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. Author manuscript; available in PMC: 2021 Sep 1.
Published in final edited form as: Psychotherapy (Chic). 2020 Feb 6;57(3):379–390. doi: 10.1037/pst0000283

Trajectories of Change in Well-Being During Cognitive-Behavior Therapies for Anxiety Disorders: Quantifying the Impact and Covariation with Improvements in Anxiety

Matthew W Gallagher 1, Colleen A Phillips 1, Johann D’Souza 1, Angela Richardson 1, Laura J Long 1, James F Boswell 2, Todd J Farchione 3, David H Barlow 3
PMCID: PMC7416465  NIHMSID: NIHMS1064779  PMID: 32027157

Abstract

Cognitive behavior therapy (CBT) has found to be very effective in reducing many forms of mental illness, but much less is known about whether CBT also promotes mental health or well-being. The goals of the present study were to 1) quantify the magnitude and timing of changes in overall well-being and specific facets of well-being during different CBT treatments for anxiety disorders, 2) determine whether these effects vary across transdiagnostic and disorder-specific CBT, and 3) examine how changes in well-being during treatment relate to changes in anxiety. 223 adults (55.6% female, Mage=31.1 yrs) were randomized to one of five CBT protocols for anxiety disorders at an outpatient clinic. Analyses included ESsg effect sizes and latent growth curve modeling. Moderate-to-large increases in overall well-being and the three components of subjective, psychological, and social well-being were observed, mainly during the second half of CBT, and these increases were maintained at a 6-month follow-up. The magnitude of effects were comparable for transdiagnostic and disorder-specific CBT protocols, and greater than in the waitlist. Parallel process latent growth curve models indicated that trajectories of change in well-being across treatment were strongly correlated with trajectories of change in clinician rated and self-reported anxiety. Together, these findings suggest that different CBT protocols for anxiety consistently produce robust and lasting changes in well-being and these changes are strongly linked to changes in anxiety during treatment.

Keywords: Well-being, Mental Health, CBT, Anxiety

Cognitive Behavioral Therapies (CBT) have been shown in recent decades to be broadly effective in reducing many forms of mental illness (Hofmann, Asnanni, Vonk, Sawyer, & Fang, 2012). In particular, CBT protocols have been shown to be quite effective in reducing mental illness in the form of anxiety disorders (Hofmann & Smits, 2008). Although concerns remain about the potential public health impact of this method of treating mental illness (Kazdin & Blasé, 2011), CBT has been identified as having strong research support for each of the anxiety disorders by the Society of Clinical Psychology (generalized anxiety disorder (GAD); social anxiety disorhttps://www.div12.org/psychological-treatments/). However, although decades of research have demonstrated clearly that CBT reduces anxiety and other disorders and reduces associated outcomes such as functional impairment, much less is known about the extent to which CBT promotes distinct domains of well-being beyond the reduction of mental illness. Increasing evidence demonstrates that mental health or well-being is more than just the absence of mental illness (e.g., Keyes, 2007), so it cannot be assumed that just because CBT reduces anxiety that it is equally effective at promoting well-being. The present study explores the extent to which different CBT protocols promote different domains of well-being and how trajectories of change in well-being relate to changes in anxiety during treatment.

Defining Well-Being

The understanding of how best to conceptualize and measure well-being and positive aspects of mental health has been studied much less and has significantly lagged behind our understanding of how to conceptualize different forms of mental illness. Whereas taxonomies of mental illness such as the DSM (American Psychiatric Association, 2013) have gone through many revisions in recent decades, efforts to identify the components of well-being and how they relate to one another are relatively more recent and have less empirical evidence. Although some debate remains about how to distinguish between different domains of well-being (e.g., Kashdan, Biswas-Diener, & King, 2009), increasing evidence suggests that the domains of subjective well-being, psychological well-being, and social well-being together represent positive mental health (Gallagher, Lopez, & Preacher, 2009; Keyes, 2005; Keyes & Annas, 2009; Keyes, Shmotkin, & Ryff, 2002). Subjective well-being emphasizes emotional experiences and cognitive evaluations of one’s life and is sometimes referred to as hedonic well-being (Deci & Ryan, 2008; Diener; Suh, Lucas, & Smith, 1999; Kahneman et al., 1999). Subjective well-being is defined as the presence of high levels of positive affect, relative low levels of negative affect, and high satisfaction with one’s life (Diener, 2009). These three components of subjective well-being are the well-being outcomes that have been most often examined in clinical trials for anxiety disorders. Psychological well-being (also referred to as eudaimonic well-being) constitutes psychological wellness, or optimal functioning, particularly in the face of obstacles (Ryff, 1989). Ryff’s multidimensional model includes six major components of psychological well-being: autonomy, environmental mastery, personal growth, positive relations with others, purpose in life, and self-acceptance (Ryff, 2014). While subjective and psychological well-being are related constructs, they are empirically and conceptually distinct (Keyes et al., 2002). Subjective well-being emphasizes hedonic or emotional functioning and global cognitive evaluations of one’s life whereas psychological well-being emphasizes the pursuit of and perceived attainment of optimal functioning in regards to the pursuit of one’s goals, meaning, and purpose in life. The final component of overall mental health, social well-being, indicates the presence of positive social functioning. While psychological well-being focuses on positive functioning at the intraindividual level, social well-being is focused on the inter-individual level. Social well-being consists of five major domains of social dimensions: social coherence, social actualization, social integration, social contribution, and social acceptance (Keyes, 1998).

The complete state model of mental health integrates these three domains of well-being and suggests that complete mental health constitutes an emotional and functional state beyond the mere absence of illness. Thus, the complete state model of mental health considers the impact of both symptoms of mental illness and well-being on functioning (Keyes, 2005) and allows for the examination of positive mental health as continuous outcomes and as different classifications of mental health. The diagnostic criteria of mental health, or flourishing, includes at least one indicator of overall happiness or life satisfaction, and a high level of at least six of the eleven indicators of psychological and social well-being (Keyes, 2005). Within this model, mental health constitutes a state of flourishing, while languishing constitutes the absence of mental health independent of the presence or absence of mental illness (Keyes, 2002). This model has been replicated in both American and international samples and across the lifespan (Keyes, 2002; Westerhof & Keyes, 2010). Thus, while mental illness and well-being are related, they represent distinct components of mental health.

Well-Being and Anxiety Disorders

Although there is limited research examining the complete state model of mental health in relation to anxiety disorders, research has consistently found that anxiety disorders are associated with significant deficits in different components of well-being. For example, symptoms of social anxiety are negatively associated with both global ratings of well-being and the daily experience of well-being (Kashdan, Julian, Merritt, & Uswatte, 2006). Similarly, in a study examining the link between well-being and mental illness in a nationally representative sample of American adults, symptoms of depression, generalized anxiety, and panic attacks were all negatively correlated with subjective, psychological, and social well-being, but only at small-to-moderate magnitudes (Keyes, 2005). Individuals with various anxiety disorders have been shown to have large deficits in quality of life compared to controls (Barrera & Norton, 2009) and meta-analytic reviews have found that lower levels of quality of life are consistent across the anxiety disorders (Olatunji, Cisler, & Tolin, 2007). Patients who experience remission of their panic disorder symptoms following exposure therapy have also been found to have lower levels of well-being than controls, which suggests that anxiety disorders can have lasting effects on decreasing well-being and that simply reducing levels of anxiety is not always enough to also promote well-being (Fava, Rafanelli, Ottolini, Ruini, Cazzaro, & Grandi, 2001).

The Importance of Well-Being

The different domains of well-being are positive outcomes that are by themselves important, but the presence of higher levels of well-being have also been shown to predict and promote many important outcomes, even when controlling for levels of mental illness. Comparisons of psychosocial functioning in adults who were categorized as having complete mental health, moderate mental health, languishing mental health, pure mental illness, or both mental illness and languishing mental health found that adults with “complete mental health” had the highest levels of positive functioning, goal resilience, and intimacy, as well as the lowest levels of occupational and psychosocial malfunctioning, helplessness, and daily functioning compared to the other categories (Keyes, 2005, 2007). More specifically, the presence of high levels of subjective well-being have been found to predict improved health and longevity acrossa range of research paradigms (Diener & Chan, 2011). Increases in well-being across time prospectively predict declines in mental illness across a ten year timespan (Keyes, Dhingra, & Simoes, 2010), and lower levels of well-being are associated with an increased probability of mortality across a ten year timespan (Keyes & Simoes, 2010). Well-being therefore represents an important outcome in the context of psychotherapy, but the promotion of well-being may also reinforce or facilitate the promotion of other positive outcomes or reductions in mental illness. Understanding the extent to which CBT interventions promote well-being in addition to reducing mental illness therefore has important implications for having a more complete understanding of psychosocial functioning beyond simply identifying the reduction of mental illness.

Promoting well-being

Fortunately, although well-being levels are generally stable in the absence of interventions, there is increasing evidence that the different domains of well-being are malleable and can be effectively increased as a result of interventions (Diener & Ryan, 2009; Diener, Suh, Lucas & Smith, 1999; Ryff, 2014). A variety of intervention strategies have been evaluated to promote well-being, particularly subjective well-being and it appears that these efforts can increase the targeted components of well-being and such increases can also foster further increases in other domains of well-being as well as potentially reduce associated symptoms of mental illness. For example, interventions designed to promote subjective well-being not only lead to lasting increase in positive emotions, but also promote other positive outcomes such as life satisfaction, purpose in life, and improved social functioning (Cohn, Fredrickson, Brown, Mikels, & Conway, 2009; Fredrickson, 2001; Fredrickson, Cohn, Coffey, Pek, & Finkel, 2008). Meta-analytic reviews of positive psychological interventions designed to cultivate well-being have demonstrated that these interventions can not only have robust effects on increasing well-being, they can also decrease associated depressive symptoms (Sin & Lyubmirksy, 2009).

Interventions that have been designed to specifically promote well-being have also been increasingly examined in clinical trials as a direct means of treating anxiety and depressive disorders (Fava & Tomba, 2009) or as a supplementary treatment module (Carl, Gallagher, & Barlow, 2018). Well-being therapy (WBT), initially developed as a supplement to CBT, emphasizes clients’ positive feelings and experiences as a way to prevent relapse of emotional disorders (Ryff, 2014). Through the course of the intervention, the client first keeps a diary of their positive experiences associated with well-being, then, with the help of the therapist, monitors thinking patterns that may prematurely minimize these positive feelings. The intervention ideally concludes with the therapist and client discussing the 6 dimensions of Ryff’s model of psychological well-being as well as maladaptive thinking patterns that can inhibit well-being (Fava, 1999). Multiple studies have demonstrated that WBT is effective in the prevention of relapse of major depressive disorder and the treatment of GAD (Fava et al., 2004, 2005; Ruini & Fava, 2009).

A number of studies have also examined the course of well-being within the context of CBT for anxiety and mood disorders. In particular, CBT trials have increasingly examined quality of life as an outcome (e.g., Arch, Eifert, Davies, Vilardaga, 2012), with meta-analytic reviews indicating that CBT for anxiety disorders generally leads to moderate improvements in quality of life (Hofmann, Wu, & Boettcher, 2014). However, although quality of life is sometimes assessed using measures that are consistent with the life satisfaction component of subjective well-being, many outcomes labeled as quality of life actually reflect the absence of functional impairment and the assumption that the absence of impairment reflects well-being (Gallagher & Long, in press). So while improving quality of life is a desired outcome, improvements in quality of life do not necessarily reflect improvements in different domains of well-being. Although there is limited research examining other aspects of well-being as an outcome in CBT for anxiety disorders, what exists is promising. For example, a small study of patients receiving CBT for emotional disorders such as depression, anxiety disorders, and OCD demonstrated a significant increase in psychological well-being, particularly in purpose in life and self-acceptance (Fava, Rafanelli, Cazzaro, Conti, & Grandi, 1998). Another small study examining the efficacy of CBT for GAD found that participants demonstrated significantly higher psychological well-being after 8 sessions (Fava et al., 2005). CBT for social anxiety has also been found to result in large improvements in life satisfaction and quality of life (e.g., Ledley et al., 2009). Current evidence is, therefore, promising that CBT may promote well-being, but measures of well-being are not a standard outcome in clinical trials so much less is known about whether CBT promotes mental health to the same extent that CBT reduces mental illness.

Unresolved Questions

In summary, although studies of CBT have increasingly examined well-being as an outcome, there is limited research addressing whether different forms of CBT promote well-being to a similar degree, whether CBT impacts different domains of well-being equally, and whether changes in well-being relate to changes in symptom recovery. It may be the case that, just as empirically supported treatments for emotional disorders often have similar outcomes when compared head to head (e.g., Resick, Nishith, Weaver, Astin, & Feuer, 2002), any well-established form of CBT would have equivalent effects on promoting well-being, but such head to head comparisons are not available for well-being. Regarding the three domains of well-being, the potential impact of CBT on subjective well-being may be the most obvious, but CBT protocols often include elements that would be expected to promote aspects of psychological and social well-being such as environmental mastery, positive relations with others, and self-acceptance. Unfortunately, there is little data specifically examining the three domains of well-being as distinct outcomes in clinical trials. Examining the impact of CBT on each domain of well-being would improve our understanding of which domains of well-being are most relevant to recovery from anxiety disorders. Furthermore, although it is clear now that mental health is more than just the absence of mental illness (e.g., Keyes, 2005), our understanding of the extent to which changes in well-being relate to changes in anxiety outcomes during CBT is limited. Given the findings that subjective, psychological, and social well-being can contribute to a more complete understanding of mental and physical health (Keyes, 2007), improving our understanding of these issues would help provide a more comprehensive assessment of patient progress during the course of empirically supported treatments for anxiety disorders.

The Present Study

The current study included three specific aims that address these research questions. The first aim is to quantify the impact of CBT on three domains of well-being (subjective well-being, psychological well-being, and social well-being) and overall well-being and when these changes occurred. In addition, we aimed to determine whether the impact of CBT on well-being varied across transdiagnostic and disorder-specific treatment protocols (e.g. CBT for GAD, SOC, PDA, and OCD1). Finally, we aimed to determine the extent to which changes in well-being correlated with changes in anxiety across treatment, and whether different facets of well-being were consistently linked with changes in anxiety. We hypothesized that transdiagnostic CBT and each of the four different disorder specific CBT protocols would consistently result in increases in overall well-being and the three domains of well-being that would be comparable across CBT protocols and that greater increases in well-being during CBT would be associated with greater decreases in anxiety.

Methods

Participants and Procedure

Participants were 223 adults (55.6% female) who sought outpatient treatment at an anxiety disorders specialty clinic in Boston, MA. The mean age of participants was 31.1 years (SD = 11.0; range 18 – 66). The majority of participants were Caucasian (83.4%) and reported having a college degree or higher levels of education (66.8%). In order to be included in the parent trial, participants had to meet diagnostic criteria for a primary diagnosis of GAD (27.8%), SOC (26.0%), PDA (26.5%), or OCD (19.7%). Participants were randomized based on their principal diagnosis using block randomization to transdiagnostic CBT (Unified Protocol; UP; Barlow et al., 2017), disorder-specific CBT, or a waitlist condition using a 2:2:1 allocation ratio. The disorder specific CBT protocols were Mastery of Your Anxiety and Worry, second edition (Craske and Barlow, 2006), Managing Social Anxiety: A Cognitive-Behavioral Therapy Approach, (Hope, Heimberg & Turk, 2010), Mastery of Your Anxiety and Panic, fourth edition (Barlow and Craske, 2006), and Treating Your Obsessive- Compulsive Disorder With Exposure and Response (Ritual) Prevention Therapy, second edition (Foa, Yadin, and Lichner, 2012). These disorder specific protocols were selected as they each represent gold-standard treatment protocols for the respective disorders with clear evidence of efficacy. Outcomes were assessed every four sessions from baseline to the final session (week 16 for OCD, GAD, SOC; week 12 for PDA). To facilitate comparisons across conditions, participants with a PDA principal diagnosis also completed an assessment at week 16. In the active treatment conditions outcomes were also assessed at a six month follow-up assessment. The vast majority of participants (84.3%) also met diagnostic criteria for at least one additional comorbid diagnosis, with a mean of 2.3 (SD = 1.8) comorbid diagnoses in the sample. See Barlow et al. (2017) for additional details about the experimental design and procedures. The study received IRB approval from Boston University.

Measures

Well-being.

Well-being was assessed using the mental health continuum-short form (MHC-SF; Keyes, 2013). This measure is based on the complete state model of mental health and was developed by selecting individual items from well-established measures of subjective, psychological, and social well-being. The MHC-SF allows for the calculation of overall well-being scores as well as scores for the three facets of well-being. There is increasing evidence that the MHC-SF provides a brief, but reliable and valid method of assessing different domains of positive mental health (Magyar & Keyes, 2019). In our sample, the internal consistency was high at each assessment for each subscale of well-being: subjective well-being alphas ranged from .87 to .91; social well-being alphas ranged from .80 to .86, and psychological well-being alphas ranged from .86 to .89.

Clinician Rated Anxiety.

Clinician ratings of anxiety were conducted using the Hamilton Anxiety Rating Scale (HAMA; Hamilton, 1959). The HAMA is a global measure of anxiety symptom severity and interference across diagnostic conditions and has been extensively used in clinical trials examining the impact of CBT on anxiety disorder symptoms and there is demonstrated validity with each of the four disorders examined in this study. Independent evaluators who were blind to treatment condition conducted the HAMA assessments following the Structured Interview Guide for the Hamilton Anxiety Scale (Shear, Vander Bilt, & Rucci, 2001) and assessments were randomly selected throughout the trial to be rated by an additional independent evaluator to ensure interrater reliability (Barlow et al., 2017).

Self-Reported Anxiety.

Self-report ratings of anxiety were conducted using the Overall Anxiety Severity and Impairment Scale (Norman, Cissell, Means-Christensen, & Stein, 2006). The OASIS consists of five items and was developed as a brief measure that quantifies both anxiety symptom frequency/severity (e.g. “In the past week, when you have felt anxious, how intense or severe was your anxiety”) and functional impairment due to anxiety disorder symptoms (e.g., “In the past week, how much did your anxiety interfere with your ability to do the things you needed to do at work, at school, or at home?”). The OASIS assesses anxiety symptoms/impairment across diagnostic boundaries and is sensitive to intraindividual changes in anxiety during treatment (e.g., Barlow et al., 2017) and there is demonstrated validity with each of the four disorders examined in this study. Internal consistencies of the OASIS were consistently high across each wave of assessment (alphas ranged from .83 to .88).

Analytic Plan

Analyses were conducted using Mplus 8.0 (Muthén & Muthén, 1998 –2016) and robust maximum likelihood estimation procedures. Missing data in all analysis was handled by using multiple imputation techniques in which 1000 imputed datasets were first created using Mplus, analyses were conducted using each of the imputed datasets, and then the pooled results across all of the imputed datasets were interpreted. We first examined the timing and magnitude of changes in the three facets of well-being by calculating effect sizes (standardized mean gain; ESsg). These effect size calculations account for the correlations between repeated assessments of the outcomes and can be interpreted in the same manner as cohen’s d.

A series of latent growth curve (LGC) models was then specified to quantify and characterize the impact of CBT on overall well-being and the three facets of well-being, how trajectories of change in well-being were impacted by CBT relative to the waitlist control condition and when comparing transdiagnostic and disorders specific CBT conditions, and the extent to which changes in well-being during treatment covaried with changes in anxiety symptoms during treatment. Shape factors were specified in all LGC models so that slope factor was centered on the baseline assessment, the loadings for the intermediate assessments during treatment were freely estimated, and the post-treatment assessment loading was fixed at 1.0. This method of specification allowed, but did not impose, for the trajectories of change in well-being to be nonlinear, meaning that the slope factors represented the overall intraindividual change in well-being from baseline to post-treatment while allowing for between individual differences in the trajectories of change.

Model fit in the LGC analyses was evaluated using standard model fit indices: the comparative fit index (CFI; Bentler, 1990), the Tucker–Lewis index (TLI; Tucker & Lewis, 1973), and the root-mean-square error of approximation (RMSEA; Steiger, 1990). Acceptable model fit was evaluated using standard model fit criteria: CFI and TLI values close to .95 or above and RMSEA values close to 0.08 or below, and (Hu & Bentler, 1998).

Results

When and How Much Does Well-Being Change During CBT?

We first examined mean levels (with 95% confidence intervals; Table 1) and intraindividual effect sizes (with 95% confidence intervals; Table 2) in overall well-being and the three facets of subjective, social, and psychological well-being across time and within each condition. As expected, results indicated that CBT led to moderate-to-large effect size increases in well-being. The majority of changes in well-being occurred during the second half of treatment. In terms of the three facets of well-being, CBT resulted in at least moderate effect size increases in all three domains, with the largest changes occurring for psychological well-being and with the smallest increases observed for subjective well-being. The changes in well-being were slightly higher in the disorder specific CBT conditions than the transdiagnostic CBT condition, but not statistically significantly different based on the confidence intervals of the effect sizes. Both disorder specific CBT and transdiagnostic CBT resulted in statistically significantly greater increases in overall well-being and each facet of well-being compared to the waitlist control condition. The magnitude of increases in overall well-being and the three facets of well-being decreased slightly by the six month follow-up, but were largely maintained in each active treatment condition, and levels of well-being were statistically significantly greater than baseline levels based on the confidence intervals of the means.

Table 1.

Means of well-being, subjective well-being, social well-being, psychological well-being (with 95% confidence interval) by condition across time

M (95%CI)
Outcome Time CBT (n=179) UP (n=88) SDP (n=91) WL (n=44)
Well-being Baseline 34.37 (32.22:36.51) 36.41 (33.14:39.69) 32.39 (29.67:35.11) 37.25 (33.04:41.47)
Session 4 35.43 (33.3:37.55) 37.2 (34.05:40.36) 33.71 (30.9:36.51) 36.36 (32.36:40.37)
Session 8 38.03 (35.86:40.2) 39.22 (36.14:42.3) 36.88 (33.84:39.91) 39.59 (35.72:43.46)
Session 12 40.89 (38.53:43.25) 41.82 (38.26:45.38) 39.99 (36.89:43.1) 39.36 (34.86:43.86)
Post Treatment 44.17 (41.96:46.38) 46.63 (43.39:49.86) 42.76 (39.78:45.74) 40.36 (35.87:44.85)
6 mo FU 42.24 (40.04:44.43) 43.03 (39.81:46.24) 41.47 (38.49:44.46)
Subjective Well-Being Baseline 9.04 (8.57:9.5) 9.14 (8.45:9.83) 8.94 (8.3:9.57) 9.02 (8.09:9.95)
Session 4 9.1 (8.63:9.57) 9.17 (8.5:9.84) 9.04 (8.39:9.69) 8.4 (7.4:9.39)
Session 8 9.47 (8.98:9.96) 9.59 (8.93:10.24) 9.36 (8.64:10.07) 8.97 (8.06:9.88)
Session 12 9.85 (9.31:10.39) 9.95 (9.18:10.72) 9.75 (9.01:10.5) 9.15 (8.1:10.19)
Post Treatment 10.48 (9.98:10.97) 10.47 (9.76:11.17) 10.49 (9.8:11.17) 9.38 (8.31:10.45)
6 mo FU 10.33 (9.85:10.81) 10.3 (9.61:10.99) 10.36 (9.7:11.02)
Social Well-Being Baseline 14.94 (13.92:15.95) 15.83 (14.3:17.36) 14.07 (12.75:15.39) 16.32 (14.4:18.23)
Session 4 15.63 (14.56:16.69) 16.44 (14.85:18.02) 14.84 (13.44:16.24) 16.41 (14.47:18.35)
Session 8 16.69 (15.66:17.73) 17.18 (15.68:18.67) 16.23 (14.79:17.66) 17.69 (15.79:19.59)
Session 12 18.25 (17.15:19.35) 18.58 (16.93:20.22) 17.93 (16.47:19.39) 16.97 (14.88:19.06)
Post Treatment 19.84 (18.83:20.85) 20.48 (18.97:22) 19.22 (17.89:20.54) 17.68 (15.59:19.77)
6 mo FU 19 (17.95:20.05) 19.4 (17.85:20.94) 18.61 (17.19:20.03)
Psychological Well-Being Baseline 10.4 (9.5:11.29) 11.44 (10.1:12.78) 9.38 (8.23:10.53) 11.91 (10.11:13.72)
Session 4 10.7 (9.87:11.53) 11.6 (10.41:12.8) 9.83 (8.7:10.95) 11.56 (9.86:13.25)
Session 8 11.87 (11.03:12.7) 12.46 (11.28:13.64) 11.29 (10.13:12.45) 12.93 (11.42:14.44)
Session 12 12.8 (11.9:13.7) 13.3 (11.95:14.65) 12.31 (11.13:13.5) 13.24 (11.41:15.06)
Post Treatment 13.85 (12.98:14.73) 14.68 (13.41:15.95) 13.06 (11.81:14.3) 13.3 (11.5:15.1)
6 mo FU 12.91 (11.99:13.83) 13.33 (12.01:14.64) 12.51 (11.23:13.78)
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Notes: CBT = combined active treatment sample; UP = Unified Protocol; SDP = Single Disorder CBT protocols; WL = Waitlist

Table 2.

Intraindividual effect sizes (ESsg) of changes in well-being, subjective well being, social well-being, psychological well-being by condition across time

ESsg (95% CI)
Outcome Timeframe (Baseline to) CBT (n=179) UP (n=88) SDP (n=91) WL (n=44)
Well-being Session 4 0.07 (−0.02:0.16) 0.05 (−0.05:0.15) 0.10 (−0.05:0.25) −0.06 (−0.22:0.10)
Session 8 0.25 (0.14:0.36) 0.18 (0.04:0.32) 0.32 (0.14:0.49) 0.17 (−0.05:0.39)
Session 12 0.42 (0.30:0.54) 0.33 (0.18:0.47) 0.53 (0.33:0.73) 0.14 (−0.05:0.33)
Post-Treatment 0.66 (0.52:0.8) 0.59 (0.41:0.77) 0.75 (0.52:0.97) 0.21 (0.01:0.41)
6 month Follow-Up 0.53 (0.39:0.67) 0.43 (0.24:0.61) 0.65 (0.44:0.86)
Subjective Well-Being Session 4 0.02 (−0.09:0.13) 0.01 (−0.13:0.15) 0.03 (−0.14:0.21) −0.19 (−0.39:0.01)
Session 8 0.13 (0.01:0.26) 0.14 (−0.04:0.32) 0.13 (−0.05:0.3) −0.02 (−0.23:0.19)
Session 12 0.24 (0.11:0.36) 0.23 (0.06:0.40) 0.24 (0.07:0.41) 0.04 (−0.17:0.24)
Post-Treatment 0.44 (0.31:0.57) 0.40 (0.23:0.57) 0.48 (0.28:0.68) 0.10 (−0.09:0.30)
6 month Follow-Up 0.40 (0.25:0.55) 0.35 (0.14:0.56) 0.45 (0.23:0.67)
Social Well-being Session 4 0.05 (−0.05:0.15) 0.03 (−0.1:0.15) 0.08 (−0.08:0.24) −0.06 (−0.24:0.12)
Session 8 0.25 (0.14:0.36) 0.17 (0.01:0.32) 0.48 (0.25:0.72) 0.18 (−0.06:0.42)
Session 12 0.39 (0.27:0.51) 0.29 (0.13:0.45) 0.52 (0.33:0.70) 0.22 (−0.01:0.44)
Post-Treatment 0.57 (0.43:0.70) 0.52 (0.34:0.7) 0.63 (0.41:0.84) 0.23 (0.00:0.46)
6 month Follow-Up 0.41 (0.26:0.55) 0.30 (0.10:0.50) 0.53 (0.32:0.74)
Psychological Well-being Session 4 0.10 (0.00:0.20) 0.08 (−0.03:0.19) 0.12 (−0.06:0.29) 0.01 (−0.19:0.22)
Session 8 0.25 (0.13:0.37) 0.19 (0.04:0.34) 0.32 (0.13:0.51) 0.21 (−0.02:0.45)
Session 12 0.46 (0.32:0.59) 0.36 (0.20:0.52) 0.57 (0.35:0.79) 0.10 (−0.12:0.31)
Post-Treatment 0.71 (0.55:0.87) 0.64 (0.44:0.84) 0.80 (0.55:1.05) 0.20 (−0.04:0.44)
6 month Follow-Up 0.58 (0.43:0.72) 0.48 (0.30:0.67) 0.68 (0.46:0.90)
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Notes: CBT = combined active treatment sample; UP = Unified Protocol; SDP = Single Disorder CBT protocols; WL = Waitlist

How does CBT impact trajectories of well-being?

We next conducted LGC models to quantify the impact of CBT on well-being. First, unconditional models were specified to examine changes in well-being just within the combined active treatment sample. The results of these models are reported in Table 3 and the slope parameters from these models indicate statistically significant increases in trajectories of change in overall well-being and all three facets of well-being from baseline to post-treatment. The intermediate slope loadings from these models represent the amount of change that had occurred by each assessment and suggest that the majority of change in well-being occurs in second half of treatment. The model fit for these four models was generally good per the CFI and TLI model fit statistics, but poor for some models per RMSEA.

Table 3.

Results from unconditional latent growth curve models examining the trajectories of change in well-being in the active treatment conditions (n = 179)

Well-Being Subjective Well-Being Social Well-being Psychological Well-being
Intercepts
 M 34.76 8.97 10.79 15.01
 95% CI 32.49:37.03 8.50:9.44 9.77:11.81 13.93:16.09
Slope
 M 9.15 1.55 3.06 4.65
 95% CI 7.01:11.29 1.06:2.04 2.12:4.00 3.53:5.77
Slope loadings
 S4 .06 .03 −.06 .14
 S8 .37 .35 .33 .41
 S12 .69 .58 .66 .69
Model fit
 χ2 (df = 7) 28.6 43.28 16.86 18.98
 RMSEA .13 .17 .08 .09
 CFI .97 .94 .99 .98
 TLI .96 .91 .98 .97
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Conditional LGC models were specified next to compare the effects of CBT vs waitlist and disorder specific CBT vs transdiagnostic CBT. Figure 1 provides an example for how these models were specified and the results of these models are presented in Table 4. When comparing CBT to waitlist, the partially standardized effects of treatment on the slope parameters indicated generally moderate to large effects of treatment on trajectories of change in well-being and three facets, with the weakest effect being observed for social well-being. When comparing disorder specific CBT vs transdiagnostic CBT, the effects of treatment condition were consistently small and indicated that disorder specific CBT resulted in slightly greater increases in overall well-being and the three facets, but that these between treatment effects were not statistically significant. The model fit for these eight models was generally good per the CFI and TLI model fit statistics, but poor for some models per RMSEA. Together, these results suggest that CBT produces meaningful increases in overall well-being and the three facets, but that CBT may influence social well-being the least and that the differences between the impact of different CBT protocols on well-being may be relatively small.

Figure 1.

Figure 1.

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Example of Conditional Latent Growth Curve Model Examining the Effect of Treatment on Intraindividual trajectories of change in Well-Being

Table 4.

Results from conditional latent growth curve models examining the effect of treatment condition on trajectories of well-being

CBT vs WL (n = 223) UP vs SDP (n = 179)
Well-Being Subjective Well-Being Social Well-being Psychological Well-being Well-Being Subjective Well-Being Social Well-being Psychological Well-being
Unstandardized Treatment effect
 B 5.08* .80 1.19 3.39* −1.74 −.21 −.79 −.65
 95% CI 1.12:9.04 −0.03:1.63 −0.50:2.88 1.26:5.52 −5.61:2.13 −0.98:0.56 −2.31:0.73 −2.84:1.54
Partially standardized Treatment effect
 b .57* .69 .37 .66* −.19 −.15 −.25 −.13
 95% CI 0.16:0.98 −0.51:1.89 −0.14:0.88 0.27:1.05 −0.60:0.22 −0.68:0.38 −0.72:0.22 −0.54:0.28
Model fit
 χ2 (df = 10) 37.01 51.32 26.66 22.65 31.71 43.08 22.50 22.87
 RMSEA .11 .13 .08 .07 .11 .13 .08 .08
 CFI .98 .95 .98 .99 .97 .95 .98 .98
 TLI .96 .93 .97 .98 .96 .92 .97 .97
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Note: CBT = combined active treatment sample; UP = Unified Protocol; SDP = Single Disorder CBT protocols; WL = Waitlist; in CBT vs WL, cbt =1 and wl = 0; in up vs sdp, UP =1 and sdp = 0

How do changes in well-being correlate with changes in anxiety?

Our final series of models consisted of parallel process LGC to examine the extent to which trajectories of changes in overall well-being and the three facets of well-being correlated with the trajectories of change in both clinician-rated and self-reported anxiety during active treatment. Figure 2 provides an example for how these parallel process models were specified and the results of the parallel process models are reported in Table 5. The model fit for these eight models was generally good across the model fit statistics. When examining the parallel process models with clinician rated anxiety, changes in well-being and the three facets were consistently negatively associated with changes in anxiety. The magnitude for the correlation between well-being and clinician rated anxiety were consistently statistically significant and moderate to large in effect size magnitude with the largest association observed for psychological well-being and anxiety.

Figure 2.

Figure 2.

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Example parallel process latent growth curve model examining how changes in well-being covary with changes in anxiety across the course of treatment.

Note – residual covariances between indicators at each time point specified (e.g., well-being session 4 with HAMA session 4) these constrained to equality

Table 5.

Parallel process model results in active treatment sample (n = 179)

HAMA OASIS
Well-Being Subjective Well-Being Social Well-being Psychological Well-being Well-Being Subjective Well-Being Social Well-being Psychological Well-being
Intercepts
 Correlation −.246 −.204 −.259 −.220 −.405 −.370 −.348 −.417
 SE .086 .089 .084 .095 .078 .086 .09 .080
Slopes
 Correlation −.524 −.462 −.420 −.623 −.573 −.649 −.455 −.610
 SE .130 .215 .138 .143 .124 .46 .179 .119
Model fit
 χ2 (df=34) 89.09 88.57 83.22 77.35 94.84 96.59 109.37 72.19
 RMSEA .09 .09 .09 .08 .10 .10 .11 .08
 CFI .96 .95 .96 .96 .96 .95 .94 .97
 TLI .95 .94 .95 .95 .94 .93 .92 .96
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Note. HAMA = Hamilton Anxiety Scale; OASIS = Overall Anxiety Severity and Impairment Scale.

Similarly, when examining the parallel process models with self-reported anxiety, changes in well-being and the three facets were consistently negatively associated with changes in anxiety. The magnitude for the correlation between well-being and clinician rated anxiety were consistently statistically significant and moderate to large in effect size magnitude with the largest association observed for subjective well-being and anxiety. Together, these results indicate that there is a robust relationship between changes in anxiety and well-being such that greater improvements in overall well-being and each facet of well-being are strongly linked with greater decreases in anxiety across multiple methods of assessment.

Discussion

Decades of research have clearly demonstrated that CBT has robust effects on many different forms of mental illness, including anxiety disorders (Hofmann et al., 2012), but much less is known about the extent to which CBT also promotes well-being or positive aspects of mental health. Given the increasing evidence that mental health is more than just the absence of mental illness (Keyes, 2005, 2007), we cannot assume that just because CBT reduces mental illness in the form of different anxiety disorders that it also promotes well-being. The extent to which CBT influences well-being has been increasingly examined in recent years, but the majority of past work in this area has examined broad measures of quality of life as a treatment outcome (Hoffman et al., 2014). These findings provide promising evidence that CBT promotes general increases in life satisfaction, but do not demonstrate how CBT influences the different domains of well-being that have been identified (Gallagher et al., 2009; Keyes, 2005; Keyes et al., 2002). The present study therefore aimed to elucidate how CBT affects both overall well-being and specific aspects of positive mental health including subjective, psychological, and social well-being. The current study sought to determine the timing of changes in well-being during CBT and whether transdiagnostic and single disorder protocols for different anxiety disorders demonstrate comparable effects on well-being. Furthermore, we sought to determine the extent to which trajectories of change in well-being during the course of CBT covaried with trajectories of change in anxiety.

The results of the present study indicate that well-being increases during the course of CBT. Overall, well-being showed a moderate-to-large increase following treatment. The active treatment conditions were associated with significantly greater increases in all three components of well-being compared to the waitlist control. Effect sizes reflecting changes in well-being were slightly larger for SDP compared to transdiagnostic CBT; however, these effect sizes were not statistically significantly different as evidenced by non-overlapping confidence intervals. Further, it is worth noting that participants in the SDP condition began with lower levels of well-being compared to the transdiagnostic condition, perhaps creating a ceiling effect for the transdiagnostic condition. Nonetheless, results suggest that well-being is a component of mental health that is responsive to both disorder specific and transdiagnostic CBT.

All three facets of well-being (subjective, psychological, and social) demonstrated moderate-to-large increases during the course of treatment. Of the three, psychological well-being showed the greatest increase, while subjective well-being showed the least amount of change. The effect size for subjective well-being is consistent with past findings examining the impact of the UP on negative affect (Farchione et al., 2012), but it is nevertheless somewhat surprising that subjective well-being changed the least given that negative and positive affect are two components of subjective well-being and the experience of emotions is a primary focus of CBT. Although speculative, it is possible that improvement in psychological well-being is more consistent with certain aspects of cognitive behavioral therapy, which focuses on practical ways to change thinking and behavior. Certain domains of psychological well-being are often targeted directly in the context of CBT, such as autonomy, self-acceptance, environmental mastery, and positive relations with others, so it may be that CBT has more robust effects on these outcomes than anticipated.

The time course of improvements in well-being reflects that the majority of change occurred in the second half of treatment for those in active treatment conditions. This suggests that improvements in well-being may be secondary to initial improvements in anxiety at the beginning of treatment, although causal inferences about the relationship between anxiety and well-being cannot be made based on the results of this study. It is possible that some reductions in anxiety are a necessary precursor to promoting increases in well-being during CBT. Interestingly, this is the reverse order of the initially hypothesized “phase model” of psychotherapy outcome, which stipulates that clinical improvements in subjective well-being potentiate symptom improvement, and reductions in symptom-related distress then potentiate life-functioning improvement (Howard, Lueger, Maling, & Martinovich, 1993). Extant research on the phase model is somewhat mixed (Sembill, Vocks, Kosfelder, & Schottke, 2017). This is likely, in part, due to inconsistencies in operationalization and measurement of well-being where indicators of general distress are taken as proxies for subjective well-being rather than measuring well-being directly, which is potentially problematic. At the 6-month follow-up, the effects of CBT on well-being decreased slightly, but were largely maintained, indicating that gains in well-being were generally stable.

The series of parallel process LGC models indicated that increases in overall well-being and the three facets of well-being are negatively related to both clinician-rated measures and self-report measures of anxiety, demonstrating moderate to large effects sizes. Clinician-rated anxiety showed the strongest relationship with psychological well-being, while self-reported anxiety was most strongly related to subjective well-being. The magnitude of the associations between trajectories of change suggest a strong link between changes in anxiety and changes in well-being during CBT, but not so strong of a relationship as to indicate that the outcomes are redundant. These findings therefore underscore the potential utility of increasing the assessment of well-being outcomes in clinical trials so as to provide a more comprehensive examination of how treatment improves mental health broadly.

Strengths of the current study include the size and scope of the clinical trial. This large clinical trial examined specific facets of well-being, allowing for comparison among these facets and a clearer understanding of how CBT for anxiety influences specific domains of well-being and not just global measures of quality of life. The inclusion of multiple assessment modalities also strengthens the conclusion that changes in anxiety and well-being during treatment are strongly linked and not solely due to method effects from the use of self-report questionnaires. Further, the current study examined response to CBT compared to a waitlist control, but also examined differences in response to therapy between single disorder treatments and transdiagnostic treatment of anxiety. The study findings provide evidence that many different forms of CBT for anxiety disorders can produce meaningful improvements in well-being. In addition, the current study examined well-being throughout the course of treatment, rather than just pre- and post-treatment. This made it possible to explore the trajectories of the outcomes across time during CBT, to understand the timeline of changes in well-being during treatment, and to examine non-linear changes in anxiety and wellbeing.

The current study had several limitations. First, the sample was fairly homogenous in terms of race, ethnicity, and education. Although the results are promising, it is important to examine the effects of CBT on well-being in more diverse populations as there little published research examining how demographic factors may moderate the impact of CBT on positive mental health outcomes. Further, there is follow-up data for the active treatment conditions, but no follow-up for the waitlist condition; therefore, we are unable to draw any conclusions about the maintenance of the effect for the waitlist group. Future studies may also include longer measures rather than the short-form measures of well-being used to allow for greater reliability and validity of assessment and may consider additional measures of well-being that capture potential facets of flourishing mental health not assessed by the MHC-SF. Although assessments were conducted at multiple timepoints during the treatment, data was not collected at every session. Future research may measure outcomes each week during treatment to better establish the trajectories of change in anxiety and well-being. Examining therapist effects and how trajectories of well-being may vary as a function of therapist characteristics would also be an important topic to explore. In this clinical trial there was little evidence of variance in outcomes between therapists (Boswell et al., 2019), but therapist effects are often an important factor in psychotherapy outcomes and examining when and how therapist effects influence changes in well-being would be important.

Lastly, although the current study allows us to examine patterns of change over time, we are unable to draw conclusions regarding causality between change in well-being and change in anxiety. Future research is needed to better understand how changes in anxiety during treatment influence changes in well-being during treatment, and vice versa. It may be that there are bidirectional influences such that change in each outcome also promotes change in the other, or it may be that anxiety and well-being represent outcomes that are correlated but independently influenced by CBT. Given that changes in anxiety started earlier in treatment it appears more likely that changes in anxiety may influence subsequent changes in well-being, but this needs to be explored further. It will also be important to examine whether the same mechanisms of change that are consistently found to predict anxiety during CBT (e.g., cognitive reappraisal, self-efficacy) also function as mechanisms of change in the promotion of well-being during treatment.

The findings of the present research provide evidence that CBT has a clear effect on well-being for both specific and transdiagnostic protocols. All five CBT protocols examined produced increases in overall well-being and the three components and there did not appear to be clinically significant differences between the CBT protocols in terms of how much well-being increased. This study builds upon previous research by establishing that changes in well-being during CBT occur for overall well-being as well as the three facets of subjective, social, and psychological well-being, and that changes are maintained at follow-up. Additionally, changes in well-being demonstrate a robust negative association with changes in anxiety across multiple types of assessment. The research design of the present study allowed us to establish that change in well-being does not occur linearly across time, but occurs primarily during the second half of treatment. Overall, the present findings suggest that not only does CBT reduce symptoms of mental illness, it increases positive aspects of mental health across both transdiagnostic and disorder specific treatments.

Clinical Impact Statement.

Question: Does CBT promote positive aspects of mental health as effectively as it reduces mental illness and how do changes in well-being relate to changes in symptoms during treatment?

Findings: Clinicians can monitor different aspects of flourishing mental health during CBT and expect improvements in those areas, which may be a marker of recovery from anxiety as well.

Meaning: CBT strongly increases different domains of well-being and increases in well-being during treatment appear to be strongly linked with anxiety symptom reduction.

Next Steps: Determine the causal influences of changes in well-being and changes in symptoms on one another during treatment and whether increases in well-being are consistent in other populations and forms of psychotherapy.

Acknowledgments

This research was supported by the National Institute of Mental Health (R01MH090053; PI D. H. Barlow). The funding agency had no role in the analysis or interpretation of the data. The authors have no conflicts of interest to disclose.

Footnotes

1 –

This clinical trial was designed prior to the publication of DSM-5, when OCD was still classified as an anxiety disorder.

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