The Bidirectional Relationship Between Sleep Disturbance and Exposure-Based Treatment for Social Anxiety Disorder: A Multi-Method Examination

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McGrory, Gary D. Fireman, Ryan M. Bottary, Natasha B. Lasko, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7121721/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 16 Sep, 2025 Read the published version in Cognitive Therapy and Research → Version 1 posted 7 You are reading this latest preprint version Abstract Background . Individuals with Social Anxiety Disorder (SAD) often experience poor sleep, which may influence treatment outcomes. Although theoretical models link sleep and fear extinction mechanisms, findings are equivocal and largely based on subjective measures. This study investigates the bidirectional relationship between sleep (duration, efficiency, quality) and outcomes from exposure-based SAD therapy. Methods . Participants (N = 32) with SAD completed five weeks of exposure-based group therapy. Daily sleep data (self-report and actigraphy) were collected pre-, during, and post-treatment. The Liebowitz Social Anxiety Scale (LSAS) assessed treatment outcomes. Multilevel modeling examined associations between sleep and treatment outcomes. Results . Treatment significantly impacted sleep such that nights after therapy were associated with reduced actigraphy-based sleep duration and participants with poor baseline sleep exhibited post-treatment improvements in sleep quality and efficiency (self-report and actigraphy). While poor baseline sleep quality and actigraphy sleep duration were associated with greater baseline symptoms, they did not predict changes across treatment. Sleep before and after exposure sessions also did not predict SAD symptoms. Conclusions . Findings suggest exposure-based SAD treatment influences sleep, particularly in poor sleepers, but that poor sleep does not hinder treatment efficacy. Additionally, clinicians may consider informing patients about potential post-exposure sleep disturbances to support engagement. cognitive-behavioral therapy exposure therapy social anxiety disorder sleep quality sleep duration actigraphy Figures Figure 1 Figure 2 Figure 3 1. Introduction 1.1 Sleep Disturbance and Social Anxiety Treatment Social anxiety disorder (SAD) is a common psychiatric disorder impacting up to 13% of the population, characterized by intense and persistent fear of social situations (Leichsenring & Leweke, 2017 ). Poor sleep is often found in individuals with SAD and has been proposed as a potential factor influencing treatment outcomes (Buckner et al., 2006; Kaczkurkin et al., 2021 ; Ramsawh et al., 2009 ), though associations are less robust in comparison to other anxiety disorders (Mellman, 2008 ). Sleep disturbances include any disruption to normal sleep patterns affecting the quality, quantity, or timing of sleep, and can be the result of insomnia, nightmares, medical conditions, genetics, substance use, or other lifestyle constraints. Notably, studies have found reports of insomnia (Buckner et al., 2008 ) and subjective sleep disturbances (Stein et al., 1993 ) in SAD, but no difference in PSG sleep architecture compared to healthy controls (Brown et al., 1994 ). Nevertheless, research has demonstrated that poor baseline sleep quality may predict poorer response to exposure-based therapies, though findings remain mixed (Dutcher et al., 2021 ; Horenstein et al., 2019; Kushnir et al., 2013; Zalta et al., 2013). While several studies have linked poor self-reported sleep quality to worse treatment outcomes, others have failed to detect this relationship, with explanations citing insufficient severity of sleep difficulties in study samples (Horenstein et al., 2019). No studies, however, have investigated objective measures of sleep and SAD treatment outcomes, leaving a significant gap in the literature that this investigation aims to address. Theoretical models of fear extinction—the neurobehavioral mechanism underlying exposure therapy—further underscore the importance of sleep in the context of SAD treatment. Sleep has been shown to play a crucial role in consolidating extinction memories and enhancing emotional regulation (Pace-Schott et al., 2015a , b ). Specifically, poor sleep quality after learning may impair these mechanisms, potentially reducing the efficacy of exposure-based interventions (Craske et al., 2008 ). Poor sleep quality before learning may impair the ability to encode new information, underscoring the potential negative impacts of poor sleep before exposure-based therapy (Kredlow et al., 2018 ). Notably, studies examining sleep around treatment sessions for SAD have provided mixed results. Zalta et al. (2013) found that better self-reported “restedness” the night after therapy predicted lower symptoms at the next session, whereas Dutcher et al. ( 2021 ) observed no such effect of sleep quality but reported that longer sleep duration the night before a session was linked to improved treatment response (Dutcher et al., 2021 ; Zalta et al., 2013). The original study from which the current investigation is derived hypothesized that post-exposure session naps would be associated with better treatment outcomes via improved extinction learning (Pace-Schott et al., 2018). However, their primary analysis, which tested for group-level differences in symptom change, found no significant differences in SAD symptom severity across experimental conditions. Notably, this analytical approach did not account for individual differences in baseline sleep characteristics, which may interact with symptom trajectory over time. Given the equivocal findings and reliance on subjective sleep measures in the existing literature, a critical next step is to employ both subjective and objective daily sleep assessments to explore the relationships among different types of sleep disturbance and exposure-based treatment for SAD. Therefore, the primary aim of this study was to further investigate the impact of sleep disturbances (i.e., sleep duration, sleep efficiency, and self-reported sleep quality) on treatment outcomes. These sleep indices were selected based on their relevance to the processes thought to influence treatment response such as emotion regulation (Palmer et al., 2017) and learning (Diekelmann et al., 2009 ). Additionally, sleep duration and efficiency capture distinct aspects of sleep and have been investigated in previous literature (e.g., Dutcher et al., 2021 ; Horenstein et al., 2019; Kushnir et al., 2013; Zalta et al., 2013). Importantly, including both subjective and objective measures allowed us to examine potential discrepancies between perceived and actual sleep. To our knowledge, this study is the first examination of the sleep-treatment relationship in SAD to comprehensively assess sleep quality and duration using both subjective self-reports and objective actigraphy data. 1.2 Exposure Therapy and Sleep While cognitive-behavioral therapy (CBT) for anxiety is widely effective in reducing anxiety symptoms, most studies do not report changes in sleep following such interventions, leaving a gap in understanding the broader impact of treatment on co-occurring sleep disturbances. A 2010 meta-analysis found a moderate effect of CBT for anxiety on sleep disturbances, though the authors noted the base of evidence "does not permit definitive conclusions" because only 2% of clinical trials investigating the impact of CBT on anxiety disorders also assess effects on sleep (Belleville et al., 2010 ). Given the well-established relationship between heightened anxiety and poorer sleep quality (Ramsawh et al., 2009 ), it stands to reason that reductions in anxiety could carry over to improvements in sleep. However, evidence suggests that sleep disturbances, such as subjective sleep quality, quantity, insomnia, and nightmares, as well as objective sleep data collected by PSG, often persist even after successful CBT for anxiety (Belleville et al., 2010 ). These findings underscore the need to directly examine whether targeted anxiety interventions, such as group CBT for SAD, influence co-occurring sleep disruptions. There is also reason to consider that the mechanisms underlying exposure-based CBT, the core component of SAD treatment, could acutely impact sleep in complex ways. Exposure therapy is effective due to its emotional intensity, designed to provoke distress and facilitate fear extinction through controlled confrontation with feared stimuli. This arousal, however, has also been shown to increase cognitive processes such as post-event-processing, or rumination, after therapy sessions for SAD (Edgar et al., 2024 ; Kocovski & Rector, 2008 ). Given the fact that rumination is a known mediator in the relationship between anxiety and sleep disturbances (Tousignant et al., 2019 ), heightened rumination following emotionally intense therapy sessions may contribute to disrupted sleep, even as global anxiety levels decline over the course of treatment. Communicating this unanticipated effect of therapy may help mitigate treatment dropout (Eskildsen et al., 2010 ; Hofmann & Suvak, 2006 ) and addressing residual sleep difficulties could be particularly important, as poor sleep has been linked to reduced treatment efficacy (Dutcher et al., 2021 ; Zalta et al., 2013). Accordingly, the secondary aim of this study was to assess the effect of exposure-based SAD therapy on sleep. To comprehensively examine this relationship, changes in both global self-reported sleep quality across the intervention and sleep duration and efficiency on the night following therapy sessions were assessed. This dual approach offers preliminary evidence on whether exposure therapy influences both long-term sleep patterns and acute sleep disruptions, contributing to a more nuanced understanding of the bidirectional relationship between anxiety treatment and sleep. Based on previous literature, to investigate our primary aim, we hypothesized that 1) pre-treatment sleep measures (self-reported and actigraphy-based sleep duration and sleep efficiency) would predict outcomes such that those with poorer sleep would evidence higher symptom severity across treatment; 2a) average sleep efficiency and duration the night before therapy sessions would be related to better treatment outcomes across treatment; and 2b) average sleep efficiency and duration the night after therapy sessions would be associated with better treatment outcomes. To test our second aim investigating the impact of exposure therapy on sleep, we hypothesized that 3) post-treatment sleep measures would be significantly improved compared to pre-treatment levels for poor sleepers (baseline PSQI > 5); and 4) sleep efficiency and duration will be poorer on the night following therapy relative to the average of the previous week. 2. Methods 2.1 Participants Participants (N = 32) were adults aged 18–39 (mean = 26 years, SD = 6.26, 18 females) who participated in a randomized clinical trial testing the effects of post-exposure naps on exposure therapy for SAD (Pace-Schott et al., 2018). To be eligible, participants had to be 18 years of age or older, meet all criteria for DSM-IV-TR SAD, and have a Liebowitz Social Anxiety Scale (LSAS) score of at least 60. Exclusion criteria included potentially confounding medical, sleep, neurological, substance use, or severe psychiatric illnesses (see Pace-Schott et al., 2018 supplementary methods for details). All study procedures accorded with the Declaration of Helsinki and were approved by the Partners Healthcare Institutional Review Board. All participants provided written informed consent, received group treatment free of charge, and were compensated for participation. 2.2 Procedures Details regarding the protocol are described in Pace-Schott et al. (2018) and associated supplementary material. All participants completed a telephone screening followed by psychiatric and sleep-disorders screening interviews. Eligible participants then completed a baseline assessment with an independent evaluator blind to condition and a battery of self-report measures before beginning an evidence-based and validated standardized 5-week exposure-based, group therapy for SAD (Hofmann, 2004 ; Hofmann et al., 2006 ; Smits et al., 2020 ). Treatment consisted of five 90-min weekly sessions led by the same two clinical psychologists for all participants. The protocol began with one psychoeducational session followed by four public speaking exposures during which extinction learning could take place. Before the third therapy session, participants were randomized in blind fashion to either the Nap (N = 17, 9 females) or Wake (N = 15, 9 females) condition who had, or didn’t have a 120-min sleep opportunity, respectively, following their third and fourth treatment sessions. At approximately 14:30 all participants were instrumented to undergo polysomnography, although the Wake group watched two episodes of Planet Earth rather than nap. Throughout the entire protocol (1-week pre-treatment, 5 weeks of treatment, 1-week post-treatment), participants completed daily sleep diaries every morning and evening (see Pace-Schott et al., 2018 supplementary materials) and wore the Actiwatch 2 (Phillips Respironics, Bend, OR). At pre-, mid- (i.e., between sessions 3 and 4), and post-treatment, participants completed social anxiety symptom measures. At pre- and post-treatment, participants completed a retrospective sleep quality assessment along with a battery of self-report measures. 2.3 Measures Retrospective Sleep Quality. The Pittsburgh Sleep Quality Index (PSQI, Buysse et al., 1989 ) is the most widely used self-report assessment of sleep quality and consists of 19 items encompassing 7 sleep-quality factors over the past month. It has demonstrated good internal consistency (α = 0.83), test-retest reliability, and construct validity (Buysse et al., 1989 ; Carpenter & Andrykowski, 1998 ). Higher scores indicate poorer sleep quality and a clinical cutoff score of greater than 5 has been established to distinguish good from poor sleepers. The PSQI was administered at pre- and post-treatment only. Prospective Sleep Duration and Efficiency. The present study investigated actigraphy-based and self-reported sleep duration (total sleep time, TST) and sleep efficiency (SE). Self-reported sleep was recorded using the Evening-Morning Sleep Questionnaire (EMSQ, Pace-Schott et al., 1994 ) administered each morning to ask about the previous night of sleep and each evening to ask about daytime activities influencing sleep (e.g., napping, caffeine). Objective sleep was captured nightly using the Actiwatch 2 (Philips Respironics, Bend, OR) device. Subjects were instructed to press the Actiwatch 2 event marker when beginning to attempt sleep and upon waking. Time stamps inserted by the event button served as demarcation of the subject’s time-in-bed within which the default Actiware 5.61 algorithm determined TST, sleep onset latency (SOL), and SE. Given the documented limitations of actigraphy devices (Grandner & Rosenberger, 2019 ), all data were reviewed using the rules below. Missing actigraphy data were not imputed, as variability in sleep metrics over time was a primary outcome of interest. Given that missingness was determined by predefined quality-control criteria rather than occurring at random, imputation would risk introducing bias by assuming stable sleep patterns where variability was expected. If actigraphy TST was 2-hour discrepancy between actigraphy SOL and self-report SOL, the night of data was removed. If actigraphy SE was 20% discrepancy with self-report, the night of data was removed. A minimum of 3 nights was required to calculate a weekly average. Treatment Outcome . The Liebowitz Social Anxiety Scale (LSAS, Liebowitz, 1987 ) and Clinician Global Impression scale (CGI, Guy, 1976 ) were used to assess symptom severity at pre-, mid-, and post-treatment timepoints. The LSAS is a 48-item clinician-administered scale that assesses the severity of social anxiety symptoms by asking participants about their level of fear and avoidance in social and performance situations. It has excellent internal consistency (α = .96), strong convergent validity with other social anxiety scales, and is sensitive to changes across treatment (Heimberg et al., 1999). The CGI is a single-item clinician-rated tool that quantifies overall clinical severity on a 1 (“normal, not at all ill”) to 7 (“extremely ill”) scale and has been validated with individuals with SAD receiving treatment (Zaider et al., 2003 ). 2.4 Statistical Analysis Multilevel modeling (MLM) was used to analyze the data. For Hypotheses 1, we assessed changes in LSAS over time from pre- to mid- to post-treatment and its relationship with baseline sleep predictors while controlling for baseline LSAS, CGI, and treatment Condition (nap vs. wake). For Hypothesis 2 , we used multilevel modeling to examine whether participants’ average SE and TST on nights before and after sessions predicted social anxiety symptoms across treatment (i.e., pre-, mid-, and post-treatment). Separate models were run for each sleep variable and each time window (pre-session, post-session). For Hypothesis 3 , we examined the effects of Time on sleep measures. Finally, for Hypothesis 4 , we used multilevel modeling to compare nightly sleep on therapy nights versus non-therapy nights across the treatment period. Specifically, we modeled self-reported and actigraphy-derived TST and SE as outcomes, with a dichotomous variable (therapy night vs. average of past week) as the key predictor. For all analyses, we included a random intercept for participant ID to account for within-subject correlations across repeated measures. All analyses were conducted in R version 2024.12.0. Model selection We compared several growth curve models for the trajectory of social anxiety symptoms (LSAS) over time. In line with findings from prior research (Horenstein et al., 2019; Kushnir et al., 2013; Zalta et al., 2013), which suggested linear symptom change over time, we utilized a linear model for our primary analyses. While the quadratic model showed marginally lower AIC and BIC values, the three measurement occasions impose constraints on the ability to robustly estimate non-linear trends. Although model fit indices marginally favored the quadratic model, visual inspection and theoretical considerations led us to prioritize the linear model, treating the quadratic trend as exploratory. No results reported below differed when using the quadratic growth model. 3. Results Sample demographics were largely representative of the city where data were collected (US Census Bureau), with most identifying as female (56%) and White (40.6%), and others identifying as Asian (25%), Black or African American (15.6%), and more than one race (12.5%). A minority of participants identified as Hispanic or Latine (21.9%). Means, SDs, and correlations for baseline variables are presented in Table 1 . Participants reported an average baseline global PSQI score of 5.06 (SD = 3.15, range: 0–13), with 34% of the sample (n = 11) identified as “poor” sleepers (PSQI > 5). As expected, self-reported (LSAS) and clinician assessed (CGI) symptom severity scores were highly correlated (p = .88). Self-reported sleep quality (PSQI) was correlated with both self-reported SE ( p = − .57) and actigraphy SE ( p = − .43) but not TST. Consistent with the literature, self-reported SE and actigraphy SE were also not correlated (Campanini et al., 2017 ; Lehrer et al., 2022 ). Table 1 Primary study variables at baseline Mean SD LSAS CGI PSQI Acti- TST SR- TST Acti- SE LSAS 85.33 17.75 CGI 5.39 1.05 .88** PSQI 5.06 3.15 .33 .24 Acti-TST 362.76 61.30 .09 .07 − .24 SR-TST 436.27 53.29 − .05 − .01 .066 .50** Acti-SE 77.88 10.42 .19 .17 − .43* .67** − .02 SR-SE 93.23 4.46 − .15 − .04 − .57** − .003 .12 .34 Note : Acti = actigraphy; CGI = Clinical Global Impression; LSAS = Liebowitz Social Anxiety Scale; PSQI = Pittsburgh Sleep Quality Index; SE = sleep efficiency; SR = self-report; TST = total sleep time. * p < .05, ** p < .01 Hypothesis 1 Relationship between baseline sleep and SAD treatment outcomes. In contrast to our hypothesis, while poorer baseline PSQI (Fig. 1 ) and actigraphy-TST predicted higher levels of SAD symptoms at baseline ( β = 1.50, t (50) = 2.04, p = .047 and β = 0.08, t(45) = 2.00, p = .05, respectively), these sleep measures did not predict LSAS symptoms across treatment ( p ’s > .52). Similarly, no other sleep measure (SR-TST, actigraphy-SE, SR-SE) yielded a significant association with LSAS over time. While Condition was included in the model as a control, results revealed a significant Condition main effect, such that participants in the Nap condition had LSAS scores at mid- and post-treatment that were significantly higher than the Wake group when controlling for baseline LSAS and CGI ( p ’s = .01 − .05). Hypothesis 2 Relationship between pre- and post-exposure session sleep and SAD treatment outcomes. In contrast to our hypothesis, no significant effects of either pre- or post-exposure session TST and SE on LSAS symptom severity over time were found. Descriptively, we found no differences between the effect sizes or significance levels of self-report measures ( p ’s = .25 − .76) and actigraphy measures ( p ’s = .28 − .61). Hypothesis 3 Effect of exposure-based therapy for SAD and on sleep quality. A binary baseline PSQI Group variable was created to divide the sample into good (PSQI ≤ 5) and poor sleep (PSQI > 5) groups based on their initial PSQI. Analyses found no main effect of Time on PSQI scores, indicating no significant overall change in PSQI scores between the two administration time points at pre- and post-treatment across the entire sample. However, in support of our hypothesis, there were significant interactions such that poor sleepers improved in PSQI sleep quality, self-reported SE, and actigraphy-based SE from pre- to post-treatment. Specifically, there was a significant Time × PSQI interaction such that poor sleepers saw a significant decrease in PSQI scores from pre- to post-treatment, β = -2.89, t (57) = -2.92, p < .01 (Fig. 2 ). In separate models, there were also significant interactions for actigraphy SE ( β = 5.41, t (52) = 2.45, p = .02) and self-reported SE ( β = 3.59, t (55) = 3.08, p < .01). This was not found for the models investigating changes in actigraphy TST ( β = 17.87, t (52) = .99, p = .33) or self-reported TST ( β = 16.48, t (55) = 1.02, p = .31). Hypothesis 4 Effect of SAD therapy sessions on sleep quality and duration that evening. In support of our hypothesis, results revealed a significant main effect of Session-Night on actigraphy TST, indicating objective sleep duration was significantly shorter on therapy nights compared to the previous week average, β = -26.48, t (237) = -2.75, p < .01 (Fig. 3 ). The main effect of Condition was not significant ( β = -15.78, t (36) = -0.76, p = .45). However, the significant Session-Night × Condition interaction ( β = 33.83, t (237) = 2.56, p = .01) revealed TST on therapy nights was even shorter for individuals in the nap condition compared to the wake condition. While there was no main effect of Session-Night on SR-TST, actigraphy-SE, or SR-SE, there was a trend level effect for Session in all models except SR-SE, such that sleep duration and efficiency decreased across the sessions ( p ’s = .06 − .09). 4. Discussion The present study investigated the bidirectional relationship between sleep difficulties and treatment outcomes in group exposure-based therapy for SAD. Inconsistent with our hypotheses, baseline global sleep quality, measured by the Pittsburgh Sleep Quality Index (PSQI), did not predict social anxiety symptoms over time, with poorer baseline sleep quality only associated with greater symptom severity at baseline. While objective TST followed a similar pattern, other actigraphy-based and self-report sleep measures did not significantly predict baseline symptom severity or symptom changes. Also contrary to our hypotheses, pre- and post-session sleep measures were not significantly related to symptom trajectories. Regarding the effects of exposure-based therapy on sleep outcomes, we observed significant improvements in sleep quality and sleep efficiency at post-treatment among individuals with poor baseline sleep, though therapy nights were associated with a significant reduction in actigraphy-based sleep duration relative to the weekly average. In line with findings from Horenstein and colleagues (2019), poorer baseline sleep quality, as well as lower sleep duration and efficiency, did not predict greater symptom severity over the course of treatment. This challenges the idea that sleep difficulties necessarily reduce the effectiveness of exposure-based therapy for SAD (Dutcher et al., 2021 ; Zalta et al., 2013). Although theoretical models suggest that sleep disruption impairs emotional regulation (Watling et al., 2017 ), fear extinction (Straus et al., 2017 ), and cognitive flexibility (Stickgold & Walker, 2013 ), our results suggest a more complex picture in practice. Specifically, while individuals with poorer sleep reported more severe social anxiety symptoms at baseline, this did not translate into poorer treatment response, as evidenced by non-significant Time × Sleep interactions. This contrasts two previous studies which reported that poor baseline sleep quality predicted worse post-treatment outcomes (Dutcher et al., 2021 ; Zalta et al., 2013). One possible explanation, as Horenstein et al. proposed, is that sleep difficulties may need to reach a higher severity threshold before they begin to meaningfully interfere with mechanisms like attention, flexibility, and learning during treatment. In our sample, due to the exclusion criteria preventing individuals with moderate to severe insomnia from participating, the sleep disturbances are perhaps too mild to influence the trajectory of symptoms across treatment. As such, future investigations with adequately powered samples consisting of individuals with SAD and co-occurring sleep disturbances are needed. Additionally, long-term follow-up timepoints will be important to include in order to capture any relationships between sleep and long-term treatment gains or remission. Interestingly, while the experimental condition was originally included as a covariate, a significant main effect of Condition emerged. Findings indicate that participants randomized to the nap condition exhibited higher SAD symptoms over time than those in the wake condition, despite the prior ANOVA-based analysis that found no significant Condition × Time interaction (Pace-Schott et al., 2018). This discrepancy may stem from differences in analytical approach—while the ANOVA tested for whether the pattern of symptom change differed on average from pre- to post-treatment between groups, our regression model accounted for individual variability in baseline symptom severity and sleep characteristics and included an additional mid-treatment time point. The inclusion of this third time point may have provided greater sensitivity to individual variability, which would explain why the Condition effect emerged in our analysis. These findings suggest that post-exposure naps may influence treatment response in a way that was not captured by the original group-level analysis, potentially interacting with baseline sleep and symptom characteristics to shape symptom progression. Future research should further investigate these dynamics to provide a clearer understanding of these relationships. Contrary to our hypotheses, neither pre-session nor post-session sleep duration or efficiency significantly predicted treatment outcomes. Although previous research suggests that poor sleep prior to learning may impair forming emotional memories (Harvey et al., 2014 ) and post-session sleep may be critical for consolidation (Krause et al., 2017), our findings suggest that single-night variations in sleep may be less influential than cumulative sleep patterns over time. Findings also support the notion that extinction learning and memory consolidation are iterative processes occurring across multiple nights, and that cumulative sleep debt may exert a greater influence on treatment outcomes than any single night of disrupted sleep. While these findings appear to contrast existing research suggesting sleep duration the night before therapy (Dutcher et al., 2021 ) and greater “restedness” the night after therapy (Zalta et al., 2013) are significantly associated with symptom severity, methods across studies differed. Specifically, these investigations measured symptoms session by session, and we examined pre-, mid-, and post-treatment timepoints. While overall PSQI scores did not significantly change across the sample, potentially explained by the limited number of participants experiencing poor sleep before treatment, a significant interaction indicated that individuals classified as poor sleepers at baseline (PSQI > 5) experienced significant improvements in global sleep quality and sleep efficiency (both self-report and actigraphy-based) at post-treatment. This finding suggests that exposure therapy for SAD may have secondary benefits for sleep among those with initial disturbances. However, it is also possible that improvements in sleep quality were driven by increased awareness and regulation of sleep patterns due to sleep monitoring. This phenomenon has been documented (Ojalvo et al., 2023 ) but is not universal across the literature and was notably not found in a study that utilized actigraphy and daily sleep diary akin to the procedures in the present investigation (Eigl et al., 2023 ). Future research should disentangle whether these improvements result from reductions in social anxiety symptoms or the effects of sleep tracking itself. Lastly, our results revealed a significant reduction in actigraphy-measured TST on therapy nights compared to the weekly average, supporting the hypothesis that exposure therapy induces short-term sleep disturbances, possibly due to heightened emotional and physiological arousal. Although other sleep parameters did not show significant changes, trend-level effects indicated a general pattern of reduced sleep duration and efficiency across therapy sessions. These findings suggest that as the exposures get more challenging across treatment, as is standard practice in the exposure-based protocol, there was even greater sleep disturbance. Although it could be hypothesized that exposure therapy elicits temporary autonomic and cognitive arousal, which may disrupt sleep on the night of treatment, future research is needed to assess the mechanism underlying this relationship and if this pattern is found in exposure therapies for other conditions. Additionally, the clinical significance of these transient sleep disturbances remains unclear, as they may not necessarily impede long-term therapeutic gains (per results of hypothesis 2 ). Regardless, clinicians should be aware that sleep disturbances the night of exposure sessions is a potential side-effect and consider informing clients to guard against discouragement and treatment dropout. This investigation is not without limitation. First, the results of this secondary analysis should be interpreted in the context of the relatively small sample size (n = 32), which may limit the ability to detect smaller effects and may have contributed to trend level findings. All covariates were theoretically driven and aligned with previous literature, although they may increase the likelihood of type II error. Additionally, while participants with a sleep disorder other than mild insomnia or delayed sleep phase disorder were excluded, participants did not complete baseline measures of insomnia. Similarly, although current major depressive disorder was an exclusion criterion, baseline measures of depression were not collected and therefore not controlled for in analyses. Excluding participants for comorbid depression and moderate to severe insomnia, both of which frequently co-occur with SAD (Buckner et al., 2008 ), may limit generalizability of our findings to more severe SAD clinical populations. It is also possible that other covariates not accounted for contributed to sleep quality, duration, efficiency, and symptom severity. This study is also limited by the fact that symptom severity was only assessed at pre-, mid-, and post-treatment. Session-by-session measures and a longer follow-up timepoint, if collected, may better reveal the relationship between sleep and social anxiety outcomes across treatment. Lastly, the correlational approach limits causal inferences that can be made. In sum, the current investigation makes a novel contribution to the literature as the first, to our knowledge, to measure nightly sleep using both subjective self-reports and objective measures (i.e., actigraphy) across an exposure-based SAD treatment. Notably, findings suggest that therapy sessions may acutely disrupt sleep, with participants sleeping less on nights following exposures, and that individuals with poor baseline sleep experience improvements in sleep quality and efficiency after completing treatment. While poorer baseline sleep was associated with greater symptom severity before treatment, it did not predict changes in symptoms over time. Similarly, neither subjective nor objective measures of sleep before or after treatment sessions predicted outcomes. Future research is needed to better elucidate these relationships, as well as replicate findings on acute sleep disruption and post-treatment improvements among poor sleepers. Declarations Author Contribution C.M.: Writing – original draft, Data Curation, Formal analysis, Visualization, Conceptualization; G.F.: Writing – review and editing, Supervision; R.B.: Project Administration, Resources, Data Curation; N.L.: Resources; N.S.: Conceptualization, Resources; A.B.: Resources; G.L.: Writing – review and editing; E.P-S: Conceptualization, Methodology, Writing - review and editing, Funding acquisition, Supervision Data Availability The data that support the findings of this study are not openly available due to reasons of sensitivity and are available from the corresponding author upon reasonable request. Data are located in controlled access data storage at Massachusetts General Brigham. References Belleville, G., Cousineau, H., Levrier, K., St-Pierre-Delorme, M. E., & Marchand, A. (2010). The impact of cognitive-behavior therapy for anxiety disorders on concomitant sleep disturbances: a meta-analysis. 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A., & Smith, R. (2014). Improving Outcome of Psychosocial Treatments by Enhancing Memory and Learning. Perspectives on Psychological Science , 9(2), 161-179. Heimberg, R. G., Horner, K. J., Juster, H. R., Safren, S. A., Brown, E. J., Schneier, F. R., & Liebowitz, M. R. (1999). Psychometric properties of the Liebowitz social anxiety scale. Psychological Medicine , 29 (1), 199-212. Hofmann, S. G. (2004). Exposure Therapy for Social Anxiety Disorder (unpublished treatment manual). Hofmann, S. G., Meuret, A. E., Smits, J. A., Simon, N. M., Pollack, M. H., Eisenmenger, K., ... & Otto, M. W. (2006). Augmentation of exposure therapy with D-cycloserine for social anxiety disorder. Archives of General Psychiatry , 63(3), 298-304. Hofmann, S. G., & Suvak, M. (2006). Treatment attrition during group therapy for social phobia. Journal of Anxiety Disorders , 20(7), 961-972. Horenstein, A., Morrison, A. S., Goldin, P., Ten Brink, M., Gross, J. J., & Heimberg, R. G. (2019). Sleep quality and treatment of social anxiety disorder. Anxiety, Stress, Coping , 32(4), 387-398. Kaczkurkin, A. N., Tyler, J., Turk-Karan, E., Belli, G., & Asnaani, A. (2021). The Association between Insomnia and Anxiety Symptoms in a Naturalistic Anxiety Treatment Setting. Behavioral Sleep Medicine , 19(1), 110–125. Kocovski, N. L., & Rector, N. A. (2008). Post-event processing in social anxiety disorder: Idiosyncratic priming in the course of CBT. Cognitive Therapy and Research , 32 , 23-36. Krause, A. J., Simon, E. B., Mander, B. A., Greer, S. M., Saletin, J. M., Goldstein-Piekarski, A. N., & Walker, M. P. (2017). The sleep-deprived human brain. Nature Reviews Neuroscience , 18 (7), 404-418. Kredlow, M. A., Eichenbaum, H., & Otto, M. W. (2018). Memory creation and modification: Enhancing the treatment of psychological disorders. American Psychologist , 73 (3), 269. Kushnir, J., Marom, S., Mazar, M., Sadeh, A., & Hermesh, H. (2014). The link between social anxiety disorder, treatment outcome, and sleep difficulties among patients receiving cognitive behavioral group therapy. Sleep Medicine , 15(5), 515-521. Lehrer, H. M., Yao, Z., Krafty, R. T., Evans, M. A., Buysse, D. J., Kravitz, H. M., ... & Hall, M. H. (2022). Comparing polysomnography, actigraphy, and sleep diary in the home environment: The Study of Women’s Health Across the Nation (SWAN) Sleep Study. Sleep Advances, 3(1), zpac001. Leichsenring, F., & Leweke, F. (2017). Social anxiety disorder. New England Journal of M edicine , 376 (23), 2255-2264. Liebowitz, M. R. (1987). Liebowitz social anxiety scale. Journal of Anxiety Disorders . Mellman, T. A. (2008). Sleep and anxiety disorders. Sleep Medicine Clinics , 3(2), 261-268. Ojalvo, D., Pacheco, A. P., & Benedict, C. (2023). A useful tool or a new challenge? Hand‐wrist‐worn sleep trackers in patients with insomnia. Journal of Sleep Research , 32 (5), e13883. Pace-Schott, E. F., Kaji, J., Stickgold, R., & Hobson, J. A. (1994). Nightcap measurement of sleep quality in self-described good and poor sleepers. Sleep , 17(8), 688-692. Pace-Schott, E. F., Germain, A., & Milad, M. R. (2015a). Effects of sleep on memory for conditioned fear and fear extinction. Psychological Bulletin , 141(4), 835. Pace-Schott, E. F., Germain, A., & Milad, M. R. (2015b). Sleep and REM sleep disturbance in the pathophysiology of PTSD: the role of extinction memory. Biology of Mood & Anxiety Disorders , 5, 1-19. Pace-Schott, E. F., Bottary, R. M., Kim, S. Y., Rosencrans, P. L., Vijayakumar, S., Orr, S. P., ... & Simon, N. M. (2018). Effects of post-exposure naps on exposure therapy for social anxiety. Psychiatry Research , 270, 523-530. Palmer, C., Bower, J., Cho, K., Clementi, M., Lau, S., Oosterhoff, B., & Alfano, C. (2023). Sleep loss and emotion: A systematic review and meta-analysis of over 50 years of experimental research. Psychological Bulletin. Ramsawh, H. J., Stein, M. B., Belik, S. L., Jacobi, F., & Sareen, J. (2009). Relationship of anxiety disorders, sleep quality, and functional impairment in a community sample. Journal of Psychiatric Research , 43(10), 926-933. Smits, J. A., Pollack, M. H., Rosenfield, D., Otto, M. W., Dowd, S., Carpenter, J., ... & Hofmann, G. (2020). Dose timing of D-cycloserine to augment exposure therapy for social anxiety disorder: a randomized clinical trial. JAMA Network Open , 3(6), e206777- e206777. Stein, M. B., Kroft, C. D., & Walker, J. R. (1993). Sleep impairment in patients with social phobia. Psychiatry Research, 49(3), 251-256. Stickgold, R., & Walker, M. P. (2013). Sleep-dependent memory triage: evolving generalization through selective processing. Nature Neuroscience , 16 (2), 139-145. Straus, L. D., Acheson, D. T., Risbrough, V. B., & Drummond, S. P. (2017). Sleep deprivation disrupts recall of conditioned fear extinction. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging , 2 (2), 123-129. Tousignant, O. H., Taylor, N. D., Suvak, M. K., & Fireman, G. D. (2019). Effects of rumination and worry on sleep. Behavior Therapy , 50(3), 558-570. S. Census Bureau QuickFacts: Boston, Massachusetts . United States Census Bureau. 2023). https://www.census.gov/quickfacts/fact/table/bostoncitymassachusetts/ PST045223 Watling, J., Pawlik, B., Scott, K., Booth, S., & Short, M. A. (2017). Sleep loss and affective functioning: more than just mood. Behavioral Sleep Medicine , 15 (5), 394-409. Zaider, T. I., Heimberg, R. G., Fresco, D. M., Schneier, F. R., & Liebowitz, M. R. (2003). Evaluation of the clinical global impression scale among individuals with social anxiety disorder. Psychological Medicine , 33(4), 611-622. Zalta, A. K., Dowd, S., Rosenfield, D., Smits, J. A., Otto, M. W., Simon, N. M., ... & Pollack, M. H. (2013). Sleep quality predicts treatment outcome in CBT for social anxiety disorder. Depression and Anxiety , 30(11), 1114-1120. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 16 Sep, 2025 Read the published version in Cognitive Therapy and Research → Version 1 posted Editorial decision: Revision requested 01 Aug, 2025 Reviews received at journal 25 Jul, 2025 Reviewers agreed at journal 16 Jul, 2025 Reviewers invited by journal 16 Jul, 2025 Editor assigned by journal 16 Jul, 2025 Submission checks completed at journal 16 Jul, 2025 First submitted to journal 14 Jul, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7121721","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":488128702,"identity":"108fe878-d135-4143-9bb1-d9fde9dcac44","order_by":0,"name":"Christopher M. McGrory","email":"data:image/png;base64,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","orcid":"","institution":"Suffolk University","correspondingAuthor":true,"prefix":"","firstName":"Christopher","middleName":"M.","lastName":"McGrory","suffix":""},{"id":488128703,"identity":"8d961edd-7e54-444a-89f9-fe59b616fbb8","order_by":1,"name":"Gary D. Fireman","email":"","orcid":"","institution":"Suffolk University","correspondingAuthor":false,"prefix":"","firstName":"Gary","middleName":"D.","lastName":"Fireman","suffix":""},{"id":488128704,"identity":"ed1f6f27-6baf-43f8-bd04-8afa9f26494d","order_by":2,"name":"Ryan M. Bottary","email":"","orcid":"","institution":"Widener University","correspondingAuthor":false,"prefix":"","firstName":"Ryan","middleName":"M.","lastName":"Bottary","suffix":""},{"id":488128705,"identity":"4b1678a8-3ca7-427a-846c-4fd138507faf","order_by":3,"name":"Natasha B. Lasko","email":"","orcid":"","institution":"Massachusetts General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Natasha","middleName":"B.","lastName":"Lasko","suffix":""},{"id":488128706,"identity":"842ca08b-166e-4ed9-be8c-3a15c7371ac9","order_by":4,"name":"Naomi M. Simon","email":"","orcid":"","institution":"New York University","correspondingAuthor":false,"prefix":"","firstName":"Naomi","middleName":"M.","lastName":"Simon","suffix":""},{"id":488128707,"identity":"ff021bfe-cd38-4ea3-bef2-96333f4fa4c1","order_by":5,"name":"Amanda W. Baker","email":"","orcid":"","institution":"Massachusetts General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Amanda","middleName":"W.","lastName":"Baker","suffix":""},{"id":488128708,"identity":"d7259a7b-00ae-4897-9dba-05d8e5f72545","order_by":6,"name":"Gabriele I. Liverant","email":"","orcid":"","institution":"Suffolk University","correspondingAuthor":false,"prefix":"","firstName":"Gabriele","middleName":"I.","lastName":"Liverant","suffix":""},{"id":488128709,"identity":"70103c96-9606-4617-bb11-f7bda31a84f9","order_by":7,"name":"Edward F. Pace-Schott","email":"","orcid":"","institution":"Massachusetts General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Edward","middleName":"F.","lastName":"Pace-Schott","suffix":""}],"badges":[],"createdAt":"2025-07-14 13:38:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7121721/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7121721/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s10608-025-10664-4","type":"published","date":"2025-09-16T15:56:50+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":87371133,"identity":"f00815c6-39a6-4472-acd5-1ca01cace9f7","added_by":"auto","created_at":"2025-07-23 07:10:16","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":225170,"visible":true,"origin":"","legend":"\u003cp\u003eLSAS score over time by PSQI group. Poor sleepers represent participants with a pre-treatment global PSQI \u0026gt; 5. Good sleepers represent participants with a pre-treatment global PSQI ≤ 5. Error bars represent standard error\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7121721/v1/f30ccab6a40ad2278a8a7cb9.png"},{"id":87371135,"identity":"783b843d-bfd2-4be0-bca6-de5e9b35d5ce","added_by":"auto","created_at":"2025-07-23 07:10:16","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":125519,"visible":true,"origin":"","legend":"\u003cp\u003ePSQI scores across time by sleep quality. Poor sleepers represent participants with a pre-treatment global PSQI \u0026gt; 5. Good sleepers represent participants with a pre-treatment global PSQI ≤ 5. Error bars represent standard error\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7121721/v1/bace60c0521ff626fb88153c.png"},{"id":87369603,"identity":"34d81ad6-1748-42b4-9f44-9258a2adfc75","added_by":"auto","created_at":"2025-07-23 07:02:16","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":225170,"visible":true,"origin":"","legend":"\u003cp\u003eLSAS score over time by PSQI group. Poor sleepers represent participants with a pre-treatment global PSQI \u0026gt; 5. Good sleepers represent participants with a pre-treatment global PSQI ≤ 5. Error bars represent standard error\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7121721/v1/54ac250052c08e797a29e34a.png"},{"id":91889860,"identity":"514cbeba-4473-495b-b72e-2c83c4d51763","added_by":"auto","created_at":"2025-09-22 16:02:52","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1016037,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7121721/v1/778cfd8a-668b-4ea8-8189-993781361831.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Bidirectional Relationship Between Sleep Disturbance and Exposure-Based Treatment for Social Anxiety Disorder: A Multi-Method Examination","fulltext":[{"header":"1. Introduction","content":"\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e\u003ch2\u003e1.1 Sleep Disturbance and Social Anxiety Treatment\u003c/h2\u003e\u003cp\u003eSocial anxiety disorder (SAD) is a common psychiatric disorder impacting up to 13% of the population, characterized by intense and persistent fear of social situations (Leichsenring \u0026amp; Leweke, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Poor sleep is often found in individuals with SAD and has been proposed as a potential factor influencing treatment outcomes (Buckner et al., 2006; Kaczkurkin et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Ramsawh et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), though associations are less robust in comparison to other anxiety disorders (Mellman, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Sleep disturbances include any disruption to normal sleep patterns affecting the quality, quantity, or timing of sleep, and can be the result of insomnia, nightmares, medical conditions, genetics, substance use, or other lifestyle constraints. Notably, studies have found reports of insomnia (Buckner et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) and subjective sleep disturbances (Stein et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e1993\u003c/span\u003e) in SAD, but no difference in PSG sleep architecture compared to healthy controls (Brown et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e1994\u003c/span\u003e). Nevertheless, research has demonstrated that poor baseline sleep quality may predict poorer response to exposure-based therapies, though findings remain mixed (Dutcher et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Horenstein et al., 2019; Kushnir et al., 2013; Zalta et al., 2013). While several studies have linked poor self-reported sleep quality to worse treatment outcomes, others have failed to detect this relationship, with explanations citing insufficient severity of sleep difficulties in study samples (Horenstein et al., 2019). No studies, however, have investigated objective measures of sleep and SAD treatment outcomes, leaving a significant gap in the literature that this investigation aims to address.\u003c/p\u003e\u003cp\u003eTheoretical models of fear extinction\u0026mdash;the neurobehavioral mechanism underlying exposure therapy\u0026mdash;further underscore the importance of sleep in the context of SAD treatment. Sleep has been shown to play a crucial role in consolidating extinction memories and enhancing emotional regulation (Pace-Schott et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2015a\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003eb\u003c/span\u003e). Specifically, poor sleep quality after learning may impair these mechanisms, potentially reducing the efficacy of exposure-based interventions (Craske et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Poor sleep quality before learning may impair the ability to encode new information, underscoring the potential negative impacts of poor sleep before exposure-based therapy (Kredlow et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Notably, studies examining sleep around treatment sessions for SAD have provided mixed results. Zalta et al. (2013) found that better self-reported \u0026ldquo;restedness\u0026rdquo; the night after therapy predicted lower symptoms at the next session, whereas Dutcher et al. (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) observed no such effect of sleep quality but reported that longer sleep duration the night before a session was linked to improved treatment response (Dutcher et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Zalta et al., 2013).\u003c/p\u003e\u003cp\u003eThe original study from which the current investigation is derived hypothesized that post-exposure session naps would be associated with better treatment outcomes via improved extinction learning (Pace-Schott et al., 2018). However, their primary analysis, which tested for group-level differences in symptom change, found no significant differences in SAD symptom severity across experimental conditions. Notably, this analytical approach did not account for individual differences in baseline sleep characteristics, which may interact with symptom trajectory over time.\u003c/p\u003e\u003cp\u003eGiven the equivocal findings and reliance on subjective sleep measures in the existing literature, a critical next step is to employ both subjective and objective daily sleep assessments to explore the relationships among different types of sleep disturbance and exposure-based treatment for SAD. Therefore, the primary aim of this study was to further investigate the impact of sleep disturbances (i.e., sleep duration, sleep efficiency, and self-reported sleep quality) on treatment outcomes. These sleep indices were selected based on their relevance to the processes thought to influence treatment response such as emotion regulation (Palmer et al., 2017) and learning (Diekelmann et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Additionally, sleep duration and efficiency capture distinct aspects of sleep and have been investigated in previous literature (e.g., Dutcher et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Horenstein et al., 2019; Kushnir et al., 2013; Zalta et al., 2013). Importantly, including both subjective and objective measures allowed us to examine potential discrepancies between perceived and actual sleep. To our knowledge, this study is the first examination of the sleep-treatment relationship in SAD to comprehensively assess sleep quality and duration using both subjective self-reports and objective actigraphy data.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e1.2 Exposure Therapy and Sleep\u003c/h2\u003e\u003cp\u003eWhile cognitive-behavioral therapy (CBT) for anxiety is widely effective in reducing anxiety symptoms, most studies do not report changes in sleep following such interventions, leaving a gap in understanding the broader impact of treatment on co-occurring sleep disturbances. A 2010 meta-analysis found a moderate effect of CBT for anxiety on sleep disturbances, though the authors noted the base of evidence \"does not permit definitive conclusions\" because only 2% of clinical trials investigating the impact of CBT on anxiety disorders also assess effects on sleep (Belleville et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Given the well-established relationship between heightened anxiety and poorer sleep quality (Ramsawh et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), it stands to reason that reductions in anxiety could carry over to improvements in sleep. However, evidence suggests that sleep disturbances, such as subjective sleep quality, quantity, insomnia, and nightmares, as well as objective sleep data collected by PSG, often persist even after successful CBT for anxiety (Belleville et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). These findings underscore the need to directly examine whether targeted anxiety interventions, such as group CBT for SAD, influence co-occurring sleep disruptions.\u003c/p\u003e\u003cp\u003eThere is also reason to consider that the mechanisms underlying exposure-based CBT, the core component of SAD treatment, could acutely impact sleep in complex ways. Exposure therapy is effective due to its emotional intensity, designed to provoke distress and facilitate fear extinction through controlled confrontation with feared stimuli. This arousal, however, has also been shown to increase cognitive processes such as post-event-processing, or rumination, after therapy sessions for SAD (Edgar et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Kocovski \u0026amp; Rector, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Given the fact that rumination is a known mediator in the relationship between anxiety and sleep disturbances (Tousignant et al., \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), heightened rumination following emotionally intense therapy sessions may contribute to disrupted sleep, even as global anxiety levels decline over the course of treatment. Communicating this unanticipated effect of therapy may help mitigate treatment dropout (Eskildsen et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Hofmann \u0026amp; Suvak, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) and addressing residual sleep difficulties could be particularly important, as poor sleep has been linked to reduced treatment efficacy (Dutcher et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Zalta et al., 2013).\u003c/p\u003e\u003cp\u003eAccordingly, the secondary aim of this study was to assess the effect of exposure-based SAD therapy on sleep. To comprehensively examine this relationship, changes in both global self-reported sleep quality across the intervention and sleep duration and efficiency on the night following therapy sessions were assessed. This dual approach offers preliminary evidence on whether exposure therapy influences both long-term sleep patterns and acute sleep disruptions, contributing to a more nuanced understanding of the bidirectional relationship between anxiety treatment and sleep.\u003c/p\u003e\u003cp\u003eBased on previous literature, to investigate our primary aim, we hypothesized that 1) pre-treatment sleep measures (self-reported and actigraphy-based sleep duration and sleep efficiency) would predict outcomes such that those with poorer sleep would evidence higher symptom severity across treatment; 2a) average sleep efficiency and duration the night before therapy sessions would be related to better treatment outcomes across treatment; and 2b) average sleep efficiency and duration the night after therapy sessions would be associated with better treatment outcomes. To test our second aim investigating the impact of exposure therapy on sleep, we hypothesized that 3) post-treatment sleep measures would be significantly improved compared to pre-treatment levels for poor sleepers (baseline PSQI\u0026thinsp;\u0026gt;\u0026thinsp;5); and 4) sleep efficiency and duration will be poorer on the night following therapy relative to the average of the previous week.\u003c/p\u003e\u003c/div\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Participants\u003c/h2\u003e\u003cp\u003eParticipants (N\u0026thinsp;=\u0026thinsp;32) were adults aged 18\u0026ndash;39 (mean\u0026thinsp;=\u0026thinsp;26 years, SD\u0026thinsp;=\u0026thinsp;6.26, 18 females) who participated in a randomized clinical trial testing the effects of post-exposure naps on exposure therapy for SAD (Pace-Schott et al., 2018). To be eligible, participants had to be 18 years of age or older, meet all criteria for DSM-IV-TR SAD, and have a Liebowitz Social Anxiety Scale (LSAS) score of at least 60. Exclusion criteria included potentially confounding medical, sleep, neurological, substance use, or severe psychiatric illnesses (see Pace-Schott et al., 2018 supplementary methods for details). All study procedures accorded with the Declaration of Helsinki and were approved by the Partners Healthcare Institutional Review Board. All participants provided written informed consent, received group treatment free of charge, and were compensated for participation.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Procedures\u003c/h2\u003e\u003cp\u003eDetails regarding the protocol are described in Pace-Schott et al. (2018) and associated supplementary material. All participants completed a telephone screening followed by psychiatric and sleep-disorders screening interviews. Eligible participants then completed a baseline assessment with an independent evaluator blind to condition and a battery of self-report measures before beginning an evidence-based and validated standardized 5-week exposure-based, group therapy for SAD (Hofmann, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Hofmann et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Smits et al., \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Treatment consisted of five 90-min weekly sessions led by the same two clinical psychologists for all participants. The protocol began with one psychoeducational session followed by four public speaking exposures during which extinction learning could take place. Before the third therapy session, participants were randomized in blind fashion to either the Nap (N\u0026thinsp;=\u0026thinsp;17, 9 females) or Wake (N\u0026thinsp;=\u0026thinsp;15, 9 females) condition who had, or didn\u0026rsquo;t have a 120-min sleep opportunity, respectively, following their third and fourth treatment sessions. At approximately 14:30 all participants were instrumented to undergo polysomnography, although the Wake group watched two episodes of \u003cem\u003ePlanet Earth\u003c/em\u003e rather than nap.\u003c/p\u003e\u003cp\u003eThroughout the entire protocol (1-week pre-treatment, 5 weeks of treatment, 1-week post-treatment), participants completed daily sleep diaries every morning and evening (see Pace-Schott et al., 2018 supplementary materials) and wore the Actiwatch 2 (Phillips Respironics, Bend, OR). At pre-, mid- (i.e., between sessions 3 and 4), and post-treatment, participants completed social anxiety symptom measures. At pre- and post-treatment, participants completed a retrospective sleep quality assessment along with a battery of self-report measures.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Measures\u003c/h2\u003e\u003cp\u003e\u003cem\u003eRetrospective Sleep Quality.\u003c/em\u003e The Pittsburgh Sleep Quality Index (PSQI, Buysse et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e1989\u003c/span\u003e) is the most widely used self-report assessment of sleep quality and consists of 19 items encompassing 7 sleep-quality factors over the past month. It has demonstrated good internal consistency (α\u0026thinsp;=\u0026thinsp;0.83), test-retest reliability, and construct validity (Buysse et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e1989\u003c/span\u003e; Carpenter \u0026amp; Andrykowski, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). Higher scores indicate poorer sleep quality and a clinical cutoff score of greater than 5 has been established to distinguish good from poor sleepers. The PSQI was administered at pre- and post-treatment only.\u003c/p\u003e\u003cp\u003e\u003cem\u003eProspective Sleep Duration and Efficiency.\u003c/em\u003e The present study investigated actigraphy-based and self-reported sleep duration (total sleep time, TST) and sleep efficiency (SE). Self-reported sleep was recorded using the Evening-Morning Sleep Questionnaire (EMSQ, Pace-Schott et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e1994\u003c/span\u003e) administered each morning to ask about the previous night of sleep and each evening to ask about daytime activities influencing sleep (e.g., napping, caffeine). Objective sleep was captured nightly using the Actiwatch 2 (Philips Respironics, Bend, OR) device. Subjects were instructed to press the Actiwatch 2 event marker when beginning to attempt sleep and upon waking. Time stamps inserted by the event button served as demarcation of the subject\u0026rsquo;s time-in-bed within which the default Actiware 5.61 algorithm determined TST, sleep onset latency (SOL), and SE. Given the documented limitations of actigraphy devices (Grandner \u0026amp; Rosenberger, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), all data were reviewed using the rules below. Missing actigraphy data were not imputed, as variability in sleep metrics over time was a primary outcome of interest. Given that missingness was determined by predefined quality-control criteria rather than occurring at random, imputation would risk introducing bias by assuming stable sleep patterns where variability was expected.\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eIf actigraphy TST was \u0026lt;\u0026thinsp;60 min, the night of data was removed.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eIf there was \u0026gt;\u0026thinsp;2-hour discrepancy between actigraphy SOL and self-report SOL, the night of data was removed.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eIf actigraphy SE was \u0026lt;\u0026thinsp;50%, and there was \u0026gt;\u0026thinsp;20% discrepancy with self-report, the night of data was removed.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eA minimum of 3 nights was required to calculate a weekly average.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eTreatment Outcome\u003c/em\u003e. The Liebowitz Social Anxiety Scale (LSAS, Liebowitz, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e1987\u003c/span\u003e) and Clinician Global Impression scale (CGI, Guy, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e1976\u003c/span\u003e) were used to assess symptom severity at pre-, mid-, and post-treatment timepoints. The LSAS is a 48-item clinician-administered scale that assesses the severity of social anxiety symptoms by asking participants about their level of fear and avoidance in social and performance situations. It has excellent internal consistency (α\u0026thinsp;=\u0026thinsp;.96), strong convergent validity with other social anxiety scales, and is sensitive to changes across treatment (Heimberg et al., 1999). The CGI is a single-item clinician-rated tool that quantifies overall clinical severity on a 1 (\u0026ldquo;normal, not at all ill\u0026rdquo;) to 7 (\u0026ldquo;extremely ill\u0026rdquo;) scale and has been validated with individuals with SAD receiving treatment (Zaider et al., \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2003\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Statistical Analysis\u003c/h2\u003e\u003cp\u003eMultilevel modeling (MLM) was used to analyze the data. For Hypotheses 1, we assessed changes in LSAS over time from pre- to mid- to post-treatment and its relationship with baseline sleep predictors while controlling for baseline LSAS, CGI, and treatment Condition (nap vs. wake). For Hypothesis \u003cspan refid=\"FPar3\" class=\"InternalRef\"\u003e2\u003c/span\u003e, we used multilevel modeling to examine whether participants\u0026rsquo; average SE and TST on nights before and after sessions predicted social anxiety symptoms across treatment (i.e., pre-, mid-, and post-treatment). Separate models were run for each sleep variable and each time window (pre-session, post-session). For Hypothesis \u003cspan refid=\"FPar4\" class=\"InternalRef\"\u003e3\u003c/span\u003e, we examined the effects of Time on sleep measures. Finally, for Hypothesis \u003cspan refid=\"FPar5\" class=\"InternalRef\"\u003e4\u003c/span\u003e, we used multilevel modeling to compare nightly sleep on therapy nights versus non-therapy nights across the treatment period. Specifically, we modeled self-reported and actigraphy-derived TST and SE as outcomes, with a dichotomous variable (therapy night vs. average of past week) as the key predictor. For all analyses, we included a random intercept for participant ID to account for within-subject correlations across repeated measures. All analyses were conducted in R version 2024.12.0.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eModel selection\u003c/strong\u003e\u003cp\u003eWe compared several growth curve models for the trajectory of social anxiety symptoms (LSAS) over time. In line with findings from prior research (Horenstein et al., 2019; Kushnir et al., 2013; Zalta et al., 2013), which suggested linear symptom change over time, we utilized a linear model for our primary analyses. While the quadratic model showed marginally lower AIC and BIC values, the three measurement occasions impose constraints on the ability to robustly estimate non-linear trends. Although model fit indices marginally favored the quadratic model, visual inspection and theoretical considerations led us to prioritize the linear model, treating the quadratic trend as exploratory. No results reported below differed when using the quadratic growth model.\u003c/p\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003eSample demographics were largely representative of the city where data were collected (US Census Bureau), with most identifying as female (56%) and White (40.6%), and others identifying as Asian (25%), Black or African American (15.6%), and more than one race (12.5%). A minority of participants identified as Hispanic or Latine (21.9%). Means, SDs, and correlations for baseline variables are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Participants reported an average baseline global PSQI score of 5.06 (SD\u0026thinsp;=\u0026thinsp;3.15, range: 0\u0026ndash;13), with 34% of the sample (n\u0026thinsp;=\u0026thinsp;11) identified as \u0026ldquo;poor\u0026rdquo; sleepers (PSQI\u0026thinsp;\u0026gt;\u0026thinsp;5). As expected, self-reported (LSAS) and clinician assessed (CGI) symptom severity scores were highly correlated \u003cem\u003e(p\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.88). Self-reported sleep quality (PSQI) was correlated with both self-reported SE (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.57) and actigraphy SE (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.43) but not TST. Consistent with the literature, self-reported SE and actigraphy SE were also not correlated (Campanini et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Lehrer et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePrimary study variables at baseline\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"9\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMean\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSD\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eLSAS\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCGI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePSQI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eActi- TST\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eSR- TST\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eActi- SE\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLSAS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e85.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e17.75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCGI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e5.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.88**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePSQI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e5.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eActi-TST\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e362.76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e61.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSR-TST\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e436.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e53.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.066\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.50**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eActi-SE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e77.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e10.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.43*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.67**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSR-SE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e93.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.57**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e.34\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003cem\u003eNote\u003c/em\u003e: Acti\u0026thinsp;=\u0026thinsp;actigraphy; CGI\u0026thinsp;=\u0026thinsp;Clinical Global Impression; LSAS\u0026thinsp;=\u0026thinsp;Liebowitz Social Anxiety Scale; PSQI\u0026thinsp;=\u0026thinsp;Pittsburgh Sleep Quality Index; SE\u0026thinsp;=\u0026thinsp;sleep efficiency; SR\u0026thinsp;=\u0026thinsp;self-report; TST\u0026thinsp;=\u0026thinsp;total sleep time.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"9\"\u003e*\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.05, **\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.01\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eHypothesis 1\u003c/strong\u003e\u003cp\u003eRelationship between baseline sleep and SAD treatment outcomes.\u003c/p\u003e\u003c/p\u003e\u003cp\u003eIn contrast to our hypothesis, while poorer baseline PSQI (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) and actigraphy-TST predicted higher levels of SAD symptoms at baseline (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.50, \u003cem\u003et\u003c/em\u003e(50)\u0026thinsp;=\u0026thinsp;2.04, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.047 and \u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.08, t(45)\u0026thinsp;=\u0026thinsp;2.00, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.05, respectively), these sleep measures did not predict LSAS symptoms across treatment (\u003cem\u003ep\u003c/em\u003e\u0026rsquo;s\u0026thinsp;\u0026gt;\u0026thinsp;.52). Similarly, no other sleep measure (SR-TST, actigraphy-SE, SR-SE) yielded a significant association with LSAS over time.\u003c/p\u003e\u003cp\u003eWhile Condition was included in the model as a control, results revealed a significant Condition main effect, such that participants in the Nap condition had LSAS scores at mid- and post-treatment that were significantly higher than the Wake group when controlling for baseline LSAS and CGI (\u003cem\u003ep\u003c/em\u003e\u0026rsquo;s\u0026thinsp;=\u0026thinsp;.01 \u0026minus;\u0026thinsp;.05).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eHypothesis 2\u003c/strong\u003e\u003cp\u003eRelationship between pre- and post-exposure session sleep and SAD treatment outcomes.\u003c/p\u003e\u003c/p\u003e\u003cp\u003eIn contrast to our hypothesis, no significant effects of either pre- or post-exposure session TST and SE on LSAS symptom severity over time were found. Descriptively, we found no differences between the effect sizes or significance levels of self-report measures (\u003cem\u003ep\u003c/em\u003e\u0026rsquo;s\u0026thinsp;=\u0026thinsp;.25 \u0026minus;\u0026thinsp;.76) and actigraphy measures (\u003cem\u003ep\u003c/em\u003e\u0026rsquo;s\u0026thinsp;=\u0026thinsp;.28 \u0026minus;\u0026thinsp;.61).\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eHypothesis 3\u003c/strong\u003e\u003cp\u003eEffect of exposure-based therapy for SAD and on sleep quality.\u003c/p\u003e\u003c/p\u003e\u003cp\u003eA binary baseline PSQI Group variable was created to divide the sample into good (PSQI\u0026thinsp;\u0026le;\u0026thinsp;5) and poor sleep (PSQI\u0026thinsp;\u0026gt;\u0026thinsp;5) groups based on their initial PSQI. Analyses found no main effect of Time on PSQI scores, indicating no significant overall change in PSQI scores between the two administration time points at pre- and post-treatment across the entire sample. However, in support of our hypothesis, there were significant interactions such that poor sleepers improved in PSQI sleep quality, self-reported SE, and actigraphy-based SE from pre- to post-treatment. Specifically, there was a significant Time \u0026times; PSQI interaction such that poor sleepers saw a significant decrease in PSQI scores from pre- to post-treatment, \u003cem\u003eβ\u003c/em\u003e = -2.89, \u003cem\u003et\u003c/em\u003e(57) = -2.92, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.01 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In separate models, there were also significant interactions for actigraphy SE (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5.41, \u003cem\u003et\u003c/em\u003e(52)\u0026thinsp;=\u0026thinsp;2.45, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.02) and self-reported SE (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3.59, \u003cem\u003et\u003c/em\u003e(55)\u0026thinsp;=\u0026thinsp;3.08, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.01). This was not found for the models investigating changes in actigraphy TST (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;17.87, \u003cem\u003et\u003c/em\u003e(52)\u0026thinsp;=\u0026thinsp;.99, p\u0026thinsp;=\u0026thinsp;.33) or self-reported TST (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;16.48, \u003cem\u003et\u003c/em\u003e(55)\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;1.02, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.31).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eHypothesis 4\u003c/strong\u003e\u003cp\u003eEffect of SAD therapy sessions on sleep quality and duration that evening.\u003c/p\u003e\u003c/p\u003e\u003cp\u003eIn support of our hypothesis, results revealed a significant main effect of Session-Night on actigraphy TST, indicating objective sleep duration was significantly shorter on therapy nights compared to the previous week average, \u003cem\u003eβ\u003c/em\u003e = -26.48, \u003cem\u003et\u003c/em\u003e(237) = -2.75, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.01 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The main effect of Condition was not significant (\u003cem\u003eβ\u003c/em\u003e = -15.78, \u003cem\u003et\u003c/em\u003e(36) = -0.76, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.45). However, the significant Session-Night \u0026times; Condition interaction (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;33.83, \u003cem\u003et\u003c/em\u003e(237)\u0026thinsp;=\u0026thinsp;2.56, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.01) revealed TST on therapy nights was even shorter for individuals in the nap condition compared to the wake condition. While there was no main effect of Session-Night on SR-TST, actigraphy-SE, or SR-SE, there was a trend level effect for Session in all models except SR-SE, such that sleep duration and efficiency decreased across the sessions (\u003cem\u003ep\u003c/em\u003e\u0026rsquo;s\u0026thinsp;=\u0026thinsp;.06 \u0026minus;\u0026thinsp;.09).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThe present study investigated the bidirectional relationship between sleep difficulties and treatment outcomes in group exposure-based therapy for SAD. Inconsistent with our hypotheses, baseline global sleep quality, measured by the Pittsburgh Sleep Quality Index (PSQI), did not predict social anxiety symptoms over time, with poorer baseline sleep quality only associated with greater symptom severity at baseline. While objective TST followed a similar pattern, other actigraphy-based and self-report sleep measures did not significantly predict baseline symptom severity or symptom changes. Also contrary to our hypotheses, pre- and post-session sleep measures were not significantly related to symptom trajectories. Regarding the effects of exposure-based therapy on sleep outcomes, we observed significant improvements in sleep quality and sleep efficiency at post-treatment among individuals with poor baseline sleep, though therapy nights were associated with a significant reduction in actigraphy-based sleep duration relative to the weekly average.\u003c/p\u003e\u003cp\u003eIn line with findings from Horenstein and colleagues (2019), poorer baseline sleep quality, as well as lower sleep duration and efficiency, did not predict greater symptom severity over the course of treatment. This challenges the idea that sleep difficulties necessarily reduce the effectiveness of exposure-based therapy for SAD (Dutcher et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Zalta et al., 2013). Although theoretical models suggest that sleep disruption impairs emotional regulation (Watling et al., \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), fear extinction (Straus et al., \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), and cognitive flexibility (Stickgold \u0026amp; Walker, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), our results suggest a more complex picture in practice.\u003c/p\u003e\u003cp\u003eSpecifically, while individuals with poorer sleep reported more severe social anxiety symptoms at baseline, this did not translate into poorer treatment response, as evidenced by non-significant Time \u0026times; Sleep interactions. This contrasts two previous studies which reported that poor baseline sleep quality predicted worse post-treatment outcomes (Dutcher et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Zalta et al., 2013). One possible explanation, as Horenstein et al. proposed, is that sleep difficulties may need to reach a higher severity threshold before they begin to meaningfully interfere with mechanisms like attention, flexibility, and learning during treatment. In our sample, due to the exclusion criteria preventing individuals with moderate to severe insomnia from participating, the sleep disturbances are perhaps too mild to influence the trajectory of symptoms across treatment. As such, future investigations with adequately powered samples consisting of individuals with SAD and co-occurring sleep disturbances are needed. Additionally, long-term follow-up timepoints will be important to include in order to capture any relationships between sleep and long-term treatment gains or remission.\u003c/p\u003e\u003cp\u003eInterestingly, while the experimental condition was originally included as a covariate, a significant main effect of Condition emerged. Findings indicate that participants randomized to the nap condition exhibited higher SAD symptoms over time than those in the wake condition, despite the prior ANOVA-based analysis that found no significant Condition \u0026times; Time interaction (Pace-Schott et al., 2018). This discrepancy may stem from differences in analytical approach\u0026mdash;while the ANOVA tested for whether the pattern of symptom change differed on average from pre- to post-treatment between groups, our regression model accounted for individual variability in baseline symptom severity and sleep characteristics and included an additional mid-treatment time point. The inclusion of this third time point may have provided greater sensitivity to individual variability, which would explain why the Condition effect emerged in our analysis. These findings suggest that post-exposure naps may influence treatment response in a way that was not captured by the original group-level analysis, potentially interacting with baseline sleep and symptom characteristics to shape symptom progression. Future research should further investigate these dynamics to provide a clearer understanding of these relationships.\u003c/p\u003e\u003cp\u003eContrary to our hypotheses, neither pre-session nor post-session sleep duration or efficiency significantly predicted treatment outcomes. Although previous research suggests that poor sleep prior to learning may impair forming emotional memories (Harvey et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) and post-session sleep may be critical for consolidation (Krause et al., 2017), our findings suggest that single-night variations in sleep may be less influential than cumulative sleep patterns over time. Findings also support the notion that extinction learning and memory consolidation are iterative processes occurring across multiple nights, and that cumulative sleep debt may exert a greater influence on treatment outcomes than any single night of disrupted sleep. While these findings appear to contrast existing research suggesting sleep duration the night before therapy (Dutcher et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and greater \u0026ldquo;restedness\u0026rdquo; the night after therapy (Zalta et al., 2013) are significantly associated with symptom severity, methods across studies differed. Specifically, these investigations measured symptoms session by session, and we examined pre-, mid-, and post-treatment timepoints.\u003c/p\u003e\u003cp\u003eWhile overall PSQI scores did not significantly change across the sample, potentially explained by the limited number of participants experiencing poor sleep before treatment, a significant interaction indicated that individuals classified as poor sleepers at baseline (PSQI\u0026thinsp;\u0026gt;\u0026thinsp;5) experienced significant improvements in global sleep quality and sleep efficiency (both self-report and actigraphy-based) at post-treatment. This finding suggests that exposure therapy for SAD may have secondary benefits for sleep among those with initial disturbances. However, it is also possible that improvements in sleep quality were driven by increased awareness and regulation of sleep patterns due to sleep monitoring. This phenomenon has been documented (Ojalvo et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) but is not universal across the literature and was notably not found in a study that utilized actigraphy and daily sleep diary akin to the procedures in the present investigation (Eigl et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Future research should disentangle whether these improvements result from reductions in social anxiety symptoms or the effects of sleep tracking itself.\u003c/p\u003e\u003cp\u003eLastly, our results revealed a significant reduction in actigraphy-measured TST on therapy nights compared to the weekly average, supporting the hypothesis that exposure therapy induces short-term sleep disturbances, possibly due to heightened emotional and physiological arousal. Although other sleep parameters did not show significant changes, trend-level effects indicated a general pattern of reduced sleep duration and efficiency across therapy sessions. These findings suggest that as the exposures get more challenging across treatment, as is standard practice in the exposure-based protocol, there was even greater sleep disturbance. Although it could be hypothesized that exposure therapy elicits temporary autonomic and cognitive arousal, which may disrupt sleep on the night of treatment, future research is needed to assess the mechanism underlying this relationship and if this pattern is found in exposure therapies for other conditions. Additionally, the clinical significance of these transient sleep disturbances remains unclear, as they may not necessarily impede long-term therapeutic gains (per results of hypothesis \u003cspan refid=\"FPar3\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Regardless, clinicians should be aware that sleep disturbances the night of exposure sessions is a potential side-effect and consider informing clients to guard against discouragement and treatment dropout.\u003c/p\u003e\u003cp\u003eThis investigation is not without limitation. First, the results of this secondary analysis should be interpreted in the context of the relatively small sample size (n\u0026thinsp;=\u0026thinsp;32), which may limit the ability to detect smaller effects and may have contributed to trend level findings. All covariates were theoretically driven and aligned with previous literature, although they may increase the likelihood of type II error. Additionally, while participants with a sleep disorder other than mild insomnia or delayed sleep phase disorder were excluded, participants did not complete baseline measures of insomnia. Similarly, although current major depressive disorder was an exclusion criterion, baseline measures of depression were not collected and therefore not controlled for in analyses. Excluding participants for comorbid depression and moderate to severe insomnia, both of which frequently co-occur with SAD (Buckner et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2008\u003c/span\u003e), may limit generalizability of our findings to more severe SAD clinical populations. It is also possible that other covariates not accounted for contributed to sleep quality, duration, efficiency, and symptom severity. This study is also limited by the fact that symptom severity was only assessed at pre-, mid-, and post-treatment. Session-by-session measures and a longer follow-up timepoint, if collected, may better reveal the relationship between sleep and social anxiety outcomes across treatment. Lastly, the correlational approach limits causal inferences that can be made.\u003c/p\u003e\u003cp\u003eIn sum, the current investigation makes a novel contribution to the literature as the first, to our knowledge, to measure nightly sleep using both subjective self-reports and objective measures (i.e., actigraphy) across an exposure-based SAD treatment. Notably, findings suggest that therapy sessions may acutely disrupt sleep, with participants sleeping less on nights following exposures, and that individuals with poor baseline sleep experience improvements in sleep quality and efficiency after completing treatment. While poorer baseline sleep was associated with greater symptom severity before treatment, it did not predict changes in symptoms over time. Similarly, neither subjective nor objective measures of sleep before or after treatment sessions predicted outcomes. Future research is needed to better elucidate these relationships, as well as replicate findings on acute sleep disruption and post-treatment improvements among poor sleepers.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eC.M.: Writing \u0026ndash; original draft, Data Curation, Formal analysis, Visualization, Conceptualization; G.F.: Writing \u0026ndash; review and editing, Supervision; R.B.: Project Administration, Resources, Data Curation; N.L.: Resources; N.S.: Conceptualization, Resources; A.B.: Resources; G.L.: Writing \u0026ndash; review and editing; E.P-S: Conceptualization, Methodology, Writing - review and editing, Funding acquisition, Supervision\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data that support the findings of this study are not openly available due to reasons of sensitivity and are available from the corresponding author upon reasonable request. Data are located in controlled access data storage at Massachusetts General Brigham.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBelleville, G., Cousineau, H., Levrier, K., St-Pierre-Delorme, M. E., \u0026amp; Marchand, A. (2010). The impact of cognitive-behavior therapy for anxiety disorders on concomitant sleep disturbances: a meta-analysis. In Database of abstracts of reviews of effects (DARE): Quality-assessed reviews [internet]. Centre for Reviews and Dissemination (UK).\u003c/li\u003e\n\u003cli\u003eBrown, T. M., Black, B., \u0026amp; Uhde, T. W. (1994). The sleep architecture of social phobia. Biological Psychiatry, 35(6), 420-421.\u003c/li\u003e\n\u003cli\u003eBuckner, J. D., Bernert, R. A., Cromer, K. R., Joiner, T. E., \u0026amp; Schmidt, N. B. (2008). 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Sleep quality predicts treatment outcome in CBT for social anxiety disorder. \u003cem\u003eDepression and Anxiety\u003c/em\u003e, 30(11), 1114-1120.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"cognitive-therapy-and-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"cotr","sideBox":"Learn more about [Cognitive Therapy and Research](http://link.springer.com/journal/10608)","snPcode":"10608","submissionUrl":"https://www.editorialmanager.com/cotr/default.aspx","title":"Cognitive Therapy and Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"cognitive-behavioral therapy, exposure therapy, social anxiety disorder, sleep quality, sleep duration, actigraphy","lastPublishedDoi":"10.21203/rs.3.rs-7121721/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7121721/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cem\u003eBackground\u003c/em\u003e. Individuals with Social Anxiety Disorder (SAD) often experience poor sleep, which may influence treatment outcomes. Although theoretical models link sleep and fear extinction mechanisms, findings are equivocal and largely based on subjective measures. This study investigates the bidirectional relationship between sleep (duration, efficiency, quality) and outcomes from exposure-based SAD therapy.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMethods\u003c/em\u003e. Participants (N = 32) with SAD completed five weeks of exposure-based group therapy. Daily sleep data (self-report and actigraphy) were collected pre-, during, and post-treatment. The Liebowitz Social Anxiety Scale (LSAS) assessed treatment outcomes. Multilevel modeling examined associations between sleep and treatment outcomes.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eResults\u003c/em\u003e. Treatment significantly impacted sleep such that nights after therapy were associated with reduced actigraphy-based sleep duration and participants with poor baseline sleep exhibited post-treatment improvements in sleep quality and efficiency (self-report and actigraphy). While poor baseline sleep quality and actigraphy sleep duration were associated with greater baseline symptoms, they did not predict changes across treatment. Sleep before and after exposure sessions also did not predict SAD symptoms.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eConclusions\u003c/em\u003e. Findings suggest exposure-based SAD treatment influences sleep, particularly in poor sleepers, but that poor sleep does not hinder treatment efficacy. Additionally, clinicians may consider informing patients about potential post-exposure sleep disturbances to support engagement.\u003c/p\u003e","manuscriptTitle":"The Bidirectional Relationship Between Sleep Disturbance and Exposure-Based Treatment for Social Anxiety Disorder: A Multi-Method Examination","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-23 07:02:11","doi":"10.21203/rs.3.rs-7121721/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-08-01T06:54:56+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-25T17:00:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"162155533388689197089196209729526099982","date":"2025-07-16T17:28:03+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-16T17:21:42+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-16T10:58:43+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-16T10:57:35+00:00","index":"","fulltext":""},{"type":"submitted","content":"Cognitive Therapy and Research","date":"2025-07-14T13:23:53+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"cognitive-therapy-and-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"cotr","sideBox":"Learn more about [Cognitive Therapy and Research](http://link.springer.com/journal/10608)","snPcode":"10608","submissionUrl":"https://www.editorialmanager.com/cotr/default.aspx","title":"Cognitive Therapy and Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"8006f61f-72ee-44cf-98b3-b087648c0be2","owner":[],"postedDate":"July 23rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-09-22T16:00:27+00:00","versionOfRecord":{"articleIdentity":"rs-7121721","link":"https://doi.org/10.1007/s10608-025-10664-4","journal":{"identity":"cognitive-therapy-and-research","isVorOnly":false,"title":"Cognitive Therapy and Research"},"publishedOn":"2025-09-16 15:56:50","publishedOnDateReadable":"September 16th, 2025"},"versionCreatedAt":"2025-07-23 07:02:11","video":"","vorDoi":"10.1007/s10608-025-10664-4","vorDoiUrl":"https://doi.org/10.1007/s10608-025-10664-4","workflowStages":[]},"version":"v1","identity":"rs-7121721","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7121721","identity":"rs-7121721","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}