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STUDY OBJECTIVES: This study examines the impact of cognitive behavioral therapy for insomnia (CBT-I) and positive airway pressure (PAP) therapy for comorbid insomnia and sleep apnea on nocturnal sleep and daytime functioning. METHODS: A partial factorial design was used to examine treatment pathways with CBT-I and PAP and the relative benefits of each treatment. One hundred eighteen individuals with comorbid insomnia and sleep apnea were randomized to receive CBT-I followed by PAP, self-monitoring followed by CBT-I concurrent with PAP, or self-monitoring followed by PAP only. Participants were assessed at baseline, PAP titration, and 30 and 90 days after PAP initiation. Outcome measures included sleep diary- and actigraphy-measured sleep, Flinders Fatigue Scale, Epworth Sleepiness Scale, Functional Outcome of Sleep Questionnaire, and cognitive emotional measures. RESULTS: A main effect of time was found on diary-measured sleep parameters (decreased sleep onset latency and wake after sleep onset; increased total sleep time and sleep efficiency) and actigraphy-measured sleep parameters (decreased wake after sleep onset; increased sleep efficiency) and daytime functioning (reduced Epworth Sleepiness Scale, Flinders Fatigue Scale; increased Functional Outcome of Sleep Questionnaire) across all arms (all P < .05). Significant interactions and planned contrast comparisons revealed that CBT-I was superior to PAP and self-monitoring on reducing diary-measured sleep onset latency and wake after sleep onset and increasing sleep efficiency, as well as improving Functional Outcome of Sleep Questionnaire and Flinders Fatigue Scale compared to self-monitoring. CONCLUSIONS: Improvements in sleep and daytime functioning were found with PAP alone or concomitant with CBT-I. However, more rapid effects were observed on self-reported sleep and daytime performance when receiving CBT-I regardless of when it was initiated. Therefore, concomitant treatment appears to be a favorable approach to accelerate treatment outcomes. CLINICAL TRIAL REGISTRATION: Registry: ClinicalTrials.gov; Name: Multidisciplinary Approach to the Treatment of Insomnia and Comorbid Sleep Apnea (MATRICS); URL: https://clinicaltrials.gov/ct2/show/NCT01785303; Identifier: NCT01785303. CITATION: Tu AY, Crawford MR, Dawson SC, et al. A randomized controlled trial of cognitive behavioral therapy for insomnia and PAP for obstructive sleep apnea and comorbid insomnia: effects on nocturnal sleep and daytime performance. J Clin Sleep Med. 2022;18(3):789–800.

Objective To examine the individual and combined effects of daytime sleepiness and insomnia disorder (ID) on measures of cognitive functioning. Design and setting This study was conducted at a medical center using a cross-sectional research design. Participants 35 persons with ID (Mage = 40.6 years; 25 women) and 54 normal sleepers (NS; Mage = 31.5 years; 38 women). Methods and measures Participants underwent two nights of home-based polysomnography (PSG) followed by daytime testing with a four-trial Multiple Sleep Latency Test (MSLT). Before each MSLT nap, they completed a computer-administered battery of reaction time tasks. Measures of response latencies and response accuracy were tabulated and used as dependent measures. The ID and NS groups were each subdivided into “alert” (eg, MSLT mean latency > 8 min) and “sleepy” (eg, MSLT mean latency ≤ 8 min) subgroups to identify hyperaroused persons with ID and allow for their comparisons with the other participant subgroups. Results Multivariate analyses of variance showed a significant main effect for level of daytime sleepiness (F [1, 84] = 8.52, p = 0.0045) on simpler performance tasks and a significant main effect for presence vs. absence of ID (F [1,84] = 6.62, p = 0.012) on complex tasks. A lack of significant participant type x MSLT alertness level interactions in study analyses suggested those ID participants with presumed hyperaousal were not relatively more impaired than the other participant subgroups. Conclusions Daytime performance deficits on simple tasks seem most dependent on individuals’ levels of daytime sleepiness, whereas performance deficits on more complex tasks appears related to the presence of ID. Therefore, it seems best to use complex performance measures both to document cognitive deficits among those with ID and to determine if insomnia treatments reduce such impairments. Trial registration ClinicalTrials.gov Identifier: NCT02290405.

INTRODUCTION: This guideline establishes clinical practice recommendations for the use of behavioral and psychological treatments for chronic insomnia disorder in adults. METHODS: The American Academy of Sleep Medicine (AASM) commissioned a task force of experts in sleep medicine and sleep psychology to develop recommendations and assign strengths based on a systematic review of the literature and an assessment of the evidence using Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology. The task force evaluated a summary of the relevant literature and the quality of evidence, the balance of clinically relevant benefits and harms, patient values and preferences, and resource use considerations that underpin the recommendations. The AASM Board of Directors approved the final recommendations. RECOMMENDATIONS: The following recommendations are intended as a guide for clinicians in choosing a specific behavioral and psychological therapy for the treatment of chronic insomnia disorder in adult patients. Each recommendation statement is assigned a strength (“strong” or “conditional”). A “strong” recommendation (ie, “We recommend…”) is one that clinicians should follow under most circumstances. A “conditional” recommendation is one that requires that the clinician use clinical knowledge and experience, and to strongly consider the patient’s values and preferences to determine the best course of action. 1. We recommend that clinicians use multicomponent cognitive behavioral therapy for insomnia for the treatment of chronic insomnia disorder in adults. (STRONG). 2. We suggest that clinicians use multicomponent brief therapies for insomnia for the treatment of chronic insomnia disorder in adults. (CONDITIONAL). 3. We suggest that clinicians use stimulus control as a single-component therapy for the treatment of chronic insomnia disorder in adults. (CONDITIONAL). 4. We suggest that clinicians use sleep restriction therapy as a single-component therapy for the treatment of chronic insomnia disorder in adults. (CONDITIONAL). 5. We suggest that clinicians use relaxation therapy as a single-component therapy for the treatment of chronic insomnia disorder in adults. (CONDITIONAL). 6. We suggest that clinicians not use sleep hygiene as a single-component therapy for the treatment of chronic insomnia disorder in adults. (CONDITIONAL). CITATION: Edinger JD, Arnedt JT, Bertisch SM, et al. Behavioral and psychological treatments for chronic insomnia disorder in adults: an American Academy of Sleep Medicine clinical practice guideline. J Clin Sleep Med. 2021;17(2):255–262.

INTRODUCTION: The purpose of this systematic review is to provide supporting evidence for a clinical practice guideline on the use of behavioral and psychological treatments for chronic insomnia disorder in adult populations. METHODS: The American Academy of Sleep Medicine commissioned a task force of 9 experts in sleep medicine and sleep psychology. A systematic review was conducted to identify randomized controlled trials that addressed behavioral and psychological interventions for the treatment of chronic insomnia disorder in adults. Statistical analyses were performed to determine if the treatments produced clinically significant improvements in a range of critical and important outcomes. Finally, the Grading of Recommendations Assessment, Development, and Evaluation process was used to evaluate the evidence for making specific treatment recommendations. RESULTS: The literature search identified 1,244 studies; 124 studies met the inclusion criteria, and 89 studies provided data suitable for statistical analyses. Evidence for the following interventions is presented in this review: cognitive-behavioral therapy for insomnia, brief therapies for insomnia, stimulus control, sleep restriction therapy, relaxation training, sleep hygiene, biofeedback, paradoxical intention, intensive sleep retraining, and mindfulness. This review provides a detailed summary of the evidence along with the quality of evidence, the balance of benefits vs harms, patient values and preferences, and resource use considerations. CITATION: Edinger JD, Arnedt JT, Bertisch SM, et al. Behavioral and psychological treatments for chronic insomnia disorder in adults: an American Academy of Sleep Medicine systematic review, meta-analysis, and GRADE assessment. J Clin Sleep Med. 2021;17(2):263–298.

Study Objectives It is common to provide insomnia patients a second treatment when the initial treatment fails, but little is known about optimal treatment sequences for different patient types. This study examined whether pre-treatment characteristics/traits predict optimal treatment sequences for insomnia patients. Methods A community sample of 211 adults (132 women; Mage = 45.6 ± 14.9 years) with insomnia were recruited. Patients were first treated with behavioral therapy (BT) or zolpidem (Zol). Non-remitting BT recipients were randomized to a second treatment with either Zol or cognitive therapy; non-remitting Zol recipients underwent BT or Trazodone as a second treatment. Remission rates were assessed at the end of the first and second 6-week treatments. We then compared the remission rates of dichotomous groups formed on the basis of gender, age, pretreatment scores on SF36 and Multidimensional Fatigue Scale, the presence/absence of psychiatric/medical comorbidities or pain disorders, and mean subjective sleep duration and efficiency within and across treatment sequences. Results Lower remission rates were noted for those: with a pain disorder, poor mental health perceptions, high MFI fatigue scores, and lower sleep times and efficiencies. Patients with a pain disorder responded best to the BT-to-Zol sequence, whereas patients with more mental impairment, severe fatigue, short sleep, and low sleep efficiency responded poorly to treatment starting with BT. Conclusions Pain, fatigue, poor mental health status, and subjective sleep duration and efficiency all affect response to different insomnia treatment sequences. Findings may guide clinicians in matching insomnia treatments to their patients. Clinical Trial Registration ClinicalTrials.gov Identifier: NCT01651442, Protocol version 4, April 20, 2011, registered June 26, 2012, https://clinicaltrials.gov/ct2/show/NCT01651442?rslt=With&type=Intr&cond=Insomnia&cntry=US&state=US%3ACO&city=Denver&age=12&draw=2&rank=1.

Jessica R Lunsford-Avery,1 Jack D Edinger,1,2 Andrew D Krystal1,3 1Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, 27710, USA; 2Department of Medicine, National Jewish Health, Denver, CO, 80206, USA; 3Departments of Psychiatry and Neurology, University of California San Francisco School of Medicine, San Francisco, CA, 94143, USACorrespondence: Jessica R Lunsford-Avery, Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, 2608 Erwin Road Suite 300, Durham, NC, 27710, USA, Tel +1 919-681-0035, Fax +1 919-681-0016, Email jessica.r.avery@duke.eduPurpose: Sleep is vital to cognition, yet underlying mechanisms remain unclear. Although sleep duration and continuity are two well-established contributors, additional factors—including homeostatic sleep drive processes—may also underlie cognition-related sleep restoration. This study investigates the relative contributions of sleep EEG factors to psychomotor functioning in adults with insomnia and healthy controls (HC) to identify the most significant sleep factors supporting psychomotor functioning.Materials and Methods: Adults with insomnia (n = 37) and HC (n = 39) completed 3 nights of polysomnography and a complex psychomotor task (switching attention task; SAT). Univariate correlations identified the most significant predictors (traditional PSG, spectral EEG, initial delta peak, and overnight delta decline) of SAT performance, which were then entered into multivariable linear regressions examining whether predictors remained significant after accounting for shortened/fragmented sleep and whether relationships differed across groups.Results: In addition to greater wake after sleep onset (WASO; r = 0.33), a slower overnight delta decline (r = 0.50) and a lower initial delta peak (r = − 0.38) were the most significant predictors of poorer SAT performance. Both overnight delta decline (F(7, 68) = 12.52, p < 0.001) and initial delta peak (F(7, 68) = 7.85, p = 0.007) remained significant predictors after controlling for demographics, total sleep time, and WASO. Relationships were analogous across subject groups.Conclusion: Findings suggest that, in addition to sleep duration and continuity, processes related to recovery from and dissipation of homeostatic sleep drive may support psychomotor performance and broadly support daytime functioning in individuals with and without insomnia. Future research may examine overnight delta dynamics as transdiagnostic processes supporting cognition-related sleep restoration across a range of clinical populations.Keywords: insomnia, EEG, homeostatic sleep drive, delta power, cognition, reaction time

Objectives To provide recommendations for the selection of comparators for randomized controlled trials of health-related behavioral interventions. Study Design and Setting The National Institutes of Health Office of Behavioral and Social Science Research convened an expert panel to critically review the literature on control or comparison groups for behavioral trials and to develop strategies for improving comparator choices and for resolving controversies and disagreements about comparators. Results The panel developed a Pragmatic Model for Comparator Selection in Health-Related Behavioral Trials. The model indicates that the optimal comparator is the one that best serves the primary purpose of the trial but that the optimal comparator's limitations and barriers to its use must also be taken into account. Conclusion We developed best practice recommendations for the selection of comparators for health-related behavioral trials. Use of the Pragmatic Model for Comparator Selection in Health-Related Behavioral Trials can improve the comparator selection process and help resolve disagreements about comparator choices.

Background: Due to concerns about overlapping symptomatology between medical conditions and depression, the validity of the Beck Depression Inventory (BDI-II) has been assessed in various medical populations. Although Major Depressive Disorder (MDD) and Primary Insomnia (PI) share some daytime symptoms, the BDI-II has not been evaluated for use with insomnia patients. Method Participants (N = 140) were screened for the presence of insomnia using the Duke Structured Clinical Interview for Sleep Disorders (DSISD), and evaluated for diagnosis of MDD using the Structured Clinical Interview for DSM-IV-TR (SCID). Participants’ mean BDI-II item responses were compared across two groups [insomnia with or without MDD) using multivariate analysis of variance (MANOVA), and the accuracy rates of suggested clinical cutoffs for the BDI-II were evaluated using a Receiver Operating Characteristic (ROC) curve analysis. Results The insomnia with depression group had significantly higher scores on several items; however, the groups did not differ on insomnia, fatigue, concentration problems, irritability, libido, increased appetite, and thoughts relating to suicide, self-criticism and punishment items. The ROC curve analysis revealed moderate accuracy for the BDI-II’s identification of depression in those with insomnia. The suggested BDI cutoff of ≥ 17 had 81% sensitivity and 79% specificity. Use of the mild cutoff for depression (≥14) had high sensitivity (91%) but poor specificity (66%). Conclusion Several items on the BDI-II might reflect sleep disturbance symptoms rather than depression per se. The recommended BDI-II cutoffs in this population have some support but a lower cutoff could result in an overclassification of depression in insomnia patients, a documented problem in the clinical literature. Understanding which items discriminate insomnia patients without depression may help address this nosological issue.

Study Objectives To investigate treatment models using cognitive behavioral therapy for insomnia (CBT-I) and positive airway pressure (PAP) for people with obstructive sleep apnea (OSA) and comorbid insomnia. Methods 121 adults with OSA and comorbid insomnia were randomized to receive CBT-I followed by PAP, CBT-I concurrent with PAP, or PAP only. PAP was delivered following standard clinical procedures for in-lab titration and home setup and CBT-I was delivered in four individual sessions. The primary outcome measure was PAP adherence across the first 90 days, with regular PAP use (≥4 h on ≥70% of nights during a 30-day period) serving as the clinical endpoint. The secondary outcome measures were the Pittsburgh Sleep Quality Index (PSQI) and Insomnia Severity Index (ISI) with good sleeper (PSQI 7) serving as the clinical endpoints. Results No significant differences were found between the concomitant treatment arms and PAP only on PAP adherence measures, including the percentage of participants who met the clinical endpoint. Compared to PAP alone, the concomitant treatment arms reported a significantly greater reduction from baseline on the ISI (p = .0009) and had a greater percentage of participants who were good sleepers (p = .044) and remitters (p = .008). No significant differences were found between the sequential and concurrent treatment models on any outcome measure. Conclusions The findings from this study indicate that combining CBT-I with PAP is superior to PAP alone on insomnia outcomes but does not significantly improve adherence to PAP.

Insomnia disorder is common in adults and children. The estimated prevalence ranges from 9% to 15% in the general population, with higher prevalence in certain subpopulations. Hypnotic medications are those that tend to produce sleep and are frequently used to treat insomnia. Commonly used hypnotics in adults include benzodiazepines (BZDs), BZD receptor agonists, antihistamines, antidepressants, melatonin receptor agonists, orexin receptor antagonists, and antipsychotics. However, hypnotic discontinuation is difficult and often unsuccessful. This article discusses strategies to discontinue hypnotics and evidence supporting their use.

Study objectivesTo determine if patients with childhood onsets (CO) of both major depression and insomnia disorder show blunted depression and insomnia treatment responses to concurrent interventions for both disorders compared to those with adult onsets (AO) of both conditions.MethodsThis study was a secondary analysis of data obtained from a multisite randomized clinical trial designed to test the efficacy of combining a psychological/behavior insomnia therapy with antidepressant medication to enhance depression treatment outcomes in patients with comorbid major depression and insomnia. This study included 27 adults with CO of depression and insomnia and 77 adults with AO of both conditions. They underwent a 16-week treatment including: (1) a standardized two-step pharmacotherapy for depression algorithm, consisting of escitalopram, sertraline, and desvenlafaxine in a prescribed sequence; and (2) either cognitive behavioral insomnia therapy (CBT-I) or a quasi-desensitization control (CTRL) therapy. Main outcome measures were the 17-item Hamilton Rating Scale for Depression (HRSD-17) and the Insomnia Severity Index (ISI) completed pre-treatment and every 2 weeks thereafter.ResultsThe AO and CO groups did not differ significantly in regard to their pre-treatment HRSD-17 and ISI scores. Mixed model analyses that adjusted for the number of insomnia treatment sessions attended showed that the AO group achieved significantly lower, subclinical scores on the HRSD-17 and ISI than did the CO group by the time of study exit. Moreover, a significant group by treatment arm interaction suggested that HRSD-17 scores at study exit remained significantly higher in the CO group receiving the CTRL therapy than was the case for the participants in the CO group receiving CBT-I. Greater proportions of the AO group achieved a priori criteria for remission of insomnia (49.3% vs. 29.2%, p = 0.04) and depression (45.5% vs. 29.6%, p = 0.07) than did those in the CO group.ConclusionsPatients with comorbid depression and insomnia who experienced the first onset of both disorders in childhood are less responsive to the treatments offered herein than are those with adult onsets of these comorbid disorders. Further research is needed to identify therapies that enhance the depression and insomnia treatment responses of those with childhood onsets of these two conditions.

Introduction Cognitive behavioral therapy for insomnia (CBT-I) reduces insomnia severity among individuals with insomnia and major depressive disorder (MDD). Understanding the long-term trajectories of insomnia symptom severity has the potential to inform optimization of CBT-I in this population. The objectives of this study were to examine trajectories of change in insomnia severity over a 16-week treatment phase and 2-year naturalistic follow-up, and explore correlates of symptom trajectories. Methods 148 adults (age 46.6±12.6, 73.0% female) with insomnia and MDD were randomly assigned to receive depression pharmacotherapy plus seven sessions of either CBT-I or control insomnia therapy. Depression and insomnia severity were assessed via the Hamilton Depression Rating Scale and Insomnia Severity Index at baseline, bi-weekly during treatment, and every 4 months over follow-up. Sleep effort and beliefs about sleep were assessed at baseline, midtreatment, and posttreatment. Results Latent class linear mixed modeling revealed four insomnia response trajectories: 1) Early Sustained-Responders (16%) showed marked improvement early in treatment, sustained over follow-up; 2) Gradual-Responders (36.7%) achieved substantial symptom reduction by posttreatment, sustained over follow-up; 3) Initial-Responders (25.3%) had substantial symptom reduction during treatment but increased in severity over follow-up; and 4) Partial-Responders (20.7%) achieved minimal improvement over treatment, and maintained moderate symptom severity over follow-up. Chi-square analyses revealed that classes did not differ significantly on sex, ethnicity, employment, relationship status, or treatment received (all ps > .05). One-way ANOVAs with Tukey’s HSD, showed that Partial-Responders consistently endorsed higher depressive symptom severity, sleep effort, and unhelpful beliefs about sleep at baseline, throughout treatment, and follow-up (ps < .05). Early Sustained-Responders endorsed lower sleep effort by midtreatment (ps < .01). Conclusion Results suggest four temporal patterns of treatment response and identified clinical correlates. Future work will be needed to determine if addressing sleep effort early in the course of treatment might enhance sustained insomnia outcome. Support MH078924, MH078961, MH079256

Objective To determine the best of commonly used methods for computing the rate of decline in non-rapid eye movement (NREM) sleep EEG delta power overnight (Delta Decline) in terms of vulnerability to missing data and to evaluate whether this rate is slower in insomnia patients than healthy controls (HC). Methods Fifty-one insomnia patients and 53 HC underwent 6 nights of polysomnography. Four methods for estimating Delta Decline were compared (exponential and linear best-fit functions using NREM (1) episode mean, (2) peak, and (3) total delta power and (4) delta power for all available NREM epochs). The best method was applied to compare groups on linear and exponential rates of Delta Decline. Results Best-fit models using all available NREM epochs were significantly less vulnerable to deviation due to missing data than other methods. Insomnia patients displayed significantly slower linear and exponential Delta Decline than HC. Conclusions Computing Delta Decline using all available NREM epochs was the best of the methods studied for minimizing the effects of missing data. Insomnia patients display slower Delta Decline, which is not explained by differences in total sleep time or wake after sleep onset. Significance This study supports using all available NREM epochs in Delta Decline computation and suggests a slower rate in insomnia.

Sleep is essential for survival and plays a key role in maintaining our physical and mental health. Over the past 40 years, the field of sleep medicine has increasingly focused on the role sleep disturbances have in the etiology of medical and psychological disorders and has proposed various methods of classifying sleep disorders as distinct clinical entities or as conditions occurring comorbid to various disorders. This chapter will provide a brief overview of sleep and sleep staging, the current classification systems used for sleep/wake disorders, a description of common sleep disorders and their relationship to various medical and mental health disorders, and frequently used assessment tools used to aid in diagnosis of sleep/wake disorders. The concluding section considers limitations to the classification systems and provides suggestions for future research.

Introduction Many patients have difficulties achieving hypnotic discontinuation due to anxiety that arises when they knowingly reduce their hypnotic dose or withhold it entirely. This study tested a blinded tapering approach to reduce patients’ anxiety and help them discontinue their hypnotics. Methods The study sample included 78 (M age = 55.2 ± 12.8 yrs.; 65.4% women) users of benzodiazepine and benzodiazepine receptor agonists. Following baseline assessments, enrollees first completed 4 sessions of cognitive behavioral insomnia therapy (CBTI). Subsequently they were randomized to one of three 20-week, double-blinded tapering protocols wherein their medication dosage either remained unchanged (CTRL) or was reduced by 25% or 10% every two weeks. At the end of the 20-week period the study blind was eliminated and those who completed one of the two blinded tapering protocols entered a 3-month follow-up period, whereas CTRL participants were offered an open label taper before completing the follow-up. Results Among those who completed one of the blinded tapering protocols, 92.9% totally discontinued their medication use by the end of the 20-week tapering phase, whereas 77.3% in the CTRL group discontinued hypnotic use by the end of their open label tapering. At follow-up 72.1% of those who completed blinded tapering remained medication free whereas only 52% of those who underwent open-label tapering remained medication free. Comparisons at follow-up showed those who received the open-label taper continued to use hypnotics on average 2.06 nights/week compared to .051 times per week for the blinded taper group (p = .042). The average weekly diazepam equivalent dose of medication used by the open label tapering group was 11.29 mg whereas the weekly dose for the blinded tapering group was 3.22 (p = .069). Conclusion CBTI combined with blinded hypnotic tapering is a promising treatment approach for helping hypnotic users overcome their medication dependence. Support (if any) National Institute of Drug Abuse, Grant # R34 DA042329-01

OBJECTIVES To test a collaborative care model for interfacing sleep specialists with primary care providers to enhance patients' sleep disorders management. METHODS This study used a randomized, parallel group, clinical intervention trial design. A total of 137 adult (29 women) VA outpatients with sleep complaints were enrolled and randomly assigned to (1) an intervention (INT) consisting of a one-time consultation with a sleep specialist who provided diagnostic feedback and treatment recommendations to the patient and the patient's primary care provider; or (2) a control condition consisting of their usual primary care (UPC). Provider-focused outcomes included rates of adherence to recommended diagnostic procedures and sleep-focused interventions. Patient-focused outcomes included measures taken from sleep diaries and actigraphy; Pittsburgh Sleep Quality Index (PSQI) scores; and self-report measures of sleepiness, fatigue, mood, quality of life, and satisfaction with health care. RESULTS The proportions of provider-initiated sleep-focused interventions were significantly higher in the INT group than in the UPC group for polysomnography referrals (49% versus 6%; P < 0.001) and mental health clinic referrals (19% versus 6%; P = 0.02). At the 10-mo follow up, INT recipients showed greater estimated mean reductions in diary total wake time (-17.0 min; 95% confidence interval [CI]: -30.9, -3.1; P = 0.02) and greater increases in sleep efficiency (+3.7%; 95% CI: 0.8, 6.5; P = 0.01) than did UPC participants. A greater proportion of the INT group showed ≥ 1 standard deviation decline on the PSQI from baseline to the 10-mo follow-up (41% versus 21%; P = 0.02). Moreover, 69% of the INT group had normal (≤ 10) Epworth Sleepiness Scale scores at the 10-mo follow-up, whereas only 50% of the UPC group fell below this clinical cutoff (P = 0.03). CONCLUSIONS A one-time sleep consultation significantly increased healthcare providers' attention to sleep problems and resulted in benefits to patients' sleep/wake symptoms. CLINICAL TRIALS REGISTRATION This study is registered with clinicaltrials.gov with identifier # NCT00390572.

Importance Despite evidence of efficacious psychological and pharmacologic therapies for insomnia, there is little information about what first-line treatment should be and how best to proceed when initial treatment fails. Objective To evaluate the comparative efficacy of 4 treatment sequences involving psychological and medication therapies for insomnia and examine the moderating effect of psychiatric disorders on insomnia outcomes. Design, Setting, and Participants In a sequential multiple-assignment randomized trial, patients were assigned to first-stage therapy involving either behavioral therapy (BT; n = 104) or zolpidem (zolpidem; n = 107), and patients who did not remit received a second treatment involving either medication (zolpidem or trazodone) or psychological therapy (BT or cognitive therapy [CT]). The study took place at Institut Universitaire en Sante Mentale de Quebec, Universite Laval, Quebec City, Quebec, Canada, and at National Jewish Health, Denver, Colorado, and enrollment of patients took place from August 2012 through July 2017. Main Outcomes and Measures The primary end points were the treatment response and remission rates, defined by the Insomnia Severity Index total score. Results Patients included 211 adults (132 women; mean [SD] age, 45.6 [14.9] years) with a chronic insomnia disorder, including 74 patients with a comorbid anxiety or mood disorder. First-stage therapy with BT or zolpidem produced equivalent weighted percentages of responders (BT, 45.5%; zolpidem, 49.7%; OR, 1.18; 95% CI, 0.60-2.33) and remitters (BT, 38.03%; zolpidem, 30.3%; OR, 1.41; 95% CI, 0.75-2.65). Second-stage therapy produced significant increases in responders for the 2 conditions, starting with BT (BT to zolpidem, 40.6% to 62.7%; OR, 2.46; 95% CI, 1.14-5.30; BT to CT, 50.1% to 68.2%; OR, 2.09; 95% CI, 1.01-4.35) but no significant change following zolpidem treatment. Significant increase in percentage of remitters was observed in 2 of 4 therapy sequences (BT to zolpidem, 38.1% to 55.9%; OR, 2.06; 95% CI, 1.04-4.11; zolpidem to trazodone, 31.4% to 49.4%; OR, 2.13; 95% CI, 0.91-5.00). Although response/remission rates were lower among patients with psychiatric comorbidity, treatment sequences that involved BT followed by CT or zolpidem followed by trazodone yielded better outcomes for patients with comorbid insomnia. Response and remission rates were well sustained through the 12-month follow-up. Conclusions and Relevance Behavioral therapy and zolpidem medication produced equivalent response and remission rates. Adding a second treatment produced an added value for those whose insomnia failed to remit with initial therapies. Trial Registration ClinicalTrials.gov Identifier:NCT01651442

Introduction Many patients have difficulties achieving hypnotic discontinuation due to anxiety that arises when they knowingly reduce their hypnotic dose or withhold it entirely. This study tested a blinded tapering approach to reduce patients’ anxiety and help them discontinue their hypnotics. Methods The study sample included 78 (M age = 55.2 ± 12.8 yrs.; 65.4% women) users of benzodiazepine and benzodiazepine receptor agonists. Following baseline assessments, enrollees first completed 4 sessions of cognitive behavioral insomnia therapy (CBTI). Subsequently they were randomized to one of three 20-week, double-blinded tapering protocols wherein their medication dosage either remained unchanged (CTRL) or was reduced by 25% or 10% every two weeks. At the end of the 20-week period the study blind was eliminated and those who completed one of the two blinded tapering protocols entered a 3-month follow-up period, whereas CTRL participants were offered an open label taper before completing the follow-up. Results Among those who completed one of the blinded tapering protocols, 92.9% totally discontinued their medication use by the end of the 20-week tapering phase, whereas 77.3% in the CTRL group discontinued hypnotic use by the end of their open label tapering. At follow-up 72.1% of those who completed blinded tapering remained medication free whereas only 52% of those who underwent open-label tapering remained medication free. Comparisons at follow-up showed those who received the open-label taper continued to use hypnotics on average 2-3 nights/week compared to about 1 time every other week for the blinded taper group (p = .05). The average weekly diazepam equivalent dose of medication used by the open label tapering group was about 5 times higher than the average weekly dose used by the blind tapering group (p = .025). Conclusion CBTI combined with blinded hypnotic tapering is a promising treatment approach for helping hypnotic users overcome their medication dependence. Support National Institute of Drug Abuse, Grant # R34 DA042329-01

Introduction Early termination (i.e., dropout) from cognitive-behavioral therapy for insomnia (CBT-I) likely attenuates benefits and may reduce motivation for future treatment. The aim of the current study was to identify characteristics of participants who dropped out of CBT-I in an RCT of combined treatment for depression and insomnia. Methods Participants were 148 adults with comorbid insomnia and depression diagnoses (73% female; M age = 46.6[SD = 12.6]) who were randomly assigned to receive depression pharmacotherapy plus 7 weekly sessions of CBT-I (n = 73) or a credible control therapy for insomnia (n = 75). Receiver operating characteristic curve (ROC) analyses were performed to determine which participant characteristics (i.e., demographics, baseline depression and sleep variables) predicted dropout at session 4 (i.e., minimum dose) and session 7 (i.e., full course of CBT-I). Results Early termination (prior to session 4) rate was 28% and ROC analyses indicated participants aged 36 or less were more likely to drop out than those older than 36 (49% vs. 22%). The model did not identify additional predictors for either of the two age categories. Overall termination (prior to session 7) rate was 45% and ROC analyses indicated participants aged 46 or less were more likely to drop out than those older than 46 (61% vs. 34%). The model further found that among participants aged 46 or less, those with less than 14y education were at greater risk for dropout than those with greater than 14y education (79% vs. 46%). No other demographic, depression, or sleep variables were significant predictors of dropout. Conclusion Age was associated with elevated rate of dropout from CBT-I among individuals with co-occurring depression and insomnia. It appears that the combination of younger age and lower education level is particularly detrimental to treatment engagement. Better understanding of factors that contribute to dropout from CBT-I in this vulnerable group can guide development of retention strategies. Support MH078924, MH078961, MH079256

Introduction This study examines the effects of treatment sequences using cognitive-behavioral therapy for insomnia (CBT-I) and continuous positive airway pressure (CPAP) therapy on daytime functioning in people with comorbid insomnia and sleep apnea (COMISA). Methods 118 participants with COMISA (Age=49.99±13.12; 53.4% female) were randomized to one of the three study arms: Arm A- CBT-I followed by CPAP, Arm B- CBT-I concurrent with CPAP, and Arm C- CPAP only. Participants were assessed at four time points [baseline/ start of phase 1 (A1), CPAP titration/ start of phase 2 (A2), 30 days (A3) and 90 days (A4) after CPAP initiation]. This study examined secondary outcome measures of daytime functioning, including the Functional Outcomes of Sleep Questionnaire (FOSQ), Epworth Sleepiness Scale, and Flinders Fatigue Scale (FFS). Results Linear mixed model analyses showed a main effect of time on improving functional outcomes in all measurements, with all p< 0.001. There were also arm by time interactions on FOSQ [F(6, 105.36)=4.21, p=0.001] and FFS scores [F(6, 106.95)=3.10, p=0.008]. Pairwise comparisons with Bonferroni adjustment showed improved FOSQ scores in Arm A from A1 to A2 (p=0.011) and A2 to A3 (p=0.005), Arm B from A2 to A3 (p< 0.001), and Arm C from A2 to A3 (p=0.006). For FFS scores, improvements were shown in Arm A from A1 to A2 (p=0.003), and Arm B from A2 to A3 (p < 0.001). Conclusion The results show daytime functioning improvements in patients with COMISA following CPAP and CBT-I. In addition, CBT-I appears to facilitate improvement in sleepiness-related functional status and daytime fatigue. The findings suggest that the combination of CBT-I and CPAP may have a beneficial effect on daytime functioning in patients with COMISA. Support This study was supported by the National Institutes of Health (R01HL114529).

OBJECTIVE:Insomnia and major depressive disorders (MDD) often co-occur, and such comorbidity has been associated with poorer outcomes for both conditions. However, individual differences in depressive symptom trajectories during and after treatment are poorly understood in comorbid insomnia and depression. This study explored the heterogeneity in long-term depression change trajectories, and examined their correlates, particularly insomnia-related characteristics. METHOD:Participants were 148 adults (age M ± SD = 46.6 ± 12.6, 73.0% female) with insomnia and MDD who received antidepressant pharmacotherapy, and were randomized to 7-session Cognitive Behavioral Therapy for Insomnia or control conditions over 16 weeks with 2-year follow-ups. Depression and insomnia severity were assessed at baseline, biweekly during treatment, and every 4 months thereafter. Sleep effort and beliefs about sleep were also assessed. RESULTS:Growth mixture modeling revealed three trajectories: (a) Partial-Responders (68.9%) had moderate symptom reduction during early treatment (p value < .001) and maintained mild depression during follow-ups. (b) Initial-Responders (17.6%) had marked symptom reduction during treatment (p values < .001) and low depression severity at posttreatment, but increased severity over follow-up (p value < .001). (c) Optimal-Responders (13.5%) achieved most gains during early treatment (p value < .001), continued to improve (p value < .01) and maintained minimal depression during follow-ups. The classes did not differ significantly on baseline measures or treatment received, but differed on insomnia-related measures after treatment began (p values < .05): Optimal-Responders consistently endorsed the lowest insomnia severity, sleep effort, and unhelpful beliefs about sleep. CONCLUSIONS:Three depression symptom trajectories were observed among patients with comorbid insomnia and MDD. These trajectories were associated with insomnia-related constructs after commencing treatment. Early changes in insomnia characteristics may predict long-term depression outcomes. (PsycINFO Database Record

OBJECTIVE: The construct of subjective sleep quality is poorly understood. One widely used measure of subjective sleep quality is the Pittsburgh Sleep Quality Index (PSQI). The role of psychiatric illness in the association between the PSQI and a prospective, sleep diary-derived sleep quality measure (SDSQ) was investigated plus the degree to which the PSQI may reflect mood states. METHOD: A sample of 211 insomnia patients (International Classification of Sleep Disorders, Second Edition) divided by the presence or absence of a comorbid psychiatric disorder (DSM-IV-TR) and recruited between January 2004 and February 2009, completed the PSQI (primary outcome) and 2 weeks of sleep diary monitoring. First, correlations between PSQI and SDSQ were compared; second, regression analyses were used to investigate whether the association between PSQI and SDSQ depends on diagnostic status; third, the differences in sleep quality between the groups, plus the contribution of anxiety and depression in explaining these differences, were explored. RESULTS: The correlation between PSQI and SDSQ was significant only in the nonpsychiatric group (P < .001). The association between PSQI and SDSQ was moderated by diagnostic status: it was weaker in psychiatric patients (P = .047). Patients with psychiatric comorbidity scored significantly higher on the PSQI than those without (P < .001); this difference disappeared after controlling for anxiety. There were no group differences for the SDSQ. CONCLUSIONS: The present findings suggest that (1) psychiatric patients may be more biased in their retrospective sleep quality ratings, and (2) the PSQI total score may reflect sleep-related distress. The use of a prospective sleep diary measure in patients with a psychiatric disorder is recommended.

The American Academy of Sleep Medicine (AASM) commissioned five Workgroups to develop quality measures to optimize management and care for patients with common sleep disorders including insomnia. Following the AASM process for quality measure development, this document describes measurement methods for two desirable outcomes of therapy, improving sleep quality or satisfaction, and improving daytime function, and for four processes important to achieving these goals. To achieve the outcome of improving sleep quality or satisfaction, pre- and post-treatment assessment of sleep quality or satisfaction and providing an evidence-based treatment are recommended. To realize the outcome of improving daytime functioning, pre- and post-treatment assessment of daytime functioning, provision of an evidence-based treatment, and assessment of treatment-related side effects are recommended. All insomnia measures described in this report were developed by the Insomnia Quality Measures Workgroup and approved by the AASM Quality Measures Task Force and the AASM Board of Directors. The AASM recommends the use of these measures as part of quality improvement programs that will enhance the ability to improve care for patients with insomnia.

In this meta-analysis, we compare the short-term efficacy of prazosin vs. IRT on nightmares, sleep quality, and posttraumatic stress symptoms (PTSS).Reference databases were searched for randomized controlled trials using IRT or prazosin for nightmares, sleep disturbance, and/or PTSS. Effect sizes were calculated by subtracting the mean posttest score in the control group from the mean posttest score in the treatment group, and dividing the result by the pooled standard deviation of both groups. Mixed effects models were performed to evaluate effects of treatment characteristics, as well as sample characteristics (veteran vs. civilian) on treatment efficacy.Four studies used prazosin, 10 used IRT alone or in combination with another psychological treatment, and 1 included a group receiving prazosin and another group receiving IRT. Overall effect sizes of both treatments were of moderate magnitude for nightmare frequency, sleep quality, and PTSS (p0.01). Effect size was not significantly different with type of treatment (psychological vs. pharmacological) on nightmare frequency (p = 0.79), sleep quality (p = 0.65), or PTSS, (p = 0.52). IRT combined with CBT for insomnia showed more improvement in sleep quality compared to prazosin (p = 0.03), IRT alone (p = 0.03), or IRT combined with another psychological intervention, (p0.01).Although IRT interventions and prazosin yield comparable acute effects for the treatment of nightmares, adding CBT for insomnia to IRT seems to enhance treatment outcomes pertaining to sleep quality and PTSS. More randomized clinical trials with long-term follow-up are warranted.A commentary on this article appears in this issue on page 9.

Study Objectives: This study examined empirically derived symptom cluster profiles among patients who present with insomnia using clinical data and polysomnography. Methods: Latent profile analysis was used to identify symptom cluster profiles of 175 individuals (63% female) with insomnia disorder based on total scores on validated self-report instruments of daytime and nighttime symptoms (Insomnia Severity Index, Glasgow Sleep Effort Scale, Fatigue Severity Scale, Beliefs and Attitudes about Sleep, Epworth Sleepiness Scale, Pre-Sleep Arousal Scale), mean values from a 7-day sleep diary (sleep onset latency, wake after sleep onset, and sleep efficiency), and total sleep time derived from an in-laboratory PSG. Results: The best-fitting model had three symptom cluster profiles: "High Subjective Wakefulness" (HSW), "Mild Insomnia" (MI) and "Insomnia-Related Distress" (IRD). The HSW symptom cluster profile (26.3% of the sample) reported high wake after sleep onset, high sleep onset latency, and low sleep efficiency. Despite relatively comparable PSG-derived total sleep time, they reported greater levels of daytime sleepiness. The MI symptom cluster profile (45.1%) reported the least disturbance in the sleep diary and questionnaires and had the highest sleep efficiency. The IRD symptom cluster profile (28.6%) reported the highest mean scores on the insomnia-related distress measures (eg, sleep effort and arousal) and waking correlates (fatigue). Covariates associated with symptom cluster membership were older age for the HSW profile, greater obstructive sleep apnea severity for the MI profile, and, when adjusting for obstructive sleep apnea severity, being overweight/obese for the IRD profile. Conclusions: The heterogeneous nature of insomnia disorder is captured by this data-driven approach to identify symptom cluster profiles. The adaptation of a symptom cluster-based approach could guide tailored patient-centered management of patients presenting with insomnia, and enhance patient care.

Study objective To compare cognitive behavioral therapy for insomnia (CBT-I) + antidepressant medication (AD) against treatments that target solely depression or solely insomnia. Design A blinded, randomized split-plot experimental study. Setting Two urban academic clinical centers. Participants 107 participants (68% female, mean age 42 ± 11) with major depressive disorder and insomnia. Interventions Randomization was to one of three groups: antidepressant (AD; escitalopram) + CBT-I (4 sessions), CBT-I + placebo pill, or AD + 4-session sleep hygiene control (SH). Measurements and results Subjective sleep was assessed via 2 weeks of daily sleep diaries (use of medication was covaried in all analyses); although there were no statistically significant group differences detected, all groups improved from baseline to posttreatment on subjective sleep efficiency (SE) and total wake time (TWT) and the effect sizes were large. Objective sleep was assessed via overnight polysomnographic monitoring at baseline and posttreatment; analyses revealed both CBT groups improved on TWT (p = .03), but the AD + SH group worsened. There was no statistically significant effect for PSG SE (p = .07). There was a between groups medium effect observed for the AD + SH and CBT + placebo group differences on diary TWT and both PSG variables. All groups improved significantly from baseline to posttreatment on the Hamilton Rating Scale for Depression (HAMD-17); the groups did not differ. Conclusions Although all groups self-reported sleeping better after treatment, only the CBT-I groups improved on objective sleep, and AD + SH's sleep worsened. This suggests that we should be treating sleep in those with depression with an effective insomnia treatment and relying on self-report obscures sleep worsening effects. All groups improved on depression, even a group with absolutely no depression-focused treatment component (CBT-I + placebo). The depression effect in CBT-I only group has been reported in other studies, suggesting that we should further investigate the antidepressant properties of CBT-I.

Objective To examine the association between physiological hyperarousal and response accuracy on reaction time tasks among individuals with insomnia. Design and setting This study was conducted at affiliated Veterans Administration (VA) and academic medical centers using a matched-group, cross-sectional research design. Participants Eighty-nine individuals (48 women) with primary insomnia, PI (MAge = 49.8 ± 17.2 y) and 95 individuals (48 women) who were well-screened normal sleepers, NS (MAge = 46.9 ± 17.0 y). Methods and measures Participants underwent 3 nights of polysomnography followed by daytime testing with a four-trial Multiple Sleep Latency Test (MSLT). Before each MSLT nap, they rated their sleepiness and completed computer-administered reaction time tasks. The mean number of correct and error responses made by each participant across testing trials served as dependent measures. The PI and NS groups were each subdivided into alert (e.g., MSLT mean onset latency > 8 min) and sleepy (e.g., MSLT mean onset latency ≤ 8 min) subgroups to allow for testing the main and interaction effects of participant type and level of alertness. Results Alert participants had longer MSLT latencies than sleepy participants (12.7 versus 5.4 min), yet both alert and sleepy individuals with PI reported greater sleepiness than NS. Alert participants also showed lower sleep efficiencies (83.5% versus 86.2%, P = 0.03), suggesting 24-h physiological hyperarousal particularly in the PI group. Individuals with PI had fewer correct responses on performance testing than did NS, whereas a significant group × alertness interaction (P = 0.0013) showed greater error rates among alert individuals with PI (mean = 4.5 ± 3.6 errors per trial) than among alert NS (mean = 2.6 ± 1.9 errors per trial). Conclusions Physiological hyperarousal in insomnia may lead to more apparent daytime alertness yet dispose individuals with insomnia to higher error rates on tasks requiring their attention.

In recent years, polysomnography-based eligibility criteria have been increasingly used to identify candidates for insomnia research, and this has been particularly true of studies evaluating pharmacologic therapy for primary insomnia. However, the sensitivity and specificity of PSG for identifying individuals with insomnia is unknown, and there is no consensus on the criteria sets which should be used for participant selection. In the current study, an archival data set was used to test the sensitivity and specificity of PSG measures for identifying individuals with primary insomnia in both home and lab settings. We then evaluated the sensitivity and specificity of the eligibility criteria employed in a number of recent insomnia trials for identifying primary insomnia sufferers in our sample.Archival data analysis.Study participants' homes and a clinical sleep laboratory.76 with primary insomnia and 78 non-complaining normal sleepers.ROC and cross-tabs analyses were used to evaluate the sensitivity and specificity of PSG-derived total sleep time, latency to persistent sleep, wake after sleep onset, and sleep efficiency for discriminating adults with primary insomnia from normal sleepers. None of the individual criteria accurately discriminated PI from normal sleepers, and none of the criteria sets used in recent trials demonstrated acceptable sensitivity and specificity for identifying primary insomnia.The use of quantitative PSG-based selection criteria in insomnia research may exclude many who meet current diagnostic criteria for an insomnia disorder.

Insomnia is frequently comorbid with psychiatric conditions, mostly depression and anxiety disorders. Because disturbed sleep is a symptom of most major mental disorders, it has been traditionally assumed that effective treatment of the psychiatric condition will resolve the coincident insomnia also. However, insomnia often persists after successful treatment of the comorbid mental disorder, suggesting that insomnia often warrants separate treatment attention. Cognitive-behavioral therapy (CBT) is a well established and efficacious treatment for insomnia. Most evidence supporting the efficacy of CBT comes from studies conducted with patients suffering from primary insomnia, yet over the past 20 years there has been growing support for the use of cognitive-behavioral insomnia intervention for patients with comorbid psychiatric conditions. Overall, promising results have been obtained from these studies, not only with regard to insomnia improvement but also concurrent improvements in comorbid psychiatric conditions. In this article we review recent studies in this area with particular focus on treatment of insomnia in the context of depression, post-traumatic stress disorder, and alcohol dependence.

Although sleep diary and actigraphy data are usually collected daily for 1 or 2 weeks, traditional analytical approaches aggregate these data into mean values. Internight variability of sleep often accompanies insomnia. However, few studies have explored the relevance of this 'construct' in the context of diagnosis, clinical impact, treatment effects and/or whether having 'variable sleep' carries any prognostic significance. We explored these questions by conducting secondary analyses of data from a randomized clinical trial. The sample included primary (PI: n = 40) and comorbid insomnia (CMI: n = 41) sufferers receiving four biweekly sessions of cognitive-behavioural therapy (CBT) or sleep hygiene education. Using the within-subject standard deviations of diary- and actigraphy-derived measures collected for 2-week periods [sleep onset latency (SOL), wake after sleep onset (WASO), total sleep time (TST) and sleep efficiency (SE)], we found that CMI sufferers displayed more variable self-reported SOLs and SEs than PI sufferers. However, higher variability in diary and actigraphy-derived measures was related to poorer sleep quality only within the PI group, as measured by the Pittsburgh Sleep Quality Index (PSQI). Within both groups, the variability of diary-derived measures was reduced after CBT, but the variability of actigraphy-derived measures remained unchanged. Interestingly, the variability of actigraphy measures at baseline was correlated with PSQI scores at 6-month follow-up. Higher SOL variability was associated with worse treatment outcomes within the PI group, whereas higher WASO variability was correlated with better treatment outcomes within the CMI group. Sleep variability differences across insomnia diagnoses, along with their distinctive correlates, suggest that mechanisms underlying the sleep disruption/complaint and treatment response in both patient groups are distinct. Further studies are warranted to support variability as a useful metric in insomnia studies.

Missing data, e.g. patient attrition, are endemic in sleep disorder clinical trials. Common approaches for dealing with this situation include complete-case analysis (CCA) and last observation carried forward (LOCF). Although these methods are simple to implement, they are deeply flawed in that they may introduce bias and underestimate uncertainty, leading to erroneous conclusions. There are alternative principled approaches, however, that are available in statistical software namely mixed-effects models and multiple imputation. In this paper we introduce terminology used to describe different assumptions about missing data. We emphasize that understanding reasons for missingness is a critical step in the analysis process. We describe and implement both linear mixed-effects models and an inclusive multiple imputation strategy for handling missing data in a randomized trial examining sleep outcomes. These principled strategies are compared with "complete-case analysis" and LOCF. These analyses illustrate that methodologies for accommodating missing data can produce different results in both direction and strength of treatment effects. Our goal is for this paper to serve as a guide to sleep disorder clinical trial researchers on how to utilize principled methods for incomplete data in their trial analyses.

Study Objectives: A significant portion of US military personnel are returning from deployment with trauma-related sleep disturbance, and disrupted sleep has been proposed as a mechanism for the development of medical conditions in those with posttraumatic stress disorder (PTSD). Although individuals with PTSD may realize improved sleep with either PTSD treatment or CBT for insomnia, many continue to experience residual sleep difficulties. Newly developed interventions designed to address nightmares are effective to this end, but often do not fully remove all aspects of PTSD-related sleep difficulties when used in isolation. A combined intervention involving both a nightmare-specific intervention and CBT for insomnia may lead to more marked reductions in PTSD-related sleep disturbances.

The type and severity of daytime symptoms reported by insomnia sufferers may vary markedly. Whether distinctive daytime symptom profiles are related to different insomnia diagnoses has not been studied previously. Using profile analysis via multidimensional scaling, we investigated the concurrent validity of ICSD-2 insomnia diagnoses by analysing the relationship of prototypical profiles of daytime symptoms with a subset of ICSD-2 diagnoses, such as insomnia associated to a mental disorder, psychophisiological insomnia, paradoxical insomnia, inadequate sleep hygiene, idiopathic insomnia, obstructive sleep apnea and restless legs syndrome. In a sample of 332 individuals meeting research diagnostic criteria for insomnia (221 women, M(age) =46 years.), the profile analysis identified four prototypical patterns of daytime features. Pearson correlation coefficients indicated that the diagnoses of insomnia associated to a mental disorder and idiopathic insomnia were associated with a daytime profile characterized by mood disturbance and low sleepiness; whereas the diagnoses of psychophysiological insomnia and inadequate sleep hygiene were related to a profile marked by poor sleep hygiene, daytime tension and low fatigue. Furthermore, whereas paradoxical insomnia was consistently associated to lower daytime impairment, insomnia associated to a mental disorder appeared as the most severe daytime form of insomnia. This classification of insomnia sufferers along multiple defining dimensions provides initial validation for two basic insomnia subtypes, with a presumably distinct aetiology: insomnia characterized mainly by an 'internal' component, and a 'learned' insomnia. Research to determine which dimensions are critical for inclusion or differential weighting for defining a general typological system for insomnia sufferers is warranted.

INSOMNIA IS A PREVALENT AND DISTRESSING ISSUE FOR BREAST CANCER PATIENTS.1–6 HOWEVER, THE PROCESS OF INSOMNIA IN THIS POPULATION HAS been largely understudied. Knowledge of this process would not only aid in further understanding insomnia in the context of breast cancer, but it would also foster the development of insomnia interventions for this population so that this prevalent and distressing issue could be better managed. One model commonly used to understand the process of insomnia is a cognitive-behavioral model, which asserts that both dysfunctional sleep related thoughts (e.g., worries about the consequences of insomnia) and behaviors (e.g., napping, extending the opportunity to sleep, staying in bed awake) perpetuate insomnia long after precipitating factors may dissipate.7,8 A large body of research shows support for this model in the context of primary insomnia (i.e., insomnia without any comorbid condition)9,12–13 and demonstrates the efficacy and effectiveness of cognitive-behavioral therapy for insomnia (CBT) for primary insomnia.14 In addition, a few studies have shown support for aspects of this model in the context of insomnia comorbid with breast cancer3,15–19 as well as demonstrated the efficacy of CBT for this population.20–22 Although a cognitive-behavioral model of insomnia shows promise in understanding the process of insomnia in breast cancer patients, cancer-related factors that could potentially contribute to sleep difficulties must be considered. Breast cancer symptoms, such as pain, fatigue, hot flashes, and mood disturbance, are of particular interest as these symptoms have been shown to be associated with poorer sleep in this population.2,3,19,23–27 Therefore, the current study sought to examine the contribution of pain, fatigue, hot flashes, mood disturbance, dysfunctional sleep related thoughts, and sleep inhibitory behaviors to the process of insomnia in breast cancer patients. Process-related questions are challenging to answer with traditional statistical techniques, which typically treat data in a cross-sectional and aggregated fashion. Fortunately, there is a methodological approach, which has been used in other areas (e.g., pain and mood) to examine process-related questions.28,29 This approach is called a daily process approach, which includes repeated prospective measurement of variables that are considered to change in meaningful ways on a daily basis.30 Using sophisticated multilevel modeling techniques, this approach provides the unique opportunity to examine relationships as they occur over time.30–33 For example, one can examine whether higher levels of pain during the day are related to poorer sleep that night and/or if poorer sleep that night is related to higher levels of pain the next day. Therefore, using a daily process approach, the current study addressed three main questions in a population of breast cancer patients with insomnia. First, to examine nighttime associations, what is the day-to-day relationship between sleep and nighttime pain and hot flashes? Second, to examine the antecedents of poorer sleep, what is the day-to-day relationship between daytime symptoms, dysfunctional sleep related thoughts, and sleep inhibitory behaviors and that night's sleep? Third, to examine the consequences of poorer sleep, what is the day-to-day relationship between sleep and the next day's symptoms, dysfunctional sleep related thoughts, and sleep inhibitory behaviors?