Abstract
ISSN 1758-1869 10.2217/PMT.11.15 © 2011 Future Medicine Ltd Pain Manage. (2011) 1(3), 195–197 Fibromyalgia syndrome (FMS) is a chronic musculoskeletal pain disorder characterized by widespread, diffuse pain and hyperalge sic responses. Various pain, functional and mood problems are also associated with FMS [1]. The exact cause or pathophysio logy of FMS continues to elude us. In the absence of specific biomarkers, the evalu ation of FMS patients must rely on self reported symptoms. Patients are typically asked to rate the severity of their symptoms over some period of time (e.g., past week or month). This requires patients to recall retrospectively the occurrence, nature and magnitude of their symptoms, and then to aggregate and average this information to arrive at a summary rating. Heavy reliance on recall, unfortunately, is known to lead to erroneous assessment. For example, the validity of pain recall is quite fragile [2–6], and it is easily influenced by various fac tors including pain severity at the time of recall [4], emotional status [7] and the patient’s beliefs about their conditions [8]. Another concern is related to ecological validity of inclinic/laboratory assessment. Owing to this concern, many have tried to use home assessment methods where symp toms can be assessed in reallife settings. The most common method is to use a paper diary format and to record symptoms on a daily basis. Patients are typically asked to record their symptoms at the end of the day, thereby reducing recall bias to some extent. However, the validity still largely depends upon patients’ willingness to adhere with the required procedure, which is typically quite low [9]. Recent advances in handheld computer technology has enabled clinical research ers to develop an electronically managed, realtime experience sampling method to assess symptoms. Typically, a patient is asked to carry a handheld device, which prompts him/her several times a day. Upon the prompt, the device becomes an electric questionnaire, requesting the person to rate the severity of their symptoms. The method, termed ecological momentary assessment (EMA), makes use of realtime sampling strategies to assess phenomena as they occur in natural settings. The method works particularly well for track ing symptoms associated with FMS and various comorbidities. Ecological momentary assessment also overcomes many of the methodological flaws from which the paper diary format suf fers. The EMA device can be programmed in a way that limits the time frame for a
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