date: Aug 16, 2004; First Submitted Date: Jan 21, 2004
Release Date:
20050516
Copyright:
American Psychological Association. 2005.
Digital Object Identifier:
10.1037/0022-3514.88.5.844
PsycINFO AN:
2005-04675-009
Accession Number:
psp-88-5-844
Number of Citations in Source:
80
Database:
PsycARTICLES
By: Audrey L. Zakriski
Department of Psychology, Connecticut College
Jack C. Wright
Department of Psychology, Brown University
Marion K. Underwood
School of Behavior and Brain Sciences, University of Texas at Dallas

Acknowledgement: We thank the children, staff, and families whose cooperation made it possible to collect the data reported here. We are deeply grateful to Harry Parad, Director of Wediko Children’s Services, whose support made this project possible, and the numerous research coordinators and assistants involved over the years. Special acknowledgment is due to the late Hugh Leichtman, previously Executive Director of Wediko, who facilitated research at Wediko over many years.

Correspondence concerning this article should be addressed to: Audrey L. Zakriski, Department of Psychology, Connecticut College, 270 Mohegan Avenue, New London, CT 06320 Electronic Mail may be sent to: alzak@conncoll.edu.

Over the last few decades, explanations of gender differences in social behavior have increasingly focused on context. Social interactive models have highlighted the variability of gender-related behavior and traced gender differences (and similarities) to interpersonal dynamics and situational demands (Deaux & Major, 1987). Recently, the two cultures view has suggested that girls and boys differ in their social behavior largely because their sex-segregated peer groups elicit behaviors that may not be characteristic of them in other social contexts (Maccoby, 1998, 2002). These and related views have clarified why gender differences are variable over studies and have identified social forces that might contribute to differences previously assumed to be inherent or “essential” (Archer, 1996; Eagly, 1995; Leaper, 2000).

In place of a few stable, enduring, and broad gender differences in behavior, what has emerged is a mosaic consisting of small differences in some contexts, no differences in others, and “reversed” differences in others. As the mosaic’s complexity grows, the usefulness of studying gender differences in personality seems to recede (see Leaper, 2000; Maccoby, 1998). Indeed, some have debated whether we should stop studying such differences altogether (Baumeister, 1988; Eagly, 1987; Lott & Eagly, 1996). We suggest that the study of personality and context need not conflict; rather than receding as the mosaic grows, personality is revealed in the mosaic itself. In our view, legitimate criticisms of research on gender differences in personality arise more from the limitations of acontextual trait models than from the concept of personality per se.

Studies of gender and personality have often focused on overall behavior rates, average trait ratings, or summary checklist scores (see meta-analyses by Feingold, 1994). This is consistent with other research on individual differences in which behavior inventories attempt to “filter out” situational variation to assess the “stable and enduring” features of the person (Barkley, 1988). One of the clearest theoretical justifications for such methods can be found in the act frequency approach to personality (Buss & Craik, 1983), which defines a disposition as an act trend, or the number of relevant acts a person displays over a period of observation. Although contemporary theorizing about personality often embraces more complex and dynamic views of traits (Johnson, 1999; Roberts & Caspi, 2001), the predominance of act frequency methods perpetuates the notion that “consistency across situations lies at the core of the concept of personality” (Weiten, 2004, p. 478; see also Gray, 2002). It is the clash between this concept of personality and the context dependence of gender differences in aggression, affiliation, helping, and other behaviors (Archer, 2000; Caldera & Sciaraffa, 1998; Eagly & Crowley, 1986) that has led some to reject the notion of gender differences in “underlying traits or abilities” (Leaper, 2000, p. 391).

There have long been alternative views of personality that more explicitly incorporate context. G. W. Allport (1937) discussed the need to understand how contexts elicit behavior and advocated idiographic approaches that could reveal response styles that distinguish one individual from another. F. Allport (1924) argued that personality is best understood as the quality of a person’s “adaptation to the social features of the environment” (p. 149) and spoke of the process by which a person’s responses can be reevoked or increased by the reactions those responses elicit from others. In a similar spirit, a contextualist approach to personality suggests that the quality of a person’s adaptation can be seen in the patterning of if … then links between contexts and behaviors (Wright & Mischel, 1987; see also Mischel & Shoda, 1995; Vansteelandt & Van Mechelen, 1998). Rather than reflecting noise to be averaged out, contextual variability is viewed as an inherent feature of personality, one that can be used to clarify what is distinctive about individuals or groups and to probe how people describe and interpret behavior (e.g., Dawson, Zeitz, & Wright, 1989; Shoda, Mischel, & Wright, 1989).

Research on anxiety (Van Mechelen & Kiers, 1999), hostility (Vansteelandt, 1999), neuroticism, and other traits (Bolger & Schilling, 1991; Van Heck, Perugini, Caprara, & Fröger, 1994) has shown how the study of reactions in context can clarify the situational specificity of individual differences in these domains. Other work has illustrated how contextual approaches can enhance clinical diagnosis (Gresham & Noell, 1993; Scotti, Morris, McNeil, & Hawkins, 1996). In child assessment, groups defined as primarily aggressive, primarily withdrawn, or both aggressive and withdrawn using a popular acontextual measure have been found to include functional subgroups that differ in the events that elicit their behaviors and in their rates of encountering those events (Wright & Zakriski, 2001). Related research (Wright, Lindgren, & Zakriski, 2001) found that people’s personality judgments were sensitive to the contextual origins of children’s behavior (e.g., aggression resulting from encountering aversive events or from aggressive reactions to those events), whereas standardized acontextual measures were not.

Conceptualizing personality in terms of contextualized behavior patterns or “signatures” has implications for the study of individuals (Shoda, Mischel, & Wright, 1993); trait groups (Wright & Zakriski, 2001); and, we suggest, gender differences. First, this approach highlights the possibility that girls and boys show different response patterns even when they have similar overall behavior rates. Suppose that Ann is aggressive when warned by adults but not when provoked by peers; Brian is aggressive when provoked but not when warned. If they encountered similar rates of these contexts, these children would have similar overall rates of aggression and would be equally aggressive in an act frequency sense. In a contextualist view, however, the children’s distinctive patterns reveal what is so different about their aggressiveness and, more broadly, their personalities.

Second, the contextual approach highlights the possibility that girls and boys show similar response patterns even when they differ in overall behavior rates. Suppose that Sue shows the same pattern of reactions as Brian (aggressive when provoked) but that she is rarely provoked by peers, whereas Brian is often provoked. From an act frequency perspective, Brian is more “aggressive” because of his higher overall rate of such acts. Inferences about the children’s personalities, however, could be misguided if their behavior rates stem from social experiences rather than reaction tendencies. Interpreting overall behavior rates becomes even more challenging when both social environments and reaction patterns differ, as may be the case for girls and boys.

Distinctions between the present and related views should be noted. Gender researchers at times use context differences to “explain away” gender differences in personality. For example, on the basis of high provocation rates among boys, it is argued that girls and boys would not differ in aggressiveness if this context effect were removed (see Maccoby, 1998). In our view, this type of analysis is useful but potentially incomplete. Higher provocation rates may contribute to boys’ overall frequency of aggression, but boys and girls may still differ in their responses to provocation. Conversely, even if girls and boys were similar in their overall frequencies for a behavior (e.g., withdrawal), they could still differ in how often they encounter eliciting events and in how they react to them. A contextual analysis of behavior is a two-edged sword: It may explain away some gender differences in overall rates of behavior yet also reveal gender differences in response patterns that exist even when children’s overall behavior rates are equal. 1

Contemporary theories of personality also consider contextual influences (Caspi & Roberts, 2001; Helson, Jones, & Kwan, 2002; Muller, Endler, & Parker, 1990). Although context is recognized as interacting with traits as personality is shaped over time, too often it is not fully integrated into the conceptualization and measurement of traits themselves. The result is a disparity between theorizing about personality that is richly contextualized and trait measures that in themselves are not (e.g., the Big Five, the California Psychological Inventory, Cattell’s 16PF). This reinforces the view that assessment is an atheoretical, actuarial task and that personality is “what personality instruments measure” (Feingold, 1994, p. 429). Our position is closer to Coombs’s (1964), who argued that data never “speak for themselves” and that all measurement rests on assumptions about why data should be collected one way as opposed to another. Even at the miniature level of measuring how often a behavior occurs, it is essential to ask what environmental and psychological processes may have contributed to the measurement before drawing conclusions about the “traits” of the individual. Understanding gender differences in personality may require not only that we contextualize our interpretations of aggregated measures after they have been collected but also that we explicitly contextualize the assessment process from the outset.

This study examined gender differences in social behavior using extensive observations of girls and boys at a summer program for children with behavior problems. We examined children’s overall rates of behavior (physical and verbal aggression, withdrawal, prosocial behavior), how often they encountered contexts that might elicit these behaviors (e.g., peer talk, adult punish), and how they responded when each context occurred. We tested three propositions. First, we expected differences in overall behavior rates to be consistent with research that used comparable measures. Although specific findings vary, girls generally display less physical aggression and more prosocial behavior than boys (Coie & Dodge, 1998; Eisenberg & Fabes, 1998; Hyde, 1984). Evidence on verbal aggression is mixed: Many studies have found no difference, whereas others have found that girls are more verbally aggressive (Archer, Pearson, & Westeman, 1988; Österman et al., 1998). Gender differences have seldom been found for withdrawal (Mullen, Snidman, & Kagan, 1993; Rubin, Burgess, & Coplan, 2002). The effect of age is unclear because of a confounding of age and methodology: Self- and other-reports often used with older children are more influenced by sex role stereotyping than are direct observations often used with younger children (Eisenberg & Fabes, 1998; Rubin et al., 2002). The present study used observational methods across a wide age range in an effort to address this issue.

Second, we tested the proposition that comparisons of overall behavior rates do not directly show differences (or similarities) in the personalities of girls and boys. Rather, overall rates can be understood only in light of the processes that contribute to them, including the quality of children’s social environments. Specifically, past research has suggested that gender differences in behavior occur partly because girls are less likely than boys to experience peer provocation, adult warnings, and adult punishments, whereas girls are more likely to experience adult praise and peer talk (Buhrmester & Prager, 1995; Leaper, Anderson, & Sanders, 1998; Smith & Boulton, 1990; Zarbatany, McDougall, & Hymel, 2000). Although we expected social environment differences across the age range we studied (7–15 years), available evidence suggests that girls’ and boys’ social worlds become more different with age (Maccoby, 1998).

Third, we tested the claim that gender comparisons of overall behavior rates obscure narrow but important differences between girls and boys in the patterning of their reactions to contexts. Research has seldom compared girls’ and boys’ reactions to multiple contexts within the same study; instead, the contextual variability of gender differences is usually extracted from reviews of multiple studies (Eisenberg & Fabes, 1998; Underwood, 2003). Thus, our predictions extrapolate from indirect evidence. We expected boys (compared with girls) to be especially likely to show physical aggression in response to peer provocation (Archer et al., 1988; Coie & Dodge, 1998). Conversely, we expected girls to show more conflict-reducing (prosocial and withdrawn) behavior to peer provocation (Fabes & Eisenberg, 1992; Miller, Danaher, & Forbes, 1986). Some indirect evidence has suggested that girls are more prosocial than boys in interactions with adults but comparably prosocial in interactions with peers (Brody, 1999; Eisenberg & Fabes, 1998; Kochanska & Aksan, 1995). Other studies have suggested that conflict with adult caretakers may be especially likely to elicit aggression from girls (Hoffenaar & Hoeksma, 2002; Walsh, Pepler, & Levene, 2002).

Method

Our data were from a multiyear project at Wediko Children’s Services’ 45-day residential summer program for children with behavior problems (i.e., aggression, withdrawal, poor social skills). Wediko admits approximately 150 children each summer, referred primarily from public schools in the Boston area and elsewhere in New England. Children live in groups of 8 to 10 same-sex, same-aged peers and participate in a schedule that includes a range of daily activities (e.g., academics, art, swimming). The girl:boy ratio is approximately 1:3, reflecting higher rates of overt behavior problems and referrals for boys, especially prepubertally (Goodman et al., 1997). Approximately 100 counselors and teachers participated each summer in data collection. Permission to use data for research purposes was obtained from parents/guardians during the interview process.

Child and Adult Participants

Children

Data were obtained on 690 children over five summers. Of these, 624 (90.4% of 690) were in residence for the entire summer and had sufficient observations (see below). All girls with sufficient observations were included (n = 180). Including all boys with sufficient observations would have involved tradeoffs. As Hays (1973) noted, increasing sample size is desirable when the goal is to obtain precise estimates of parameters, but caution is needed when the goal is to identify effects that are robust enough to warrant further investigation. Using all boys also would have created a disparity between boys and girls in the power of tests of age differences within gender groups. Therefore, 180 boys were randomly sampled, and the present study examined data for 360 children. 2 The composition of the sample was 53% White, 37% African American, 7% Hispanic, 1% Asian, and 2% other; the children were predominantly lower and middle socioeconomic status. Children were divided into two age groups using a median cutoff of 11 years: younger girls (n = 93; mean age 9 years 2 months), younger boys (n = 93; mean age 9 years 4 months), older girls (n = 87; mean age 12 years 11 months), older boys (n = 87; mean age 13 years 0 months). Wechsler Intelligence Scale for Children—Revised (Wechsler, 1974) scores obtained by Hayes (1995) on a subsample of children indicated that their scores fell in the average range: Verbal (M = 97.9), Performance (M = 99.1), and Full Scale (M = 98.5).

Adults

A total of 519 counselors, teachers, and supervisors were employed at Wediko over the 5-year period; these staff were students or recent graduates recruited from numerous colleges and universities. Teachers and activity counselors ran classes and activities for 4 hr each day; cabin counselors remained with their group most of the day. Four to 6 counselors and a supervisor were assigned to each group of children. More female than male cabin counselors were assigned to girls’ groups; male:female staff ratios were roughly equal in boys’ groups. Of the 519 staff, 410 nonsupervisory staff provided observational data as described below.

Behavior Coding Materials and Procedure

As in related research (Patterson, 1982), the coding system emphasized behaviors that were observable and common in everyday interactions. Earlier methods used at Wediko (Shoda et al., 1993) were expanded to create a set of 7 context codes and 10 response codes (Wright et al., 1999). The response codes included aggressive, withdrawn, and prosocial behaviors often sampled in past studies: “hit or physically attacked”; “teased, provoked or ridiculed”; “bossed, bullied, or threatened”; “argued or disapproved”; “withdrew, isolated self”; “whined or cried”; “talked in age-appropriate way”; “attended or listened to other(s)”; “showed positive emotion”; and one item not used here, “self-stimulation/self-abuse.” The contexts included positive and aversive adult and child behaviors found in previous research to elicit individual differences for these behaviors: “adult praised the child verbally”; “adult gave the child a warning”; “adult instructed the child to do something”; “adult gave the child a time out”; “peer talked in age-appropriate way”; “peer teased, provoked, or ridiculed”; “peer bossed, bullied, or threatened.”

The coding manual provided definitions of each code and explained how to record contexts and responses. Staff training included group presentations, practice coding of written and role-play vignettes, and individual and group feedback from research staff. Coders observed children during hourly activity and class periods and recorded their behavior at the end of the period. Recordings were made on optical scan forms to minimize memory and writing demands. Each coder typically completed forms for 2 to 6 children per period, and each child was observed in three to five periods each day. Each child was observed by a range of coders, including cabin staff who interacted with the child for at least 8 hr per day, teachers who interacted with the child each day for 1.5 hr, and activity staff who interacted with the child during their activity specialty (e.g., crafts, archery).

At the end of each period, the coder identified the target child and provided a global rating of how often she or he displayed each of the 10 responses (“On the whole, how did the child behave during this observation period?”) using a 0–3 scale (not at all, somewhat, moderately, a lot). The coder then recorded whether the target encountered each of the seven contexts, the name of the peer or adult involved, and the responses shown to each recorded context. If two or more instances of the same context occurred, coders recorded the most recent one to minimize memory demands. Multiple responses were allowed for a given context.

As in previous work (Wright et al., 1999), categories were formed from individual codes. Nine response codes were combined into four composites: verbal aggression (argue, tease, and boss), physical aggression (hit/physically attack), withdrawal (withdraw and whine), and prosocial behavior (talk, attend, positive emotion). We did not analyze self-stimulate because its frequency was low and because it is not commonly studied in the gender literature. Peer boss/threat and peer tease were combined because of the relatively low frequency of peer threat, yielding six context categories: adult praise, adult instruct, adult warn, adult punish, peer talk, and peer boss/tease.

“Overall behavior rates” were computed for each response category by averaging the mean behavior ratings a child received over the summer. “Context rates” were computed by dividing the number of times each child encountered each context by the total number of contexts encountered. “Reaction rates” were computed by dividing the number of responses to a context by the number of times that context occurred (e.g., the number of instances of withdraw in response to boss/tease divided by the number of instances of boss/tease). This yielded a matrix of 4 (response) × 6 (context), or 24 reactions. For our main analyses, each measure was converted to a z score—that is, (raw score – Mall children)/SD—yielding variables with M = 0 and SD = 1. A positive (negative) z indicates that a group was high (low) relative to the sample as a whole; a z near 0 indicates the group was near the mean for the sample.

The sample of 360 children had a mean per child of 115.8 hourly observations, 386.6 responses to contexts, and 215.0 instances of contexts. Context frequencies (with mean relative frequencies) per child per context were as follows: adult instruct 64.7 (.30), adult praise 54.4 (.25), peer talk 32.7 (.15), adult warn 22.8 (.11), peer boss/tease 22.0 (.10), and adult punish 18.4 (.09).

Interobserver Agreement

Analyses of individual coders would have been uninformative, because a typical coder provided relatively few observations and did not code all children. To assess reliability, we therefore examined how well two randomly selected panels of coders agreed. 3 We performed univariate and multivariate within-child analyses. For the univariate analyses of each behavior rate, we correlated (over children) the rates from one panel with the rates from the other, then used the Spearman-Brown procedure to estimate reliability for both combined (McNemar, 1962). In the within-child analyses, for each child we correlated the set of four overall rates from one panel with the set of four rates from the other panel, computed the average within-child correlation, and again used the Spearman-Brown procedure. A similar approach was used for the context rates and reaction rates.

The univariate reliabilities for overall behavior rates were verbal aggression (.89), prosocial behavior (.89), withdrawal (.88), and physical aggression (.82); the mean reliability for the within-child method was.90. Univariate reliabilities for contexts were peer boss/tease (.84), adult praise (.82), peer talk (.77), adult warn (.77), adult punish (.76), and adult instruct (.69); the mean within-child reliability was.65. We examined each set of reactions separately (e.g., withdrawal to six contexts). The mean within-child reliabilities were prosocial (.91), verbal aggression (.90), physical aggression (.86), and withdrawal (.75). Univariate reliabilities for individual reactions should be interpreted with caution because some reactions (e.g., physical aggression when praised) were expected to show little variability over children. Three variables (physical and verbal aggression to praise and physical aggression to instruction) had lower variability than other measures (SDs <.05); these were not included in reliability summaries or interpreted further. Averaged over contexts, the mean reliabilities for reactions were verbal aggression (.64), prosocial behavior (.59), withdrawal (.56), and physical aggression (.53). Averaging over reactions, mean reliabilities were peer talk (.64), adult instruct (.63), adult praise (.60), adult punish (.58), peer boss/tease (.57), and adult warn (.50).

Results

We first examine overall behavior rates, then context rates and context-specific reactions. We used multivariate analysis of variance (MANOVA) because it does not require corrections to control Type I errors (Maxwell & Delaney, 1990). We used Hotelling T2 to test for multivariate differences among the four Gender × Age groups. For brevity, we report the range of significant Fs (p <.05) rather than a list of all tests. Certain comparisons were of little interest (e.g., younger girls and older boys differ in age and gender); therefore, planned comparisons within age groups (with Bonferroni adjustments of α/2) were used for univariate tests of gender differences. Each figure also shows tests of age differences within gender. Cohen’s d is used to report effect sizes for significant main effects and planned comparisons.

Overall Behavior Rates

The patterning of overall behavior varied as a function of gender, age, and both interactively, Fs(3, 354) = 3.03–13.18, ps <.03 (see Figure 1). Overall, girls were less physically aggressive and more prosocial than boys (ds =.45 and.34, respectively); younger children were more physically aggressive, prosocial, and withdrawn than older ones (ds =.39,.29,.26). There were multivariate differences between all Gender × Age groups, with the smallest T2 between older girls and boys, T2 = 18.22, F(4, 169) = 4.48, p <.01. Both younger and older girls were less physically aggressive than age-matched boys (ds =.36,.60). Only younger girls were reliably more prosocial than boys (d =.37).

psp-88-5-844-fig1a.gifFigure 1. Mean (± 1 SEM) behavior rates (top row) and context rates (bottom row) for gender and age groups, expressed as standard deviates (z scores) from the mean for all children. Groups not sharing a subscript showed a significant multivariate difference. An asterisk indicates a significant gender comparison within age group; a circle indicates a significant age comparison within gender. Bonferroni-adjusted p values were p <.025, p <.005, and p <.0005 for both notations. VAGG = verbal aggression; PAGG = physical aggression; WDR = withdrawal; PRO = prosocial; AWAR = adult warn; APUN = adult punish; PBOT = peer boss/tease; AINS = adult instruct; APRA = adult praise; PTLK = peer talk

Context Rates

The pattern of contexts varied as a function of gender, age, and both interactively, Fs(5, 352) = 4.45–13.34, ps <.001 (see Figure 1). Overall, girls experienced more peer talk and less adult punish and warn than boys (ds =.61,.45,.26); younger children experienced less peer talk but more adult praise and warn than older ones (ds =.50,.29,.23). There were multivariate differences between all Gender × Age groups, with the smallest difference between younger girls and older boys, T2 = 15.57, F(5, 174) = 3.04, p <.02. 4 Younger girls encountered more peer talk and less adult instruct than younger boys but more peer boss/tease (ds =.62,.46,.52). Older girls encountered more peer talk and adult praise than older boys (ds =.65,.43) but less adult punish, adult warn, and peer boss/tease (ds =.71,.54,.36).

Reactions to Contexts

Peer boss/tease

The pattern of reactions varied as a function of gender, age, and both interactively, Fs(3, 354) = 4.89–9.56, ps <.002 (see Figure 2). Girls were less likely than boys to react to peer boss/tease with physical aggression (d =.37) but more likely to react with withdrawn and prosocial behavior (ds =.34,.22); younger children were more likely than older ones to react with physical aggression and withdrawal (ds =.42,.38). There were multivariate differences between all Gender × Age groups, with the smallest difference between younger girls and boys, T2 = 18.02, F(4, 181) = 4.43, p <.01. Younger girls were less likely than younger boys to react with physical aggression and more likely to react with withdrawal (ds =.39,.35); older girls were more likely than older boys to react with prosocial and withdrawn behavior (ds =.58,.43) and less likely to react with physical or verbal aggression (ds =.37,.35).

psp-88-5-844-fig2a.gifFigure 2. Mean (± 1 SEM) rates of reactions to peer boss/tease (top row) and adult instruction (bottom row) for gender and age groups, expressed as standard deviates (z scores) from the mean for all children. An asterisk indicates a significant gender comparison within age group; a circle indicates a significant age comparison within gender. Bonferroni-adjusted p values were p <.025, p <.005, and p <.0005 for both notations. Groups not sharing a subscript showed a significant multivariate difference. VAGG = verbal aggression; PAGG = physical aggression; WDR = withdrawal; PRO = prosocial behavior

Adult instruct

Reactions varied as a function of age and as a function of gender and age interactively, Fs(3, 354) = 9.70 and 4.36, respectively, ps <.005 (see Figure 2). Older children were more likely than younger ones to react to adult instruction with verbal aggression (d =.53). All Gender ×Age groups differed multivariately, with the smallest difference between younger girls and boys, T2 = 11.00, F(4, 181) = 2.70, p <.04. Younger girls were less likely than younger boys to react with physical aggression (d =.34); older girls were more likely than older boys to react prosocially (d =.55).

Adult warn

Reactions varied as a function of gender, age, and both interactively, Fs(3, 354) = 5.34–10.54, ps <.002 (see Figure 3). Girls were more likely than boys to react to adult warnings with verbal aggression and less likely to react with physical aggression (ds =.28,.22); younger children were less likely than older ones to react with verbal aggression and more likely to react with physical aggression (ds =.38,.22). All groups differed multivariately except younger girls and older boys, with the smallest significant difference for older girls versus older boys, T2 = 15.92, F(4, 169) = 3.90, p <.01. Younger girls were more likely than younger boys to react with verbal aggression (d =.48); older girls were more likely than older boys to react prosocially (d =.42).

psp-88-5-844-fig3a.gifFigure 3. Mean (± 1 SEM) rates of reactions to adult warning (top row) and adult punishment (bottom row) for gender and age groups, expressed as standard deviates (z scores) from the mean for all children. An asterisk indicates a significant gender comparison within age group; a circle indicates a significant age comparison within gender. Bonferroni-adjusted p values were p <.025, p <.005, and p <.0005 for both notations. Groups not sharing a subscript showed a significant multivariate difference. VAGG = verbal aggression; PAGG = physical aggression; WDR = withdrawal; PRO = prosocial behavior

Adult punish

The reactions varied as a function of gender and age, Fs(3, 354) = 2.93 and 10.66, respectively, ps <.03 (see Figure 3). Overall, girls were more likely than boys to react to adult punishment with verbal aggression and prosocial behavior (ds =.28,.24); younger children were more likely than older ones to react with physical aggression and withdrawal but less likely to react with verbal aggression (ds =.23,.21,.40). All Gender × Age groups differed multivariately except for older girls and older boys, with the smallest significant difference between younger girls versus older boys, T2 = 10.88, F(4, 175) = 2.67, p <.05. Planned comparisons showed that older girls were more likely than older boys to react with verbal aggression (d =.38).

Adult praise and peer talk

The MANOVA indicated that reactions to praise and talk varied only with age, Fs(3, 354) = 3.99 and 5.27, respectively, ps <.01. Younger children were less likely than older ones to withdraw in response to adult praise (d =.29) and more likely to be physically aggressive and withdrawn in response to peer talk (ds =.25,.27). Although the MANOVA for gender was not significant, we report significant univariate tests for gender to compare with other results. Younger girls were less prosocial and physically aggressive to adult praise than younger boys (ds =.42,.35); older girls were more prosocial to peer talk than older boys (d =.46).

Aggregated reactions

We have noted that overall behavior rates can be affected by how often children encounter contexts and by how they react to them. An alternative approach to summarizing behavior also uses aggregation, but only over children’s reactions to contexts, thus removing any effect of context rates. Specifically, we computed the average for each reaction (e.g., verbal aggression) over the six contexts (e.g., peer boss/tease, adult warn). These aggregated reactions again varied as a function of gender, age, and both interactively, Fs(3, 354) = 5.46–16.72, ps <.001, but the specific findings differed from those for overall behavior rates. Overall, girls reacted with physical aggression less often than boys (d =.35); younger children reacted with verbal and physical aggression more often than older ones (ds =.40,.30). There were multivariate differences between all Gender × Age groups, with the smallest T2 between younger girls and older boys, T2 = 13.48, F(4, 175) = 3.31, p <.02. Younger girls reacted with physical aggression less often than younger boys (d =.45); older girls reacted prosocially more often than older boys (d =.57). We compare these results with the overall behavior rates in the Discussion section.

Summary

Three sets of findings lend qualified support to our predictions. First, girls had lower overall rates of physical aggression and higher prosocial rates than boys; however, only the difference in physical aggression was reliable for both age groups. Second, we found robust differences between girls’ and boys’ social environments, especially for older children. Compared with boys in their age groups, older girls more often experienced peer talk and adult praise, but they less often experienced peer boss/tease, adult warn, and adult punish. Younger girls experienced more peer talk and boss/tease but less adult instruct. Third, we found localized gender differences in reactions to contexts. In both age groups, girls were less likely than boys to be aggressive in response to peer provocation and were more likely to withdraw in response to that event. However, girls were more likely than boys to be aggressive in response to direct adult control (warn or punish). Gender differences in prosocial responses depended on age but less so on context; compared with older boys, older girls were more prosocial to peer talk, peer boss/tease, adult instruct, and adult warn. Consistent with our other analyses, we found that two ways of summarizing behavior—an overall act frequency measure that is affected by context rates and an aggregated reaction measure that is not—revealed distinct sets of gender and age differences.

Discussion

This research examined how a contextual model of personality can deepen our understanding of gender differences and similarities. Consistent with past work using overall behavior rates, we found differences for physical aggression and prosocial behavior but not for verbal aggression or withdrawal (Eisenberg & Fabes, 1998; Hyde, 1984; Österman et al., 1998; Rubin et al., 2002). What is notable about these findings is not only what they reveal but also what they conceal. In some cases, differences in overall behavior obscured the fact that girls and boys differed in the contexts they encountered but not in their responses to them. In other cases, similarities in overall behavior obscured the fact that girls and boys differed both in their environments and in their response patterns.

Deconstructing Differences and Similarities

Gender researchers often suggest that differences in social experiences could account for gender differences in behavior. Indeed, our results revealed robust context effects. In both peer and adult interactions, older girls’ experiences were more positive than older boys’, with effect sizes that were larger than those for overall behavior rates. Although it might be argued that such context effects explain away gender differences in behavior, our results reveal why such conclusions must be drawn with care. Older boys experienced a higher rate of peer provocation than older girls, but they were also more likely to be physically aggressive in response to that event. Younger children’s prosocial behavior illustrates a different pattern. Younger girls, who exhibited more prosocial behavior than younger boys, were not more likely to be prosocial to any context we assessed but were more likely to encounter contexts that elicit such behavior (peer talk). Older boys’ physical aggression thus was linked both to social opportunities and to heightened reactivity, whereas younger girls’ prosocial behavior was linked to opportunities alone.

Our results illustrate how similarities in girls’ and boys’ overall behavior rates can mask other gender differences. One type of masking occurs when aggregation obscures localized gender differences. Older girls were verbally aggressive when punished by adults but not when bossed or teased by peers; older boys showed the reverse pattern. Not surprisingly, measures that aggregated over this variability showed no gender difference. Likewise, overall comparisons obscured a narrow but robust gender difference in withdrawal to peer provocation. A second type of masking occurs when context rates and reactions to contexts offset each other. Older girls were less likely than older boys to encounter peer boss/tease, adult warn, and adult instruct yet more likely to react prosocially when those contexts occurred. Because overall measures conflate reactions to events and the rate of encountering them, a net result of no difference is found.

Because context rates and reaction rates can either converge or diverge, gender comparisons will depend on how one’s measure of overall behavior is affected by contexts, reactions, or both. Omnibus act frequency measures and average reaction rates are both cross-situationally broad, yet they differ in that the former is sensitive to context rates, whereas the latter is not. Using the act frequency measure, older boys were more physically aggressive than older girls (d =.60), but the difference for prosocial behavior was unreliable (d =.34). Using aggregated reactions, the difference in physical aggression was small (d =.17), but a difference for prosocial behavior emerged (d =.57). Thus, older boys were more physically aggressive when the measure could be affected by their high rate of encountering conflict; older girls were more prosocial when the measure focused on their reactivity.

Our point is not that one way of defining overall behavior is intrinsically superior to the other but that each requires careful interpretation. Omnibus act frequency measures provide an efficient way to screen for problem (or other) behaviors in the child-environment system, regardless of their origins, but such measures do not provide explicit information about possible contextual influences. Aggregated reaction measures focus on the child’s response properties, but this can be done only if relevant contexts are identified. Oversimplifying either tradeoff has risks. Overrelying on act frequency measures could reinforce the view that problem behavior is always “in” the child (see Scotti et al., 1996). Focusing exclusively on reactivity to contexts could lead one to neglect problem behaviors whose frequency stems primarily from a high rate of encountering eliciting contexts.

Gender Differences in Cycles of Cooperation and Coercion

A challenge for models of personality development (Block, 2002; Caspi, Elder, & Bem, 1988; Magnusson, 1992; Patterson, 1997) is to clarify how children’s behaviors shape, and are shaped by, the behaviors of people with whom they interact. Several processes need to be considered, including how children select interaction partners, evoke responses from them, and manipulate their behavior (Buss, 1987). There is evidence that girls’ and boys’ behavioral styles predict their preferences for gender-segregated play (Moller & Serbin, 1996) and that aggressive children select aggressive peer groups (Cairns, Cairns, Neckerman, Gest, & Gariepy, 1988). However, when peer groups are assigned (as they were in our study), children’s peer relations are likely to reflect evocation more than selection effects. In this view, older girls enjoy a mutually rewarding cycle in which their prosocial responses to peer talk reevoke and increase reciprocal behaviors from peers, and their conciliatory responses to provocation mitigate against escalating coercion. In contrast, older boys appear to be enmeshed in a cycle in which their counterattacks to provocation lead to escalating coercion from peers (see Coie et al., 1999).

As socializing or therapeutic agents, teachers, counselors, and other adults are often responsible for children’s behaviors toward both peers and adults and are expected to manage behavior strategically. Adults’ behaviors toward older girls (high praise, moderate instruction, low warn and punish) are likely to have multiple antecedents and to reflect both evocation and (hopefully therapeutic) “manipulation.” For example, adults may use praise often to encourage older girls’ positive peer relations. When adults use mild pressure (instruction), older girls respond positively, reducing the need for more direct control, but when adults do use direct control, older girls are highly reactive (verbal aggression). Older girls’ responsiveness to minimal pressure and their resistance to direct control may encourage adults to use minimal pressure to manage their behavior. High rates of peer conflict among older boys presumably require more frequent adult intervention, and boys’ responses to such intervention—including their resistance to instruction but acceptance of punishments—help shape adults’ greater reliance on direct control.

The finding that gender differences in reaction patterns were clearer among older children supports the view that girls and boys diverge as they adapt to different social experiences (Leaper, 2000; Maccoby, 1998). However, two developmental consistencies deserve note. First, in their peer relations, both younger and older girls were more withdrawn and less physically aggressive to peer provocation than age-matched boys. These and related results in even younger children (Fabes & Eisenberg, 1992) reveal how the distinct peer cultures of girls and boys may have their roots in “weak,” or what we would call contextually narrow, initial gender differences (Maccoby, 1998). Second, in relations with adults, boys were more aggressive to adult instruction than girls, whereas girls were more aggressive to direct control. Greater male resistance to instruction also has been noted in toddlers (Kochanska & Aksan, 1995), suggesting it is a key feature of boys’ interactions with adults. Our finding of girls’ reactivity to discipline with mainly female counselors is consistent with evidence that girls’ aggression is pronounced with female caregivers (Walsh et al., 2002) and suggests that girls may perceive such interventions as violations of female relationship norms (Mikolic, Parker, & Pruitt, 1997). More research is needed on the meaning of these different contexts to girls and boys and on how their reactions to them shape their development (e.g., Deaux & Major, 1987).

It could be argued that because children’s environments reflect their personalities, it is unnecessary to disentangle contexts and reactions when studying personality. One difficulty with this view is that individuals vary in their social impact, and environments vary in their malleability. Young children influence their worlds, but their influence is limited compared with older children’s or adults’ (see Caspi & Roberts, 2001); some adults are permissive in their child-rearing practices, but others are more controlling (see Eisenberg & Fabes, 1998). Children’s social interactions often involve complex reciprocal influences and constraints precisely because the people with whom they interact are also designing their own environments in a way that partly reflects their personalities and their attempts to alter the behaviors of others (e.g., increase prosocial behavior, decrease aggression). Moreover, children encounter some contexts and life stressors—divorce, unemployment, family relocation, school placement—for reasons that may have nothing to do with their preexisting behavior. Even in ongoing interactions, children’s experiences sometimes result not from their own behaviors but rather from who they are, what they look like, or the stereotypes of people around them (Zebrowitz & Montepare, 1992). For example, we found few clear links between young girls’ positive peer environments and their reactions; these girls may encounter higher rates of friendly behavior primarily because they are girls. Our claim is not that our findings point unequivocally to a particular interactional mechanism. Rather, it is that multiple contributing mechanisms usually need to be considered when interpreting gender differences or similarities in overall act trends.

Our findings should be interpreted in light of methodological strengths and weaknesses. Although our sample covered a wide age range, cross-sectional studies are limited in their ability to identify processes that produce age differences. We believe the concept of behavioral signatures may be useful in research on personality development, but we do not know how well the signatures we found will generalize to other populations. A related question is whether our sample gives unfair advantage to context variables by restricting the range of individual differences. Because our sample included children with a range of behavior problems (Wright et al., 1999), our measures of aggression and withdrawal are less affected by restricted range than our measures of prosocial behavior; future research should examine the patterning of prosocial behaviors in normative samples. Given what is known about relational and indirect aggression, future work should investigate contexts that influence gender differences in these more subtle forms of aggression (Crick, Casas, & Nelson, 2002; Underwood, 2003). Our peer context results reflect mainly same-sex interactions among boys and girls; more research is needed on how sex of interactant affects children’s behavior patterns (Archer, 1996); the sex of interactant in adult-child interactions also deserves study. Although observational methods have advantages, they are laborious; methods that use peer and adult reports are also needed (Wright & Zakriski, 2001). Other connections between this and related work should also be explored, including the ordering and organization of girls’ and boys’ context-specific reactions (Mikolic et al., 1997), what aggregated or context-specific reactions add to the prediction of life outcomes (Bolger & Schilling, 1991), how context-specific reactions are linked to single and multiple traits (Van Heck et al., 1994; Wright & Zakriski, 2001), and how they may be used to facilitate personality typing (Vansteelandt & Van Mechelen, 1998). Future work should also investigate individual differences within gender groups, especially in the contextual predictors of behavior, because too often such questions are overshadowed by attention to mean differences between gender groups (see Hare-Mustin & Marecek, 1988).

As Hershberger, Plomin, and Pedersen (1995) noted, “the most common measure of individual differences in personality research has undoubtedly been the total scale score obtained on an inventory or questionnaire” (p. 673). Although traits are increasingly acknowledged to be “complex patterns of behavior,” a common view is that such patterns “need to be examined, interpreted, and aggregated across numerous situations, places and times, to arrive at a reliable and valid index of a personality trait” (Roberts & Caspi, 2001; p. 105). This creates a conflict for gender researchers and other developmentalists, who regularly confront these complex patterns but then conclude that they must reject the notion of personality to preserve them (Leaper, 2000; Lewis, 2001). Our point is not that aggregation necessarily leads to the mismeasure of traits or that context-specific measures always reveal personality more clearly. Rather, it is that overall behavior summaries afford multiple social interactional interpretations and cannot simply be assumed to point uniquely to “stable and enduring” nomothetic traits within the individual. Under certain conditions, aggregation can indeed filter out error or nuisance variation, leaving a purer and more refined measure of personality. Under other conditions, aggregation acts less as a filter than as a dragnet that catches a variety of effects that lie in its path, including contextual, dispositional, and dynamic interactions between the two. As we hope our findings illustrate, some gender differences in personality—especially those that are narrow and circumscribed yet potentially important in shaping children’s experiences—are revealed not by collapsing the matrix of contexts and behaviors but by preserving and scrutinizing the matrix itself.

Footnotes

1 In the present study, we place no priority on finding gender differences (alpha bias; Hare-Mustin & Marecek, 1988) or similarities (beta bias). Instead, we suggest that neither can be adequately understood through comparisons of overall frequency measures that ignore the rates of encountering contexts and the patterning of people’s responses to them.

2 Portions of the data from one of these years were analyzed elsewhere (Wright, Zakriski, & Drinkwater, 1999; Wright & Drinkwater, 1997), but the focus of those studies was on syndromal groups and on undergraduates’ judgments of personality. A small number of girls was included in Wright et al. (1999), but behavioral observations in that study were normed within gender group, thereby limiting the exploration of gender differences. The current article uses a multiyear sample not previously reported, focuses on gender and age rather than syndrome groups, and examines prosocial behavior as well as aggression and withdrawal.

3 Analyses are presented on data from a single summer and were restricted to children who had at least 20 hourly observations per panel and at least 2 observations of each behavior in each context per panel (n = 101).

4 Here and for any subsequent Hotelling T2 test where it was needed to control Type I error rates, degrees of freedom were reduced by 1 because of linear dependencies among variables (see Maxwell & Delaney, 1990).

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Submitted: January 21, 2004 Revised: August 16, 2004 Accepted: December 29, 2004


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Source: Journal of Personality and Social Psychology. Vol.88 (5) US : American Psychological Association pp. 844-855.
Accession Number: psp-88-5-844 Digital Object Identifier: 10.1037/0022-3514.88.5.844



Not so ugly after all: When shame acts as a commitment device

February 5, 2011
Title:
Not so ugly after all: When shame acts as a commitment device. By: de Hooge, Ilona E., Breugelmans, Seger M., Zeelenberg, Marcel, Journal of Personality and Social Psychology, 0022-3514, 2008, Vol. 95, Issue 4
Database:
PsycARTICLES
By: Ilona E. de Hooge
Department of Social Psychology and Tilburg Institute for Behavioral Economics Research, Tilburg University, Tilburg, the Netherlands
Seger M. Breugelmans
Department of Cross-Cultural Psychology, Tilburg University
Marcel Zeelenberg
Department of Social Psychology and Tilburg Institute for Behavioral Economics Research, Tilburg University, Tilburg, the Netherlands

Acknowledgement: We thank Paul Van Lange for providing us with a programmed version of the 10-coin give-some dilemma game and Linda de Hooge for help with the data collection of Experiment 4.

Correspondence concerning this article should be addressed to: Ilona E. de Hooge, Department of Social Psychology, Tilburg University, P.O. Box 90153, 5000 LE Tilburg, the Netherlands Electronic Mail may be sent to: i.e.dehooge@uvt.nl.

Shame is one of the most intense self-conscious emotions (Lindsay-Hartz, 1984; Tangney, 1991), playing a central role in development, pathology, and self-regulation (Erikson, 1963; Freud, 1923/1961). Many psychologists tend to think of shame as a painful emotion that has profound negative psychological and behavioral consequences (see Tangney & Dearing, 2002). These negative consequences raise questions with respect to the function of shame, because emotion theorists generally assume that emotions are functional in the sense that they promote behavior that has beneficial consequences for the individual or community (Frijda, 1986; Keltner & Gross, 1999). As such, the current psychological knowledge of shame poses a kind of paradox: How could shame be a functional emotion when it has only negative psychological consequences?

Emotions that entail negative experiences can be functional. Moral emotions, for example, are assumed to motivate prosocial interpersonal behaviors (e.g., Haidt, 2003). Moral emotions make selfish behavior less attractive, thereby promoting behavior that is beneficial to others within one’s social group (Frank, 1988, 2004; Ketelaar, 2004; Smith, 1759). However, such prosocial effects have been found for guilt but not yet for shame (de Hooge, Zeelenberg, & Breugelmans, 2007). In this article, we solve the apparent paradox concerning the function of shame by revealing that shame motivates prosocial behavior when its experience is relevant for the decision at hand (what we refer to as endogenous) but that its experience has no such effect when it is not relevant (what we refer to as exogenous). We first provide an overview regarding the supposedly opposing views of shame as an ugly emotion on the one hand and as a moral emotion on the other hand, and then explain the role of the relevance of emotion in solving this paradox. To our knowledge, our data constitute the first empirical evidence of positive interpersonal effects of shame, providing more insight in the function of this prevalent self-conscious emotion.

The Function of Shame as an Ugly Emotion

Tangney (1991) summarized the scientific knowledge concerning shame as follows: “Shame is an ugly feeling” (p. 600). Shame is an overwhelming and unpleasant emotion associated with feelings of worthlessness, inferiority, and a damaged self-image (Ausubel, 1955). Experiences of shame are characterized by confusion in thought, inability to speak, and rumination (e.g., Miller, 1995; Orth, Berking, & Burkhardt, 2006). The primary tendency associated with this emotion is to withdraw from the situation that elicited the shame and to hide from other people (Lindsay-Hartz, De Rivera, & Mascolo, 1995; Tangney & Fischer, 1995). Many scholars have described the negative psychological and behavioral consequences of shame, for example, by linking chronic experiences of shame to having a lower self-esteem, less empathy, more shyness, more social anxiety, and a higher likelihood of depression (e.g., Gilbert, Pehl, & Allan, 1994; Harder, Cutler, & Rockart, 1992). This consensus on the negative effects of shame has led Tangney (1999) to question whether shame serves any adaptive functions at all.

The absence of a positive function of shame is especially puzzling because emotions are currently understood as psychological processes that function to benefit the person or society (Keltner & Gross, 1999). Emotions react to signals in the environment that one’s concerns are at stake and motivate goal-directed behaviors that serve to protect and further these concerns (Frijda, 1986; Zeelenberg & Pieters, 2006). Depending on the situation, their effects can be functional or dysfunctional, and the dysfunctional effects help us to understand what is necessary for emotions to be functional (Parrott, 2001). It is useful to differentiate the function of an emotion from its behavioral consequences, although the two are obviously related. The function of an emotion is a theoretical account of why it motivates particular types of behavior and is directed toward benefiting one’s own best interest. The observable behavioral consequences of emotions are all possible effects that follow from an emotion (Frijda & Zeelenberg, 2001). Functions can be defined at the intrapersonal level, coordinating physiological, perceptual, and cognitive processes that enable the person to adapt, and at the interpersonal level, addressing concerns within ongoing interactions such as redressing injustice or mate protection (Keltner & Gross, 1999). Especially for self-conscious emotions, which are grounded in social relationships, a prime function is to adjust interpersonal relationships (Caplovitz Barrett, 1995; De Rivera, 1984). For example, Baumeister, Stillwell, and Heatherton (1994) have argued that guilt serves relationship-enhancing functions by motivating people to treat partners well and to avoid interpersonal transgressions. However, the field of emotion research has remained largely mute with regard to possible interpersonal functions of shame. An exception is the work of Fessler and Haley (2003), who speculated about the possible functions of shame: “Shame and pride can promote cooperation in purely dyadic interactions, as the actor can feel shame if she defects and the partner knows about, or is likely to learn of, her defection” (p. 26).

There is an abundance of empirical research on shame, but there are at least two reasons why the empirical record so far has not shed much light upon the possible interpersonal functions of shame. First, research supporting the view of shame as an ugly emotion consists primarily of studies concerning the correlates of shame-proneness and not of situationally induced experiences of shame. Shame-proneness is the general tendency of an individual to experience shame (Tangney, 1990). This research convincingly shows that people who are likely to experience shame, or who experience shame very frequently, are also prone to feelings of inferiority, anxiety, lessened empathy, shyness, interpersonal distrust, and depression (Gilbert et al., 1994; Harder et al., 1992; Tangney and Dearing, 2002). However, it is not at all clear that these findings of shame-proneness as a trait can be generalized to experiences of the emotion shame as a state. As a case in point, Allan, Gilbert, and Goss (1994) examined the relationship of shame-proneness and actual experiences of shame with multiple factors. Although shame-proneness and experiences of shame were related, they were found to have different relations with social dysfunction, feelings of inferiority, and anger. Whereas shame-proneness was strongly related to depression and social dysfunction, experiences of shame were related to feelings of inferiority and anger at self and others. This finding was recently replicated by Rüsch et al. (2007), who found that shame-proneness was negatively related to self-efficacy and empowerment, and positively related to psychopathology, whereas experiences of shame were only related to state anxiety.

A second reason why studies of shame may have failed to capture the interpersonal functions of shame is methodological. The few studies that did focus on the interpersonal effects of shame as a state only examined a limited set of action tendencies. In line with the view of shame as an ugly emotion, studies have so far mainly focused on tendencies to withdraw or to hide. For example, Wicker, Payne, and Morgan (1983) found that people reported a higher tendency to hide after describing a shame experience than after describing a guilt experience. Tangney, Miller, Flicker, and Barlow (1996) replicated this finding in a comparison of shame, guilt, and embarrassment. In addition, they measured the tendency to admit what people had done and to make amends, showing that people who experienced shame reported a lower inclination of both tendencies compared with guilt. Frijda, Kuipers, and Ter Schure (1989) measured behavioral tendencies to approach others, to disappear, to move away from others, and to reject things. They found that shame was characterized by the tendency to disappear from view but also by the desire to undo the shame situation. These action tendencies are an important experiential component of emotions because they reflect the priority of goal-directed behavior that is motivated by the emotion (Frijda, 1986). However, the relationship between action tendencies and actual behavior is not always strong and sometimes even absent because of the many situational, personal, and social factors that may intervene (Frijda, 2004). Thus, we can tentatively conclude that studies of shame experiences so far have not yet addressed the possibility that shame may serve a positive interpersonal function.

The Function of Shame as a Moral Emotion

Apart from being a self-conscious emotion, shame has also been perceived as one of the moral emotions that motivate prosocial behavior (e.g., Emde & Oppenheim, 1995; Goldberg, 1991). Moral emotions are emotions that are linked to the interests of other people (Haidt, 2003). Adam Smith, the founder of modern economics, suggested as early as 1759 that moral sentiments lead people to focus on the other and on how one’s own behavior affects the others’ well-being (Smith, 1759). When there is a conflict between self-interest and others’ interests (i.e., a social dilemma), moral sentiments motivate people to take into account other people’s interests. This view has been developed further by Frank (1988, 2004), according to whom moral emotions commit people to a prosocial, long-term strategy when selfishness might seduce them to choose immediate rewards at the expense of others. When choosing the immediate reward elicits unpleasant moral emotions such as shame or guilt, this behavioral alternative becomes less attractive. Thus, moral emotions have an interpersonal function in that they stimulate prosocial behaviors in the short run, committing people to long-term prosocial strategies. In Frank’s words: “these emotions serve as commitment devices” (p. 5). It should be emphasized that this conception does not contradict the view that personal experiences of shame may be negative or even ugly. Rather, it emphasizes that the actual function of shame lies in promoting prosocial behavior. Note, however, that this theorizing has not yet been the subject of extensive empirical testing.

The proposed prosocial effects of moral emotions have only recently been supported by empirical research. For example, Ketelaar and Au (2003) showed that people with the natural tendency to act selfishly acted more prosocially in social dilemmas and ultimatum games when they experienced guilt. These findings were replicated by Nelissen, Dijker, and De Vries (2007), who found that induction of the moral emotion, guilt, increased prosocial behavior for people with the tendency to act selfishly but that induction of the nonmoral emotion, fear, did not. However, in contrast to guilt, the case for shame as a moral emotion is less clear. In a series of recent studies, we found prosocial effects for guilt but not for shame (de Hooge et al., 2007). Guilt experiences increased prosocial behavior in everyday situations as well as in a social dilemma, but these effects were not found when participants recalled experiences of shame.

To summarize, the view of shame as a moral emotion suggests that it may have an interpersonal function, but the empirical evidence is still wanting. We think that shame does have this prosocial function but that previous studies have not been able to find this because of the way that emotions were induced. We argue that the relevance of the induced emotion for the behavioral decision at hand is crucial for understanding the interpersonal function of shame.

Exogenous and Endogenous Influences of Shame

Maybe the most important reason to study emotions is that they can explain or predict human behavior (Frijda, 2004). The influence of emotions on behavior is either exogenous or endogenous to current goal pursuit (Zeelenberg & Pieters, 2006). In the literature, this distinction has been made under different names such as integral versus incidental emotions (Lerner & Keltner, 2000) and task-related versus incidental affect (Garg, Inman, & Mittal, 2005). We prefer to use exogenous and endogenous influences of emotions because these terms precisely capture whether the influence comes from within (endogenous) or outside (exogenous) the goal-striving process. Influences of emotions are denoted as endogenous when they concern behaviors in situations that are related to the emotion-causing event. These influences are relevant for and part of current goal pursuit. Examples are the influence of fear of animals on the decision to visit a zoo or the experience of sadness when taking a loved one to the airport for her departure. One instance of endogenous influence in research is Ketelaar and Au’s (2003) Study 2, in which guilt felt after selfish behavior in a social dilemma influenced subsequent interactions with the same interaction partner. We refer to influences of emotions as exogenous when they influence behaviors in situations that are unrelated to the emotion-causing event. These influences are irrelevant for and external to current goal pursuit. Examples of exogenous influences are the spillover effects of emotions resulting from a prior experience, such as watching a happy or a sad movie, on subsequent, unrelated decisions, such as deciding how much to tip the driver of the cab that brings you home. Endogenous and exogenous influences of emotions can have similar behavioral effects, such as guilt motivating prosocial behavior in related and unrelated situations (Ketelaar & Au, 2003). However, due to the specific action tendencies of shame, we think that a distinction between endogenous and exogenous influences of emotions is especially important for understanding the interpersonal effects of shame, as is outlined below.

The central focus of experiences of shame is a threatened or damaged self (Lewis, 1971). Thus, a central motivation of shame will be to cope with this threat. Possible action tendencies following this motivation are social withdrawal (i.e., leaving or hiding; Tangney et al., 1996) but also prosocial behavior (Goldberg, 1991). These action tendencies represent different behavioral options that people can use in order to prevent more damage or even restore the threatened self that is experienced in shame.

When the influence of shame is exogenous, that is, not relevant to the current decision situation, the situation in which the self was threatened is already different from the decision situation at hand. For example, one might still feel residual shame over having given a very bad presentation at a conference when one is sitting in an airplane flying home directly after one’s talk. In this case, the shame is no longer relevant for any decision taken in the airplane, for example, when a stranger asks to swap seats. In fact, by being in a different situation, the motivation underlying shame has already been (partially) satisfied because one has already left the threatening situation (i.e., one’s peers at the conference venue). Therefore, the shame is no longer part of the current goal pursuit and no effects of shame on prosocial behavior are to be expected. Indeed, in previous studies we found no effects of shame on prosocial behavior in situations unrelated to the induction procedure (de Hooge et al., 2007).

When the influence of shame is endogenous, that is, relevant to the current decision situation, stronger behavioral effects can be expected. For example, if one is still at the conference venue after the very bad presentation, one’s self would still be threatened and shame would still motivate action tendencies aimed at reducing or alleviating this threat. One may feel the urge to withdraw from the situation by leaving the conference early, but withdrawal may not always be a realistic option. Alternatively, when confronted with one’s peers at the conference dinner, one may cope with the damaged self by complying with norms for prosocial behavior. In this case, the shame is still highly relevant for one’s decisions at the dinner, for example when an unknown colleague asks to swap seats. Therefore, we hypothesize that endogenous shame does motivate prosocial behavior, whereas exogenous shame does not. This prediction is consistent with the analysis of shame as a commitment device because that theory also predicts prosocial effects and is explicitly designed to explain effects of moral emotions that we currently call endogenous (Frank, 1988, 2004).

It is interesting that the theory of shame as a commitment device also makes another prediction about who will be affected most by experiences of shame. Some people, called prosocials, have a natural tendency to act prosocially, whereas others, called proselfs, have a natural tendency to act more selfishly (Messick & McClintock, 1968). Moral emotions act as commitment devices by making immediate selfish options less attractive. Shame is expected to motivate prosocial behavior especially in people who are tempted to choose the immediate selfish option (i.e., proselfs). Ample research has shown that situational activation of a goal only affects behavior of people for whom that goal is not already chronically activated (Higgins, 1996). Because acting prosocially can be seen as a chronically activated goal for prosocials (see Nelissen et al., 2007), endogenous shame should have little effect on their level of prosocial behavior. Therefore, we hypothesize that endogenous shame most strongly affects the behavior of proselfs by motivating them to act prosocially. This differential behavioral effect for prosocials and proselfs has already been shown in studies of guilt (de Hooge et al., 2007; Ketelaar & Au, 2003; Nelissen et al., 2007). Here, we argue that similar results should be found for shame, but only when the emotion is relevant for the current decision, that is, when it is endogenous.

Examining the Prosocial Effects of Shame

Let us summarize: The current research addresses the interpersonal function of shame. The views of shame as an ugly emotion and shame as a moral emotion appear to espouse contrasting predictions with regard to the question of whether shame does or does not have a positive interpersonal function (i.e., can promote prosocial behavior). We try to reconcile these contradicting views by showing that exogenous shame does not augment prosocial behavior (in line with the view of shame as an ugly emotion), but that endogenous shame does augment prosocial behavior (in line with the view of shame as a moral emotion). The behavioral effects of shame should be found mainly for people with proself orientations, because for these people the motivation to behave prosocially is not chronically activated.

In order to provide a thorough test of our predictions we conducted four experiments using three different types of shame inductions and two different measures for prosocial behavior. In the first three experiments, we measured prosocial behavior in a social dilemma situation. One-shot social dilemma situations are often used to study commitment to long-term prosocial strategies because the costly choice for mutual cooperation in these situations is only beneficial in the long run (Frank, 2004; Ketelaar, 2004). In Experiment 1 (imagined shame) we induced shame via a scenario describing a performance situation, in Experiment 2 (recalled shame) we induced shame with an autobiographical recall procedure, and in Experiment 3 (experienced shame) we induced shame in the lab using an actual performance situation. In Experiment 4, we again induced shame with a scenario, as in Experiment 1, but we measured general prosocial tendencies in everyday situations. Because the design of the four studies and the general approach was identical, we describe them here. The specifics of each experiment are described in the separate method sections.

In all experiments participants were assigned to the conditions of a 2 (emotion condition: shame vs. control) × 2 (emotion influence: exogenous vs. endogenous) between-subjects factorial design with prosocial behavior as dependent variable. Participants first completed the emotion induction that will be described separately for each experiment.

In Experiments 1, 2, and 3, participants continued with a 10-coin give-some dilemma game (Van Lange & Kuhlman, 1994), our dependent measure of prosocial behavior. This measure is often used in social dilemma research (de Hooge et al., 2007; Ketelaar & Au, 2003; Nelissen et al., 2007). In this game, we manipulated the nature of exogenous and endogenous shame by coupling the participant with different interaction partners. In the exogenous condition, the interaction partner was unaware of and unrelated to the shame event. In the endogenous condition, the interaction partner was related to and aware of the shame event. In the 10-coin give-some dilemma, the participants have 10 coins, each worth €0.50 for the participant but €1 for the interaction partner. The interaction partner also has 10 coins, each worth €0.50 for themselves but €1 for the participant. The participant decides how many coins to give to the interaction partner without knowing how many coins the interaction partner would give. In this game, participants would earn most if they kept all their coins for themselves (the most selfish option). In contrast, dyads would earn most if the two members offered all their coins to the other player (the most cooperative option). The number of coins offered was the measure of prosocial behavior. In Experiment 4, we used the nine-item Prosocial Tendencies Scale (de Hooge et al., 2007) as dependent measure.

In all experiments, the overall tendency to act prosocially or selfishly was measured with the often-used Triple Dominance Measure of Social Value Orientations (Van Lange, Otten, De Bruin, & Joireman, 1997). This measure contains nine items consisting of different monetary divisions between the participant and an unknown other. The divisions encompass both prosocial (equality) and proself (maximizing and individualistic) choices. When participants made six or more consistent choices, they were classified as prosocials or proselfs. Following the standard procedure, we left participants who could not be classified out of the analyses. Usually, this constitutes 10% to 20% of all participants, and in our experiments this ranged from 3% to 11%. Social value orientation was always measured last. In all studies, both manipulations of emotion condition and emotion influence had no effects on the SVO classification, all χ2s < 2.20, ns, and all χ2s < 1.70, ns, respectively. After completion of all tasks, participants were thanked and debriefed. In all experiments, we tested the hypothesis that endogenous shame motivated prosocial behavior for proselfs and that exogenous shame had no influence on prosocial behavior. In our studies, we used the Dutch emotion word schaamte for the English emotion word shame. Crosscultural research shows that schaamte refers to similar experiences as the English shame (see Breugelmans & Poortinga, 2006; Breugelmans et al., 2005; Fontaine et al., 2006).

Experiment 1: Imagined Shame

Method

Participants and design

One hundred forty-four undergraduate students at Tilburg University participated in a series of unrelated studies and were paid €7 (approximately $9 at the time of the experiment). After exclusion of 12 participants who could not be classified as prosocial or proself, 132 participants remained (41 males and 91 females, Mage = 21.48 years, SD = 2.41). There were 62 prosocials and 70 proselfs in our sample.

Participants were asked the following: “Imagine you are following a course where everybody has to give a presentation in a work group. In the work group, 25 fellow students are present.” In the shame condition, participants then read the following:

When you have to give your presentation everything goes completely wrong. You stumble over your own words, your story is muddled and at the end it is clear that nobody understood what you were trying to tell. At the end some people from the audience ask you questions. Then it becomes clear that you have no mastery of the subject at all.

In the control condition, participants read the following: “When you have to give your presentation everything goes normally. Your presentation is as good as those of the other students and in no way do you stand out.” A pretest of these materials (N = 123, Mage = 22) showed that participants in the shame condition reported significantly more shame (on a scale ranging from 0 = not at all to 10 = very strongly; M = 8.95, SD = 1.13) than participants in the control condition (M = 2.06, SD = 2.37), t(121) = 21.70, p < .001.

After the emotion induction, participants imagined they played the 10-coin give-some dilemma game with a fellow student whom they did not know very well. In the exogenous condition, the fellow student had not seen the presentation. In the endogenous condition, the fellow student had seen the presentation.

Results and Discussion

Results are displayed in Table 1. We hypothesized that only endogenous shame would motivate prosocial behavior for proselfs. We expected participants in the exogenous shame condition to contribute the same amount of coins as participants in the control conditions, and we expected proselfs in the endogenous shame condition to contribute more to the other person than proselfs in the other three conditions.

psp-95-4-933-tbl1a.gifProsocial Behavior as a Function of Emotion Condition, Emotion Influence, and Social Value Orientation (SVO) in Experiments 1, 2, and 3

The findings supported our hypothesis. A 2 (emotion condition: shame vs. control) × 2 (emotion influence: exogenous vs. endogenous) × 2 (SVO: prosocial vs. proself) ANOVA with prosocial behavior as dependent variable showed significant main effects of emotion influence, F(1, 124) = 9.95, p < .01, ηp2 = .07, and of SVO, F(1, 124) = 16.43, p < .001, ηp2 = .12, and showed no significant two-way interactions, all Fs(1, 124) < 3.01, ns. 1 More important, the results showed a significant three-way interaction, F(1, 124) = 3.82, p = .05, ηp2 = .03. The effects of shame on prosocial behavior differed for prosocials and proselfs, depending on emotion influence. Prosocials and proselfs did not contribute more in the exogenous shame condition compared with the exogenous control condition. Prosocials and proselfs also did not contribute more in the exogenous shame condition compared with the endogenous control condition, t(58) = 1.11, ns, and t(66) = 1.70, ns, respectively.

Endogenous shame did influence prosocial behavior. Proselfs in the endogenous shame condition contributed more to the interaction partner than proselfs in the endogenous control condition and proselfs in the exogenous control condition, t(66) = 3.95, p < .001. A contrast analysis of endogenous shame versus exogenous shame, endogenous control, and exogenous control also showed that proselfs acted more prosocially when experiencing endogenous shame, t(124) = 4.17, p < .001. For prosocials, there was no difference between endogenous shame and endogenous control, or between endogenous shame and exogenous control, t(58) = 0.13, ns. A contrast analysis of endogenous shame versus exogenous shame, endogenous control, and exogenous control showed no differences for prosocials, t(124) = 0.26, ns.

Experiment 1 thus provided support for our hypothesis considering the prosocial effects of exogenous and endogenous shame. Exogenous shame did not influence behavior. In contrast, endogenous shame motivated prosocial behavior for proselfs. To replicate the findings of Experiment 1, we conducted Experiment 2 using a different induction of shame.

Experiment 2: Recalled Shame

Method

Participants and design

One hundred forty-seven undergraduate students of Tilburg University participated in this experiment in partial fulfillment of a course requirement. After exclusion of 12 participants who could not be classified as prosocial or proself, 135 participants remained (32 males and 103 females, Mage = 19.68 years, SD = 2.86). There were 66 prosocials and 69 proselfs in our sample.

Procedure and variables

For our emotion induction manipulation, participants were asked to complete a questionnaire that was placed next to the computer. This questionnaire was adopted from Ketelaar and Au (2003). In the shame condition, participants were asked to report a personal experience in which they felt very ashamed. For example, they wrote about failing an exam, a bad performance in sports, or behaving inappropriately while drunk. In the control condition, participants were asked to describe a normal weekday. Participants worked approximately 10 min on the emotion induction task.

Next, participants continued with the 10-coin give-some dilemma game. In the exogenous condition, participants imagined they played this game with a person whom they had never met before and would probably never meet again in the future. In the endogenous condition, participants imagined they played with a person who was present at or knew of the described event (shame condition) or the normal weekday (control condition).

After the game, participants were asked to reread their situation description and indicate how alone they felt, how much they felt that all attention was drawn toward them, how much they did not want others to know about the described event, and how much they were worried about what others would think of them. These are described in the emotion literature as basic elements of shame (Caplovitz Barrett, 1995; Tangney & Fischer, 1995). Subsequently, participants rated how much shame they felt in the situation or on the normal weekday. We also asked participants to indicate how much guilt, regret, disappointment, sadness, fear, anger at self, anger at others, and dissatisfaction they felt in the situation. All items were rated on 11-point scales ranging from 0 (not at all) to 10 (very strongly). Furthermore, to control for possible differences in type of interaction partner between conditions, we asked participants to indicate whether the person present was a close relative or partner, a friend or colleague, or a vaguely known or unknown other.

Results and Discussion

Manipulation checks

The manipulation checks showed that our manipulation of the emotion shame was successful. Participants in the shame condition scored significantly higher on all basic elements of shame compared with participants in the control condition, all ts(133) > 7.39, all ps < .01. Furthermore, participants in the shame condition felt significantly more shame (M = 8.49, SD = 1.45) than participants in the control condition (M = 1.27, SD = 1.91), t(133) = 24.60, p < .001, and felt significantly more shame than other emotions, all ts(64) > 6.51, all ps < .001. There were no differences between the emotion conditions on the other assessed emotions.

Prosocial behavior

Results for prosocial behavior are displayed in Table 1. Similar to Experiment 1, we expected that only endogenous shame would motivate prosocial behavior for proselfs. A 2 (emotion condition) × 2 (emotion influence) × 2 (SVO) ANOVA with prosocial behavior as dependent variable supported our hypotheses. First, there were significant main effects of emotion condition, F(1, 127) = 3.30, p = .07, ηp2 = .03, of emotion influence, F(1, 127) = 10.02, p < .01, ηp2 = .07, and of SVO, F(1, 127) = 20.32, p < .001, ηp2 = .14, and there was a significant two-way interaction of emotion condition and SVO, F(1, 127) = 8.64, p < .01. More important, the results showed a significant three-way interaction, F(1, 127) = 9.17, p < .01, ηp2 = .07. The effects of shame on prosocial behavior differed for prosocials and proselfs, depending on emotion influence. Prosocials and proselfs did not contribute more in the exogenous shame condition compared with the exogenous control condition. Proselfs also did not contribute more in the exogenous shame condition compared with the endogenous control condition, t(65) = 1.14, ns.

Endogenous shame did influence prosocial behavior. Proselfs in the endogenous shame condition contributed more to the interaction partner than proselfs in the endogenous control condition and proselfs in the exogenous control condition, t(65) = 3.72, p < .001. A contrast analysis of endogenous shame versus exogenous shame, endogenous control, and exogenous control also showed that proselfs acted more prosocially when experiencing endogenous shame, t(127) = 4.73, p < .001. For prosocials, there was no difference between endogenous shame and endogenous control, or between endogenous shame and exogenous control, t(62) = 1.53, ns. A contrast analysis of endogenous shame versus exogenous shame, endogenous control, and exogenous control also showed no differences for prosocials, t(127) = 0.44, ns. Thus, while exogenous shame did not influence prosocial behavior, endogenous shame did motivate prosocial behavior for proselfs.

Unexpectedly, prosocials in the exogenous shame condition contributed less than prosocials in the endogenous control condition, t(62) = 2.70, p < .01. This finding might be explained by the manipulation used. In the shame condition, 34% of the prosocials reported the other to be an unknown other and 34% reported the other to be a friend or colleague. In the control condition, 50% of the prosocials reported the other to be a close relative or their partner. This difference was significant, χ2(2, N = 107) = 6.09, p < .05. Furthermore, in the exogenous conditions, participants interacted with an unknown other. Thus, it is likely that prosocials acted less prosocially in the exogenous shame condition because they interacted with unknown others, whereas in the endogenous control condition they interacted with close relatives or their partner.

To summarize, the findings of Experiment 1 were replicated with a different shame induction. Again the data revealed that only endogenous shame motivates prosocial behavior for proselfs. Even though these two previous studies employed emotion inductions that are commonly used in literature, the credibility of the findings would be much increased if shame was experimentally induced. Therefore, we conducted Experiment 3.

Experiment 3: Experienced Shame

Method

Participants and design

One hundred sixty-three undergraduate students of Tilburg University participated in this experiment in partial fulfillment of a course requirement. After the exclusion of 5 participants who could not be classified as prosocial or proself, 158 participants remained (47 males and 111 females, Mage = 19.88 years, SD = 3.38). There were 89 prosocials and 69 proselfs in our sample.

Procedure and variables

Participants entered the laboratory in groups of 8 to 12 participants. They were seated in separate cubicles and informed that they would form groups with 3 other participants present. The participants would be connected to the other group members through their computer. The session started with two intelligence tests. Participants were told that the intelligence tests were meant to see whether group members were comparable in knowledge and academic abilities. In total, participants could earn 20 points on the two intelligence tests. In the first test, participants answered 10 general knowledge questions (adopted from Van Harreveld, Van Der Pligt, Nordgren, & Claassen, in press). For every good answer, participants received 1 point. In the second test, English language skills were examined by 10 items, where every good answer counted as 1 point.

Following the intelligence tests, the computer calculated the number of points earned by each group member. In the meantime, participants were told that their score would give insight into their academic abilities and their chances of obtaining an academic degree. They were explained that a score below 12 points indicated (highly) insufficient abilities, between 12 and 16 points indicated normal abilities, and above 16 points indicated (highly) sufficient abilities. After the explanation, participants publicly received bogus feedback about their performance. In the shame condition, all group members saw on their computer screen that the participant earned 9 points (insufficient), whereas the other group members earned 19 (highly sufficient), 17 (sufficient), and 16 points (normal/sufficient). In the control condition, the participants earned 16 points (normal/sufficient), similar to the points earned by the other group members (19, 17, and 16 points). Note that in the control condition, although they received an average number of 16 points, participants still had the lowest score in the group. This makes our experiment a conservative test of the effects of shame.

After the feedback, participants continued with the 10-coin give-some dilemma game with a student from another group who knew nothing about the intelligence score of the participant (exogenous condition) or with a student from the same group who knew about the intelligence scores (endogenous condition). As a manipulation check, participants responded to the same items as in Experiment 2.

Results and Discussion

Manipulation checks

The manipulation checks showed that our manipulation of shame was successful. Participants in the shame condition scored significantly higher on all elements of shame compared with the control condition, all ts(156) > 8.75, all ps < .001. Furthermore, participants in the shame condition felt significantly more shame (M = 6.90, SD = 1.66) than participants in the control condition (M = 1.25, SD = 1.27), t(156) = 23.92, p < .001, and significantly more shame than any other emotion, all ts(81) > 8.08, all ps < .001. There were no differences between emotion conditions on the other assessed emotions.

Prosocial behavior

Results for prosocial behavior are displayed in Table 1. The findings again supported our hypothesis. A 2 (emotion condition) × 2 (emotion influence) × 2 (SVO) ANOVA with prosocial behavior as dependent variable showed a main effect of SVO, F(1, 150) = 10.80, p < .01, ηp2 = .07, no significant two-way interactions, all Fs(1, 150) < 2.41, ns, and a significant three-way interaction, F(1, 150) = 3.78, p = .05, ηp2 = .03. The effects of shame on prosocial behavior differed for prosocials and proselfs, dependent upon emotion influence. Prosocials and proselfs did not contribute significantly more in the exogenous shame condition compared with the exogenous control condition or compared with the endogenous control condition, t(85) = 0.78, ns, and t(65) = 0.19, ns, respectively.

Endogenous shame did influence prosocial behavior. Proselfs in the endogenous shame condition contributed more to the interaction partner than proselfs in the endogenous control condition and proselfs in the exogenous control condition, t(65) = 1.69, p = .09. A contrast analysis of endogenous shame versus exogenous shame, endogenous control, and exogenous control also showed that proselfs acted more prosocially, t(150) = 2.54, p < .05. For prosocials, there was no difference between endogenous shame and endogenous control, or between endogenous shame and exogenous control, t(85) = 0.85, ns. A contrast analysis of endogenous shame versus exogenous shame, endogenous control, and exogenous control also showed no differences for prosocials, t(150) = 1.05, ns.

The results of Experiments 1 and 2 were thus replicated using a performance situation in the lab. The data revealed that only endogenous shame motivated prosocial behavior for proselfs, whereas exogenous shame had no influence on prosocial behavior. In Experiments 1, 2, and 3 we used a social dilemma game to measure prosocial behavior. To extend these findings beyond social dilemma situations, Experiment 4 was conducted. In this experiment, we induced shame with the scenario used in Experiment 1 and measured prosocial tendencies in everyday situations.

Experiment 4: Prosocial Behavior in Daily Situations

Method

Participants

One hundred seventy undergraduate students at Avans University Breda and at Tilburg University volunteered to participate in this experiment. After exclusion of 20 participants who could not be classified as prosocial or proself, 150 participants remained (43 males and 107 females, Mage = 20.03 years, SD = 3.83). There were 71 prosocials and 79 proselfs in our sample.

Design

Participants first read the scenario used in Experiment 1 and subsequently rated how much shame, pride, guilt, fear, and sadness they would feel in this situation on a scale ranging from 0 (not at all) to 10 (very strongly). Next, participants continued with the Prosocial Tendencies Scale, our dependent measure. This 9-item scale is a measure of everyday prosocial tendencies and helping (de Hooge et al., 2007). We adapted the Prosocial Tendencies Scale for the endogenous and exogenous condition. For each item, participants were asked to report how much they wanted to undertake that action directly after the scenario. In the exogenous condition, the items concerned a fellow student who had not seen the presentation. In the endogenous condition, the items concerned a fellow student who had seen the presentation. Two example items are “I would like to comfort the student when (s)he is emotionally upset” and “I would like to help the student while others are watching me.” All items were rated on 11-point scales ranging from 0 (not at all) to 10 (very much). A confirmatory factor analysis on the nine items showed a clear one factor solution with an eigenvalue of 5.08 (second and third eigenvalues were 1.40 and 0.68). The factor explained 56% of the variance and the nine items formed a reliable scale (α = .90).

Results and Discussion

The manipulation check showed that the emotion induction was successful. Participants in the shame condition reported significantly more shame (M = 8.68, SD = 1.44) than participants in the control condition (M = 2.11, SD = 2.36), t(148) = 21.37, p < .001, and reported significantly more shame than the other reported emotions, all ts(87) > 11.15, all ps < .001.

Results for prosocial behavior are displayed in Table 2. A 2 (emotion condition) × 2 (emotion influence) × 2 (SVO) ANOVA with prosocial behavior as dependent variable showed a main effect of SVO, F(1, 142) = 3.93, p = .05, ηp2 = .03, no significant two-way interactions, all Fs(1, 142) < 3.00, ns, and a significant three-way interaction, F(1, 142) = 4.21, p < .05, ηp2 = .03. The effects of shame on prosocial behavior differed for prosocials and proselfs, depending on emotion influence. Prosocials and proselfs did not score higher in the exogenous shame condition compared with the exogenous control condition or compared with the endogenous control condition, t(67) = 0.63, ns, and t(75) = 0.07, ns, respectively.

psp-95-4-933-tbl2a.gifProsocial Behavior as a Function of Emotion Condition, Emotion Influence, and Social Value Orientation (SVO) in Experiment 4

Endogenous shame did influence prosocial behavior. Proselfs in the endogenous shame condition had a higher score than proselfs in the endogenous control condition and proselfs in the exogenous control condition, t(75) = 2.14, p < .05. A contrast analysis of endogenous shame versus exogenous shame, endogenous control, and exogenous control also showed that proselfs had a higher score when experiencing endogenous shame, t(142) = 3.59, p < .001. For prosocials, there was no difference between endogenous shame and endogenous control, or between endogenous shame and exogenous control, t(67) = 0.40, ns. The contrast analysis also showed no differences for prosocials, t(142) = 0.47, ns.

Taken together, endogenous shame also motivates prosocial tendencies in everyday situations for proselfs. Exogenous shame does not motivate prosocial tendencies. These results obtained with the different measure of prosocial behavior replicate the results of Experiments 1, 2, and 3.

General Discussion

As ugly and negative as shame experiences can be, feeling this emotion can have clear positive consequences for interpersonal behavior. Shame can act as a commitment device, motivating people to act prosocially and thereby committing them to long-term strategies. This prosocial behavior benefits others’ well-being and improves social relationships. Thus, shame does have a constructive interpersonal function.

Four experiments clearly support the notion that shame serves an interpersonal function. Using three different emotion inductions and two different dependent measures, we repeatedly found that endogenous shame motivates prosocial behavior. After imagining shame with a scenario, proself participants acted more prosocially toward the audience in a social dilemma game (Experiment 1). This finding was replicated when participants recalled a shame event (Experiment 2). Moreover, when experiencing shame after a failure on performance tasks, proself participants also acted prosocially toward the audience in the lab (Experiment 3). Finally, Experiment 4 showed that this effect could be generalized beyond social dilemmas to helping tendencies in everyday situations. Therefore, it seems safe to conclude that shame can be seen as a moral emotion motivating prosocial behavior.

Given that these experiments are the first empirical evidence for prosocial effects of shame, it is only sensible to ask why these effects were not found earlier. We think that there are at least three reasons for this. First, shame research has mainly focused on the correlates of shame-proneness and not on effects of situational experiences of shame (e.g., Gilbert et al., 1994; Harder et al., 1992). Shame-proneness is generally related to a wide array of negative psychological conditions and behaviors (for an overview, see Tangney & Fischer, 1995). However, while shame-proneness and situational experiences of shame are related, they do not have similar behavioral effects (e.g., Allan et al., 1994; Rüsch et al., 2007). Findings for shame-proneness can therefore not be generalized to behavioral effects of situational experiences of shame. Second, in line with the view of shame as an ugly emotion, studies on effects of situational experiences of shame have mainly focused on action tendencies like social withdrawal (e.g., Tangney et al., 1996; Wicker et al., 1983). Effects of situational experiences of shame on behaviors other than withdrawal tendencies have simply not been addressed. Third, the one exception that did focus on behavior other than withdrawal tendencies, namely the studies on prosocial behavior reported by de Hooge et al. (2007), used only exogenous influences of shame and therefore found no effects. By moving beyond shame-proneness and withdrawal tendencies, and focusing on endogenous influences of shame on prosocial behavior, the present experiments contribute to our understanding of the behavioral effects of shame.

We hasten to say that, even though the results showed that shame is a moral emotion motivating prosocial behavior, they are not at variance with the view of shame as an ugly emotion. If anything, we believe that the two views can easily be reconciled. In line with the ugly view, experiences of shame are often unpleasant, giving rise to a wide array of negative intrapersonal thoughts and feelings (e.g., Ausubel, 1955; Tangney, 1991). The moral view additionally suggests that these negative experiences induce people to engage in prosocial behavior. Negative, self-conscious emotions act as commitment devices precisely because they raise the costs of selfish behavior. This benefits people by committing them to long-term strategies, and it benefits others by increasing their well-being (Frank, 1988). The present experiments thus lend empirical credibility to Adam Smith’s (1759) claim that “moral sentiments are sufficient for the harmony of society” (p. 23).

There are two alternative explanations that might be given for the prosocial effects of shame. One could be that shame motivates prosocial behavior as an appeasement strategy (e.g., Tangney & Fischer, 1995). The reasoning behind this explanation would be that shame, arising after violation of a social norm, motivates appeasement behaviors in order to avoid conflicts or punishment. Another explanation is that shame motivates prosocial behavior in order to boost social esteem (Goldberg, 1991). The person would be motivated to boost the damaged self that has been caused by the shame experience. However, neither alternative is supported by the findings of Experiment 4. If shame motivated prosocial behavior in order to appease or to boost social esteem, stronger prosocial behavior would be expected with an audience than without an audience. However, participants in the endogenous shame condition preferred “helping the student when (s)he does not know who is helping” (M = 5.78, SD = 2.20) above “helping the student while I get in the spotlight as a consequence” (M = 4.51, SD = 2.21), t(40) = 3.24, p < .01, and preferred “helping the student when (s)he does not know who is helping” (M = 5.78, SD = 2.20) above “helping the student while others are watching the way I do everything” (M = 4.83, SD = 2.40), t(40) = 2.52, p < .01, as well as “helping the student without him/her knowing” (M = 5.37, SD = 2.15) above “helping the student while I get in the spotlight as a consequence” (M = 2.06, SD = 2.37), t(40) = 2.00, p = .05. In our view, the view of shame as a commitment device provides the most parsimonious explanation of the prosocial effects found in our experiments.

We want to stress the fact that the present findings cannot be attributed to general negative affect or negative mood. It is the case that there is much research attesting to the fact that people act prosocially when they are sad or experiencing a bad mood. They may do so because acting prosocially can be a reinforcing, mood-enhancing experience. For example, people are more willing to collect donations for a charity after a bogus aptitude test (Weyant, 1978), they help more after reminiscing about unhappy events or after reading a series of depressing statements (Cialdini, Kenrick, & Baumann, 1982), and they donated more money to all kinds of charities after the fearful events of September 11, 2001 (Penner, Dovidio, Piliavin, & Schroeder, 2005). None of the mood-management theories differentiates between endogenous and exogenous affect, and much of the empirical work showed increased prosocial behavior induced by negative affect stemming from unrelated events (exogenous affect, using our terminology). In that light it is important to realize that we had strong theoretical reasons to predict only effects of endogenous shame, and not of exogenous shame, and only for proselfs, not for prosocials. We are not aware of a model or theory that would be consistent with this specific pattern of results. In addition, when we computed a measure of general negative affect by averaging all negative emotions that were assessed, we found that there were no significant differences between the endogenous shame and exogenous shame conditions. Thus, the behavioral differences that we obtained across four experimental studies could not be explained in terms of general negative affect.

Although the present experiments show that shame is a moral emotion similar to guilt, we do not mean to imply that shame and guilt are identical emotions. Shame and guilt are both moral emotions that motivate prosocial behavior. They both act as commitment devices and can have similar behavioral effects. Nonetheless, the phenomenological experiences and psychological origins of shame and guilt are clearly distinct. Shame arises after a negative evaluation of the self, reflecting the appraisal that something is wrong or defective with one’s core self (Lewis, 1971). It activates a focus on others’ thoughts about oneself and on being accepted by the group. In contrast, guilt arises after an evaluation of the behavior, reflecting the appraisal that one has caused harm, loss, or distress to a relationship partner (Breugelmans & Poortinga, 2006; Tangney et al., 1996). Indeed, guilt appears to be strongest in dyadic, communal relationships, activating a focus on the hurt other and behavior to maintain and enhance the dyadic relationship (Baumeister et al., 1994). Thus, shame and guilt are clearly distinct moral emotions, although they both motivate prosocial behavior.

The distinction that we made between endogenous and exogenous emotions is important for emotion research. The distinction has been made theoretically (Zeelenberg & Pieters, 2006), but our studies are the first to simultaneously examine the endogenous and exogenous influences of an emotion. For some emotions, exogenous and endogenous influences may be similar. For example Ketelaar and Au (2003) showed that exogenous influences of guilt in one study and endogenous influences of guilt in another study both led to increased prosocial behavior. However, for other emotions such as shame, the distinction can explain important differences in observed behavior. For shame, the distinction is important due to its different action tendencies. Being in a situation unrelated to the shame event already (partially) fulfills the action tendency of shame to withdraw. In contrast, being in situations related to the shame event leaves the action tendencies of shame unfulfilled. Therefore, exogenous influences of shame do not have the same prosocial effects as endogenous influences of shame. In view of these results, it seems safe to suggest that, for a complete understanding of the functions of emotions, studies of both exogenous and endogenous influences are necessary.

Taken together, shame has been understood as a social emotion, as an ugly emotion, and as a moral emotion. Until now empirical research has been guided primarily by the ugly view, drawing attention to a focus on the negative consequences of shame. This left students of emotion wondering whether shame had any function at all. At present, we argue that this paradox is solvable. The current findings suggest an important interpersonal function of shame: Shame can act as a commitment device motivating prosocial behavior. Shame may not be so ugly after all.

Footnotes

1 Throughout the manuscript we report effect sizes in the form of partial eta squared, which is the sum of squares of the relevant effect divided by the sum of squares of the effect plus the sum of squares of the relevant error term. This is the standard effect size produced by SPSS (Tabachnick & Fidell, 2001).

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Submitted: April 23, 2007 Revised: February 6, 2008 Accepted: February 17, 2008


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Source: Journal of Personality and Social Psychology. Vol.95 (4) US : American Psychological Association pp. 933-943.
Accession Number: psp-95-4-933 Digital Object Identifier: 10.1037/a0011991

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