Biobehavioral and Environmental Influences on Sleep in Children with Cancer

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DESCRIPTION (provided by applicant): Cancer symptom management is a National Cancer Institute and National Institute of Nursing Research priority for improving quality of life. Few studies have addressed sleep in children with cancer, and sources of sleep disturbances in children with cancer in inpatient settings are not well understood. Studies of acutely ill children indicate that hospital environmental stimuli impair sleep quantity and quality. Other cancer symptoms also can contribute to disturbed sleep. Temperament characteristics can impact children's response to hospital stimuli and impair sleep. Common genetic polymorphisms associated with variations in temperament may influence response to physiologic and environmental stimuli and impact symptom burden. Design: The proposed study will utilize a multiple-case study design to describe biobehavioral and environ- mental influences on sleep-wake patterns among children with cancer receiving inpatient chemotherapy. Specific aims are: 1. Describe nighttime sleep-wake patterns among children with cancer receiving inpatient chemotherapy. 2. Describe nighttime patterns of variation in environmental factors (room sound, light, and temperature levels), and relationships with clinical variables (pain, nausea/vomiting, and medication administration). 3. Describe relationships between nighttime sleep-wake patterns in children with cancer, environmental variables, biobehavioral variables (temperament and behavioral genotype), and fatigue. Methods: Fifteen children with cancer ages 5 to 12 years receiving inpatient chemotherapy will be included. Actigraphs will measure sleep variables. Data loggers will measure environmental variables. Carey Temperament Scales and behavioral genotyping using polymerase chain reaction will measure biobehavioral variables. Fatigue will be measured using the Fatigue Scales for 7- to 12-Year Olds and for Parents. Analysis: (Aim 1) Descriptive time series plots of sleep variables will be generated for individual and group data. Repeated measures ANOVA will evaluate change in sleep. (Aim 2) Graphical plots will be generated for environmental variables and superimposed with clinical variables. Autocorrelation functions will evaluate environmental variable trends. (Aim 3) Individual time-series plots will compare sleep, environment, and fatigue data. Correlation coefficients will evaluate associations between temperament, sleep, and fatigue. Kruskall-Wallis statistics will evaluate differences in sleep and fatigue based on behavioral genotype. Public Health: The study will promote quality of life for children with cancer through identification of factors contributing to disturbed sleep in the hospital and the development of interventions to improve sleep.