title: Sequential analyses of daily symptoms in women with fibromyalgia syndrome.
abstract: Fibromyalgia syndrome (FMS) is a chronic musculoskeletal pain disorder characterized by generalized pain, chronic fatigue, sleep disturbance, and a range of other symptoms having no definitive pathology. Consequently, patient evaluations rely on self-report. Ecological Momentary Assessment (EMA) allows frequent real-time collection of self-report measures, removing recall bias and increasing external validity. We studied 81 females with FMS aged 18 to 42 years. Participants carried EMA devices (Palm Pilot M100) programmed to request ratings to 8 FMS symptoms/conditions 3 times daily for 30 days. Completeness of response rates varied across participants and over time. Controlling for immediately previous fatigue (ie, fatigue rating from the immediately preceding rating), unit increases in immediately previous pain and immediately previous emotional distress predicted 9 and 7% increases, respectively, in current fatigue. Controlling for immediately previous emotional distress, a unit increase in immediately previous pain predicted 7% increase in current emotional distress. Controlled for immediately previous pain, a unit increase in immediately previous fatigue predicted a 7% increase in current pain, enhanced by prior diurnal effects; immediately previous emotional distress was not significant. Collectively these results suggest an asymmetry in which emotional stress and pain may increase fatigue, fatigue but not emotional distress may increase pain, and pain but not fatigue may increase emotional distress. Despite small effects and person-to-person variability, these findings suggest that longitudinal data collection by EMA may reveal sequential or causal explanatory patterns with important clinical implications.
  
  
  CONCLUSIONS
  Understanding how multiple symptoms covary in FMS is essential for optimal treatment planning. Our results show small but significant temporal relations among pain, fatigue, and emotional distress. Our results also provide support for the use of EMA as a viable data collection method that allows longitudinal, real-time assessment of multiple FMS symptoms.
authors.affiliation: Pain Research and Management Center, Department of Anesthesiology, University of Utah, 615 Arapeen Drive, Salt Lake City, UT 84108, USA. Akiko.okifuji@hsc.utah.edu
authors.forename: Akiko
authors.initials: A
authors.lastname: Okifuji
authors.forename: David H
authors.initials: DH
authors.lastname: Bradshaw
authors.forename: Gary W
authors.initials: GW
authors.lastname: Donaldson
authors.forename: Dennis C
authors.initials: DC
authors.lastname: Turk
mesh_terms: D000203:Activities of Daily Living; D000293:Adolescent; D000328:Adult; D034201:Computers, Handheld; D003430:Cross-Sectional Studies; D005221:Fatigue / Q000175:diagnosis / Q000209:etiology; D005260:Female; D005356:Fibromyalgia / Q000150:complications* / Q000175:diagnosis; D006801:Humans; D010147:Pain Measurement; D057566:Self Report; D013315:Stress, Psychological / Q000175:diagnosis / Q000209:etiology*; D011795:Surveys and Questionnaires; D055815:Young Adult