Emotional Reactivity to Daily Events in Major and Minor Depression

Transcription

1 Journal of Abnormal Psychology 2011 American Psychological Association 2011, Vol. 120, No. 1, X/11/$12.00 DOI: /a Emotional Reactivity to Daily Events in Major and Minor Depression Lauren M. Bylsma, April Taylor-Clift, and Jonathan Rottenberg University of South Florida Although emotional dysfunction is an important aspect of major depressive disorder (MDD), it has rarely been studied in daily life. Peeters, Nicolson, Berkhof, Delespaul, and devries (2003) observed a surprising mood-brightening effect when individuals with MDD reported greater reactivity to positive events. To better understand this phenomenon, we conducted a multimethod assessment of emotional reactivity to daily life events, obtaining detailed reports of appraisals and event characteristics using the experience-sampling method and the Day Reconstruction Method (Kahneman, Krueger, Schkade, Schwarz, & Stone, 2004) in 35 individuals currently experiencing a major depressive episode, 26 in a minor depressive (md) episode, and 38 never-depressed healthy controls. Relative to healthy controls, both mood-disordered groups reported greater daily negative affect and lower positive affect and reported events as less pleasant, more unpleasant, and more stressful. Importantly, MDD and md individuals reported greater reductions in negative affect following positive events, an effect that converged across assessment methods and was not explained by differences in prevailing affect, event appraisals, or medications. Implications of this curious mood-brightening effect are discussed. Keywords: major depression, minor depression, experience-sampling method, Day Reconstruction Method, emotional reactivity Major depressive disorder (MDD) is a prevalent and debilitating disorder characterized by deficient positive affect (PA) and excessive negative affect (NA), as assessed by a variety of questionnaire and interview measures (Clark, Watson, & Mineka, 1994). Although MDD features persistent affective disturbance by definition, surprisingly few studies have collected data on emotion in MDD in daily life settings. This is puzzling because, as discussed later, understanding how individuals with this disorder react to events in their daily lives is a critical aspect of descriptive psychopathology and one with obvious clinical relevance. One advantage of examining emotional reactivity in naturalistic settings is that this provides a more ecologically valid estimate of an individual s emotional functioning. Another advantage of naturalistic data collection methods is that experience-sampling method (ESM) approaches enable dense and repeated sampling of daily life (also known as ecological momentary assessment); repeated sampling is more reliable than single-point assessments and can capture dynamic patterns of reactivity to the environment (Csikszentmihalyi & Larson, 1987), especially when used with This article was published Online First January 10, Lauren M. Bylsma, April Taylor-Clift, and Jonathan Rottenberg, Department of Psychology, University of South Florida. Jonathan Rottenberg was supported by National Institute of Mental Health Grant MH The authors express their appreciation to Bethanne Bower, Lindsay Brauer, Amy Godin, Jennifer Greene, Shantal Henriques, Bethany Morris, and Casey Williams for their help in conducting this study, as well as John Ferron for his statistical guidance on the multilevel analyses. Correspondence concerning this article should be addressed to Jonathan Rottenberg, Department of Psychology, University of South Florida, PCD 4118G, 4202 East Fowler Avenue, Tampa, FL jrottenb@cas.usf.edu new statistical methodologies (i.e., multilevel modeling) that are well suited for repeated assessments (see e.g., Nezlek, 2001). One issue in this line of work is that there is no gold standard for studying emotional functioning in everyday life. Not only have depression researchers used different naturalistic data collection methods to study emotions, but data from these investigations have not been well integrated. For example, one small literature uses daily diary studies, which involve retrospective reports that reflect an average estimate or end-day total on the measure of interest (i.e., overall affect, daily activities). Another small literature uses ESM approaches, which typically examine the short-term dynamics of reported emotion over time using computerized or paperand-pencil approaches (Myin-Germeys et al., 2009; Ebner-Priemer & Trull, 2009). In the sections that follow, we review the small body of work with each method and propose a study that attempts to harness the strengths of each. Daily Diary Studies of Emotion and Depression Earlier studies of emotion in everyday life used daily diary methods (see e.g., Hammen & Glass, 1975; Larson, Raffaelli, Richards, Ham, & Jewell, 1990; Lewinsohn & Graf, 1973; Lewinsohn & Libet, 1972; Nezlek, Hampton, & Shean, 2000) to gather data from depressed participants, who typically provided end-ofday estimates of daily activities, social interactions, or mood. A common focus in many daily diary studies has been on examining the number of positive daily events occurring and the relationship between the number of events and depressed persons overall mood for the day. Depressed patients engagement in a greater number of positive activities has been associated with better overall daily mood (Lewinsohn & Libet, 1972). However, although some findings have suggested that depressed individuals engage in fewer positive activities than do healthy individuals (Lewinsohn & 155

2 156 BYLSMA, TAYLOR-CLIFT, AND ROTTENBERG Graf, 1973), others studies do not find such differences (Lewinsohn & Libet, 1972). Importantly, there is evidence that depressed persons PA may be tied more closely to how pleasant activities are appraised than the absolute amount of pleasant activities (Hammen & Glass, 1975). This finding underscores the importance of appraisals, which have been found to be valuable in predicting emotional reactivity in healthy individuals (see e.g., Marco, Neale, Schwartz, Shiffman, & Stone, 1999; van Eck, Nicolson, & Berkhof, 1998) but have rarely been examined in predicting emotional reactivity in mood-disordered samples. Extant work, for example, has shown that depressed individuals do not differ in the absolute number of social interactions in which they engage but do differ in the perception of these interactions, typically rating them as less positive or enjoyable (see e.g., Larson et al., 1990; Nezlek et al., 2000). Additionally, depressed individuals, relative to controls, have been found to be more likely to rate positive events as more stressful (Peeters, Nicolson, Berkhof, Delespaul & devries, 2003) and to respond with greater increases in NA as subjective stress increases (Myin-Germeys et al., 2003). In sum, a number of findings have suggested that perception or appraisal of daily activities may be as important as or more important than objective event characteristics and that it may be useful to examine the dose response relationship between appraisals and depressed persons emotional responses to daily events. ESM Studies in Depression Researchers have used the strengths of ESM strategies to understand diverse facets of depression. Its dense sampling capabilities have, for example, been used to examine affective instability (see e.g., Jahng, Wood, & Trull, 2008), a construct related to emotional reactivity, which reflects overall mood variability over time (not tied to specific triggers). For example, Peeters et al. (2006) found that individuals with MDD exhibited more variable NA relative to healthy controls. ESM studies are also well suited to examine emotional reactivity to specific types of daily life events. Basic research clearly establishes that even relatively minor pleasant and unpleasant daily life events can reliably induce short-term emotional reactions (see e.g., David, Green, Martin, & Suls, 1997; Gable, Reis, & Elliot, 2000; Marco et al., 1999; van Eck et al., 1998). Studies of daily life events have potential for elucidating variables that influence the naturalistic course of depression. Hankin, Fraley, and Abela (2005) found that greater depressogenic daily negative cognitions about stressors predicted increases in daily depression symptoms. Studies of daily life events can also potentially elucidate how MDD treatments work; for example, they could be used to understand the efficacy of behavioral activation, a component of cognitive behavioral therapy based on the idea that depressed individuals can be taught to seek out positive reinforcements in their daily lives, resulting in increased PA (see e.g., Jacobson, Martell, & Dimidjian, 2001). Despite the potential payoffs of using ESM to study reactivity to everyday life contexts, we know of only one such ESM study comparing diagnosed MDD and healthy control groups (Peeters et al., 2003). In this sample, MDD participants reported blunted NA and PA changes in response to negative life events, and NA responses persisted longer in MDD individuals. Unexpectedly, when responding to positive events, MDD individuals reported greater reductions in NA and larger increases in PA relative to controls. In other words, although depressed individuals affective responses to negative events were blunted relative to healthy individuals, their affective responses to positive events were actually enhanced. Nezlek and Gable (2001) also found unexpected mood brightening in nonclinical samples of college students; students who were high on depression symptomatology reported greater positive emotional reactivity to positive daily events (as indexed by increases in self-esteem). Bridging the Gap Between Daily Diary and ESM Assessments of Emotion Only modest to moderate correlations have been noted between daily diary studies and ESM measures of affect (e.g., kappa estimates for mood shifts ranged from.001 to.03; Solhan, Trull, Jahng, & Wood, 2009). The relatively low correspondence may be due to retrospective biases or memory errors that are common in a standard implementation of the daily diary method (see Pohl, 2004). Importantly, the Day Reconstruction Method (DRM; Kahneman, Krueger, Schkade, Schwarz, & Stone, 2004) has been proposed as a means to record daily emotions and events, while mitigating these biases and errors. The DRM is a self-report survey instrument that enables individuals to systematically reconstruct events and emotions experienced the previous day (Kahneman et al., 2004). Empirical findings with the DRM in healthy populations have thus far tended to replicate findings established with ESM methods (e.g., PA and well-being; Kahneman et al., 2004). Perhaps most encouraging, the first study to examine the correspondence between the DRM and ESM in a healthy sample found between-subject correlations ranging from 0.58 to 0.90 for affect intensity and variations over the day (Dockray et al., 2010). Thus, early findings indicate that the DRM is valid and that use of this instrument may help to bridge the gap between daily diary and ESM methodologies in the context of depression. To our knowledge, the DRM method has never been applied to a clinical sample. The Current Study Our primary objective was to test the hypothesis that depressed individuals would exhibit greater improvement in affect in response to positive events compared with healthy controls (Nezlek & Gable, 2001; Peeters et al., 2003); we used a stronger design with multiple naturalistic sampling methods to potentially provide convergent validity. In this case, replication and extension are particularly important because greater mood brightening in depression is somewhat counterintuitive and also varies from patterns found in laboratory studies (e.g., depressed individuals are typically less reactive to positive material; Rottenberg, Gross, & Gotlib, 2005; see Bylsma, Morris, & Rottenberg, 2008, for review). We also had two secondary goals: (1) we sought to model the influence of subjective event appraisals on daily affect in a depressed sample and (2) we aimed to model a wider range of depressive symptomatology than previous studies had through the inclusion of a group with subthreshold depression, or minor depression (md). This study had three critical features to achieve these goals.

3 EMOTIONAL REACTIVITY TO DAILY EVENTS 157 First, in order to achieve a more comprehensive hypothesis test, we used two complementary naturalistic sampling methods: the computerized ESM and the DRM. ESM allows respondents to document their thoughts, feelings, and actions within the context of daily life by capturing information about experiences as they occur (Christensen, Barrett, Bliss-Moreau, Lebo, & Kaschub, 2003). The advantages of ESM include its ability to capture information in the moment over multiple assessments in the course of the day, making it less vulnerable to retrospective recall bias. Computerized ESM has an added advantage over paper-and-pencil methods because of its ability to verify completion of reports at a specific time. The DRM is a self-report survey instrument that enables participants to systematically reconstruct events and emotions experienced the previous day (Kahneman et al., 2004). The DRM structure for reconstructing experiences from the previous day uses a series of contiguous episodes, a format that is designed to help minimize recall biases (Belli, 1998; Kahneman et al., 2004; Robinson & Clore, 2002). The two methods use slightly different approaches to reconstructing emotional experience and events: Whereas ESM can capture data at only the time points that it is programmed to assess, the DRM is designed to obtain complete coverage of the day, including duration of daily activities, while not interrupting the flow of daily life (i.e., the entire day, rather than a sampling of time points, can be assessed), thus providing complementary information about daily life (see Wilhelm & Grossman, 2010). To examine the role of appraisals on daily affect and whether mood disorders influence the dose response relationship between appraisals and affect, we examined to what extent the magnitude of affective reactions to daily life events covaried in each group with appraisals of pleasantness, unpleasantness, stressfulness, feelings of control, expectedness, and importance. Subjective ratings on these appraisals have demonstrated a relationship with emotional responses in healthy individuals (see e.g., Siemer, Mauss, & Gross, 2007; van Eck et al., 1998). Third, in order to sample the full range of depressive symptoms and shed light on an important variant of depression, we included a group of individuals with md according to the Diagnostic and Statistical Manual of Mental Disorders (4th ed.; DSM IV; American Psychiatric Association, 2000) in the study sample, in addition to persons with current MDD and healthy controls with no history of psychopathology. Evidence to date indicates that md results in impairments that are similar to, though less severe than, those observed in MDD (see e.g., Cuijpers, de Graaf, & van Dorsselaer, 2004; Howland et al., 2008). Surprisingly, there is virtually no research on the emotional characteristics of md (as defined by DSM criteria). Method Participant Recruitment and Selection Participants were recruited from fliers and online forum postings in and around the Tampa Bay community. Individuals responding to research ads via and phone were initially screened over the phone to determine potential eligibility. Screening items were based on key diagnostic questions from the Structured Clinical Interview for DSM IV TR Axis I Disorders, Research Version, Patient Edition With Psychotic Screen (SCID-I/P W/PSY SCREEN; First, Spitzer, Gibbon, & Williams, 2002). A total of 502 potential participants were initially screened by telephone. Of those individuals, 271 were invited into the lab to complete the diagnostic interviews. Clinical psychology doctoral students conducted the interviews; final diagnoses for study inclusion were based on the SCID administration. Of those who completed the initial telephone screening, 107 individuals failed to attend their appointment and were not able to be rescheduled or decided they were no longer interested in participating. A total of 164 participants completed the SCID. Participants in all groups were excluded from the study if they had any of the following: history of a major head injury, hearing impairment, diagnosis of bipolar disorder, substance abuse occurring within 6 months prior to entry into the study, or any history of primary psychotic symptoms, as assessed by the telephone screen and the SCID. Of those participants who completed a SCID, approximately 57 were excluded for failing to meet inclusion or exclusion criteria, leaving 107 eligible participants who were invited to participate in the ESM and DRM protocols. Participants deemed eligible on the basis of the initial SCID interview were invited to begin the ESM protocol or to return to the lab within 3 weeks to complete the ESM and DRM. Seven individuals of the 107 were excluded for failing to complete the ESM and DRM due to scheduling difficulties. Two more participants were not able to complete the ESM and DRM within 3 weeks of the initial SCID and had to be rescreened for the mood disorders module of the SCID; of these two, one was excluded for no longer meeting criteria for an md diagnosis. Included participants who completed the study met criteria for MDD with a current episode (n 35) or md with a current episode (n 26) or had no past or present psychopathology (i.e., no history of any Axis I disorder as assessed by the SCID; n 38). Provisional DSM IV TR criteria recommend an absence of past episodes of MDD for an md diagnosis. To improve study feasibility, we loosened this criterion, and 31% of md participants experienced at least one major depressive episode (MDE) at least 8 weeks prior to onset of the md symptoms. Final participants were primarily women (77.8%), fluent in English, and between the ages of 18 and 55 years (mean age 28.3). The final sample approximated the ethnic distribution of the Tampa Bay area: 56.7% Caucasian, 13.5% African American, 6.7% Latino/ Hispanic, 4.8% Asian, 1.9% Native American or Native Hawaiian/ Pacific Islander, 1.0% Middle Eastern, 15.4% Other or Mixed. Groups were matched on age, ethnicity, gender, education level, income, and marital status (all ps.05 for Cramer V tests). Table 1 provides sample demographic characteristics by diagnostic group. Procedure Computerized ESM. The computerized ESM procedure was employed using Palm Pilots (Zire22) and the Experience Sampling Program (Barrett & Feldman Barrett, 2004). The ESM protocol began on a Monday and ended on a Friday, with data collection occurring Tuesday Thursday. Participants carried the Palm Pilot with them as they engaged in their daily activities over three weekdays (weekends were not used, in order to have a more homogenous sampling of days). Participants completed at least four practice assessments on the evening prior to the first ESM

4 158 BYLSMA, TAYLOR-CLIFT, AND ROTTENBERG Table 1 Demographic and Clinical Characteristics Characteristic MDD (n 35) md (n 26) Control (n 38) Age in years (SD) (9.42) (7.58) (8.55) Caucasian (%) Female (%) Education a (SD) 5.30 (1.73) 5.28 (1.67) 5.94 (2.06) Income b (SD) 5.30 (3.37) 4.39 (3.18) 6.41 (3.64) Married (%) Number of children (SD) 0.48 (0.94) 0.44 (0.86) 0.47 (0.92) BDI-II (SD) (9.71) (8.52) 2.41 (3.42) BAI (SD) (10.24) (9.19) 1.78 (2.01) Antidepressants (%) Psychotherapy (%) Comorbid anxiety diagnosis (%) Note. MDD major depressive disorder; md minor depression; BDI-II Beck Depression Inventory II; BAI Beck Anxiety Inventory. a Education was assessed on an 8-point scale, with higher numbers representing more education, with a score of 5 6 reflecting graduation from a 2-year or a technical college. b Income was assessed on a 12-point scale, with a score of 5 6 representing an annual income of between $25,000 and $34,999. sampling day. On each of the three days, the Palm Pilots were programmed to alarm 10 times a day semirandomly between 8:00 a.m. and 11:00 p.m. (approximately once every 1.5 hr). Participants were given 15 min to respond after the alarm, and if they did not respond in time, the questionnaire would disappear and be marked as missed. For each questionnaire, participants were first asked to report on their current mood and were then prompted to provide information about the context and nature of the most important emotional event that had occurred since their last report, similar to the procedure used by Myin-Germeys, Krabbendam, Delespaul, and van Os (2004). For each event, participants responded to a list of choices about what they were doing, the nature of the event, the location of the event, and with whom they were interacting. Next, participants provided affective ratings of the events (i.e., episodes). The entire questionnaire generally took less than 5 min to complete. After completion of the three ESM sampling days, participants returned to the lab to return the Palm Pilots and to complete the DRM assessment. The DRM. The DRM survey packet (Kahneman et al., 2004) was tailored so that the queries and response options mirrored those used in our ESM data collection while still following the general framework of Kahneman and colleagues (2004). The survey asked about the previous day, which corresponded to the third ESM day, to allow us to compare the data from the two sampling procedures. Participants returned to the lab to complete the DRM on the Friday of the ESM week, in order for the questions to correspond to Thursday, the last day of the ESM data collection. The DRM prompted participants to reconstruct the previous day by thinking of their day as a continuous series of episodes. For each episode, participants were asked to provide details about each event, including what they were doing, time of the episode, duration, and what their thoughts and feelings were during the episode. As in the ESM procedure, participants responded to an identical series of multiple-choice questions about the context of the events and provided ratings of their mood during the events and appraisal ratings of the events. The instructions for the DRM followed that of Kahneman and colleagues. Specifically, participants were asked to do the following: Think of your day as a continuous series of scenes or episodes in a film. Give each episode a brief name that will help you remember it (e.g., commuting to work, or at lunch with B). Write down the approximate times at which each episode began and ended. The episodes people identify usually last between 15 min and 2 hr. Indications of the end of an episode might be going to a different location, ending one activity and starting another, or a change in the people you are interacting with. 1 It is important to note that, although we made ESM and DRM reports as comparable as possible, there are necessarily slight differences in how an episode is defined in the ESM versus the DRM. Specifically, due to the nature of the data collection, the ESM represents a random sampling of episodes over the day (which may or may not be contiguous), whereas the DRM represents a continuous series of episodes reconstructed from memory. At the time of the DRM, participants also completed a state measure of NA and PA using the same mood items from the ESM and the DRM. Three participants were not able to return for their scheduled appointments on Friday and had to return on Thursday instead. These individuals DRM data covered Wednesday instead of Thursday. One additional participant was not able to return until Monday to return the Palm Pilot and did not complete the DRM. Measures Depression and anxiety severity. Participants completed the Beck Depression Inventory II (BDI-II; Beck, Steer, & Brown, 1996) and the Beck Anxiety Inventory (BAI; Beck, Epstein, Brown, & Steer, 1988) at the time of the DRM to provide measures of depression and anxiety severity. The BDI-II and the BAI are well-validated 21-item selfadministered scales, with higher scores representing greater severity of symptoms. Coefficient alphas for the BDI-II ( 1 Full instructions for the Day Reconstruction Method can be found at

5 EMOTIONAL REACTIVITY TO DAILY EVENTS ; Beck, Steer, Ball, & Ranieri, 1996) and the BAI (.92; Steer, Ranieri, Beck, & Clark, 1993) are high. PA and NA. State PA and NA were measured for each event recorded by the ESM and DRM methods, as well as in the lab at the beginning of the DRM session. Composite PA and NA scores were computed from the DRM and ESM data by summing the seven positive mood ratings of each episode for PA (talkative, enthusiastic, confident, cheerful, energetic, satisfied, and happy) and the seven negative mood ratings for each episode for NA (tense, anxious, distracted, restless, irritated, depressed, and guilty). The NA and PA mood adjectives were comparable to those used successfully in previous clinical ESM studies (see e.g., Barge-Schaapveld & Nicolson, 2002; Myin-Germeys et al., 2003; Peeters et al., 2003). Because the traditional approach to calculating internal consistency has been criticized for use in multilevel data (see Nezlek, 2007), we used a multilevel approach to calculate reliability estimates. Using the approach described by Nezlek and Gable (2001), we calculated the person-level reliability estimates, which confirmed that the scales had high internal consistency (multilevel reliability estimates all.90 for NA and PA). For the DRM data and the state laboratory assessment, each item was coded on a 7-point Likert scale ranging from 0 (not at all) to6 (very). For the ESM data, the Palm Pilots stored responses on an analog scale; participants slid a bar from not at all to very to correspond to their current feeling state, and responses were later converted into a 0 6 scale. Event contexts. Contextual information about each event recorded was obtained through identical multiple-choice questions for both the ESM and DRM methods. Information obtained included the type of activity participants were engaging in, the nature of the event, the location of the event, and information about with whom the participant was interacting (as described earlier). Participants selected options from a list of choices for each question and had the option of selecting more than one answer if applicable to the situation. Event appraisals and derivation of pleasant, unpleasant, and neutral events. For each episode in the DRM and the ESM, participants provided an appraisal indicating their subjective experience of pleasantness, unpleasantness, stressfulness, importance, expectedness, and feelings of control, using the same response format as used for NA and PA mood adjectives. The pleasantness and unpleasantness ratings were used to define the event valences; appraisals of stressfulness, importance, expectedness, and feelings of being in control were included to match those commonly found in the literature on appraisals and emotion experience (see e.g., Peeters et al., 2003; Siemer et al., 2007; van Eck et al., 1998). Pleasant, unpleasant, and neutral events were defined on the basis of the participants appraisals of the pleasantness and unpleasantness of each event. Following prior empirical work (Peeters et al., 2003) and theory (Watson, Wiese, Vaidya, & Tellegen, 1999) that focuses on reactions to relatively intense emotional stimuli, we coded pleasant events as events that were rated high on pleasantness ( 80/100 for the ESM data, 5/6 for the DRM data, approximately 1 standard deviation above the mean) and low on unpleasantness. Similarly, we coded unpleasant events as events rated high on unpleasantness and low on pleasantness. Events that were not rated high on pleasantness or unpleasantness were coded as neutral events. Event codings were nonoverlapping, such that an event could be categorized as only pleasant, unpleasant, or neutral. Ambiguous events (i.e., events coded high on both pleasantness and unpleasantness) were extremely rare ( 1%) and were not categorized. Objective event ratings. Finally, we also obtained objective ratings of the pleasantness and unpleasantness of events, on the basis of the written event descriptions provided by participants in the DRM data. These data were potentially useful in estimating to what extent groups may have had different thresholds for estimating events as pleasant or unpleasant (i.e., would mood-disordered persons rate events less pleasant than would objective observers?). Three trained research assistants independently coded pleasantness and unpleasantness on the basis of the participants written event descriptions from the DRM procedure using the same rating scales the participants used. The coders were blind to the group status of the participants event descriptions, and each coder rated event descriptions for approximately 50% of the participants (interrater reliability s.80). All DRM episodes were rated by two coders, and interrater reliability was calculated on the basis of the first five events of each participant. Statistical Analyses To estimate differences in NA and PA in response to daily events, we implemented hierarchical linear modeling using the HLM statistical software package Version 6.06 (Raudenbush, Bryk, & Congdon, 2004). HLM, also known as multilevel modeling or multilevel random coefficient modeling, is a variant of multiple regression and is appropriate for data sets with a multilevel structure, such as ESM data (see Nezlek, 2001; Schwartz & Stone, 1998). In our case, there are two levels of nesting: time points (Level 1) nested within individuals (Level 2). In this type of data, observations from the same individual are more similar than are observations from different individuals, resulting in nonindependent residuals. HLM is able to take this into account by estimating variance at multiple levels. HLM handles missing data points using a restricted maximum likelihood approach to estimate the variance covariance components; therefore, it is not problematic for there to be different numbers of reports for each individual (see Raudenbush & Bryk, 2002). Separate estimates are provided for fixed (significance tests of coefficients) and random (error variances associated with individual effects) effects for each level of the model. Separate models were estimated for NA and PA using the HLM. Initial models estimated overall differences in NA and PA with group (MDD or md vs. control) as a predictor. These were followed by the primary models of interest, which estimated group differences in NA and PA following positively and negatively valenced events. To estimate the impact of group status, two dummy-coded variables (MDD or md coded as 1 and controls coded as 0) were entered into the model. For event type, pleasant and unpleasant events were also entered as dummy-coded variables (with neutral events coded as 0). The models can be expressed as follows, where the dependent variable (Y) is NA or PA, pleasant event and unpleasant event are the Level 1 predictors, and MDD and md group status are the Level 2 predictors. The betas represent the parameter estimates, e is the Level 1 variance, and r 0,r 1,r 2 are the Level 2 random effects.

6 160 BYLSMA, TAYLOR-CLIFT, AND ROTTENBERG The Level 1 model is as follows: Y 0 1 (pleasant event) 2 (unpleasant event) e. The Level 2 model consists of the following: MDD 02 md r 0, MDD 12 md r 1, MDD 22 md r 2. and Finally, to examine factors that may be influencing group differences in emotional reactivity, a series of follow up analyses with additional Level 1 and Level 2 predictors were added to the models individually. Level 1 predictors (episode level) included dummycoded event type (i.e., pleasant, unpleasant, neutral) and grandmean-centered event appraisals (i.e., pleasantness, unpleasantness, stressfulness, importance, expectedness, in control). MDD and md group status were included as dummy-coded Level 2 (individual level) predictors. Because individual differences were expected, all intercepts and slopes were allowed to vary for Level 1 predictors (i.e., random effects were modeled). Dummy-coded variables were already centered around the 0 value, and all other Level 1 predictors were grand-mean-centered. Results The results are organized by the following structure: We first provide the clinical characteristics of our sample and information on missing data and noncompliance for the ESM and DRM data; second, we present multilevel models demonstrating the convergence between the overall ESM and DRM affective variables; third, we present the overall ESM and DRM event characteristics by group; fourth, several multilevel models are then presented, with parallel analyses for the DRM and ESM data, encompassing results for prevailing daily PA and NA and positive and negative emotional reactivity; fifth, we present multilevel analyses of group differences in event appraisals and conclude with an analysis of the dose response relationship between appraisal and affect by group. Clinical Characteristics of the Sample Of those with MDD, 76.5% were recurrent (i.e., had one plus a previous MDE) and 3% also met criteria for dysthymia (i.e., double depression). Concerning MDD subtypes, 39.4% were melancholic and 36.4% were atypical. Of those with md, 32% experienced at least one MDE in the past. Clinical characteristics of each group are listed in Table 1. Analyses comparing group differences in depression severity scores were in line with the diagnostic categorizations. A one-way analysis of variance (ANOVA) found expected group differences in BDI-II scores, F(2, 94) , p.001, such that MDD individuals had the highest depression severity scores, followed by md individuals and then control individuals ( p.001 for all comparisons). BAI scores also differed significantly between groups, F(2, 95) 46.50, p.001, such that MDD individuals and md individuals reported higher anxiety levels than did healthy individuals ( p.001), and MDD individuals reported higher anxiety levels than did md individuals ( p.01). Missing Data and Compliance A total of 100 participants completed both the ESM and DRM protocols. One additional person completed the ESM but was unable to complete the DRM. Two participants (both in the control group) were excluded from the ESM data for failing to complete at least five questionnaires (due to concerns about the validity of these participants data), and one person s ESM data was lost due to a technical problem. Three participants who were unable to complete the DRM on the Friday corresponding to the last ESM sampling day were excluded from the analyses directly comparing the ESM and DRM assessment methods. There were no differences in ESM protocol compliance across groups, and the mean number of completed reports was (SD 5.56) out of a possible 30 for the included participants. This compliance rate of 65% is comparable to, though somewhat lower than, that of other published ESM studies with clinical samples (see e.g., Myin-Germeys et al., 2004). This response rate is still respectable given that our protocol required response to ESM prompts within 15 min; most participants were employed or enrolled in school (86%), and we expected that timely responses to prompts would sometimes be impossible (i.e., while driving or during a business meeting or classes). ESM data included a total of 99 participants and 1,903 ESM episodes. However, 30 ESM episodes were discarded as invalid because participants selected the default option for all answers, leaving a total of 1,873 valid entries. For the DRM data, the number of reported episodes ranged from three to 30. Groups did not differ significantly on the number of reported episodes, with an overall mean of (SD 5.75) DRM episodes. In the multilevel DRM analyses, there were a total of 1,191 Level 1 (episode) and 100 Level 2 (individual) units. Did ESM and DRM Data Converge? Because one of our objectives was to conduct a multimethod assessment of emotion experience, we first examined whether the DRM and ESM data did in fact converge. Pairwise Pearson s correlations were computed between average daily PA and NA with the DRM data and the corresponding ESM data (from Day 3). These ratings were also compared with the single-point laboratory measure of PA and NA taken at the session in which participants completed the DRM. All correlations were significant and large in magnitude between the averaged NA and PA obtained from the ESM, DRM, and laboratory measure (rs for PA and for NA; all ps.001). In addition, multilevel analyses were conducted with assessment type (ESM 0, DRM 1) as a Level 1 predictor to examine the impact of assessment type on reported NA and PA. For both NA and PA, there was a significant effect of assessment type, such that average reported PA and NA were both somewhat lower for the DRM data compared with the ESM data: NA: B 61.15, t(98) 5.56, p.001; PA: B 25.64, t(98) 2.38, p.02. However, importantly, these effects did not interact with group status: NA: B 4.84, t(97) 0.45, p.65; PA: B 12.81, t(97) 1.15, p.25. The tau matrix values for assessment type were.29 for NA and.16 for PA, which represent the variance associated with assessment type. In sum, initial analyses suggested a high correspondence between the emotion data collected by the retrospective DRM and the online computerized ESM methods. Indeed, as we report next,

7 EMOTIONAL REACTIVITY TO DAILY EVENTS 161 nearly all significant findings involving group replicated across the two methods. Event Characteristics of the ESM and DRM Data Pleasant, unpleasant, and neutral events were defined on the basis of the participants pleasantness and unpleasantness ratings (frequencies presented in Table 2). There were significant group differences for the number of reported pleasant and unpleasant events that were consistent for the DRM and ESM data. Both the md and MDD groups reported fewer pleasant and more unpleasant events relative to controls ( p.05), though this effect was marginal for the md group in the DRM data ( p.1). Follow-up t tests revealed that the md and MDD groups did not significantly differ from each other on the proportion of reported pleasant and unpleasant events, and none of the groups differed from each other on the number of neutral events ( ps.05). To provide some basic descriptive information concerning the kinds of specific events to which participants were reacting, we report in Table 3 the percentages of event characteristics recorded in the ESM and DRM sampling (calculated within individual, then averaged by group), including information about the activity type, nature of the event, and interactions with others. Each variable was dummy-coded as 1 the item was selected for the event by the participant and 0 the item was not selected for the event. Percentages by group of each event characteristic are reported in Table 3. Due to the nonnormality of the proportional data, an arcsine transformation was used on the proportions of each event type for each individual for the purposes of group comparison. ANOVA analyses revealed that, overall, daily event characteristics were remarkably similar across groups, though a few differences were observed. In both the ESM and DRM data, both depressed groups reported fewer personal successes and more personal failures relative to healthy controls (all ps.05). Also, in both the ESM and DRM data, MDD individuals reported fewer goals accomplished, with the md group additionally reporting more blocked goals in the ESM data (all ps.05). In the DRM data, both depressed groups reported fewer positive social events, and md individuals reported more negative social events relative to controls (all ps.05). Multilevel Analyses of Prevailing Daily PA and NA Before testing our primary hypotheses, we first examined whether group status predicted PA and NA in the ESM and DRM data to establish a context for interpreting reactivity to pleasant and unpleasant events. The overall descriptive statistics by group are presented in Table 4. PA and NA were analyzed (separately) using multilevel models, which were unconditional at Level 1, with MDD and md group status as dummy-coded predictors entered uncentered at Level 2. For the ESM data, both depressed groups reported reduced daily PA relative to healthy controls: MDD: B 9.37, t(96) 7.08, p.001; md: B 8.55, t(96) 6.09, p.001, and the MDD and md depressed groups did not differ significantly from each other. Additionally, both depressed groups reported greater overall daily NA compared with healthy controls: MDD: B 14.05, t(96) 7.59, p.001; md: B 11.43, t(96) 7.59, p.001, and the MDD and md groups, again, did not differ significantly from each other. The results with the DRM data were comparable for both PA: MDD: B 10.03, t(97) 6.38, p.001; md: B 9.73, t(97) 5.70, p.001, and NA: MDD: B 12.03, t(97) 8.09, p.001; md: B 11.01, t(97) 6.66, p.001. Multilevel Models of Positive and Negative Emotional Reactivity to Everyday Life Events To test our main hypothesis, we conducted parallel multilevel analyses in the ESM and DRM data examining group differences in positive emotional reactivity and negative emotional reactivity to pleasant and unpleasant daily life events. Given the similar data structure, for both the DRM and ESM analyses, episodes (Level 1) were treated as nested within persons (Level 2). Importantly, overall results were consistent for both the ESM and DRM data analyses. The multilevel results of the overall analyses are presented in Table 5. Multilevel analyses of overall emotional reactivity. In order to examine the impact of group status on positive and negative emotional reactions in response to both pleasant and unpleasant emotional events, we added the dummy-coded variables pleasant event and unpleasant event to the multilevel model with PA and Table 2 Aggregated Mean Event Ratings by Group and Assessment Method DRM ESM Event rating Control md MDD Control md MDD Pleasant 4.07 (1.65) 3.30 (1.85) 3.37 (1.81) 3.53 (1.61) 2.53 (1.69) 2.81 (1.65) Unpleasant 1.26 (1.68) 2.16 (1.96) 2.05 (1.88) 1.53 (1.70) 2.89 (1.74) 2.77 (1.76) Stressful 1.41 (1.79) 2.54 (2.12) 2.57 (1.91) 1.82 (1.81) 3.39 (1.69) 3.42 (1.81) Important 4.00 (1.70) 3.30 (2.00) 3.41 (2.03) 3.38 (1.59) 3.15 (1.76) 3.42 (1.81) In control 4.33 (1.56) 4.02 (1.87) 4.08 (1.76) 3.56 (1.67) 2.95 (1.65) 3.03 (1.70) Expected 4.20 (1.64) 3.96 (1.92) 4.05 (1.84) 3.36 (1.66) 2.86 (1.55) 3.04 (1.71) No. rated positive 3.16 (3.21) 1.63 (1.96) 1.57 (2.12) 4.97 (4.67) 2.00 (2.02) 2.86 (3.22) No. rated negative 0.42 (0.89) 0.93 (1.41) 0.77 (0.91) 1.28 (1.81) 3.08 (3.58) 3.03 (4.38) No. rated neutral 9.16 (5.64) 9.22 (5.03) 8.77 (5.29) (6.00) (5.60) 8.77 (5.29) Note. Standard deviations are given in parentheses. Data were calculated within individuals, then averaged across individuals. DRM Day Reconstruction Method; ESM experience-sampling method; md minor depression; MDD major depressive disorder. p.05 in comparison with controls. p.01 in comparison with controls.

8 162 BYLSMA, TAYLOR-CLIFT, AND ROTTENBERG Table 3 Event Contexts by Group and Assessment Method, Displayed as Percentages of All Reported Events DRM ESM Event context Control md MDD Control md MDD Activity type Socializing Eating, cooking Commuting Paid work TV, reading, computer Grooming, self-care Studying, schoolwork Napping, resting Childcare Housework, chores Shopping, errands Exercising Praying, meditating Nature of the event Positive social Neutral social Negative social Personal success Personal failure Goal accomplished Goal blocked Interacting with Anyone Friends Coworkers, supervisor Significant other Parents, relatives Children Clients, customers, students Strangers Pets Location Home Car, bus Work School Retail store Restaurant, place of entertainment Friend s or family member s home Note. Percentages were calculated within individuals, then averaged across individuals. Data includes all days sampled for the ESM (3) and DRM (1) methods. DRM Day Reconstruction Method; ESM experience-sampling method; md minor depression; MDD major depressive disorder. Significantly different from the control group ( p.05). Significantly different from the control group ( p.01). NA as the dependent variables. For the model with PA as the dependent variable, all groups reported similar increases in PA in response to pleasant events, as well as similar decreases in PA in response to unpleasant events. For NA, consistent with previous mood-brightening effects and our research hypothesis (Peeters et al., 2003), both MDD and md groups reported greater decreases in NA in response to pleasant events relative to controls. However, groups did not differ in their NA responses to unpleasant events. See Table 5 for the ESM and DRM models of PA and NA. Multilevel control analyses. To better understand this moodbrightening effect, we conducted control analyses of three factors that may have influenced the results: baseline NA, observer ratings, and antidepressants. First, we reran the multilevel model controlling for prevailing daily NA (i.e., by adding average daily NA as a Level 1 predictor to the model). In both the ESM and DRM data, the mood-brightening effect was still apparent even after controlling for baseline mood, suggesting the moodbrightening effect could not be accounted for by high levels of prevailing negative mood in the mood-disordered groups. Second, because events were selected for analysis on the basis of participants subjective ratings and because depressed participants reported experiencing fewer pleasant events relative to controls, we used the objective event ratings (only available for the DRM data) to examine whether depressed individuals may have had a higher threshold for considering an event to be pleasant. If this were the case, it could potentially explain why depressed individuals reported greater mood brightening to pleasant events than did controls. A one-way ANOVA was conducted on objective coder ratings of the DRM data (with group as the between-subjects factor and participants pleasantness ratings

9 EMOTIONAL REACTIVITY TO DAILY EVENTS 163 Table 4 Mean Daily Affect Ratings by Group and Assessment Type Method and valence MDD md Controls DRM PA (9.99) (9.96) (10.62) NA (10.19) (9.91) 5.01 (6.16) ESM PA (7.70) (7.97) (8.33) NA (7.62) (8.01) 7.90 (6.63) Lab PA (7.13) (8.89) (7.60) NA (9.97) (7.09) 5.16 (5.88) Note. Standard deviations are given in parentheses. Ratings are based on the sum of seven positive and seven negative mood ratings, each on a scale ranging from 0 to 6 points, with a total range of For the DRM and ESM, PA and NA values were averaged over all reports within individuals before calculating overall group means. MDD major depressive disorder; md minor depression; DRM Day Reconstruction Method; PA positive affect; NA negative affect; ESM experience-sampling method. as the within-subjects factor). For events rated by participants as highly pleasant, there were no group differences ( ps.05) in objective coder ratings, suggesting that depressed individuals did not have a higher threshold for rating events as pleasant. Thus, a higher threshold for rating events as pleasant did not explain greater mood brightening to pleasant events in mooddisordered individuals. Finally, because two md and seven MDD individuals were taking antidepressants at the time of the study, we examined the impact of antidepressant use on affect and emotional reactivity in multilevel models of the ESM and DRM data and specifically whether this usage might explain the mood-brightening effect. Antidepressant use did relate to less daily NA in the depressed samples in both the ESM (B 70.82, p.07) and DRM (B 6.04, p.05) data when controlling for diagnostic group (MDD 1, md 0) as a covariate. Depressed individuals taking antidepressants showed greater increases in NA after negative events in the ESM (B 38.95, p.04) but not the DRM data. Finally, antidepressant use was also related to changes in NA, such that depressed individuals taking antidepressants showed greater decreases in NA after positive events in both the ESM (B 45.87, p.02) and DRM (B 5.53, p.05) data. These latter findings are consistent with the possibility that greater mood brightening in response to positive events could be reflective of a medication effect. To rule out this alternative explanation, we reran the NA analyses only in the subsample of unmedicated participants. In the unmedicated subsample, the main findings were essentially unchanged in both the ESM (MDD: B 1.32, p.17; md: B 2.24, p.05) and DRM (MDD: B 2.87, p.05); md: B 2.85, p.06) data. Did Groups Differ in Event Appraisals? Finally, we compared participants ratings on subjective appraisals of the events. Mean ratings by group are presented in Table 2 for ratings of event pleasantness, unpleasantness, stress- Table 5 Summary of Parameter Estimates and Model Fit for Multilevel Models of Negative and Positive Affect Negative affect Positive affect ESM DRM ESM DRM Fixed and random effects B SE p B SE p B SE p B SE p Fixed effects For Intercept 1, 0 Intercept 2, MDD, md, For positive event slope, 1 Intercept 2, MDD, md, For negative event slope, 2 Intercept 2, MDD, md, Random effects VC SD VC SD VC SD VC SD Intercept 1, r Positive event slope, r Negative event slope, r Level 1, e (Sigma squared) Note. ESM experience-sampling method; DRM Day Reconstruction Method; MDD major depressive disorder; md minor depression; VC variance component.