Erin Koffel

Psychological and Behavioral Interventions for Managing Insomnia Disorder: An Evidence Report for a Clinical Practice Guideline by the American College of Physicians

Sleep difficulties, including the inability to initiate or maintain sleep, are common in adults. Sleep difficulties are typically transient; however, when they become chronic and cause distress or daytime dysfunction, insomnia disorder may be present. The American Psychiatric Associations Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, defines insomnia disorder as a predominant symptom of difficulty with sleep initiation, difficulty maintaining sleep, or early-morning waking with inability to return to sleep causing clinically significant distress or impairment in activities, occurring at least 3 nights per week for 3 months or more (1). Furthermore, individuals must have adequate opportunity for sleep and the symptoms cannot be better explained by medical or mental conditions, including another sleep disorder (such as breathing-related sleep disorder), or medication or substance use. The term previously used for insomnia disorder is chronic insomnia (14), for which diagnostic criteria required sleep problems lasting from weeks to months. These criteria are empirically similar to current criteria for insomnia disorder. We use the term insomnia disorder even though much of the primary research has used other terminology (such as chronic insomnia and persistent insomnia). Between 6% and 10% of adults meet the diagnostic criteria for insomnia disorder (4). Duration ranges from 1 to 20 years across longitudinal studies (5). Insomnia disorder is more common in female patients and older adults (6, 7). Older adults typically report difficulty maintaining sleep as opposed to initiating sleep, which is common in younger adults (8). Many treatment types are available once insomnia disorder is accurately diagnosed by using established diagnostic criteria (4, 9). These include psychological and behavioral treatments, pharmacologic therapies, and complementary and alternative medicine. The American Academy of Sleep Medicine recommends psychological and behavioral interventions and supports short-term supplementary medication (9, 10). Psychological and behavioral interventions include cognitive behavioral therapy for insomnia (CBT-I), multicomponent behavioral therapy (brief behavioral therapy for insomnia), and single-component interventions (such as sleep hygiene and education, stimulus control, sleep restriction, and relaxation) (Table). Cognitive behavioral therapy for insomnia most commonly includes behavioral therapies (sleep restriction, stimulus control, relaxation training), cognitive therapy (cognitive restructuring) to change dysfunctional beliefs about sleep, as well as sleep hygiene education (3). Multicomponent behavioral therapies combine several behavioral therapies and do not include a cognitive component. Table. Psychological and Behavioral Interventions for Insomnia Disorder* Treatment goals include improving quality and quantity of sleep and associated impairments (10). Ideally, meaningful improvements in global outcomes measuring sleep and associated distress and dysfunction are realized. The Insomnia Severity Index (ISI) and the Pittsburgh Sleep Quality Index (PSQI) are commonly used for measuring global outcomes. Sleep outcomes include specific sleep variables (sleep-onset latency [SOL], wake time after sleep onset [WASO], total sleep time [TST], sleep efficiency (sleep time/time in bed), and sleep quality. Sleep variables can be measured objectively (with polysomnography or actigraphy) or subjectively (sleep diaries). Guidelines suggest monitoring symptoms with sleep diaries and polysomography is not indicated (10). We conducted a systematic review on the management of insomnia disorder for the Agency for Healthcare Research and Quality (11). This article reports evidence on psychological and behavioral interventions. Another article reports on the evidence on pharmacologic interventions and the comparison of pharmacologic interventions with psychological and behavioral interventions (12), and the full report provides evidence on complementary and alternative interventions. This evidence was used by the American College of Physicians to develop the guideline on the treatment of insomnia disorder in primary care. Evidence summarized here enhances previous reports (1315) by providing a comprehensive evaluation of psychological and behavioral interventions across all delivery modes with a primary emphasis on global outcomes. Methods Data Sources and Searches We searched bibliographic databases, including MEDLINE, Embase, and PsycINFO via Ovid, as well as the Cochrane Library, to identify randomized, controlled trials published from 2004 through September 2015 (Supplement). We identified studies published before 2004 by searching the citations in relevant systematic reviews. Supplement. Supplementary Material Study Selection Two investigators independently reviewed titles and abstracts of search results to identify potentially eligible references. Two investigators independently screened full texts of those references to determine whether inclusion criteria were met. We included randomized, controlled trials of psychological and behavioral interventions if they enrolled adults, provided at least 4 weeks of treatment, reported global or sleep outcomes, and were published in English. We excluded trials enrolling pure subgroups of patients with major medical conditions or conditions that may explain the sleep problems (such as menopause, pregnancy, and neurologic conditions). Data Extraction and Quality Assessment Risk of bias was independently assessed by two investigators using an instrument developed using Agency for Healthcare Research and Quality guidance (16) and was summarized as low, medium, or high on the basis of summary risk of bias and confidence that results were believable given limitations. Study, participant, and treatment characteristics; outcomes; and adverse events were extracted from eligible trials with low or moderate risk of bias. Data Synthesis and Analysis We used RevMan 5.2 (Nordic Cochrane Center) for pooling when adequate data were provided and populations, interventions, and outcomes were similar (17). DerSimonian and Laird random-effects estimates of risk ratios and absolute risk differences with 95% CIs were calculated for categorical outcomes, and weighted mean differences (WMDs) and/or standardized mean differences with 95% CIs were calculated for continuous outcomes. We assessed heterogeneity with the Cochran Q test and I 2 statistic (75% indicates substantial heterogeneity) (18). We analyzed the general adult population and older adults separately because sleep measures vary. We used established minimum important differences (MIDs) to capture clinical significance in global outcomes. The MID for the ISI is a 6-point change from baseline (19). Trials that conducted remitter or responder analysis on the basis of established MID offer simplistic interpretation. When trials provided mean scores, we interpreted WMDs in relation to MID by using the method of Johnson and colleagues (20). Weighted mean differences equal to or greater than the MID suggest that many patients gain important benefits, WMDs greater than half the MID but less than the MID suggest that an appreciable number of patients benefit, and WMDs less than half of the MID suggest that patients do not achieve important benefits (20). One investigator assessed strength of evidence for unique comparisons as high, moderate, low, or insufficient (21); assessments were confirmed through consensus. Role of Funding Source This topic was nominated to and funded by the Agency for Healthcare Research and Quality Effective Health Care Program. Key informants representing various perspectives offered suggestions as refined the review scope. Our draft protocol was shared with a technical expert panel that had the opportunity to review the draft report. The American College of Physicians provided support for this manuscript preparation. The authors are solely responsible for its contents. Results We identified 3572 citations; 559 required full-text review after title and abstract screening (Appendix Figure 1). Seventy-six articles (2297) reporting on 70 trials that compared psychological and behavioral interventions with inactive controls or other psychological and behavioral interventions were eligible. We extracted data and analyzed results for 60 trials with low to moderate risk of bias. We grouped trials by intervention type and comparison. Interventions for CBT-I had cognitive and behavioral components; multicomponent behavioral therapy interventions had several behavioral components and no cognitive component; and single-component interventions included sleep restriction, stimulus control, and relaxation. Appendix Figure 1. Summary of evidence search and selection. Intervention type totals do not equal total references because several trials were used in the analysis for 2 different types of interventions. RCT = randomized, controlled trial. Eligible trials (Tables 1 and 2 of the Supplement) enrolled individuals most commonly diagnosed with chronic insomnia according to Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, with mean durations of several years. Participants were predominantly female and white. Trials were conducted in the United States, Canada, the United Kingdom, Sweden, Australia, Norway, Scotland, the Netherlands, and China. Mean age was mid-40s in general adult populations and lower 70s in older adults. Baseline ISI scores were approximately 17, indicating moderate severity, and baseline SOL was more than 45 minutes. Comparisons varied across trials. Inactive controls included information (such as sleep hygiene education) or waitlist; trials infrequently used sham treatments. Adverse effects were rarely reported. Withdrawals were not always reported by group. Evidence on adverse effects and withdrawals was insufficient for all comparisons. We assessed strength of

Pre-deployment daytime and nighttime sleep complaints as predictors of post-deployment PTSD and depression in National Guard troops

There is growing evidence that disturbed sleep is a risk factor for the development of a number of psychiatric diagnoses including depression, PTSD and substance use. The goal of this study was to use a subset of participants from a larger prospective longitudinal study to examine whether preexisting daytime and nighttime sleep disturbances predict depression, PTSD and substance use in US National Guard Soldiers deployed to Iraq. Data on daytime and nighttime sleep complaints, baseline symptoms and personality variables were gathered prior to deployment to Iraq. Measures of psychopathology were collected at three time points post-deployment over the course of two years using both questionnaires and interviews. Multiple regressions were used to predict diagnoses and symptoms of depression, PTSD and substance use. Pre-deployment daytime and nighttime sleep complaints contributed significantly to the prediction of PTSD and depression up to two years after deployment, but not substance use. This study suggests that daytime and nighttime sleep complaints are a risk factor for internalizing disorders including PTSD and depression.

The bidirectional relationship between sleep complaints and pain: Analysis of data from a randomized trial.

OBJECTIVE The goal of this study was to examine the bidirectional relationship of sleep and pain to determine whether changes in sleep complaints over the course of a chronic pain treatment trial predict pain outcomes and vice versa, controlling for changes in depression and anxiety. METHODS Data were analyzed from a 12-month randomized, controlled trial that tested the effectiveness of a collaborative care intervention for veterans with chronic musculoskeletal pain. Participants were 250 veterans from 5 primary care clinics in a Veteran Affairs (VA) medical center. Measures of pain, sleep, and depression/anxiety symptoms were collected at baseline, 3 months, and 12 months. Factor analysis was used to clarify the boundaries of these domains, and structural equation modeling was used to examine whether changes in sleep complaints and depression/anxiety during the trial predicted pain at the end of the trial, controlling for covariates. An alternative model was also tested in which changes in pain predicted sleep complaints. RESULTS Changes in sleep complaints at 3 months significantly predicted changes in pain at 12 months (standardized path coefficient = .29, p < .001). To a lesser extent, changes in pain predicted changes in sleep (standardized path coefficient = .15, p < .05). Changes in depression/anxiety did not significantly predict changes in pain or sleep. There was also evidence of differential relations of specific sleep complaints with pain. CONCLUSIONS This work helps to further disentangle the complex relationship between pain and sleep. This bidirectional relationship may need to be considered to improve pain outcomes.

A randomized controlled pilot study of CBT-I Coach: Feasibility, acceptability, and potential impact of a mobile phone application for patients in cognitive behavioral therapy for insomnia

There has been growing interest in utilizing mobile phone applications (apps) to enhance traditional psychotherapy. Previous research has suggested that apps may facilitate patients’ completion of cognitive behavioral therapy for insomnia (CBT-I) tasks and potentially increase adherence. This randomized clinical trial pilot study (n = 18) sought to examine the feasibility, acceptability, and potential impact on adherence and sleep outcomes related to CBT-I Coach use. All participants were engaged in CBT-I, with one group receiving the app as a supplement and one non-app group. We found that patients consistently used the app as intended, particularly the sleep diary and reminder functions. They reported that it was highly acceptable to use. Importantly, the app did not compromise or undermine benefits of cognitive behavioral therapy for insomnia and patients in both groups had significantly improved sleep outcomes following treatment.

Sleep Disturbances in Posttraumatic Stress Disorder: Updated Review and Implications for Treatment

Sleep disturbances are common in adults with PTSD and range from insomnia and nightmares to periodic leg movements and disruptive nocturnal behaviors. Together these findings suggest profound disturbances in rapid eye movement (REM) and non-REM (NREM) sleep, although there is a lack of consensus regarding a distinct profile of objective sleep disturbances associated with PTSD. Prospective, longitudinal studies have established that sleep disturbances represent a risk factor for the development and course of PTSD, suggesting that sleep is an important neurobiological mechanism in the etiology and maintenance of this disorder. This research highlights the importance of early identification and treatment of sleep disturbances in at-risk and trauma exposed populations. A number of psychological and pharmacological treatments are effective at treating sleep disturbances in PTSD. Additional research is needed to further develop clinical guidelines informing when and how to integrate sleep-specific treatment with PTSD focused clinical care.

Provider Types and Outcomes in Obstructive Sleep Apnea Case Finding and Treatment: A Systematic Review

Obstructive sleep apnea (OSA) is associated with excessive daytime sleepiness, decreased quality of life, myocardial infarction (1, 2), heart failure (3), stroke (4, 5), and cognitive decline (6, 7). Continuous positive airway pressure (CPAP) improves quality of life and symptoms among persons with OSA and excessive daytime sleepiness (8). Although CPAP has not been shown in randomized trials to reduce myocardial infarctions, stroke, or death (912) among patients with OSA, it decreases blood pressure and is associated with reduced risk for motor vehicle accidents (13). As patients and providers gain awareness of OSA, and as prevalence of obesity (a major risk factor for OSA) increases (14), health care systems need to develop strategies to address the increasing demand for sleep services. The traditional evaluation and care model relies on primary care providers to refer patients with suspected OSA to a sleep specialist physician (SSP). The process often includes consultation, in-laboratory diagnostic polysomnography (PSG), CPAP initiation and titration PSG for persons with OSA, and SSP follow-up of treatment adherence and efficacy. This traditional model may be expensive and inefficient. New OSA care models have been proposed and implemented, including home sleep testing for diagnostic purposes (15, 16), followed by treatment with an autotitrating CPAP device (17), which has internal algorithms that adjust pressure to keep the airway open during sleep. These models reduce PSG-associated costs and logistical barriers but typically still include SSP consultation and follow-up. Given recent data indicating a decreasing supply of SSPs (18), other models have been proposed that would reduce reliance on SSPs by including providers not specifically trained as SSPs (nonsleep specialists [NSSs]), such as nurses or primary care physicians, to provide the majority of OSA diagnosis and treatment. Although studies testing some of these new models have been conducted, systematic reviews of studies focusing on who should deliver care are lacking. In this article, we expand on 1 aspect of a larger evidence report conducted for the Department of Veterans Affairs Evidence-based Synthesis Program (protocol registered in PROSPERO [CRD42016036810]) (19) by assessing the comparative effectiveness and harms of new OSA evaluation and treatment models comparing different provider types. Specifically, we evaluated case finding and care by NSSs versus SSPs for patients with suspected or diagnosed OSA. Methods Data Sources and Searches We searched Ovid MEDLINE and CINAHL for articles published from January 2000 through July 2017. Our search was limited to studies that enrolled adults and were published in English. The search for studies of NSSs versus SSPs included the Medical Subject Headings terms sleep apnea syndromes; sleep apnea, obstructive; and health personnel (Appendix Table 1). We obtained additional articles by hand-searching reference lists of relevant studies. Appendix Table 1. Search Strategies Study Selection Abstracts and full-text reports were independently reviewed by 2 trained investigators and research associates. Full-text reports of studies identified as potentially eligible after abstract review were obtained for further review. We included randomized or controlled clinical trials and observational studies that reported results in adults with suspected or diagnosed OSA and were conducted in geographic settings likely to have similar populations and sleep medicine resources (United States, Canada, Europe, Australia, and New Zealand). We adopted a broad definition of care models but required that the study include a comparison of providers with different qualifications (for example, primary care physician vs. SSP). We did not include studies that compared home sleep testing with sleep laboratory testing if all test results were interpreted by SSPs. We excluded studies evaluating the role of dentists or anesthesiologists and studies in which the goal of the intervention was not OSA care. We also excluded studies if they did not report our outcomes of interest or were dissertations, conference abstracts, case reports, narrative reviews, editorials, or commentaries. Reasons for exclusion of a study at full-text review were noted, and disagreements were resolved by a third reviewer. Data Abstraction and Quality Assessment Study characteristics and outcomes were extracted by one investigator and verified by a second. Our outcomes of interest included patient-centered outcomes (mortality, access to care, quality of life, patient satisfaction, adherence, symptom scores, and adverse events) and intermediate or resource-related outcomes (resource use, costs, time to initiation of treatment, and case finding). Two trained investigators rated the risk of bias of individual studies over all outcomes as low, medium, or high. For randomized controlled trials (RCTs), we based risk-of-bias ratings on the following criteria: allocation sequence generation, allocation concealment, blinding, incomplete outcome data, and selective outcome reporting (20). For observational studies, we rated risk of bias using criteria from the Agency for Healthcare Research and Quality Methods Guide (21). We assessed strength of evidence as high, moderate, low, or insufficient, based on the following domains: study limitations (low, moderate, or high, based on the quality or risk of bias of individual studies), consistency (consistent, inconsistent, or unknown or not applicable), directness (direct or indirect), and precision (precise or imprecise) (22). Strength of evidence was rated by one methodologist and verified by a second. Discrepancies were resolved by discussion. Data Synthesis and Analysis We described and qualitatively compared findings of included studies. Analyses were performed in Comprehensive Meta-Analysis, version 3 (Biostat), using random-effects models to calculate mean differences with corresponding 95% CIs. Role of the Funding Source The Department of Veterans Affairs, Veterans Health Administration, Office of Research and Development, Quality Enhancement Research Initiative assigned the topic and reviewed the original protocol but was not involved in data collection, analysis, or manuscript preparation or submission. Results Search results are shown in Figure 1. Our search identified 12 studies that were eligible for inclusion. Figure 1. Evidence search and selection. * An additional 23 studies on autotitrating positive airway pressure vs. continuous positive airway pressure were included in the full evidence report only. Case Finding in Adults With Suspected OSA We identified 4 observational studies on case finding in adults with suspected OSA (2326). Study characteristics are summarized in Appendix Table 2, with additional information provided in Supplement Table 1. Two studies received government funding, 1 received both government and respiratory society funding, and 1 did not report a funding source. Each study took a different approach to case finding. Two were rated as having high risk of bias (23, 25), and 2 were rated as having medium risk of bias (24, 26). Although populations, interventions, comparators, and settings differed across studies, outcomes were similar and results suggested good agreement between SSPs and NSSs (Supplement Tables 2 and 3). Supplement. Supplementary Material Appendix Table 2. Summary of Study Characteristics In a single-site study in the United States, a nurse practitioner experienced in sleep medicine and supervised by an SSP reviewed electronic health records of patients referred for evaluation of OSA (23). The goal was risk stratification and determination of eligibility for an unattended sleep study. If information from the health records was inadequate, a clinic visit with an SSP was scheduled. The health record review (nurse practitioner evaluation) found adequate information for 115 patients, whereas 90 had a clinic visit (SSP evaluation). A community-based study in the United States included 191 patients with at least 4 hours of interpretable recording time from a portable sleep monitoring device (24). The classification of disease severity that was based on the ApneaHypopnea Index value generated by the monitoring device software was compared with the classification that was based on an independent review of the monitoring device output by a board-certified SSP. In the third study, conducted in Spain, 88 patients with suspected OSA were evaluated by 2 providers: a respiratory physician who was trained in sleep medicine and used results from respiratory polygraphy, and an SSP who used results from PSG (26). Both evaluations took place within 1 month. Each of these studies reported on classification of OSA severity (none to severe). Two reported coefficients of 0.75 (24) and 0.71 (26), indicating good agreement. The third study only reported that the final diagnoses of severity did not statistically significantly differ between groups (23). We found low-strength evidence that classification of OSA severity was similar (Table 1). One of the studies also reported agreement on the ApneaHypopnea Index (<10, 10 to 29, or 30 events per hour), with a coefficient of 0.65 (26). Table 1. Strength of Evidence The fourth study, also done in Spain, compared the ability of a primary care pulmonologist (described as having basic knowledge of sleep medicine) and an SSP to identify the most suitable diagnostic test for individual patients (25). Ninety-six patients were included. A coefficient of 0.74 was reported for agreement on the diagnostic test prescribed. No studies assessed patient satisfaction with care, but 1 study evaluated patient-reported clinical improvement (23). The percentage who perceived clinical improvement at 30-day follow-up was similar (P= 0.76) among patients who were evaluated by chart review and those who required a clinic visit. Many of our other outcomes of interest were not r

Resilience and Posttraumatic Stress Disorder Symptoms in National Guard Soldiers Deployed to Iraq: A Prospective Study of Latent Class Trajectories and Their Predictors

This study examined the prospective course of posttraumatic stress disorder (PTSD) symptoms in a cohort of National Guard soldiers (N = 522) deployed to combat operations in Iraq. Participants were assessed 4 times: 1 month before deployment, 2-3 months after returning from deployment, 1 year later, and 2 years postdeployment. Growth mixture modeling revealed 3 distinct trajectories: low-stable symptoms, resilient, 76.4%; new-onset symptoms, 14.2%; and chronic distress, 9.4%. Relative to the resilient class, membership in both the new-onset symptoms and chronic distress trajectory classes was predicted by negative emotionality/neuroticism, odds ratios (ORs) = 1.09, 95% CI [1.02, 1.17], and OR = 1.22, 95% CI [1.09,1.35], respectively; and combat exposure, OR = 1.07, 95% CI [1.02, 1.12], and OR = 1.12, 95% CI [1.02, 1.24], respectively. Membership in the new-onset trajectory class was predicted by predeployment military preparedness, OR = 0.95, 95% CI [0.91, 0.98], perceived threat during deployment, OR = 1.07, 95% CI [1.03, 1.10], and stressful life events following deployment, OR = 1.44, 95% CI [1.05, 1.96]. Prior deployment to Iraq or Afghanistan, OR = 3.85, 95% CI [1.72, 8.69], predeployment depression, OR = 1.27, 95% CI [1.20, 1.36], and predeployment concerns about a deployments impact on civilian/family life, OR = 1.09, 95% CI [1.02, 1.16], distinguished the chronic distress group relative to the resilient group. Identifying predeployment vulnerability and postdeployment contextual factors provides insight for future efforts to bolster resilience, prevent, and treat posttraumatic symptoms.

Personality traits and combat exposure as predictors of psychopathology over time

BACKGROUND Research suggests that personality traits have both direct and indirect effects on the development of psychological symptoms, with indirect effects mediated by stressful or traumatic events. This study models the direct influence of personality traits on residualized changes in internalizing and externalizing symptoms following a stressful and potentially traumatic deployment, as well as the indirect influence of personality on symptom levels mediated by combat exposure. METHOD We utilized structural equation modeling with a longitudinal prospective study of 522 US National Guard soldiers deployed to Iraq. Analyses were based on self-report measures of personality, combat exposure, and internalizing and externalizing symptoms. RESULTS Both pre-deployment Disconstraint and externalizing symptoms predicted combat exposure, which in turn predicted internalizing and externalizing symptoms. There was a significant indirect effect for pre-deployment externalizing symptoms on post-deployment externalizing via combat exposure (p < 0.01). Negative Emotionality and pre-deployment internalizing symptoms directly predicted post-deployment internalizing symptoms, but both were unrelated to combat exposure. No direct effects of personality on residualized changes in externalizing symptoms were found. CONCLUSIONS Baseline symptom dimensions had significant direct and indirect effects on post-deployment symptoms. Controlling for both pre-exposure personality and symptoms, combat experiences remained positively related to both internalizing and externalizing symptoms. Implications for diagnostic classification are discussed.

Feasibility and Preliminary Real-World Promise of a Manualized Group-Based Cognitive Behavioral Therapy for Insomnia Protocol for Veterans

Insomnia is increasingly common among the general population, even more so among veterans. Given the adverse impact of insomnia on both mental and physical health of veterans, it is important to provide effective treatments within the Veterans Health Administration (VHA) system. Group-based cognitive behavioral therapy for insomnia (CBT-I) provides a viable option for treatment. This study reports the feasibility, acceptability, initial effectiveness, and durability of group-based CBT-I in a clinical sample of veterans with comorbid medical and mental health diagnoses; the treatment was provided in a real-world VHA hospital setting using a manualized protocol that was explicitly adapted from the existing 1:1 CBT-I VHA protocol. Overall, we found the treatment to be feasible and acceptable to veterans, as well as effective. We found medium to large effect sizes for both questionnaire and sleep diary measures, including sleep onset latency, awakenings during the night, sleep efficiency, insomnia scores, and dysfunctional beliefs about sleep. Improvements in insomnia symptoms were maintained over 1 month.

Increasing access to and utilization of cognitive behavioral therapy for insomnia (CBT-I): a narrative review

The American College of Physicians (ACP) recently identified cognitive behavioral therapy for insomnia (CBT-I) as the first-line treatment for insomnia. Although CBT-I improves sleep outcomes and reduces the risks associated with reliance on hypnotics, patients are rarely referred to this treatment, especially in primary care where most insomnia treatment is provided. We reviewed the evidence about barriers to CBT-I referrals and efforts to increase the use of CBT-I services. PubMed, PsycINFO, and Embase were searched on January 11, 2018; additional titles were added based on a review of bibliographies and expert opinion and 51 articles were included in the results of this narrative review. Implementation research testing specific interventions to increase routine and sustained use of CBT-I was lacking. Most research focused on pre-implementation work that revealed the complexity of delivering CBT-I in routine healthcare settings due to three distinct categories of barriers. First, system barriers result in limited access to CBT-I and behavioral sleep medicine (BSM) providers. Second, primary care providers are not adequately screening for sleep issues and referring appropriately due to a lack of knowledge, treatment beliefs, and a lack of motivation to assess and treat insomnia. Finally, patient barriers, including a lack of knowledge, treatment beliefs, and limited access, prevent patients from engaging in CBT-I. These findings are organized using a conceptual model to represent the many challenges inherent in providing guideline-concordant insomnia care. We conclude with an agenda for future implementation research to systematically address these challenges.