Emotions and the Self: Depression and Identity ... - Wiley Online Library

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doi: 10.1111/tsq.12085

The Sociological Quarterly ISSN 0038-0253

EMOTIONS AND THE SELF: Depression and Identity Change Alicia D. Cast* University of California, Santa Barbara

Bridget K. Welch Western Illinois University

Emotions hold a central place in sociological understandings of the self, both as a facet of identity management and as an outcome of self-processes. We extend identity theory and research on emotions by suggesting that emotion may be another source of identity change and examine this using a longitudinal sample of newly married couples, focusing on person identities and depression. We find that individuals’ identities change to become consistent with others’ views. We also find that the more depressive symptoms that individuals experience, the more negative their identities. The identity meanings that change, however, are different for men and women.

INTRODUCTION The sociology of emotions has experienced a rapid growth in the last 30 years. Much of this growth has occurred within the larger framework of symbolic interactionism and the study of the self. This research has represented both an explicit and an implicit challenge to what some have argued to be an almost exclusive emphasis on cognition in the study of the self (Farberman 1989; Boyns 2007). This is not to say that emotions have not been important to literature on the self. Indeed, emotions have been a critical element in much, if not all, research devoted to understanding a variety of selfprocesses. Historically, however, much of this research has conceptualized emotions as a by-product of more “important” self-processes. More recent research has given emotion a central place in theorizing about the self and interaction (e.g., Kemper 1978; Heise 1979; Hochschild 1983; Stryker 2004; Stets and Burke 2005; Burke and Stets 2009). In general, this research has conceptualized emotion in one of two ways: as something that is “managed” in the construction of a particular self or identity in interaction (e.g., Hochschild 1983; Thoits 1985) or as an outcome of self and identity processes (and/or other social processes) (e.g., Kemper 1978; Tesser 1986; Burke 1991; Heise 2007; Burke and Stets 2009).1 These two avenues of research have been critical to understanding what kinds of social processes produce what kinds of emotions (and when), as well as an understanding of how emotions are socially constructed and managed in interaction. While such research may implicitly

*Direct all correspondence to Alicia D. Cast, Department of Sociology, University of California, Santa Barbara, 3005 SSMS Building, Santa Barbara, CA 93106-9430; e-mail: [email protected] The Sociological Quarterly 56 (2015) 237–266 © 2015 Midwest Sociological Society

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Emotions and the Self

Alicia D. Cast and Bridget K. Welch

suggest emotion as a force that shapes interaction (see Stryker 2004), research that directly examines emotion as a force that actively, independently, and directly shapes the interaction process has been limited.2 In this article, we contribute to research that is beginning to address this gap in the literature (e.g., Lawler 2001; Hallett 2003; Stets and Osborn 2008). As part of the larger process of social interaction, emotions should not only be seen as something that are an outcome or a “managed” part of interaction but something that individuals bring into interaction with them and that have the potential to shape that interaction (Stets 2010). We suggest that emotions have the ability to shape a person’s understanding of the definition of the situation, including his or her own understandings of self. We develop this idea using insights from social psychological research that conceptualizes the self as a control system (e.g., affect control theory [ACT] and identity theory [IT]). For both theories, emotions and moods (Burke 2004a) are primarily conceptualized as outcomes of identity processes. More specifically, emotions are viewed as signals that indicate to an actor how well the self (and others) are performing within a particular situation (Smith-Lovin and Robinson 2006). In order to further develop the idea that emotions have the potential to influence the self (e.g., Stryker 2004; Heise 2007; Stets and Osborn 2008), we utilize IT to discuss how self-meanings (identities) are changed. We then draw on insights from ACT and psychological theories to discuss how emotions may be part of the identity change process. In doing so, we extend IT to include emotions as another possible source of identity change. In this article, we examine the relationship between an emotion (depression) and an individual’s identity (person identity) among a longitudinal sample of newly married couples. Previous research with these data have examined cognitive sources of identity change (e.g., reflected appraisals) (Cast and Cantwell 2007). In addition to these established relationships, we also include an investigation of emotional sources of identity change by examining the effects of a common emotion (depression) on identity change. In brief, if individuals utilize emotional states to make self-assessments, individuals who experience the negative emotion of depression should come to see the self more negatively over time.

DEPRESSION Depression encompasses a wide range of negative emotional experiences ranging from a temporary sense of “feeling down” (often in response to specific events in one’s life) to a long-term, severe, and potentially life-disrupting sense of hopelessness and despair (Shaver and Brennan 1990; Gurung 1999; Rubin 2000). Emotionally, individuals feel “deeply unhappy” (Norcross et al. 2003) and experience a loss of interest or pleasure in daily activities, fatigue or loss of energy, feelings of worthlessness, and diminished ability to concentrate, among other symptoms (American Psychiatric Association 2000). 238

The Sociological Quarterly 56 (2015) 237–266 © 2015 Midwest Sociological Society



We focus on depression for several reasons. First, and most importantly, depression is an emotion that is directed at the self, reflecting dissatisfaction with one’s ability to achieve individually held desires and wishes (Higgins 1987). It is, thus, likely to be related to individuals’ self-assessments compared with emotions that are other-directed (like anger) (Stets and Burke 2005; Burke and Stets 2009). Second, depression is one of the most common mood disorders diagnosed in the United States (Rubin 2000). Third, clinical research suggests that depression is developed and maintained through a variety of cognitive distortions that affect individuals’ assessments of themselves and their lives (e.g., Beck 1976; Gotlib and Krasnoperova 1998; Stewart et al. 2004; Riskind and Alloy 2006). This research suggests that emotions have the potential to shape our understanding of situations, including our understandings of who we are in interaction. It is important to note that most of the research on depression is focused on clinical populations. Our objective here is not to understand how chronic, severe depression affects individuals’ assessments of themselves. Our objective is to examine how an emotion (such as depressed feelings) may be utilized by the self as an important source of information about who the self is. In doing so, we suggest that, much like clinical populations, the general public utilizes their emotional state as one possible source of information in interaction—thus, we suggest that the same sorts of theoretical mechanisms are involved, albeit to a lesser degree (see Thoits 1985 for a similar argument). DEFINITIONS Before laying out our theoretical argument, distinctions between terms such as emotion, affect, and mood need to be made as they are often used interchangeably (Robinson, Smith-Lovin, and Wisecup 2007). Within sociology, the term affect refers to “any evaluative (positive or negative) orientation toward an object” (Robinson et al. 2007:181). It is thought of as representing one of three major dimensions of meaning (Osgood, Suci, and Tannenbaum 1957). Like affect, emotions are generally conceptualized along a positive/negative continuum, although there are other important dimensions to emotions as well (see Turner and Stets 2005). The term emotion refers to how individuals feel within a particular situation. Emotions involve both a physiological element as well as a cognitive element. The cognitive element reflects the cultural labels that individuals apply to the different physiological responses they experience that make the emotions meaningful to the individual (Robinson et al. 2007). Moods are more general than emotions in that they are likely to be cross-situational and longer in their duration (Burke 2004a; Robinson et al. 2007). Moods are less likely than emotions to be associated with a particular situation or event (Thoits 1989). As we are primarily interested in depression, the question becomes whether it is appropriate to frame depression as an emotion or a mood. Depression can be both an emotion (in terms of being short term) and a mood (being more diffuse and lasting months or longer) (MacKinnon and Goulbourne 2006). The longitudinal nature of The Sociological Quarterly 56 (2015) 237–266 © 2015 Midwest Sociological Society

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our data would suggest that we are examining moods rather than emotions per se, but we draw upon and extend our research into the emotions literature for the following reasons. First, emotions and moods are rarely distinguished in much of sociology leading to difficulties in distinguishing between emotion and mood processes in theoretical and empirical findings. Second, a series of emotional experiences can develop into long-term mood states (Collins 1990). Thus, it is reasonable to draw on research on emotions to discuss the possible long-term effects that short-term emotions may have through mood states. PREVIOUS RESEARCH Emotion as Outcome of Identity Processes: IT and ACT There are two predominant social psychological theories that utilize control theories to understand self and interaction: IT and ACT. While similar in many respects, there are a few important distinctions between the two theoretical perspectives. Below, we discuss each of the two theories in turn and how each would predict the experience of depression as an outcome of control processes. We first discuss IT and its prediction of how failure to verify person identities would result in negative emotions (such as depression). Second, we review ACT’s main elements and explain how its predictions for depression are contrary to those of IT.3 According to IT, an identity is a set of meanings about the self as a particular kind of person (person identities), as a role occupant (role identities), or as a member of a group (group identities). Individuals are motivated to act in ways that maintain consistency between meanings in the identity (the identity standard) and meanings in the social situation (reflected appraisals, social comparisons, and self-attributions). If meanings in the social situation do not match meanings contained in the identity standard, individuals experience distress and work to minimize the discrepancy through meaningful behavior in the situation (Burke 1991). The cycle of “action → situation → perception continue[s] until this discrepancy between perceptions and the identity standard are eliminated” (Burke 2004b:575). From this perspective, individuals are assumed to prefer feedback that is consistent with identity standards. According to Swann (1990), individuals prefer consistent feedback (even if it is negative) because it provides a sense of existential security to the individual. Because of this, feedback that is either more positive or more negative than the identity standard is equally distressful to the individual (Burke and Harrod 2005). In this article, we focus on person identities. Person identities reflect the set of meanings that individuals hold for themselves as unique individuals. Often these reflect culturally recognized characteristics that individuals have internalized as their own (Burke 2004c; Burke and Stets 2009:125). Like role and group identities, the meanings contained in person identities serve as standards within the identity control system. As such, individuals attempt to maintain these identities through the verification process described above. While these self-meanings are derived from the wider culture, these identity standards reflect the “essence or core” (Burke 2004c:9) of the individual and 240




consequently are more important to verify than other identities (see, for example, Stets 1995). As person identities are more idiosyncratic in nature, verification “leads to increased feelings of authenticity, that is, one who is able to be who one really is” (Burke 2004c; Burke and Stets 2009:125). This makes it a “master identity” with high levels of both salience and commitment (Burke 2004c). As person identities are high in commitment and salience, failure to verify will lead to an intensely negative valiance emotion such as depression4 (Burke 1991; Cast 2004; Burke and Harrod 2005; Burke and Stets 2009). Thus, following from an IT perspective we hypothesize that: Hypothesis 1a: A discrepancy between individuals’ identities and others’ views will be associated with more depressive symptoms. Hypothesis 1b: Discrepancies in a positive or negative direction will affect the experience of depressive symptoms to the same degree. The attempt to control meaning is also at the core of ACT. According to ACT, individuals work to maintain meanings in interaction to confirm fundamental sentiments (the referent) in the situation. According to this theory, people are not motivated to confirm self-meanings; they are motivated to maintain the meanings within the situation— meanings that may or may not reflect the self. Each component of the situation (actor, behavior, object, setting, emotion, traits, etc.) has fundamental sentiments attached to it, reflecting three dimensions of meaning: evaluation (good-bad), potency (powerfulweak), and activity (fast-slow). These fundamental sentiments are assumed to be widely shared within a culture and are essentially the set of meanings to be maintained in interaction. Like IT, ACT suggests that actors are motivated to construct events to verify these fundamental sentiments. While IT emphasizes possible discrepancies between identity standards and situational perceptions (input), the concept of deflection in ACT serves a similar purpose, and serves as a signal that something is wrong in the system.5 Within ACT, the emotions experienced are determined by both the transient impressions (the feelings generated by the specific situation) in an interaction and how these feelings differ from cultural meanings generating the deflection in the interaction (Averett and Heise 1988). When there is no deflection (i.e., transient impressions match the fundamental sentiments of an identity), the resulting emotion is solely determined by the fundamental sentiments of the identity. In other words, a person not experiencing any deflection will experience an emotion that is as good/bad, powerful/powerless, slow/fast as is his or her identity. Positive identities are associated with positive emotions and negative identities with negative emotions. For example, characteristic emotional states for newlyweds include optimistic, jubilant, overjoyed, or cheerful. When fundamental sentiments are not confirmed, the nature of the deflection becomes important. Like IT, ACT suggests that individuals experience negative emotions when transient impressions are more negative than fundamental sentiments. The Sociological Quarterly 56 (2015) 237–266 © 2015 Midwest Sociological Society

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Unlike IT, ACT suggests that when the situational meanings are more positive than the fundamental sentiments, individuals should experience more positive emotions. In other words, persons who receive feedback that they are more attractive than they believe themselves to be will feel pretty good about it (see Stets 2003). While exact emotion predictions depend upon the actor, behavior, and object in an interaction, two general hypotheses consistent with ACT can be derived: Hypothesis 2a: Positive discrepancies will be associated with fewer depressive symptoms. Hypothesis 2b: Negative discrepancies will be associated with more depressive symptoms. IDENTITY CHANGE Within both systems, individuals can respond to discrepancies in a variety of ways. First, they can change their behavior in order to alter perceptions such that they become more consistent with identity standards (e.g., Stets 1997; Robinson 2007). Second, they can change others’ views so that the opinions or views of others about who the self is match their own identity standards (e.g., Cast, Stets, and Burke 1999; Cast 2003a). Last, individuals can alter identity standards such that they become more consistent with social perceptions (Burke 1991, 1996, 2006). It is the last process that we focus on here. Cognitive Sources of Identity Change Much of the research on identity change has focused on the cognitive processes by which individuals become aware of how they are viewed by others (see Burke and Stets 2009 for a review). Through the processes of role taking (Mead 1934), the looking-glass self (Cooley 1902), and reflected appraisals (Kinch 1963), individuals are thought to adopt others’ views in order to create consistency between identity standards and perceptual input. Indeed, research finds that identity standards change in response to the views of others, becoming more consistent with others’ views (Cast et al. 1999; Cast 2003a; Cast and Cantwell 2007). Thus, consistent with other research, we hypothesize that: Hypothesis 3a: When there is a discrepancy between individuals’ identity standards and others’ views of the self, individuals’ identity standards will shift to become more consistent with others’ views. As previously discussed, most control theories of the self assume that inconsistency between identity standards and input from the social environment produces distress regardless of whether the feedback is more positive (a positive discrepancy) or more negative (a negative discrepancy) than identity standards. Indeed, some empirical research supports this (e.g., Swann et al. 1990; Cast and Burke 2002; Burke and Harrod 242




2005). Given that individuals are motivated to alleviate the distress that results from inconsistency between feedback and identity standards (Burke 1991, 1996), positive and negative discrepancies should be equally influential in changing identity standards. Hypothesis 3b: Individuals’ identity standards will change equally in response to positive and negative discrepancies. Other self-theories would suggest, however, that positive feedback would produce greater change in identity standards because of the motivation to self-enhance. These perspectives suggest that only negative feedback is distressing to individuals (Tesser 1986, 1988; Robinson 2007). For example, Stets and colleagues (Stets 2003; Stets and Ascencio 2008; Stets and Osborn 2008) find that distress only occurred when an underevaluation occurred; overevaluations produced positive emotions. This work suggests that that positive feedback may be incorporated into the self more quickly than negative feedback because it satisfies both consistency and enhancement motives. Consequently, it is possible that identity standards will change more in response to positive feedback from others than in response to negative feedback from others. Thus, we propose the following contrasting hypothesis: Hypothesis 3c: Positive discrepancies will produce greater change in individuals’ identity standards than negative discrepancies. It is important to note here that previous research has found that status not only affects identity change and verification (Stets 1997; Cast et al. 1999; Cast 2003a, 2004; Stets and Cast 2007; Burke 2008) but also individuals’ self-views (e.g., Rosenberg and Pearlin 1978; Gecas and Seff 1990), what emotions are experienced because of changes in status (e.g., Kemper 1978, 1984), and levels of depression (e.g., Mirowsky and Ross 1986). We do not offer hypotheses regarding status as it is not central to our theoretical question. Because status is likely to be correlated with levels of depression and identity meanings, however, we do control for it in our analysis. EMOTION AS A SOURCE OF IDENTITY CHANGE While cognitive sources of identity change (i.e., reflected appraisals, the looking-glass self, etc.) have a long history in sociological social psychology, less attention has been paid to other mechanisms by which individuals come to understand who they are, including other possible sources of identity change. IT posits a largely cognitive process in which the discrepancy between inputs into the system and system referents (identity standards) are the source of change in identity standards—the negative emotion experienced simply motivates that change. It does not have an effect on the nature of the change in identity standards. Some research, however, has suggested other possible sources of identity change. For example, individuals’ assessments of their behavior in interaction may provide The Sociological Quarterly 56 (2015) 237–266 © 2015 Midwest Sociological Society

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information to individuals as to who they are (e.g., Bem 1972; Blumstein 1991; Cast 2003b). Similarly, we suggest that emotion, in addition to cognition and behavior, may also serve as an important source of information to individuals as they come to an understanding of who they are in interaction. The idea that emotion influences interaction can be seen in other areas of social psychological research. In this research, sociologists consider the ways in which emotion can affect cognition (e.g., Lawler and Yoon 1993, 1996; Lawler 2001; Stets and Osborn 2008). The implication of this research is that emotion should not simply be conceptualized as an outcome of social interaction, but also something that individuals bring into interaction with them and subsequently influences the course of that interaction, including individuals’ understandings of self and other. While sociologists may agree with psychologists that emotion and the self are reciprocally related, attention to the way in which emotions serve as a source of information to the self, by indicating who and what type of person the self is, is limited in actual empirical research (Stryker 2004). One exception to this is Thoits’s (1985, 1990) research on emotional deviance. Combining the emotion management literature (Hochschild 1979, 1983) and labeling theory, Thoits argues that when individuals experience emotions that are nonnormative for enacted roles, they may come to self-define as mentally ill. In brief, Thoits (1985) suggests that one way to think about emotional disorders is as the outcome of unsuccessful emotional management. Individuals who are unable to successfully present normative emotional reactions may come to see these emotional reactions as symptomatic of an emotional disorder. As a result, they may come to label themselves as mentally ill and in need of treatment. Indeed, Karp (2006) suggests that one of the issues that those with mental illness struggle with is whether the emotions that they experience (or do not experience) as a result of taking medication to treat their illness reflects their “true self.” While Thoits (1985:245) uses the example of emotional disorders to make her point, she suggests that these processes should also apply to “normal” conforming behaviors or what Beck (1991:370) would refer to as “normal adaptive processes.” Thus, while still emphasizing the role of cognition (in terms of the cognitive labeling of emotions), both Thoits (1985) and Karp (2006) suggest that that emotional experience can result in the redefinition of the self.6 Other research in psychology supports the idea that emotion can lead to changes in identities. Two such forms are of interest to us here. The first area of research examines moods and emotions as a source of information (e.g., Schwarz and Clore 1983, 2007; Clore and Pappas 2007). Combining this research with ACT provides logic to suggest how emotions can operate as input within an identity control system. The second has to do with the way that mood disorders distort cognitive processes, ultimately affecting what information becomes attended to (e.g., Beck 1976; Abramson, Melansky, and Alloy 1989; Riskind and Alloy 2006). We discuss each in turn. Affect-as-Information and ACT Emotions have been suggested to be one source of information to individuals as they assess situations. This is known as the affect-as-information hypothesis (Schwarz and 244




Clore 1983, 2007; Clore and Huntsinger 2007). This perspective maintains that judgments are made by individuals asking themselves, “How do I feel?” in relation to an attitude object. Emotions and moods are presumed to directly affect what cognitions are formed by indicating what judgment individuals should make about an attitude object (Ottati and Isbell 1996; Isbell and Wyer 1999; Gasper and Clore 2000; Clore and Huntsinger 2007). In short, if individuals feel positive about an attitude object, they are likely to utilize this information (this emotion or mood) to evaluate the object positively. The object is more likely to be evaluated negatively if emotions about the object are negative.7 The type of mood (positive or negative) a person is in affects the nature of the cognition (positive or negative). In general, there is agreement that “happy moods predict more positive judgment than sad moods” (Schwarz and Clore 2007:390). Individuals, thus, appear to have an affect heuristic that aids them in assessing situations and objects in situations. The question becomes, “Do affective influences operate the same way on identity?” (Clore and Pappas 2007:336). In other words, can emotions and moods create a change in persons’ identities the same way that cognition can? Using insights from ACT (Heise 1979; Smith-Lovin and Heise 1988; MacKinnon 1994), Clore and Pappas (2007) suggest that emotions and moods can act as an affect heuristic for individuals who are making self-assessments. According to ACT, actors cognitively evaluate the situation to develop the definitions that direct behavior. At the same time, emotions also directly affect what cognitions occur in terms of influencing how the situation is defined. For example, if a person is originally acting in a situation where she defines the other as “friend” but an event reveals that her friend is angry, the behavior suggested for the following event will be based on the affective meanings attached to “angry friend.” The theory begins with an initial definition of the situation. Emotions can alter this definition suggesting that emotions do influence cognitions. Yet, with its focus on the overall definition of the situation and emphasis on cultural meanings, it is beyond the scope of ACT to theorize whether these modifications become incorporated into individuals’ self-meanings (Smith-Lovin and Robinson 2006). Clore and Pappas (2007) attempt to make the jump from change in the overall meaning of the situation to change in meanings of the self through affect-asinformation. To do so, they utilize recent unpublished research by Pappas to suggest that experienced emotions can alter how people see themselves. In this research, individuals who felt “strong and excited” after watching a horror film rated themselves as less anxious than others. In other words, individuals changed their own self-views as a result of the emotions experienced. Depression and Changes in Self-Meaning Another way that psychologists have examined how emotions affect cognition is by examining how emotions affect information processing (attention, memory, recall, attributions) (Forgas 1995). For some mood disorders, such as depression and anxiety, the presence of biased information processing is viewed to be both a cause and an The Sociological Quarterly 56 (2015) 237–266 © 2015 Midwest Sociological Society

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outcome of the disorder (Nolen-Hoeksema 2000). On the one hand, some individuals seem to be more “cognitively vulnerable” to depression because of how they respond to stressful events. For example, those who are likely to attribute negative life events to internal, stable causes are more vulnerable to depression than those who are more likely to attribute negative life events to external, unstable causes (Beck 1976; Abramson et al. 1989; Fresco, Alloy, and Reilly-Harrington 2006; Riskind and Alloy 2006). When individuals experience a stressful event, previously existing knowledge structures and schemas affect the meanings that individuals attribute to these events and thus their emotional response (Riskind and Alloy 2006). On the other hand, the emotional state of depression also seems to support the negative cognitive style that makes a person vulnerable to depression. Depressed individuals tend to have uncontrollable negative thoughts (Gotlib and Krasnoperova 1998). They tend to pay more attention to negative information and are more likely to recall negative information (Williams et al. 1997; Joorman et al. 2005). Depressed individuals also tend to ruminate over stressful events, thereby extending the negative emotional experience (Nolen-Hoeksema 2000). The negative cognitive processes that place an individual at risk for depression by influencing their response to stressful conditions have been linked to negative life events (Fresco et al. 2006; Safford et al. 2007). Thus, depression not only places an individual at risk directly by affecting cognitive processes, but also indirectly by facilitating events that could potentially cause a recurrence of the depressive episode (Joiner, Wingate, and Otamendi 2005). What we are left with are several possible mechanisms that suggest that emotions (and depression, in particular) would result in changes in identity meanings. The combination of affect-as-information with ACT suggests that emotions can result in transient impressions that are at odds with fundamental sentiments—motivating a change in how the self is defined. Furthermore, non-normative emotional experiences (such as suffering from depression) would result in a (negative) redefinition of self-views. Finally, research also suggests that emotions can alter how individuals process information, making them more likely to recall particular kinds of information as well as attend to particular kinds of information. More specifically, depression leads individuals to experience more negative thoughts and to pay more attention to those thoughts, potentially affecting the degree to which those thoughts become influential in individuals’ understandings of themselves, others, and social situations more broadly. All of these possible mechanisms suggest the following hypothesis: Hypothesis 4: The more depressive symptoms individuals experience, the more negative their identity standards will become. DATA The data for this research were from a study investigating marital dynamics during the first two years of marriage. All couples registering for a marriage license in two midsize communities in Washington State in 1991 and 1992 that met the project criteria 246




(first marriage, no children, and age 18 and over) were contacted and asked to participate in the study. Out of the 574 couples that were contacted, 207 participated in all three data collection periods. Couples were interviewed shortly after their marriage (t1), a year later (t2), and a year after that (t3). Each data collection period involved a 90-minute face-to-face interview, four one-week daily diaries kept at four-week intervals by each respondent, and a 15-minute videotaping of couples’ conversations as they worked to resolve an area of disagreement. Analyses presented here utilized data from the face-to-face interviews. Couples participating in the study were similar to other couples marrying for the first time during the early 1990s in the United States. For example, the mean age of women and men marrying for the first time in the United States was age 24 and 26, respectively (Vital Statistics 1995). This was not significantly different from the mean ages in the present sample. The couples in this sample were also educationally similar to other couples marrying at this time. Nationally, the mean level of education for husbands and wives marrying for the first time was two years of college (Vital Statistics 1995). The mean educational level for the couples in this sample was “some college.” The racial composition of this sample was also similar to the racial distribution in Washington State: 89 percent white, 3 percent black, and 9 percent other minorities. On a national scale, this sample also looked like first-marrieds; nationally, firstmarrieds were 85 percent white and 13 percent minority (Vital Statistics 1995). Attrition from the first year to the second year was 15 percent with an additional 4.2 percent attrition from the second year to the third. Couples withdrew for personal reasons (e.g., relocation, time constraints) and administrative reasons (e.g., difficulty in scheduling). After two years, 206 couples remained involved in the project. Couples who dropped out of the study after the first or second year were younger (p < 0.01), less educated (p < 0.01), and of lower socioeconomic status (p < 0.05). Because of missing data for some cases, the analyses presented here were based on 192 couples for whom complete data were available.8 Variables Identities Individuals possess attitudes toward the self on a variety of different dimensions. As previously discussed, person identities reflect individuals’ understandings of themselves as unique and distinct from others (Stets 2006; Burke and Stets 2009), typically involving particular characteristics or traits that individuals see themselves possessing. As such, they are likely to be relevant across groups and situations. Furthermore, person identities that are important to individuals are likely to be those that reflect socially desirable characteristics. And, like all social objects, they have a positive/ negative valence dimension to them that may potentially link them to emotion. In an effort to link a more general emotion or mood, like depression, with general views about the self that were likely to be important to the individual, we examined how the individual viewed the self on the following five dimensions: intelligence, physical appearance, understanding, friendliness, and likability. All five of these The Sociological Quarterly 56 (2015) 237–266 © 2015 Midwest Sociological Society

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characteristics can be thought of as highly valued, positive characteristics within American society, linking them with the positive and negative dimension of emotion. Specifically, each respondent was asked: “How would you rate yourself on . . .” Responses ranged from 0 (low) to 100 (high). Respondents were also asked to rate their spouse on the same dimensions using the same scale. Respondents’ self-ratings (identity) and their spouses’ ratings are presented in Table 1. Discrepancy Identity verification occurs when there is correspondence between an identity standard and a person’s perception as to how others view him or her in that identity. In this study, we had a measure of self-ratings on the five characteristics mentioned above; however, we did not have a measure of the person’s perception of their spouse’s evaluation of him/her along these five dimensions. We only had the spouse’s actual ratings of the person along these five dimensions so we use these actual ratings as a proxy. This may introduce some measurement error but it is likely to be minimal because these are intimate relationships and one should be able to expect a high correlation between a person’s perception of their spouse’s view and their spouse’s actual view (see Kinch 1963). Therefore, while the discrepancy measure was not exact, it should be a close approximation. Similar measures have been used successfully elsewhere (e.g., Burke and Stets 1999; Cast and Burke 2002; Cast 2003a; Burke and Harrod 2005). We then created measures that indicated a positive or negative discrepancy between individuals’ identities and others’ views. A positive discrepancy reflected that a spouse’s view was more positive than an individual’s identity and a negative discrepancy reflected that the spouse’s view was more negative than the individual’s identity. Specifically, a positive discrepancy measure was created by determining whether individuals’ identities were more positive or more negative than their spouses’ ratings of them for each of the five characteristics. A value of 1 was assigned if spouses’ views were more positive than individuals’ identities and a value of 0 was assigned if spouses’ views were equal to or less than individuals’ identities. A negative discrepancy measure was created by determining whether spouses’ views were more positive or more negative than individuals’ identities. A value of −1 was assigned if spouses’ views were more negative than individuals’ identities and a value of 0 was assigned if spouses’ views were equal to or more positive than individuals’ identities. The distribution into positive discrepancy categories and negative discrepancy categories for each of the identities can be seen in Table 2.9 Depression In order to effectively distinguish between the affective and cognitive effects of emotion on identity change, a measure of depression that emphasizes the affective or symptomatic aspects of emotion was important. Therefore, we utilized a measure of depression designed to measure depressive symptoms among the general public, the Center for Epidemiologic Studies Depression Scale (CES-D) (Radloff 1977). Respondents were asked how many days during the week they had felt the following ways: “have trouble 248



11.44 9.58

13.29 12.10

15.52 13.10

12.78 15.35

11.82 12.15

77.65 81.81 4.16*

69.84 82.21 12.37*

75.99 83.35 7.36*

79.20 84.83 5.63*

80.07 86.66 6.59*

79.18 86.24 7.06*

79.22 84.34 5.13*

75.80 80.18 4.38*

70.02 82.81 12.79*

78.10 82.97 4.87*

12.74 12.21

12.96 14.74

16.04 14.35

12.44 11.46

10.70 8.51

SD

78.98 85.56 6.58*

78.8 83.53 5.01*

74.41 78.18 3.77*

70.68 81.43 10.75*

78.97 83.04 4.07*

Mean

t3

*Two-tailed test: identity and spouse view were significantly different p < 0.05.

Intelligence Identity Spouse view Mean difference Physical appearance Identity Spouse view Mean difference Understanding Identity Spouse view Mean difference Friendliness Identity Spouse view Mean difference Likable Identity Spouse view Mean difference

Mean

Mean

SD

t2

t1

Husbands (N = 192)

13.48 11.47

14.01 13.59

16.40 13.75

13.00 10.87

10.92 8.88

SD

TABLE 1. Means and Standard Deviations for Identity and Spouse View Measures

79.36 85.98 6.62*

80.23 85.82 5.58*

81.02 82.38 1.36

68.82 83.04 14.22*

73.94 78.60 4.66*

Mean

t1

12.27 10.80

13.23 11.82

12.75 13.22

14.36 11.91

12.90 11.27

SD

79.27 85.54 6.27*

79.83 84.73 4.90*

80.67 79.33 1.34

67.89 82.42 14.54*

75.88 78.79 2.91*

Mean

t2

13.59 12.24

13.85 13.23

12.17 15.35

14.68 12.37

10.84 10.53

SD

Wives (N = 192)

79.06 85.57 6.51*

80.33 85.22 4.89*

80.57 81.16 0.59

67.71 81.88 14.17*

76.86 79.46 2.60*

Mean

t3

12.04 10.94

13.11 10.86

12.61 14.79

14.42 12.81

10.53 11.07

SD

Alicia D. Cast and Bridget K. Welch Emotions and the Self

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TABLE 2. Distribution of Discrepancy Measures Husbands (N = 192) t1 N Intelligence Positive discrepancy Spouse view more positive (1) Spouse view equal to or negative (0) Negative discrepancy Spouse view more negative (−1) Spouse view equal to or positive (0) Physical appearance Positive discrepancy Spouse view more positive (1) Spouse view equal to or negative (0) Negative discrepancy Spouse view more negative (−1) Spouse view equal to or positive (0) Understanding Positive discrepancy Spouse view more positive (1) Spouse view equal to or negative (0) Negative discrepancy Spouse view more negative (−1) Spouse view equal to or positive (0) Friendliness Positive discrepancy Spouse view more positive (1) Spouse view equal to or negative (0) Negative discrepancy Spouse view more negative (−1) Spouse view equal to or positive (0) Likable Positive discrepancy Spouse view more positive (1) Spouse view equal to or negative (0) Negative discrepancy Spouse view more negative (−1) Spouse view equal to or positive (0)

t2 N

Wives (N = 192)

t3 N

t1 N

t2 N

t3 N

95 97

100 92

98 94

96 96

84 108

100 92

51 141

39 153

49 143

48 144

65 127

55 137

132 60

143 49

130 62

145 49

145 47

147 45

30 162

26 166

23 169

24 168

20 172

23 169

111 81

97 95

104 88

88 104

81 111

95 97

48 144

66 126

72 120

61 131

76 116

70 122

107 85

109 83

101 91

108 84

103 89

107 85

45 147

48 144

51 141

49 143

45 147

46 146

108 84

120 72

101 91

108 84

115 77

114 78

41 151

42 150

45 147

40 152

40 152

41 151

keeping your mind on what you were doing,” “feel that everything you did was an effort,” “feel lonely,” and “feel sad.” Responses range from 0 (“not at all”) to 7 (“seven days”). Items were analyzed using principal components factor analysis; one strong factor emerged. Items were summed and a high score indicated high levels of depression. Individual items and factor loadings for the depression measure can be found in Table 3. Alpha reliability for this measure was 0.82 at t1, 0.85 at t2, and 0.90 at t3.10 250




TABLE 3. Principle Components Analysis of Depression Measure (N = 384) Factor loadings Items Feel bothered by things that don’t usually bother you? Not feel like eating; your appetite was poor? Feel that you could not shake off the blues even with help from your family and friends? Have trouble keeping your mind on what you were doing? Feel depressed? Feel that everything you did was an effort? Feel fearful? Sleep restlessly? Talk less than usual? Feel lonely? Feel sad? Feel you could not get going? Eigenvalue Alpha reliability

t1

t2

t3

.46 .35 .72

.62 .43 .78

.68 .65 .83

.58 .77 .60 .42 .51 .57 .57 .74 .61 4.15 .82

.60 .81 .71 .50 .50 .59 .64 .72 .65 4.90 .85

.69 .83 .74 .65 .59 .69 .72 .80 .64 6.09 .90

Control Variables Status Status was measured by combining measures of occupational status and education. The education item was an ordinal measure and ranged from 1 (“no formal education”) to 13 (“a graduate degree”). For the measure of occupational status, respondents were asked to describe the work they did at their current job. If they were not currently working, they were asked to describe their previous job. Responses were then coded according to the Socioeconomic Index (Stevens and Cho 1985). Education and occupational status were significantly correlated over time (r = 0.52 at t1, r = 0.45 at t2, and r = 0.53 at t3). The measures of education and occupational status were standardized and then averaged to create an overall measure of status.11 Analysis To examine our hypotheses, we estimated our model using three-stage least squares. A variety of techniques might have been used to analyze these data; we chose three-stage least squares for the following reasons. First, it was a “full-information” method; all equations were estimated simultaneously, which is necessary when variables from one equation affect variables in other equations as was the case with our analysis. Second, the three-stage least squares method controlled for likely interdependence between observations in the system of equations by assuming that error terms in the equations were correlated (StataCorp 1999; Greene 2000). Third, because three-stage least squares estimates a system of equations, we were able to compare effects across equations within the system. The Sociological Quarterly 56 (2015) 237–266 © 2015 Midwest Sociological Society

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Our analysis was conducted at the couple level, including separate equations for husbands and wives. Given possible gender differences in the emotional lives of men and women (see Simon and Nath 2004), this allowed us to directly compare whether these processes operate similarly for men and women. This type of analysis also allowed us to directly compare whether these effects were similar across the five identities. Some research has suggested that the importance of these individual identities may vary for men and women (see Bosson and Swann 2001). We were interested in the change in our dependent variables (identities and depression). Therefore, each equation included a lagged value for each of our dependent variables, allowing us to assess the impact of positive and negative discrepancies on changes in depression as well as the effects of changes in depression on identities. The effects of depression on identities, the effects of positive and negative discrepancies on depression, and the effects of positive and negative discrepancies on identities were included as lagged effects (t2 values were regressed on t1 values, t3 values were regressed on t2 values). This allowed us to examine the effects of these variables at previous time points on subsequent changes in depression and identities. Identities tend to be stable (Burke and Cast 1997) and thus, it may take some time for these effects to be seen. Model Constraints In an effort to create as parsimonious a model as possible, we examined several preliminary models. Before discussing the specific results presented in Table 4, we discuss these preliminary models and constraints in our final model. We first examined whether stability coefficients (effects of t–1 on t for measures of depression and identities) in the model were the same over time. To do this, we compared the overall fit of a model in which the coefficients were allowed to vary across time to the overall fit of a model in which coefficients were constrained to be equal over time. If the fit of the model changed significantly when constraints were added, then we could conclude that these effects were not significantly different over time. These preliminary analyses suggested that the stability effects for our measures of depression and identities were significantly different across time (chi-square = 81.05, df = 12, p < 0.05). Thus, these effects were not constrained to be equal to one another in the final model. We next examined whether our hypothesized effects were significantly different across time. Following the logic described above, we compared a model in which hypothesized effects were constrained to be equal to one another to a model in which these coefficients were allowed to vary. These preliminary analyses suggested that the effects of depression on identity (chi-square = 15.67, df = 10, p > 0.05), the effects of identity discrepancies on identities (chi-square = 14.48, df = 20, p > 0.05), and the effects of the discrepancy on depression (chi-square = 23.92, df = 20, p < 0.05) were not significantly different across time. Thus, we constrained these effects to be equal across time. We then examined whether the hypothesized effects were the same across characteristics. Preliminary analyses indicated that the stability coefficients were significantly different across items (chi-square = 57.07, df = 24, p > 0.05). Furthermore, preliminary 252




TABLE 4. Effects of Discrepancy on Identity Change and Spouse View and Effects of Depression on Identity Change Husbands (N = 192) Identity t3

t2 Intelligence t1 t2 Positive discrepancy t1 Positive discrepancy t2 Negative discrepancy t1 Negative discrepancy t2 Depression t1 Depression t2 Status t2 Status t3 Physical appearance t1 t2 Positive discrepancy t1 Positive discrepancy t2 Negative discrepancy t1 Negative discrepancy t2 Depression t1 Depression t2 Status t2 Status t3 Understanding t1 t2 Positive discrepancy t1 Positive discrepancy t2 Negative discrepancy t1 Negative discrepancy t2 Depression t1 Depression t2 Status t2 Status t3 Friendliness t1 t2 Positive discrepancy t1 Positive discrepancy t2 Negative discrepancy t1

.57*

Wives (N = 192)

Depression t2

t3

.26* .60*

.08*

t2

t3

.68* ns

.08* .08*

Identity

ns .08*

.08*

ns

ns −.13*

ns ns

ns

ns .94*

.08*

.59* ns

.08* .08*

ns .08*

.28* .42*

.08* ns

ns .08*

.08* ns

ns ns

.08*

ns

−.11*

ns

−.11*

ns ns

ns ns

ns

.26* .70*

.08*

.57* ns

.08* .08*

ns .08*

.18* .74*

.08* ns

ns .08*

.08* ns

ns

ns ns

.08*

ns

ns ns

ns

ns

ns ns

ns

.23** .64**

.08**

.50** ns

.08** .08**

ns ns

ns −.11*

.48**

ns .08*

ns

ns

.50*

t3

ns .77*

.08*

−.11*

.58*

t2

.08* ns

Depression

.08** ns

ns

.19** .55** ns .08**

.08**


ns ns

253



TABLE 4. Continued Husbands (N = 192) Identity t3

t2 Negative discrepancy t2 Depression t1 Depression t2 Status t2 Status t3 Likable t1 t2 Positive discrepancy t1 Positive discrepancy t2 Negative discrepancy t1 Negative discrepancy t2 Depression t1 Depression t2 Status t2 Status t3 Depression t1 Depression t2 Status t2 Status t3

Wives (N = 192)

Depression t2

.08**

t3

Identity t2

t3

ns

−.11**

t2

t3

.08**

ns

ns −.11**

ns

−.09**

ns ns

.47**

Depression

ns

.24** .56**

.08**

.48** ns

.08** .08**

.08** ns

ns .08**

.16** .47** ns .08**

.08** ns

−.16**

ns ns

.08**

ns

ns −.16**

ns

ns

.15** ns

ns .47**

.65** −.50**

.41**

.44** ns

−.18**

ns .12**

−.16**

*p < 0.05 two-tailed test. **p < 0.05.

analyses also indicated that the effects of verification on identity change (chisquare = 21.57, df = 16, p < 0.05) and the effects of positive and negative discrepancies on depression (chi-square = 25.23, df = 16, p < 0.05) were not significantly different across characteristics. However, preliminary analyses also indicated that the effects of depression on identity change were significantly different across characteristics (chi-square = 24.22, df = 8, p < 0.05). We also examined whether the coefficients in our model were the same for men and women in the model. Preliminary analyses suggested that the stability coefficients for men and women were significantly different (chi-square = 33.62, df = 10, p < 0.05). Therefore, in our final analyses, we allowed these coefficients to vary across men and women. When looking to see if the hypothesized effects were the same for men and women, preliminary analyses indicated that the effects of positive and negative discrepancies on identity change were not significantly different for women and men (chi-square = 0.44, df = 2, p > 0.05) and that the effects of positive and negative discrepancies on depression were not significantly different for women and men (chi-square = 0.16, df = 2, p > 0.05). 254




As discussed above, the effects of depression on identity change were found to be significantly different from one another in previous analyses. As a result, we next examined whether they were the same for men and women, even though depression influenced identity change differently depending on the characteristic being examined. These preliminary analyses indicated that the effects of depression on identity change were not only different across characteristics but that these coefficients were also significantly different for men and women (chi-square = 20.72, df = 5, p < 0.05). Therefore, the effects of depression on identity change were allowed to vary across women and men. Next, we examined whether positive and negative discrepancies had the same effect on identities and depression. Preliminary analyses indicated that the effects of positive and negative discrepancies on identity change were not significantly different (chisquare = 0.03, df = 1, p > 0.05) and that positive and negative discrepancies also similarly affected change in depression (chi-square = 2.97, df = 1, p > 0.05). Therefore, in the final model, the effects of positive and negative discrepancies were constrained to equally influence changes in identities and to equally influence changes in depression. Thus, in the final model, the effects of discrepancies on depression and identity change are constrained to be equal across time; however, the effects of depression on identity change are allowed to vary across characteristics and vary for men and women. RESULTS Stability of Identities and Depression Turning to the results presented in Table 4, we see that the identities examined (intelligence, physical appearance, understanding, friendliness, and likable) were very stable over time (effects of t–1 on t). This was consistent with other research (Burke and Cast 1997; Cast 2003a, 2003b). Effects of Discrepancy on Depression Looking at the effects of positive and negative discrepancies on depression, the results in Table 4 disconfirmed Hypotheses 1a (a discrepancy between individuals’ identities and others’ views will be associated with more depressive symptoms) and 1b (discrepancies in a positive or negative direction will affect the experience of depressive symptoms to the same degree). Results also disconfirmed Hypotheses 2a (positive discrepancies will be associated with fewer depressive symptoms) and 2b (negative discrepancies will be associated with more depressive symptoms). Unlike other research, we found that a discrepancy between individuals’ identities and others’ views was not related to depression (β = ns, p > 0.05). Effects of Discrepancy on Identity Change Hypothesis 3a suggested that when there was a discrepancy between identities and the views of others, identities would change to become more consistent with others’ views. This would reflect identity change as a result of the primarily cognitive processes The Sociological Quarterly 56 (2015) 237–266 © 2015 Midwest Sociological Society

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discussed earlier (e.g., reflected appraisals, etc.). The results in Table 4 supported this hypothesis. When others’ views were more positive than individuals’ identities (positive discrepancy), individuals’ identities changed to become more positive (β = 0.08, p < 0.05). When others’ views were more negative than individuals’ identities (a negative discrepancy), individuals’ identities became more negative (β = 0.08, p < 0.05).12 As noted previously, the effect of a positive discrepancy was not significantly stronger than the effect of a negative discrepancy on changes in identities (chi-square = 0.03, df = 1, p > 0.05). This confirmed Hypothesis 3b (individuals’ identity standards change equally in response to positive and negative discrepancies) but disconfirmed Hypothesis 3c (positive discrepancies produce greater change in individuals’ identity standards than negative discrepancies). Effects of Depression on Changes in Identities In Hypothesis 4, we hypothesized that emotions would also influence identity change. Specifically, we hypothesized that the more individuals experienced depressive symptoms, the more negative their identities would become over time. We find some support for this hypothesis. Our results suggest that this varies according to the particular characteristic examined and sex category. Looking first at the results for husbands, we see that the more depressed he is at t–1, the less intelligent (β = −0.11, p < 0.05), friendly (β = −0.11, p < 0.05), and likable (β = −0.16, p < 0.05) he sees himself the following year. Among wives, Hypothesis 4 only is confirmed for attractiveness. The more depressed wives are at t–1, the less they perceive themselves as physically attractive in the following year (β = −0.11, p < 0.05). DISCUSSION AND CONCLUSION While research on emotions in sociology has emphasized how emotions are managed within interaction and are outcomes of a variety of social processes, there has been limited research on how individuals utilize their emotions to develop an understanding of that interaction. In the research presented here, we offer one possible way to incorporate emotions as an input, or source of information, into the IT model of the self. Consistent with previous research (Cast and Cantwell 2007), a discrepancy between an individual’s identities and his or her spouse’s views leads to change in identity. In addition, we find that positive and negative feedback equally influence identity change, further supporting self-consistency motivations (see also Burke and Harrod 2005; Cast and Cantwell 2007) rather than self-enhancement motives (e.g., Tesser 1986). Most importantly, our research also suggests that emotions shape the identities that individuals bring into interaction with them. While we did not find that a discrepancy between individuals’ identities and others’ views is related to depression (as IT would predict), we do find that the negative emotion of depression affects individuals’ identities. Depression, as an indicator of discrepancy, leads individuals to reassess the self in ways that are consistent with the negative emotion they experience. Consequently, individuals who were depressed at previous points in time came to have more negative 256




identity meanings (albeit along separate dimensions for men and women) at later time points. Thus, this research finds that emotions have the potential to influence the self through their effects on individuals’ identities. That different identities were influenced by depression for men and women was a bit surprising given that all five of these characteristics are generally socially valued. We offer two possible explanations for these findings. First, and most simply, research consistently finds that women experience more depressive symptoms than men (Simon and Lively 2010). Furthermore, research also notes that depressive emotions are normative for women but non-normative for men (Briton and Hall 1995; Kelly and Hutson-Comeaux 1999; Plant et al. 2000; Simon and Nath 2004). Given this, when men experience depressive emotion, they may view it as particularly telling about who they are. In contrast, the experience of depressive symptoms may be viewed as normative by women and thus not necessarily interpreted as reflective of who they are. Indeed, this would be consistent with Thoits (1985). Individuals who experience (or are unable to successfully manage) non-normative emotions may redefine the self. Other research finds that individuals displaying gender inconsistent emotions are believed to be more sincere (Huston-Comeaux and Kelly 2002) suggesting that others see the inconsistent emotion as a true reflection of that person. If others use gender normativeness to determine whether emotions expressed reflect “the truth,” it seems logical that individuals use similar criteria to evaluate the self when such emotions are experienced. Second, there may be gender differences in which person identity domains are affected by depression. As argued by Bosson and Swann (2001), the domains of meaning that are important to a particular identity depend upon the goal of that identity. For example, they argue that the goal of dating relationships is to “obtain and maintain the affections of the partner” making attractiveness a “highly relevant” domain for dating identities (2001:70). Previous research has identified the important domains for a variety of identities such as gender (Stets 1995; Stets and Burke 1996; Burke and Cast 1997; Burke and Tully 1977), college students (Burke and Reitzes 1980), spousal identities (Burke and Stets 1999), and moral identities (Stets and Carter 2006). Here we are discussing person identities and did so through measuring five domains (intelligence, physical appearance, understanding, friendliness, and likability). Of these five domains, physical appearance may be the one that is highly relevant for women while intelligence, likability, and friendliness are all highly relevant for men. It is also possible that women (and men) have domains not included in this analysis that would have also been changed in response to these depressive symptoms. It was also surprising that we did not find that discrepancies between individuals’ identities and others’ views produce depression, especially as others have found such a relationship, even with the same data set and measures (see Burke and Harrod 2005). We think there are three possibilities to consider. The first is our small sample size and the number of parameters that we estimate in our model. We simply may not have the degrees of freedom to allow us to find significant effects for those that are smaller in size in our data. Second, and in contrast to Burke and Harrod (2005), we have The Sociological Quarterly 56 (2015) 237–266 © 2015 Midwest Sociological Society

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conceptualized these processes as occurring as lagged effects. We think, however, that given the stability of identities (and the subsequent slow nature of identity change) that this is an appropriate conceptualization. Third, it is also possible that the dichotomous measure of discrepancy did not allow us to pick up on changes in levels of depressive symptoms. We compared the model here to a model with similar constraints and a continuous measure of discrepancy and found only a small change in coefficient size (−0.017 to −0.0008). Regardless of the reason, it does suggest that identity theorists might need to begin to theorize a bit more extensively about how these different processes should be modeled. One limitation of our study is our inability to directly examine the exact mechanisms through which depression affects identities. We have suggested that depressive symptoms directly affect identity meanings although it is unclear how. It is possible that emotions themselves operate as a type of control system with a certain type of emotional response expected of certain types of people. As discussed previously, this type of process would explain the sex category differences we see here. This would also be consistent with ACT. For example, the person who considers himself or herself to be a “success” who suddenly finds that he or she is unhappy (a non-normative emotion) may begin to wonder if a “truly” successful person should experience such emotional lows because “successful” people should be happy. The discrepancy between the person’s experienced emotion and “emotional standard” leads him or her to come to define himself or herself actually as an “unsuccessful” person despite possessing other identity markers such as a home, a car, a stable job, and so on. Much like in the identity model presented by Burke (1991, 1996), it is not the input itself (the emotion) that is the source of change in the identity standard, but it is the discrepancy between these “emotional standards” for that identity. Future research should examine in more detail the processes by which individuals utilize emotions to define the self. Some may suggest that it is inappropriate to utilize research on mood disorders to develop models of general social functioning. Like others (e.g., Thoits 1985; Beck 1991; Flett, Vrendenburg, and Krames 1997; Beutler, Clarkin, and Bonger 2000), we believe that the more extreme emotional processes that are described by research on mood disorders can provide insights into more general social processes that are typically of interest to sociologists. What may first appear as cognitive distortions of those struggling with mood and personality disorders may, in actuality, provide sociologists with insights into not only the importance of incorporating emotions into our models of the self and human behavior more broadly, but also how it is that we might do that. By examining these processes among a nonclinical sample, we by no means suggest that the experiences of those struggling with mood and personality disorders are somehow not serious—clearly they are. What we would suggest, however, is that these more serious examples and experiences of mood disorders can provide us with insights into more general social processes that describe how individuals make sense of themselves and their world. While we utilize ACT to provide insights into how emotions can become an input for IT, it is beyond the scope of this manuscript to address the debate between the 258




relative usefulness of ACT and IT (e.g., see Smith-Lovin and Robinson 2006; Burke and Stets 2009; Owens, Robinson, and Smith-Lovin 2010). From our perspective, IT is useful and productive for examining self-meanings (identities) and a wide variety of outcomes, including emotional outcomes. ACT, in contrast, is concerned with how individuals manage broader cultural meanings in the situation but not necessarily individual identity meanings. ACT does, however, provide insight into how emotions can shape the overall definition of the situation that then have the potential to shape selfmeanings as we have discussed here in this manuscript. Therefore, while we utilize the understanding of self-meanings and the theoretical processes underlying identity change developed by IT, the logic for our ideas about how emotions might change selfmeanings draws on ACT—along with several psychological theories. Most clearly, our research can be understood as an extension of IT by recognizing the unique contributions that ACT has to offer the study of emotions. We believe that our use of both theoretical traditions points to a need for theorists in these areas to be open to greater theoretical integration and believe that this is an important step in that direction.

NOTES 1

Not all research will fall cleanly into these two broad approaches as we have categorized them. We emphasize these as distinct only to make the point that emotion as a precursor or defining element of interaction has received limited attention. 2 We note that there are some exceptions to this. For example, Robinson et al. (2007) suggest that a major area of research in affect control theory is the study of how emotions signal particular identities. However, it seems reasonable to state that this has been studied much less often than research that examines emotions as outcomes of interaction. 3 Given space constraints and because the predictions we develop here have been examined elsewhere (Cast and Cantwell 2007), we present a brief account of these theoretical processes, allowing us to more fully develop our central ideas about how emotion affects identity. 4 While there has been recent theorizing about which emotions will be experienced as a by-product of different discrepancies (see Stets and Burke 2005), heretofore, IT research simply has predicted that any discrepancy (whether positive or negative) will result in a negative emotion. Given the lack of specific predictions about which emotions and moods will be experienced as a result of different involved identities and/or types of feedback, it is consistent with the theory to predict that discrepancy will result in depressive symptomology. 5 Affect control theory is a formalized mathematical model. For example, a simple interaction (with only actor, behavior, and object) has deflection calculated as the sum of squared differences between the fundamental sentiments and transient impressions for the actor, behavior, and object. Presenting all the equations for predictions is beyond the scope of this article (see Heise 1992). 6 It is important to note that Thoits (1985) does not say this redefinition will always occur. She argues that identities may be qualified or modified—as in a “crazy mother”—or a new identity could be formed (such as adopting a “mental patient” identity). We would suggest, however, that emotion is still causing changes in meanings associated with these identities. The Sociological Quarterly 56 (2015) 237–266 © 2015 Midwest Sociological Society

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7

This process is similar to what clinical psychologists refer to as “emotional reasoning.” Individuals reason based on the emotions that they experience. Research supports such reasoning for both depression and anxiety disorders but that it may also serve as adaptive, protective mechanisms for the self (Morren, Muris, and Kindt 2004). 8 For a more complete description of the study and the data collection process, see Tallman, Burke, and Gecas (1998). 9 Ideally, these discrepancy measures would be left in continuous form in order to retain as much information as possible. We chose to use dichotomous measures, however, for the following reasons. First, because large discrepancies should produce larger changes in identity and depression, any effects found here would be conservative; the overall pattern of results should be the same. Second, we seek to extend research on identity change conducted by Cast and Cantwell (2007) to include emotional sources of identity change; therefore, we decided to keep our analysis as similar as possible to the model in that analysis. Last, even though information is lost when categorical variables are used, the interpretation of the coefficients is more straightforward. Given the complexity of our analysis (24 individual equations estimated simultaneously), we decided that simpler was better. 10 Among the individual depression scale items, we were missing 19 pieces of data (e.g., a respondent would respond to only 11 out of the 12 items). In order to retain as many cases as possible for analysis, we imputed these values based on other responses to the items within that same year. 11 It is likely that there are other factors beyond status that are correlated with depression. By using longitudinal data and examining changes within the individual, our analyses control through fixed effects for factors that do not vary over the time period of our study but still may contribute to depression. 12 As might be expected, these coefficients were similar to those reported by Cast and Cantwell (2007) who used these data solely to examine the effects of positive and negative discrepancies on changes in identities.

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