TY - JOUR
T1 - A Rasch Analysis of Assessments of Morning and Evening Fatigue in Oncology Patients Using the Lee Fatigue Scale
AU - Lerdal, Anners
AU - Kottorp, Anders
AU - Gay, Caryl
AU - Aouizerat, Bradley E.
AU - Lee, Kathryn A.
AU - Miaskowski, Christine
N1 - Publisher Copyright:
© 2016 American Academy of Hospice and Palliative Medicine.
PY - 2016/6/1
Y1 - 2016/6/1
N2 - Context To accurately investigate diurnal variations in fatigue, a measure needs to be psychometrically sound and demonstrate stable item function in relationship to time of day. Rasch analysis is a modern psychometric approach that can be used to evaluate these characteristics. Objectives To evaluate, using Rasch analysis, the psychometric properties of the Lee Fatigue Scale (LFS) in a sample of oncology patients. Methods The sample comprised 587 patients (mean age 57.3 ± 11.9 years, 80% women) undergoing chemotherapy for breast, gastrointestinal, gynecological, or lung cancer. Patients completed the 13-item LFS within 30 minutes of awakening (i.e., morning fatigue) and before going to bed (i.e., evening fatigue). Rasch analysis was used to assess validity and reliability. Results In initial analyses of differential item function, eight of the 13 items functioned differently depending on whether the LFS was completed in the morning or in the evening. Subsequent analyses were conducted separately for the morning and evening fatigue assessments. Nine of the morning fatigue items and 10 of the evening fatigue items demonstrated acceptable goodness-of-fit to the Rasch model. Principal components analyses indicated that both morning and evening assessments demonstrated unidimensionality. Person-separation indices indicated that both morning and evening fatigue scales were able to distinguish four distinct strata of fatigue severity. Conclusion Excluding four items from the morning fatigue scale and three items from the evening fatigue scale improved the psychometric properties of the LFS for assessing diurnal variations in fatigue severity in oncology patients.
AB - Context To accurately investigate diurnal variations in fatigue, a measure needs to be psychometrically sound and demonstrate stable item function in relationship to time of day. Rasch analysis is a modern psychometric approach that can be used to evaluate these characteristics. Objectives To evaluate, using Rasch analysis, the psychometric properties of the Lee Fatigue Scale (LFS) in a sample of oncology patients. Methods The sample comprised 587 patients (mean age 57.3 ± 11.9 years, 80% women) undergoing chemotherapy for breast, gastrointestinal, gynecological, or lung cancer. Patients completed the 13-item LFS within 30 minutes of awakening (i.e., morning fatigue) and before going to bed (i.e., evening fatigue). Rasch analysis was used to assess validity and reliability. Results In initial analyses of differential item function, eight of the 13 items functioned differently depending on whether the LFS was completed in the morning or in the evening. Subsequent analyses were conducted separately for the morning and evening fatigue assessments. Nine of the morning fatigue items and 10 of the evening fatigue items demonstrated acceptable goodness-of-fit to the Rasch model. Principal components analyses indicated that both morning and evening assessments demonstrated unidimensionality. Person-separation indices indicated that both morning and evening fatigue scales were able to distinguish four distinct strata of fatigue severity. Conclusion Excluding four items from the morning fatigue scale and three items from the evening fatigue scale improved the psychometric properties of the LFS for assessing diurnal variations in fatigue severity in oncology patients.
KW - Fatigue
KW - Rasch analysis
KW - cancer
KW - diurnal pattern
KW - psychometrics
KW - quality of life
KW - symptoms
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U2 - 10.1016/j.jpainsymman.2015.12.331
DO - 10.1016/j.jpainsymman.2015.12.331
M3 - Article
C2 - 26975624
AN - SCOPUS:84961912077
SN - 0885-3924
VL - 51
SP - 1002
EP - 1012
JO - Journal of Pain and Symptom Management
JF - Journal of Pain and Symptom Management
IS - 6
ER -