Journal of Social and Clinical Psychology, Vol. 33, No. 9, 2014, pp. 805-830

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© 2014 Guilford Publications, Inc.

This research was supported in part by a grant from the National Institute of Mental Health R21MH072533 (Shrier).

We would like to thank Eli Finkel for his comments on an earlier draft of this article.Address correspondence to Ashley D. Kendall, Department of Psychology,

Northwestern University, 2029 Sheridan Road, Swift 102, Evanston, IL 60208; E-mail: kendall@u.northwestern.edu.

DEPRESSED YOUTH

KENDALL ET AL.

THE SOCIAL CONTEXT OF POSITIVE AND NEGATIVE AFFECTIVE STATES IN DEPRESSED YOUTH

ASHLEY D. KENDALLNorthwestern University; Boston Children’s Hospital

JOSHUA WILTNorthwestern University

COURTNEY E. WALLSBoston Children’s Hospital

EMILY A. SCHERER AND WILLIAM R. BEARDSLEEBoston Children’s Hospital; Harvard Medical School

WILLIAM REVELLENorthwestern University

LYDIA A. SHRIERBoston Children’s Hospital; Harvard Medical School

Depression, which is characterized by low positive affect (PA) and high negative affect (NA), is relatively common during late adolescence and young adulthood. During this period, interaction with an increasing social sphere gains importance, and interest in romantic companions assumes a central role. However, little is known about how PA and NA manifest in the daily lives of depressed youth, par-

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ticularly in romantic settings. Current companionship, location, and affect were assessed 4 to 6 times per day over 2 weeks in 51 adolescents and young adults (mean age = 18 years) with clinically-significant depressive symptoms. Multilevel modeling was used to examine the associations of companionship and location with changes in the between-person mean effects as well as the within-person covariation effects of PA and NA. Generally, when alone versus with people, PA decreased, NA increased, and changes in the levels of PA and NA were rela-tively independent of each other. In the context of romantic companionship, in general, PA increased and NA decreased, but these changes were more strongly inversely linked. The implications for understanding the emotional experiences of depressed youth, as well as informing the development of treatments for this population, are discussed.

The social environment, including companionship and setting, pro-vides the context in which everyday emotional experience unfolds. During adolescence, interpersonal relationships and interaction with an increasing social sphere gain importance (Giordano, 2003), with interest in romantic companions assuming a central role (Col-lins, Welsh, & Furman, 2009). Accordingly, examining the associa-tions of affective states with social contexts, particularly romantic companionship, may yield important insights into the emotional experiences of young people. Elucidating the nature of the associa-tions in late adolescents and young adults with depression is of par-ticular interest because depression occurs at relatively high rates in these populations (e.g., Merikangas et al., 2010).

Depression is often conceptualized in a hierarchical affective framework, with positive affect (PA) and negative affect (NA) rep-resenting higher-order dimensions that subsume a range of posi-tive and negative emotional experiences, respectively (e.g., Watson & Tellegen, 1985). Indeed, these two core affects account for a siz-able proportion of the variability in mental health (Watson & Clark, 1997). The dominant theoretical models of affective disorders (e.g., Mineka, Watson, & Clark, 1998) converge in positing that depres-sion is characterized by low PA and high NA. There is now a wealth of empirical support for these models (see Watson & Naragon-Gainey, 2010).

Although these associations are robust and have emerged across a variety of samples and methods, knowledge of how depression manifests in the contexts of daily life remains limited. It is largely unknown, for example, how youth with clinically significant de-

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pressive symptoms experience changes in levels of PA and NA as they transition through the different settings of their everyday lives, particularly romantic contexts. Moreover, it remains to our knowl-edge entirely unknown whether social contextual factors influence the extent to which changes in levels of one affective dimension are linked to changes in the other.

Importantly, depression has been conceptualized as an emotion regulation disorder (Forbes & Dahl, 2005; Gross & Muñoz, 1995). Examining affective variation (i.e., changes in mean levels of mo-mentary PA and NA) and affective covariation (i.e., the range of within-person momentary correlations between these two dimen-sions) in relation to social contexts could thus provide useful infor-mation regarding modifiable factors on which to focus in treatment. These analyses could, respectively, point to the contexts in which depressed people are likely to experience changes in levels of PA and NA, and reveal the extent to which these changes are linked to each other in different contexts.

Focusing on affective dynamics in romantic settings may be espe-cially useful, as emotions related to romantic interest are believed to constitute a substantial part of young people’s daily emotional lives (Larson, Clore, & Wood, 1999). Additionally, there is growing evidence of a positive association between romantic involvement among youth and depression (e.g., Compian, Gowen, & Hayward, 2004; Davila, Steinberg, Kachadourian, Cobb, & Fincham, 2004). For example, among girls, depression is positively associated with ro-mantic activities including dating, flirting, and feeling sexually at-tracted to another person (e.g., Steinberg & Davila, 2008). This asso-ciation may seem counterintuitive, given that among adults, being married or in a relationship is associated with lower depression (see Umberson & Williams, 1999). Research on the reasons that roman-tic involvement is positively associated with depression in youth is lacking. However, it has been suggested that depressed youth might seek out romantic company in order to regulate their affec-tive states (see Davila, Stroud, & Starr, 2008). Consistent with this idea, there is some evidence that romantic involvement may be part of an emotion regulation effort (e.g., Bancroft et al., 2003).

Momentary sampling methods, in which a representative sample of data is collected as people go about their daily lives (see Bolger, Davis, & Rafaeli, 2003; Shiffman, Stone, & Hufford, 2008), are ideal for such investigations. Although the controlled laboratory envi-

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ronment allows more precise measurements to be obtained, gener-alizability suffers as it is virtually impossible to recreate everyday social experiences in a laboratory. Retrospective reports of emotion, in turn, are subject to recall bias (see Shiffman et al., 2008). This limi-tation may be particularly relevant to depression, as depressed peo-ple are likely to report information in a way that is congruent with their negative thoughts (e.g., Mokros, 1993). Momentary sampling methods directly address these limitations by collecting data in the natural environment and in real time, thereby maximizing ecologi-cal validity and minimizing recall bias.

Preliminary evidence that affective variation differs as a function of social context in young people with high-risk symptoms came from a momentary sampling study of seventh-grade students iden-tified as high- versus low-risk based on a cluster analysis of prob-lem measures (Schneiders et al., 2007). High-risk youths reported more intense depressed mood than did their low-risk peers. Across the sample, youths generally experienced higher PA and lower de-pressed mood when with company versus alone and when outside versus inside the home. The only study of which we are aware that systematically applied momentary sampling methods to the exam-ination of affective variation and social contexts in young people with depressive disorders came from Silk et al. (2011). The authors compared 47 participants with major depressive disorder (MDD) to 32 controls. The intensity of NA distinguished the groups, with youths with MDD reporting higher levels of NA across a variety of social contexts. This is consistent with other momentary sampling research in young people with high-risk (Schneiders et al., 2007) and depressive (Brown, Strauman, Barrantes-Vidal, Silvia, & Krapil, 2011; Larson, Rafaelli, Richards, Ham, & Jewell, 1990) symptoms. The MDD and control groups from the Silk et al. (2011) study were similar in both reporting more negative emotion when alone versus with company. This, too, is in line with past work in young people with and without high-risk symptoms (Schneiders et al., 2007), de-pressive symptoms (Brown et al., 2011), and depressive disorders (Merrick, 1992).

These studies demonstrated that social context was related to changes in mean levels of momentary PA and NA (i.e., affective variation) in young people with and without depressive symptoms and disorders. They stopped short, however, of addressing an im-portant and largely unanswered question: Do everyday social con-

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texts influence the extent to which moment-to-moment changes in PA and NA are linked to each other (i.e., changes in affective co-variation)?

Emerging research on affective covariation, also known as affec-tive synchrony (Rafaeli, Rogers, & Revelle, 2007), indicates that in most people within-person variations in PA and NA occur indepen-dently of each other over time (Rafaeli et al., 2007; Wilt, Funkhouser, & Revelle, 2011). However, there is a sizable minority of people who reliably exhibit inverse within-person associations between the di-mensions and another sizable minority who reliably show synchro-nous (i.e., positive) within-person associations (Rafaeli, Rogers, & Revelle, 2007; Wilt, Funkhouser, & Revelle, 2011). It remains unclear whether affective covariation differs as a function of the everyday social environment.

In considering this possibility, it may be helpful to review two concepts. First, PA and NA are separable dimensions, capable of op-erating independently (e.g., Thayer, 1989; Watson & Tellegen, 1985). Although debate about the structure of affective space continues, research from the past two decades provides substantial evidence for a bivariate model of orthogonal affective dimensions (see Rafa-eli & Revelle, 2006; Schimmack & Reisenzein, 2002).

Second, there may be circumstances in which changes in the af-fective dimensions become dependent on each other. For example, Zautra, Reich, Davis, Potter, and Nicolson (2000) have demonstrat-ed that affect independence is influenced by stressful events. They found that although PA and NA were uncorrelated in low-stress contexts, there was a significantly stronger inverse correlation in a range of stressful situations. This work converges with several other studies showing that stress is associated with more inverse relations between PA and NA (see Zautra, 2003). Zautra, Potter, and Reich, (1997, Zautra et al., 2000) speculated that processing PA and NA separately provides maximum information but is maximally costly in terms of cognitive resources. Under stress, the benefits of fuller information processing are offset by the costs (Zautra et al., 1997, 2000). Emotional experience therefore becomes constrained: a per-son is aware of only one affective dimension, reflected by a stronger inverse relation between the dimensions (Zautra et al., 1997, 2000). In other words, in stressful contexts, people are more likely to feel all good or all bad.

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The compression of affective dimensions under stressful condi-tions could have important implications for the study of depres-sion. According to Beck’s (Beck, Steer, & Brown, 1996) model of depression, dichotomous thinking, which occurs in all-or-nothing terms (e.g., If my boyfriend and I have one fight, it means we don’t love each other), fuels depressed mood (see Beck, 1995). Beck et al. (1996), suggested that such polarized thinking reflected less com-plex cognitive processing. Similarly, polarized emotional experi-ence (i.e., experiencing all PA or NA) could reflect more simplified cognition (Zautra et al., 1997, 2000) and contribute to depression. In support of the association with depression, evidence indicates that among bereaved adults, increased emotional polarity is associated with depressive and anxiety symptoms, whereas greater emotional complexity is associated with psychological resilience (Coifman, Bonanno, & Rafaeli, 2007).

To our knowledge, inverse relations between affective dimen-sions have only been demonstrated in the direction of lower PA and higher NA. However, we suggest that the stronger links between affects could also occur in the opposite direction, which could be especially relevant to depression. Depressed people, like their non-depressed peers, experience increased PA and decreased NA when in the company of others (e.g., Silk et al., 2011). Compared to those without depression, however, depressed people experience sub-stantially more interpersonal stress (see Hammen, 2005). Social con-texts might therefore be more stressful for depressed people, lead-ing them to experience stronger correlations between emotions in the direction of higher PA and lower NA. This would suggest that although socializing could be a useful tool for depressed people to use to improve their mood, it could also place them at greater risk for returning to their hallmark emotional state of low PA and high NA. The reason is that any drop in PA would necessarily cor-respond with a rise in NA, and vice versa.

To summarize, research on affective covariation has revealed in-dividual differences in the tendency to experience inverse, zero, or synchronous (i.e., positive) correlations between momentary PA and NA over time (Rafaeli et al., 2007; Wilt et al., 2011), but has not ex-amined the influence of social contextual factors on these dynamic associations. Studies of the within-person correlations between PA and NA provide a rationale for such examination by demonstrating that contextual factors—in particular, stressful situations—influ-

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ence dependence between the affective dimensions (e.g., Zautra et al., 2000).

The primary objective of the present study was to elucidate the associations among companionship, location, and affective states in adolescents and young adults with clinically significant depressive symptoms. We examined the associations of social contexts with both affective variation and covariation, with an emphasis on ro-mantic contexts. Although the causal relations between everyday social contexts and momentary affective states have not been estab-lished, time-lagged analyses of daily events and adjustment suggest that, on average, events predict affect (Nezlek & Gable, 2001); we developed our hypotheses accordingly.

The first set of hypotheses concerned the affective dynamics as-sociated with companionship. Following from research identifying time spent alone as an emotionally-meaningful context in adoles-cence (e.g., Larson & Csikszentmilhalyi, 1978), we focused on soli-tude in addition to romantic company. We hypothesized the fol-lowing ordered relation concerning higher PA and lower NA (i.e., changes in affective variation) and greater affective polarization (i.e., changes in affective covariation): alone < nonromantic com-pany < romantic company.

Regarding affective variation, we expected youth to experience the lowest PA and highest NA when alone, and the reverse pattern when with romantic companions. Solitude has been associated with lower PA and higher NA, including among youth with and without depressive symptoms and disorders (e.g., Brown et al., 2011; Silk et al., 2011). As previously noted, depressed youth might seek out romantic company to regulate their affective states (see Davila et al., 2008). If spending time with a romantic companion is effective in improving mood, then depressed youth should generally feel in-creased PA and decreased NA when in romantic versus other social contexts.

Regarding affective covariation, we reasoned that solitude should be less stressful than companionship, and thus hypothesized that young people would experience weaker affective covariation, on average, when alone versus with any type of company. This expec-tation was driven by findings that the presence of others increases general arousal (Zajonc, 1965), and that depression in particular is related to high levels of interpersonal stress (see Hammen, 2005). We further hypothesized that time spent with a boy/girlfriend

812 KENDALL ET AL.

would be the most stressful, reflected by the strongest inverse cor-relations between affective dimensions. This was based on findings that young people described romantic relationships as emotionally chaotic, being characterized by frequent swings between positive and negative emotions (see Larson et al., 1999).

Our second set of hypotheses concerned the associations between location and emotional dynamics. We examined these hypotheses to further test our general expectation that social isolation is asso-ciated with lower PA and higher NA, but less emotional polarity. We selected home as our comparison group based on the expec-tation that it would provide the least opportunity for socializing. Although other people may be at home, we anticipated that oth-er locations—including public places such as school, and private spots to which an invitation would be necessary, such as friends’ homes—were likely to offer more opportunity for companionship. We predicted that when at home, participants would experience, on average, lower PA, higher NA, and weaker correlations between these dimensions.

METHOD

PARTICIPANTS

Depressed young people 15–22 years old were recruited from an urban New England children’s hospital as part of a larger study on depression and sexual behavior (Shrier et al., 2011). Evidence indi-cates that depression exists on a continuum such that the clinical significance of depressive symptoms does not depend on crossing a diagnostic threshold (e.g., Lewinsohn, Solomon, Seeley, & Zeiss, 2000). We thus used the Beck Depression Inventory (BDI)-II (Beck, Steer, & Brown, 1996) rather than a diagnostic interview for screen-ing. The inclusion criteria for the larger study were reports of cur-rent clinically-significant depressive symptoms (BDI-II score ≥ 16), and heterosexual activity (penile-vaginal sexual intercourse) at least once per week, on average. The hospital institutional review board granted approval and a waiver of parental consent for participants under 18 years old.

The full study consisted of 54 youths, 51 of whom were included in the analytic sample. Of those not included, one had technical problems, one failed to provide momentary data, and one was giv-

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en a different momentary affective states measure than other partic-ipants. Our sample ranged in age from 15 to 22 years (M = 18.12, SD = 1.78), and included 44 (86%) females. Almost one-third (31%) of participants self-identified as non-Hispanic African-American and approximately one-quarter (24%) as non-Hispanic white. Over a third (39%) indicated Hispanic ethnicity and three participants (6%) other or mixed non-Hispanic race/ethnicity. This roughly reflected the racial/ethnic composition of the clinic population from which the sample was drawn. One-quarter of participants (25%) were pre-scribed antidepressant medication; one participant was also pre-scribed an atypical antipsychotic medication.

PROCEDURES

At the first study visit, participants completed a depression measure via audio computer-assisted self-interview (ACASI) programmed with QDS Software (Nova Research v. 2.1, Bethesda, MD), and trained in using a touch-screen handheld computer (Palm® Tung-sten E or E2; for full protocol, see Shrier et al., 2011). A research assis-tant programmed each handheld computer using the Configurable Electronic Real-Time Assessment System (CERTAS) program (PICS, Inc., Reston, VA) to signal only during participants’ self-identified waking hours.

Audible signals were emitted randomly 4–6 times per day for ap-proximately two weeks. In response, participants completed mul-tiple-choice questions including measures of social contexts and affective states at the time of the signal. All reports were automati-cally date- and time-stamped.

Forty-nine participants (96%) completed the recall visit at the end of momentary data collection. One participant was hospitalized before recall and had a parent return the handheld computer; the other was lost to follow-up. Average response rate for the sample was 76% (SD = 17.20, Range = 25%–97%).

MEASURES

Depression. The BDI-II, administered at the first visit via ACASI, measured depressive symptoms over the past two weeks. It con-sisted of 21 items rated from 0 to 3, with higher total scores indicat-

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ing more depressive symptoms. The BDI-II has demonstrated good psychometric properties in adolescents (Steer, Kumar, Ranieri, & Beck, 1998). The mean BDI-II score in our sample was in the severe depression range (M = 30.29, SD = 8.89, range = 17–50, α = .85).

Momentary Social Contexts. Multiple-choice questions adminis-tered during momentary data collection assessed companionship and location at the time of the signal. Participants were asked “Were you alone?” and, if not, prompted to select the option that best rep-resented their main companion: boy/girlfriend, other friends, par-ents, other family, or other. Options for location were home, school, work, friend’s house, or other. For analyses of the relations between solitude and affect, companionship was dichotomized as alone ver-sus with company. For analyses of companion type, companionship was categorized as alone, romantic company (boy/girlfriend), close company (other friends, parents, other family) and other compa-ny. Location was categorized as home, school, and other locations (work, friend’s house, other).

Momentary Affective States. An abbreviated version of the Positive Affect-Negative Affect Schedule (PANAS; Watson, Clark, & Telle-gen, 1988) was administered during momentary data collection to measure affective states “at the time of the signal.” It consisted of six positive (interested, strong, proud, alert, inspired, determined; α = .85, omegatotal (ωt) = .89) and six negative (distressed, upset, guilty, scared, hostile, irritable; α = .83, ωt = .88) affect items. Each item was endorsed on a 5-point scale, with higher numbers indicating stronger affective experience. Items were selected based on previ-ous research with similar age groups (Shrier, Shih, Hacker, & de Moor, 2007).

DATA ANALYSES

Multilevel models (also called linear mixed effects models) were used to examine the relations between social contexts and emotion-al dynamics, while simultaneously accounting for the clustering of observations within an individual. Multilevel models are regression models with additional variance terms for handling group mem-bership or repeated observations within a person. They were ap-propriate for the present study because the momentary sampling observations were nested within participants. On the first level of

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analysis were within-person effects: location, companionship, and momentary PA and NA. The second level consisted of between-per-son effects: severity of depressive symptoms and personal charac-teristics assessed at baseline.

Affective variation was tested with two sets of models: those ex-amining the momentary associations of a social context variable (e.g., companionship type) with (1) PA and (2) NA. All models in-cluded a random intercept term.

Affective covariation was tested by examining the momentary associations between each social context variable and the range of within-person correlations between PA and NA. This was accom-plished by including an interaction term between the social context variable and NA while considering PA the outcome.1 Affect scores were mean-centered within participants, and the relations between PA and NA were allowed to vary randomly across participants. Main effects were included in the interaction models, and context was included as the moderator term. The interaction term thus test-ed whether there were differences in the relations between PA and NA across contexts, above and beyond variation across individuals. In order to test the inclusion of the random slope, we compared each affective covariation model to a similar model that instead in-cluded fixed effects, using maximum likelihood estimates. In each case, the random effects model provided significantly better fit (all ps < .001).

Both the affective variation and covariation models adjusted for characteristics of the person, including age group (15–18 versus 19–22 years), gender, and BDI-II score, as well as report characteris-tics, including time of day (defined by four blocks of six hours) and weekend (3:00 PM on Friday to 11:59 PM on Sunday; Shrier, Walls, Lops, Kendall, & Blood, 2012). Unstructured covariance models were employed.2

Given that the large majority of the sample (86%) was female, each of the affective variation and covariation models was re-run

1. We also ran each of the affective covariation models with NA, rather than PA, entered as the outcome. In each case, the magnitude and direction of the associations remained similar to those from the original models.

2. It is possible that affect ratings made closer together in time were more strongly correlated than those made further apart. We thus re-ran all of our models with an autoregressive covariance structure imposed on the data. These re-analyses did not result in any meaningful changes to our findings.

816 KENDALL ET AL.

with females only. There were no meaningful changes to the pattern of results with respect to the direction, magnitude, or significance of the effect sizes. In addition, a substantial minority (25%) of partici-pants were on antidepressant medications, so each of the original models was re-run with medication status included as a categorical variable. In the variation models, medication status was entered as a main effect and as a moderator of the effect of context. In the co-variation models, medication status was included as a moderator of the effect of the predictor affect. Again, there were no meaningful changes to the pattern of results. All results are thus reported for the full sample (i.e., females and males) and do not include the medica-tion variable.

Follow-up analyses were conducted to examine whether baseline depressive symptoms interacted with the relations between social contexts and affective variation or covariation. In the affective vari-ation models, the social context variable was set to interact with continuous scores on the BDI-II. In the affective covariation models, a three-way interaction was entered between the social context vari-able, NA, and BDI-II score.

Analyses were performed in R (R Development Core Team, 2014) using the multilevel (Bliese, 2013), nlme (Pinheiro, Bates, DebRoy, & Sarkar, 2014), and psych (Revelle, 2014) packages. We report un-standardized regression coefficients (b) to indicate the effect of the independent variable on the dependent variable.

RESULTS

Participants provided 2,713 completed momentary reports. They most often reported being with close company (M number of re-ports/participant = 20.78, SD = 13.07), followed by alone (M = 16.33, SD = 11.66), with a boy/girlfriend (M = 9.02, SD = 8.72), or with oth-er company (M = 7.06, SD = 8.15) (see Table 1). They were most of-ten at home (M = 28.31, SD = 19.28), followed by other locations (M = 18.94, SD = 12.65), or school (M = 5.94, SD = 6.74). Over the course of momentary data collection, mean momentary PA was 14.33 (SD = 6.08, range = 6–30), corresponding to an average item response of 2.39 (SD = 1.01, range = 1–5). Mean momentary NA was 11.62 (SD = 5.54, range = 6–30), corresponding to an average item response of 1.94 (SD = 0.92, range = 1–5). For PA, the intraclass correlation

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(ICC) 1 was .50, and the ICC 2 was .98, indicating that, on average, 50% of the variance could be attributed to person-level variability, and that the reliability of the group mean was 98%, respectively. For NA, the ICC 1 was .37 and the ICC 2 was .97. The average correla-tions between PA and NA across all contexts were b = -.08, t (2657) = -1.38, p = .17, suggesting that, on average, levels of PA and NA within a person were largely unrelated to each other. There were no significant relations between the severity of depressive symptoms at baseline and average variation in PA or NA, or in average affec-tive covariation. These person-level variables therefore did not ap-pear to predict random variation in the slopes between PA and NA.

COMPANIONSHIP AND AFFECT

We began by comparing time spent alone to time spent with any type of companion. Consistent with our hypotheses, solitude was, on average, inversely associated with PA, F (1, 1986) = 31.48, p < .001; b = -1.02, t (1986) = -5.61, p <.001 (see Table 2). In order to determine how representative this finding was of our sample, we calculated the effect of being alone versus with company for each participant.

TABLE 1. Descriptive Statistics of Momentary Reports

Report Positive Affect Negative Affect

Social Context n (%) Item Mean (SD) Item Mean (SD)

Companionship

Alone 833 (30.70) 2.29 (0.93) 2.03 (0.90)

Other family 479 (17.66) 2.45 (1.06) 1.82 (0.87)

Boy/Girlfriend 460 (16.96) 2.35 (0.96) 1.66 (0.78)

Other friends 393 (14.49) 2.41 (1.05) 1.88 (0.88)

Other people 360 (13.27) 2.65 (1.14) 2.20 (1.10)

Parents 188 (6.93) 2.29 (0.94) 2.14 (0.99)

Location

Home 1,444 (53.23) 2.36 (0.99) 1.94 (0.92)

Other location 604 (22.26) 2.53 (0.95) 2.00 (1.02)

School 303 (11.17) 2.55 (0.99) 1.92 (0.79)

Work 192 (7.08) 1.61 (0.53) 1.94 (0.79)

Friend’s house 170 (6.27) 2.07 (0.97) 1.78 (0.93)

Note. Momentary reports (n = 2,713) on social contexts and affective states were collected over a two-week period from 51 participants. Affective states were measured with an abbreviated version of the Positive and Negative Affect Schedule (PANAS) (Watson, Clark, & Tellegen, 1988).

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We found that 90% of participants (46/51) experienced, on average, lower PA when alone versus with company (range of b effects for each participant = -2.23 to 0.22). Similarly, solitude appeared to be positively associated with NA, F (1, 1989) = 6.07, p = .01; b = 0.45, t (1989) = 2.46, p = .01, with 86% of participants (44/51) reporting, on average, higher NA when alone (range of b effects = -1.12 to 1.85).

In the affective covariation model, when alone, the average regres-sion slope between PA and NA was b = 0.03 points, (t (2655) = 0.43, p = .66. This slope differed by b = -0.16 points when participants were with company, indicating a significant interaction effect, t (2655) = -3.46, p < .001). In the context of companionship, the average slope between PA and NA was b = -0.13 points, t (2655) = -2.01, p = .04. As hypothesized, participants therefore experienced significantly weaker inverse correlations between PA and NA, on average, when alone versus with company (see Figure 1 for a frequency distribu-tion of individuals’ b coefficients). In order to quantify the effect sizes, the differences in correlations between being alone and with company were calculated on the individual level. Consistent with the results from the covariation model, this yielded a difference of r = .12, indicating that, on average, participants had less negative correlations between affective dimensions when alone versus with company.

Next, we focused on the affective dynamics associated with ro-mantic versus other types of companionship: solitude, close, and

TABLE 2. Affective Variation (i.e., Between-Person Mean Effects) by Social Context

Positive Affect Negative Affect

Social Context Overalla Change Overalla Change

Solitude F (1, 1986) = 31.48*** F (1, 1989) = 6.07*

Alone versus with Company b = –1.02, t (1986) = –5.61*** b = 0.45, t (1989) = 2.46*

Companionship Type F (3, 1984) = 14.02*** F (3, 1986) = 16.51***

Romantic versus Alone b = 1.02, t (1984) = 3.88*** b = –1.48, t (1986) = –5.60***

Romantic versus Close b = 0.23, t (1984) = 0.90 b = –1.07, t (1986) = –4.14***

Romantic versus Other b = –0.65, t (1984) = –2.00* b =–2.14, t (1986) = –6.57***

Location F (2, 1985) = 23.58*** F (2, 1987) = 1.00

Home versus School b = –0.59, t (1985) = –3.05** b = –0.23, t (1987) = –1.19

Home versus Other b = –2.07, t (1985) = –6.73*** b = 0.13, t (1987) = 0.43

Note. ap-value from repeated measures analysis, type 3 test of fixed effects. Momentary reports (n = 2,713) on social contexts and affective states were collected over a two-week period from 51 participants. Affective states were measured with an abbreviated version of the Positive and Negative Affect Schedule (PANAS) (Watson, Clark, & Tellegen, 1988). *p < .05, **p < .01, ***p < .001.

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other company. As expected, companionship type was associated with PA, F (3, 1984) = 14.02, p < .001. Participants reported signifi -cantly higher PA, on average, when with romantic company versus alone, b = 1.02, t (1984) = 3.88, p < .001; 63% of participants (32/51) showed this pattern, on average (range of b effects = -3.30 to 6.10). Contrary to our expectations, PA did not change signifi cantly when participants were with romantic compared with close company, on average, b = 0.23, t (1984) = 0.90, p = .37. Approximately half of the sample (26/51; 51%) reported, on average, lower PA when with ro-mantic companions (range of b effects = -2.88 to 3.11). Furthermore, PA decreased in the context of romantic versus other companions, b = -0.65, t (1984) = -2.00, p = .05, with the majority of participants (35/50; 70%) reporting, on average, lower PA when with romantic company (range of b effects = -6.36 to 5.63).

Companionship type and NA were also associated, F (3, 1986 = 16.51, p < .001. NA decreased, on average, when participants were with romantic company versus any other type: alone, b = -1.48, t

FIGURE 1. Frequency distributions of individuals’ b coeffi cients relating mean-centered positive to negative affective states in the contexts of solitude and companionship show differences in affective covariation (i.e., changes in within-person covariation effects) across individuals.

820 KENDALL ET AL.

(1986) = -5.60, p < .001, close b = -1.07, t (1986) = -4.14, p <.001, or oth-er, b = -2.14, t (1986) = -6.57, p <.001, company. When with romantic company, 94% of participants (48/51) reported, on average, lower NA versus when alone (range of b effects = -5.98 to 1.18) or with close company (range of b effects = -3.61 to 0.63). When with roman-tic versus other company, on average, every participant could be expected to experience lower NA (range of b effects = -4.63 to -0.42).

In the affective covariation model, the average regression slope between PA and NA was b = -0.12 points, t (2651) = -1.47, p = .14, when participants were with romantic company. This slope differed

FIGURE 2. Frequency distributions of individuals’ b coeffi cients relating mean-centered positive to negative affective states by companionship type, arranged from highest to lowest mean b coeffi cient, show individual differences in affective covariation.

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by b = 0.15 points when participants were alone, indicating a signifi-cant interaction effect, t (2651) = 2.16, p = .03. In the context of soli-tude, the average slope between PA and NA was b = 0.03, t (2651) = 0.44, p = .66. Participants thus experienced stronger inverse momen-tary correlations between PA and NA when with romantic company versus alone, on average (see Figure 2). The average difference in correlations for each participant between being with romantic com-pany and alone was r = .13. This was consistent with the covariation results in showing that, on average, participants had more nega-tive correlations between affective dimensions when with romantic company versus alone. Affective covariation, on average, did not change significantly when participants were with romantic versus close, b = -0.01, t (2651) = -0.20, p = .84; or other, b = -0.03, t (2651) = -0.42, p = .67, company.

LOCATION AND AFFECT

Finally, as hypothesized, we found that location was associated with PA, F (2, 1985) = 23.58, p < .001. PA was lower, on average, when par-ticipants were at home versus at school, b = -0.59, t (1985) = -3.05, p = .002, or in other locations, b = -2.07, t (1985) = -6.73, p < .001. When at home, all but one participant (50/51; 98%) reported, on average, lower PA versus when at school (range of b effects = -6.97 to 0.98), and the majority (45/51; 88%) reported, on average, lower PA versus when in other places (range of b effects = -1.94 to 0.55). Notably, the associations of PA with being at home versus school, b = -0.40, t (1985) = -2.03, p < .05, or other locations, b = -1.78, t (1985) = -5.66, p < .001, remained significant, on average, after entering the dichotomous companionship variable into the models. Contrary to our expectations, location was not associated with NA, F (2, 1987) = 1.00, p = .37.

In the affective covariation model, the average slope between PA and NA when participants were at home was b = -0.03 points, t (2653) = -0.51, p = .61. This slope differed by b = -0.27 points when participants were at school, indicating a significant interaction ef-fect, t (2653) = -4.13, p < .001. In the context of school, the average slope between PA and NA was b = -0.30 points, t (2653) = -3.65, p < .001. Consistent with our expectations, participants experienced sig-

822 KENDALL ET AL.

nifi cantly weaker affective polarization, on average, when at home versus school (see Figure 3). On the individual level, the average difference in correlations between being at home versus school was r = .12. Consistent with the covariation fi ndings, this suggested that participants, on average, had less negative correlations between af-fective dimensions when at home versus school. Affective covaria-tion, on average, did not change signifi cantly when participants were at home versus in other locations, b = -.07, t (2653) = -1.60, p = .11.

FIGURE 3. Frequency distributions of b coeffi cients relating mean-centered positive to negative affective states by location, arranged from highest to lowest mean b coeffi cient, show individual differences in affective covariation.

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EFFECTS OF BASELINE DEPRESSION

Follow-up analyses showed that baseline depressive symptoms sig-nificantly interacted with the social environment to predict NA. De-pression was more strongly linked to NA in the context of compan-ionship versus aloneness, b = 0.04, t (1986) = 2.86, p < .01. Examining specific types of companionship revealed that baseline depression was specifically related to higher NA when participants were with close company versus when alone, b = 0.05, t (1982) = 2.11, p < .05, and when with other company versus when alone, b = 0.09, t (1982) = 2.99, p < .01. Furthermore, baseline depression was more strongly related to NA when participants were at home versus school, b =.08, t (1984) = -2.39, p < .05. Baseline depression did not significantly interact with the social environment to predict affective covariation.

DISCUSSION

We found that when alone versus with others, depressed young people generally reported lower PA and higher NA. Moreover, they tended to experience weaker momentary correlations between these dimensions, suggesting that changes in levels of PA and NA were less strongly linked to each other. It should be emphasized that our models tested differences in the relations between PA and NA across contexts, above and beyond variation across individuals. Perhaps the most striking aspect of our findings was that stronger links between affective dimensions were shown, for the first time of which we are aware, in the direction of higher PA and lower NA.

Our results were in line with previous studies in finding that depressed young people reported lower PA and higher NA when alone versus with company. We built on past work by revealing that changes in the affective dimensions were more independent of each other in the context of solitude. Given substantial evidence that PA and NA become polarized under stress (see Zautra, 2003), these findings could be interpreted as suggesting that solitude is less stressful than companionship for depressed youth, although this interpretation is speculative and requires further investigation.

Turning to specific types of companionship, when with romantic company versus alone, depressed youths generally reported higher

824 KENDALL ET AL.

PA and lower NA. This lends some empirical support to the idea that depressed young people might seek out romantic compan-ionship in order to regulate their affective states (see Davila et al., 2008). Furthermore, youths in the present study tended to experi-ence stronger inverse correlations between these affective dimen-sions when with romantic companions. Taken together, these find-ings suggest that although seeking romantic companionship could help depressed young people to improve their mood, it could also pose an emotional risk, as any decrease in PA will necessarily corre-spond with an increase in NA. Contrary to our expectations, mean levels of PA did not increase significantly when depressed youths were with romantic versus close company, and decreased when they were with romantic versus other companions.

Consistent with past work (Schneiders et al., 2007), we found that when at home versus in other places, depressed youths experienced lower PA. Location was not associated with NA. Nonetheless, our findings from the affective variation and covariation models pro-vided support for our general expectation that (presumably) less social contexts were associated with lower PA and higher NA, but also less emotional polarization.

Finally, taking into account baseline levels of depression revealed that more severely depressed young people encountered greater distress in certain environments. Those with greater depression did not experience as substantial a reduction in NA when with close or other companions versus alone. Additionally, more depressed young people were more prone to experiencing higher levels of NA in the home setting.

Our findings, which may generalize more clearly to females, could have theoretical and clinical relevance. Not only does de-pression increase during adolescence (e.g., Merikangas et al., 2010), but a robust sex difference emerges during this period that persists through much of the lifespan, with females being twice as likely as males to be depressed (e.g., Wade, Cairney, & Pevalin, 2002). Sev-eral theoretical models suggest that interpersonal stress increases during adolescence, and that females in particular have greater ex-posure and reactivity to this stress (e.g., Hankin & Abramson, 2001). In support of these models, evidence indicates that social stress is a potent predictor of depression (see Hammen, 2005) and that ado-lescent girls versus boys experience more interpersonal stress (e.g., Larson & Ham, 1993). Our findings that greater affective polariza-

DEPRESSED YOUTH 825

tion occurs in social—and particularly romantic—contexts could be indicative of ways in which reactivity to interpersonal stress influ-ences affective processes relevant to depression.

Importantly, affective polarization has been associated with a va-riety of adverse clinical outcomes. As previously noted, one study found that greater polarization among bereaved adults was associ-ated with higher levels of depression and anxiety, whereas greater emotional complexity was associated with higher resilience (Coif-man et al., 2007). A study of affective covariation in people with borderline personality disorder showed that stronger covariation in some social contexts was associated with an increase in impulsive behavior (Coifman, Berenson, Rafaeli, & Downey, 2012). Coifman and colleagues (2012) speculated that being able to maintain emo-tional complexity during stressful situations might be an adaptive mechanism that facilitates high levels of functioning in times of need. Given that establishing and sustaining healthy romantic re-lationships is a developmental milestone (Furman & Weher, 1994), our findings could suggest that it would be particularly beneficial for depression interventions to focus on reducing emotional polar-ity in romantic contexts.

Mindfulness-based interventions and cognitive restructuring are promising methods of reducing emotional polarity. Mindfulness practice, in which people learn to nonjudgmentally observe and ac-cept their thoughts and emotions, has been linked to enhanced emo-tion regulation (see Chambers, Gullone, & Allen, 2009). Although the mechanisms are not fully understood, it has been proposed that mindfulness improves executive control by fostering a more com-plex awareness and nonjudgemental acceptance of present-moment affective states (Teper, Segal, & Inzlicht, 2013). To the extent that a person has an early awareness of and openness to changes in his or her affect, that person might then be better positioned to recruit regulatory resources before an intense shift in mood occurs (Teper et al., 2013).

Cognitive restructuring is effective in reducing polarized think-ing, which appears to result from simplified cognitive processing (see Beck, 1995). If affective polarization also results from simplified cognition (e.g., Zautra et al., 1997, 2000), then cognitive restructur-ing might similarly be used to improve emotional complexity. In particular, there is some evidence that people who described chal-lenging situations as threatening were more likely to experience

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affective polarization, whereas those who perceived challenges as opportunities for reward were more likely to maintain awareness of both positive and negative emotions (Wilt et al., 2011). Cognitive restructuring focused on teaching depressed people to re-appraise stressful conditions as challenges rather than threats might there-fore be especially useful. The effects of mindfulness-based interven-tions and cognitive restructuring on emotional polarity in depres-sion merit further investigation.

Three main limitations to the present study should be noted. First, although depressive symptoms interacted with the companionship and location variables to predict variation in NA, we could not conclude that baseline depression interacted with social context to predict affective covariation. This is in contrast to previous find-ings showing that greater affective polarization was associated with higher levels of psychopathology, including depression (Coifman et al., 2007, 2012). Although we had some range in BDI-II scores, it might be that once (young) people reach a certain severity of depressive symptoms, they do not significantly differ in some of their affective dynamics. The high levels of depression in our sam-ple—with the mean BDI-II score falling in the severe depression range—ensured that we were able to meet our primary objective of elucidating the everyday emotional experiences of young people with clinically significant depression. It will be important for future research to build on the contributions from this paper by studying a sample of adolescents and young adults with a broader range of depressive symptoms.

Second, because data on context and affect were collected concur-rently in an observational study design, and time-lagged analyses were not conducted, directionality could not be inferred. More-over, stress in each context was not directly assessed, so our inter-pretation that greater affective covariation reflected higher levels of stress should be treated as speculative and is in need of future corroboration. However, as previously noted, past research indi-cates that everyday events influence affective experience (Nezlek & Gable, 2001). Furthermore, there is consistent support from both laboratory and field studies that under stress, PA and NA are more strongly inversely correlated (see Zautra, 2003).

Third, the nature of our sample should be considered. The broad age range could raise questions from a developmental perspective. However, age was not significantly associated with affective dy-

DEPRESSED YOUTH 827

namics in any of our variation or covariation models. Caution is further warranted in attempting to generalize our findings beyond female youth, given that our sample was largely female. Although the present study would have been strengthened by the inclusion of more males, analyses of females are nonetheless highly relevant (e.g., Hankin & Abramson, 2001; Larson & Ham, 1993).

Despite its limitations, the present study illuminates how PA and NA manifest for depressed young people in their everyday environ-ments, and shows the extent to which changes in levels of PA and NA are tied to each other in these different settings. By revealing the nuanced ways in which social contexts might influence affective states, these findings make a contribution to understanding the na-ture of mood in young people with depression. It is hoped that this work will ultimately help inform the development of interventions specifically tailored to counteract maladaptive affective processes in this population.

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