Symptom Measurement and Interrelationships During Chemotherapy for Ovarian Cancer

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DESCRIPTION (provided by applicant): Research has highlighted the prevalence and disruptiveness of fatigue and depression during chemotherapy for ovarian cancer. Effective interventions are now needed to reduce fatigue and depression, but development of such interventions is hampered by gaps in current understanding of: 1) the factors that give rise to fatigue and depression, and 2) the best methods of assessing these symptoms. The current proposal extends previous research suggesting that fatigue and depression in ovarian cancer patients may be associated with disruptions in sleep/activity circadian patterns (i.e., disruptions in the rhythmicity of sleep and physical activity behaviors over a 24 hour period). The proposed study will model longitudinal changes and inter-relationships between fatigue, depression, and sleep/activity circadian patterns during the first three cycles of chemotherapy for ovarian cancer. Additionally, it will compare results obtained by two different assessment methods of fatigue and depression: retrospective self-report and real-time assessment. The specific aims are: 1) to examine changes in fatigue, depression, and sleep/activity circadian patterns prior to initiation of chemotherapy and across the first three infusions; 2) to examine competing models of relationships between fatigue, depression, and sleep/activity circadian patterns; 3) to examine the accuracy of retrospective self-reports of fatigue and depression. It is hypothesized that rates of change between symptoms will be correlated and will follow a cyclical pattern, increasing dramatically in the days following each chemotherapy infusion, then declining gradually. Further, it is hypothesized that symptoms follow a cascade pattern, in which disruptions in sleep/activity circadian patterns contribute to fatigue, which in turn contributes to depression. Finally, it is hypothesized that retrospective self-reports of fatigue and depression will be less accurate than real-time assessment, particularly when symptom variability is high. These hypotheses will be examined by collecting real-time and retrospective fatigue and depression data during three, two week periods surrounding each of the first three chemotherapy infusions. Sleep/activity circadian patterns will be recorded during these periods through an actigraph, a device worn on the non-dominant wrist that measures motion. The proposed study will contribute to a better understanding of the course and inter-relationships between fatigue, depression, and sleep/activity circadian patterns, which will serve as the basis for developing a behavioral intervention to reduce symptoms in ovarian cancer patients. In addition, the proposed study will examine the accuracy of retrospective self-reports, a common measure of symptoms. Accurate measurement is essential to assess the efficacy of new interventions, ensuring that patients receive the highest quality care. A better understanding of the relationships between common symptoms during chemotherapy may be helpful in developing more effective interventions to prevent or reduce these symptoms, thereby improving public health. Additionally, accurate measurement is essential to assess the efficacy of new interventions, ensuring that patients receive the highest quality care. The proposed study will model change and relationships over time between fatigue, depression, and sleep/activity circadian patterns, as well as examine the accuracy of a common method of assessing symptoms.