Hostname: page-component-848d4c4894-ttngx Total loading time: 0 Render date: 2024-06-12T17:45:28.663Z Has data issue: false hasContentIssue false

Should symptoms be scaled for intensity, frequency, or both?

Published online by Cambridge University Press:  29 April 2003

Center on Outcomes, Research and Education (CORE), Evanston Northwestern Healthcare, Evanston, Illinois Feinberg School of Medicine, Northwestern University, Chicago, Illinois
Center on Outcomes, Research and Education (CORE), Evanston Northwestern Healthcare, Evanston, Illinois Feinberg School of Medicine, Northwestern University, Chicago, Illinois
Feinberg School of Medicine, Northwestern University, Chicago, Illinois
Feinberg School of Medicine, Northwestern University, Chicago, Illinois Rehabilitation Institute of Chicago, Chicago, Illinois
Feinberg School of Medicine, Northwestern University, Chicago, Illinois
Feinberg School of Medicine, Northwestern University, Chicago, Illinois Rehabilitation Institute of Chicago, Chicago, Illinois


Objective: This study evaluated the comparability of two 5-point symptom self-report rating scales: Intensity (from “not at all” to “very much”) and Frequency (from “none of the time” to “all of the time”). Questions from the Functional Assessment of Chronic Illness Therapy (FACIT)-Fatigue 13-item scale was examined.

Methods: Data from 161 patients (60 cancer, 51 stroke, 50 HIV) were calibrated separately to fit an item response theory-based rating scale model (RSM). The RSM specifies intersection parameters (step thresholds) between two adjacent response categories and the item location parameter that reflects the probability that a problem will be endorsed. Along with patient fatigue scores (“measures”), the spread of the step thresholds and between-threshold ranges were examined. The item locations were also examined for differential item functioning.

Results: There was no mean raw score difference between intensity and frequency rating scales (37.2 vs. 36.4, p = n.s.). The high correlation (r = .86, p < .001) between the intensity versus frequency scores indicated their essential equivalence. However, frequency step thresholds covered more of the fatigue measurement continuum and were more equidistant, and therefore reduced floor and ceiling effects.

Significance of results: These two scaling methods produce essentially equivalent fatigue estimates; it is difficult to justify assessing both. The frequency response scaling may be preferable in that it provides fuller coverage of the fatigue continuum, including slightly better differentiation of people with relatively little fatigue, and a small group of the most fatigued patients. Intensity response scaling offers slightly more precision among the patients with significant fatigue.

Research Article
© 2003 Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)



Andrich, D. (1978a). Application of a psychometric rating model to ordered categories which are scored with successive integers. Applied Psychological Measurement, 2, 581594.Google Scholar
Andrich, D. (1978b). Scaling attitude items constructed and scored in the Likert tradition. Educational and Psychological Measurement, 38, 665680.Google Scholar
Andrich, D. (1978c). A rating formulation for ordered response categories. Psychometrika, 43, 561573.Google Scholar
Cella, D. (1997). The Functional Assessment of Cancer Therapy-Anemia (FACT-An) Scale: A new tool for the assessment of outcomes in cancer anemia and fatigue. Seminars in Hematology, 34(Suppl.), 1319.Google Scholar
Cella, D. (1998). Factors influencing quality of life in cancer patients: Anemia and fatigue. Seminars in Oncology, 25, 4346.Google Scholar
Cella, D., Davis, K., Breitbart, W., & Kurt, G. (2001). Cancer-related fatigue: Prevalence of proposed diagnostic criteria in a United States sample of cancer survivors. Journal of Clinical Oncology, 19, 33853391.Google Scholar
Cella, D., Lai, J.-S., Chang, C.-H., Peterman, A., & Slavin, M. (2002). Fatigue in cancer patients compared to that of the general United States population. Cancer, 94(2), 528538.Google Scholar
Coons, S.J. & Kaplan, R.M. (1992). Assessing health-related quality of life: Application to drug therapy. Clinical Therapeutics, 14, 850858.Google Scholar
Curt, G.A., Breitbart, W., Cella, D., Groopman, J.E., Horning, S.J., Itri, L.M., Johnson, D.H., Miaskowski, C., Scherr, S.L., Portenoy, R.K., & Vogelzang, N.J. (2000). Impact of cancer-related fatigue on the lives of patients: New findings from the Fatigue Coalition. Oncologist, 5(5), 353360.CrossRefGoogle Scholar
Hann, D.M., Jacobsen, P.B., Azzarello, L.M., Martin, S.C., Curran, S.L., Fields, K.K., Greenberg, H., & Lyman, G. (1998). Measurement of fatigue in cancer patients: Development and validation of the Fatigue Symptom Inventory. Quality of Life Research, 7, 301310.Google Scholar
Hays, D., Sherbourne, C.D., & Mazel, R.M. (1995). User's manual for the Medical Outcomes Study (MOS) core measures of health-related quality of life. Santa Monica, CA: RAND.
Hays, R.D., Bell, R.M., Damush, T., Hill, L., DiMatteo, M.R., & Marshall, G.N. (1994). Do response options influence alcohol use self-reports by college students? International Journal of Addictions, 29(14), 19091920.Google Scholar
Kong, S.X. & Gandhi, S.K. (1997). Methodological assessments of quality of life measures in clinical trials. Annals of Pharmacotherapy, 31, 830836.Google Scholar
Krupp, L.B., LaRocca, N.G., Muir-Nash, J., & Steinberg, A.D. (1989). The fatigue severity scale. Archives of Neurology, 46, 11211123.Google Scholar
Linacre, J.M. & Wright, B.D. (2001). WINSTEPS Rasch model computer program. Chicago: MESA Press.
MacKeigan, L.D. & Pathak, D.S. (1992). Overview of health-related quality of life measures. American Journal of Hospital Pharmacy, 49, 22362245.Google Scholar
McNair, D.M., Lorr, M., & Droppleman, L.F. (1971). EdITS manual for the profile of mood states. San Diego, CA: Educational and Industrial Testing Service.
Mendoza, T.R., Wang, X.S., Cleeland, C.S., Morrissey, M., Johnson, B.A., Wendt, J.K., & Huber, S.L. (1999). The rapid assessment of fatigue severity in cancer patients: Use of the Brief Fatigue Inventory. Cancer, 85, 11861196.Google Scholar
Piper, B.F., Dibble, S.L., Dodd, M.J., Weiss, M.C., Slaughter, R.E., & Paul, S.M. (1998). The revised Piper Fatigue Scale: Psychometric evaluation in women with breast cancer. Oncology Nursing Forum, 25, 677684.Google Scholar
Schwartz, A.L. (1998). The Schwartz Cancer Fatigue Scale: Testing reliability and validity. Oncology Nursing Forum, 25, 711717.Google Scholar
Schwartz, A. & Meek, P. (1999). Additional construct validity of the Schwartz Cancer Fatigue Scale. Journal of Nursing Measurement, 7, 3545.Google Scholar
Smets, E.M., Garssen, B., Bonke, B., & de Haes, J.C. (1995). The Multidimensional Fatigue Inventory (MFI): Psychometric qualities of an instrument to assess fatigue. Journal of Psychosomatic Research, 39, 315325.CrossRefGoogle Scholar
Stein, K.D., Martin, S.C., Hann, D.M., & Jacobsen, P.B. (1998). A multidimensional measure of fatigue for use with cancer patients. Cancer Practice, 6, 143152.CrossRefGoogle Scholar
Stewart, A.L. & Ware, J.E., Jr. (1992). Measuring Functioning and Well-being: The Medical Outcomes Study Approach. Durham, NC: Duke University Press.
Stone, P., Hardy, J., Huddart, R., A'Hern, R., & Richards, M. (2000). Fatigue in patients with prostate cancer receiving hormone therapy. European Journal of Cancer, 36(9), 11341141.Google Scholar
Vogelzang, N.J., Breitbart, W., Cella, D., Curt, G.A., Groopman, J.E., Horning, S.J., Itri, L.M., Johnson, D.H., Scherr, S.L., & Portenoy, R.K. (1997). Patient, caregiver, and oncologist perceptions of cancer-related fatigue: Results of a tripart assessment survey; The Fatigue Coalition. Seminars in Hematology, 34, 412.Google Scholar
Wright, B.D. & Stone, M.H. (1979). Best Test Design. Chicago: MESA Press.
Yellen, S.B., Cella, D., Webster, K., Blendowski, C., & Kaplan, E. (1997). Measuring fatigue and other anemia-related symptoms with the Functional Assessment of Cancer Therapy (FACT) measurement system. Journal of Pain and Symptom Management, 13, 6374.CrossRefGoogle Scholar