Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2021 Apr 1.
Published in final edited form as: J Affect Disord. 2020 Jan 13;266:207–214. doi: 10.1016/j.jad.2020.01.041

A Tale of Two Systems: Testing a Positive and Negative Valence Systems Framework to Understand Social Disconnection Across Anxiety and Depressive Disorders

Charles T Taylor a,*, Sarah L Pearlstein a,b, Murray B Stein a
PMCID: PMC7351468  NIHMSID: NIHMS1597474  PMID: 32056878

Abstract

Background:

Social disconnection is a common and pernicious feature of anxiety and depressive disorders, yet is insufficiently addressed by our best available treatments. To better understand why people with anxiety and depression feel socially disconnected, we tested a positive and negative valence systems framework informed by research on how normative social connections develop and flourish.

Method:

Individuals seeking treatment for anxiety or depression (N=150) completed measures of perceived social connectedness, positive and negative valence temperament, social goals, affect, symptoms, and life satisfaction.

Results:

Feeling less socially connected was associated with diminished life satisfaction, beyond clinical symptom severity. Regression analyses revealed that both diminished positive valence and heightened negative valence temperament, and their corresponding motivational and affective outputs, were significantly and uniquely (with no significant interaction between them) associated with lower perceived connectedness.

Limitations:

Data was cross-sectional and based on self-report—limiting conclusions about causality and social disconnection processes at different units of analysis.

Conclusions:

Understanding social disconnection through the lens of a positive and negative valence systems framework may inform transdiagnostic models and treatment approaches.

Keywords: Anxiety, depression, positive valence, negative valence, social connectedness, life satisfaction

The need to belong within social relationships is a fundamental human motivation (Baumeister & Leary, 1995)—one that confers important health benefits (Holt-Lunstad, Smith, & Layton, 2010; House, Landis, & Umberson, 1988; Santini, Koyanagi, Tyrovolas, Mason, & Haro, 2015; Umberson & Montez, 2010; Yang et al., 2016). Individuals who have stronger social connections display fewer psychological symptoms, better stress resilience and immune function, and greater life satisfaction (Chu, Saucier, & Hafner, 2010; Cohen, 2004; Eisenberger & Cole, 2012; Fredrickson, 2001; 2003; Lyubomirsky, King, & Diener, 2005; Teo, Choi, & Valenstein, 2013; Uchino, Cacioppo, & Kiecolt-Glaser, 1996). In contrast, social disconnection and loneliness increase risk for early mortality to levels on par with well-established risk factors such as obesity and smoking (Cacioppo & Cacioppo, 2018; Holt-Lunstad, Smith, Baker, Harris, & Stephenson, 2015; Holt-Lunstad et al., 2010).

Social disconnection is one of the more common and pernicious features of anxiety and depressive disorders—two highly prevalent conditions that incur a significant public health burden worldwide (Baxter, Scott, Ferrari, & Whiteford, 2014; Whiteford et al., 2013). Individuals diagnosed with these conditions have smaller networks of people with whom they have important and consistent contact than those with no history of psychiatric illness, and they engage in fewer social activities (Saris, Aghajani, van der Werff, van der Wee, & Pennix, 2017)—they also report higher loneliness and perceived social disability, and diminished quality of life in social domains (Cramer, Torgersen, & Kringlen, 2005; Marver et al., 2017; McKnight & Kashdan, 2009; Olatunji, Cisler, & Tolin, 2007). The strong association between social connectedness and well-being in non-clinical (community) samples suggests that perceived social disconnection in people who experience excessive anxiety or depression should account in part for their tendency to be dissatisfied with their lives. It remains unknown, however, whether social disconnection accounts for perceptions of diminished life satisfaction beyond variance accounted for by clinical symptoms.

Current theories of anxiety and depression tend to conceptualize problems in social functioning as byproducts of disorder-specific etiology (e.g., excessive fear and avoidance in anxiety; avolition and avoidance in depression), and prevailing treatment approaches target them as such—yielding modest response rates that leave room for improvement (Hofmann, Wu, & Boettcher, 2014; McKnight & Kashdan, 2009). Dimensional frameworks that begin with an understanding of how normative positive social connections develop and thrive are agnostic about diagnostic categories—accommodating both comorbidity and within-disorder heterogeneity—and may therefore point to key transdiagnostic processes that underpin social impairments that are partially distinct from those that maintain symptoms. This approach is consistent with emerging models of psychopathology that endeavor to study fundamental dimensions of functioning that cut across traditional diagnostic categories (Insel et al., 2010).

Social relationships provide opportunities for both reward and punishment—developing a meaningful connection with others or being rejected. We therefore drew on bivariate models of human motivation and behavior (Elliot, 2006; Elliot & Thrash, 2010; Gable, 2006; Gable & Berkman, 2008; Gable, Reis, & Elliot, 2000, 2003; Gray, 1987; Lang, 1995; Watson, Clark & Tellegen, 1988) to examine the role of positive and negative valence systems as broad dispositional factors hypothesized to account for social disconnection across anxiety and depressive disorders. The negative valence system (also referred to as the avoidance or aversive system) coordinates psychological and behavioral processes involved in preventing the experience of unwanted outcomes (e.g., loss, punishment, rejection) and is characterized by negative cognitions (e.g., rumination, attentional biases toward negatively valenced stimuli), emotions (e.g., sadness, anxiety), and inhibitory/avoidance behaviors. The positive valence system (also referred to as the approach or appetitive system) is a partially independent dimension (Aupperle & Paulus, 2010; Paulus et al., 2017; Watson et al., 1988) that coordinates processes involved in pursuing desired or rewarding outcomes (e.g., social acceptance), including fostering attention toward reward-relevant stimuli, positive emotions such as excitement and joy, and approach-oriented behaviors (e.g., curiosity, social initiation). The positive and negative valence systems framework has been applied to understand symptom dimensions underlying anxiety and depressive disorders (e.g., Rodebaugh et al., 2017; Struijs et al., 2017, 2018). Symptoms, however, are at least partially distinct from positive social functioning (Alden & Taylor, 2011; Keyes, 2005). Our purpose herein was to determine whether this framework can be applied transdiagnostically to inform the nature of social disconnection across the anxiety and depression spectrum.

The current work draws heavily on hierarchical models of approach and avoidance temperament within the social domain (Gable, 2006; Gable & Berkman, 2008) and seeks to extend initial disorder-specific applications of this framework (Trew & Alden, 2012). Individual differences in temperament that preferentially activate either system have been shown in non-clinical samples to underlie (1) differential frequencies of having proximal social goals that are either positive valence (approach) oriented (e.g., meeting new people; deepening existing relationships) or negative valence (avoidance) oriented (e.g., not making a fool of oneself; avoiding conflict), and (2) differential propensities to experience positive vs. negative affect (Elliot, Gable, & Mapes, 2006; Gable, 2006; Gable et al., 2000). Negative valence processes (e.g., avoidance-oriented social goals) are linked to relationship insecurity, loneliness, low relationship satisfaction, and a higher likelihood of relationship dissolution over time, whereas positive valence processes (e.g., approach-oriented social goals) are positively associated with relationship satisfaction and the frequency of positive relational events (Elliot et al., 2006; Gable, 2006; Impett, Gable, & Peplau, 2005; Impett, Peplau, & Gable, 2005). Heightened negative valence sensitivity is a core defining feature of anxiety and depressive disorders that is reliably observed across multiple units of analysis (Brown, Chorpita, & Barlow, 1998; Barlow, Sauer-Zavala, Carl, Bullis, & Ellard, 2014; Dillon et al., 2014). Diminished positive valence sensitivity (e.g., low positive affect, diminished approach motivation and behavior, reduced behavioral and neural reactivity to rewards) is also observed within depression (Bijttebier, Beck, Claes, & Vandereycken, 2009; Trew, 2011), as well as social anxiety disorder (Coplan, Wilson, Frohlick, & Zelenski, 2006; Kashdan, 2007, Trew & Alden, 2012) and posttraumatic stress disorder (Nawijn et al., 2015; for reviews see Carl, Soskin, Kerns, & Barlow, 2013; Craske, Meuret, Ritz, Treanor, & Dour, 2016; Dillon et al., 2014). Social disconnection within anxiety and depressive disorders may therefore be the product of dysregulation in either positive or negative valence systems, or both.

Current study

The current study had three objectives. First, to determine whether indices of positive social functioning (e.g., perceived connectedness) were related to life satisfaction in individuals with clinically impairing anxiety or depression, beyond variance accounted for by symptoms. Evidence of such a link would underscore the importance of social connections, in addition to symptoms, to life satisfaction within a treatment-seeking sample—emphasizing that both are important outcomes in treatment. We hypothesized that greater perceived social disconnection would be associated with diminished life satisfaction beyond symptoms. The second aim was to determine the unique contribution of individual differences in positive and negative valence temperament to perceived social disconnection, and the extent to which these do or do not interact. We hypothesized that diminished positive valence temperament and higher negative valence temperament would be associated with greater social disconnection. The third aim was to examine processes that may account for the predicted relationship between positive and negative valence temperament and social disconnection, namely approach/avoidance social goals as well as positive/negative affect. Consistent with prior work in non-clinical samples (Gable & Berkman, 2008), we hypothesized that positive valence temperament would be related to approach-oriented social goals and positive affect (but not avoidance goals and negative affect), whereas negative valence temperament would be more strongly related to avoidance-oriented social goals and negative affect (cf. approach goals and positive affect). We also predicted that diminished social approach goals and positive affect as well as greater social avoidance goals and negative affect would relate to greater social disconnection. Examining unique variance accounted for by individual positive and negative valence processes is the first step in identifying potential distinct pathways and intervention targets that give rise to and maintain social disconnection across anxiety and depressive disorders.

Method

Participants

The sample included 150 individuals between the ages of 18 and 55 (91 women, 57 men, 2 participants did not identify with either gender category) seeking treatment for depression or anxiety within the context of three parent clinical trials that, respectively, selected for participants with (1) a current principal diagnosis of social anxiety disorder (SAD) defined using the Structured Clinical Interview for the Diagnostic and Statistical Manual (4th ed.; DSM–IV; American Psychiatric Association, 2000) Axis 1 Disorders (SCID-I; First, Spitzer, Gibbon, & Williams, 2002)1 and clinician administered Liebowitz Social Anxiety Scale (LSAS; Liebowitz, 1987) score ≥ 50 (n=71); (2) a current principal diagnosis of major depression defined using the clinician administered Mini International Neuropsychiatric Interview for DSM-5 (MINI Version 7.0.0)2, as well as scoring 10 or higher on the Patient Health Questionnaire-9 (PHQ-9; n=42), and (3) current clinically elevated symptoms of anxiety and/or depression, defined as scoring 10 or higher on the Patient Health Questionnaire-9 (PHQ-9) and/or scoring 8 or higher on the Overall Anxiety Severity and Impairment Scale (OASIS; n=37). Participants were recruited through clinical referrals as well as posted announcements in community and online settings (e.g., ResearchMatch.org).

Assessments to determine principal and comorbid diagnoses were conducted using the MINI Version 7.0.03 by a PhD-level clinician, a PhD student in clinical psychology, and two post-baccalaureate clinical research coordinators, all of whom received extensive training in the interview protocols. Diagnostic consensus was reached by reviewing completed interviews during team meetings with the first author. Exclusionary criteria across all three samples used to determine parent study eligibility were: (1) active suicidal ideation with intent or plan; (2) moderate to severe alcohol or marijuana use disorder (past year); (3) all other mild substance use disorders (past year); (4) bipolar I or psychotic disorders; (5) moderate to severe traumatic brain injury with evidence of neurological deficits, neurological disorders, or severe or unstable medical conditions that might be compromised by participation in the study; (6) inability to speak or understand English; (7) concurrent psychotherapy (unless 12-week stability criteria had been met for non-empirically supported therapies only); (8) concurrent psychotropic medication (e.g., SSRIs, benzodiazepines); and (9) characteristics that would compromise safety to complete an MRI scan (e.g., metal fragments in body)4.

The sample demographic composition was as follows: age (M = 26.04, SD = 8.50), gender (38.0% men, 60.7% women, 1.3% who did not identify with either gender), race (45.3% Caucasian, 28.7% Asian American, 4.7% African American, 1.3% Native American/Alaskan Native, 8.7% more than one race, 5.3% identified as “other,” and for 4.0% of participants, race was unknown or they declined to respond), ethnicity (24.0% Hispanic); and years of education (M = 15.65; SD = 1.98). Thirty-five percent of participants reported their annual household income as $50,000 or above; 30.7% reported $20,001 to $50,000; 13.3% reported $5,001 to $20,000, and 20.7% reported $5,000 or less. The majority of participants (72%) identified their romantic relationship status as single, 8.7% were married, 8.0% were cohabitating with a romantic partner, 5.3% were divorced or separated, 0.7% were widowed, and 4.7% identified their relationship status as “other.” The sample met DSM criteria for a range of diagnoses: social anxiety disorder (70.7%), major depressive disorder (current; 55.3%), generalized anxiety disorder (28.7%), panic disorder (3.3%), agoraphobia (5.3%), obsessive compulsive disorder (2.7%), posttraumatic stress disorder (6.0%), mild alcohol use disorder (4.7%), and mild marijuana use disorder (2.7%). Approximately two-thirds (62.7%) of participants reportedly received prior psychological treatment, and 27.3% previously received psychotropic medication.

Measures

A full description of each measure and review of psychometric properties is presented in the Supplemental Materials.

Symptom measures.

The Patient Health Questionnaire-9 (PHQ-9; Kroenke, Spitzer, & Williams, 2001) assessed depression severity during the past two weeks based on DSM-5 symptom criteria. Anxiety symptoms were assessed using the Overall Anxiety Severity and Impairment Scale (OASIS; Norman et al., 2006), a widely used 5-item scale that measures the frequency and severity of anxiety symptoms, as well as level of anxiety-based avoidance and interference during the previous two weeks.5 Current sample Cronbach’s α = .82 and .84, respectively.

Positive and Negative Valence Temperament.

The Approach-Avoidance Temperament Questionnaire (ATQ; Elliot & Thrash, 2010) is a 12-item measure designed to measure sensitivity to positive (i.e., reward; 6 items) and negative (i.e., punishment; 6 items) stimuli or contexts. Items within each of these domains measure temperament dimensions of affective reactivity, perceptual vigilance, and behavioral inclination. Current sample Cronbach’s α = .87 and α = .82 for positive and negative valence temperament, respectively.

Social Relationship Functioning.

The Social Connectedness Scale-Revised (SCS-R; Lee, Draper, & Lee, 2001) served as our primary measure of social connectedness. The SCS-R is a 20-item measure that assesses one’s sense of belonging, or the degree to which individuals perceive closeness with others in their interpersonal world (Lee et al., 2001). Current sample Cronbach’s α = .87. Participants also completed ancillary measures of positive social functioning (social initiation and relationship satisfaction; Alden & Taylor, 2011; Alden, Buhr, Robichaud, Trew, & Plasencia, 2018). Results using a composite index comprised of the SCS-R and ancillary measures are reported in the Supplemental Materials for parsimony.

Affect.

Participants completed the 20-item Positive and Negative Affect Schedule (PANAS; Watson, Clark, & Tellegen, 1988) to assess activated forms of positive and negative affect; and the 20-item Modified Differential Emotions Scale (mDES; Fredrickson, Tugade, Waugh, & Larkin, 2003) to assess a broader array of discrete positive (e.g., joy, love, awe) and negative emotions (e.g., guilt, anger, fear). Participants responded according to how they felt daring the past week. Current sample Cronbach’s α = .90 for both PANAS positive and negative affect scales, and .91 and .84 for mDES positive and negative emotions, respectively. Given the high correlation between the PANAS and mDES scales (see Supplemental Table 1), composite indices for positive and negative affect were created by averaging the standardized scores (i.e., Z scores; M = 0, SD = 1) for each scale (Rosenthal & Rosnow, 1991).

Social Goals.

Consistent with prior work (Gable, 2006; Trew & Alden, 2012), an assessment comprised of ten items was designed for this study to reflect approach-oriented goals, that is, goals focused on obtaining positive outcomes (e.g., “I wanted to get to know the people I interacted with”) and avoidance-oriented goals, that is, goals focused on avoiding negative outcomes (e.g., “I did not want the people I interacted with to think negatively about me”). Items were rated on a 7-point scale with anchors of not at all and very much. Participants provided ratings based on their reactions to social situations they encountered daring the past week. High internal consistency was observed in this sample (Cronbach’s α = .84 for approach and α = .84 for avoidance goals).

Life Satisfaction.

A subsample (n=112)5 completed the Satisfaction With Life Scale (SWLS; Diener, Emmons, Larsen, & Griffin, 1985), a well-established measure that assesses global satisfaction with one’s life. Current Cronbach’s α = .83.

Procedures

The study procedures were approved by the University of California, San Diego Human Research Protections Program. The current study took place within the context of overarching treatment studies for anxiety and depressive disorders. After receiving information about the research, participants provided informed written consent to participate, and then completed the diagnostic and symptom eligibility assessment. Eligible participants then completed a battery of self-report measures as described above.

Overview of Statistical Analyses

All analyses were conducted using SPSS version 25. We first conducted a hierarchical regression analysis to determine whether perceptions of social connectedness (SCSR) contribute additional variance to life satisfaction (SWLS), above and beyond core symptoms of anxiety (OASIS) and depression (PHQ-9). Next, we examined whether individual differences in positive and negative valence temperament related to perceived social connectedness by examining zero-order Pearson’s correlations between the SCSR and ATQ, followed by a hierarchical regression analysis to test main and interaction effects of positive and negative valence dispositions as unique predictors of perceived social connectedness. ATQ scores were centered at the sample mean prior to computing the interaction term (Aiken & West, 1991). Third, we examined two variables shown to be important in promoting positive social bonds, namely social approach and avoidance goals and positive and negative affect, as putative outputs of positive/negative valence dispositions that predict variance in social connectedness. We examined zero-order Pearson’s correlations between social goals and affect, temperament, and perceived social connectedness. Next, we conducted separate regression models for goals and affect predicting connectedness through main effects of positive and negative valence processes simultaneously, followed by their interaction. For example, positive and negative affect were entered together in step 1 of the regression model predicting SCSR scores, followed by a positive * negative affect interaction term. Finally, we tested a model including both goals and affect simultaneously. Continuous predictor variables were mean centered prior to computing the interaction terms (Aiken & West, 1991). The assumptions underlying linear regression were tested and confirmed for each model, namely normally distributed residuals (predicted-probability plot), linear associations between the independent and dependent variables (scatterplots), homoscedasticity (residual vs. predicted value plots), and absence of multicollinearity (variation inflation factor < 2.00).

Results

Relationship between social connectedness and life satisfaction

Descriptive information and zero-order correlations for all dependent measures are presented in Supplemental Table 1. Perceived social connectedness was significantly and positively associated with life satisfaction, r(112) = .42, p < .001. Greater anxiety and depression symptom severity was associated with lower life satisfaction, r(111)6 = −.18, p = .056 and r(112) = −.40, p < .001, respectively, though the magnitude of this effect was considerably stronger for depression. Critically, results of the regression analysis revealed that social connectedness was a significant unique predictor of life satisfaction when accounting for shared variance with anxiety and depression symptoms, β = .34, t(109) = 3.96, p < .001, accounting for 11% of additional variance in life satisfaction.

Relationship between positive/negative temperament and social connectedness

Positive and negative temperament were largely orthogonal, r(150) = −.02, p =.82. Lower positive valence temperament and higher negative valence temperament were significantly associated with lower perceived connectedness, r(150) = .32 and −.32, p < .001. Results of the regression analysis revealed that both positive and negative valence temperament continued to explain unique (and approximately equal) variance in predicting social connectedness when considered together, β = .30, t(148) = 4.05, p < .001 (positive valence); β = −.33, t(148) = −4.32, p < .001 (negative valence). The approach*avoidance interaction term did not explain significant additional variance in SCSR scores, β = −.07, t(148) = −.94, p = .35.

Relationship between temperament, social goals, affect, and social connectedness

Positive valence temperament was positively associated with approach-oriented social goals and positive affect, r(150) = .45 and r(150) = .57, both p < .001, but was not significantly related to avoidance goals or negative affect, r(150) = .11, p = .17 and r(150) = −.06, p = .48. Conversely, higher negative valence temperament was significantly associated with greater avoidance social goals and negative affect, r(150) = .39 and r(150) = .49, both p < .001, but was not significantly related to approach goals or positive affect, r(150) = .09, p = .29 and r(150) = .01, p = .88. Social approach goals and positive affect were positively associated with social connectedness, r(150) = .34, and r(150) = .38, both p < .001, whereas avoidance goals and negative affect were negatively associated with social connectedness, r(150) = −.21, p = .01 and r(150) = −.18, p = .03.

The regression analyses sought to clarify the unique variance accounted for by positive and negative processes (goals and affect) when considered together in the model predicting perceived connectedness. See Tables 1 and 2. Both greater avoidance goals and diminished approach goals uniquely predicted lower social connectedness. The interaction of approach and avoidance goals was not significant. Lower positive affect and higher negative affect uniquely predicted diminished connectedness when considered together; however, the interaction of positive and negative affect was not significant. Finally, the model combining both goals and affect revealed the same pattern of findings; that is, greater avoidance goals and negative affect as well as lower approach goals and positive affect all uniquely predicted diminished social connectedness.

Table 1.

Multiple Regression Analyses of (a) Approach and Avoidance Social Goals and (b) Positive and Negative Affect Predicting Perceived Connectedness.

Predictor (a) Social Goals (b) Affect
B SE B B t p ΔR2 B SE B B t p ΔR2
Positive Valence 1.09 0.18 .46 6.05 <001 .23 2.75 0.56 .37 4.95 < .001 .17
Negative Valence 2.75 0.56 .37 −4.70 <001 −1.19 0.55 −.16 −2.17 .03
Positive x Negative −0.01 0.03 −.03 −0.39 .69 .001 −0.10 0.32 .02 0.30 .76 .001
Open in a new tab

Note. Because no interaction effects emerged, the main effects statistics are reported from models that did not include interaction terms.

Table 2.

Multiple Regression Analysis of Positive Valence (Social Approach Goals and Positive Affect) and Negative Valence Processes (Social Avoidance Goals and Negative Affect) Combined in Predicting Social Connectedness.

Predictor
B SE B B t p ΔR2
Approach Goals 0.81 0.19 .35 4.26 <001 .31
Positive Affect 1.92 0.57 .26 3.37 .001
Avoidance Goals −0.85 0.19 −.33 −4.51 <001
Negative Affect −1.00 0.51 −.14 −1.98 .049
Approach x Avoidance Goals −0.02 0.03 −.05 −0.65 .52 .002
Positive x Negative Affect 0.07 0.29 .02 0.24 .81
Open in a new tab

Note. Because no interaction effects emerged, the main effects statistics are reported from the model that did not include interaction terms.

Discussion

This study used a positive and negative valence systems framework to understand why people with anxiety or depressive disorders feel socially disconnected. Four main findings emerged: First, lower perceived social connectedness was associated with diminished life satisfaction, even after accounting for variance due to core symptoms of anxiety and depression. Second, both positive and negative valence temperament were associated with perceived connectedness, each contributing unique significant variance of roughly the same magnitude. Third, positive and negative valence temperament displayed unique associations with processes shown to underpin social connections, namely social approach goals/positive affect and avoidance goals/negative affect, respectively. Finally, diminished positive valence goals and affect as well as greater negative valence goals and affect uniquely predicted social disconnectedness. Findings remained robust when examining a broader index of social functioning comprised of perceived connectedness, frequency of social initiation, and satisfaction with different types of relationships. The current findings support the heuristic value of applying positive and negative valence systems frameworks to understand the source of social disconnection and relational impairments in anxiety and depressive disorders.

The perception that participants were not connected to others in their social world explained meaningful variance in their sense of dissatisfaction with their lives, beyond symptom severity. These findings extend to a clinical treatment-seeking sample for the first time the well-established link observed in community samples between social connections and aspects of well-being (Chu et al., 2010; Lyubomirsky et al., 2005), and highlight that perceived connectedness contributes to life satisfaction to a degree on par with symptoms. To the extent that life satisfaction represents an important outcome separate from symptom remission (Keyes, 2005; World Health Organization, 1946), explicitly targeting social connections may be a worthwhile treatment goal. The modest efficacy of existing interventions in improving social functioning and well-being (Hofmann et al., 2014; McKnight & Kashdan, 2009) underscores the value of identifying processes that contribute to social disconnection in clinical samples.

Positive and negative valence temperaments were orthogonal in this treatment-seeking sample—mirroring prior clinical research (Campbell-Sills, Liverant, & Brown, 2004; Paulus et al., 2017) and supporting the relative independence of the dual valence systems framework (Elliot, 2006; Elliot & Thrash, 2010; Gable et al., 2000, 2003; Gray, 1987; Lang, 1995; Watson et al., 1988). Diminished positive valence and greater negative valence dispositions both contributed a moderate amount of unique variance to perceived social disconnection—findings consistent with research in non-clinical samples underscoring the importance of both systems to positive social functioning (Gable & Berkman, 2008; Keltner & Kring, 1998; Ramsey & Gentzler, 2015) and especially relevant for depressive disorders, and some anxiety disorders characterized by dysregulation of both systems (Aupperle & Paulus, 2010; Barlow et al., 2014; Brown et al., 1998; Carl et al., 2013; Dillon et al., 2014). Knowing where a given individual lies along both positive and negative valence dimensions may therefore facilitate an understanding of the source of social disconnection and point to targets for treatment. Although evidence suggests that the negative valence system may be particularly characteristic of anxiety and depressive disorders (Struijs et al., 2017) and their chronicity (Struijs et al., 2018), the current findings suggest that the positive valence system is at least as important to understanding the source of impairments in the social domain (cf. symptoms per se). Positive and negative valence temperament did not interact, suggesting that each dimension was sufficiently robust to independently account for perceptions of connectedness and social functioning.

Positive and negative valence temperament correlated in predicted ways with corresponding motivational and affective processes previously shown to underpin social relationship functioning. Lower positive valence temperament was associated with diminished positive affect and social approach goals, but not negative affect and avoidance goals. In contrast, greater negative valence temperament was associated with higher negative affect and social avoidance goals, but not positive affect and approach goals. This unique pattern of associations supports the relative independence of motivational and affective processes regulated by positive and negative valence systems, and underscores the potential value of measuring both systems within anxiety and depressive disorder samples (e.g., Campbell-Sills et al., 2004; Paulus et al., 2017).

Central to the present aims were results of the regression models testing whether positive/negative valence motivational and affective processes were associated with perceived social disconnection. Positive and negative valence goals and affect were all significantly associated with perceived connectedness. Lower perceived connectedness was accounted for by both lower social approach goals and positive affect—findings consistent with the non-clinical literature underscoring the importance of positive affect and approach-oriented motivation to positive relational outcomes (Gable, 2006; Elliot et al., 2006; Gable & Berkman, 2008; Ramsey & Gentzler, 2015). Higher avoidance goals were also significantly associated with perceived social disconnection—consistent with the notion that motivation to avoid negative social outcomes may limit opportunities for, and reduce engagement within social encounters. Higher negative affect was significantly, albeit modestly associated with perceived disconnectedness, yet was not significantly related to the broader social functioning index (see Supplemental Results). Those findings converge with prior studies finding a weak (e.g., Taylor, Pearlstein, & Stein, 2017) or non-existent link (Clark & Watson, 1988; Watson, Clark, McIntyre, & Hamaker, 1992) between negative affect and sociability and connectedness. Considered together, the current findings suggest that motivational and affective processes underlying both positive and negative valence dispositions may be important contributors to social relationship impairments in anxiety and depression, and that to downplay the role of either system would be to risk missing out on a key piece of the social-functional picture.

Bivariate models of motivation and behavior (Elliot, 2006; Elliot et al., 2006; Elliot & Thrash, 2010; Gable, 2006; Gable & Berkman, 2008; Gray, 1987) conceptualize and measure motivational processes in a way that is conflated with valence-based outcomes. That is, approach motivation is tied to positive valence (reward-related) stimuli and avoidance motivation is tied to negative valence (aversive) stimuli. There is now compelling evidence, however, to suggest a more complex conceptualization of motivation and valence-based processing in relation to anxiety and depression (Winer & Salem, 2016; Winer et al., 2017). For example, rather than simply showing diminished approach, depressed individuals demonstrate active avoidance in response to stimuli that were once rewarding. One implication of those findings is that approach motivation and behavior cannot be assumed to be associated only with rewarding stimuli, and avoidance motivation and behavior cannot be assumed to only be associated with aversive/punishing stimuli. It is therefore possible that social disconnection for some individuals may be driven by avoidance of positively valenced social cues or outcomes. Future research is needed to dissociate motivation and valence-based processes in relation to social functioning in clinical samples.

The current findings highlight the importance of assessing, and potentially targeting both positive and negative valence processes in treatment in the service of enhancing social connections. The relative independence of each system supported here and in prior clinical research (e.g., Campbell-Sills et al., 2004; Paulus et al., 2017) suggests that knowledge about an individual’s functioning on one dimension may not be sufficient. Current evidence-based treatments for anxiety and depression primarily target negative valence thoughts, emotions, and behaviors (Craske et al., 2008; Cuijpers et al, 2013; Hofman & Smits, 2008; Norton & Price, 2007). Because depressive disorders and some forms of anxiety are also characterized by positive valence deficits (Carl et al., 2013; Craske et al., 2016; Dillon et al., 2014), upregulating the positive valence system may offer a complementary approach to improving positive social functioning. Several existing (e.g., mindfulness-based interventions; Strege, Swain, Bochicchio, Valdespino, & Richey, 2018) and newer positive valence targeted treatments show promise in increasing positive emotions and associated outcomes (e.g., relationship satisfaction, psychological well-being) in people with elevated anxiety or depression (e.g., Alden & Trew, 2013; Craske et al., 2019; Taylor, Lyubomirsky, & Stein, 2017).

Several limitations of the current study should be addressed in future work. The cross-sectional data collection limits inferences about causality. Although goals and affect are ostensibly downstream effects of temperamental dispositions, there are likely bi-directional relationships between goals and affect that unfold over time. Future experimental and longitudinal studies are therefore needed to clarify the direction of the observed relationships and to disentangle potential interactions between the positive and negative systems in influencing social relationship outcomes over time. The regression models tested herein separately evaluated components of a hierarchical model wherein positive and negative valence temperament are hypothesized to relate to more proximal affective and motivational processes that influence social outcomes and perceptions of connectedness (e.g., Elliot et al., 2006; Gable, 2006). Larger samples are needed to implement multivariate approaches (e.g., structural equation modeling) that would offer a more integrated test of the proposed framework. Another limitation is that all constructs were assessed via self-report. While perceptions of one’s goals for social encounters and sense of connection with others are important contributors to social health and overall well-being (Cacioppo & Cacioppo, 2018; Gable & Berkman, 2008; Lee et al., 2001), research is needed to investigate other facets of social functioning, including size and cohesiveness of one’s social network, as well as rate of engagement in activities with others (Saris et al., 2017). Measures of positive and negative valence dimensions are also needed at other units of analysis (e.g., behavior, neural circuit function) to offer a more comprehensive understanding of the biobehavioral processes that influence the development and maintenance of positive social connections (Fareri & Delgado, 2014; Vrticka, 2012). Finally, social anxiety and major depression diagnoses were disproportionately represented in the current sample. Although these are two of the most prevalent conditions that individuals who seek treatment in outpatient settings experience (Zimmerman & Mattia, 2000), it would be beneficial to test the current framework within a more heterogeneous sample, including individuals with principal symptoms other than anxiety or depression. These limitations notwithstanding, the current findings support the potential transdiagnostic value of using a dual valence systems framework to understand, and possibly identify treatment targets underlying social disconnection across the anxiety and depression spectrum.

Supplementary Material

Supplemental Materials

Acknowledgements

We would like to thank the many individuals who helped make this research possible: Taylor Smith and Sarah Dowling for conducting diagnostic interviews and overseeing project management; Karalani Cross for overseeing project management; and Carl Bolano, Kevin Carlis, Michelle Chang, Joanna Chen, Melody Chen, Christina Cui, Vivi Dang, Angelica Estrada, Alyson Johnson, Sanskruti Kakaria, Sarah Knapp, Stephanie Lee, Mercy Lopez, Gregory Pak, Jasmine Rai, Atiyeh Samadi, Rachel Storer, Aaron Tay, Sarah Tran, Stephanie Zepeda for their help with recruitment, screening, data collection and management.

Funding

This research was supported by grants awarded to Charles T. Taylor from the National Institute of Mental Health (R00MH090243, R61MH113769), Brain and Behavior Research Foundation (21695), and the University of California, San Diego, National Institute of Health Clinical and Translational Science Awards Program Grant UL1TR001442.

Footnotes

Conflict of Interest: Sarah Pearlstein declares no conflicts of interest. Charles T. Taylor declares that in the past 3 years he has been a paid consultant for Homewood Health, and receives payment for editorial work for UpToDate. Murray B. Stein declares that in the past 3 years he has been a paid consultant for Actelion, Aptinyx, Bionomics, Janssen, Neurocrine, Pfizer, and Oxeia Biopharmaceuticals, and receives payment for editorial work for UpToDate and the journals Biological Psychiatry and Depression and Anxiety.

All procedures performed involving human participants were in accordance with the ethical standards of the University of California San Diego Human Research Protection Program and with the Code of Ethics of the World Medical Association (Declaration of Helsinki).

1

Enrollment began prior to the release of the SCID for DSM-5. Interview questions were subsequently scored to reflect DSM-5 criteria for SAD.

2

We thank David Sheehan for giving us permission to use a preliminary version of the MINI for DSM-5 in this study.

3

Because enrollment began prior to the release of MINI Version 7.0.0 for DSM-5, 40 participants were administered MINI Version 5.0.0 for DSM-IV to assess comorbid diagnoses.

4

Participants completed a functional magnetic resonance imaging (fMRI) scan to address a separate research question. Several of the exclusion criteria were therefore implemented to ensure MRI safety and minimize confounding of the imaging findings.

5

Administration of the SWLS, PHQ-9, and OASIS began part way through data collection (n=112).

6

Sample size differences were due to missing data because some measures were inadvertently not administered to some participants.

References

  1. Aiken LS, & West SG (1991). Multiple regression: Testing and interpreting interactions. Newbury Park: Sage. [Google Scholar]
  2. Alden LE, Buhr K, Robichaud M, Trew JL, & Plasencia ML (2018). Treatment of social approach processes in adults with social anxiety disorder. Journal of Consulting and Clinical Psychology, 86(6), 505–517. 10.1037/ccp0000306 [DOI] [PubMed] [Google Scholar]
  3. Alden LE, & Taylor CT (2011). Relational treatment strategies increase social approach behaviors in patients with Generalized Social Anxiety Disorder. Journal of Anxiety Disorders, 25(3), 309–318. 10.1016/jjanxdis.2010.10.003 [DOI] [PubMed] [Google Scholar]
  4. Alden LE, & Trew JL (2013). If it makes you happy: Engaging in kind acts increases positive affect in socially anxious individuals. Emotion, 73(1), 64–75. [DOI] [PubMed] [Google Scholar]
  5. American Psychiatric Association. (2000). Diagnostic and statistical manual of mental disorders: DSM-IV-TR. Washington, DC: American Psychiatric Association. [Google Scholar]
  6. Arrindell WA, Heesink J, & Feij JA (1999). The Satisfaction With Life Scale (SWLS): Appraisal with 1700 healthy young adults in The Netherlands. Personality and Individual Differences, 26(5), 815–826. 10.1016/S0191-8869(98)00180-9 [DOI] [Google Scholar]
  7. Aupperle Robin, L., & Martin PP. (2010). Neural systems underlying approach and avoidance in anxiety disorders. Dialogues in Clinical Neuroscience, 12(4), 517–531. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Barlow DH, Sauer-Zavala S, Carl JR, Bullis JR, & Ellard KK (2014b). The nature, diagnosis, and treatment of neuroticism: Back to the future. Clinical Psychological Science, 2(3), 344–365. 10.1177/2167702613505532 [DOI] [Google Scholar]
  9. Baumeister RF, & Leary MR (1995). The need to belong: Desire for interpersonal attachments as a fundamental human motivation. Psychological Bulletin, 117(3), 497. [PubMed] [Google Scholar]
  10. Baxter AJ, Scott KM, Ferrari AJ, Norman RE, Vos T, & Whiteford HA (2014). Challenging the myth of an “epidemic” of common mental disorders: Trends in the global prevalence of anxiety and depression between 1990 and 2010. Depression and Anxiety, 31(6), 506–516. 10.1002/da.22230 [DOI] [PubMed] [Google Scholar]
  11. Bijttebier P, Beck I, Claes L, & Vandereycken W (2009). Gray’s Reinforcement Sensitivity Theory as a framework for research on personality-psychopathology associations. Clinical Psychology Review, 29(5), 421–430. 10.1016/j.cpr.2009.04.002 [DOI] [PubMed] [Google Scholar]
  12. Brown TA, Chorpita BF, & Barlow DH (1998). Structural relationships among dimensions of the DSM-IV anxiety and mood disorders and dimensions of negative affect, positive affect, and autonomic arousal. Journal of Abnormal Psychology, 107(2), 179–192. [DOI] [PubMed] [Google Scholar]
  13. Cacioppo JT, & Cacioppo S (2018). The growing problem of loneliness. Lancet, 397(10119), 426. doi: 10.1016/S0140-6736(18)30142-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Campbell-Sills L, Liverant GI, & Brown TA (2004). Psychometric evaluation of the behavioral inhibition/behavioral activation scales in a large sample of outpatients with anxiety and mood disorders. Psychological Assessment, 16(3), 244–254. 10.1037/1040-3590.16.3.244 [DOI] [PubMed] [Google Scholar]
  15. Carl JR, Soskin DP, Kerns C, & Barlow DH (2013). Positive emotion regulation in emotional disorders: A theoretical review. Clinical Psychology Review, 33(3), 343–360. 10.1016/j.cpr.2013.01.003 [DOI] [PubMed] [Google Scholar]
  16. Chu PS, Saucier DA, & Hafner E (2010). Meta-analysis of the relationships between social support and well-being in children and adolescents. Journal of Social and Clinical Psychology, 29(6), 624–645. 10.1521/jscp.2010.29.6.624 [DOI] [Google Scholar]
  17. Clark LA, & Watson D (1988). Mood and the mundane: Relations between daily life events and self-reported mood. Journal of Personality and Social Psychology, 54(2), 296–308. [DOI] [PubMed] [Google Scholar]
  18. Cohen S (2004). Social relationships and health. American Psychologist, 59(8), 676–684. [DOI] [PubMed] [Google Scholar]
  19. Coplan RJ, Wilson J, Frohlick SL, & Zelenski J (2006). A person-oriented analysis of behavioral inhibition and behavioral activation in children. Personality and Individual Differences, 41(5), 917–927. 10.1016/j.paid.2006.02.019 [DOI] [Google Scholar]
  20. Cramer V, Torgersen S, & Kringlen E (2005). Quality of life and anxiety disorders: A population study. The Journal of Nervous and Mental Disease, 193(3), 196–202. 10.1097/01.nmd.0000154836.22687.13 [DOI] [PubMed] [Google Scholar]
  21. Craske MG, Kircanski K, Zelikowsky M, Mystkowski J, Chowdhury N, & Baker A (2008). Optimizing inhibitory learning during exposure therapy. Behaviour Research and Therapy, 46(1), 5–27. 10.1016/j.brat.2007.10.003 [DOI] [PubMed] [Google Scholar]
  22. Craske MG, Meuret AE, Ritz T, Treanor M, & Dour HJ (2016). Treatment for anhedonia: A neuroscience driven approach. Depression and Anxiety, 33(10), 927–938. 10.1002/da.22490 [DOI] [PubMed] [Google Scholar]
  23. Craske MG, Meuret AE, Ritz T, Treanor M, Dour HJ & Rosenfield D (2019). Positive affect treatment for depression and anxiety: A randomized clinical trial for a core feature of anhedonia. Journal of Consulting and Clinical Psychology, 57(5), 457–471. doi: 10.1037/ccp0000396. [DOI] [PubMed] [Google Scholar]
  24. Crawford JR, & Henry JD (2004). The Positive and Negative Affect Schedule (PANAS): Construct validity, measurement properties and normative data in a large non-clinical sample. British Journal of Clinical Psychology, 43(3), 245–265. 10.1348/0144665031752934 [DOI] [PubMed] [Google Scholar]
  25. Cuijpers P, Berking M, Andersson G, Quigley L, Kleiboer A, & Dobson KS (2013). A meta-analysis of cognitive-behavioural therapy for adult depression, alone and in comparison with other treatments. The Canadian Journal of Psychiatry, 58(1), 376–385. 10.1177/070674371305800702 [DOI] [PubMed] [Google Scholar]
  26. Diener E, Emmons RA, Larsen RJ, & Griffin S (1985). The Satisfaction With Life Scale. Journal of Personality Assessment, 49( 1), 71–75. 10.1207/s15327752jpa4901_13 [DOI] [PubMed] [Google Scholar]
  27. Dillon DG, Rosso IM, Pechtel P, Killgore WDS, Rauch SL, & Pizzagalli DA (2014). Peril and pleasure: An RDoC-inspired examination of threat responses and reward processing in anxiety and depression. Depression and Anxiety, 31(3), 233–249. 10.1002/da.22202 [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Eisenberger NI, & Cole SW (2012). Social neuroscience and health: Neurophysiological mechanisms linking social ties with physical health. Nature Neuroscience, 15(5), 669–674. 10.1038/nn.3086 [DOI] [PubMed] [Google Scholar]
  29. Elliot AJ (2006). The hierarchical model of approach-avoidance motivation. Motivation and Emotion, 30(2), 111–116. 10.1007/s11031-006-9028-7 [DOI] [Google Scholar]
  30. Elliot AJ, Gable SL, & Mapes RR (2006). Approach and avoidance motivation in the social domain. Personality and Social Psychology Bulletin, 32(3), 378–391. 10.1177/0146167205282153 [DOI] [PubMed] [Google Scholar]
  31. Elliot AJ, & Thrash TM (2010). Approach and avoidance temperament as basic dimensions of personality. Journal of Personality, 78(3), 865–906. 10.1111/j.1467-6494.2010.00636.x [DOI] [PubMed] [Google Scholar]
  32. First MB, Spitzer RL, Gibbon MWJB, & Williams JB (1995). Structured clinical interview for DSM-IV axis I disorders. New York: New York State Psychiatric Institute. [Google Scholar]
  33. Fredrickson BL (2001). The role of positive emotions in positive psychology: The broaden-and-build theory of positive emotions. American Psychologist, 56(3), 218–226. 10.1037/0003-066X.56.3.218 [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Fredrickson BL (2003). The value of positive emotions: The emerging science of positive psychology is coming to understand why it’s good to feel good. American Scientist, 91(4), 330–335. [Google Scholar]
  35. Fredrickson BL (2013). Positive emotions broaden and build In Devine P & Plant A (Eds.), Advances in Experimental Social Psychology (Vol. 47, pp. 1–53). Academic Press; 10.1016/B978-0-12-407236-7.00001-2 [DOI] [Google Scholar]
  36. Fredrickson BL, Cohn MA, Coffey KA, Pek J, & Finkel SM (2008). Open hearts build lives: Positive emotions, induced through loving-kindness meditation, build consequential personal resources. Journal of Personality and Social Psychology, 95(5), 1045–1062. 10.1037/a0013262 [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Fredrickson BL, Tugade MM, Waugh CE, & Larkin GR (2003). What good are positive emotions in crisis? A prospective study of resilience and emotions following the terrorist attacks on the United States on September 11th, 2001. Journal of Personality and Social Psychology, 84(2), 365–376. [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Gable SL (2006). Approach and avoidance social motives and goals. Journal of Personality, 74(1), 175–222. 10.1111/j.1467-6494.2005.00373.x [DOI] [PubMed] [Google Scholar]
  39. Gable SL & Berkman ET (2008). Making connections and avoiding loneliness: Approach and avoidance social motives and goals In Elliot A (Ed.), Handbook of approach and avoidance motivation (pp. 201–214). NY, New York: Taylor & Francis Group. [Google Scholar]
  40. Gable SL, Reis ΗT, & Elliot AJ (2000). Behavioral activation and inhibition in everyday life. Journal of Personality and Social Psychology, 75(6), 1135–1149. [DOI] [PubMed] [Google Scholar]
  41. Gable SL, Reis ΗT, & Elliot AJ (2003). Evidence for bivariate systems: An empirical test of appetition and aversion across domains. Journal of Research in Personality, 37(5), 349–372. 10.1016/S0092-6566(02)00580-9 [DOI] [Google Scholar]
  42. Gray JA (1987). The psychology of fear and stress (2nd ed.). New York: Cambridge University Press. [Google Scholar]
  43. Hofmann SG, & Smits JAJ (2008). Cognitive-behavioral therapy for adult anxiety disorders: A meta-analysis of randomized placebo-controlled trials. The Journal of Clinical Psychiatry, 69(4), 621–632. [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Hofmann SG, Wu JQ, & Boettcher H (2014). Effect of cognitive-behavioral therapy for anxiety disorders on quality of life: A meta-analysis. Journal of Consulting and Clinical Psychology, 52(3), 375–391. [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Holt-Lunstad J, Smith TB, Baker M, Harris T, & Stephenson D (2015). Loneliness and social isolation as risk factors for mortality: A meta-analytic review. Perspectives on Psychological Science, 10(2), 227–237. 10.1177/1745691614568352 [DOI] [PubMed] [Google Scholar]
  46. Holt-Lunstad J, Smith TB, & Layton JB (2010). Social relationships and mortality risk: A meta-analytic review. PLOSMedicine, 7(1), el000316 10.1371/journal.pmed.1000316 [DOI] [PMC free article] [PubMed] [Google Scholar]
  47. House JS, Landis KR, & Umberson D (1988). Social relationships and health. Science, 247(4865), 540–545. 10.1126/science.3399889 [DOI] [PubMed] [Google Scholar]
  48. Impett EA, Gable SL, & Peplau LA (2005). Giving up and giving in: The costs and benefits of daily sacrifice in intimate relationships. Journal of Personality and Social Psychology, 89(3), 327–344. 10.1037/0022-3514.89.3.327 [DOI] [PubMed] [Google Scholar]
  49. Impett EA, Gordon AM, Kogan A, Oveis C, Gable SL, & Keltner D (2010). Moving toward more perfect unions: daily and long-term consequences of approach and avoidance goals in romantic relationships. Journal of personality and social psychology, 99(6), 948–963. 10.1037/a0020271 [DOI] [PubMed] [Google Scholar]
  50. Impett EA, Peplau LA, & Gable SL (2005). Approach and avoidance sexual motives: Implications for personal and interpersonal well-being. Personal Relationships, 12(4), 465–482. 10.1111/j.1475-6811.2005.00126.x [DOI] [Google Scholar]
  51. Insel T, Cuthbert B, Garvey M, Heinssen R, Pine DS, Quinn K, … Wang P (2010). Research Domain Criteria (RDoC): Toward a new classification framework for research on mental disorders. American Journal of Psychiatry, 167(7), 748–751. 10.1176/appi.ajp.2010.09091379 [DOI] [PubMed] [Google Scholar]
  52. Kashdan TB (2007). Social anxiety spectrum and diminished positive experiences: Theoretical synthesis and meta-analysis. Clinical Psychology Review, 27(3), 348–365. 10.1016/j.cpr.2006.12.003 [DOI] [PubMed] [Google Scholar]
  53. Keltner D, & Kring AM (1998). Emotion, social function, and psychopathology. Review of General Psychology, 2(3), 320. [Google Scholar]
  54. Keyes CL (2005). Mental illness and/or mental health? Investigating axioms of the complete state model of health. Journal of Consulting and Clinical Psychology, 73(3), 539–548. [DOI] [PubMed] [Google Scholar]
  55. Kok BE, Coffey KA, Cohn MA, Catalino LI, Vacharkulksemsuk T, Algoe SB, …Fredrickson BL (2013). How positive emotions build physical health perceived positive social connections account for the upward spiral between positive emotions and vagal tone. Psychological Science, 24(1), 1123–1132. 10.1177/0956797612470827 [DOI] [PubMed] [Google Scholar]
  56. Kroenke K, Spitzer RL, & Williams JBW (2001). The PHQ-9. Journal of General Internal Medicine, 16(9), 606–613. 10.1046/j.1525-1497.2001.016009606.x [DOI] [PMC free article] [PubMed] [Google Scholar]
  57. Lang PJ (1995). The emotion probe: Studies of motivation and attention. American Psychologist, 50(5), 372–385. [DOI] [PubMed] [Google Scholar]
  58. Lee RM, Draper M, & Lee S (2001). Social connectedness, dysfunctional interpersonal behaviors, and psychological distress: Testing a mediator model. Journal of Counseling Psychology, 48(3), 310–318. 10.1037/0022-0167.48.3.310 [DOI] [Google Scholar]
  59. Liebowitz MR (1987). Social phobia. Modern Problems in Pharmacopsychiatry, 22, 141–173. [DOI] [PubMed] [Google Scholar]
  60. Lyubomirsky S, King L, & Diener E (2005). The benefits of frequent positive affect: Does happiness lead to success? Psychological Bulletin, 131(6), 803–855. [DOI] [PubMed] [Google Scholar]
  61. Marver JE, Galfalvy HC, Burke AK, Sublette ME, Oquendo MA, Mann JJ, & Grunebaum MF (2017). Friendship, depression, and suicide attempts in adults: Exploratory analysis of a longitudinal follow-up study. Suicide and Life-Threatening Behavior, 47(6), 660–671. 10.1111/sltb.12329 [DOI] [PubMed] [Google Scholar]
  62. McKnight PE, & Kashdan TB (2009). The importance of functional impairment to mental health outcomes: A case for reassessing our goals in depression treatment research. Clinical Psychology Review, 29(3), 243–259. 10.1016/j.cpr.2009.01.005 [DOI] [PMC free article] [PubMed] [Google Scholar]
  63. Nawijn L, van Zuiden M, Frijling JL, Koch SBJ, Veltman DJ, & Olff M (2015). Reward functioning in PTSD: A systematic review exploring the mechanisms underlying anhedonia. Neuroscience & Biobehavioral Reviews, 51, 189–204. 10.1016/j.neubiorev.2015.01.019 [DOI] [PubMed] [Google Scholar]
  64. Norman SB, Campbell-Sills L, Hitchcock CA, Sullivan S, Rochlin A, Wilkins KC, & Stein MB (2011). Psychometrics of a brief measure of anxiety to detect severity and impairment: The overall anxiety severity and impairment scale (OASIS). Journal of Psychiatric Research, 45(2), 262–268. 10.1016/jjpsychires.2010.06.011 [DOI] [PMC free article] [PubMed] [Google Scholar]
  65. Norman SB, Cissell SH, Means Christensen, A. J., & Stein MB. (2006). Development and validation of an Overall Anxiety Severity And Impairment Scale (OASIS). Depression and Anxiety, 23(4), 245–249. 10.1002/da.20182 [DOI] [PubMed] [Google Scholar]
  66. Norton PJ, & Price EC (2007). A meta-analytic review of adult cognitive-behavioral treatment outcome across the anxiety disorders. The Journal of Nervous and Mental Disease, 195(6), 521 10.1097/01.nmd.0000253843.70149.9a [DOI] [PubMed] [Google Scholar]
  67. Olatunji BO, Cisler JM, & Tolin DF (2007). Quality of life in the anxiety disorders: A meta-analytic review. Clinical Psychology Review, 27(5), 572–581. 10.1016/j.cpr.2007.01.015 [DOI] [PubMed] [Google Scholar]
  68. Paulus MP, Stein MB, Craske MG, Bookheimer S, Taylor CT, Simmons AN, … Fan B (2017). Latent variable analysis of positive and negative valence processing focused on symptom and behavioral units of analysis in mood and anxiety disorders. Journal of Affective Disorders, 216, 17–29. 10.1016/jjad.2016.12.046 [DOI] [PMC free article] [PubMed] [Google Scholar]
  69. Pavot W, & Diener E (1993). The affective and cognitive context of self-reported measures of subjective well-being. Social Indicators Research, 28(1), 1–20. 10.1007/BF01086714 [DOI] [Google Scholar]
  70. Ramsey MA, & Gentzler AL (2015). An upward spiral: Bidirectional associations between positive affect and positive aspects of close relationships across the life span. Developmental Review, 36, 58–104. 10.1016/j.dr.2015.01.003 [DOI] [Google Scholar]
  71. Rodebaugh TL, Levinson CA, Langer JK, Weeks JW, Heimberg RG, Brown PJ, … Liebowitz MR (2017). The structure of vulnerabilities for social anxiety disorder. Psychiatry Research, 250, 297–301. 10.1016/j.psychres.2017.01.073 [DOI] [PMC free article] [PubMed] [Google Scholar]
  72. Rosenthal R & Rosnow RL (1991). Essentials of behavioral research Methods and data analysis (2nd ed.). New York, NY: McGraw-Hill. [Google Scholar]
  73. Santini ZI, Koyanagi A, Tyrovolas S, Mason C, & Haro JM (2015). The association between social relationships and depression: A systematic review. Journal of Affective Disorders, 175, 53–65. 10.1016/jjad.2014.12.049 [DOI] [PubMed] [Google Scholar]
  74. Saris IMJ, Aghajani M, van der Werff SJA, van der Wee NJA, & Penninx BWJH (2017). Social functioning in patients with depressive and anxiety disorders. Acta Psychiatrica Scandinavica, 736(4), 352–361. 10.1111/acps.12774 [DOI] [PMC free article] [PubMed] [Google Scholar]
  75. Semin GR, & Manstead ASR (1982). The social implications of embarrassment displays and restitution behaviour. European Journal of Social Psychology, 12(4), 367–377. 10.1002/ejsp.2420120404 [DOI] [Google Scholar]
  76. Strege MV, Swain D, Bochicchio L, Valdespino A, & Richey JA (2018). A pilot study of the effects of mindfulness-based cognitive therapy on positive affect and social anxiety symptoms. Frontiers in Psychology, 9, 866. doi: 10.3389/fpsyg.2018.00866 [DOI] [PMC free article] [PubMed] [Google Scholar]
  77. Struijs SY, Lamers F, Rinck M, Roelofs K, Spinhoven P, & Penninx BWJH (2018). The predictive value of Approach and Avoidance tendencies on the onset and course of depression and anxiety disorders. Depression and Anxiety, 35(6), 551–559. 10.1002/da.22760 [DOI] [PMC free article] [PubMed] [Google Scholar]
  78. Struijs SY, Lamers F, Vroling MS, Roelofs K, Spinhoven P, & Penninx BWJH (2017). Approach and avoidance tendencies in depression and anxiety disorders. Psychiatry Research, 256, 475–481. 10.1016/j.psychres.2017.07.010 [DOI] [PubMed] [Google Scholar]
  79. Taylor CT, Lyubomirsky S, & Stein MB (2017). Upregulating the positive affect system in anxiety and depression: Outcomes of a positive activity intervention. Depression and Anxiety, 34(3), 267–280. 10.1002/da.22593 [DOI] [PMC free article] [PubMed] [Google Scholar]
  80. Taylor CT, Pearlstein SL, & Stein MB (2017). The affective tie that binds: Examining the contribution of positive emotions and anxiety to relationship formation in social anxiety disorder. Journal of Anxiety Disorders, 49, 21–30. 10.1016/j.janxdis.2017.03.007 [DOI] [PMC free article] [PubMed] [Google Scholar]
  81. Teo AR, Choi EL, & Valenstein M (2013). Social relationships and depression: Ten-year follow-up from a nationally representative study. PLOS ONE, 8(4), e62396 10.1371/journal.pone.0062396 [DOI] [PMC free article] [PubMed] [Google Scholar]
  82. Trew JL (2011). Exploring the roles of approach and avoidance in depression: An integrative model. Clinical Psychology Review, 31(1), 1156–1168. 10.1016/j.cpr.2011.07.007 [DOI] [PubMed] [Google Scholar]
  83. Trew JL, & Alden LE (2012). Positive affect predicts avoidance goals in social interaction anxiety: Testing a hierarchical model of social goals. Cognitive Behaviour Therapy, 41(2), 174–183. 10.1080/16506073.2012.663402 [DOI] [PubMed] [Google Scholar]
  84. Cichino BN, Cacioppo JT, & Kiecolt-Glaser JK (1996). The relationship between social support and physiological processes: A review with emphasis on underlying mechanisms and implications for health. Psychological Bulletin, 119(3), 488–531. [DOI] [PubMed] [Google Scholar]
  85. Umberson D, & Karas Montez J (2010). Social relationships and health: A flashpoint for health policy. Journal of Health and Social Behavior, 57(1_suppl), S54–S66. 10.1177/0022146510383501 [DOI] [PMC free article] [PubMed] [Google Scholar]
  86. Watson D, Clark LA, & Tellegen A (1988). Development and validation of brief measures of positive and negative affect: The PANAS scales. Journal of Personality and Social Psychology, 54(6), 1063–1070. [DOI] [PubMed] [Google Scholar]
  87. Waugh CE, & Fredrickson BL (2006). Nice to know you: Positive emotions, self-other overlap, and complex understanding in the formation of a new relationship. The Journal of Positive Psychology, 7(2), 93–106. 10.1080/17439760500510569 [DOI] [PMC free article] [PubMed] [Google Scholar]
  88. Whelan DC, & Zelenski JM (2012). Experimental evidence that positive moods cause sociability. Social Psychological and Personality Science, 3(4), 430–437. 10.1177/1948550611425194 [DOI] [Google Scholar]
  89. Whiteford HA, Degenhardt L, Rehm J, Baxter AJ, Ferrari AJ, Erskine ΗE, … Vos T (2013). Global burden of disease attributable to mental and substance use disorders: Findings from the Global Burden of Disease Study 2010. The Lancet, 352(9904), 1575–1586. 10.1016/S0140-6736(13)61611-6 [DOI] [PubMed] [Google Scholar]
  90. Winer ES, Bryant J, Bartoszek G Rojas E, Nadorff MR, & Kilgore J (2017). Mapping the relationship between anxiety, anhedonia, and depression. Journal of Affective Disorders, 227, 289–296. doi: 10.1016/j.jad.2017.06.006 [DOI] [PMC free article] [PubMed] [Google Scholar]
  91. Winer ES, & Salem T (2016). Reward devaluation: Dot-probe meta-analytic evidence of avoidance of positive information in depressed persons. Psychological Bulletin, 142, 18–78. doi: 10.1037/bul0000022 [DOI] [PMC free article] [PubMed] [Google Scholar]
  92. World Health Organization (1946). Constitution of the World Health Organization. Geneva: WHO. [Google Scholar]
  93. Yang YC, Boen C, Gerken K, Li T, Schorpp K, & Harris KM (2016). Social relationships and physiological determinants of longevity across the human life span. Proceedings of the National Academy of Sciences, 773(3), 578–583. 10.1073/pnas.1511085112 [DOI] [PMC free article] [PubMed] [Google Scholar]
  94. Zimmerman M, & Mattia JI (2000). Principal and additional DSM-IV disorders for which outpatients seek treatment. Psychiatric Services, 57(10), 1299–1304. 10.1176/appi.ps.51.10.1299 [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplemental Materials
NIHMS1597474-supplement-Supplemental_Materials.pdf (399.6KB, pdf)

RESOURCES