US Veterans Show Improvements in Subjective but Not Objective Sleep following Treatment for Posttraumatic Stress Disorder: Secondary Analyses from a Randomised Controlled Trial

Mathersul, Danielle C.; Schulz-Heik, R. Jay; Avery, Timothy J.; Allende, Santiago; Zeitzer, Jamie M.; Bayley, Peter J.

doi:https://doi.org/10.1155/2023/7001667

Depression and Anxiety

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Abstract Introduction Methods Results Discussion Conclusion Data Availability Ethical Approval Consent Disclosure Conflicts of Interest Authors’ Contributions Acknowledgments Supplementary Materials References Copyright Related Articles

Research Article | Open Access

Volume 2023 | Article ID 7001667 | https://doi.org/10.1155/2023/7001667

US Veterans Show Improvements in Subjective but Not Objective Sleep following Treatment for Posttraumatic Stress Disorder: Secondary Analyses from a Randomised Controlled Trial

Danielle C. Mathersul,^1,2,3R. Jay Schulz-Heik,³Timothy J. Avery,³Santiago Allende,^3,4Jamie M. Zeitzer,^4,5and Peter J. Bayley^3,4

Academic Editor: Giulia Landi

Received14 Nov 2022

Revised09 Jun 2023

Accepted30 Jun 2023

Published14 Aug 2023

Abstract

Background. Sleep disturbances are a prominent feature of posttraumatic stress disorder (PTSD), and poorer sleep quality is associated with higher PTSD severity. This highlights the importance of monitoring sleep outcomes alongside PTSD symptoms in treatments targeting PTSD. Yet few studies monitor both sleep and PTSD outcomes, unless sleep is the primary treatment target. Furthermore, inconsistencies remain about the effects of first-line, evidence-based PTSD treatments on sleep. Methods. Here, we explored changes in sleep in secondary analyses from a randomised controlled trial that originally assessed the noninferiority of a breathing-based yoga practice (Sudarshan kriya yoga; SKY) to a first-line PTSD treatment (cognitive processing therapy (CPT)) for clinically significant PTSD symptoms among US veterans (intent-to-treat ; per protocol ). Sleep was assessed via subjective (self-reported sleep diary), PTSD symptom severity items (self-reported and clinician-administered insomnia/nightmare sleep items), and objective (wrist actigraphy) measures. Results. Following treatment, subjective sleep diary measures of quality, latency, and wake duration showed small effect size () improvements, with no significant differences between treatment groups. Significant improvements were also observed in PTSD sleep symptoms, though CPT () more reliably reduced nightmares while SKY (d = .44-.45) more reliably reduced insomnia. In contrast, there were no significant treatment-related effects for any of the actigraphy-measured sleep indices. Conclusions. To our knowledge, this is the first study to investigate sleep as an outcome of CPT or SKY for PTSD, across a combination of subjective diary, PTSD symptom severity, and objective actigraphic measures. Findings lend support to a growing body of evidence that trauma-focused psychotherapy for PTSD improves sleep and suggest that yoga-based interventions may also be beneficial for sleep among individuals with emotional or mental health disorders like PTSD. This trial is registered with NCT02366403.

1. Introduction

Sleep disturbances are a prominent feature of posttraumatic stress disorder (PTSD) and appear in two of the five diagnostic symptom clusters (category B, nightmares; category E, difficulty sleeping (insomnia); [1]). Not surprisingly, most individuals with PTSD have sleep disturbance [2–4]. Sleep disturbances are also the most commonly reported symptom among individuals who have been exposed to a traumatic event yet do not meet full PTSD criteria [2, 5, 6]. Indeed, insomnia and PTSD symptoms are bidirectionally related over time [7], and poorer sleep quality is associated with higher subsequent PTSD severity [6, 8]. Meta-analyses of objective biomarkers of sleep (e.g., polysomnography, actigraphy) are consistent with the high frequency of self-reported sleep disturbances in PTSD [9, 10]. These findings have led to the notion that sleep disturbances are a core feature of PTSD, beyond mere secondary symptoms [11].

Clearly, it is important to monitor sleep outcomes alongside PTSD symptoms in treatments targeting PTSD. Yet few studies do, unless sleep is the primary treatment target. A recent systematic review and meta-analysis across pharmacological, psychological, behavioural, and complementary and integrative health interventions for PTSD found only 89 randomised controlled trials (RCTs) out of 2139 full-text publications reported a sleep outcome [12]. Overall, interventions significantly improved both sleep and PTSD outcomes, with those specifically targeting sleep the most successful at improving sleep outcomes. However, the extant literature remains inconclusive regarding the effect of first-line PTSD treatments on sleep. On closer inspection of these 89 studies, only four [13–16] delivered a first-line, evidence-based treatment for PTSD (e.g., cognitive processing therapy (CPT), prolonged exposure therapy (PE), trauma-focused cognitive behavioural therapy (TF-CBT), or eye-movement desensitisation and reprocessing (EMDR)) [17–22]. Of these four studies, two demonstrated significant improvements in self-reported sleep [13, 16]—though neither achieved full remission of sleep disturbances—while the other two studies found significant residual sleep disturbances despite improvements in PTSD severity [14, 15]. Furthermore, the two studies reporting improvements in sleep [13, 16] used a self-report measure specifically designed to assess sleep quality (e.g., a sleep diary or standardised questionnaire), while the other two studies [14, 15] relied solely on the insomnia and nightmare items from PTSD symptom severity measures. Together, these inconsistencies and limitations across only a handful of studies with very different sample demographics—females only [13], chronic PTSD [15], or actively serving military/defence personnel [14]—highlight the need for further research.

An overreliance on self-report measures of sleep exposes findings to bias [23], whether these are sleep-specific or subsumed within PTSD assessment. The most relevant biases to treatment studies are social desirability and demand characteristics, where participants may adjust their responses for specific reasons (e.g., to be less personally disclosing or to appear “better” or “worse” at the end of treatment). For sleep research specifically, memory recall is another likely potential bias. Using objective measures alongside subjective self-report measures is an important way of increasing ecological validity. Yet, to our knowledge, no study to date has examined both subjective and objective sleep within the context of a treatment study for PTSD. Here, we address multiple gaps in the literature by examining both subjective and objective sleep in US veterans undergoing first-line PTSD treatment (CPT) for clinically significant PTSD symptoms. Sleep was assessed via subjective reporting (a standardised, valid, and reliable self-reported sleep diary), PTSD symptom severity items (insomnia/nightmare sleep items on self-reported and clinician-administered PTSD measures), and objective measures (validated wrist actigraphy). This combination addresses the extant literature inconsistencies and limitations, such as differences in the type of sleep measure (some used standardised sleep diaries/questionnaires, others used PTSD insomnia/nightmare sleep items, and we used both), failure to deliver a first-line, evidence-based treatment for PTSD (we used CPT), and an overreliance on subjective, and self-reported sleep (we used objective actigraphy).

To determine whether any sleep changes were specific to trauma-focused treatment or might occur following other interventions, we explored these sleep changes as secondary analyses from an RCT that originally assessed the noninferiority of a breathing-based yoga practice (Sudarshan kriya yoga (SKY)) to CPT. As the primary outcomes study found SKY was clinically noninferior to CPT for symptoms of PTSD, depression, and negative affect at the end of treatment, we hypothesised that all sleep measures (self-reported, clinician-administered, and actigraphy) would improve with both CPT and SKY for PTSD. We also examined differences in sleep between treatment groups, though based on the limited extant literature, we did not pose directional hypotheses.

2. Methods

2.1. Participants

US veterans with clinically significant levels of PTSD symptoms (≥38 on the PTSD Checklist for DSM-5; PCL-5; [24]) were recruited from the San Francisco Bay Area via flyers and advertisements. In total, 85 veterans with PTSD (59 treatment completers) were randomised to treatment [25, 26]. As per the recommended rigorous approach to testing noninferiority [27], here, we report both intent-to-treat (ITT; ) and per protocol (PP; ≥75% treatment sessions; ) secondary exploratory analyses on the sleep data. Approximately 14% and 9% of sleep actigraphy data were lost at baseline and end-of-treatment, respectively, due to poor data quality. Demographics by treatment group sample are presented in Table 1 (additional demographic data are available in the primary outcomes study; [25]). The presence of sleep apnoea and restless legs were assessed via two well-validated self-report measures with high sensitivity and specificity: the Multivariate Apnea Prediction Index (MAPI; [28]) and Restless Legs Syndrome Diagnostic Index (RLS-DI; [29]), respectively. The recommended cut-off for the MAPI is .50, suggesting our sample likely had sleep apnoea. Negative scores on the RLS-DI suggest our sample did not have restless legs syndrome. Groups did not differ on basic demographics (all ). The CONSORT 2010 checklist of information for RCT is presented as a Supplementary File (available here).

2.2. Procedure

The study was approved by the Stanford University Institutional Review Board. The full RCT protocol is described elsewhere [25, 26]. Briefly, US veterans who had clinically significant PTSD symptoms were randomised to receive 6 weeks of either CPT (individual, twice-weekly) or SKY (initial 5-day group workshop, then 5 weeks of twice-weekly groups), per recommendations and protocols for each intervention [25, 26]. Multiple clinician-administered, self-report, and physiological measures were administered at multiple timepoints. Here, we report sleep measures taken at two timepoints: baseline and end-of-treatment. All overnight sleep assessments were taken on weekday nights.

2.3. Measures

2.3.1. PTSD Sleep Symptoms

The afternoon before the overnight objective sleep assessment, participants completed several self-report questionnaires and clinician-administered measures, including the Posttraumatic Stress Disorder Checklist–Civilian Version (PCL-C) [32] and Clinician-Administered PTSD Scale for DSM-5 (CAPS-5) [33]. The PCL-C was the primary outcome measure for our RCT and is a well-validated measure that assesses DSM-IV PTSD symptom severity in the last month on a 5-point Likert scale from 1 “not at all” to 5 “extremely”, such that higher scores indicate greater severity and scores of 3 “moderately” or more on individual items indicate clinically significant severity. We chose the PCL-C over the PCL-5 as our primary outcome measure for the original noninferiority RCT because, at the time of commencement, there was no established threshold for clinically significant (or noninferiority) improvement for the PCL-5 [25, 26]. Instead, the PCL-5 was used as a screening measure to ensure clinically significant levels of PTSD symptoms for inclusion.

Per previous studies [14, 16], we obtained the PTSD sleep symptom values from the PCL-C for self-reported nightmares (item 2: “Repeated, disturbing dreams of a stressful experience from the past?”) and insomnia (item 13: “Trouble falling or staying asleep?”). The CAPS-5 is the gold standard, semistructured, clinical diagnostic interview for DSM-5-defined PTSD. Clinicians rate each symptom item on a scale from 0 “absent” to 4 “extreme/incapacitating,” such that higher scores indicate greater severity and scores of 2 “moderate/threshold” or more on individual items indicate clinically significant severity. Per previous studies [13, 15, 16], we obtained the PTSD sleep symptom values from the CAPS-5 for nightmares (criterion B2: “In the past month, have you had any unpleasant dreams about (EVENT)?”) and insomnia (criterion E6: “In the past month, have you had any problems falling or staying asleep?”).

2.3.2. Objective Sleep (Actigraphy)

Following completion of the PTSD symptom measures, participants were fitted with a Motionlogger wristwatch (Ambulatory Monitoring, Ardsley, NY) that records triaxial accelerometer (actigraphy) data and asked to wear the device until they returned for their follow-up assessment the next morning. We collected a single night’s sleep at each timepoint (baseline, end-of-treatment) and used validated algorithms [34] embedded in manufacturer-provided software (ActionW, Ambulatory Monitoring, Ardsley, NY) to define established quantitative sleep variables. Specifically, we extracted sleep fragmentation (objective index of quality; measure of sleep interruptions due to physical movement), latency (time to sleep onset), duration (total sleep time in mins), wake duration (total duration in mins of time awake after sleep onset), and efficiency(percentage of total sleep time relative to total time in bed) to correspond with the self-reported sleep diary indices.

2.3.3. Subjective Sleep (Diary)

The morning following the overnight objective sleep assessment, participants completed the Core Consensus Diary, a standardised, valid, and reliable self-report measure of nightly subjective sleep [35]. From question responses, we obtained values for self-reported sleep quality (“How would you rate the quality of your sleep?” (, , , , and )), latency (“How long did it take you to fall asleep?”), duration (calculated as time between “What time did you try to go to sleep?” and “What time was your final awakening?” minus latency minus wake duration), wake duration (“In total, how long did these awakenings last?”), and efficiency ().

2.4. Analyses

All analyses were conducted blind to treatment group and separately by ITT and PP in IBM SPSS Statistics 28 with the significance threshold set at . Cohen’s and estimates are reported as measures of effect size. As these secondary analyses are exploratory, we did not correct for multiple comparisons in pairwise comparisons, instead reporting effect sizes to underscore findings that merit further investigation and replication. Simple Pearson correlations were calculated between change scores (baseline minus end-of-treatment) for overall PTSD symptom severity (PCL total/CAPS total, with and without insomnia/nightmare sleep items, per recommendations (e.g., [30])) and each of the sleep measures (self-reported sleep diary, PTSD sleep symptom severity items, and sleep actigraphy).

While our primary outcomes study was a noninferiority design [25, 26], those analyses are not recommended here since our active control comparison group (CPT) is a first-line treatment for PTSD not sleep [27]. Instead, we estimated separate fixed linear time, random intercept, mixed models for each of the sleep measures (PTSD nightmares, PTSD insomnia; diary/actigraphy indices for each of quality/fragmentation, latency, duration, wake duration, efficiency). The full models included fixed effects for group (CPT, SKY; coded -0.5, +0.5 for ease of interpretation; [36, 37]), time (baseline, end-of-treatment), and their interaction. Per recommendations, time was mean-centred [36–39], and outliers (≥ ±3 SD) were Winsorized and replaced with the next highest value [40]. (Each of the actigraphy sleep indices had three outliers.) We tested only the simplest covariance structure (compound symmetry; CS) as all repeated measures had only two time points (baseline, end-of-treatment; [39]), and within-subject correlations over time were moderate-to-large and positive [41]. Per recommendations, sleep measure variances at each time point were consistent (i.e., homogeneity of group variances assumption was met), and examination of residual plots showed that models the met assumptions of normality, linearity, independence, and constant variance [41].

3. Results

3.1. PTSD Sleep Symptoms

3.1.1. Nightmares

There was a main effect of time (baseline vs. end-of-treatment) for nightmares on both PCL (ITT: , Cohen’s ; PP: , Cohen’s ) and CAPS (ITT: , Cohen’s ; PP: , Cohen’s ). While there were no main or interaction effects of group, pairwise comparisons revealed that CPT (PCL: Cohen’s ; Figure 1(a); CAPS: Cohen’s ; Figure 1(b); Table 2) tended to demonstrate reductions in nightmares more reliably than SKY, especially on the CAPS (PCL: Cohen’s ; CAPS: Cohen’s ).

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3.1.2. Insomnia

There was a significant main effect of time (baseline vs. end-of-treatment) for insomnia on both PCL (ITT: , Cohen’s ; PP: , Cohen’s ) and CAPS (ITT: , Cohen’s ; PP: , Cohen’s ). While there were no main or interaction effects of group, pairwise comparisons revealed that SKY (PCL: Cohen’s ; Figure 1(c); CAPS: Cohen’s ; Figure 1(d); Table 2) tended to demonstrate reductions in insomnia more reliably than CPT, especially on the PCL (PCL: Cohen’s ; CAPS: Cohen’s ).

3.2. Objective Sleep (Actigraphy)

There were no significant main or interaction effects of group (CPT vs. SKY) or time (baseline vs. end-of-treatment) for any of the actigraphic sleep indices (Figure 2; Table 3). Exploratory pairwise comparisons revealed inconsistent findings: CPT demonstrated small-to-moderate effect size improvements for sleep efficiency (ITT: Cohen’s ; PP: Cohen’s ) and wake duration (ITT: Cohen’s ; PP: Cohen’s ), while SKY demonstrated a small-to-moderate effect size worsening for sleep latency (i.e., longer; ITT: Cohen’s ; PP: Cohen’s ). For sleep fragmentation (objective “quality”), CPT demonstrated small-to-moderate effect size improvements (ITT: Cohen’s ; PP: Cohen’s ), while SKY demonstrated small-to-moderate effect size worsening (ITT: Cohen’s ; PP: Cohen’s ).

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Figure 2

Mean sleep diary and actigraphy scores at baseline and end-of-treatment for veterans who received either cognitive processing therapy (CPT) or Sudarshan kriya yoga (SKY) for PTSD (ITT analyses). (a) Self-reported sleep quality. (b) Actigraphic sleep quality. (c) Self-reported sleep latency (mins). (d) Actigraphic sleep latency (mins). (e) Self-reported sleep duration (hours). (f) Actigraphic sleep duration (hours). (g) self-reported wake duration (mins). (h) actigraphic wake duration (mins). (i) Self-reported sleep efficiency (%). (j) Actigraphy sleep efficiency (%).

3.3. Subjective Sleep (Diary)

Overall, both CPT and SKY interventions were associated with improvements in self-reported sleep, with no differences between groups. Findings were similar across both ITT and PP analyses.

3.3.1. Quality

There was a nonsignificant trend in the main effect of time (baseline vs. end-of-treatment) for subjective sleep quality in the ITT sample (; Cohen’s ) that reached significance among the PP sample (; Cohen’s ). Pairwise comparisons confirmed that both CPT (ITT: Cohen’s ; PP: Cohen’s ; Figure 2(a); Table 4) and SKY (ITT: Cohen’s ; PP: Cohen’s ; Figure 2(a); Table 4) demonstrated small effect size treatment-related improvements in self-reported sleep quality, and this improvement did not differ by the treatment group.

3.3.2. Latency

There was a significant main effect of time (baseline vs. end-of-treatment) for subjective sleep latency (ITT: , Cohen’s ; PP: , Cohen’s ). Pairwise comparisons confirmed that both CPT (ITT: Cohen’s ; PP: Cohen’s ; Figure 2(c); Table 4) and SKY (ITT: Cohen’s ; PP: Cohen’s ; Figure 2(c); Table 4) demonstrated small effect size treatment-related reductions in self-reported sleep latency, and this improvement did not differ by the treatment group.

3.3.3. Duration

There was a trend main effect of time (baseline vs. end-of-treatment) for subjective sleep total duration in the ITT sample (p = .054, Cohen’s d = -.21) but not in the PP sample (, Cohen’s ), suggesting both CPT and SKY were associated with trend-level, small effect size, and treatment-related increases in self-reported total sleep time, though this effect was not evident for treatment completers. Although there were no group main or interaction effects, exploratory pairwise comparisons revealed that only the SKY group demonstrated consistent improvements (ITT: Cohen’s ; PP: Cohen’s ; Figure 2(e); Table 4); CPT effect sizes were null (ITT: Cohen’s ; PP: Cohen’s ; Figure 2(e); Table 4).

3.3.4. Wake Duration

There was a significant main effect of time (baseline vs. end-of-treatment) for subjective sleep wake duration (ITT: , Cohen’s ; PP: , Cohen’s ). Pairwise comparisons confirmed that both CPT (ITT: Cohen’s ; PP: Cohen’s ; Figure 2(g); Table 4) and SKY (ITT: Cohen’s ; PP Cohen’s ; Figure 2(g); Table 4) demonstrated small effect size treatment-related reductions in self-reported total time awake during the night, and this improvement did not differ by the treatment group.

There were no significant main or interaction effects of group (CPT vs. SKY) or time (baseline vs. end-of-treatment) for subjective/self-reported sleep efficiency (Figure 2(i); Table 4).

3.4. Associations between Treatment-Related Change in PTSD Symptom Severity and Sleep

Correlations are presented in Supplementary Tables 1 and 2. Overall, sleep actigraphy failed to show any statistically significant treatment-related associations with overall PTSD symptom severity. However, sleep as measured by the PTSD sleep symptoms and sleep diary showed numerous statistically significant correlations with overall PTSD symptom severity. The directions of the associations were in the expected direction: improvements in sleep following either CPT or SKY were positively associated with treatment-related improvements in global PTSD severity. The strongest associations were between PCL/CAPS sleep symptoms and total PCL/CAPS. For the sleep diary measures, following CPT, associations were strongest between PCL total and sleep quality, latency, and duration change scores, and following SKY, they were strongest between CAPS total and sleep latency, duration, number of awakenings, and wake duration change scores.

4. Discussion

To our knowledge, this is the first study to investigate sleep as an outcome of CPT or SKY for PTSD across a combination of subjective diary, PTSD sleep symptom severity, and objective actigraphic measures. Across subjective sleep measures, we found significant treatment-related improvements in self-reported sleep quality, shorter sleep latency, less total time awake during the night, fewer nightmares, and less insomnia, for both CPT and SKY. However, there were no statistically significant effects of either CPT or SKY for any of the objective actigraphy-measured sleep indices.

Improvements in subjective sleep measures following CPT lend support to a growing body of evidence that trauma-focused psychotherapy for PTSD improves sleep alongside PTSD symptoms. Previous studies examined either female-only samples [13, 15], chronic PTSD linked to multiple traumas [16], or actively serving Military/Defence personnel [14]. Our findings confirm that these treatment-related subjective sleep improvements extend to a sample of predominantly male ex-serving Military/Defence (i.e., veterans). Interestingly, SKY, a regulated, cyclical, yoga breathing meditation, also produced improvements in subjective sleep measures. To date, much of the literature on yoga for sleep has focused on cancer [42, 43], older adults [44], or healthy adults [45]. Here, we extend these findings to suggest that yoga-based interventions may also be beneficial for subjective sleep among individuals with emotional or mental health disorders like PTSD. Given the high drop-out rates associated with trauma-focused psychotherapy, these positive sleep effects for SKY further enhance its promise as a PTSD treatment. As sleep improvements are associated with resilience [46] and general physical and mental wellness [5, 47–50], future research might investigate whether psychological and mind-body interventions like CPT and SKY could be delivered to both active and returned military/defence personnel during recruitment training and discharge to build resilience and protect against future psychopathology and/or physical health problems.

Despite statistically significant improvements in subjective diary and PTSD symptom severity sleep measures, we did not achieve full remission of all sleep disturbances following either CPT or SKY. First, in our study, PTSD insomnia symptoms remained at end-of-treatment, on average, within a range considered clinically significant as measured by the PCL (≥3; [32]) but not by the CAPS (≥2; [33]). Second, total sleep duration was, on average, below recommendations for adults (<7-9 hrs; [35, 51]). However, on average, at end-of-treatment across both groups, PTSD nightmares were below clinical threshold on both PCL and CAPS, subjective sleep quality was fair, and sleep latency and efficiency were at clinical cut-off for insomnia (30 min and 85%, respectively; [52]), whereas at baseline, they were closer to (though slightly better than) ratings seen in individuals with insomnia disorder (49 min and 70%, respectively; [35]). Overall, this suggests fair-to-good sleep on these indices (though it is worth noting that PTSD nightmares were, on average, at or just below the threshold for both groups at baseline). These general sleep improvements are consistent with the PTSD, depression, and negative affect improvements we observed with both SKY and CPT in the primary outcomes study [25]. The presence of residual sleep disturbance symptoms despite improvements in PTSD severity is consistent with extant literature [13–15] and aligns with our primary outcomes study where many veterans retained significant residual PTSD symptoms despite overall treatment-related improvements (an effect commonly reported in PTSD treatment research; [53, 54]). In particular, PTSD insomnia symptoms commonly remain despite improvements on PTSD nightmares and self-reported sleep diary measures [16], which has led some researchers to speculate this residual insomnia represents a distinct disorder rather than secondary PTSD symptoms [14]. As poor sleep is a risk factor for PTSD relapse [6–8] and poor mental and physical health more generally [5, 47–50], it is critical for PTSD interventions to target sleep. A recent meta-analysis of RCTs suggests that cognitive behavioural therapy for insomnia (CBT-I) improves PTSD symptoms at similar effect sizes to first-line PTSD treatments [55], yet all comparisons were to wait-list controls. Future research should investigate head-to-head comparisons of CBT-I to trauma-focused psychotherapies and assess for noninferiority for both sleep and PTSD outcomes, as well as for any potential additive or interactive effects of their combinations. These studies should also explore the potential moderating effects of comorbid insomnia disorder and comorbid sleep apnoea.

We did not observe statistically significant changes in any of the objective sleep indices following CPT or SKY. While exploratory pairwise comparisons revealed some (nonsignificant) small-to-moderate effect size within-group changes, these effects were not apparent in data visualisations, and inconsistent findings concealed any clear pattern in the data. Overall, this suggests a high level of variability in the objective sleep indices rather than any true group or treatment-related differences, possibly due to the high proportion of likely sleep apnoea in our sample [56] which may obscure any treatment-related effects. Alternatively, our lack of significant treatment-related objective sleep effects might be due to floor effects: the objective sleep indices in our study, both at baseline and end-of-treatment, were consistent with those of objectively assessed “good sleepers” (sleep duration >5.37 hrs; [35]) and/or better than the objective clinical cut-offs for insomnia (sleep latency <20 min, sleep efficiency >80%; [57]), suggesting no clinically-significant actigraphy-measured sleep difficulties in our sample. Indeed, a diagnosis of insomnia disorder requires only a (self-reported) dissatisfaction with sleep quality/quantity [1], not formal confirmation via objective measures, and our findings are consistent with several studies that have failed to find agreement between subjective and objective sleep measures [35, 58, 59]. Specifically, one noninferiority RCT that compared CBT-I to Tai Chi Chih (i.e., a treatment design similar to our study, comparing a psychological to a complementary and integrative health intervention) found improvements in self-reported but not polysomnographic sleep across both groups [60]. A failure to find treatment-related improvements in objective measures adds further weight to the argument that it may be more the perceived (i.e., subjective) disruptions to sleep that underpin clinical mental health disorders, rather than objective disruptions. A growing body of evidence demonstrates that maladaptive beliefs about sleep may drive the development and maintenance of insomnia and influence self-report ratings of sleep [61, 62], especially in individuals with emotional disorders like PTSD [63–65]. CBT-I, the gold standard evidence-based intervention for sleep, targets both poor sleep hygiene and maladaptive beliefs about sleep, and at least one study has used actigraphy to inform behavioural experiments and shift sleep cognitions in the context of therapy for individuals with insomnia [66]. While our RCT employed a trauma-focused psychotherapy (CPT) that does not specifically target sleep cognitions, it is possible that by targeting beliefs about the trauma, veterans were able to transfer these reappraisal skills to other domains such as sleep beliefs, thus leading to improvement in self-reported sleep. Yoga practices like SKY typically cultivate mindfulness which could lead to similar enhancement of reappraisal skills, possibly indirectly via increased acceptance [67]. While the supplementary correlation analyses are consistent with these inferences, mechanistic studies that explore reappraisal and acceptance as mediators of treatment outcome are needed to confirm these hypotheses.

The main strength of our study is the use of both subjective and objective sleep measures to gain a more comprehensive understanding of sleep responses to CPT or SKY for PTSD. Furthermore, we used both standardised sleep-specific diary measures and more general PTSD insomnia/nightmare sleep symptom items to increase the reliability of subjective self-report measures and to allow direct comparison with previous studies that have used only one of these self-report measures. A clear picture emerged of consistent improvements across subjective diary and PTSD symptom severity sleep measures for both CPT and SKY. Yet, inconsistencies between subjective and objective measures and subtle differences in whether improvements reached clinical threshold support continued use of multiple measures in clinical treatment studies involving PTSD.

A limitation of our study is that the sleep diary and actigraphy measures were taken from only a single night’s sleep at each baseline and end-of-treatment. Assessing 1-2 continuous weeks of data tends to increase both their independent reliabilities [61, 68] and the likelihood of strong concordance between the two [35], especially for latency [57]. Moreover, night-to-night variability in sleep is more strongly related to subjective than objective measures [69]. We chose a single night’s sleep to reduce participant burden [70], given that the high number of treatment-related assessments in our RCT. The consistency of findings across measures with varying timeframes (sleep diary rated across one night, CAPS and PCL rated across the previous month) increases confidence in their reliability. Furthermore, all overnight sleep assessments were taken on weekday nights; therefore, we reduced the likelihood of impact from weekday versus weeknight variabilities [71, 72]. However, it is possible that the single-night assessment period accounts for our inconsistent and nonsignificant actigraphy effects. Similarly, another limitation is that we did not conduct a comprehensive sleep evaluation (e.g., presence of diagnosed mental or physical sleep disorders, use of sleep medications). Self-report measures suggest, on average, the veterans in both the CPT and SKY groups likely had sleep apnoea, with no differences between groups. This high prevalence rate is common among individuals with PTSD, especially veterans [73]. However, it may also explain the lack of concordance between our self-report and actigraphy sleep measures, as there is some suggestion that actigraphy precision may be lower for single night assessment of individuals with sleep apnoea [56]. Future research should replicate our study using a longer sleep assessment period (e.g., 1-2 weeks); a more general sleep measure like the Insomnia Severity Index (past 2 weeks; [74]), Pittsburgh Sleep Quality Index (past month; [75]), or Sleep Timing Questionnaire (normal average week; [70]); and conduct sensitivity analyses based on presence/absence of sleep disorders (using clinician administered or objective tests) and use of sleep medications. We also acknowledge our use of the outdated PCL-C due to RCT design parameters [25, 26] and recommend future studies replicate using the PCL-5, though there is no difference between the two measures (nor DSM criteria) for the insomnia/nightmare items.

5. Conclusion

To our knowledge, this is the first study to investigate sleep as an outcome of either CPT or SKY for PTSD across a combination of subjective diary, PTSD symptom severity, and objective actigraphic measures. We found significant treatment-related improvements in self-reported and clinician-administered measures of sleep quality, shorter sleep latency, less total time awake during night, fewer nightmares, and less insomnia for both CPT and SKY. In contrast, we did not observe significant changes in any of the objective (actigraphy) sleep indices for either CPT or SKY. The similarities in sleep-related improvements between CPT and SKY lend support to a growing body of evidence that trauma-focused psychotherapy for PTSD improves sleep and suggest that yoga-based interventions may also be beneficial for sleep among individuals with emotional or mental health disorders like PTSD.

Data Availability

The datasets generated and/or analysed during the current study are not publicly available due to institutional regulations protecting service member data but are available from the corresponding author on reasonable written request (may require data use agreements to be developed).

Ethical Approval

The protocol was approved by the Stanford University Institutional Review Board and conducted in accordance with the Declaration of Helsinki. The full procedure for the RCT is described elsewhere [25, 26].

Participants gave informed consent to participate in the study.

Disclosure

R. Jay Schulz-Heik is now at the Peninsula Behavioral Health, Palo Alto, CA 94306, United States of America. Timothy J. Avery is now at the Peninsula Vet Center, Department of Veterans Affairs, Menlo Park, CA 94025, United States of America. Funding bodies have not and will not participate in the study design, the collection, management, analysis, or interpretation of data, nor the writing of findings for publication. The contents of this manuscript do not represent the views of the US Department of Veterans Affairs or the United States Government.

Conflicts of Interest

The authors declare no conflict of interest.

Authors’ Contributions

Danielle C. Mathersul did the conceptualization, methodology, validation, formal analysis, investigation, data curation, writing—original draft, and writing—review and editing. R. Jay Schulz-Heik was assigned to software, validation, investigation, data curation, and writing—review and editing. Timothy J. Avery performed the investigation, and writing—review and editing. Santiago Allende conducted the visualization, and writing—review and editing. Jamie M. Zeitzer worked on the software, validation, resources, and writing—review and editing. Peter J. Bayley performed the conceptualization, methodology, investigation, resources, writing—review and editing, supervision, project administration, and funding acquisition.

Acknowledgments

This RCT was funded by a Department of Veterans Affairs RR&D Merit Review (1 I01 RX001485-01; PJB). DCM, RJSH, and TJA received Department of Veterans Affairs Advanced Fellowships in the War Related Illness and Injury Study Center, a National Veterans Affairs Post-Deployment Health Resource. Open access publishing is facilitated by Murdoch University, as part of the Wiley-Murdoch University agreement via the Council of Australian University Librarians. The authors would like to thank the participants for their time. We also thank Julia S. Tang, Kamini Dixit, Melinda Wong, Rachael H. Cho, Marcelle A. Friedman, Jennifer Hanft, and Adam S. Burn for assistance with data collection.

Supplementary Materials

Supplementary 1. CONSORT 2010 checklist of information for the RCT.

Supplementary 2. Supplementary tables: simple Pearson correlations between each of the sleep measures (self-reported sleep diary, PTSD sleep symptom severity items, and sleep actigraphy) and overall PTSD symptom severity change scores (baseline minus end-of-treatment; PCL total/CAPS total, with and without insomnia/nightmare sleep items, per recommendations).

References

APA, Diagnostic and Statistical Manual of Mental Disorders, American Psychiatric Publishing, 5th edition, 2013.
M. E. Milanak, K. L. Zuromski, I. Cero, A. K. Wilkerson, H. S. Resnick, and D. G. Kilpatrick, “Traumatic event exposure, posttraumatic stress disorder, and sleep disturbances in a National Sample of U.S. adults,” Journal of Traumatic Stress, vol. 32, no. 1, pp. 14–22, 2019.
View at: Publisher Site | Google Scholar
M. B. Miller, J. Metrik, B. Borsari, and K. M. Jackson, “Longitudinal associations between sleep, intrusive thoughts, and alcohol problems among veterans,” Alcoholism: Clinical and Experimental Research, vol. 43, no. 11, pp. 2438–2445, 2019.
View at: Publisher Site | Google Scholar
A. D. Seelig, I. G. Jacobson, B. Smith et al., “Sleep patterns before, during, and after deployment to Iraq and Afghanistan,” Sleep, vol. 33, no. 12, pp. 1615–1622, 2010.
View at: Publisher Site | Google Scholar
S. P. Byrne, E. McCarthy, J. C. DeViva, S. M. Southwick, and R. H. Pietrzak, “Prevalence, risk correlates, and health comorbidities of insomnia in US military veterans: results from the 2019–2020 National Health and resilience in veterans study,” Journal of Clinical Sleep Medicine, vol. 17, no. 6, pp. 1267–1277, 2021.
View at: Publisher Site | Google Scholar
R. N. McLay, W. P. Klam, and S. L. Volkert, “Insomnia is the most commonly reported symptom and predicts other symptoms of post-traumatic stress disorder in U.S. service members returning from military deployments,” Military Medicine, vol. 175, no. 10, pp. 759–762, 2010.
View at: Publisher Site | Google Scholar
D. Kartal, H. A. Arjmand, T. Varker et al., “Cross-lagged relationships between insomnia and posttraumatic stress disorder in treatment-receiving veterans,” Behavior Therapy, vol. 52, no. 4, pp. 982–994, 2021.
View at: Publisher Site | Google Scholar
R. C. Rosen, B. Cikesh, S. Fang et al., “Posttraumatic stress disorder severity and insomnia-related sleep disturbances: longitudinal associations in a large, gender-balanced cohort of combat-exposed veterans,” Journal of Traumatic Stress, vol. 32, no. 6, pp. 936–945, 2019.
View at: Publisher Site | Google Scholar
R. C. Cox and B. O. Olatunji, “Sleep in the anxiety-related disorders: a meta-analysis of subjective and objective research,” Sleep Medicine Reviews, vol. 51, 2020.
View at: Publisher Site | Google Scholar
Y. Zhang, R. Ren, L. D. Sanford et al., “Sleep in posttraumatic stress disorder: a systematic review and meta-analysis of polysomnographic findings,” Sleep Medicine Reviews, vol. 48, article 101210, 2019.
View at: Publisher Site | Google Scholar
V. I. Spoormaker and P. Montgomery, “Disturbed sleep in post-traumatic stress disorder: secondary symptom or core feature?” Sleep Medicine Reviews, vol. 12, no. 3, pp. 169–184, 2008.
View at: Publisher Site | Google Scholar
A. R. Maher, E. A. Apaydin, L. Hilton et al., “Sleep management in posttraumatic stress disorder: a systematic review and meta-analysis,” Sleep Medicine, vol. 87, pp. 203–219, 2021.
View at: Publisher Site | Google Scholar
C. A. Gutner, M. D. Casement, K. Stavitsky Gilbert, and P. A. Resick, “Change in sleep symptoms across cognitive processing therapy and prolonged exposure: a longitudinal perspective,” Behaviour Research and Therapy, vol. 51, no. 12, pp. 817–822, 2013.
View at: Publisher Site | Google Scholar
K. E. Pruiksma, D. J. Taylor, J. S. Wachen et al., “Residual sleep disturbances following PTSD treatment in active duty military personnel,” Psychological Trauma: Theory, Research, Practice, and Policy, vol. 8, no. 6, pp. 697–701, 2016.
View at: Publisher Site | Google Scholar
P. P. Schnurr and C. A. Lunney, “Residual symptoms following prolonged exposure and present-centered therapy for PTSD in female veterans and soldiers,” Depression and Anxiety, vol. 36, 169 pages, 2019.
View at: Publisher Site | Google Scholar
E. Woodward, A. Hackmann, J. Wild, N. Grey, D. M. Clark, and A. Ehlers, “Effects of psychotherapies for posttraumatic stress disorder on sleep disturbances: results from a randomized clinical trial,” Behaviour Research and Therapy, vol. 97, pp. 75–85, 2017.
View at: Publisher Site | Google Scholar
ACPMH, Australian Guidelines for the Treatment of Acute Stress Disorder and Posttraumatic Stress Disorder, AustralianCentreforPosttraumaticMentalHealth, Phoenix Australia, 2013.
D. M. Benedek, M. J. Friedman, D. Zatzick, and R. J. Ursano, “Guideline watch (March 2009): practice guideline for the treatment of patients with acute stress disorder and posttraumatic stress disorder,” Focus, vol. 7, no. 2, pp. 204–213, 2009.
View at: Publisher Site | Google Scholar
ISTSS, Effective treatments for PTSD: practice guidelines from the International Society for Traumatic Stress Studies, E. B. Foa, T. M. Keane, M. J. Friedman, and J. A. Cohen, Eds., Guilford Press, 2nd edition, 2008.
NICE, Post-Traumatic Stress Disorder: The Management of PTSD in Adults and Children in Primary and Secondary Care,vol. 26, NationalClinicalPracticeGuideline, Ed., Gaskell Royal College of Psychiatrists and The British Psychological Society, 2005.
VA/DoD, VA/DoD Clinical Practice Guideline for the Management of Posttraumatic Stress Disorder and Acute Stress Disorder, vol. 3.0 (TheManagementofPosttraumaticStressDisorderWorkGroup, Ed.), Department of Veterans Affairs and Department of Defense, 2017.
WHO, Guidelines for the Management of Conditions Specifically Related to Stress, World Health Organization Press (WHO Press), 2013.
A. Althubaiti, “Information bias in health research: definition, pitfalls, and adjustment methods,” Journal of Multidisciplinary Healthcare, vol. 9, pp. 211–217, 2016.
View at: Publisher Site | Google Scholar
F. W. Weathers, B. T. Litz, T. M. Keane, P. A. Palmieri, B. P. Marx, and P. P. Schnurr, The PTSD checklist for DSM-5 (PCL-5), 2013, http://www.ptsd.va.gov.
P. J. Bayley, R. J. Schulz-Heik, J. Tang et al., “Randomised clinical non-inferiority trial of breathing-based meditation and cognitive processing therapy for symptoms of post-traumatic stress disorder in military veterans,” BMJ Open, vol. 12, no. 8, article e056609, 2022.
View at: Publisher Site | Google Scholar
D. C. Mathersul, J. S. Tang, R. Jay Schulz-Heik, T. J. Avery, E. M. Seppälä, and P. J. Bayley, “Study protocol for a non-inferiority randomised controlled trial of SKY breathing meditation versus cognitive processing therapy for PTSD among veterans,” BMJ Open, vol. 9, no. 4, article 027150, 2019.
View at: Publisher Site | Google Scholar
C. J. Greene, L. A. Morland, V. L. Durkalski, and B. C. Frueh, “Noninferiority and equivalence designs: issues and implications for mental health research,” Journal of Traumatic Stress, vol. 21, no. 5, pp. 433–439, 2008.
View at: Publisher Site | Google Scholar
G. Maislin, A. I. Pack, N. B. Kribbs et al., “A survey screen for prediction of apnea,” Sleep, vol. 18, no. 3, pp. 158–166, 1995.
View at: Publisher Site | Google Scholar
H. Beneš and R. Kohnen, “Validation of an algorithm for the diagnosis of restless legs syndrome: the restless legs syndrome-diagnostic index (RLS-DI),” Sleep Medicine, vol. 10, no. 5, pp. 515–523, 2009.
View at: Publisher Site | Google Scholar
W. R. Pigeon, C. E. Campbell, K. Possemato, and P. Ouimette, “Longitudinal relationships of insomnia, nightmares, and PTSD severity in recent combat veterans,” Journal of Psychosomatic Research, vol. 75, no. 6, pp. 546–550, 2013.
View at: Publisher Site | Google Scholar
D. V. Sheehan, M.I.N.I. Mini International Neuropsychiatric Interview. English version 7.0.0 for DSM-5, University of South Florida, Tampa, USA, 2014.
F. W. Weathers, B. T. Litz, D. Herman, J. Huska, and T. M. Keane, The PTSD checklist-civilian version (PCL-C), National Center for PTSD, 1994, http://www.ptsd.va.gov.
F. W. Weathers, M. J. Bovin, D. J. Lee et al., “The clinician-administered PTSD scale for DSM-5 (CAPS-5): development and initial psychometric evaluation in military veterans,” Psychological Assessment, vol. 30, no. 3, pp. 383–395, 2018.
View at: Publisher Site | Google Scholar
R. J. Cole, D. F. Kripke, W. Gruen, D. J. Mullaney, and J. C. Gillin, “Automatic sleep/wake identification from wrist activity,” Sleep, vol. 15, no. 5, pp. 461–469, 1992.
View at: Publisher Site | Google Scholar
K. H. G. Maich, A. M. Lachowski, and C. E. Carney, “Psychometric properties of the consensus sleep diary in those with insomnia disorder,” Behavioral Sleep Medicine, vol. 16, no. 2, pp. 117–134, 2018.
View at: Publisher Site | Google Scholar
H. C. Kraemer, “Discovering, comparing, and combining moderators of treatment on outcome after randomized clinical trials: a parametric approach,” Statistics in Medicine, vol. 32, no. 11, pp. 1964–1973, 2013.
View at: Publisher Site | Google Scholar
H. C. Kraemer and C. M. Blasey, “Centring in regression analyses: a strategy to prevent errors in statistical inference,” International Journal of Methods in Psychiatric Research, vol. 13, no. 3, pp. 141–151, 2004.
View at: Publisher Site | Google Scholar
J. F. Dawson, “Moderation in management research: what, why, when, and how,” Journal of Business and Psychology, vol. 29, no. 1, pp. 1–19, 2014.
View at: Publisher Site | Google Scholar
D. T. L. Shek and C. M. S. Ma, “Application of SPSS linear mixed methods to adolescent development research: basic concepts and steps,” International Journal on Disability and Human Development, vol. 13, no. 2, pp. 169–182, 2014.
View at: Publisher Site | Google Scholar
I. Guttman, “Premium and protection of several procedures for dealing with outliers when sample sizes are moderate to large,” Technometrics, vol. 15, no. 2, pp. 385–404, 1973.
View at: Publisher Site | Google Scholar
S. Landau and B. S. Everitt, A Handbook of Statistical Analyses Using SPSS, Chapman and Hall/CRC, 2003.
View at: Publisher Site
C. Kreutz, M. E. Schmidt, and K. Steindorf, “Effects of physical and mind–body exercise on sleep problems during and after breast cancer treatment: a systematic review and meta-analysis,” Breast Cancer Research and Treatment, vol. 176, no. 1, pp. 1–15, 2019.
View at: Publisher Site | Google Scholar
N. Takemura, D. S. T. Cheung, R. Smith et al., “Effectiveness of aerobic exercise and mind-body exercise in cancer patients with poor sleep quality: a systematic review and meta-analysis of randomized controlled trials,” Sleep Medicine Reviews, vol. 53, 2020.
View at: Publisher Site | Google Scholar
M. Weber, T. Schnorr, M. Morat, T. Morat, and L. Donath, “Effects of mind–body interventions involving meditative movements on quality of life, depressive symptoms, fear of falling and sleep quality in older adults: a systematic review with meta-analysis,” International Journal of Environmental Research and Public Health, vol. 17, no. 18, article 6556, pp. 1–22, 2020.
View at: Publisher Site | Google Scholar
X. Wang, P. Li, C. Pan, L. Dai, Y. Wu, and Y. Deng, “The effect of mind-body therapies on insomnia: a systematic review and meta-analysis,” Evidence-based Complementary and Alternative Medicine, vol. 2019, Article ID 9359807, 17 pages, 2019.
View at: Publisher Site | Google Scholar
C. C. Tomaso, A. B. Johnson, and T. D. Nelson, “The effect of sleep deprivation and restriction on mood, emotion, and emotion regulation: three meta-analyses in one,” Sleep, vol. 44, no. 6, pp. 1–30, 2021.
View at: Publisher Site | Google Scholar
J. P. Davis, J. Prindle, S. K. Saba et al., “What's sleep got to do with it? Longitudinal associations between insomnia, PTSD, and alcohol use among U.S. Veterans,” Addictive Behaviors, vol. 132, article 107358, 2022.
View at: Publisher Site | Google Scholar
D. G. Maguire, M. W. Ruddock, M. E. Milanak, T. Moore, D. Cobice, and C. Armour, “Sleep, a governor of morbidity in PTSD: a systematic review of biological markers in PTSD-related sleep Disturbances,” Nature and Science of Sleep, vol. 12, pp. 545–562, 2020.
View at: Publisher Site | Google Scholar
M. S. McCarthy, C. Hoffmire, L. A. Brenner, and S. Nazem, “Sleep and timing of death by suicide among U.S. veterans 2006-2015: analysis of the American time use survey and the National Violent Death Reporting System,” Sleep, vol. 42, no. 8, article zsz094, pp. 1–8, 2019.
View at: Publisher Site | Google Scholar
N. A. Short, N. P. Allan, M. E. Oglesby, S. Moradi, N. B. Schmidt, and T. Stecker, “Prospective associations between insomnia symptoms and alcohol use problems among former and current military service personnel,” Drug and Alcohol Dependence, vol. 199, pp. 35–41, 2019.
View at: Publisher Site | Google Scholar
M. Hirshkowitz, K. Whiton, S. M. Albert et al., “National sleep foundation's sleep time duration recommendations: methodology and results summary,” Sleep Health, vol. 1, no. 1, pp. 40–43, 2015.
View at: Publisher Site | Google Scholar
C. M. Morin, P. J. Hauri, C. A. Espie, A. J. Spielman, D. J. Buysse, and R. R. Bootzin, “Nonpharmacologic treatment of chronic insomnia,” Sleep, vol. 22, no. 8, pp. 1134–1156, 1999.
View at: Publisher Site | Google Scholar
M. A. Schottenbauer, C. R. Glass, D. B. Arnkoff, V. Tendick, and S. H. Gray, “Nonresponse and dropout rates in outcome studies on PTSD: review and methodological considerations,” Psychiatry, vol. 71, no. 2, pp. 134–168, 2008.
View at: Publisher Site | Google Scholar
M. M. Steenkamp, B. T. Litz, C. W. Hoge, and C. R. Marmar, “Psychotherapy for military-related PTSD: a review of randomized clinical trials,” JAMA, vol. 314, no. 5, pp. 489–500, 2015.
View at: Publisher Site | Google Scholar
F. Y. Y. Ho, C. S. Chan, and K. N. S. Tang, “Cognitive-behavioral therapy for sleep disturbances in treating posttraumatic stress disorder symptoms: a meta-analysis of randomized controlled trials,” Clinical Psychology Review, vol. 43, pp. 90–102, 2016.
View at: Publisher Site | Google Scholar
A. Alakuijala, T. Sarkanen, T. Jokela, and M. Partinen, “Accuracy of actigraphy compared to concomitant ambulatory polysomnography in narcolepsy and other sleep disorders,” Frontiers in Neurology, vol. 12, 2021.
View at: Publisher Site | Google Scholar
D. Fekedulegn, M. E. Andrew, M. Shi, J. M. Violanti, S. Knox, and K. E. Innes, “Actigraphy-based assessment of sleep parameters,” Annals of Work Exposures and Health, vol. 64, no. 4, pp. 350–367, 2020.
View at: Publisher Site | Google Scholar
B. Miner, K. L. Stone, J. M. Zeitzer et al., “Self-reported and actigraphic short sleep duration in older adults,” Journal of Clinical Sleep Medicine, vol. 18, no. 2, pp. 403–413, 2022.
View at: Publisher Site | Google Scholar
A. Sadeh, “The role and validity of actigraphy in sleep medicine: an update,” Sleep Medicine Reviews, vol. 15, no. 4, pp. 259–267, 2011.
View at: Publisher Site | Google Scholar
M. R. Irwin, R. Olmstead, C. Carrillo et al., “Tai Chi Chih compared with cognitive behavioral therapy for the treatment of insomnia in survivors of breast cancer: a randomized, partially blinded, noninferiority trial,” Journal of Clinical Oncology, vol. 35, no. 23, pp. 2656–2665, 2017.
View at: Publisher Site | Google Scholar
A. E. Carney, D. L. Wescott, N. E. Carmona, C. E. Carney, and K. A. Roecklein, “The role of beliefs about sleep in nightly perceptions of sleep quality across a depression continuum,” Journal of Affective Disorders, vol. 311, pp. 440–445, 2022.
View at: Publisher Site | Google Scholar
J. D. Edinger, A. I. Fins, D. M. Glenn et al., “Insomnia and the eye of the beholder: are there clinical markers of objective sleep disturbances among adults with and without insomnia complaints?” Journal of Consulting and Clinical Psychology, vol. 68, no. 4, pp. 586–593, 2000.
View at: Publisher Site | Google Scholar
S. Chang, Q. Ma, E. Seow et al., “Sleep beliefs and attitudes and the association with insomnia among psychiatric outpatients,” Journal of Mental Health, vol. 29, no. 1, pp. 33–39, 2020.
View at: Publisher Site | Google Scholar
M. Jansson-Frojmark and S. J. Linton, “The role of psychological mechanisms to insomnia in its early phase: a focus on arousal, distress, and sleep-related beliefs,” Psychology and Health, vol. 23, no. 6, pp. 691–705, 2008.
View at: Publisher Site | Google Scholar
C. M. Morin, F. Blais, and J. Savard, “Are changes in beliefs and attitudes about sleep related to sleep improvements in the treatment of insomnia?” Behaviour Research and Therapy, vol. 40, no. 7, pp. 741–752, 2002.
View at: Publisher Site | Google Scholar
N. K. Y. Tang and A. G. Harvey, “Altering misperception of sleep in insomnia: behavioral experiment versus verbal feedback,” Journal of Consulting and Clinical Psychology, vol. 74, no. 4, pp. 767–776, 2006.
View at: Publisher Site | Google Scholar
P. R. Goldin, A. S. Morrison, H. Jazaieri, R. G. Heimberg, and J. J. Gross, “Trajectories of social anxiety, cognitive reappraisal, and mindfulness during an RCT of CBGT versus MBSR for social anxiety disorder,” Behaviour Research and Therapy, vol. 97, pp. 1–13, 2017.
View at: Publisher Site | Google Scholar
W. K. Wohlgemuth, J. D. Edinger, A. I. Fins, and R. J. Sullivan Jr., “How many nights are enough? The short-term stability of sleep parameters in elderly insomniacs and normal sleepers,” Psychophysiology, vol. 36, no. 2, pp. 233–244, 1999.
View at: Publisher Site | Google Scholar
S. Lemola, T. Ledermann, and E. M. Friedman, “Variability of sleep duration is related to subjective sleep quality and subjective well-being: an actigraphy study,” PLoS ONE, vol. 8, no. 8, article e71292, 2013.
View at: Publisher Site | Google Scholar
T. H. Monk, D. J. Buysse, K. S. Kennedy, J. M. Potts, J. M. DeGrazia, and J. M. Miewald, “Measuring sleep habits without using a diary: the sleep timing questionnaire,” Sleep, vol. 26, no. 2, pp. 208–212, 2003.
View at: Publisher Site | Google Scholar
T. Åkerstedt, F. Ghilotti, A. Grotta et al., “Sleep duration and mortality – does weekend sleep matter?” Journal of Sleep Research, vol. 28, no. 1, article e12712, 2019.
View at: Publisher Site | Google Scholar
S. E. Roepke and J. F. Duffy, “Differential impact of chronotype on weekday and weekend sleep timing and duration,” Nature and Science of Sleep, vol. 2010, no. 2, pp. 213–220, 2010.
View at: Publisher Site | Google Scholar
Y. Zhang, J. G. Weed, R. Ren, X. Tang, and W. Zhang, “Prevalence of obstructive sleep apnea in patients with posttraumatic stress disorder and its impact on adherence to continuous positive airway pressure therapy: a meta-analysis,” Sleep Medicine, vol. 36, pp. 125–132, 2017.
View at: Publisher Site | Google Scholar
C. H. Bastien, A. Vallières, and C. M. Morin, “Validation of the insomnia severity index as an outcome measure for insomnia research,” Sleep Medicine, vol. 2, no. 4, pp. 297–307, 2001.
View at: Publisher Site | Google Scholar
D. J. Buysse, C. F. Reynolds Iii, T. H. Monk, S. R. Berman, and D. J. Kupfer, “The Pittsburgh sleep quality index: a new instrument for psychiatric practice and research,” Psychiatry Research, vol. 28, no. 2, pp. 193–213, 1989.
View at: Publisher Site | Google Scholar

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Copyright © 2023 Danielle C. Mathersul et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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