Ecological momentary assessment of fatigue in patients receiving intensive cancer therapy.


The ability to accurately assess the incidence, intensity, and timing of cancer-related fatigue is important for clinicians attempting to manage this symptom and for researchers evaluating interventions to reduce or alleviate fatigue. This methodological report describes our experiences with ecological momentary assessment (EMA) and discusses its applicability for capturing real-time, real-world assessments of fatigue in patients receiving intensive cancer therapy. This methodological report is part of a larger study examining fatigue and physical activity before and after hematopoietic stem cell transplantation (HSCT). A prospective, repeated measures design was used to assess changes in fatigue three days before and three days after intensive cancer therapy and HSCT. A convenience sample (n=20 before HSCT, and n=17 after HSCT) was drawn from two Midwestern academic medical centers. Real-time fatigue was measured with a single-item, global, fatigue intensity scale. Multiple fatigue assessments were conducted throughout each study day. Data were collected electronically, facilitating examination of compliance. Subjects responded to fatigue intensity queries 87% of the time before HSCT and 86% after HSCT. Response rates were not unduly influenced by level of fatigue, time of day, or gender. The study findings demonstrate that it is feasible to use computerized EMA to collect self-report fatigue data in acutely ill oncology patients. Most HSCT patients were able to provide real-time fatigue data even when experiencing multiple side effects from the preparatory regimen. EMA is a novel approach that holds substantial promise for investigating fatigue and other cancer symptoms.


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@article{Hacker2007EcologicalMA, title={Ecological momentary assessment of fatigue in patients receiving intensive cancer therapy.}, author={Eileen Danaher Hacker and Carol Ferrans}, journal={Journal of pain and symptom management}, year={2007}, volume={33 3}, pages={267-75} }