Behavioral Treatment of Menopausal Insomnia; Sleep and Daytime Outcomes
Phase: NA
Conditions: Menopause
Sponsor: Christopher Drake

 
 
 
 
 
 
Behavioral Treatment of 
Menopausal Insomnia; Sleep, 
Depression, Daytime (MENO) 
 
NCT01933295 
 
Updated on April 19th 2017 
 
 
 
 
 
 
 
 
 

Insomnia is a key symptom of the menopausal transition with 40-50% of postmenopausal women (> 17 
million) having insomnia. Insomnia associated with menopause has a pattern of sleep disturbance 
predominantly characterized by sleep maintenance difficulties including frequent awakenings and 
arousals, reduced sleep efficiency, and overall fragmented sleep. It has recently been demonstrated that 
this pattern of sleep disturbance, difficulty maintaining sleep, increases throughout the progression of 
menopause. We have recently found sleep maintenance problems in menopause are associated with 
reduced work performance, increased healthcare utilization, and impaired quality of life.  
Cognitive-behavioral therapy for insomnia (CBT-I) yields equivalent short-term efficacy and superior 
long-term durability to pharmacological treatment of insomnia. However, the efficacy of cognitive 
behavioral therapy for insomnia comorbid with menopause, one of the primary focuses of the present 
proposal, has not been tested. Traditional CBT-I has disadvantages however, including the need for a 
trained therapist and significant time commitment on the part of the patient. Therefore, widespread 
availability of multicomponent CBT-I is limited by the relatively low number of CBT sleep specialists, 
complexity of therapy, and patient burden. Thus, another aim of this project is to test the acute and 
long-term efficacy of a single component behavioral therapy for menopausal-related insomnia. Given 
the significant daytime impairment present in insomnia comorbid with menopause including depression, 
quality of life, and fatigue, a final aim of this proposal is to determine the efficacy of CBT-I on these 
measures in women with menopausal-related insomnia. 
Each patient who meets the criteria and opts for CBT-I as part of their standard clinical treatment for 
insomnia will be asked if they wish to participate in the study. Consented subjects will then receive CBT-I 
treatment for 4 weeks (2 face-to-face sessions and 2 phone contacts). The patients will maintain a sleep 
diary to measure sleep efficiency (number of hours asleep over number of hours in bed) and sleep 
latency (amount of time taken to fall asleep). This diary will be collected at each visit. The patients will 
fill out the following pre and post standardized surveys before and after the start of treatment: ISI, BAI, 
ESS, FSI, BDI-II, and SF-36 QoL, PSAS, DBAS. These surveys will measure secondary factors, such as, 
severity of insomnia, sleepiness, hyperarousal, fatigue, anxiety, depression, and quality of life (all 
included in the appendix). Our primary aim is to maximize and/or improve sleep efficieny in patients 
(number of hours asleep over number of hours in bed) and to shorten sleep latency (amount of taken to 
fall asleep). Other secondary measures will be taken regarding aspects other than sleep in patients. 
These will be recorded through the surveys mentioned above and will measure improvement in severity 
of insomnia, sleepiness, depression, anxiety, dysfunctional beliefs and quality of life. 
Each variable of interest (sleep diary measures and questionnaire assessments) will be compared 
between pre and post-treatment (the primary evaluation time points) using standard analysis of 
covariance, with the baseline demographics as covariates.  Then the data on sleep efficiency, sleep 
latency, will be analyzed across all of the weekly time points using repeated measures analysis of 
covariance, with covariates included for the baseline levels of those variables along with age, BMI, and 
time since cancer development.  The repeated measures modeling will primarily evaluate the main time 
effect.  The repeated measures sphericity will be examined and an appropriate variance/covariance 
modeling structure will be used.  If the analysis of variance assumption of distributional normality is 
violated, then an appropriate data transformation will be utilized.