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When Are Apologies Effective?
An Investigation of the Components that Increase an Apology’s Efficacy
A dissertation presented
by
Krista M. Hill
To
The Department of Psychology
In partial fulfillment of the requirements for the degree of
Doctor of Philosophy
in the field of
Psychology
Northeastern University
Boston, Massachusetts
May 10, 2013 2
WHEN ARE APOLOGIES EFFECTIVE?
AN INVESTIGATION OF THE COMPONENTS THAT INCREASE AN APOLOGY’S
EFFICACY
by
Krista M. Hill
ABSTRACT OF DISSERTATION
Submitted in partial fulfillment of the requirements
For the degree of Doctor of Philosophy in Psychology
In the College of Science of
Northeastern University
May 10, 2013
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ABSTRACT
Although apologies are a staple of civil society, it is unclear whether they are effective and if effective, what components are involved in the perfect apology. The term “components” refers to general categories of actions (both verbal and nonverbal) that may be present in an apology. Two studies were conducted to examine (1) whether apologies are effective in eliciting positive outcomes for an apologizer and (2) potential apology components that may obtain positive outcomes for an apologizer.
For Study 1, six meta-analyses of previously published studies, examined the relation between apologies and offended parties’ (1) forgiveness, (2) attributions of positive qualities to the apologizer, (3) positive emotions toward the apologizer, (4) positive legal outcomes for the apologizer, (5) intentions to purchase goods from the apologizer, and (6) overall positive reactions and behaviors toward the apologizer (i.e., combining across all outcomes). High- inference coding was used to determine which theory-driven components contribute most to the effectiveness of apologies. Analyses revealed a significant influence of apologizing on forgiveness (k = 79, r = .32, random effects Z = 8.16 p < .001), positive attributions of the apologizer (k = 60, r = .24, random effects Z = 6.69, p < .001), positive emotions toward the apologizer (k = 43, r = .33, random effects Z = 9.41, p < .001), legal sentencing (k = 11, r = .13, random effects Z = 3.49, p < .001), and purchase intentions (k = 10, r = .23, random effects Z =
2.85, p < .01). Combining across all outcomes apologizing was effective (k = 144, r = .27, random effects Z = 10.72, p < .001). All distributions of effect sizes were significantly heterogeneous. Significant moderators included the apology components of remorse, offers of compensation, and an acknowledgment of violated rules and norms. 4
The aim of Study 2 was to examine the relationship between apology components and judge-rated outcomes. Participants apologized for a transgression they committed on video.
Trained coders then rated the apologies for apology components. Finally, videos were watched by new participants (i.e., judges) who rated the apologies on various outcomes. This was the first time this paradigm was used to study apologies. The apology components included both apologizer-rated emotions and coder-rated verbal (i.e., remorse, acknowledgment of violated rules and norms, and compensation) and expressive behavior (i.e., guilt and shame). The judge- rated outcomes included empathy, sympathy, dispositional attributions, forgiveness, trust, and sincerity. Analyses revealed that coder-rated remorse, guilt, and shame were significant predictors of judge-rated empathy, sympathy, forgiveness, trust, and sincerity. Similarly, apologizer-rated self-conscious emotions also predicted these outcomes. These relationships remained significant even when controlling for judge-rated severity of the transgression.
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Acknowledgments
First and foremost I would like to thank my family for their endless encouragement and support. Thank you for being my biggest fans throughout this process and throughout my life.
Words cannot express how much your support and love have meant to me. From a very young age you instilled in me the importance of hard work, which made this degree possible.
I would also like to extend my deepest thanks to the faculty that have helped me tremendously during this process. To my advisor, Randy Colvin, I can never thank you enough for taking a chance on me as an undergraduate so many years ago. Thank you for your guidance, support, and believing in my abilities. I hope we continue our friendship and collaborate for years to come. Thank you, Judith Hall and Nancy Kim, for your helpful comments on the many stages of my dissertation.
To my research brother and sister, Sun Park and Stefanie Tignor, thank you for your professional advice, encouragement, and bringing joy to this experience. I loved working with the both of you and hope to continue to do so.
Thank you Allison Seitchik and Sarah Gunnery. Not only I am leaving graduate school with a degree, but also with two best friends. I feel so fortunate to have gone through this process with such wonderful and intelligent women and I promise many “networking” meetings in the future.
To Martha Caffrey, Amy DiBattista, Mollie Ruben, Jolie Baumann, Leah Dickens,
Danielle Blanch Hartigan, and Susan Andrzejewski, you are the reasons why I enjoyed coming to the office everyday. Thank you for the coffee breaks and laughs. 6
Thank you to my dear friends, specifically Jessie Canor and Corinne McHugh, for always being there to listen, especially during these last few years. You never stopped encouraging me to work hard and always brought a smile to my face with your daily emails.
I would also like to thank the following undergraduate assistants who contributed to the completion of this project: Katie McEnaney, Lisa Bartucca, Gina Strumolo, Nicole Colley,
Colleen Trinh, and Kelly Kolkmeyer.
And finally I dedicate this dissertation to my wonderful husband-to-be, Matt. I can never thank you enough for your love and encouragement. Thank you for listening when I needed someone to listen, for opening your arms when I needed support, and for making me laugh when
I needed to smile. These past five years have brought so many wonderful things for us and I look forward to our post-PhD life together.
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TABLE OF CONTENTS
Abstract 2
Acknowledgments 5
Table of Contents 7
List of Tables 8
List of Figures 9
Chapter 1: Introduction 11 I. What Is An Apology and Why Do People Apologize? 13 II. Are Apologies Effective in Producing Positive Outcomes? 15 III. Which Components Make Apologies More Effective? 17 IV. Why Do Apologies and The Components Work? 20
Chapter 2: Study 1- Meta-Analysis 23 I. Methods 24 II. Results 28 III. Discussion 35
Chapter 3: Study 2 40 I. Methods 40 II. Results 46 III. Discussion 54
Chapter 4: General Discussion 58 I. Limitations and Future directions 60 II. Conclusion 62
References 63
Footnotes 81
Tables 82
Figures 107
Appendix A 109
Appendix B 111
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List of Tables
Table 1: Characteristics of Studies Included in the Meta-Analysis 82
Table 2: Results for Meta-Analyses Examining Efficacy of Apologies 92
Table 3: Correlations Among Apology Components and Effect Size 93
Table 4: Interaction Analysis for Remorse, Acknowledgment of Violated Rules 94
and Norms, and Compensation for High Social Distance Relationships
Table 5: Inter-Rater Reliability Indices and Inter-Correlations For Apology 95
Components
Table 6: Phase 1 Apologizer Self-Rated Emotion Descriptive Statistics and 96
Factor Loadings
Table 7: Apologizer Self-Rated Emotion Factor Descriptive Statistics and 98
Inter-correlations
Table 8: Apologizer Self Rated Emotion Factors Correlated with Apology and 99
Transgression Specific Questions
Table 9: Correlations Among Judge-Rated Items 100
Table 10: Coder-Rated Items Correlated with Apologizer and Judge-rated Items 101
Table 11: Apologizer-rated Items Correlated with Judge-rated Items 103
Table 12: Apologizer and Coder-Rated Components Correlated with 104
Judge-Rated Outcomes Controlling for Judge-Rated Severity
Table 13: Apologizer-rated Emotions Predicting Judge Reactions 105
Table 14: Acknowledgment, Remorse, and Compensation Predicting Judge 106
Reactions
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Table 15: Interaction Analysis for Coder-Rated Remorse, Coder-Rated 107
Guilt-Shame Aggregate, and Apologizer-Rated Self-conscious
emotions
Table 16: Coder Rated Remorse, Coder Rated Guilt-Shame Aggregate, and 108
Apologizer Self Conscious Emotions Predicting Judge Reactions
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List of Figures
Figure 1: Apology-Outcome Process Model 109
Figure 2: Mediation Analysis Diagram 110
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Chapter 1: Introduction
Apologies are a core feature of human relationships. Politicians, CEOs, public figures, criminals, romantic partners, and friends all use apologies to repair relationships and protect their reputations (Lazare, 2005). Although apologies are a staple of civil society, it is unclear when they are effective and which components are involved in the perfect apology. Some studies suggest that apologies are beneficial (e.g., Darby & Schlenker, 1982; Eaton, Struthers, &
Santelli, 2006; Exline & Baumeister, 2000) and lead to positive outcomes such as forgiveness
(e.g., Fehr, Gelfand, & Nag, 2010), positive feelings toward the transgressor (e.g., DeCremer, van Dijk, & Pillutla, 2010), and reduced sentencing in legal cases (e.g., Robbennolt, 2003). Other studies suggest that apologies can have detrimental effects, especially if not done well (e.g.,
DeCremer et al., 2010; Eaton, Struthers, Shomrony, & Santelli, 2007; Zechmeister, Garcia,
Romero, Vas, 2004).
Researchers who find the latter suggest that an apology’s effectiveness is highly dependent on whether certain components of the apology are present or absent. The term
“components” refers to three general categories of actions (both verbal and nonverbal) that may be present in an apology. These three categories are (1) an expression of empathy for the offended party/an expression of remorse, (2) an acknowledgment of violated rules and norms, and (3) an offer of compensation. Researchers have found that when one or more of these components is (are) manipulated, an apology’s effectiveness is likely to change (e.g., Scher &
Darley, 1997). This begs the question: which components produce the most positive outcomes?1
To date, there is no agreed upon empirical answer. For my dissertation two studies were conducted to answer this question. In Study 1 six meta-analyses were conducted that evaluated the empirical literature on the effectiveness of apologies and the components that moderate the 12 relationship between apology and offended party outcomes. One meta-analysis was completed for each of five outcomes and the sixth meta-analysis examined all outcomes together. These outcomes include forgiveness, positive perceptions of the transgressor, positive emotions toward the transgressor, positive legal outcomes for the transgressor, and offended parties’ purchase intentions (i.e., willingness to purchase from a transgressor in the future). In Study 2 judges observed and evaluated real life apologies (i.e., apologies for transgressions given by those who transgressed) on several dimensions to examine the components that make an apology more and less effective.
Figure 1 displays the model used to guide the presentation of the literature as well as the proposed studies. The model outlines the apology process starting at the transgression. The offended party and others who experienced the transgression react to it. They might become upset, angry, or terminate their relationship with the transgressor. Next, the transgressor either admits to him or herself that a transgression was committed and acknowledges its consequences on others, or the transgressor might be unaware of the transgression because its consequences were not observed or defensive processes kept it from the transgressor’s conscious awareness. If the transgressor acknowledges the effect of his or her transgression on others, the transgressor will have a cognitive-emotional response (Figure 1, a). The transgressor might experience feelings of empathy and guilt, or be motivated to manage his or her public reputation. In both cases, the transgressor will provide an apology. One or more components (Figure 1, b) of the apology may elicit emotional or cognitive responses from the offended party (Figure 1, c). These internal responses may be followed by behavioral responses (Figure 1, d) from the offended party. In this dissertation, I specifically focus on the processes occurring during and after the transgressor’s apology (i.e., Figure 1, a). 13
What is an Apology and Why do People Apologize?
An apology, as defined by Lazare (2005) is “an encounter between two parties in which one party, the offender, acknowledges responsibility for an offense or grievance and expresses regret or remorse to a second party, the aggrieved” (p. 23). Apologies may be interpersonal, intergroup, or a mix of the two. In the latter case, an organization might apologize to an individual (e.g., a CEO apologizes to an individual) or a person might apologize to a group (e.g., person apologizes to church congregation).
Researchers have identified several motives for why people apologize. These motives fall into two categories, internal regulation and social reputation maintenance (e.g., Lazare, 2005;
McCullough, Worthington, & Rachal, 1997; Zechmeister et al., 2004). Internal regulation motives are characterized by internal distress such as empathic concern for another, or emotions such as guilt and embarrassment (Baumeister, Stillwell, & Heatherton, 1994; Hareli &
Eisikovits, 2006; Tangney & Dearing, 2003). For internal regulation motives, transgressors seek to restore their dignity and self-esteem, and restore the image of the harmed. For example, after cheating on a spouse, a person may feel guilt for what he or she has done and feel empathy for the spouse who was hurt. Transgressors who are motivated to maintain their social reputation attempt to influence how others perceive and behave toward them. For example, an athlete who is caught using performance-enhancing drugs may apologize to restore his status as a beloved celebrity as opposed to relieving internal distress. Below both motives are discussed in greater detail.
As seen in Figure 1 both internal regulation and social reputation maintenance motives are (1) the transgressor’s emotional and cognitive reactions to how they perceive the reactions of 14 others and (2) reasons for why people apologize. Below I discuss both the internal and external motives in further detail.
Internal regulation. Research suggests that when people become aware their behavior has offended someone, they will experience various emotional states such as guilt and empathy for the offended party (Baumeister et al., 1994; Tangney, Stuewig, & Mashek, 2007). Guilt is defined as regret about behavior that violated an ethical or social code. It is considered a self- conscious emotion because it occurs in response to self-reflection (Tangney & Dearing, 2002).
Subjectively, guilt is an unpleasant emotional state that has two affective components--empathic concern for the suffering of the offended party (e.g., Hoffman, 1982) and anxiety about the transgression and its implications for the relationship between the transgressor, the offended party, and observers (see Baumeister & Tice, 1990).
Empathy is, in part, a “shared emotional response between an observer and a stimulus person” (Feshbach, 1975). Definitions of empathy typically include cognitive and affective components. The cognitive component emphasizes understanding another person’s affective or cognitive status (e.g., Borke, 1971; Hogan, 1969). For example, a man experiencing cognitive empathy toward his romantic partner may understand that she is feeling sad. The affective component focuses on the matching of another’s affective state (e.g., you feel sad so I feel sad).
It may also include feeling an emotion that is similar, but different from the emotion the other person is feeling (e.g., I feel upset when you feel depressed).
Guilt and empathy may prompt apologizing for two reasons. First, guilt prompts the transgressor to focus on the transgression and its implications, including how the transgression affected the offended party. Focusing on the offended party leads to awareness of the internal state of the offended party (i.e., empathy) and the damaged status of the relationship between the 15 transgressor and the offended party (Eisenberg, 1986; Hoffman, 1982; Zahn-Waxler &
Robinson, 1995). Once the transgressor understands the offended party’s feelings about the transgression and the relationship, the transgressor may be motivated to help the offended party feel better and mend the relationship. Second, guilt and empathy may motivate apologies because the transgressor may wish to relieve the personal distress that accompanies these states
(Eisenberg & Miller, 1987; Lazare, 2005).
Social reputation maintenance. Transgressors often offer apologies with the goal of repairing their post-transgression reputations (Hareli, Shomrat, & Biger, 2005). In these self- serving situations, transgressors apologize in an attempt to return to their pre-transgression status without regard for how the offended party is feeling. For example, an athlete who is caught using performance-enhancing drugs may apologize to restore his celebrity status as opposed to relieving the shame felt by being a poor role model for young fans. In this case, apologizing acts as a tool for impression management (Schlenker, 1985; Tedeschi & Riess, 1981).
Impression management refers to “the process by which individuals attempt to control the impressions others form of them” (p. 34, Leary & Kowalski, 1990). People’s reputations are important because they affect how others will behave toward them. A good reputation is associated with social approval, successful interpersonal relationships, social support from others, and power. People whose reputations diminish may lose these rewards. Therefore, people often feel compelled to fix their damaged reputations by apologizing for their bad deeds (Leary
& Kowalski, 1990, Schlenker, 1980).
Are Apologies Effective in Producing Positive Outcomes?
Although peoples’ motivations for apologizing range from well-intentioned to self- centered, the majority of research indicates that apologies are associated with positive outcomes, 16 such as forgiveness. In Fehr, Gelfand, and Nag’s (2010) meta-analysis on the situational and dispositional correlates of forgiveness, they synthesized the effects of 23 studies on the relationship between apology and forgiveness and found an overall positive effect size of r = .42.
Similarly, apologies have been found to be associated with the offended party’s positive emotions for, and positive perceptions of, the transgressor (DeCremer, van Dijk, & Pillutla,
2010; Xie & Peng, 2009). For example, apologies are associated with ratings of transgressor (i.e., apologizer) trustworthiness (DeCremer et al., 2010), liking (Bono, 2005), and satisfaction by the offended party (Howley, 2009). Further, apologies often alter an offended party’s behavior, leading to less retaliation (e.g., Mullet, Riviere, & Sastre, 2007), increases in purchasing behavior after a corporate apology (Liao, 2007), and positive intentions such as investing in a company, recommending a company, and requesting more information about a company after the company apologized (Lyon & Cameron, 2004).
However, the correlation between the presence of an apology and positive outcomes (e.g., forgiveness) is not perfect. Apologies vary greatly and may contain components (i.e., categories of verbal and nonverbal actions) that influence their effectiveness (e.g., Fehr & Gelfand, 2009).
This raises the question: How do components influence the effectiveness of an apology? The answer is not yet clear. This may be due to the fact that in most apology studies participants are simply assigned to ‘‘apology present” versus ‘‘no apology present” conditions (e.g., Frantz &
Bennigson, 2005; McCullough, Rachal, Sandage, Worthington, Brown, & Hight, 1998; Ohbuchi,
Kameda, & Agarie, 1989; Struthers, Eaton, Santelli, Uchiyama, & Shirvani, 2008; Tomlinson,
Dineen, & Lewicki, 2004) and the implications of specific components are not systematically evaluated (for exceptions see Darby & Schlenker, 1982; Fehr & Gelfand, 2009; Santelli,
Struthers, & Eaton, 2009; Schmitt, Gollwitzer, Forster, & Montada, 2004). This is not to say that 17 components are not present in the apology stimuli provided to participants. In fact, in most apology studies these components are present, but are not empirically examined. For example, in a study by Giacalone and Payne (1995), participants read the apology, "I am very sorry and embarrassed by what I did. I understand that revealing such personal information is wrong, and that I made a mistake. I can only promise that I will not do it again. I am prepared to make restitution to the company and to the employees affected as a result of my actions." Within this apology several components are present, such as acknowledgment of a violated rule and compensation. Because these components are present in many studies, they can be analyzed in a meta-analysis. Meta-analysts can code each apology for the components and then examine how these components moderate the impact of the apology on positive outcomes across many studies.
I use this method in the current meta-analyses to provide insight into the composition of an effective apology.
Which Components Make Apologies More Effective?
Across such fields as law, sociology, and psychiatry, scholars have proposed components that may increase an apology's effectiveness. This discussion is mostly theoretical with the exception of some recent empirical studies (Boyd, 2011; Cunningham, 2004; Darby &
Schlenker, 1982; Fehr & Gelfand, 2009; Goffman, 1967; Govier & Verwoerd, 2002; Lazare,
2004; Scher & Darley, 1997; Schlenker, 1980; Schmitt et al., 2004; Tavuchis, 1991; Tedeschi &
Nesler, 1993; Tedeschi & Riess, 1981). Throughout the literature there has been a focus on three apology components: (1) expressions of empathy/remorse, (2) acknowledgments of violated rules/norms, and (3) offers of compensation. These components can be seen in Figure 1, b. As the figure shows, an apology only occurs if the transgressor feels guilt, empathy, or is motivated to repair his or her reputation (Figure 1, a). Depending on the motivation behind the apology, the 18 apology may contain different components. For example, a transgressor motivated purely by empathy may say and do different things than a transgressor who is purely motivated to fix his or her reputation.
Expressions of empathy/remorse. An apology that includes an expression of empathy occurs when a transgressor recognizes how an offended party is feeling and communicates this to the offended party or when the transgressor simultaneously feels what the offended party is feeling and expresses this outwardly. Transgressors may demonstrate empathy in several ways.
From the cognitive perspective, transgressors may indicate verbally that they understand the offended party’s feelings. For example, “I know that you are upset and are feeling embarrassed.”
From the affective perspective, transgressors may respond with their own affective feelings through expressions of sadness or shame. Transgressor empathy may even be communicated through warmth or compassion toward the offended party (Fehr et al., 2010). Transgressors experiencing empathy often experience remorse once they become cognizant of how they made the offended party feel. Expressing this remorse may also be helpful in eliciting forgiveness (e.g.,
Boyd, 2011; Darby & Schlenker, 1982; Schmitt et al., 2004).
Apologizers who express empathy and remorse tend to experience positive outcomes. For example, in Schmitt et al.’s (2004) study participants read a vignette in which they took the perspective of an individual whose friend borrowed and lost a bike that belonged to him or her.
In one condition the friend provided an apology that included an expression of remorse/empathy.
In this condition the friend said, “I feel really sorry for what I have done. I know how you feel now” (p. 469). Relative to the no empathy condition, the empathy vignette was associated with interpersonal trust, reduced anger, positive character attributions of the transgressor, and positive emotions toward the transgressor. 19
Acknowledgments of violated rules/norms. The literature indicates transgressors’ apologies are often successful if they include an admission of wrongdoing (e.g., Scher & Darley,
1997). This component involves stating what the transgression was and expressing that the transgression involved unacceptable behavior. For example a transgressor may say “I failed to show up on time and have disappointed those who rely on me. My behavior is unacceptable.”
This component may also involve an internal attribution (Boyd, 2011). In this case transgressors blame themselves instead of an external source. In his public apology for actions resulting in the loss of billions of dollars, Gerald Levin, CEO of Time Warner during the Time Warner-AOL merger, made an internal attribution stating that “I presided over the worst deal of the century, apparently. And I guess it's time for those who were involved in companies to stand up and say, you know what, I'm solely responsible for it. I was the CEO, I was in charge. I'm really very sorry about the pain and suffering and loss that was caused” (Levin, 2010). By taking responsibility for their actions, transgressors show their awareness of violating social norms and their desire to behave differently in the future (Scher & Darley, 1997). Apologizers who make internal attributions may also include a promise for change. This may be a statement such as, “I will seek therapy so I never behave this way again” or “I will avoid situations in which I am tempted to transgress.” This strategy is effective because (1) offended parties’ feelings are validated and they are shown that what they believed to be wrong is viewed similarly by others and (2) offended parties believe that similar wrongdoing by the transgressor will not occur in the future (Lazare, 2005).
Offers of compensation. Apologies are often effective when transgressors offer to compensate victims for their pain and suffering. For example, a CEO may offer monetary compensation to consumers for a problem caused by his or her company. Compensation does not 20 always need to be an offer of a tangible good. Restoring the offended party’s reputation or showing respect to the offended party in front of others can also be considered compensatory
(Boyd, 2011).
Several studies have shown the importance of compensation in an apology (Conlon &
Murray, 1996; Scher & Darley, 1997; Schmitt et al., 2004). For example, Conlon and Murray
(1996) asked business students if they had been compensated by a company after complaining about one of their products. Results indicated that compensation was associated with satisfaction and the likelihood of doing business with the company in the future.
Nonverbal behaviors. Despite little empirical evidence, researchers have suggested that nonverbal behaviors may be associated with the effectiveness of an apology because they serve as cues to the internal states of transgressors (Darby & Schlenker, 1982; Scher & Darley, 1997).
Recipients of apologies can use cues to judge the transgressor’s sincerity. For example, a transgressor may state that he is feeling remorseful. However, the apology may not be effective unless “remorseful” facial expressions accompany the apology.
Why Do Apologies and the Components Work?
The literature that attempts to answer the question of why apologies work has largely focused on the apology-forgiveness relationship. In this literature offended parties are thought to be motivated to protect themselves and thus seek revenge and estrangement from the transgressor. Therefore, any reparative actions taken by the transgressor must a) decrease retaliation motivation; b) decrease the offended party’s desire for estrangement; and c) motivate conciliation and goodwill toward the transgressor (McCullough, Worthington, & Rachal, 1997).
Keeping this in mind, researchers have attempted to identify why apologies are associated with forgiveness. The proposed explanations are the offended party’s emotional and cognitive 21 reactions to the transgressor’s apology and can be seen in Figure 1, c. As seen in the figure, each component in Figure 1, b is associated with a different offended party reaction in Figure 1, c. For example the component of compensation is associated with the offended party believing that equity has been restored to the relationship. The figure also demonstrates that the offended party’s emotional and cognitive reactions influence the offended party’s behavioral reactions
(see Figure 1, d). These reactions are the outcomes of apology such as forgiveness, legal outcomes, and purchase intentions. Below I discuss the proposed explanations shown in Figure
1, c.
Apologies induce empathy. Several researchers have proposed that the offended party’s empathy for the transgressor affects the apology-forgiveness relationship (e.g., McCullough et al., 1997). As mentioned above, empathy has the ability to motivate individuals to help others.
This was discussed as a reason for why people may apologize, but it might also explain why victims forgive transgressors. In this case, the offended party feels empathy for the transgressor.
The expression of an apology, especially if the transgressor is expressing guilt, sadness, loneliness, or other negative emotions, may induce empathy in the offended party (Baumeister et al., 1994). In other words, transgressor empathy may beget empathy in the offended party. If the offended party experiences empathy for the transgressor, the offended party may exhibit prosocial behavior toward him or her, including forgiveness, relationship repair, and a reduced motivation for retaliation (Batson, 1990; Batson, 1991; Baumeister et. al, 1994; Eisenberg &
Miller, 1987; McCullough et al., 2007).
Apologies affect attributions. Apologies can enhance victims’ perceptions of the transgressor. Apologizing may convey the message that the transgressor is not a bad person and that the misdeed was a chance event. As a result, an apology often overrides people’s tendency to 22 make trait attributions (Weiner, Graham, Peter, & Zmuidinas, 1991). Furthermore, if the offended party believes the transgressor is fundamentally good and is unlikely to repeat the transgression, the offended party will forgive the transgressor. Thus, an important component of successful apologies may be the transgressor’s acknowledgment of violated rules or norms.
Apologies restore equity. Equity theory states that transgressions create relationship inequality because negative outcomes are more frequent or intense for the offended party than the transgressor (Walster, Berscheid, & Walster, 1973). In order for forgiveness to occur, equality must be restored. An apology can restore equality through compensation strategies. For example, if a transgressor spoke poorly about an offended party to others, the transgressor may compensate the offended party by promising to talk positively about the offended party in the future or acting respectfully toward the offended party in front of others (Ohbuchi et al., 1989).
Apologies may also help to restore equality because when transgressors apologize they tend to put themselves in a subservient role, coming to the offended party “on bended knee”, and asking for forgiveness. In this case, transgressors offer power to the offended party as a social offering and place the offended party in the dominant role (Exline, Deshea, & Holeman, 2007).
If offended parties are satisfied with this power and the return to equality then they may become more forgiving (Fagenson & Cooper, 1987).
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Chapter 2: Study 1
The goal of Study 1 was to examine the relationship between apologies and offended party outcomes, some of which were interpersonal, while others were behavioral (e.g., purchasing intentions). Six meta-analyses of previously published studies were completed on the relationship between apology and (a) forgiveness, (b) positive perceptions of the transgressor, (c) positive emotions toward the transgressor, (d) positive legal outcomes for the transgressor, (e) purchase intentions, and (f) overall positive outcomes (i.e., combining across all outcomes).
These categories were chosen after reviewing the literature and making logical categories out of the various dependent variables used. The inclusion criteria for forgiveness included dependent variables that were associated with decreased retaliation motivation, decreased desire for estrangement by the offended party, and motivation for conciliation and goodwill toward the transgressor. Positive perceptions of the transgressor included any positive attributions made by the judges about the transgressor after the apology. Positive emotions toward the transgressor included any positive affective feelings toward the transgressor such as liking, less anger, and satisfaction. Positive legal outcomes included legal settlements as well as more lenient punishment decisions in a legal setting. Finally, purchase intentions included any dependent variable assessing an offended parties’ willingness to purchase from a transgressor. For this dependent variable, the transgressors were exclusively companies. See Appendix A for a list of all outcomes.
There were two goals for the meta-analyses: (1) to collect and summarize the existing published literature to draw conclusions and identify research gaps; and (2) to calculate mean effect sizes for the relationship between apologies and forgiveness, positive perceptions of the transgressor, positive emotions toward the transgressor, positive legal outcomes for the 24 transgressor, and purchase intentions. Even when apologies produce positive outcomes for the apologizer, questions remain as to when they are most effective (i.e., what are the components involved in an effective apology). Therefore, I coded potential moderators of apology effectiveness in each meta-analysis.
Methods
Search Method
The following procedures were used to locate studies: (1) PsycINFO search from earliest possible year through September 2011 using a list of terms that included apology, repentance, confession, regret, penance, service-recovery, crisis management, and remorse, (2) PsycINFO search of names of key authors known to conduct apology or forgiveness research, (3) search of bibliographies of relevant sources.
Inclusion Criteria
The criteria for study inclusion included the following: (1) Participants were from a typical population of adults (i.e., not clinically diagnosed), 2) Participants were at least 18 years old, (3) The apology in the study must have had a verbal acknowledgment of a wrong doing (i.e., emotion displays alone were not counted as apologies), (4) The study was published in an
English-language article or book, (5) The apology was manipulated within a vignette, recalled from a previous experience, or occurred during a laboratory interaction, and (6) The judges of the apology (i.e., the participants making the ratings of the apology outcomes) could be the receivers or onlookers of the apology. Transgressions often affect more than the direct victim, therefore it was important to understand the reactions of those indirectly affected. The final two criteria were: (7) Both dyadic and intergroup apologies were included, (8) The apology must have occurred after the transgression. Offended parties may react differently to ex ante apologies 25 because they have yet to experience the cognitive and emotional outcomes of the transgression, therefore it was important to keep the different apologies separate.
Variables Coded from Each Study
The following information was recorded from each study: (1) date of publication, (2) sample size, (3) country the study was conducted in, (4) stimulus materials (vignette; recall; or lab interaction), and (5) social distance (i.e., interpersonal connectedness of the relationship dichotomously coded as “low” or “high”) between apologizer and offended party. These variables were coded by two independent raters.
For stimulus materials, a vignette study was defined as a study in which participants reported on various outcomes (e.g., forgiveness, emotions) after reading a hypothetical transgression in which an apology occurred or did not occur. A recall study was defined as a study in which offended parties reported on various outcomes, such as forgiveness, in response to an actual transgression that occurred outside of the lab and indicated whether they received an apology. A laboratory interaction methodology was defined as a study in which participants experienced a transgression in the laboratory and were subsequently given or not given an apology. Participants then reported their reactions to the situation.
Because forgiveness is more likely to occur in close relationships (McCullough, Kurzban,
& Tabak, 2013) it was important to code for social distance. Social distance was dichotomously coded as “low” or “high.” A relationship was “low” on social distance when the apologizer and offended party were members of the same ingroup (e.g., romantic partners, friends, coworkers, and participants within the same study). A relationship was “high” on social distance when their ingroups differed (e.g., boss-employee, company-customer, doctor-patient). On the social distance continuum, low social distance implies greater interpersonal connectedness and 26 relatively egalitarian relationships. In contrast, high social distance implies little or no interpersonal connectedness or power imbalance between members.
Variables Constructed From Scripts of Apologies
The apology components were the primary moderators of interest. Three researcher assistants were trained as coders and directed to read each apology (if provided by authors) and coded for the presence of remorse (the observable signal of empathy), acknowledgments of violated rules/norms, and compensation, all on a 1(not at all present)-5 (very present) scale.
Coders were informed an expression of remorse involves a verbal expression of negative affect.
For example, “I feel terrible.” An acknowledgment of violated rules and norms was defined as recognizing the transgression committed violated rules and norms that interpersonal behavior is bound by. Finally, to identify compensation coders were asked, “does the apologizer offer to fix what they did (i.e., do they focus on restoration of equity through exchange)?” For example, in offering compensation an apologizer may say, “Let me make it up to you” or “I want to bring you out to make up for this.”
The three trained coders also rated the severity of each transgression on a 1(not at all severe)-9(very severe) scale. Inter-rater reliability was then calculated. The Cronbach’s alphas for the moderators were .85, .78, .96, and .94 respectively. With high reliability among ratings I then aggregated the scores by averaging across the three coders resulting in a score on each moderator for each apology.
Statistical Methodology
The meta-analyses focused on effect sizes from between-subjects designs, where participants who received an apology were compared to control groups who did not receive an apology. The Pearson correlation, r, was used as the effect size indicator, which represents the 27 strength of association between the presence of an apology and a positive outcome. A positive r indicated an apology was associated with a positive outcome in the original study. When r was not present, it was calculated using the statistics provided. For example, in many cases the original authors reported means and standard deviations in both apology and control samples. A basic two-sample t-test was calculated using these means and standard deviations and the t- statistic was then converted to r using standard formulas. When a partial r or standardized regression coefficient was present and the Pearson r was not, the former was used. When a result was reported as nonsignificant with no data, r = .00 was assigned.
Several meta-analyses were conducted, one for each dependent variable. These dependent variables included (1) forgiveness, (2) positive perceptions of the transgressor, (3) positive emotions toward the transgressor, (4) positive legal outcomes for the transgressor, and (5) purchase intentions. Additionally, a “combined outcomes” meta-analysis was conducted across all dependent variables (i.e., forgiveness, positive perceptions, positive emotions, positive legal outcomes, and purchase intentions). For the combined outcomes meta-analysis there were some cases in which effect sizes had to be averaged if multiple dependent variables were assessed in the same sample. For example, if participants in one study reported on more than one dependent variable such as forgiveness and legal outcomes, the effect sizes for these were combined. The moderator analyses were conducted using the combined meta-analysis.
Both fixed and random effects models were calculated. A fixed effects model assumes that there is one true effect size, which underlies all observed effects and that differences among these observed effects are due to sampling error. A fixed effects analysis can be generalized to new subjects that are run though the same stimuli and procedures. Fixed effects models are often used in fields with little methodological variance. In a random effects model the true effect is 28 assumed to vary from study to study because of both subject-level sampling error and study-level sampling error. In a random-effects meta-analysis it is assumed that the true effects are normally distributed. Random effects analyses can generalize to new people in similar conditions as well as to new, conceptually similar conditions. The fixed effects model produces smaller confidence intervals and more significant results, while the random effects model is more conservative. For a more in depth discussion of fixed and random effects models see Lipsey and Wilson (2001).
The heterogeneity statistic was computed to assess whether each effect size was an estimate of the common population; it determined whether the variability among the effect sizes was greater than the variability due to sampling error. Determining the effect sizes to be heterogeneous allows for the testing of moderators to examine if any of them account for the variability in the effect sizes (Rosenthal & Rubin, 1982). Finally, the “file drawer N” to estimate the number of unretrieved study effect sizes that average to zero needed to produce a nonsignificant effect.
The goals of the moderation analyses were to (1) assess the impact of various components (i.e., remorse, acknowledgment of violated rules and norms, and compensation) on the apology-outcome relationship and (2) assess the impact of study methodology on the magnitude of the effect sizes. Analyses were facilitated by the Comprehensive Meta-Analysis
Software program (Bornstein et al., 2005).
Results
Study Characteristics/Summary of the Existing Literature
A list of the studies and effect sizes included in the meta-analyses can be seen in Table 1.
The meta-analyses were based on a sample of 34,399 participants. The average sample size was
165 participants (SD = 162). The sample sizes of individual studies ranged from 22 to 1652 29 participants. The majority of studies used samples drawn from college student populations. A large amount of the studies were conducted in the United States and Canada while others were conducted in Australia (k = 11), The Netherlands (k = 6), France (k = 4), Singapore (k = 3),
Lebanon (k = 2), China (k = 1), Taiwan (k = 4), Kuwait (k = 1), Germany (k = 1), and Greece (k
= 1). The majority of studies were vignette studies (58%), while only 16% were recall and 26% were live interaction. The live interactions always used confederates who either interacted in person with the participants or through a computer. In these studies the confederates transgressed against the participants and then either apologized using a scripted apology or did not apologize.
I obtained apology scripts from 42% of the studies. Scripts were not used in recall studies or live interaction studies. In recall studies, participants recalled a time in which they were the victim of a transgression and reported whether or not the transgressor apologized. Thus, no standard apology was provided. In several other studies, researchers stated that a transgressor apologized to a victim but provided no additional information about the apology.
For studies that utilized scripts, 40% involved high social distance relationships (i.e., the apologizer and offended party belonged to different in-groups; k = 48), 44% included low social distance relationships (i.e., the apologizer and offended party are from the same in-group; k = 53), and 16% (k = 19) could not be categorized due to insufficient information.2
Effects of Apology
Forgiveness. Combining 79 independent effect sizes that investigated the effect of apology on forgiveness (see Table 2), the random effect size was r = .32 (Z = 8.16, p < .001) and the fixed, weighted mean effect size (computed by weighting each effect size by the inverse of its variance) was r = .41 (Z = 38.58, p < .001). The significant combined Z indicated the presence of an apology has a significant effect on forgiveness. Fail-safe N analysis indicated it 30 would take 25,193 additional findings that average to r = .00 for this fixed combined Z to no longer be significant. The effect sizes ranged from r = -.29 to r = .97 and were significantly heterogeneous.
Positive perceptions of the transgressor. Combining 60 independent effect sizes that investigated the effect of apology on positive perceptions (e.g., trustworthy, honest) of the transgressor (see Table 2), the random effect size was r = .24 (Z = 6.69, p < .001) and the fixed, weighted mean effect size was r = .19 (Z = 17.80, p < .001). The significant combined Z indicated the presence of an apology has a significant effect on positive perceptions of the transgressor. Fail-safe N analysis indicated it would take 5,647 findings that average to r = .00 for this combined Z to no longer be significant. The effect sizes ranged from r = -.51 to r = .85 and were significantly heterogeneous.
Positive emotions toward the transgressor. Combining 43 independent effect sizes that investigated the effect of apology on positive emotions (e.g., satisfaction, liking) toward the transgressor (see Table 2), the random effect size was r = .33 (Z = 9.41, p < .001) and the fixed, weighted mean effect size was r = .39 (Z = 37.74, p < .001). The significant combined Z indicated the presence of an apology has a significant effect on positive emotions toward the transgressor. Fail-safe N analysis indicated it would take 98 findings that average to r = .00 for this combined Z to no longer be significant. The effect sizes ranged from r = .00 to r = .71 and were significantly heterogeneous.
Legal sentencing. Combining 11 independent effect sizes that investigated the effect of apology on legal sentencing (see Table 2), the random effect size was r = .13 (Z = 3.49, p <
.001) and the fixed, weighted mean effect size was r = .11 (Z = 6.30, p < .001). The significant combined Z indicated the presence of an apology is associated with less harsh legal sentencing. 31
Fail-safe N analysis indicated it would take 98 findings that average to r = .00 for this combined
Z to no longer be significant. The effect sizes ranged from r = -.05 to r = .37 and were significantly heterogeneous.
Purchase intentions. Combining 10 independent effect sizes that investigated the effect of apology on purchase intentions from the transgressor (see Table 2), the random effect size was r = .23 (Z = 2.85, p < .001) and the fixed, weighted mean effect size was r = .24 (Z = 10.82, p < .001). The significant combined Z indicated the presence of an apology has a significant effect on purchase intentions. Fail-safe N analysis indicated it would take 222 findings that average to r = .00 for this combined Z to no longer be significant. The effect sizes ranged from r = -.27 to r = .57 and were significantly heterogeneous.
Combined outcomes. Combining 144 independent effect sizes from 94 articles that assessed the effects of apology on positive outcomes (i.e., forgiveness, positive emotions, positive perceptions, legal sentencing, and purchase intentions; see Table 2), the random effects mean effect size was r = .27 (Z = 10.72, p < .000) and the fixed, weighted mean effect size
(i.e., the effect size weighted by sample size) was r = .22 (Z = 46.83, p < .000) 3. The significant combined Z indicated that the presence of an apology has a significant effect on positive outcomes. Fail-safe N analysis indicated it would take 24,177 findings that average r =
.00 for the combined Z to no longer be significant. The effect sizes ranged from r = -.51 to r =
.97 and were significantly heterogeneous.
Key Moderators of an Apology’s Effectiveness
Stimulus materials. Seventy-seven studies employed a vignette paradigm, twenty-nine studies were recall studies, and thirty-eight studies were live interactions (with a confederate in person or on a computer). I ran a fixed effects contrast to examine the moderating effect of 32 methodology. Across all studies, stimulus material moderated the relationship between apology and positive outcome (Q(2) = 164.03, p = .00; vignette use r = .28, recall methodology r = .38
, interaction studies r = .15). Similarly, a one way ANOVA (the random effects analogue to the fixed effects moderator analysis) also revealed a significant effect of stimulus materials, F(2,141)
= 3.067, p = .05. Vignette use (r = .30) and recall methodologies (r = .35) had larger effect sizes than live interaction studies (r = .18). A Tukey test revealed that recall and live interaction effect sizes significantly differed, p = .06.
Apology components. To begin, I first examined the relationships between our coded apology component variables. It is important to note that a random-effects model was used for these analyses and all subsequent analyses. That is, the effects reported are weighted equally and not by sample size. Furthermore, these analyses are completed across all dependent variables.
Table 3 displays these results. As can be seen, severity was significantly correlated with remorse and compensation. Therefore apologies for more severe transgressions included more remorse and offers of compensation. The three apology components (acknowledgment of violated rules and norms, remorse, and compensation) were all significantly positively correlated suggesting that these components often appear simultaneously in apologies.
Next, I correlated each of the coded components with the independent effect sizes found in our studies. As seen in Table 3, studies with apologies that contained remorse or compensation had larger effect sizes, while there was no association between acknowledgment of violated rules and norms and severity with effect sizes.
To better understand these relationships I entered the components as predictors of effect size in a multiple regression. For ease of discussion these results are presented in absolute terms
(e.g., remorse is present or not present), but it is important to note that the components were 33 coded on a continuous scale and should be interpreted as such. The model was significant, R2 =
.129, F(4, 66) = 2.44, p = .05. Remorse was a significant predictor of effect size when controlling for compensation, acknowledgment of violated rules and norms, and severity (β =
.27, p = .04)4. Compensation (β = .25, p = .05) and acknowledgment of violated rules and norms (β = -.24, p = .05) also significantly predicted effect size, while controlling for the other moderators. Severity was not a significant predictor (β = -.11, p = .38).Therefore studies containing apologies that include remorse or compensation tend to obtain higher effect sizes than those without these components, while studies with apologies that include acknowledgments of violated rules and norms tend to obtain smaller, or even negative effect sizes than those without this component.
Social distance. Although the construct of social distance represents a continuum, the methods used and details provided limit how social distance can be characterized in apology studies. As a result, the social distance between transgressor and victim was assigned one of two values: low or high social distance. To evaluate social distance, I conducted a multiple regression analysis in which social distance (i.e., low social distance = 0, high social distance = 1), remorse, acknowledgment of violated rules and norms, and compensation predicted effect size.
This model was significant, R2 = .18, F(4,59) = 4.53, p = .003. Furthermore, social distance was significant (β = -.11, p = .08) suggesting a stronger relationship between apology and offended party outcomes for low social distance relationships.
To examine whether the components moderated effect size differentially for the social distance groups, the data was split into two separate files: one for high social distance studies (k
= 48) and one for low social distance studies (k = 53). Next, I entered acknowledgment of violated rules and norms, remorse, and compensation into a multiple regression model predicting 34 effect size for high social distance studies and then for low social distance studies. For high social distance, acknowledgment of violated rules and norms (β = -.40, p = .03), remorse (β
= .34, p = .09), and compensation (β = .41, p = .02) were all significant predictors. For low social distance, remorse was a significant predictor (β = .48, p = .02), while acknowledgment of violated rules and norms (β = -.26, p = .21) and compensation were not (β = -.01, p =
.97).
Interaction and additive effects. Given that remorse, acknowledgment of violated rules and norms, and compensation were all significant moderators of the apology-outcome relationship in high social distance relationships it was important to test for interaction and additive effects. To do this all three variables were centered by subtracting the mean of all data points from each individual data point. I then created four interaction variables by multiplying
(1) remorse with acknowledgment of violated rules and norms, (2) remorse with compensation,
(3) acknowledgment of violated rules and norms with compensation, and (4) remorse, acknowledgment of violated rules and norms, and compensation. The centered variables of interest and the interaction variables were entered as predictors of effect size in high social distance relationships. The model was significant (R2 = .30, F(7, 23) = 3.410). See Table 4 for results. As seen in the table, there were no significant interaction effects. Furthermore, this model was no more predictive of effect size than the three component model in which remorse, acknowledgment of violated rules and norms, and compensation predicted effect size (R2 = .29,
F(3, 27) = 5.081, p = .006, p = .012; Δ R2 = .15, p = .176). Thus, for the sake of parsimony the three component model was used to examine the additive effects of the components. As mentioned above, all three components were significant predictors of effect size when entered 35 simultaneously, thus suggesting an additive effect. In other words, the regression of effect size on one predictor is constant over all values of the other predictors.
Discussion
Results from the six meta-analyses demonstrate that apologies were effective in producing positive outcomes even when tested with the more conservative random effects model, which permits wider generalization to new studies than the fixed effects model does
(Lipsey & Wilson, 2001). These positive outcomes include forgiveness of the apologizer, positive perceptions of the apologizer, positive emotions toward the apologizer, positive legal outcomes for the apologizer, and offended parties’ positive purchase intentions.
Studies utilizing vignette or recall methodologies were more effective than studies using live interactions, suggesting that apologies may not be as effective in more naturalistic settings.
Confounding variables found in live-interaction studies may affect the efficacy of apologies. For example, nonverbal behaviors may be important factors in live-interaction studies. If nonverbal behaviors do not correspond to the verbal statements an apologizer is making (e.g., an apologizer expresses remorse while smiling) then apologies may be less effective. This is an important avenue for researchers to pursue in the future.
Remorse, compensation, and acknowledgment of violated rules and norms were all significant moderators. Remorse and compensation enhanced, whereas acknowledgment of violated rules and norms diminished, apology effectiveness. However, in transgressor-offended party relationships characterized by low social distance a different pattern emerged. In these relationships, only remorse predicted effect size. Compensation had no effect. The rarity of compensation in low social distance relationship apologies may explain this. In fact, when examining the frequency of compensation I found forty-two out of the fifty-three apologies that 36 occurred in low social-distance relationships were given a score of “1” (i.e., not at all present).
Thus, suggesting that compensation may not be used in emotion-based close relationships.
Similarly, an acknowledgment of violated rules and norms may be ineffective because it makes the transgression salient again, causing offended parties to reflect on the source of their emotional discomfort. After a transgression occurs, offended parties often make dispositional attributions (as opposed to situational attributions) when evaluating the transgressor (Ross,
1977), believing that only a malevolent person would commit such a hurtful act (Weiner,
Graham, Peter, & Zmuidinas, 1991). If an apology can override the tendency to make negative dispositional attributions it should be more effective. An acknowledgment of violated rules and norms appears not to override this tendency and instead may reinforce the offended parties’ beliefs that the transgression was reflective of the apologizer’s character. By reminding an offended party about the transgression and detailing why it was morally wrong, it becomes easier for an offended party to assume the apologizer is the cause of the transgression (Kim, Ferrin,
Cooper, & Dirks, 2004).
Gaps in the Existing Literature
Besides recall studies, which were unable to report apology components, there was not one study in which real apologies were examined. Thus, our examination of apology components may not generalize to real life situations because real apologies may not contain these components. For example, in interpersonal apologies it may be fairly rare for an apologizer to offer compensation to a close other. This component may occur more often in public apologies given by corporate executives. For example, when ice storms trapped Jetblue passengers on planes for hours, the CEO apologized and offered passengers monetary compensation that could help restore their finances after the cancelled flight. 37
The absence of naturally occurring apologies in the literature inherently suggests that nonverbal behaviors and emotions that typically accompany real apologies (e.g., frowning, smiling, crying, posture) are unexamined. However, theorists believe nonverbal behaviors are associated with apology efficacy because these behaviors serve as cues to the internal states of transgressors (Darby & Schlenker, 1982; Scher & Darley, 1997). Offended parties can therefore use nonverbal cues to judge the transgressor’s sincerity. For example, an apologizer may state that he is feeling remorseful, but his apology may be ineffective unless “remorseful” expressions
(e.g., a bowed head and crying; Scher & Darley, 1997; Weisman, 2004) accompany it. In the future, researchers should examine the expressive behaviors that accompany an apology and how they affect outcomes.
Only eight studies were conducted in eastern culture countries. Therefore the current results can only be generalized to western culture apologies. The components considered effective may differ in eastern cultures. This is especially true considering those in eastern cultures apologize quite differently than those from western cultures (Lazare, 2004). This difference most likely stems from the individualistic mentality of the west and the collectivist mentality of the east (Schwartz & Bilsky, 1987). In countries that tend to be individualistic such as the USA and Canada, there is an emphasis on personal achievement at the expense of the group’s goals. In countries that tend to be collectivist such as China and Singapore, there is an emphasis on family and work group goals above individual needs or desires. Thus, collectivist culture apologies are more likely than individualistic culture apologies to focus on restoring the relationship with the offended party, rather than on relieving an internal state, such as guilt.
Subsequently, offended parties in collectivist cultures may prefer this type of apology. Interested researchers may wish to examine this possibility. 38
Limitations of the Present Meta-Analyses
Although meta-analysis is a powerful tool for understanding data across multiple studies, there are inherent limitations. Much of the variance in effect sizes cannot be fully explained by the moderator analyses. There may be additional moderators that were not coded or could not be coded from the information provided by the authors. For example, characteristics of the apologizer such as age, attractiveness, and gender may influence the efficacy of apologies, but were not available for the current meta-analyses.
Publication bias is also a concern especially because this meta-analysis did not include dissertations or unpublished manuscripts. However, the large fail-safe N indicators suggest that it would take many studies with null results to produce a nonsignificant combined effect size for apology effectiveness.
Practical Implications
The take-home message of the current meta-analyses is apologies work. Apologies produce positive outcomes such as forgiveness, positive emotions and perceptions, legal sentencing, and purchase intentions in favor of the apologizer in many contexts including business-customer (e.g., Bolkan & Daly, 2009), doctor-patient (e.g., Bornstein et al., 2002), colleague (Braaten et al., 1993), and romantic relationships (e.g., Gunderson & Ferrari, 2008).
However, an apology can backfire, especially if not done correctly. In low social distance relationships, apologizers need only include an expression of their remorse. Neither compensation nor an acknowledgment of violated rules or norms predict offended party outcomes.
Those in high social distance relationships wishing to provide an effective apology might need to express their remorse and include an offer of compensation. Interestingly, an apologizer 39 in a high social-distance relationship should sparsely acknowledge violated rules and norms.
Reminding the offended party of what has been done and why it was wrong is detrimental and instead may offend the recipient of the apology. Instead the apologizer may wish to focus on expressing their regret or compensating the offended party. Future research should explore additional components to better understand what a “perfect” apology includes.
40
Chapter 3: Study 2
The results reported in the present chapter extend the results reported in previous chapters. As seen in the meta-analyses, not one study involved evaluating real apologies. The research method used to study apologies typically involves a vignette that describes a person’s transgression. Participants are told that an apology was, or was not, given. Then, participants report whether they would forgive the transgressor based on this apology. However, this method does not accurately represent how apologies are perceived and how transgressions are forgiven in real life. Real apologies involve emotion and expressive behaviors (e.g., facial expressions, vocal tone) that are absent in vignette studies.
Furthermore, the meta-analyses were unable to answer the question of why the apology components (i.e., remorse, acknowledgment of violated rules and norms, and compensation) are associated with offended party outcomes such as forgiveness. There were two main goals of
Study 2: (1) to examine the relationship between apology verbal components, expressive behavior, apologizer self-reported emotions, and offended party-rated emotional, cognitive, and behavioral reactions using real apologies given by participants who committed transgressions;
(2) to test the mediating role of offended party-rated emotional and cognitive reactions (Figure
2,c) in the apology component (Figure 2,b) and offended party-rated behavioral reactions (Figure
2,d) relationship. From here on, participants who present apologies will be called apologizers and participants who evaluate apologies will be referred to as judges.
Methods
Study 2 investigates real apologies given by participants who committed the transgression for which they are apologizing. Apologizers were video recorded while apologizing for a transgression they committed. Trained coders rated the apologies on various 41 dimensions identified in the literature as important for an effective apology (e.g., remorse, compensation). Finally judges observed the video recorded apologies and evaluated their sincerity, and whether the apologizer deserved forgiveness and could be trusted.
The relationships between the rated components (e.g., remorse, offers of compensation, empathy) and judges’ perceptions of the apology (i.e., forgiveness, trust, and sincerity) were examined.
Phase 1: Creating Apology Stimuli
Participants
50 apologizers were recruited and paid $10 for participating in a study that they were told investigated forgiveness and life events. The apologizers were primarily senior undergraduate students from Northeastern University. Judges ranged in age from 18 to 25. The sample was racially diverse. Thirteen videos were removed from our stimuli set for various reasons. Three participants requested their videos not be seen by future participants, two participants reported extremely low levels of sincerity during the task (i.e., they did not take the task seriously), and the remaining eight were randomly chosen to be eliminated for the judgment-phase time purposes. Therefore 37 stimuli videos were used. Twenty of these videos had female apologizers, while seventeen had male apologizers.
Measures
Each apologizer completed several questionnaires post-apology. Apologizers reported on their apology experience as well as the transgression they chose to apologize for.
Directly following the apology, apologizers rated their emotional state on a 5-point Likert scale. Twenty-two emotions were rated; although, the emotions of primary interest were “guilt,”
“shame,” “embarrassment,” “pity,” and “empathy for the offended party.” The other emotions 42 assessed were “amusement,” “anger,” “compassion, ” “contempt,” “contentment,” “disgust,”
“excitement,” “fear,” “happiness,” “hope,” “inspiration,” “jealousy,” “love,” “relaxation,”
“sadness,” “surprise,” and “worry.”
In addition to reporting their emotions after the apology, apologizers were asked to provide more information about their experience while giving the apology as well as the transgression that led to the apology. Participants were asked, “How sincere was the apology that you just provided?”, “How upset was the person who was hurt by you after they found out about your behavior?”, and “How reasonable was the person that you hurt's reaction to your behavior?”All questions were responded to using a 7-point scale. A score of one represented low levels of the construct being assessed (e.g., not at all sincere, not at all upset, not at all reasonable, not at all bad/severe), while a seven represented a very high level of the construct
(e.g., very sincere, very upset, very reasonable, very bad/severe). Participants also rated on a 5- point scale, “How bad/severe do you think the behavior that you apologized for was?” A score of one indicated behaviors were not at all bad/severe, while a five indicated the behavior was very bad/severe.
Procedure
Each participant was run individually in the lab. Each participant completed an informed consent and was given a sheet of paper that read, “Please take the next few minutes to think of a time in which you committed a transgression (i.e., you did something wrong) that emotionally hurt another person that you are close with. This should be a transgression for which you have not yet apologized. Once you think of a transgression please spend the next two minutes writing about the transgression. You may wish to write about how you felt, to write about how the 43 offended party of the transgression felt, to write about how you feel about it now, or to even write about the transgression itself.”
The researcher then left the room while the apologizer wrote about the transgression.
After two minutes the researcher returned to the room and let the apologizer know that he or she would be apologizing for this transgression. Before the apology was given, the apologizers were told that only the researchers would be allowed to see their video tape. Furthermore, they could request that their video be destroyed if they felt uncomfortable with others watching it.
Apologizers were told that their video was private before they apologized in order to reduce impression management during the apology. The apologizer was then asked to imagine that the intended recipient of the apology was present in the room. The apologizer then offered an apology to a laptop camera approximately 2 feet away.
The researcher left the room while the apologizers apologized. The apologizers were told to retrieve the researcher once they had completed the apology. This method allowed apologizers to choose the amount of time they wanted for their apology. After completing the video recorded apologies, apologizers completed several questionnaires about their feelings while giving the apology and about the transgression.
After completing all questionnaires apologizers were given a second consent form that asked for permission to show their videotaped apologies to prospective participants. Apologizers were told that they would be paid either way (i.e., whether they said yes or no) and were not pressured in any way to respond yes. To better understand what these stimuli consisted of, see
Appendix B for complete transcripts of two apologies
Coded Behavior 44
Three trained research assistants independently coded each videotaped apology. Coders viewed each apology a minimum of two times and read a transcript of the apology before making any ratings. They then rated the apology and apologizer on verbal and expressive behavior components.
Verbal components. Similar to the coding for the meta-analyses, the verbal components of an apology that may influence its effectiveness were coded. The same three research assistant coders rated the extent to which each apology contained an (a) expression of remorse (the verbal cue of empathy), (b) acknowledgment of violated rules/norms, and (c) offer of compensation on a 0-7 scale. A score of zero was given if the component was not present at all, while a 7 represented a very high level of the component. Table 5 provides the reliabilities of each item.
The Cronbach’s alpha for each item ranged from .54-.86, suggesting inter-rater reliability, thus, the three ratings were averaged to create a composite rating of each component for each apologizer.
Expressive behaviors. Two expressive behaviors were coded that may be cues to apologizers’ internal states and their sincerity. Coders rated to what extent the apologizer appeared to be experiencing 1) guilt and 2) shame. Coders were asked to focus on the nonverbal behaviors of the apologizers (e.g., facial expressions, tone of voice, etc.) while making their judgments. However, coders watched the apology videos with sound so it is not possible to know whether or not coders made their judgments based on nonverbal behavior (as they were told), verbal behavior, or a mixture of both. Coders demonstrated high inter-rater reliability
(Cronbach’s alphas reported in Table 5) so I collapsed the scores across coders resulting in a rating of each component for each apologizer.
Phase 2: Judgments of the Apologies 45
Participants
Eighty-nine judges were recruited for Introduction to Psychology class credit. The judges were primarily white undergraduate students from Northeastern University. Forty percent of the judges were female. Judges ranged in age from 18 to 27.
Measures
Judges’ ratings of the transgressions. Before watching each apology, judges read a short description of the transgression. For example, before watching one of the apologizers, judges read, “This apologizer told his friend he did not want to be friends with him anymore.” After reading the transgression description judges responded to the following three questions, “Have you ever committed a similar transgression?”, “How severe was the transgression that this person committed?”, and “Has anyone ever committed this transgression against you?”
Judges ’ Ratings of the Apologies. After watching an apology, judges answered the following questions: “If you were the recipient of this apology, to what extent would you forgive the person?”, “How sincere was this person's apology?”, and “To what extent would you trust this person?” These questions were answered on a 7 point scale and indicate the effectiveness of each apology. A score of one was given for low levels of the construct being measured (e.g., definitely would not forgive, not at all sincere, definitely would not trust), while a score of seven indicated high levels (i.e., definitely would forgiven, very sincere, definitely would trust). Judges also answered the following questions about forgiving the transgressor: “To what extent can you feel/understand what this person is feeling?” (this question gets at empathy for the offended party), and “To what extent do you feel badly for this person (feel sympathy for this person)?”
Furthermore, judges were asked the question, “The cause of this behavior was...” with a rating scale from 1 (reflects an aspect of the situation) to 7 (reflects an aspect of the transgressor). From 46 now on this variable is referred to as judge-rated attributions. Means were calculated across judges to create a single score on each of the judge-rated variables for each apologizer5.
Procedure
After being consented, judges were seated in front of a computer monitor displaying a movie player. Up to five judges were run at the same time in the lab. Judges were asked not to speak with one another. Judges watched all apologies collected from apologizers in Phase 1.
Prior to watching each videotaped apology, judges read a short description of the transgression and answered three questions about it. After watching each video, judges evaluated the apology on several dimensions.
Results
I will present the results section as follows: First I will present the descriptive statistics of all study variables and the relationship among them. Next, I will examine the apologizer and coder-rated components associated with judge-rated outcomes by conducting correlation and multiple regression analyses. I will examine the interactive and additive effects of the components in the multiple regression analyses. Finally, I will conduct analyses to examine whether judge-rated emotional and cognitive reactions mediate the relationship between apologizer and coder-rated components and judge-rated behavioral reactions.
Descriptive Statistics for Apologizer Variables
Table 6 displays the means of apologizer self-reported emotions. Apologizers reported high levels of guilt, compassion, shame, sadness, and empathy and low levels of jealousy, surprise, disgust, anger, and excitement. All 22 items were subjected to a principal-factors analysis followed by a varimax rotation for purposes of data reduction. The resulting eigenvalues, the percent of variance accounted for by each factor, and the scree plot were 47 examined. There was a clear break in the scree plot between the fourth and fifth factor. To determine the most appropriate factor solution I examined a four, five, and six factor solution.
The five-factor solution was most interpretable. The factor loadings for each item are shown in
Table 6. I labeled these 5 factors as follows: self-consciousness, apology-reactions, insincerity, empathy, and contentment. Self-consciousness was made up of guilt, shame, sadness, love, worry, fear, and embarrassment. Apology-reactions consists of excitement, anger, surprise, relaxation, inspiration, and happiness. Jealousy, contempt, disgust, and amusement are all part of the factor labeled insincerity. Empathy consists of pity, empathy, and compassion and contentment is made up of contentment and hope.
The self-consciousness items are self-conscious emotions that may occur upon reflection of the transgression. The emotions within the apology-reactions factor would not normally correspond with one another because of their mix of valence and arousal. However, in the context of an apology, the emotions may be related because transgressors were likely to experience them after completing their apology. Apologizers may feel relief, excitement, or even anger post-apology. The insincerity factor consists of emotions that may occur in a fake or forced apology. The empathy factor is made up of emotions that are associated with identifying how another is feeling. The contentment factor contains two emotions associated with being content.
The means and intercorrelations of the five factors are presented in Table 7. The data reveal that the factors of self-consciousness and empathy are significantly correlated.
Considering that empathy often leads to the experience of guilt and shame (Eisenberg, 1986;
Hoffman, 1982; Zahn-Waxler & Robinson, 1995), this relationship is understandable. The data also reveal that empathy is associated with feelings of contentment. The apology-reactions factor 48 is associated with insincerity, empathy, and contentment. As mentioned earlier, this factor contains emotions that vary greatly in valence and arousal, which may account for these relationships.
Table 8 displays correlations between the five emotion factors and the apology and transgression-specific question variables. Only one relationship was significant among these analyses: the relationship between self-consciousness and apology sincerity. Although not a strong correlation, this relationship suggests that those experiencing self-conscious emotions may provide sincere apologies.
Descriptive Statistics for Coder Variables
The descriptive statistics for the coder variables are presented in Table 5. The mean for compensation was low relative to the other coded variables. Compensation received a score of zero for 28 of the 37 apologies suggesting that compensation was rarely offered.
Remorse was positively correlated with acknowledgment of violated rules and norms, guilt, and shame. Compensation was not associated with any of the self-conscious emotions, while acknowledgment of violated rules and norms was positively correlated with guilt and shame.
Descriptive Statistics for Judge Variables
The descriptive statistics and relationships among the judge variables are presented in
Table 9. Judges reported less empathy and sympathy for apologizers when they (i.e., the judges) had committed a similar transgression. Judges also reported less empathy for the apologizer if they had been the recipient of a similar transgression in the past (i.e., if someone committed this transgression against the judges). 49
The three judge-rated outcomes (i.e., forgiveness, trust, and sincerity) were all positively correlated. Furthermore, judges reported high levels of these three variables when they also reported experiencing empathy and sympathy and attributed the transgression to external causes.
Interestingly, severity of the transgression was only related to the forgiveness variable. Judges were less willing to forgive when the transgression was seen as severe.
Relationships Between Apologizer, Coder, and Judge Variables
I next examined the relationships between apologizer, coder, and judge variables (see
Tables 10 and 11). First, I correlated apologizer emotion (Figure 1,a) with coder ratings of verbal and expressive behavior (Figure 1,b). Results revealed that apologizers who reported high levels of self-conscious emotions were rated by coders as expressing guilt. Thus, coders may have been able to detect apologizers’ internal experience.
Next I examined the relationship between apologizer emotion (Figure 1,a) and judges’ emotional and cognitive reactions (i.e., empathy, sympathy, attributions; Figure 1,c).
Apologizers’ self-conscious emotions were significantly correlated with judge sympathy and empathy, suggesting judges recognize the apologizers’ negative emotions and subsequently feel sympathy for them. I next correlated apologizers’ emotions (Figure 1,a) with judges’ behavioral reactions (e.g., forgiveness, sincerity, and trust; Figure 1,d). Self-conscious emotions were positively correlated with forgiveness, trust, and ratings of sincerity.
Finally, I correlated coders’ ratings (Figure 1,b) with judges’ emotional and cognitive reactions (Figure 1,c) and judges’ behavior reactions (Figure 1,d). Coder-rated remorse, acknowledgment of violated rules and norms, guilt, and shame were all positively correlated with judge-rated empathy, sympathy, forgiveness, sincerity, and trust. Thus, judges have positive reactions to apologizers when apologizers include remorse and an acknowledgment of violated 50 rules and norms in their apologies as well as when apologizers appear to be experiencing guilt and shame.
As shown in Table 9, judge-rated severity is negatively associated with judge-rated forgiveness. This relationship has also been shown in the literature (Fincham, Jackson, & Beach,
2005). Therefore, it was important to test whether the apology components predicted the judge- rated outcomes while controlling for judge-rated severity of the transgression. I ran several partial correlations, correlating the significant predictors (i.e., self-conscious emotion factor, guilt, shame, remorse, and acknowledgment of violated rules and norms) with the judge-rated outcomes while controlling for judge-rated severity. See Table 12 for results. Guilt, shame, remorse, acknowledgment of violated rules and norms, and the self-conscious emotion factor were all significant predictors of empathy, sympathy, forgiveness, trust, and sincerity. Thus, the apology components predicted judge-rated outcomes at all levels of transgression severity.
Apologizer and Coder Variables Predicting Judge Ratings
Thus far, transgressors’ emotional reactions (Figure 1,a) and apology components (Figure
1,b) predict the role-playing offended parties’ emotional and cognitive reactions (Figure 1,c) and behavioral reactions (Figure 1,d). These analyses, however, do not test (1) the individual contributions of the apologizer-rated emotions (Figure 1,a) and coder-rated components (Figure
1,b) in the prediction of the judge-rated outcomes (Figure 1,c and Figure 1,d), (2) the interactions among the verbal (i.e., remorse, acknowledgment of violated rules and norms, and compensation) and expressive behavior (i.e., guilt, shame, self-conscious emotions) components;
(3) the additive effects of the various components (i.e., does including more than one component improve prediction of judge-rated outcomes); or (4) why the apology components are associated with the judge-rated outcomes. In order to answer these questions I first used multiple regression 51 to assess the individual contributions each of the components makes in the prediction of judge- rated outcomes. These analyses were conducted separately for apologizer-rated emotions and coder-rated verbal components. Next, to assess the interactive and additive effects between the components, coder and apologizer-rated variables and their interaction terms were entered as predictors of judge-rated emotional, cognitive, and behavioral reactions. Finally, analyses were conducted to examine whether judge-rated emotional reactions (Figure 1,c) mediated the relationship between coder-rated verbal and expressive behavior apology components (Figure
1,b), apologizer-rated emotions (Figure 1,a), and judge-rated behavioral reactions (Figure 1,d).
Apologizer-rated emotions predicting judge reactions. To examine the individual contributions that apologizer-rated emotions (Figure 1,a) have on judges’ emotional, cognitive, and behavioral reactions (Figure 1,c and Figure 1,d), the five apologizer-rated emotion factors were entered as predictors of the judge-rated outcomes. Table 13 displays the results of this analysis. The self-conscious emotion factor was the sole significant predictor of empathy, sympathy, trust, and sincerity. The self-consciousness factor did not significantly predict forgiveness or attributions.
Coder-rated verbal components predicting judge reactions. To test the predictive ability of the coder-rated verbal components I entered acknowledgment of violated rules and norms, remorse, and compensation as predictors of judges’ emotional and cognitive reactions
(Figure 1,c) and judges’ behavioral reactions (Figure 1,d). To control for severity of the transgression, judge-rated severity was also entered as a predictor. The individual contributions of each component (i.e., acknowledgment, remorse, compensation, and severity) were examined for each judge-rated outcome (Figure 1,c and Figure 1,d). See Table 14 for the results. Remorse was a significant predictor for all judge-rated outcomes except for attributions. Acknowledgment 52 of violated rules and norms and compensation did not predict any of the judge-rated outcomes.
Severity was a positive predictor of attributions (i.e., severity was associated with the tendency to make a dispositional attribution) and a negative predictor of forgiveness and trust.
Interaction and additive effects of the verbal and expressive behavior components.
Thus far the analyses reveal that coder-rated remorse predicts judge-rated empathy, sympathy, forgiveness, trust, and ratings of apologizer sincerity. Furthermore, coder-rated guilt and shame and apologizer-rated self-conscious emotions predict judge-rated outcomes. What is still unknown is whether there are interaction or additive effects between these components. Because guilt and shame were highly correlated, I aggregated them to create a coder-rated guilt-shame aggregate variable for these analyses. Six interaction analyses were completed, one for each of the judge-rated outcomes: empathy, sympathy, attributions, forgiveness, trust, and sincerity.
To begin, I centered the variables of interest: coder-rated remorse, guilt, and shame as well as apologizer-rated self-conscious emotions factor. I then created four interaction variables by multiplying (1) remorse with self-conscious emotions (2) remorse with the guilt-shame aggregate, (3) self-conscious emotions and the guilt-shame aggregate, and (4) remorse, self- conscious emotions, and the guilt-shame aggregate. For each analysis the centered variables and the interaction variables were entered as predictors to predict the judge-rated outcome (i.e., empathy, sympathy, attribution, forgiveness, trust, or sincerity). See Table 15 for interaction results. As the table shows, there were no significant interaction effects. Thus, to examine additive effects (i.e., whether the components are significant predictors of the dependent variables when controlling for each other) I simplified the model by including remorse, self- conscious emotions, and the guilt-shame aggregate as predictors of empathy, sympathy, attributions, forgiveness, trust, and sincerity. See Table 16 for the results. As the table reveals, 53 there were additive effects of remorse and self-conscious emotions in the prediction of empathy, sympathy, and sincerity. There were no additive effects (i.e., the betas were nonsignificant) in the prediction of trust and forgiveness.
The mediating role of judges’ cognitive and affective responses. The final question I sought to answer was why the components are effective. With coder-rated verbal (i.e., remorse) and expressive behavior components (i.e., coder-rated guilt, coder-rated shame, and apologizer- rated self-conscious emotions) as well as judge-rated emotional and cognitive responses (i.e., empathy and sympathy) significantly predicting judge-rated behavioral reactions (i.e., forgiveness, trust, and sincerity), I conducted a mediation analysis to test whether the judge-rated emotional and cognitive responses mediated the relationship between the coder-rated verbal and expressive behavior components and the judge-rated behavioral reactions (see Figure 2). For these analyses, coder-rated remorse, guilt, shame, and apologizer self-conscious emotions were aggregated to create a components variable. Judge-rated empathy and sympathy were aggregated to create a judge-rated empathic response variable. Judge-rated forgiveness, trust, and sincerity were aggregated to create a judge-rated outcomes variable.
To examine the statistical significance of the effect of the components variable (i.e.,
Figure 2,a; the mediated variables) on the judge-rated outcomes variable (i.e., Figure 2,c; forgiveness, trust, and sincerity) via the mediators (i.e., Figure 2, b; judge-rated empathic response) I followed procedures suggested by Kenny, Kashy, and Bolger (1998). As shown in
Figure 2, judge-rated empathic response mediated the effect of components on judge-rated outcomes, Sobel Z = 4.299, p = .000. Thus, the apology components predicted judge-rated forgiveness, trust, and sincerity by virtue of their ability to elicit judge empathic response (i.e., judge-rated empathy and sympathy). However, these results can also be interpreted in an 54 alternative manner. The path between judge empathic response and judge-rated outcomes is quite strong and may be the reason why the mediation analysis was significant. In fact, if judge empathic response and judge-rated outcomes are switched in the mediation model (i.e., judge empathic response becomes the dependent variable and judge-rated outcomes becomes the mediator), the mediation analysis is also significant, Sobel Z = 4.022 , p < .001. Another way to interpret this data is that judge empathic response is an ingredient of the judge outcomes. For example, empathy is an element of forgiveness, rather than a cause.
Discussion
The aim of the present study was to examine the relationship between apology components (i.e., verbal and expressive behavior actions displayed by an apologizer) and judge- rated outcomes. The apology components included both apologizer-rated emotions and coder- rated verbal (i.e., remorse, acknowledgment of violated rules and norms, and compensation) and expressive behavior (i.e., guilt and shame) components. The judge-rated outcomes included empathy, sympathy, dispositional attributions, forgiveness, trust, and sincerity.
Descriptive statistics revealed apologizers experienced high levels of self-conscious emotions. Therefore, the methodology used was able to evoke the emotional experience typically felt by apologizers (Lazare, 2004). It also was revealed that apologizers rarely made verbal offers of compensation. This may be due to the nature of the relationship between the apologizer and recipients. Apologizers were asked to apologize to a “close other.” As previously speculated, compensation may not be used in emotion-based close relationships whereas it might be a common strategy used by individuals apologizing to outgroups or exchange-based relationships.
Correlation and multiple regression analyses revealed that coder-rated remorse, guilt, and shame were significant predictors of judge-rated empathy, sympathy, forgiveness, trust, and 55 sincerity. Similarly, apologizer-rated self-conscious emotions also predicted these outcomes.
Thus, apologizers who felt and expressed their self-conscious emotions were more likely to receive positive responses from offended parties. The relationships between judge-rated empathy, sympathy, forgiveness, trust, and sincerity with coder-rated remorse, guilt, and shame, and apologizer-rated self-conscious emotions remained significant after controlling for judge- rated severity of the transgression. Thus, these components predict judge-rated outcomes regardless of transgression severity level.
Analyses revealed an additive effect for coder-rated remorse and apologizer-rated self- conscious emotions. These additive effects suggest that apologies produce the most effective judge outcomes when apologizers feel bad about the transgression (i.e., reports self-conscious emotions) and express negative emotions externally through verbal behavior (i.e., coder-rated remorse). This finding has an important implication for apologizers suggesting that the best apologies are ones in which apologizers genuinely feel sorry for what they have done.
The final question addressed by Study 2 was why verbal and expressive behavior apology components elicit judge-rated outcomes. To answer this question analyses were conducted to test whether judge-rated empathy and sympathy mediated the relationship between the apology components (i.e., coder-rated remorse, guilt, shame, and apologizer self-conscious emotions) and judge-rated outcomes (i.e., forgiveness, trust, and sincerity). Although the mediation model was significant, the mediator (i.e., empathy and sympathy) and judge-rated outcome (i.e., forgiveness, trust, and sincerity) path was extremely high. The strong relationship between judge empathic response (i.e., empathy and sympathy) and judge-rated outcomes (forgiveness, trust, and sincerity) suggests these variables may be so highly correlated that they are interchangeable rather than causal. McCullough et al. (1997) reported a similar finding when they examined the 56 relationship between empathy and forgiveness. In their study, items from an empathy scale and a forgiveness scale were factor analyzed. The factor analysis revealed two factors. However, three of the eight items from the empathy scale loaded on both factors suggesting that empathy and forgiveness share similar features.
Limitations. Apologies were observed by judges instead of the actual individuals who were offended. This approach may not be ideal, but it is similar to the analogue patient methodology used in doctor-patient communication research (Blanch-Hartigan, Hall, Krupat, &
Irish, 2012; Schmid Mast, Hall, & Roter, 2008). In this research, analogue patients and doctors are believed to provide results that are informative about actual patient-doctor communication. In fact, research has demonstrated that subjective ratings provided by analogues correspond with ratings provided by real patients (Blanch-Hartigan, Hall, Krupat, & Irish, 2012). Therefore the judgments made by the judges in the current study may closely reflect how the intended apology recipients would respond.
Using this methodology, insight may also be gained into the effects apologies have on people indirectly affected by a transgression. A transgression typically offends people in addition to the intended recipient. The transgressor’s apology may influence these unintended victims.
While at a holiday celebration, a spouse’s hurtful comments to her husband might be offensive to family members within hearing distance. If these same bystanders hear the woman apologize to her husband, their vicarious feelings of being offended may be relieved.
The effects of transgression type were not thoroughly investigated in the current study.
Although transgression severity was measured and statistically controlled in several analyses, this variable only provided insight into how the intensity of a transgression influences judge outcomes and not how the type of transgression affects judge outcomes. Transgressions receiving 57 similar ratings of severity may in fact be quite different. For example, in the current study one apologizer reported cheating on a significant other while another reported breaking a sibling’s iPod. Both transgressions were rated high on severity, but most likely for different reasons. The cheating transgression most likely included emotional consequences whereas the iPod transgression was probably associated with financial consequences. In these two examples, an effective apology may have required different apology components to elicit victims’ forgiveness.
Future studies may wish to examine this possibility.
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Chapter 4: General Discussion
According to theorists and researchers, apologies represent an effective tool for communicating regret and remorse. Previous research has shown that apologies are associated with positive outcomes for transgressors and offended parties (e.g., Fehr, Gelfand, & Nag, 2010;
DeCremer, van Dijk, & Pillutla, 2010; Robbennolt, 2003). However, apologies can backfire if not done properly (e.g., DeCremer et al., 2010; Eaton, Struthers, Shomrony, & Santelli, 2007;
Zechmeister, Garcia, Romero, Vas, 2004). The present research investigated the components that influence an apology’s effectiveness.
Across a meta-analysis and lab study, remorse strongly predicted offended parties’ emotional and cognitive reactions. In the meta-analysis, remorse predicted effect size for both high and low social-distance relationships. In the lab study, remorse predicted offended party empathy, sympathy, forgiveness, trust, and sincerity. Furthermore, the outward expression of remorse (i.e., coder-rated guilt, shame, and apologizer rated self-conscious emotions) similarly predicted these same outcomes.
A mediation analysis in which the apology components predicted judge outcomes with judge empathic response as the mediator, was unable to explain why the components work.
Although the proposed mediators were statistically significant, these effects were best explained by the relationship between the mediators (i.e., empathy and sympathy) and the judge-rated outcomes (i.e., forgiveness, trust, and sincerity). The strong relationship between the mediators and the judge-rated outcomes may suggest two things: (1) the measurement of the constructs was not sufficiently precise or (2) the two constructs may be one in the same, rather than causal. If the former is true then researchers may wish to use more detailed scales or behavioral measures of these constructs. If that latter is true, alternative explanations for why the components elicit 59 judge-rated outcomes should be explored. One potential framework to use is McCullough et al.’s
(2013) theory on forgiveness systems. According to this framework, forgiveness can occur when apologizers signal to the offended parties that they (i.e., the apologizers) are valuable (i.e., they are willing to share fitness-relevant resources) and safe (i.e., will not harm the offended party again in the future).
Remorse most likely indicates safety. By expressing remorse, apologizers signal to offended parties that they realize the benefits gained by committing the transgression did not outweigh the consequences (i.e., negative affect, loss of friendship, etc.). Thus, apologizers implicitly, perhaps explicitly, promise that they will not commit the same transgression again.
Apologies that contain an acknowledgment of violated rules and norms might also signal to victims the relative “safety” of the transgressor. After experiencing a transgression, offended parties typically search for an explanation for why it occurred. This might result in assigning blame to the transgressor (i.e., the offended party will attribute the cause of the behavior).
Typically, offended parties make dispositional attributions, believing the transgressor was the cause of the transgression and the transgression was not due to some situational force (e.g.,
Weiner, Graham, Peter, & Zmuidinas, 1991). An acknowledgment of violated rules and norms can cement this inference by reminding offended parties of the transgression and its negative impact (Kim, Ferrin, Cooper, & Dirks, 2004). Supporting this argument, acknowledgment of violated rules and norms negatively predicted effect size for high social-distance relationships in the meta-analysis. This finding was not observed, however, in low social-distance relationships or in the lab study (which involves low social distance relationships). In the latter two cases acknowledgment of violated rules and norms did not predict effect size or judge-rated outcomes. 60
In close relationships, attributions have been well-established over time and an apology that acknowledges rules and norms were violated will not change those attributions.
Finally, using McCullough et al.’s (2013) forgiveness systems model, compensation may be effective because it is a signal of value. When apologizers make an offer of compensation, they express their willingness to share resources and indicate the value in maintaining a relationship with them. In the meta-analyses compensation was a significant predictor of effect size in high social-distance relationships, but not for low social-distance relationships.
Furthermore, it was not significant in the lab study. The type of compensation coded for in the current studies may not occur in low social-distance relationships because these relationships are not exchange-based. In these relationships it may be the case that compensation comes in the form of emotional support or services. Alternatively it may simply not occur and value is signaled through other channels. Future research may wish to examine alternative components that may elicit value perceptions.
Limitations and Future directions
The current studies examine the effectiveness of three apology components (i.e., remorse, an acknowledgment of violated rules and norms, and compensation). However, there may be additional components that influence an apology’s effectiveness. Using McCullough et al.’s
(2013) forgiveness framework, components that may signal to offended parties that the apologizer is valuable and safe are predicted to be effective in eliciting positive outcomes from the offended party such as forgiveness. One potential component is excuse making. Excuse making is often examined outside the context of apology or in comparison to an apology (e.g.,
Conlon & Murray, 1996), but apologies may also include excuse or external blame. By holding a 61 force outside of the apologizer culpable, the apologizer is signaling that the transgression was not the fault of the apologizer and is unlikely to happen again.
Another interesting line of work involves linguistic analysis of apologies. For example, using Pennebaker, Booth, and Francis’ (2007) Linquistic Inquiry and Word Count (LIWC) analysis researchers can calculate the degree to which apologizers use different categories of words such as negative emotions, self-references, causal words and determine how effective they are in producing positive offended party outcomes. Similarly, nonverbal behavior researchers may be interested in using the Facial Action Coding System (FACS; Ekman, Friesen, Hager,
2002) to identify the apologizers’ expressions associated with offended party outcomes.
Another potential avenue of research is to examine the interaction between verbal and expressive behavior components. The lab study did not find significant interactions between verbal and expressive behavior components, but this may be because apologizers rarely exhibited low levels of guilt, shame, and self-conscious emotions when exhibiting high levels of verbal remorse. It would be interesting to create videos in which actors, who are not experiencing true self-conscious emotions, read scripts of apologies given by truly remorseful apologizers. Judges could then watch both videos and researchers could examine whether judges forgive the truly remorseful apologizers more than the actors.
Finally, researchers interested in apologies may wish to further explore the interaction between judges’ traits and apology components. Fehr and Gelfand (2010) found individual differences in what offended parties must hear in an apology in order for it to be effective.
Specifically they found that forgiveness was more likely when the apology components matched the offended parties’ self-construal. Therefore, it can be predicted that individual differences in 62 judges will affect the type of apology components they wish to hear in order to forgive. This may be expanded to cultural and gender differences.
Conclusion
This dissertation examined the components that render an apology more effective.
Identifying effective components may help apologizers who wish to mend relationships. Three theoretically driven components were examined: remorse, an acknowledgment of violated rules and norms, and compensation. Based on the findings of the current research studies, apologizers in high social distance relationships who wish to mend their relationship with an offended party may wish to include a verbal statement of remorse, an offer of compensation, and should not make an acknowledgment of a violated rule or norm. Making this acknowledgment may remind offended parties of what the apologizer has done and makes it difficult for them to forgive.
Apologizers in low social distance relationships seeking forgiveness should include a verbal expression of remorse in their apology. Furthermore, and more importantly, apologizers should genuinely feel remorseful for what they have done. This remorse may then express itself through expressive behaviors and act as a cue to sincerity for the offended party.
63
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Footnotes
1 This dissertation examines how apologies elicit positive outcomes for apologizers (e.g., being forgiven by an offended party). However, positive outcomes for apologizers are not always favorable for offended parties. Forgiving an insincere apologizer who will transgress again is not adaptive for offended parties. Therefore, it is important to state that the results of these studies are not meant to be used in a manipulative way. Instead the results should be used to inform good-intentioned apologizers.
2The majority of the 16% involved jury-defendant relationships. Although these relationships could be classified as high social distance they differ from others in this category because the defendant (i.e., an individual) is apologizing to a group, while the other relationships in this category involve a group (or a representative of a group) apologizing. Thus, we excluded defendant-jury relationships in social-distance analyses.
3Five additional studies were included in the overall meta-analysis, but did not fall into our five categories. These studies examined the relationship between apologies and voting (Sigal,
1988) and apologies and hiring intentions (Ferrin, 2007; Kim, 2004).
4The standardized β coefficients are presented for all analyses.
5Means were also calculated separately for female and male judges. Independent t-tests comparing the male and female means for the six judge-rated variables revealed no differences.
82
Table 1
Characteristics of Studies Included in the Meta-Analysis
First author Year N Effect size (r) Dependent variable
Ahmend 2007 517 .40 Forgiveness
Allan 2006 134 .10 Positive Perceptions
Anderson 2006 184 .00 Positive Emotions
Azar 2001 96 .73 Forgiveness
Azar 1999 48 .66 Forgiveness
Bachman 2006 263 .40 Forgiveness
Bhandari 2012 80 .21 Purchase Intentions
80 .57 Purchase Intentions
Bolkan 2009 134 .13 Positive Emotions
134 .18 Purchase Intentions
Bono 2005 32 .38 Positive Emotions
32 .00 Positive Emotions
241 .35 Positive Emotions
241 .11 Forgiveness
149 .33 Positive Emotions
149 .25 Forgiveness
Bono 2011 115 .13 Forgiveness
112 .17 Forgiveness
Bornstein 2002 173 .04 Legal Sentencing
173 .26 Positive Perceptions 83
128 .18 Legal Sentencing
Braaten 1993 51 .43 Forgiveness
Bradford 1995 85 .30 Positive Emotions
Brown 2005 200 .37 Forgiveness
Brown 2008 80 .58 Forgiveness
80 .63 Positive Emotions
Coombs 2007 167 .07 Positive Perceptions
167 .14 Positive Emotion
Coombs 2008 83 .38 Positive Perceptions
83 .00 Positive Emotions
Dardis 2008 189 .05 Positive Perceptions
Dawar 2000 90 .42 Positive Perceptions
164 .30 Positive Perceptions
Day 2010 518 .16 Legal Sentencing
512 .18 Legal Sentencing
Dean 2005 107 .36 Positive Perceptions
291 .05 Positive Perceptions
DeCremer 2008 128 .81 Positive Perceptions
119 .33 Positive Emotions
119 .36 Positive Emotions
DeCremer 2010 36 .27 Positive Perceptions
Dijke 2011 95 .08 Forgiveness
128 .13 Forgiveness 84
Dirks 2011 143 .43 Positive Perceptions
60 .26 Positive Perceptions
Dunn 2000 709 .02 Positive Perceptions
Eaton 2006 107 .54 Forgiveness
107 .34 Positive Emotions
Eaton 2006 67 .22 Forgiveness
67 .27 Positive Perceptions
62 .15 Forgiveness
62 -.08 Positive Perceptions
Eaton 2007 79 -.29 Forgiveness
Exline 2004 276 .42 Forgiveness
Exline 2007 86 .32 Forgiveness
Exline 2008 218 .53 Forgiveness
218 .35 Positive Emotions
Ferrin 2007 67 -.12 Positive Perceptions
67 -.03 Other/Hiring Decision
160 .02 Positive Perceptions
160 -.05 Other/Hiring Decision
Giacalone 1995 87 .03 Forgiveness
Giner-Sorolla 2007 271 .32 Positive Emotions
Girard 1997 236 .58 Forgiveness
Goei 2007 64 .05 Positive Emotions
64 -.01 Forgiveness 85
186 .03 Positive Emotions
186 .11 Forgiveness
Gold 2000 112 .39 Positive Perceptions
112 .65 Positive Emotions
112 .29 Forgiveness
Goodwin 1992 285 .00 Positive Perceptions
285 .00 Positive Emotions
Green 2011 65 .35 Forgiveness
65 .27 Forgiveness
Gunderson 2008 196 .67 Forgiveness
Haigh 2010 170 .11 Positive Attributions
Harrell 1980 48 .58 Forgiveness
Hodgins 2003 64 .48 Forgiveness
Howley 2009 1652 .58 Positive Emotions
Huang 2006 233 .06 Positive Perceptions
456 -.01 Positive Perceptions
350 .12 Positive Perceptions
177 .43 Positive Perceptions
Huang 2010 278 .26 Positive Perceptions
Kelley 2005 186 .17 Forgiveness
Kim 2009 207 .24 Forgiveness
Kim 2004 200 -.01 Positive Perceptions
200 -.09 Other/Hiring Decision 86
116 .02 Positive Perceptions
116 .03 Other/Hiring Decision
Kleinke 2001 98 .29 Positive Perceptions
184 .25 Positive Perceptions
184 .13 Legal Sentencing
Leonard 2011 95 .25 Positive Emotions
95 .15 Positive Perceptions
95 .22 Forgiveness
Liao 2007 658 .37 Purchase Intentions
658 .53 Positive Emotions
395 .07 Purchase Intentions
395 .12 Positive Emotions
Luzombe 2009 98 .15 Forgiveness
Lyon 2004 80 .37 Purchase Intentions
80 .46 Positive Perceptions
McCullough 2010 125 .09 Forgiveness
372 .11 Forgiveness
McCullough 1998 187 .56 Positive Emotions
187 .42 Forgiveness
McCullough 1997 239 .45 Forgiveness
Morse 2011 360 .24 Forgiveness
Mullet 2007 224 .97 Forgiveness
258 .74 Forgiveness 87
Niedermeier 2001 362 -.05 Legal Sentencing
264 .27 Legal Sentencing
Ohbuchi 1989 58 .38 Positive Perceptions
58 .25 Positive Emotions
58 .38 Forgiveness
80 .85 Positive Perceptions
80 .71 Positive Emotions
80 .36 Forgiveness
Orleans 1984 60 .24 Forgiveness
60 .37 Positive Perceptions
Pace 2010 264 .20 Positive Perceptions
264 .37 Positive Emotions
Philpot 2008 60 .03 Positive Emotions
60 .12 Forgiveness
60 .40 Positive Emotions
73 .15 Forgiveness
73 .58 Positive Emotions
214 .07 Forgiveness
214 .54 Positive Emotions
79 .18 Forgiveness
79 .10 Positive Emotions
79 .17 Forgiveness
79 .09 Positive Emotions 88
79 .35 Forgiveness
79 .47 Positive Emotions
79 .54 Forgiveness
79 .36 Positive Emotions
Philpot 2010 116 .24 Forgiveness
76 .14 Forgiveness
Pipes 1999 149 .17 Forgiveness
Proeve 2006 77 .02 Legal Sentencing
Risen 2007 43 .22 Positive Perceptions
42 .20 Positive Perceptions
41 .05 Positive Perceptions
37 -.51 Positive Perceptions
24 .44 Positive Perceptions
25 .44 Positive Perceptions
22 .51 Positive Perceptions
23 .00 Positive Perceptions
Robbennolt 2006 556 .20 Forgiveness
556 .09 Legal Sentencing
Robbennolt 2008 190 .00 Forgiveness
190 -.15 Legal Sentencing
Rumsey 1976 45 .37 Legal Sentencing
Santelli 2009 28 .55 Forgiveness
28 .17 Forgiveness 89
28 .26 Forgiveness
28 .27 Forgiveness
Schmitt 2010 480 -.15 Positive Perceptions
480 .41 Positive Emotions
Schweitzer 2006 132 .11 Positive Emotions
Sigal 1988 73 -.26 Other/Voting
Struthers 2010 168 .46 Forgiveness
250 .13 Forgiveness
250 .43 Positive Emotions
90 .17 Forgiveness
Struthers 2008 177 .50 Positive Perceptions
177 .39 Forgiveness
Tabak 2012 100 .19 Positive Perceptions
100 .84 Forgiveness
Taylor 1992 320 .00 Legal Sentencing
Thomas 2008 60 .35 Positive Emotions
Tomlinson 2004 90 .07 Forgiveness
Tucker 2006 94 .47 Positive Perceptions
50 .30 Positive Perceptions
224 .27 Positive Perceptions van Laer 2010 76 -.39 Positive Perceptions
76 -.27 Purchase Intentions
76 .47 Positive Perceptions 90
76 .39 Purchase Intentions
145 .03 Positive Perceptions
Vassilikopoulous 2008 240 .39 Positive Perceptions
240 .39 Purchase Intentions
Vinsonneau 2001 203 .82 Forgiveness
Weiner 1991 125 .45 Positive Perceptions
125 .29 Forgiveness
87 .20 Forgiveness
Wenzel 2010 88 .18 Forgiveness
88 .06 Positive Perceptions
Whited 2010 79 .18 Positive Emotions
79 .00 Forgiveness
Wirtz 2003 187 .47 Positive Emotions
Wooten 2009 200 .23 Forgiveness
200 .20 Positive Perceptions
162 .26 Forgiveness
162 .16 Positive Perceptions
216 .28 Forgiveness
Xie Peng 2009 220 .57 Positive Perceptions
220 .53 Forgiveness
Younger 2004 103 .17 Forgiveness
Zechmeister 2004 56 .20 Forgiveness
56 -.24 Forgiveness 91
113 -.25 Positive Perceptions
N = 94 papers
92
Table 2
Results for Meta-Analyses Examining Efficacy of Apologies
Mean r
Outcome k w uw Range Z fixed Z random Heterogeneity File drawer
Combined 144 .22 .27 -.51-.97 46.83*** 10.72*** 2300.71*** 24177
Forgiveness 79 .41 .32 -.29-.97 38.576*** 8.155*** 1427.81*** 25193
Positive Attributes 60 .19 .24 -.51-.85 17.796*** 6.689*** 599.474*** 5647
Positive Emotions 43 .39 .33 .00-.71 37.741*** 9.414*** 422.347*** 98
Legal Sentencing 11 .11 .13 -.05-.37 6.297*** 3.493*** 29.897** 98
Purchase Intentions 10 .24 .23 -.27-.57 10.815*** 2.848** 97.965*** 222
Note. k effect sizes= the total number of samples utilized to estimate a given effect; Mean r= the unweighted mean of correlations for a given correlate; Weighted mean r= the weighted mean of correlations for a given correlate; Z-combined= test of whether the mean r is greater than zero; Heterogeneity=whether effects vary more than expected by chance; Fail-safe k= the number of studies needed to shift the demonstrated effect to include zero.
93
Table 3
Correlations Among Apology Components and Effect Size
Component Severity Remorse Ack Compensation Effect Size
Severity ------.35** -.06 .30** .11
Remorse ------.33** .28* .24*
Ack ------.32** -.08
Compensation ------.21+
Note. Ack = acknowledgment of violated rules and norms
k = 77
+p < .10, * p < .05, **p < .01
94
Table 4
Interaction Analysis for Remorse, Acknowledgment of Violated Rules and Norms, and
Compensation for High Social Distance Relationships
Apology component as predictor of effect size β
Remorse .66*
Acknowledgment of Violated Rules and Norms -.52
Compensation .03
Remorse x Acknowledgment of Violated Rules and Norms .37
Remorse x Compensation .04
Acknowledgment of Violated Rules and Norms x Compensation -.36
Remorse x Acknowledgment of Violated Rules and Norms x Compensation .38
Note. R2 = .30, F(7, 23) = 3.410, p = .012 k = 37
+p < .10, *p < .05, **p < .01
95
Table 5
Inter-Rater Reliability Indices and Inter-Correlations for Apology Components
Component Alpha Mean SD 1 2 3 4 5
1. Remorse .77 2.76 1.94 --- .05 .56** .63** .70**
2. Compensation .86 0.58 1.42 ------.00 -.09 -.18
3. Acknowledgment .54 4.65 1.39 ------.65** .57**
4. Guilt .65 3.29 1.71 ------.66**
5. Shame .67 1.47 1.50 ------
Note. n = 37
*p < .05, **p < .01
96
Table 6
Phase 1 Apologizer Self-Rated Emotion Descriptive Statistics and Factor Loadings
Factor
Emotion Mean SD 1 2 3 4 5
Shame 3.30 1.02 .80 .00 -.19 .12 -.01
Guilt 4.00 1.08 .78 .05 -.17 .28 .15
Love 2.54 1.41 .73 .11 .21 .01 .05
Sadness 2.92 1.12 .72 .05 .11 .32 .06
Worry 2.51 1.24 .67 .39 .33 .51 -.08
Fear 2.03 1.19 .59 .46 .21 .15 -.25
Embarrassment 2.89 1.31 .57 .13 .21 .34 .02
Excitement 1.51 0.96 .20 .85 .42 .14 .08
Anger 1.49 0.73 .08 .73 .32 .42 -.19
Surprise 1.38 0.68 .09 .72 .57 .32 .08
Relaxation 1.64 0.99 .12 .71 .15 .17 .36
Inspiration 1.78 1.03 .25 .63 .39 .23 .38
Happiness 1.54 0.93 -.11 .61 .26 -.04 .52
Jealousy 1.27 0.73 .04 .47 .85 -.02 .17
Contempt 1.78 0.92 -.02 .42 .73 .39 .00
Disgust 1.49 0.77 .39 .15 .72 .20 -.02
Amusement 2.08 1.26 -.27 .33 .54 -.01 .26
Pity 1.89 0.97 .11 .28 .17 .83 -.11
Empathy 2.73 1.31 .44 .10 .04 .79 .23 97
Compassion 3.32 1.16 .24 .18 .21 .69 .48
Contentment 2.16 1.04 -.07 .14 .07 -.05 .81
Hope 2.59 1.36 .26 .16 .21 .40 .81
Note. Factor 1 = self-consciousness; Factor 2 = apology-reactions; Factor 3 = insincerity;
Factor 4 = empathy; Factor 5 = contentment. n = 37
98
Table 7
Apologizer Self-Rated Emotion Factor Descriptive Statistics and Inter-correlations
Factor
Emotion factor Mean SD 1 2 3 4 5
1. Self-consciousness 2.88 0.84 --- .37 .12 .39* .15
2. Apology-Reactions 1.55 0.66 ------.54** .34* .38*
3. Insincerity 1.66 0.66 ------.22 .29
4. Empathy 2.65 0.94 ------.46**
5. Contentment 2.38 1.06 ------
Note. n = 37
*p < .05, **p < .01
99
Table 8
Apologizer Self-Rated Emotion Factors Correlated with Apology and Transgression-Specific
Questions
Emotion factor
Question Self-Consciousness Apology-Reactions Insincerity Empathy Contentment
Sincere .28+ .22 -.05 .05 -.21
Upset -.23 .14 .19 .00 -.02
Reasonable .28 -.15 .01 -.06 -.11
Severe .20 -.09 -.23 .05 -.22
Note. Sincere refers to the question, “How sincere was the apology that you just provided?”
Upset refers to “How upset was the person who was hurt by you after they found out about your behavior?” Reasonable refers to “How reasonable was the person that you hurt's reaction to your behavior?” Severe refers to “How bad/severe do you think the behavior that you apologized for was?” n = 37
+p < .10*p < .05, **p < .01 100
Table 9
Correlations among Judge-rated Items
Item Mean SD 1 2 3 4 5 6 7 8 9
1. Commit 1.56 .25 ---- .77** -.23 -.17 -.26 .20 -.37* -.30+ .08
2. Against 1.62 .21 ------.14 -.17 -.18 .11 -.28+ -.24 .23
3. Forgive 4.61 .94 ------.91** .96** -.32+ .87** .86** -.65**
4. Sincere 4.38 1.14 ------.89** -.00 .94** .93** -.55**
5. Trust 4.14 .90 ------.25 .90** .91** -.71**
6. Severe 3.87 .80 ------.01 .08 .31
7. Empathy 4.11 .75 ------.96** -.52**
8. Sympathy 3.37 .93 ------.60**
9. Attributions 4.61 .79 ------
Note. n=37
+p<.10, *p<.05, **p<.01
101
Table 10
Coder-rated Items Correlated with Apologizer and Judge-rated Items
Coder-rated items
Remorse Compensation Acknowledge Guilt Shame
Apologizer-rated
1. Self-consciousness .23 .11 .16 .29+ .22
2. Apology-reactions -.06 .02 -.06 .18 .08
3. Insincerity .02 -.16 .12 .11 .10
4. Empathy -.01 .01 .15 .18 .00
5. Contentment -.07 .27 .10 -.01 -.19
Judge-rated
1. Commit -.09 .30+ -.07 .06 -.21
2. Against -.02 .15 .05 .25 -.03
3. Forgive .49** .21 .48** .43** .38*
4. Sincere .62** .17 .51** .54** .46**
5. Trust .46** .19 .43** .42* .35*
6. Severe .15 .05 -.04 .09 .03 102
7. Empathy .53** .16 .44** .48** .39*
8. Sympathy .54** .20 .40* .48** .37*
9. Attributions -.16 -.26 -.13 .02 .04
Note. Commit= Have you ever committed a similar transgression?; Against= Has anyone ever committed this transgression against you?
n=37
+p<.10, *p<.05, **p<.01
103
Table 11
Apologizer-rated Items Correlated with Judge-rated Items
Apologizer-rated Items
Judge-rated Items Self-Consciousness Apology-reactions Insincerity Empathy Contentment
1. Commit -.26 -.10 .09 -.05 -.12
2. Against -.32 -.03 -.04 -.19 -.19
3. Forgive .33* .05 -.07 .17 .04
4. Sincere .40* -.04 -.13 .19 .07
5. Trust .36* .01 -.11 .09 -.01
6. Severe .13 -.26 -.27 -.11 -.02
7. Empathy .40* -.08 -.26 .03 -.02
8. Sympathy .49** -.07 -.24 .06 -.03
9. Attributions -.15 .12 .13 -.07 .08
Note. n=37
+p<.10, *p<.05, **p<.01
104
Table 12
Apologizer and Coder-Rated Components Correlated with Judge-Rated Outcomes Controlling for Judge-Rated Severity
Component Empathy Sympathy Forgiveness Trust Sincerity
Guilt .39* .37* .41* .37* .46**
Shame .48** .48** .49** .45** .55**
Remorse .54** .54** .57** .52** .63**
Acknowledgment .44** .41* .49** .43** .51**
Compensation .16 .19 .24 .21 .17
Self-Conscious Factor .40* .48** .40* .41* .41*
Note. n=37
+p<.10, *p<.05, **p<.01
105
Table 13
Apologizer-rated Emotions Predicting Judge Reactions
Apologizer-rated emotions betas
Judge reactions Self-consciousness Apology-reactions Insincerity Empathy Content
Empathy .48** -.04 -.29 -.11 .06
Sympathy .57** -.06 -.26 -.10 .02
Attributions -.16 .13 .07 -.10 .08
Forgiveness .31 .01 -.12 .08 -.01
Trust .40* -.01 -.14 -.02 -.02
Sincerity .42* -.11 -.16 .07 .06
Note. n = 37; The significant models included empathy (R2 = .14, F(5,31) = 2.206, p = .079) and sympathy (R2 = .23, F(5,31) = 3.16, p = .020). The models for attributions (R2 = .-.09,
F(5,31) = .402, p = .844), forgiveness (R2 = .-.02, F(5,31) = .887, p = .501), trust (R2 = .022,
F(5,31) = 1.159, p = .351), and sincerity (R2 = .081, F(5,31) = 1.63, p = .181) were nonsignificant.
+p < .10, *p < .05, **p < .01
106
Table 14
Acknowledgment, Remorse, and Compensation Predicting Judge Reactions
Coder-rated verbal component betas
Judge reactions Acknowledgment Remorse Compensation Severity
Empathy .20 .42* .14 -.08
Sympathy .16 .44* .17 .01
Attributions -.00 -.20 -.27 .36*
Forgiveness .24 .41* .21 -.39**
Trust .20 .39* .19 -.31*
Sincerity .23 .50** .15 -.08
Note. n = 37; This model was significant for all judge-rated outcomes: empathy (R2 = .25,
F(4,32) = 3.98, p = .010), sympathy (R2 = .25, F(4,32) = 4.03, p = .009), attributions (R2 = .11,
F(4,32) = 2.16, p = .096), forgiveness (R2 = .41, F(4,32) = 7.35, p = .000), trust (R2 = .30,
F(4,32) = 4.85, p = .004), and sincerity (R2 = .39, F(4,32) = 6.64, p = .001).
+p < .10, *p < .05, **p < .01
107
Table 15
Interaction Analysis for Coder-Rated Remorse, Coder-Rated Guilt-Shame Aggregate, and Apologizer-Rated Self-conscious emotions
Judge reactions Remorse SC GS-Agg Rem Rem SC All R2 x x x SC GS-Agg GS-Agg Empathy .40+ .25 .12 -.18 -.08 .10 -.04 .30
Sympathy .42* .44* .07 -.16 -.01 .05 -.14 .35
Attributions -.34 -.28 .27 .14 -.14 .11 .18 -.09
Forgiveness .32 .27 .21 -.12 .03 -.13 -.11 .16
Trust .30 .38+ .18 -.15 .03 -.08 -.19 .15
Sincerity .46* .27 .18 -.22 .08 -.03 -.05 .37
Note. Remorse=coder-rated remorse; SC= apologizer-rated self-conscious emotions; GS-Agg=coder-rated guilt-shame aggregate;
Rem+SC= interaction between coder-rated remorse and apologizer self-conscious emotions; Rem+GS-Agg=interaction between coder-rated remorse and coder guilt-shame aggregate; SC+ GS-Agg=interaction between apologizer self-conscious emotions and coder-rated guilt-shame aggregate; All=interaction between coder-rated remorse, coder-rated guilt-shame aggregate, and apologizer self-conscious emotions; Adjusted R2 reported. n=37
+p<.10, *p<.05, **p<.01 108
Table 16
Coder Rated Remorse, Coder Rated Guilt-Shame Aggregate, and Apologizer Self Conscious
Emotions Predicting Judge Reactions
Betas(β)
Judge reactions Remorse Guilt-Shame SC R2
Empathy .37+ .13 .28+ .31
Sympathy .41* .07 .38* .38
Attributions -.37 .34 -.15 .01
Forgiveness .34 .14 .22 .23
Trust .32 .12 .26 .23
Sincerity .46* .14 .26+ .42
Note. Remorse = Coder rated remorse; Guilt-Shame = coder rated guilt-shame aggregate; SC =
Apologizer rated self-conscious emotions; Adjusted R2 reported.
+p < .10, *p < .05, **p < .01
109
110
Figure 2
Mediation Analysis Diagram
Note. Judge empathic response as a mediator of judge-rated outcomes. Coefficients in parentheses indicate zero-order correlations. Coefficients not in parentheses represent parameter estimates for a recursive path model including both predictors. Double asterisks (**) indicate parameter estimates or correlations that differ from zero at p < .01.
111
Appendix A
List of Dependent Variables and Their Categorizations in Study 1
1. Forgiveness a. Forgiveness b. Less punishment (outside of a legal context) c. Less aggression d. Less revenge/less retaliation e. Positive ratings of future relationship closeness/friendship f. Trust repair g. Cooperation h. Reconciliation i. Less avoidance j. Benevolence k. Compliance
2. Positive Attributions a. Honesty b. Trustworthiness c. Positive press d. Competence e. Integrity f. Positive regard g. Positive leadership (i.e., rating the apologizer as a good leader) h. Positive character ratings i. Positive word-of-mouth j. Morality k. Socially responsible l. Credibility m. Ethical n. Favorable
3. Positive Emotions a. Positive emotions/positive emotional reaction b. Satisfaction c. Compassion d. Empathy e. Concern f. Less begrudging emotions g. Liking h. Less anger i. Sympathy j. Gratitude k. Indebtedness l. Less unpleasant affect 112
m. Trust n. Less hostility o. Respect
4. Legal Sentencing a. Less punishment b. Shorter prison sentence c. Less harsh legal settlement d. Less likely to be found guilty
5. Purchase Intentions a. Purchase intentions b. Intention to switch hotels (reverse coded) c. Repurchase intentions d. Intent to invest in company e. Intention to switch doctors (reverse coded)
6. Other a. Hiring decisions b. Voting intentions
113
Appendix B
Transcripts and Coder Ratings of Three Apologies from Study 2
Participant 26: “I'm sorry that the last time we spoke we were not very kind to each other. I wish I had taken more time to really figure out the best way to say that you've changed. You've changed in a way that you, you let your ego get in the way. And you could not relate to the problems that are going on in my life. For a whole year you, you've never, you've never asked me how I was handling my problems at home. You never did. And I tried to tell you that you were just not the same, but I blew up on you. And that, I was having a bad time I had just, it was, I was too proud, I don't know. I couldn't tell you what was going on without actually screaming it to your face, and you should have known. But, I'm sorry that it had to end this way, that our last words together will never be that we are just gonna agree to disagree. I'll, I'll always love you, but right now I don't think that we're the same people, and as much as it hurts me that we aren't speaking anymore, I think it's for the best in which we need to just take time to do ourselves.” **This apology received the following coder-rated scores: Remorse M=1.67; Acknowledgment of violated rules and norms M=2.33; Compensation M=0
Participant #32: “Hi (name removed to protect privacy). Umm I want to apologize for all the times that I was not there for you growing up. I know that being your older brother and being the second, sibling in our family I didn't treat you as well as I should have. I know that growing up I always wanted to be like Andrew because he was the oldest one and I thought he was super cool and just the best person that I could think of to want to be. And I know growing up you were just doing what I was doing. Umm looking up to me, hoping for some sort of role model, some sort of someone to lean on. Umm, and I was so focused on trying to be like (name removed to protect privacy), I sort of pushed you to the side and didn't really give you the, I guess uhh the love and the role model guidance that you needed or wanted growing up. And, you know, you are an amazing person. Now and today you were umm pre-med, you're doing everything that you've always wanted to do, even without my help. Umm, but I know that if I was there for you more, umm maybe you would have had a lot more confidence in yourself, a lot more strength, not that you're not a strong person, and I just want to say I'm sorry for not being there for you growing up. You are a beautiful, amazing woman, and I am so proud of being your brother, and I know that now that we're a little bit older I am trying even harder to create and strengthen our relationship because I feel like you've had ten years of me being not the best big brother to you, and I want you to know that I will always be there for you. And, yeah, so, I love you, bye.” **This apology received the following coder-rated scores: Remorse M=4.67; Acknowledgment of violated rules and norms M=6.00; Compensation M=0
Participant #34 “I'm really sorry for hooking up with someone else on Valentine’s day, and, even though it wasn't my fault and he went in for it and I was not into it and shoved him away, and like it wasn't mutual, we shouldn't have been that close to each other in the first place, and I'm sorry that it ever happened because I didn't enjoy it and it shouldn't have happened.” 114
** This apology received the following coder-rated scores: Remorse M=1.67; Acknowledgment of violated rules and norms M=4.33; Compensation M=0