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Measurement of Fatigue in HIV-Positive Adults: Reliability and Validity of the Global Fatigue Index
JANAC Vol. 12, No. 3, May/June 2001 Bormann et al. / Measurement of Fatigue in HIV/AIDS
Measurement of Fatigue in HIV-Positive Adults: Reliability and Validity of the Global Fatigue Index Jill Bormann, PhD, RN, CS Martha Shively, PhD, RN Tom L. Smith, PhD Allen L. Gifford, MD Fatigue is among the most common and distressing symptoms in patients with HIV/AIDS. Little is known about the clinical assessment of fatigue, especially in patients using highly active antiretroviral regimens. The purpose of this study was to evaluate the psychometric properties of the Global Fatigue Index (GFI) in a community-based sample of 209 patients with HIV/AIDS. The GFI is a measure that quantifies five dimensions of fatigue from the Multidimensional Assessment of Fatigue instrument into one score. To assess construct validity, the study included measures of depression, perceived stress, activities of daily living (ADLs), health behaviors, and clinical markers. Cronbach’s alpha was calculated for internal consistency reliability, and factor analysis and bivariate correlations were conducted. The GFI was found to be easily self-administered, reliable, and a valid measure of overall fatigue burden in an HIV population. This instrument may be used by clinicians and researchers for assessing fatigue. Key words: HIV/AIDS, fatigue, measurement
F
atigue has been cited as among the most bothersome and frequently reported symptoms of HIV infection (Bormann, Gifford, Shively, Timberlake, Page, & Seefried, 1999; Breitbart, McDonald, Rosenfeld, Monkman, & Passik, 1998; Cunningham et al., 1998; Darko, McCutchan, Kripke, Gillin & Golshan, 1992;
O’Dell, Meighen, & Riggs, l996; Perdices, Dunbar, Grunseit, Hall, & Cooper, 1992; Shively, Gifford, Bormann, & Smith, 1998). Several studies have indicated that fatigue interferes with quality of life (Breitbart et al., 1998; Cleary et al., 1993; Cunningham et al., 1998; Wilson & Cleary, 1997). Fatigue often decreases activities of daily living (ADLs) and limits physical functioning (Wilson & Cleary, l997). Fatigue, functional status, and severity of symptoms have predicted overall perceived health status in persons with AIDS (Cleary et al., 1993) and fatigue has been associated with significant physical and psychological morbidity (Breibart et al., 1998). These quantitative findings have been further supported by interviews of 21 HIV-positive patients about painful losses, including the loss of energy, time, and independence.
Jill Bormann, PhD, RN, CS, was supported by a VA postdoctoral fellowship through the VA Office of Academic Affiliations. Martha Shively, PhD, RN, is a professor, San Diego State University School of Nursing and Associate Chief, Nursing Service for Research at the VA San Diego Healthcare System. Tom L. Smith, PhD, is a principal statistician, Department of Psychology, School of Medicine, University of California, San Diego. Allen L. Gifford, MD, is an assistant professor of medicine at the University of California, San Diego, and a principal investigator at the VA San Diego Healthcare System.
JOURNAL OF THE ASSOCIATION OF NURSES IN AIDS CARE, Vol. 12, No. 3, May/June 2001, 75-83 Copyright © 2001 Association of Nurses in AIDS Care
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Loss of energy was described as an overwhelming presence in their lives. Frequently, this loss of energy had a direct impact on their abilities to be involved with people and with daily events. This limited their social lives, and the limitation was identified as being painful. (Laschinger & Fothergill-Bourbonnais, 1999, p. 62) Fatigue is a complex construct consisting of cognitive, emotional, and physical components. Aaronson et al. (1999) categorized fatigue according to five salient characteristics: (a) subjective quantification of fatigue, (b) subjective distress due to fatigue, (c) subjective assessment of the impact of fatigue on activities of daily living, (d) correlates of fatigue, and (e) key biological parameters. In a literature review, Barroso (1999) concluded that measuring fatigue in HIV/AIDS patients has been problematic and recommended that an instrument needs to “capture the intensity, circumstances, and consequences of fatigue” (p. 46). A variety of methods have been used to measure fatigue in HIV-infected patients ranging from hermeneutic phenomenology using semistructured qualitative interviews (Rose, Pugh, Lears, & Gordon, 1998) to visual analog scales (O’Dell et al., 1996; Wagner, Rabkin, & Rabkin, 1997; Walker, McGown, Jantos, & Anson, 1997). Approaches have included the AIDS symptom checklist and the Memorial Symptom Assessment Scale (Breitbart et al., 1998), rating scales (Cunningham et al., 1988), the fatigue subscale from the Profile of Mood States (POMS) (McNair, Lorr, & Droppleman, 1981; Gifford, Laurent, Gonzales, Chesney, & Lorig, 1998) and single-item questions. Often, fatigue measures have consisted of a few items that targeted only one or two aspects of fatigue or simply assessed the presence or absence of fatigue. Instruments developed to assess fatigue in other populations have been used in HIV research. These include the Chalder Fatigue Scale (CFS) developed in general practice medical patients (Chalder et al., 1993); the Fatigue Assessment Inventory developed in patients with multiple sclerosis (Cohen & Fisher, 1989); a version of the Piper Fatigue Scale developed in cancer patients (Piper, Lindsey, Dodd, Ferketich, Paul & Weller, 1989) and modified by Grady, Anderson, and Chase (1998); and the Global Fatigue Index (GFI)
taken from the Multidimensional Assessment of Fatigue (MAF) instrument developed in patients with rheumatoid arthritis (Belza, Henke, Yelin, Epstein, & Gilliss, 1993; Belza, 1995). Wagner et al. (1998) measured physical fatigue using 7 of 14 items from the CFS in a clinical trial of testosterone therapy as a treatment for fatigue in a sample of HIV-infected men with hypogonadism. Items included asking patients whether, in the past week, they had (a) felt tired, (b) needed rest during the day, (c) felt sleepy or drowsy, (d) found it difficult to start doing things, (e) had enough energy, (f) had enough muscle strength, and (g) felt weak. Items were rated with a 5-point Likert scale ranging from 0 (never) to 4 (always). In addition, a single 10-point visual analog scale was used to measure energy. No psychometric information was provided on the CFS. An advantage of the CFS was its brevity, but it failed to measure the variability of fatigue or the impact that fatigue had on ADLs. In essence, these items primarily captured the presence or absence of physical fatigue. O’Dell et al. (1996) measured fatigue in 20 HIV-infected men using the Fatigue Assessment Inventory (FAI) (Cohen & Fisher, 1989) and a visual analog scale. The FAI consists of 42 statements about fatigue such as “I feel helpless when fatigued” rated on a 4-point scale from not at all to totally. A disadvantage of the FAI was its length and the fact that no psychometric properties were reported. Grady et al. (1998) measured fatigue in a sample of HIV-infected men who were randomized in a clinical trial to either receive Interleukin-2 (IL-2) therapy (n = 28 in an experimental group) or not (n = 22 in a control group). They utilized the GFI (Belza, 1995; Belza et al., 1993) and a modified version of the Piper Fatigue Scale (Piper et al., 1989) to measure fatigue. Data were collected at baseline and several time points around the 8-week cycle of IL-2 therapy in the experimental group. For controls, fatigue was measured at baseline, 1 week, and 1 month. Measures were obtained again for control participants who crossed over to receive IL-2. The GFI and Piper scales were highly correlated (r = .95), but this was not surprising because the GFI was generated from the earlier work by Piper and colleagues. The original Piper scale contained 42 items, and that lengthiness may be why Grady and colleagues did not use the entire scale.
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Table 1. Dimensions/Items of the Multidimensional Assessment of Fatigue Instrument Degree Severity Distress Impact on Activities of Daily Living (11 items)
Timing
1. To what degree have you experienced fatigue? 2. How severe is the fatigue which you have been experiencing? 3. To what degree has fatigue caused you distress? In the past week, to what degree has fatigue interfered with your ability to do: 4. Household chores? 5. Cook? 6. Bathe or wash? 7. Dress? 8. Work? 9. Visit or socialize with friends or family? 10. Engage in sexual activity? 11. Engage in leisure and recreational activities? 12. Shop and do errands? 13. Walk? 14. Exercise, other than walking? 15. Over the past week, including today, how often have you been fatigued? 16. To what degree has your fatigue changed during the past week?
Because fatigue is so prevalent in chronic illnesses including HIV, it would be useful for both researchers and clinicians to find a single instrument that could adequately measure and quantify all aspects of fatigue. We chose the GFI from the MAF instrument to measure fatigue in HIV/AIDS because it is easy to administer, relatively short in length, and can assess the subjective components of fatigue summarized by Aaronson et al. (1999): (a) quantity or degree of fatigue, (b) distress due to fatigue, and (c) subjective assessment of the impact of fatigue on ADLs. In addition, it measures the severity of fatigue and allows patients to omit activity items that do not apply to them, thus making a more accurate assessment of the impact of fatigue on ADLs. All of these aspects are then summarized into one score. The purpose of this study was to examine the psychometric properties of the GFI (Belza, 1990, 1995; Belza et al., 1993) in a community-based sample of HIV-symptomatic adults. Correlates of fatigue such as stress and depression, clinical markers of CD4, HIV-PCR counts, and opportunistic infections were also examined.
The Global Fatigue Index The GFI comes from the MAF instrument, a revision of the original Piper Fatigue Scale developed for use with cancer patients (Piper et al., l989). Belza et al.
(1993) designed the GFI to capture the subjective experience of fatigue in patients with rheumatoid arthritis. It has been used to compare fatigue in older adults with rheumatoid arthritis to normal controls (Belza, 1995) and to measure fatigue in rural patients with cancer (Winstead-Fry, 1998), patients with multiple sclerosis (Schwartz, Coulthard-Morris, & Zeng, 1996), and patients with HIV infection (Grady et al., 1998). The GFI consists of 15 out of 16 items from Belza et al.’s MAF instrument that assesses five dimensions of fatigue (see Table 1). For the 11 items asking about the degree to which fatigue has interfered with ADLs, the participant can indicate with an X that he or she does not participate in an activity for reasons other than fatigue (Belza, 1990). The first 14 items are rated on a Likert scale ranging from 1 (not at all) to 10 (a great deal). Item 15 asks how often one has fatigue and is rated from 0 (no days) to 4 (every day). Item 16 asks the degree to which fatigue has changed during the past week and is rated from 0 (I didn’t have fatigue this past week) to 4 (increased). (Note that in the most recent version of the instrument, Item 15 is rated from 1 [hardly any days] to 4 [every day] and Item 16 from 1 [decreased] to 4 [increased] [Belza, 2000].) The GFI scores range from 1 to 50 with higher scores indicating greater impairment from fatigue. Scoring of the GFI involves the sum of Items 1, 2, and 3 plus the average of Items 4 through 14 (activities of
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daily living) and a newly scored multiple choice Item 15 (converted to a 0-10 scale by multiplying each score by 2.5) (Belza, 1990). Item 16 is not used in the GFI, as it measures the degree of change or variability in fatigue over the past week. The GFI is calculated using the average score of the answered ADL items. This takes into account those participants who indicated with an X that they did not engage in an activity and thus does not overinflate the fatigue scores. In Belza’s (1995) work, the GFI was compared to the POMS fatigue subscale for convergent validity (r = .84, p < .001) and with the POMS vigor subscale for divergent validity (r = –.62, p < .001). There were significant bivariate associations between fatigue and the POMS subscale of depression and also with measures of pain, function, and sleep. For internal consistency reliability, Belza et al. (1993) and Belza (1995) reported a Cronbach’s alpha of .93 on the instrument as a whole. Although some researchers have analyzed data using the individual dimension scales, Belza never intended the GFI to be interpreted as separate dimensions but rather as one global measure of fatigue. This was substantiated by her factor analysis, in which items loaded primarily on one factor (personal communication, May 5, 2000).
Method A longitudinal, descriptive survey design was used to collect data over 8 weeks from respondents participating in the HIV Education and Support Study. This was a randomized controlled trial to compare the efficacy of three behavioral interventions: self-management education, social support, and printed information. Major outcomes included symptom status and quality of life. Sample The nonrandom sample (N = 209) was drawn from a San Diego, California, population of adults who were HIV positive and symptomatic. Participants were recruited from HIV community agencies, health clinics, provider referrals, and flyers posted throughout the community. Inclusion criteria included HIV-positive status, 18 years and older, ability to read and speak
English, no HIV-related dementia, and no current drug or alcohol abuse. Procedure The study was approved by institutional review boards, and participants were self-selected for a screening interview and informed consent. Participants who met study criteria filled out questionnaires and had blood drawn at two time points 8 weeks apart. Participants were recruited from September 1997 to August 1999. Measurement The GFI was part of a comprehensive paper-andpencil questionnaire that included patient characteristics, clinical variables, health behaviors, and health outcomes. Depressive symptoms were assessed using the Beck Depression Inventory (Beck, Steer, & Garbin, 1988). Stress and health distress constructs were measured using the Perceived Stress Scale (Cohen, Kamarck, & Mermelstein, 1983; Pbert, Doerfler, & DeCosimo, 1992); the Health Distress Scale, a modified version of the Medical Outcomes Study (MOS) Health Distress Scale (Stewart, Hays, & Ware, 1992); and the Perceived Illness Intrusiveness Scale (Devins, Edworthy, Guthrie, & Martin, 1992). Scoring of the physical health and mental health items from the MOS 36 Item Short-Form Health Survey (SF-36) was done as in the Health Cost and Services Utilization Study (HCSUS) (Hays et al., 1998, 2000). Two items from the vitality subscale of the MOS SF-36 and the 4-item self-efficacy for managing fatigue subscale from the HIV Self-Efficacy instrument (Shively, Gifford, Bormann, & Smith, 1998) were also used. These instruments have reported reliability and validity. The knowledge scale consisted of 6 multiple choice and 27 true/false questions that were developed for this study from published patient education materials. Data Analysis Data were analyzed using SPSS for Windows 9.0 and Stata for Windows 6.0. Internal consistency reliability of the GFI was assessed with Cronbach’s alpha.
Bormann et al. / Measurement of Fatigue in HIV/AIDS
Validity was assessed with factor analysis and bivariate correlations. Findings The sample consisted of 183 HIV-positive men (87.6%) and 26 HIV-positive women (12.4%) with a mean age of 40.8 (SD = 8.3, range = 26 to 70). For clinical status, 50% reported having an AIDS diagnosis. Approximately three quarters (71.8%) of patients reported taking highly active antiretroviral therapy (HAART) consisting of a regimen with at least one protease inhibitor or nonnucleoside reverse transcriptase inhibitor. For additional sample characteristics, see Table 2. More than three quarters of this sample (87.56%) reported some level of fatigue in response to GFI Item 1: “To what degree have you experienced fatigue?” The mean GFI score at baseline was 23.8 (SD = 13.48, range = 1 to 50). As for the frequency of fatigue, 126 (61%) reported having fatigue at least 2 days in a week. Only 26 (12.44%) reported having no fatigue. Examination of demographic data and patient characteristics (age, gender, ethnicity, education, employment, and types of antiretroviral therapy) revealed no significant relationships with the GFI. Reliability Internal consistency reliability was assessed using Cronbach’s alpha on the 15 items of the GFI for a score of .96. Item-to-corrected total correlations ranged from .64 to .86, and the mean interitem correlation was .63. Using the GFI to assess fatigue at two points in time over an 8-week period, the mean GFI scores did not change significantly from the first assessment (M = 23.2, SD = 13.61) to the second assessment (M = 24.1, SD = 13.58) (t = –0.66, df = 194, p = .52), indicating stability. Construct Validity Construct validity was assessed using principal components factor analysis on the GFI items using data from the 85 participants who completed every item of the instrument at baseline, including each of the ADL items. When evaluating the first unrotated
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Table 2. Sample Characteristics (N = 209) Characteristic
n
%
Gender Male 183 87.6 Female 26 12.4 Race/ethnicity Caucasian (not Hispanic) 128 61.2 African American 47 22.5 Hispanic 21 10.0 Other 13 6.3 Education High school or less 65 31.1 Some college 98 46.9 Completed college or graduate degree 46 22.0 Employed Not employed 151 72.2 Less than 20 hours per week 20 9.6 20-35 hours per week 11 5.3 More than 35 hours per week 27 12.9 Personal income $0-$5,000 50 23.9 $5,001-$10,000 81 38.8 > $10,000 78 37.3 HIV risk factors Male sex with male (MSM) only 133 63.6 Heterosexual only 24 11.5 Other 23 11.0 IV drug use (IDU) only 12 5.7 MSM and IDU 11 5.3 Transfusion 6 2.9 Laboratory CD4 (n = 207) < 50 9 4.4 50-199 23 11.1 200-499 89 43.0 > 500 86 41.5 Laboratory viral load (n = 207) < 50 61 29.5 50-999 41 19.8 1,000-9,999 39 18.8 10,000-50,000 31 15.0 50,001-750,000 29 14.0 > 750,000 6 2.9 Past opportunistic infections Yes 165 78.9 No 44 21.1 Antiretroviral therapy None 41 19.6 a 18 8.6 Some without HAART On HAART 150 71.8 Age: M = 40.8, SD = 8.3, Range = 26-70 Years living with HIV: M = 6.4, SD = 4.2, Range = 0.1-16.4 a. HAART = highly active antiretroviral therapy, which is any combination of three or more antiretroviral agents including at least one protease inhibitor or one nonnucleoside reverse transcriptase inhibitor.
factor, there appeared to be only one general factor (Gorsuch, 1997). All 15 items loaded at .63 or greater
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(see Table 3). With varimax rotation using the Kaiser criterion of an eigenvalue greater than one, the analysis yielded two factors accounting for a total of 75.76% of the variance. Factor 1 had an eigenvalue of 9.89, accounting for 65.94% of the variance. Factor 1, which appeared to be level of fatigue, consisted of 13 items related to physical activity (degree, severity, distress, chores, cooking, working, socializing, sexual activity, recreation, shopping, walking, exercise, and timing). Factor 2 had an eigenvalue of 1.5 and accounted for 9.82% of the variance. Factor 2, which appeared to be personal body care, consisted of only two items of dressing and bathing. Construct validity was also assessed using Pearson’s correlations with the BDI, Perceived Stress Scale, Health Distress Scale, Illness Intrusiveness Scale, and number of days spent in bed, all with significant relationships at or above .51, p < .001 (see Table 4). The GFI also correlated inversely with the SF-36 physical health summary scores (r = –.79, p < .001) and SF-36 mental health summary scores (r = –.74, p < .001), indicating that the poorer the physical or mental health, the greater the fatigue. Divergent validity was assessed using the two-item vitality subscale from the SF-36, resulting in a high inverse relationship (r = –.80, p < .001). The GFI was also highly correlated with the HIV Self-Efficacy fatigue subscale measuring one’s confidence in managing fatigue (r = –.64, p < .001). As one has more vitality and greater ability to manage fatigue, one reports less fatigue. Additional construct validity was tested by correlations between the GFI and knowledge or gender. These constructs were not expected to be related to fatigue, and their correlations were appropriately not significant. Clinical Markers and Fatigue The GFI was examined in relationship to serum HIV-RNA, CD4 counts, and the presence of opportunistic infections. There were no significant relationships between the GFI and HIV-RNA or CD4 counts. However, the mean GFI in patients with one or more past opportunistic infections was significantly higher (M = 24.9, SD = 13.25) than in those without prior infections (M = 19.7, SD = 13.29) (t = –24.80, df = 208, p < .001).
Table 3. Principal Components Factor Analysis of Global Fatigue Index Item/Variable Recreation Cook Socialization Chores Shop Severity Walk Distress Exercise Degree Work Sexual activity Timing Bathe Dress
1st Unrotated 1st Rotated 2nd Rotated Factor Factor Factor .88 .87 .87 .87 .86 .86 .85 .83 .81 .81 .79 .77 .74 .68 .63
.67 .62 .61 .62 .62 .87 .61 .86 .73 .86 .67 .61 .86 .16 –.09
.58 .63 .64 .62 .62 .28 .60 .40 .38 .18 .42 .48 –.10 .90 .91
NOTE: The extraction method was principal component analysis. The rotation method was varimax with Kaiser normalization.
Table 4. Correlation Coefficients Global Fatigue Index Beck Depression Inventory Perceived Stress Scale Health distress Illness intrusiveness Number of days in bed SF-36 Physical Health Summary SF-36 Mental Health Summary Vitality (SF-36) subscale Knowledge Gender
.61* .52* .59* .58* .51* –.79* –.74* –.80* –.02 .08
NOTE: SF-36 = Medical Outcomes Study 36 Item Short-Form Health Survey. *p < .001.
Discussion This study examined the psychometric properties of the GFI in a sample of HIV-infected symptomatic adults over time. The GFI appeared to be a valid and reliable measure of fatigue comparable to Belza’s original work on patients with rheumatoid arthritis
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(personal communication, May 5, 2000). This study also supported relationships between fatigue and its correlates such as depression, perceived stress, health distress, and illness intrusiveness. The effects of fatigue can alter one’s physical and mental health, creating additional psychological distress, including feelings of discouragement, fear, worry, and frustration. Several studies have demonstrated that fatigue is consistently associated with severity of depressed mood and major depressive disorder (Ferrando et al., 1998; O’Dell et al., 1996; Perkins et al., 1995; Walker, McGown, Jantos, & Anson, 1997). The finding that fatigue is related to an increased number of days in bed and greater limits in physical and mental functioning is not surprising. Fatigue has been shown to impair physical functioning and to limit activities of daily living (Ferrando et al., 1998). Several studies have reported that fatigue has an impact on health-related quality of life and HIV symptoms (Cleary et al., 1993; Cunningham et al., 1998; Sousa, Holzemer, Bakken Henry, & Slaughter, 1999; Walker et al., 1997; Wilson & Cleary, 1997). People suffering from chronic fatigue have reported diminished life satisfaction (Cleary et al., 1993; Wagner et al., 1998). One unique feature of this study was that it examined fatigue in patients taking HAART. To date, there has been little information on the relationship between viral load and fatigue. HAART has demonstrated suppression of HIV and a decrease in opportunistic infections, which have been cited as contributing to fatigue (Breitbart et al., 1998). Several studies have shown that fatigue is more often associated with psychological markers such as dysphoria, depressed mood, distress, and disability rather than CD4 counts or HIV-RNA (Ferrando et al., 1998; O’Dell et al., 1996; Perkins et al., 1995; Walker et al., 1997). Ferrando et al. (1998) found that chronic fatigue was not directly correlated with CD4 count or HIV-RNA in a sample comparing HIV-positive to HIV-negative men. O’Dell et al. (1996) did not find an association between disability and CD4 count in 528 men and 18 women with an AIDS-defining diagnosis. In this study, the GFI was not related to serum CD4 counts or HIV-RNA. However, there was a significant relationship between the GFI and the presence of one or more opportunistic infections. These outcomes were supported by Ferrando and colleagues’ findings.
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Nursing Implications The GFI provides a comprehensive measure of fatigue that quantifies degree, severity, distress, impact on ADLs, and timing into one global score. One of the unique features of the GFI is that it takes into account the possibility that patients may not engage in certain activities of daily living for reasons other than fatigue. For example, some patients get help with household chores merely because they have family or friends who care for them. Other patients may be impaired due to the progression of HIV disease that causes disability (Stanton et al., 1994). These factors are taken into account in the scoring of the scale. Another strength of the GFI is the inclusion of items that address both the emotional, or subjective, experience of fatigue and the physical impact of fatigue. Items about the extent to which fatigue affects one’s socialization, recreation, or sexual activity also address the social concerns of patients. The potential for isolation, withdrawal, and inability to seek social support are often consequences of severe fatigue (Rose et al., 1998) and should be taken into account when assessing the consequences of fatigue. The inverse association between the GFI and one’s self-efficacy or confidence in managing fatigue was a noteworthy outcome. People who had greater confidence in managing their fatigue symptom also experienced less fatigue. This finding supports the need for patient teaching on strategies to help people cope with fatigue. The GFI is a useful tool in HIV research because of its demonstrated construct validity and internal consistency reliability in a community-based sample of HIV-infected patients. It is a practical, patient-centered, and relatively short instrument that takes only about 5 minutes to complete. It could be used in clinical trials or experimental studies testing new medications and/or interventions that may have an effect on fatigue. As a clinical measure, it has multiple purposes such as assessing baseline fatigue, monitoring the course of fatigue over time or in relation to new drug regimens, and assessing the need for further psychosocial assessment and referral. For example, nurses could give the GFI to new patients in the clinical setting as a measure of their baseline fatigue. Scores taken at follow-up
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visits could provide a long-term view of the progress of fatigue. Because fatigue has been shown to be a predictor of health decline and is associated with physical and psychological morbidity (Breitbart et al., 1998; Wilson & Cleary, 1997), regular fatigue assessments could guide the care plan and be used as an indicator of disease progression. The GFI could also serve as a clinical marker for additional patient assessments that might otherwise be overlooked. For example, patients with high GFI scores should be assessed for clinical depression or dysphoria (Ferrando et al., 1998; Perkins et al., 1995). Due to the strong associations of fatigue with psychological stressors, further psychosocial assessment and referrals could be made for patients with high levels of fatigue. Results of high fatigue scores could also prompt nurses to explore possible causes of fatigue such as side effects of medication or inability to sleep well. In summary, the measurement of fatigue in HIV has been problematic due to its complexity. Finding an instrument such as the GFI that quantifies the various dimensions of fatigue including subjective degree, severity, distress, timing, and impact on ADLs provides researchers and clinicians with a tool to improve patient care. The GFI has been shown to be a valid and reliable measure of fatigue in this community-based sample of patients with HIV. Additional testing in other HIV populations is needed to further support these findings.
Acknowledgements This work was supported by the National Institute of Nursing Research, the National Institutes of Health (1R01 NR04415), the California Universitywide AIDS Research Program (R97SD1137), the VA San Diego Healthcare System, and partially from the NCRR of the NIH for the General Clinical Research Center (MO1-RR00827) at the University of California, San Diego. Permission to use the Multidimensional Assessment of Fatigue Instrument must be obtained from the developer, Dr. Basia Belza, Department of Biobehavioral Nursing and Health Systems, Box 357266, University of Washington, Seattle, WA 98195-7266. Correspondence concerning this article should be addressed to Jill Bormann, PhD, RN, CS, at
the VA San Diego Healthcare System, 3350 LaJolla Village Drive 111N-1, LaJolla, CA, 92161; e-mail: [email protected]. The authors wish to acknowledge Judy Page, RN, and Edward L. Seefried, RN, for participant recruitment, screening, and data collection; Sonia Melendez for administrative support; Tracey Bryant for community outreach efforts; Jim Johnson for data collection and entry; and Uma Bommakanty for data management.
References Aaronson, L. S., Teel, C. S., Cassmeyer, V., Neuberger, G. B., Pallikkathayil, L., Pierce, J., Press, A. N., Williams, P. D., & Wingate, A. (1999). Defining and measuring fatigue. Image: Journal of Nursing Scholarship, 31(1), 45-50. Barroso, J. (1999). A review of fatigue in people with HIV infection. Journal of the Association of Nurses in AIDS Care, 10(5), 42-49. Beck, A. T., Steer, R. A., & Garbin, M. G. (l988). Psychometric properties of the Beck Depression Inventory: Twenty-five years of evaluation. Clinical Psychology Review, 8, 77-100. Belza, B. L. (1990). Multidimensional assessment of fatigue user’s guide. Seattle: University of Washington Press. Belza, B. L. (1995). Comparison of self-reported fatigue in rheumatoid arthritis and controls. The Journal of Rheumatology, 22, 639-643. Belza, B. L. (2000). Multidimensional assessment of fatigue (option 1), user’s guide. Seattle: University of Washington Press. Belza, B. L., Henke, C. J., Yelin, E. H., Epstein, W. V., & Gilliss, C. L. (1993). Correlates of fatigue in older adults with rheumatoid arthritis. Nursing Research, 42, 93-99. Bormann, J., Gifford, A., Shively, M., Timberlake, D., Page, J., and Seefried, E. (1999). Reliability and validity of the Multidimensional Assessment of Fatigue Instrument in patients with HIV/AIDS [Abstract]. Annals of Behavioral Medicine, 21(Suppl.), S032. Breitbart, W., McDonald, M. V., Rosenfeld, B., Monkman, N. D., & Passik, S. (1998). Fatigue in ambulatory AIDS patients. Journal of Pain and Symptom Management, 15(3), 159-167. Chalder, T., Berelowitz, G., Pawlikowska, T., Watts, L., Wessely, S., Wright, D., & Wallace, E. P. (1993). Development of a fatigue scale. Journal of Psychosomatic Research, 37(2), 147-153. Cleary, P., Fowler, F. J., Weissman, J., Massagi, M. P., Wilson, I., Seage, G. R., Gatsonis, C., & Epstein, A. (1993). Health related quality of life in persons with AIDS. Medical Care, 31, 569-580. Cohen, R. A., & Fisher, M. (1989). Amantadine treatment of fatigue associated with multiple sclerosis. Archives of Neurology, 46, 676-680. Cohen, S., Kamarck, T., & Mermelstein, R. (1983). A global measure of perceived stress. Journal of Health and Social Behavior, 24(4), 385-396.
Bormann et al. / Measurement of Fatigue in HIV/AIDS Cunningham, W. E., Shapiro, M. F., Hays, R. D., Dixon, W. J., Visscher, B. R., George, L., Ettl, M. K., & Beck, C. K. (1998). Constitutional symptoms and health related quality of life in patients with symptomatic HIV disease. The American Journal of Medicine, 104, 129-136. Devins, G. M., Edworthy, S. M., Guthrie, N. G., & Martin, L. (1992). Illness intrusiveness in rheumatoid arthritis: Differential impact on depressive symptoms over the adult lifespan. Journal of Rheumatology, 19, 709-715. Darko, D. F., McCutchan, J. A., Kripke, M. D., Gillin, J. C., & Golshan, S. (1992). Fatigue, sleep disturbance, disability, and indices of progression of HIV infection. American Journal of Psychiatry, 149, 514-520 Ferrando, S., Evans, S., Goggin, K., Sewell, M., Fishman, B., & Rabkin, J. (1998). Fatigue in HIV illness: Relationship to depression, physical limitations, and disability. Psychosomatic Medicine, 60, 759-764. Gifford, A. L., Laurent, D. D., Gonzales, V. M., Chesney, M. A., & Lorig, K. R. (1998). Pilot randomized trial of education to improve self-management skills of men with symptomatic HIV/AIDS. Journal of Acquired Immune Deficiency Syndrome and Human Retrovirology, 18, 136-144. Gorsuch, R. L. (1997). Explaining factor analysis: Its role in item analysis. Journal of Personality Assessment, 68, 532-560. Grady, C., Anderson, R., & Chase, G. A. (1998). Fatigue in HIV-infected men receiving investigational interleukin-2. Nursing Research, 47(4), 227-234. Hays, R. D., Cunningham, W. E., Sherbourne, C. D., Wilson, I. B., Wu, A. W., Cleary, P. D., McCaffrey, D. F., Fleishman, J. A., Crystal, S. C., Collins, R., Eggan, F., Shapiro, M. F., & Bozzette, S. A. (2000). Health-related quality of life in people receiving care for HIV infection in the United States: Results from the HIV cost and services utilization study. American Journal of Medicine, 108, 714-722. Hays, R. D., Spritzer, K. L., McCaffrey, D., Cleary, P. D., Collins, R., Sherbourne, C., Wu, A. W., Bozzette, S., Shapiro, M., Cunningham, W., Eggan, F., Crystal, S., & Fleishman, J. (1998). The HIV cost & services utilization study (HCSUS): measures of health related quality of life (DRU-1897AHCPR). Santa Monica, CA: RAND. Laschinger, S., & Fothergill-Bourbonnais, F. (1999). The experience of pain in persons with HIV/AIDS. Journal of the Association of Nurses in AIDS Care, 10(5), 59-67. McNair, D. M., Loor, M., & Droppleman, L. F. (1981). Profile of mood states. San Diego, CA: Educational and Industrial Testing Service. O’Dell, M., Meighen, M., & Riggs, R. V. (1996). Correlates of fatigue in HIV infection prior to AIDS: A pilot study. Disability and Rehabilitation, 18(5), 249-254. Pbert, L., Doerfler, L. A., & DeCosimo, D. (1992). An evaluation of the perceived stress scale in two clinical populations. Journal of Psychopathology and Behavioral Assessment 14, 363-375. Perdices, M., Dunbar, N., Grunseit, A., Hall, W., & Cooper, D. A. (1992). Anxiety, depression and HIV related symptomology
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across the spectrum of HIV disease. Australian and New Zealand Journal of Psychiatry, 26, 560-566. Perkins, D. O., Leserman, J., Stern, R. A., Baum, S. F., Liao, D., Golden, R. N., & Evans, D. L. (1995). Somatic symptoms and HIV infection: Relationship to depressive symptoms and indicators of HIV disease. American Journal of Psychiatry, 152, 1776-1781. Piper, B. F., Lindsey, A. M., Dodd, M. J., Ferketich, S., Paul, S. M., & Weller, S. (1989). The development of an instrument to measure the subjective dimension of fatigue. In S.G. Funk, E. M. Tournquist, M. T. Champagne, L.A. Copp, & R. A. Weise (Eds.), Key aspects of comfort: Management of pain, fatigue, and nausea (pp. 199-208). New York: Springer. Reillo, M. R. (1993). Hyperbaric oxygen therapy for the treatment of debilitating fatigue associated with HIV/AIDS. Journal of the Association for Nurses in AIDS Care, 4(3), 33-38. Rose, L., Pugh, L. C., Lears, K., & Gordon, D. L. (1998). The fatigue experience: Persons with HIV infection. Journal of Advanced Nursing 28(2), 295-304. Schwartz, C. E., Coulthard-Morris, L., & Zeng, Q. (1996). Psychosocial correlates of fatigue in multiple sclerosis. Archives of Physical Medicine and Rehabilitation, 77(2), 165-170. Shively, M., Gifford, A., Bormann, J., & Smith, T. (1998). Development of an HIV Self-Efficacy Instrument [Abstract]. Annals of Behavioral Medicine, 20(Suppl.), S149. Sousa, K. H., Holzemer, W. L., Bakken Henry, S., & Slaughter, R. (1999). Dimensions of health-related quality of life in persons living with HIV disease. Journal of Advanced Nursing, 29(1), 178-187. Stanton, D. L., Wu, A. W., Moore, R. D., Rucker, S. C., Piazza, M. P., Abrams, J. E., & Chaisson, R. E. (1994). Functional status of persons with HIV infection in an ambulatory setting. Journal of Acquired Immune Deficiency Syndromes, 7, 1050-1056. Stewart, A. L., Hays, R. D., & Ware, J. E. (1992). Health perceptions, energy/fatigue, and health distress measures. In A. L. Stewart and J. E. Ware (Eds.), Measuring functioning and well being: The medical outcomes study approach. Durham, NC: Duke University Press. Wagner, G. J., Rabkin, J. G., & Rabkin, R. (l997). Dextroamphetamine as a treatment for depression and low energy in AIDS patients: A pilot study. Journal of Psychosomatic Research, 42, 407-411. Wagner, G. J., Rabkin, J. G., & Rabkin, R. (1998). Testosterone as a treatment for fatigue in HIV+ men. General Hospital Psychiatry, 20, 209-213. Walker, K., McGown, A., Jantos, M., & Anson, J. (1997). Fatigue, depression, and quality of life in HIV-positive men. Journal of Psychosocial Nursing and Mental Health Services, 35(9), 32-40. Wilson, I. B., & Cleary, P.D. (1997). Clinical predictors of declines in physical functioning in persons with AIDS: Results of a longitudinal study. Journal of Acquired Immune Deficiency Syndromes and Human Retrovirology, 16, 343-349. Winstead-Fry, P. (1998). Psychometric assessment of four fatigue scales with a sample of rural cancer patients. Journal of Nursing Measurement, 6(2), 111-122.
Measurement of Fatigue in HIV-Positive Adults: Reliability and Validity of the Global Fatigue Index Jill Bormann, PhD, RN, CS Martha Shively, PhD, RN Tom L. Smith, PhD Allen L. Gifford, MD Fatigue is among the most common and distressing symptoms in patients with HIV/AIDS. Little is known about the clinical assessment of fatigue, especially in patients using highly active antiretroviral regimens. The purpose of this study was to evaluate the psychometric properties of the Global Fatigue Index (GFI) in a community-based sample of 209 patients with HIV/AIDS. The GFI is a measure that quantifies five dimensions of fatigue from the Multidimensional Assessment of Fatigue instrument into one score. To assess construct validity, the study included measures of depression, perceived stress, activities of daily living (ADLs), health behaviors, and clinical markers. Cronbach’s alpha was calculated for internal consistency reliability, and factor analysis and bivariate correlations were conducted. The GFI was found to be easily self-administered, reliable, and a valid measure of overall fatigue burden in an HIV population. This instrument may be used by clinicians and researchers for assessing fatigue. Key words: HIV/AIDS, fatigue, measurement
F
atigue has been cited as among the most bothersome and frequently reported symptoms of HIV infection (Bormann, Gifford, Shively, Timberlake, Page, & Seefried, 1999; Breitbart, McDonald, Rosenfeld, Monkman, & Passik, 1998; Cunningham et al., 1998; Darko, McCutchan, Kripke, Gillin & Golshan, 1992;
O’Dell, Meighen, & Riggs, l996; Perdices, Dunbar, Grunseit, Hall, & Cooper, 1992; Shively, Gifford, Bormann, & Smith, 1998). Several studies have indicated that fatigue interferes with quality of life (Breitbart et al., 1998; Cleary et al., 1993; Cunningham et al., 1998; Wilson & Cleary, 1997). Fatigue often decreases activities of daily living (ADLs) and limits physical functioning (Wilson & Cleary, l997). Fatigue, functional status, and severity of symptoms have predicted overall perceived health status in persons with AIDS (Cleary et al., 1993) and fatigue has been associated with significant physical and psychological morbidity (Breibart et al., 1998). These quantitative findings have been further supported by interviews of 21 HIV-positive patients about painful losses, including the loss of energy, time, and independence.
Jill Bormann, PhD, RN, CS, was supported by a VA postdoctoral fellowship through the VA Office of Academic Affiliations. Martha Shively, PhD, RN, is a professor, San Diego State University School of Nursing and Associate Chief, Nursing Service for Research at the VA San Diego Healthcare System. Tom L. Smith, PhD, is a principal statistician, Department of Psychology, School of Medicine, University of California, San Diego. Allen L. Gifford, MD, is an assistant professor of medicine at the University of California, San Diego, and a principal investigator at the VA San Diego Healthcare System.
JOURNAL OF THE ASSOCIATION OF NURSES IN AIDS CARE, Vol. 12, No. 3, May/June 2001, 75-83 Copyright © 2001 Association of Nurses in AIDS Care
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Loss of energy was described as an overwhelming presence in their lives. Frequently, this loss of energy had a direct impact on their abilities to be involved with people and with daily events. This limited their social lives, and the limitation was identified as being painful. (Laschinger & Fothergill-Bourbonnais, 1999, p. 62) Fatigue is a complex construct consisting of cognitive, emotional, and physical components. Aaronson et al. (1999) categorized fatigue according to five salient characteristics: (a) subjective quantification of fatigue, (b) subjective distress due to fatigue, (c) subjective assessment of the impact of fatigue on activities of daily living, (d) correlates of fatigue, and (e) key biological parameters. In a literature review, Barroso (1999) concluded that measuring fatigue in HIV/AIDS patients has been problematic and recommended that an instrument needs to “capture the intensity, circumstances, and consequences of fatigue” (p. 46). A variety of methods have been used to measure fatigue in HIV-infected patients ranging from hermeneutic phenomenology using semistructured qualitative interviews (Rose, Pugh, Lears, & Gordon, 1998) to visual analog scales (O’Dell et al., 1996; Wagner, Rabkin, & Rabkin, 1997; Walker, McGown, Jantos, & Anson, 1997). Approaches have included the AIDS symptom checklist and the Memorial Symptom Assessment Scale (Breitbart et al., 1998), rating scales (Cunningham et al., 1988), the fatigue subscale from the Profile of Mood States (POMS) (McNair, Lorr, & Droppleman, 1981; Gifford, Laurent, Gonzales, Chesney, & Lorig, 1998) and single-item questions. Often, fatigue measures have consisted of a few items that targeted only one or two aspects of fatigue or simply assessed the presence or absence of fatigue. Instruments developed to assess fatigue in other populations have been used in HIV research. These include the Chalder Fatigue Scale (CFS) developed in general practice medical patients (Chalder et al., 1993); the Fatigue Assessment Inventory developed in patients with multiple sclerosis (Cohen & Fisher, 1989); a version of the Piper Fatigue Scale developed in cancer patients (Piper, Lindsey, Dodd, Ferketich, Paul & Weller, 1989) and modified by Grady, Anderson, and Chase (1998); and the Global Fatigue Index (GFI)
taken from the Multidimensional Assessment of Fatigue (MAF) instrument developed in patients with rheumatoid arthritis (Belza, Henke, Yelin, Epstein, & Gilliss, 1993; Belza, 1995). Wagner et al. (1998) measured physical fatigue using 7 of 14 items from the CFS in a clinical trial of testosterone therapy as a treatment for fatigue in a sample of HIV-infected men with hypogonadism. Items included asking patients whether, in the past week, they had (a) felt tired, (b) needed rest during the day, (c) felt sleepy or drowsy, (d) found it difficult to start doing things, (e) had enough energy, (f) had enough muscle strength, and (g) felt weak. Items were rated with a 5-point Likert scale ranging from 0 (never) to 4 (always). In addition, a single 10-point visual analog scale was used to measure energy. No psychometric information was provided on the CFS. An advantage of the CFS was its brevity, but it failed to measure the variability of fatigue or the impact that fatigue had on ADLs. In essence, these items primarily captured the presence or absence of physical fatigue. O’Dell et al. (1996) measured fatigue in 20 HIV-infected men using the Fatigue Assessment Inventory (FAI) (Cohen & Fisher, 1989) and a visual analog scale. The FAI consists of 42 statements about fatigue such as “I feel helpless when fatigued” rated on a 4-point scale from not at all to totally. A disadvantage of the FAI was its length and the fact that no psychometric properties were reported. Grady et al. (1998) measured fatigue in a sample of HIV-infected men who were randomized in a clinical trial to either receive Interleukin-2 (IL-2) therapy (n = 28 in an experimental group) or not (n = 22 in a control group). They utilized the GFI (Belza, 1995; Belza et al., 1993) and a modified version of the Piper Fatigue Scale (Piper et al., 1989) to measure fatigue. Data were collected at baseline and several time points around the 8-week cycle of IL-2 therapy in the experimental group. For controls, fatigue was measured at baseline, 1 week, and 1 month. Measures were obtained again for control participants who crossed over to receive IL-2. The GFI and Piper scales were highly correlated (r = .95), but this was not surprising because the GFI was generated from the earlier work by Piper and colleagues. The original Piper scale contained 42 items, and that lengthiness may be why Grady and colleagues did not use the entire scale.
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Table 1. Dimensions/Items of the Multidimensional Assessment of Fatigue Instrument Degree Severity Distress Impact on Activities of Daily Living (11 items)
Timing
1. To what degree have you experienced fatigue? 2. How severe is the fatigue which you have been experiencing? 3. To what degree has fatigue caused you distress? In the past week, to what degree has fatigue interfered with your ability to do: 4. Household chores? 5. Cook? 6. Bathe or wash? 7. Dress? 8. Work? 9. Visit or socialize with friends or family? 10. Engage in sexual activity? 11. Engage in leisure and recreational activities? 12. Shop and do errands? 13. Walk? 14. Exercise, other than walking? 15. Over the past week, including today, how often have you been fatigued? 16. To what degree has your fatigue changed during the past week?
Because fatigue is so prevalent in chronic illnesses including HIV, it would be useful for both researchers and clinicians to find a single instrument that could adequately measure and quantify all aspects of fatigue. We chose the GFI from the MAF instrument to measure fatigue in HIV/AIDS because it is easy to administer, relatively short in length, and can assess the subjective components of fatigue summarized by Aaronson et al. (1999): (a) quantity or degree of fatigue, (b) distress due to fatigue, and (c) subjective assessment of the impact of fatigue on ADLs. In addition, it measures the severity of fatigue and allows patients to omit activity items that do not apply to them, thus making a more accurate assessment of the impact of fatigue on ADLs. All of these aspects are then summarized into one score. The purpose of this study was to examine the psychometric properties of the GFI (Belza, 1990, 1995; Belza et al., 1993) in a community-based sample of HIV-symptomatic adults. Correlates of fatigue such as stress and depression, clinical markers of CD4, HIV-PCR counts, and opportunistic infections were also examined.
The Global Fatigue Index The GFI comes from the MAF instrument, a revision of the original Piper Fatigue Scale developed for use with cancer patients (Piper et al., l989). Belza et al.
(1993) designed the GFI to capture the subjective experience of fatigue in patients with rheumatoid arthritis. It has been used to compare fatigue in older adults with rheumatoid arthritis to normal controls (Belza, 1995) and to measure fatigue in rural patients with cancer (Winstead-Fry, 1998), patients with multiple sclerosis (Schwartz, Coulthard-Morris, & Zeng, 1996), and patients with HIV infection (Grady et al., 1998). The GFI consists of 15 out of 16 items from Belza et al.’s MAF instrument that assesses five dimensions of fatigue (see Table 1). For the 11 items asking about the degree to which fatigue has interfered with ADLs, the participant can indicate with an X that he or she does not participate in an activity for reasons other than fatigue (Belza, 1990). The first 14 items are rated on a Likert scale ranging from 1 (not at all) to 10 (a great deal). Item 15 asks how often one has fatigue and is rated from 0 (no days) to 4 (every day). Item 16 asks the degree to which fatigue has changed during the past week and is rated from 0 (I didn’t have fatigue this past week) to 4 (increased). (Note that in the most recent version of the instrument, Item 15 is rated from 1 [hardly any days] to 4 [every day] and Item 16 from 1 [decreased] to 4 [increased] [Belza, 2000].) The GFI scores range from 1 to 50 with higher scores indicating greater impairment from fatigue. Scoring of the GFI involves the sum of Items 1, 2, and 3 plus the average of Items 4 through 14 (activities of
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daily living) and a newly scored multiple choice Item 15 (converted to a 0-10 scale by multiplying each score by 2.5) (Belza, 1990). Item 16 is not used in the GFI, as it measures the degree of change or variability in fatigue over the past week. The GFI is calculated using the average score of the answered ADL items. This takes into account those participants who indicated with an X that they did not engage in an activity and thus does not overinflate the fatigue scores. In Belza’s (1995) work, the GFI was compared to the POMS fatigue subscale for convergent validity (r = .84, p < .001) and with the POMS vigor subscale for divergent validity (r = –.62, p < .001). There were significant bivariate associations between fatigue and the POMS subscale of depression and also with measures of pain, function, and sleep. For internal consistency reliability, Belza et al. (1993) and Belza (1995) reported a Cronbach’s alpha of .93 on the instrument as a whole. Although some researchers have analyzed data using the individual dimension scales, Belza never intended the GFI to be interpreted as separate dimensions but rather as one global measure of fatigue. This was substantiated by her factor analysis, in which items loaded primarily on one factor (personal communication, May 5, 2000).
Method A longitudinal, descriptive survey design was used to collect data over 8 weeks from respondents participating in the HIV Education and Support Study. This was a randomized controlled trial to compare the efficacy of three behavioral interventions: self-management education, social support, and printed information. Major outcomes included symptom status and quality of life. Sample The nonrandom sample (N = 209) was drawn from a San Diego, California, population of adults who were HIV positive and symptomatic. Participants were recruited from HIV community agencies, health clinics, provider referrals, and flyers posted throughout the community. Inclusion criteria included HIV-positive status, 18 years and older, ability to read and speak
English, no HIV-related dementia, and no current drug or alcohol abuse. Procedure The study was approved by institutional review boards, and participants were self-selected for a screening interview and informed consent. Participants who met study criteria filled out questionnaires and had blood drawn at two time points 8 weeks apart. Participants were recruited from September 1997 to August 1999. Measurement The GFI was part of a comprehensive paper-andpencil questionnaire that included patient characteristics, clinical variables, health behaviors, and health outcomes. Depressive symptoms were assessed using the Beck Depression Inventory (Beck, Steer, & Garbin, 1988). Stress and health distress constructs were measured using the Perceived Stress Scale (Cohen, Kamarck, & Mermelstein, 1983; Pbert, Doerfler, & DeCosimo, 1992); the Health Distress Scale, a modified version of the Medical Outcomes Study (MOS) Health Distress Scale (Stewart, Hays, & Ware, 1992); and the Perceived Illness Intrusiveness Scale (Devins, Edworthy, Guthrie, & Martin, 1992). Scoring of the physical health and mental health items from the MOS 36 Item Short-Form Health Survey (SF-36) was done as in the Health Cost and Services Utilization Study (HCSUS) (Hays et al., 1998, 2000). Two items from the vitality subscale of the MOS SF-36 and the 4-item self-efficacy for managing fatigue subscale from the HIV Self-Efficacy instrument (Shively, Gifford, Bormann, & Smith, 1998) were also used. These instruments have reported reliability and validity. The knowledge scale consisted of 6 multiple choice and 27 true/false questions that were developed for this study from published patient education materials. Data Analysis Data were analyzed using SPSS for Windows 9.0 and Stata for Windows 6.0. Internal consistency reliability of the GFI was assessed with Cronbach’s alpha.
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Validity was assessed with factor analysis and bivariate correlations. Findings The sample consisted of 183 HIV-positive men (87.6%) and 26 HIV-positive women (12.4%) with a mean age of 40.8 (SD = 8.3, range = 26 to 70). For clinical status, 50% reported having an AIDS diagnosis. Approximately three quarters (71.8%) of patients reported taking highly active antiretroviral therapy (HAART) consisting of a regimen with at least one protease inhibitor or nonnucleoside reverse transcriptase inhibitor. For additional sample characteristics, see Table 2. More than three quarters of this sample (87.56%) reported some level of fatigue in response to GFI Item 1: “To what degree have you experienced fatigue?” The mean GFI score at baseline was 23.8 (SD = 13.48, range = 1 to 50). As for the frequency of fatigue, 126 (61%) reported having fatigue at least 2 days in a week. Only 26 (12.44%) reported having no fatigue. Examination of demographic data and patient characteristics (age, gender, ethnicity, education, employment, and types of antiretroviral therapy) revealed no significant relationships with the GFI. Reliability Internal consistency reliability was assessed using Cronbach’s alpha on the 15 items of the GFI for a score of .96. Item-to-corrected total correlations ranged from .64 to .86, and the mean interitem correlation was .63. Using the GFI to assess fatigue at two points in time over an 8-week period, the mean GFI scores did not change significantly from the first assessment (M = 23.2, SD = 13.61) to the second assessment (M = 24.1, SD = 13.58) (t = –0.66, df = 194, p = .52), indicating stability. Construct Validity Construct validity was assessed using principal components factor analysis on the GFI items using data from the 85 participants who completed every item of the instrument at baseline, including each of the ADL items. When evaluating the first unrotated
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Table 2. Sample Characteristics (N = 209) Characteristic
n
%
Gender Male 183 87.6 Female 26 12.4 Race/ethnicity Caucasian (not Hispanic) 128 61.2 African American 47 22.5 Hispanic 21 10.0 Other 13 6.3 Education High school or less 65 31.1 Some college 98 46.9 Completed college or graduate degree 46 22.0 Employed Not employed 151 72.2 Less than 20 hours per week 20 9.6 20-35 hours per week 11 5.3 More than 35 hours per week 27 12.9 Personal income $0-$5,000 50 23.9 $5,001-$10,000 81 38.8 > $10,000 78 37.3 HIV risk factors Male sex with male (MSM) only 133 63.6 Heterosexual only 24 11.5 Other 23 11.0 IV drug use (IDU) only 12 5.7 MSM and IDU 11 5.3 Transfusion 6 2.9 Laboratory CD4 (n = 207) < 50 9 4.4 50-199 23 11.1 200-499 89 43.0 > 500 86 41.5 Laboratory viral load (n = 207) < 50 61 29.5 50-999 41 19.8 1,000-9,999 39 18.8 10,000-50,000 31 15.0 50,001-750,000 29 14.0 > 750,000 6 2.9 Past opportunistic infections Yes 165 78.9 No 44 21.1 Antiretroviral therapy None 41 19.6 a 18 8.6 Some without HAART On HAART 150 71.8 Age: M = 40.8, SD = 8.3, Range = 26-70 Years living with HIV: M = 6.4, SD = 4.2, Range = 0.1-16.4 a. HAART = highly active antiretroviral therapy, which is any combination of three or more antiretroviral agents including at least one protease inhibitor or one nonnucleoside reverse transcriptase inhibitor.
factor, there appeared to be only one general factor (Gorsuch, 1997). All 15 items loaded at .63 or greater
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(see Table 3). With varimax rotation using the Kaiser criterion of an eigenvalue greater than one, the analysis yielded two factors accounting for a total of 75.76% of the variance. Factor 1 had an eigenvalue of 9.89, accounting for 65.94% of the variance. Factor 1, which appeared to be level of fatigue, consisted of 13 items related to physical activity (degree, severity, distress, chores, cooking, working, socializing, sexual activity, recreation, shopping, walking, exercise, and timing). Factor 2 had an eigenvalue of 1.5 and accounted for 9.82% of the variance. Factor 2, which appeared to be personal body care, consisted of only two items of dressing and bathing. Construct validity was also assessed using Pearson’s correlations with the BDI, Perceived Stress Scale, Health Distress Scale, Illness Intrusiveness Scale, and number of days spent in bed, all with significant relationships at or above .51, p < .001 (see Table 4). The GFI also correlated inversely with the SF-36 physical health summary scores (r = –.79, p < .001) and SF-36 mental health summary scores (r = –.74, p < .001), indicating that the poorer the physical or mental health, the greater the fatigue. Divergent validity was assessed using the two-item vitality subscale from the SF-36, resulting in a high inverse relationship (r = –.80, p < .001). The GFI was also highly correlated with the HIV Self-Efficacy fatigue subscale measuring one’s confidence in managing fatigue (r = –.64, p < .001). As one has more vitality and greater ability to manage fatigue, one reports less fatigue. Additional construct validity was tested by correlations between the GFI and knowledge or gender. These constructs were not expected to be related to fatigue, and their correlations were appropriately not significant. Clinical Markers and Fatigue The GFI was examined in relationship to serum HIV-RNA, CD4 counts, and the presence of opportunistic infections. There were no significant relationships between the GFI and HIV-RNA or CD4 counts. However, the mean GFI in patients with one or more past opportunistic infections was significantly higher (M = 24.9, SD = 13.25) than in those without prior infections (M = 19.7, SD = 13.29) (t = –24.80, df = 208, p < .001).
Table 3. Principal Components Factor Analysis of Global Fatigue Index Item/Variable Recreation Cook Socialization Chores Shop Severity Walk Distress Exercise Degree Work Sexual activity Timing Bathe Dress
1st Unrotated 1st Rotated 2nd Rotated Factor Factor Factor .88 .87 .87 .87 .86 .86 .85 .83 .81 .81 .79 .77 .74 .68 .63
.67 .62 .61 .62 .62 .87 .61 .86 .73 .86 .67 .61 .86 .16 –.09
.58 .63 .64 .62 .62 .28 .60 .40 .38 .18 .42 .48 –.10 .90 .91
NOTE: The extraction method was principal component analysis. The rotation method was varimax with Kaiser normalization.
Table 4. Correlation Coefficients Global Fatigue Index Beck Depression Inventory Perceived Stress Scale Health distress Illness intrusiveness Number of days in bed SF-36 Physical Health Summary SF-36 Mental Health Summary Vitality (SF-36) subscale Knowledge Gender
.61* .52* .59* .58* .51* –.79* –.74* –.80* –.02 .08
NOTE: SF-36 = Medical Outcomes Study 36 Item Short-Form Health Survey. *p < .001.
Discussion This study examined the psychometric properties of the GFI in a sample of HIV-infected symptomatic adults over time. The GFI appeared to be a valid and reliable measure of fatigue comparable to Belza’s original work on patients with rheumatoid arthritis
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(personal communication, May 5, 2000). This study also supported relationships between fatigue and its correlates such as depression, perceived stress, health distress, and illness intrusiveness. The effects of fatigue can alter one’s physical and mental health, creating additional psychological distress, including feelings of discouragement, fear, worry, and frustration. Several studies have demonstrated that fatigue is consistently associated with severity of depressed mood and major depressive disorder (Ferrando et al., 1998; O’Dell et al., 1996; Perkins et al., 1995; Walker, McGown, Jantos, & Anson, 1997). The finding that fatigue is related to an increased number of days in bed and greater limits in physical and mental functioning is not surprising. Fatigue has been shown to impair physical functioning and to limit activities of daily living (Ferrando et al., 1998). Several studies have reported that fatigue has an impact on health-related quality of life and HIV symptoms (Cleary et al., 1993; Cunningham et al., 1998; Sousa, Holzemer, Bakken Henry, & Slaughter, 1999; Walker et al., 1997; Wilson & Cleary, 1997). People suffering from chronic fatigue have reported diminished life satisfaction (Cleary et al., 1993; Wagner et al., 1998). One unique feature of this study was that it examined fatigue in patients taking HAART. To date, there has been little information on the relationship between viral load and fatigue. HAART has demonstrated suppression of HIV and a decrease in opportunistic infections, which have been cited as contributing to fatigue (Breitbart et al., 1998). Several studies have shown that fatigue is more often associated with psychological markers such as dysphoria, depressed mood, distress, and disability rather than CD4 counts or HIV-RNA (Ferrando et al., 1998; O’Dell et al., 1996; Perkins et al., 1995; Walker et al., 1997). Ferrando et al. (1998) found that chronic fatigue was not directly correlated with CD4 count or HIV-RNA in a sample comparing HIV-positive to HIV-negative men. O’Dell et al. (1996) did not find an association between disability and CD4 count in 528 men and 18 women with an AIDS-defining diagnosis. In this study, the GFI was not related to serum CD4 counts or HIV-RNA. However, there was a significant relationship between the GFI and the presence of one or more opportunistic infections. These outcomes were supported by Ferrando and colleagues’ findings.
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Nursing Implications The GFI provides a comprehensive measure of fatigue that quantifies degree, severity, distress, impact on ADLs, and timing into one global score. One of the unique features of the GFI is that it takes into account the possibility that patients may not engage in certain activities of daily living for reasons other than fatigue. For example, some patients get help with household chores merely because they have family or friends who care for them. Other patients may be impaired due to the progression of HIV disease that causes disability (Stanton et al., 1994). These factors are taken into account in the scoring of the scale. Another strength of the GFI is the inclusion of items that address both the emotional, or subjective, experience of fatigue and the physical impact of fatigue. Items about the extent to which fatigue affects one’s socialization, recreation, or sexual activity also address the social concerns of patients. The potential for isolation, withdrawal, and inability to seek social support are often consequences of severe fatigue (Rose et al., 1998) and should be taken into account when assessing the consequences of fatigue. The inverse association between the GFI and one’s self-efficacy or confidence in managing fatigue was a noteworthy outcome. People who had greater confidence in managing their fatigue symptom also experienced less fatigue. This finding supports the need for patient teaching on strategies to help people cope with fatigue. The GFI is a useful tool in HIV research because of its demonstrated construct validity and internal consistency reliability in a community-based sample of HIV-infected patients. It is a practical, patient-centered, and relatively short instrument that takes only about 5 minutes to complete. It could be used in clinical trials or experimental studies testing new medications and/or interventions that may have an effect on fatigue. As a clinical measure, it has multiple purposes such as assessing baseline fatigue, monitoring the course of fatigue over time or in relation to new drug regimens, and assessing the need for further psychosocial assessment and referral. For example, nurses could give the GFI to new patients in the clinical setting as a measure of their baseline fatigue. Scores taken at follow-up
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visits could provide a long-term view of the progress of fatigue. Because fatigue has been shown to be a predictor of health decline and is associated with physical and psychological morbidity (Breitbart et al., 1998; Wilson & Cleary, 1997), regular fatigue assessments could guide the care plan and be used as an indicator of disease progression. The GFI could also serve as a clinical marker for additional patient assessments that might otherwise be overlooked. For example, patients with high GFI scores should be assessed for clinical depression or dysphoria (Ferrando et al., 1998; Perkins et al., 1995). Due to the strong associations of fatigue with psychological stressors, further psychosocial assessment and referrals could be made for patients with high levels of fatigue. Results of high fatigue scores could also prompt nurses to explore possible causes of fatigue such as side effects of medication or inability to sleep well. In summary, the measurement of fatigue in HIV has been problematic due to its complexity. Finding an instrument such as the GFI that quantifies the various dimensions of fatigue including subjective degree, severity, distress, timing, and impact on ADLs provides researchers and clinicians with a tool to improve patient care. The GFI has been shown to be a valid and reliable measure of fatigue in this community-based sample of patients with HIV. Additional testing in other HIV populations is needed to further support these findings.
Acknowledgements This work was supported by the National Institute of Nursing Research, the National Institutes of Health (1R01 NR04415), the California Universitywide AIDS Research Program (R97SD1137), the VA San Diego Healthcare System, and partially from the NCRR of the NIH for the General Clinical Research Center (MO1-RR00827) at the University of California, San Diego. Permission to use the Multidimensional Assessment of Fatigue Instrument must be obtained from the developer, Dr. Basia Belza, Department of Biobehavioral Nursing and Health Systems, Box 357266, University of Washington, Seattle, WA 98195-7266. Correspondence concerning this article should be addressed to Jill Bormann, PhD, RN, CS, at
the VA San Diego Healthcare System, 3350 LaJolla Village Drive 111N-1, LaJolla, CA, 92161; e-mail: [email protected]. The authors wish to acknowledge Judy Page, RN, and Edward L. Seefried, RN, for participant recruitment, screening, and data collection; Sonia Melendez for administrative support; Tracey Bryant for community outreach efforts; Jim Johnson for data collection and entry; and Uma Bommakanty for data management.
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