A Screening Scale for Chronic Fatigue Syndrome: Reliability and Validity. Leonard A. Jason, Michael T. Ropacki, Nicole B. Santoro, DePaul University

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1 CFS 1 A Screening Scale for Chronic Fatigue Syndrome: Reliability and Validity Leonard A. Jason, Michael T. Ropacki, Nicole B. Santoro, DePaul University Judith A. Richman University of Illinois at Chicago Wendy Heatherly, Renee Taylor, Joseph R. Ferrari, Trina M. Haney-Davis DePaul University Alfred Rademaker, Josée Dupuis Northwestern University Jacqueline Golding University of California-San Francisco Audrius V. Plioplys and Sigita Plioplys Mercy Hospital and Medical Center Jason, L.A., Ropacki, M.T., Santoro, N.B., Richman, J.A., Heatherly, W., Taylor, R.R., Ferrari, J.R., Haney-Davis, T.M., Rademaker, A., Dupuis, J., Golding, J., Plioplys, A.V., & Plioplys, S. (1997). A screening instrument for Chronic Fatigue Syndrome: Reliability and validity. Journal of Chronic Fatigue Syndrome, 3,

2 CFS 2 Abstract Because estimates of the prevalence of Chronic Fatigue Syndrome (CFS) have been quite variable, there is a need for a screening instrument and second stage medical assessment that will produce the most valid estimate of the CFS prevalence. In the present study, four groups of 15 subjects each were recruited: patients diagnosed with 1) CFS, 2) Lupus, 3) Multiple Sclerosis, and 4) a healthy control group. Participants were interviewed twice over a two week period of time with a screening instrument comprising The Fatigue Scale and a newly configured section. The screening scale had excellent test-retest and interrater reliability. This screening scale therefore has utility for CFS community-based epidemiologic research. However, while the scale differentiates patients with CFS from those who are healthy, it is less likely to distinguish CFS from other autoimmune diseases (especially Lupus). Thus, future community-based CFS prevalence studies should encompass both a screening scale and a medical examination to adequately differentiate CFS from other illnesses with overlapping symptomatology. We recommend a two-stage research design with 1) a screening instrument with good sensitivity and 2) medical assessments of CFS positives from stage 1 to deal with the specificity problem. Key Words: Screening scale, Epidemiology, Chronic Fatigue Syndrome

3 CFS 3 A Screening Scale for Chronic Fatigue Syndrome: Reliability and Validity Many articles have made recommendations concerning the assessment instruments needed to diagnosis Chronic Fatigue Syndrome (CFS) (1, 2,3,4,5,6,7,8). The present study involves an effort to explore the problem of sensitivity and specificity in prevalence studies; that is, to discriminate between CFS cases and cases representing other illnesses and to establish a basis of sampling in order to obtain prevalence estimates. A challenge for population-based epidemiologic research involves the means to discriminate between fatigue in general and CFS as a specific diagnosis (9,10,11,12,13). Unfortunately, almost none of the current prevalence studies, which are reviewed below, have validated screening instruments before beginning their research, which suggests there is a need to develop a screening scale with good sensitivity, identifying all those with CFS. Moreover, such a scale should have good specificity, separating those who have other medical or immunological disorders from those who have chronic fatigue. Because the present study will evaluate a screening scale that attempts to differentiate CFS from other medical conditions, other studies that have compared CFS to other medical disorders are reviewed in Table 1. In general, the findings indicate that CFS and MS groups evidence higher levels of fatigue and activity levels than healthy controls (15,21), and that CFS groups have more difficulties in information processing (19) whereas MS groups have overall higher levels of cognitive dysfunction (16). CFS

4 CFS 4 groups have fewer psychiatric diagnoses than depressed groups (17,18). Insert Table 2 here In the present study, an effort will be made to differentiate a group of people with CFS from those with two other medical conditions and a healthy control group. This is an issue of specificity for epidemiologic research, but another important measurement issue involves sensitivity. In other words, is it possible to use a screening scale that identifies those who have CFS? A central problem with most of the CFS epidemiologic studies is that the studies have not validated their screening scales, an issue reviewed below. Research addressing epidemiologic parameters of CFS has often been confined to individual clinical settings, thereby underestimating the "true" prevalence rates (23). Insert Table 2 here Table 2 provides a summary of the CFS prevalence studies conducted to date. Prevalence rates for studies with physician-identified populations vary from 2.0 to 130 per 100,000 (24,7,25). A drawback of these studies is that medical centers are sites where patients are more severely ill or are more highly motivated in seeking help (3). In addition, if physicians do not believe in the validity of CFS and/or patients with CFS do not enter the health care system, then these studies significantly underepresent the prevalence of CFS. In addition, validated initial screening scales were not used to

5 CFS 5 identify those with CFS. Epidemiologic studies directly sampling from health facilities have produced rates of CFS from 75 to 1,800 per 100,000 (26-29). A selection bias within these studies is that patient recruitment focused solely on individuals with access to the health care system. Unfortunately, initial screening scales were not validated except for a study conducted in Great Britain (Wessely, 29,30). This study did use an instrument that had established reliability during their initial stage one screening, and their Fatigue Scale will be used in the present study. This instrument will be defined in the method section; however, the specificity of this instrument has not been determined, that is, the ability to differentiate those who are fatigued due to CFS rather than from other immunological medical conditions. A third group of CFS epidemiologic studies involved random samples (12, 31-33), and rates of CFS varied from 7.4 to 1,088 per 100,000. Unfortunately, the scales used in these studies had not been validated. In summary, CFS is a syndrome of exclusion. Each of the CFS definitions encompass a six month period of severe fatigue and the exclusion of other conditions that could produce these symptoms. The discrepant prevalence rates found across studies might reflect sampling biases and lack of validation of screening scales in the first stage involving identification of those who might have CFS. It is remarkable that almost none of the reviewed studies had validated their initial screening scales. The present study assessed the reliability and validity of a screening instrument that might be used in future studies to estimate the prevalence of CFS. Method

6 CFS 6 Screening Scale A CFS screening questionnaire was developed that is a combination of existing and new measures including: 1) several demographic related items, 2) The Fatigue Scale, and 3) a list of symptoms associated with CFS. Sociodemographic characteristics included information on age, ethnicity, socioeconomic status, marital status, and gender. Socioeconomic status incorporated the revised scoring rules for Hollingshead's (34) scale that were developed and validated by Wasser (35). CFS-relevant fatigue was assessed by The Fatigue Scale (36). Three scores are derived from this scale: a total score of 11 items, a physical fatigue sub-scale (7 items), and a mental fatigue sub-scale (4 items). Each item (e.g., Do you have problems with tiredness?) has a 4-point scale associated with it, with each anchor point being defined (e.g., 1=Not at all, 4=much more than usual). The period of time that the respondents reflect about their fatigue is the last month. Despite its brevity, the scale was found to be reliable and valid, with good face validity (37-38,13). The scale takes about 3 minutes to complete. Scores range from 11 to 44. This scale originally was used in a hospital-based case control study (patients with unexplained chronic postviral fatigue were compared to patients with neuromuscular diseases and those with major depression) (14) and in a study designed to measure response to treatment (39-40). In a sample in Great Britain, David et al. (41) found that this scale produced a continuous distribution of fatigue scores, and the scale was endorsed by Barofsky and Legro (42) in an important review article on measuring fatigue. The Fatigue Scale was further refined by Chalder et al. (36), who began with a larger pool of items, 14. After a factor analysis a Receiver Operating Characteristics analysis defined a cut-off score on the fatigue

7 CFS 7 scale, three items were deleted. Cronbach s alpha was high (range ), and split half reliabilities were also high (.86 and.85). The scale has been used with different populations, including: a general population (13); patients with chronic postviral fatigue, patients with neuromuscular disorders, patients with major depression (14); patients in a general practice (36); patients who presented with a viral illness (37); patients serving a three-partner practice (38, 41); and patients who had the principal complaint of physical fatigue (39,40). In the present study, respondents were asked these fatigue questions (36), in order to assess their general level of fatigue on a standardized and well-accepted instrument. In addition to the Fatigue Scale, interviewees were asked a series of questions that assessed whether or not they had a number of symptoms commonly experienced by people with Chronic Fatigue Syndrome (See Tables 5 & 6). The symptoms needed to be experienced for 6 or more months. Two items assessed functional impairment due to fatigue causes and the frequency of fatigue. One item asked whether any disease or illness accounted for their fatigue. Detailed characteristics and patterns related to fatigue were also asked. These questions were obtained from a number of sources, including the Chronic Fatigue Syndrome Clinical Interview that is being used in an international collaborative study (Andrew Lloyd, personal communication, Jan. 20, 1994). The developed list of symptoms associate with CFS was reviewed by our multidisciplinary research team, which included epidemiologists, a biostatistician, a survey research specialist, physicians, and a psychiatrist. Participants were also asked to provide reasons for their fatigue. The interviews took approximately 15 minutes to

8 CFS 8 complete. The questions were asked by interviewers rather than being completed as a self-administered questionnaire because the epidemiological research that our team has been conducting has validated the use of a telephone interview (43) in epidemiologic research with CFS patients, and this is our current method used in gathering stage one data in our epidemiological research. Interviewer Training Two interviewers with survey research experience were recruited. Training of these individuals took part in three phases. In phase 1, the interviewers were familiarized with the survey questionnaire and procedures. An important part of this orientation was to make sure the interviewers understood the technical terms and medical concepts included in the survey well enough to explain these terms to those interviewed. Phase 2 of the training involved an intensive role playing session in which each interviewer participated in mock interviews, received feedback concerning his or her performance, and then role played other interviews with criticisms and suggestions in mind. The final training phase involved individual supervision of each interviewer during his or her first two interviews with immediate feedback provided. Weekly meetings were held where the interviewers discussed with the first author their progress and any difficulties that occurred. These are standard training procedures that are used in survey research involving telephone interviewing. Participant Recruitment A total of 60 individuals (15 with CFS, 15 Controls, 15 with MS, and 15 with Lupus) were recruited from the greater Chicago area for the present study. With 15 persons per group, there is 80% power to detect an area of.76 or more using the

9 CFS 9 Receiver Operating Characteristic (ROC) statistic, to be described below. Under the assumption that the true sensitivity or specificity is 80%, we are 95% confident that our estimates would be within 20% of the true value. Fifteen of the subjects were diagnosed by a physician in Chicago with experience in diagnosing and treating CFS. Each subject met the Fukuda et al. (8) definition of CFS, using standard procedures recommended by several leading investigators of CFS (5,8). Fifteen healthy control participants had not been diagnosed with CFS or any other illness that could cause significant fatigue. These participants had also been seen by a physician, and no illnesses that could cause fatigue were found (e.g., unresolved cases of hepatitis C virus infection, untreated hypothyroidism)(8). In addition, fifteen participants with a diagnosis of Multiple Sclerosis (MS) were recruited from self-help groups in the Chicago area. Each of these participants met Poser et al.'s (44) criteria for definite MS. Participants with other chronic medical conditions in addition to MS were excluded. Finally, fifteen participants with a diagnosis of Systemic Lupus Erythematosus (SLE) were recruited from self-help groups in the Chicago area. The participants with Lupus had to meet the SLE criteria as defined by the American Rhuematology Association (45). Participants with other chronic medical conditions in addition to SLE were excluded. MS and Lupus were chosen as comparison illnesses in so far as they both encompass substantial levels of fatigue. Procedures All 60 participants were interviewed by a trained interviewer. Two weeks later,

10 CFS participants were re-interviewed by the same interviewer, and 23 participants were re-interviewed by a second trained interviewer. Statistical Analysis Sociodemographic data, symptoms and characteristics of fatigue were compared across the four study groups using Fisher's exact test for dichotomous and multinomial data, and analysis of variance for age. Pairwise comparisons of symptoms and characteristics of fatigue were made between the CFS group and each of the other three groups using Fisher's exact test or the t-test at the.05 level of significance. The fatigue scales were compared across the four groups using analysis of variance followed by Tukey's multiple comparison procedure. Results Demographic characteristics of the four groups of participants are shown in Table 3. There were no significant differences between groups with respect to race (p = 0.74), age (p = 0.15), education (p = 0.59), marital status (p = 0.81) and occupation (p= 0.49). However, there were significantly fewer women in the healthy control group as compared to the other groups (p=0.01), and more people were on disability in the CFS and MS group compared to the healthy control group (p = ). Insert Table 3 here Using the Fukuda et al. (8) definition of CFS, all 15 people in the CFS group met

11 CFS 11 the criteria for CFS, whereas none of the individuals in the healthy, Lupus or MS groups met the screening criteria. In other words, the screening instrument had 100% sensitivity, 100% specificity, 100% agreement, and a kappa of 1.0. Because the subjects in the Lupus and MS groups indicated they had exclusionary medical illnesses, none of them would have met the CFS definition. However, if the subjects had not known they had exclusionary illnesses, then the screening instrument would have identified eleven in the Lupus and four in the MS group as having CFS. Therefore, the screening instrument would have had 100% sensitivity, 67% specificity, 75% agreement, and a kappa of 0.5. The total score on the Fatigue Scale achieved.81 interrater reliability and.95 test-retest reliability. Reliability for the Fatigue Scale was evaluated using Pearson correlation coefficient between the first and second administration of the scale. Reliability for the demographic questions (interrater agreement: 87%-100%, kappa: ; test-retest agreement: 92%-100%, kappa: ) and symptom questions (interrater agreement: 78%-100%, kappa: ; test-retest agreement: 76%-92%, kappa: ) was high. Insert Table 4 here Table 4 lists the means and standard deviations for the physical and mental subscale total, and the overall fatigue scale. We used an analysis of variance to test the differences between the four groups of subjects, and Tukey s procedure at the.05

12 CFS 12 level to test pairwise differences between groups. For both subscales and the total score, there were significant overall differences between the four groups (p<.001). In addition, the CFS, Lupus, and MS groups on all three measures were significantly different from the healthy controls. Finally, across all three measures, the CFS group was significantly different from the MS group, but there were no significant differences between the CFS and the Lupus groups, or the Lupus and the MS groups. A Receiver Operating Characteristic (ROC) curve analysis was used to evaluate the ability of the fatigue scale to discriminate between CFS and non-cfs individuals (46). A ROC curve is produced by plotting the sensitivity versus 1 - specificity for all cutoff points of the total fatigue scale. The area under the curve is an indicator of the discriminatory ability of the scale: a straight line (area = 0.5) means that the scale is doing no better than chance in classifying CFS and non-cfs while a perfect scale would have a ROC curve with an area of 1. The informative area under the Receiver Operating Characteristic curve ranges from 0.5 to 1.0, and not from 0.0 to 1.0 as would the area under a probability distribution curve. With 15 persons per group, there is 80% power to detect an area of.76 or more. The ROC curves for total fatigue score are presented in figure 1. Three curves are included: CFS vs. Lupus, CFS vs. MS and CFS vs. healthy control. The scale was able to discriminate precisely (area under the curve = 1) the CFS and healthy control population. However, the CFS and Lupus population had similar scores on the fatigue scale, making it more difficult to classify the Lupus individuals correctly (area = 0.7). Differentiating the MS from the CFS was easier than for the Lupus subjects (area = 0.84), but could not be done precisely using the scale. ROC curves using the

13 CFS 13 subscales (mental and physical) were constructed and similar results were obtained, with slightly smaller areas obtained from the curves for the mental subscale. If we used a cutoff value of 20 on the total fatigue scale to classify CFS, all CFS and healthy individuals would be classified correctly and 6 MS and 10 Lupus people would be misclassified. This is very similar to results obtained using Fukuda et al. (8) definition of CFS, if the subjects had not known they had exclusionary illnesses. Insert Figure 1 here In Table 5, the frequencies of 22 symptoms are compared among the four study groups. The CFS group differed most from the control group in that all 22 symptoms occurred significantly more frequently in the CFS individuals. In comparing the CFS group to the MS group, 14 symptoms occurred significantly more frequently in the CFS group. The CFS group was most similar to the Lupus group in that only 5 symptoms occurred significantly more frequently in the CFS group. Insert Table 5 here In Table 6, the frequencies of 13 characteristics of fatigue are compared among the groups. Ten of the characteristics occurred more frequently in the CFS group when compared to the control group. The MS and Lupus group also experienced high levels of fatigue in that few differences between the CFS group and the other two patient groups were found.

14 CFS 14 Insert Table 6 here Discussion As mentioned in the introduction, almost all CFS prevalence studies have used screening instruments that have not been validated to select with good sensitivity. There is a need to use of validated screening instruments when conducting CFS epidemiologic research. The present screening scale did not succeed in differentiating CFS from those with other medical disorders, and we believe that it is useful to document this finding. There have been many epidemiologic studies that have only used self-report, non-validated, screening scales, without medical work-ups. Our research suggests that it is a mistake to estimate the prevalence of CFS without medical examinations to rule out other illnesses. Some readers might be concerned that this screening scale would misclassify too many, creating large numbers of false positives. In one study (32), with a random sample, 5% had severe fatigue for 6 months or more (this being one of the items employed on the screening scale used in this article). In that study, when those subjects with 4 or more of the Fukuda et al. (8) symptoms were selected, the target sample was reduced to just 2% of overall sample. Based on these data, only about 2% of a sample interviewed with the screening questionnaire would need to be evaluated with a medical examination. If an investigator was dealing with an extremely large

15 CFS 15 sample, it would be possible to sample from this group of 2%. Using a screening scale, as described in this article, would allow investigators to identify a reasonably small group for a second stage medical work-up. The screening scale used in the present study was demonstrated to be both reliable and valid. The instrument has good sensitivity in that it can identify those who might have CFS in community samples. Unfortunately, it also will identify many with other immunological disorders, but this problem with specificity can be resolved by including medical assessments of CFS positives from stage one. Findings from this study support the usefulness of The Fatigue Scale. Using a version of this scale, McDonald et al. (38), David et al. (41), and Cope et al. (37) found that total scores of 9 or above indicated severe and chronic fatigue. Those who said they had ME (the term used for CFS in Great Britain) had mean scores of in the McDonald et al. study, a score somewhat lower than the score of in the present study; however, two more items, as recommended by Chalder et al. (36), were used in the present study. David et al. found a median score of 4, whereas Cope et al. found a mean score of 4.78 for non- cases of chronic fatigue, numbers close to the mean total score of 4.53 for the healthy control group in the present study. Findings from the present study suggest that a CFS sample can be differentiated from healthy controls. If we had not known that individuals with Lupus and MS had medical exclusionary conditions that could explain their fatigue, using the screening scale and the CDC definition we would have misclassified many of the Lupus and some of the MS individuals. The total fatigue scale performed similarly to the CDC definition in terms of correctly identifying CFS cases and excluding individuals from the other

16 CFS 16 groups. Other symptoms could be used to differentiate the CFS population from healthy controls, those with Lupus, and those with MS, although the individuals with Lupus were most similar to those with CFS. Those with Lupus tended to be differentiated from the CFS group by the following symptoms: sore throat, mild fever and chills, sick for > 24 hours after exercise, new or different headaches, and difficulty concentrating. An important issue for further research involves differentiating between variability within groups (the fluctuating course of symptoms over time) and between groups. Thus it is important to better understand the course of CFS versus the course of MS and Lupus, determining how the illnesses compare at different stages. The healthy control group did differ significantly from the other groups on gender. However, women tend to have a higher incidence of autoimmune diseases. If we had a larger sample, we could have explored gender differences. However, the CFS and healthy control groups were so different on most variables that it is unlikely that gender alone explained these differences. There is a need to readminister the screening scale used in this study to a validation sample so that predictive validity can be established. Those items from the fatigue scale and the symptom scale that are most discriminating could be taken and used as predictors in a much larger sample. Most past epidemiologic studies have relied on referrals from physicians or treatment centers (22). These studies might under-represent disadvantaged minorities who have been shown to manifest higher levels of chronic illness while being less likely to receive adequate care and are thus less likely to be counted in epidemiologic rates derived from treatment sources (47). Existing studies of CFS, whether clinical or

17 CFS 17 epidemiologic, have lacked the ability to depict either the overall magnitude of CFS in the general population or its relative distribution across important sociodemographic groups (22). The findings of Buchwald et al. (27), Jason et al. (33), and Bates et al. (26) suggest that there might be either 190,000; 387,000; or 581,000 people with CFS in the U.S. ( There are 193,650,000 people in the U.S. who are 18 years of age or older; Statistical Abstract of the US, 48). The rates found in a recent study in Great Britain by Wessely et al. (30) are even higher( 3,486,000 people). These rates are significantly higher than those found by Gunn et al., (24)(4,000 to 14,000), Lloyd et al., (7)(77,000), and Price et al. (12) (14,000). Differences in these prevalence estimates might be in part due to the lack of standardized and validated screening instruments when conducting these studies, and different methods of recruiting subjects during the stage 1 (1, 22). There is a need for a study to evaluate rigorously the prevalence of CFS, using a reliable and valid screening instrument. Following identification of fatigued individuals, a medical examination is necessary in order to exclude individuals whose other medical illnesses are causing the fatigue. In other words, what is needed is a two-stage research design with 1) a screening instrument with good sensitivity and 2) medical assessments of CFS positives from stage 1 to deal with the specificity problem. It is also important to employ a random community-based sample in order to establish rates of CFS unbiased by illness and help-seeking behaviors or differential access to the health care system. The prevalence rates from such a study might be higher than current estimates that have been largely based on physician referrals or health

18 maintenance organization coverage. CFS 18

19 CFS 19 References 1. Jason LA, Wagner L, Taylor R, Ropacki MT, Shlaes J, Ferrari J, Slavich, SP, Stenzel C. Chronic Fatigue Syndrome: A new challenge for health care professionals. J Community Psych 1995;23: Armon C, Kurland LT. Chronic Fatigue Syndrome: Issues in the diagnosis and estimation of incidence. Rev Inf Dis 1991;13:S68-S Grufferman S.Issues and problems in the conduct of epidemiologic research on chronic fatigue syndrome. Rev Inf Dis 1991;13:, S60-S Holmes GP, Kaplan JE, Gantz NM, Komaroff AL, Schonberger LB, Strauss SS, Jones JF, Dubois RE, Cunningham-Rudles C, Pahwa S, Tosato G, Zegans LS, Purtilo DT, Brown W, Schooley RT, Brus I. Chronic Fatigue Syndrome: A working case definition. Annals Intern Med 1988;108: Schluederberg A, Straus SE, Peterson P, Blumenthal S, Komaroff AL, Spring SB, Landay A, Buchwald D.Chronic Fatigue Syndrome research: Definition and medical outcome assessment. Annals Intern Med 1992;117: Sharpe MC, Archard LC, Banatvala JE, et al. A report-chronic fatigue syndrome: guidelines for research. J Roy Soc Med 1991;84: Lloyd AR, Hickie I, Boughton CR, Spencer O, Wakefield D. Prevalence of chronic fatigue syndrome in an Australian population. Med J Aust 1990;153: Fukuda K, Straus SE, Hickie I, Sharpe MC, Dobbins JG, Komaroff A. (1994). The Chronic Fatigue Syndrome: A comprehensive approach to its definition and study. Annals Intern Med 121, Kroenke K, Wood D, Mangelsdorff D, Meier N, Powell J. Chronic fatigue in

20 CFS 20 primary care: Prevalence, patient characteristics and outcome. JAMA 1988;260: Manu P, Lane TJ, Matthews DA. Chronic Fatigue Syndromes in clinical practice. Psychother Psychosom 1992;58: Chen M. The epidemiology of self-perceived fatigue among adults. Preven Med 1986;15: Price RK, North CS, Wessely S, Fraser VJ. Estimating the prevalence of Chronic Fatigue Syndrome and associated symptoms in the community. Public Health Reports 1992;107: Pawlikowska T, Chalder T, Wessely S, Wright D, Hirsch S, Wallace P. A population based study of fatigue and psychological distress. British Med J 1994;308: Wessely S, Powell R. Fatigue syndromes: A comparison of chronic 'postviral' fatigue with neuromuscular and affective disorders. J Neurol, Neurosurg, Psychiatry 1989;52: Krupp LB, Mendelson WB, Friedman R. An overview of Chronic Fatigue Syndrome. J Clin Psych 1991;52(10): Krupp LB, Sliwinski M, Masur DM, Friedberg F, Coyle PK. (1994). Cognitive functioning and depression in patients with Chronic Fatigue Syndrome and Multiple Sclerosis. Arch Neurol, 51, Pepper CM, Doscher M, Hirsch M, Guadino E, Coyle PK, Krupp LB. Comparison of the psychiatric and psychological profiles of patients with Chronic Fatigue Syndrome, and Major Depression. Clin Infect Dis 1994; 18(Suppl 1): S86-S87.

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24 CFS 24 identifying people with Chronic Fatigue Syndrome. J Community Psych 1993;21: Poser CM, Paty DW, Scheinberg L, McDonald, W.I., Davis, F.A., Ebers, GC, Johnson KP, Sibley WA, Silberberg DH, Toureteliotte WW.New diagnostic criteria for multiple sclerosis: Guidelines for research protocols. Annals Neur 1983;13: Tan EM, Cohen AS, Fries JF, et al.the 1982 revised criteria for the classification of systemic lupus erythematosus. Arthritis Rheum 1982;25: Hanley JA, Mc Neil BJ. The meaning and use of the area under a Receiver Operating Characteristics (ROC) curve. Radiology 1982;143: Dutton DB. Social class, health and illness. In: Aiken, L Mechanic, D, eds, Applications of social science to clinical medicine, and health policy. New Brunswick, N.J.: Rutgers University Press, 1986: Statistical Abstract of the United States. Washington, DC: Bureau of the Census

25 CFS 25 Author Notes We thank W. McCready, Ph.D.; Joyce Goodlatte, MD; and Harriet Melrose for their help in this study. The authors appreciate the financial support from the CFIDS Association of America, Minnan, Inc., and NIAID (AI36295). Requests for reprints should be sent to Leonard A. Jason, Ph.D., Department of Psychology, DePaul University, 2219 N. Kenmore Ave., Chicago, Il The actual interview used in this study can be obtained by contacting the first author.

26 CFS 26 Figure Caption Figure 1. ROC Curve for CFS Data.

27 CFS 27 Table 1. Comparative Studies Authors Samples Findings Wessely & Powell (14) CFS, neuromuscular fatiguing illness, major depression CFS & Affective groups-- more physical fatigue; Neuromuscular group--less mental fatigue. Krupp et al. (15-18) CFS, multiple sclerosis (MS), systemic lupus erythematosus, Lyme disease, and controls CFS and MS levels of fatigue and psychopathology similar, but depression more frequent in CFS group following onset of illness; MS group greater cognitive impairment; CFS higher fatigue and fewer psychiatric diagnoses than depression. Deluca et al. (19) Johnson et al. (20) CFS, depression, MS, controls CFS deficit information processing speed & efficiency; Depressed group more severe psychopathology. Packer, Sauriol, & Brouwer (21) CFS, MS, controls CFS & MS higher levels of fatigue and reduced activity levels.

28 CFS 28 Komaroff et al. (22) Chronic Fatigue (CF), MS,depression,controls Severe debilitating fatigue in 100%(CF), 80%(MS), 28%(depression). Chronic fatigue differs other 2 groups on these symtpoms: mylagias, postexertional malaise, headaches, infectious type symptoms.

29 CFS 29 Table 2 Prevalence Studies Conducted to Date Physician-identified populations Author Sample size Rates Gunn, Connell & Randall (24) 408 physicians 2.0 to 7.3 per 100, to 15.1 per 100,000 (adjusted) Lloyd, Hickie, Boughton, 104 physicians 39.6 per 100,000 Spencer & Wakefield (7) Ho-Yen & McNamara (25) 195 physicians 130 per 100,000 Health facility population directly surveyed Author Sample size Rates Bates et al. (26) 1,000 patients 300 per 100,000 (CDC criteria) 400 per 100,000 (British criteria) 1,000 per 100,000 (Australian crt.) Buchwald, Umali, Umali, Kith, Pearlman & Komaroff (27) 4,000 patients 75 per 100, per 100,000 (adjusted) Lawrie & Pelosi (28) 1,000 patients 560 per 100,000

30 CFS 30 British criteria Wessely, Chalder, Hirsch, Pawlikowska, Wallance & 2,366 patients 1,800 per 100,000 (Fukuda criteria) Wright (30) Randomly selected populations Author Sample size Rates Price, North, Wessely and Faser (12) 13,538 respondents 7.4 per 100,000 Jason, Wagner, Rosenthal, et al. 3,400 nurses 1,088 per 100,000 (31) Jason, Fitzgibbon, Taylor, Johnson & Salina (32) 1,031 respondents 200 per 100,000 Centers for Disease Control (L. Steele, 33) 17,155 households 76 to 233 per 100,000

31 CFS 31 Table 3: Social-demographic Data on the Four Samples Comparison Groups Fisher's Exact CFS MS Lupus Normal test (n=15) (n=15) (n=15) (n=15) (p value) Gender 0.01 Women Men Race 0.74 White African-American Hispanic Age Education 0.59 H.S. Degree Partial College Standard College Grad./Professional

32 CFS 32 Marital Status 0.81 Married Widowed Divorced/Separated Never Married Occupation 0.49 Labored/Unskilled worker Skilled manual worker /Clerical Semiprofessional/Manager Administrator /Higher Executive

33 CFS 33 Work Status On disability Unemployed Working part-time Working full-time = p value from one-way ANOVA

34 CFS 34 Table 4 Group Means and Standard Deviations on the Fatigue Scales Comparison Groups CFS MS Lupus Control (n=15) (n=15) (n=15) (n=15) Physical Subscale (1.84) (5.46) (5.41) (1.87) Mental Subscale (2.47) (3.18) (3.31) (1.22) Fatigue Score (3.70) (7.89) (8.32) (2.45)

35 CFS 35 Table 5 Number of Reported Symptoms Across the Four Groups Comparison Groups CFS MS Lupus Control (n=15) (n=15) (n=15) (n=15) Symptoms: Sore throat? a, b, c Mild fever or chills? a, b, c Swollen glands neck, underam? a, b Unexplained weakness in muscles? a Aching or stiff muscles? a, b Sick for > 24 hours after excercising? a, b, c Experiencing headaches? a, b New or different headaches than before illness? a, b, c Pain in joints without swelling? a, b Feel rested after nights sleep? a, b Bright lights bother eyes? a Temporary periods of blindness? a Do you get easily irritated? a Is it difficult to think? a Do you feel depressed? a

36 CFS 36 Do you feel confused? a Do you feel forgetful? a Is it difficult to concentrate? a, b, c Concentration interferes w/work, study.? a, b Is it difficult to remember things? a, b Does this difficulty interfere w/work study? a, b Did your fatigue develp over a few hours or days? a, b a: CFS group is statistically different than healthy control (p<0.05) b: CFS group is statistically different than MS (p<0.05) c: CFS group is statistically different than Lupus (p<0.05)

37 CFS 37 Table 6: Group Characteristics of Fatigue Comparison Groups CFS MS Lupus Control (n=15) (n=15) (n=15) (n=15) Do you experience high level of fatigue after normal daily activity? *a h,j Has your fatigue been present > 50% of the time? *a h,i Have you been fatigued or tired > 6 months? *a h Has your fatigue reduced energy levels by 50% > 6 months? *a h Do you have a medical doctor overseeing your fatigue problem? *a h

38 CFS 38 Does disease or illness account for the fatigue? *a h Did your fatigue problem begin suddenly? *a i Does anything else account for the fatigue? *b h How long have you had the fatigue? (M) *c Has fatigue, tiredness, or lack of energy caused: (M) *d h,i,j How frequently do you feel fatigued, tired, or lack energy? (M) *e h,j Would you describe your fatigue problem as: (M) *f

39 CFS 39 Which of the following statements best describes your fatigue during the last month? (M) *g h,j * a = number of respondents who answered yes * b = 3 people in the CFS group mentioned depression; in the MS group, 3 people mentioned depression and 1 person mentioned stress; in the Lupus group, 3 people mentioned stress; and in the Control group, 7 mentioned stress, 1 mentioned overwork, and 1 mentioned back problems * c = in years * d 1 = no problems, 2 = minor problems, 3 = moderate problems, 4 = severe problems * e 1 = not at all, 2 = less than once a week, 3 = 1-4 times a week, 4 = more than 4 times a week * f 1 = getting worse, 2 = staying same, 3 = getting better * g 1 = bedridden, 2 = able to do light housework, 3 = work part-time or complete some family responsibilities, 4 = work full-time or finish all family responsibilities, but no energy for anything else, 5 = able to fulfill work and all family responsibilities h: CFS vs. Healthy Control (p< 0.05) i: CFS vs. MS (p< 0.05) J: CFS vs. Lupus (p< 0.05)