Poor sleep is among the most frequent, yet least addressed, health concern among women during the menopause transition and the prevalence of poor sleep increases with age. In addition, poor sleep has been associated with increased risks for other health problems, adverse effects of prescription sleep medications, and mortality;affecting the quality of life and health of midlife women. Our laboratory has identified that hypnosis, when delivered with five (5), therapist delivered, individualized hypnosis inductions can improve self- reported sleep quality among postmenopausal women presenting with a primary complaint of hot flashes. However, as currently developed, hypnosis is labor intensive and not easily disseminable, thus, limiting its potential public health impact. If a hypnosis program could be developed that is less personnel-intensive and more easily disseminable, it could have a large public health impact on the sleep of midlife women. In addition, the potential impact of any hypnosis program on objectively measured sleep has not yet been examined and there is little data for effect size estimates. Our long range goal is to identify a safe, efficacius, and widely disseminable hypnosis intervention for the treatment of sleep problems during the menopause transition. The purpose of this application is to determine the optimal dose and delivery method for a hypnosis program that shows feasibility, acceptable adherence, and preliminary effects on sleep (primary outcomes) and other secondary outcomes (sleep quality, insomnia symptom severity, daytime sleepiness, menopausal symptoms, and pain). We will enroll 80 menopausal women into a 2X2 factorial design to compare two dosing (three vs. five sessions) and two delivery methods of hypnosis (audio recorded vs. therapist delivered inductions) with assessments at baseline and four, six, and eight weeks post-intervention.
Specific aims are to (1) Determine the feasibility of and adherence to the four hypnosis programs;(2) Determine initial effect sizes for the primary outcome of objectively measured sleep duration, including the percent of women who achieve a clinically meaningful improvement;(3) Determine initial effect sizes for secondary outcomes of sleep quality, insomnia symptom severity, daytime sleepiness, menopausal symptoms, and pain;and (4) Trends in potential covariates including endogenous factors (e.g., age, race/ethnicity, menopausal stage) and exogenous factors (e.g., sleep environment, socioeconomic status). Statistical analysis will determine feasibility (<25% dropout;rating of "good" or better for the program, and <5% adverse events) and adherence (>75% compliance with daily at-home practice). Estimated effect sizes for primary and secondary outcomes will be calculated using standard methods and the optimal programs identified (e.g., a >b>c>d). Trends in potential covariates will be analyzed using Pearson correlations for continuous covariates (e.g., age), and for categorical covariates (e.g., demographic/environment variables) t tests or ANOVAs will be conducted, as appropriate. Findings will provide the requisite data to plan a subsequent R01 application for a multi-site, large-scale, randomized controlled trial.

Public Health Relevance

Poor sleep during the menopausal transition is a significant problem and sleep concerns have been linked to increased morbidity and mortality. The proposed R34 study will identify the optimal dose and delivery method of a hypnosis program to improve sleep and provide the preliminary data needed to develop a larger randomized clinical trial. This research has important public health relevance as safe and effective alternative treatments for poor sleep are needed and an optimal hypnosis intervention will be identified;thereby potentially improving health care for millions of menopausal women.

National Institute of Health (NIH)
National Center for Complementary & Alternative Medicine (NCCAM)
Planning Grant (R34)
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Special Emphasis Panel (ZAT1-PK (28))
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Alekel, D Lee
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Baylor University
Schools of Arts and Sciences
United States
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