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Patient-Related Barriers to Fatigue Communication
Vol. 24 No. 5 November 2002
Journal of Pain and Symptom Management
481
Original Article
Patient-Related Barriers to Fatigue Communication: Initial Validation of the Fatigue Management Barriers Questionnaire Steven D. Passik, PhD,* Kenneth L. Kirsh, PhD, Kathleen Donaghy, PhD, Elizabeth Holtsclaw, BA, Dale Theobald, MD, PhD, David Cella, PhD, and William Breitbart, MD, for the Fatigue Coalition Symptom Management and Palliative Care Program (S.D.P., K.L.K.), Markey Cancer Center, University of Kentucky, Lexington, Kentucky; Oncology Symptom Control & Research (K.D., E.H., D.T.), Community Cancer Care, Indianapolis, Indiana; Institute for Health Services Research and Policy Studies (D.C.), Northwestern University, Evanston, Illinois; and Psychiatry Service (W.B.), Memorial Sloan-Kettering Cancer Center, New York, New York, USA
Abstract Fatigue is a highly prevalent and distressing symptom of cancer and its treatment. However, cancer patients often fail to communicate with their oncologists about fatigue. In this study, we attempted to identify the patient-related barriers to communication about fatigue, as cited by patients. Two hundred patients were sampled across the Community Cancer Care, Inc. (CCC) network of Indiana using the Cancer Behavior Inventory-Brief scale (CBI-B), the Zung Self-Rating Depression Scale (ZSDS), the Functional Assessment of Cancer Inventory-Fatigue scale (FACT-F), and the Fatigue Management Barriers Questionnaire (FMBQ), a questionnaire devised by experts in the field of cancer-related fatigue. There were no significant correlations between the instrument scores and demographic variables. Scores on the instruments did not differ significantly based on whether the patient was from a rural or urban site. One hundred thirty-two patients (66%) reported that they had never spoken to their doctor about fatigue. The most frequently reported reasons for this lack of patient communication about fatigue included the doctor’s failure to offer interventions (47%), patients’ lack of awareness of effective treatments for fatigue (43%), a desire on the patient’s part to treat fatigue without medications (40%), and not wanting to complain to the doctor (28%). Patients reported that medical staff offered a mean of 11.63 recommendations for dealing with fatigue. The FMBQ was found to correlate significantly with self-efficacy (CBI-B, r 0.20, P 0.01) and correlate weakly with the number of recommendations made (r 0.15, P 0.05). The FMBQ was noted to have acceptable internal consistency ( 0.88) and validity and may prove to be a useful instrument for understanding why
*Address reprint requests to: Steven D. Passik, PhD, Symptom Management and Palliative Care, University of Kentucky, Markey Cancer Center — cc 449, 800 Rose Street, Lexington KY 40536, USA. Accepted for publication: January 19, 2002. © U.S. Cancer Pain Relief Committee, 2002 Published by Elsevier, New York, New York
0885-3924/02/$–see front matter PII S0885-3924(02)00518-3
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patients do not communicate about fatigue. Multiple barriers contribute to why cancer patients do not comment about fatigue but may be overcome if physicians screen and assess for this symptom. J Pain Symptom Manage 2002;24:481–493. © U.S. Cancer Pain Relief Committee. 2002 Key Words Fatigue, cancer, communication
Introduction Fatigue is the most common symptom reported by cancer patients.1–4 Past studies report prevalence rates ranging from 61%–90% for fatigue in various oncology samples.4–6 Cancer-related fatigue (CRF) is associated with significant impairment. A recent study by Ashbury and colleagues7 found that cancer patients with CRF were more likely to have impairment in performing normal daily activities and to more frequently use health care services than their non-fatigued counterparts. To date, the mechanisms of CRF are not fully understood, nor is there consensus on how to best identify clinically relevant fatigue.8 Perhaps the best way to characterize fatigue is to view it as a multidimensional problem involving chronic exhaustion and diminished capacity for physical activity that is not alleviated by rest.1,9 This is not to say that fatigue is solely a physical entity, however. The etiology may be physical, psychological, or pathological.1,10,11 In addition, fatigue level may be influenced by a variety of factors including cancer treatment, changes in sleeping patterns, symptom distress, mood disturbance, low hemoglobin levels, or poor performance status.5,6,12,13 In a recent survey of nearly 200 oncologists,4 80% reported that fatigue is either neglected or undertreated in cancer patients. This survey also queried patients and found that most (74%) believed fatigue to be an untreatable symptom that one had to endure as a normal part of cancer and its accompanying treatment. This perception contrasts with the reality of many potential treatments to combat fatigue. For instance, self-care activities and education for the patient and family can be useful.14 Several recent studies15–20 have shown that aerobic exercise can help to improve the physical performance of cancer patients. Recombinant human erythropoietin (r-HuEPO, epoetin alfa) has been shown to increase he-
moglobin levels and to subsequently reduce fatigue in cancer patients.21–24 Epoetin alfa improved patients’ perceived energy levels, functional status, and overall quality of life. Patient-related barriers to communicating about fatigue have not been well studied, but barriers that might be similar have been described in cancer pain25 and AIDS pain.26 Ward and colleagues25 found that patient concerns were fairly universal with regard to treatment of cancer pain. Fears of addiction, tolerance, side effects, and distracting physicians were reported as barriers by over 70% of patients. Endorsement of these barriers was related to the undermedication of the patient’s pain. Breitbart and colleagues26 reported similar findings with regard to barriers endorsed by patients with AIDS. In addition, these investigations added concerns specific to AIDS patients. They observed that patients often showed a preference for “natural” or alternative interventions and a desire to limit their overall use of medications. The present study is modeled after these prior efforts and was intended to understand specific barriers to fatigue communication commonly endorsed by cancer patients. When better understood, knowledge of the prominent barriers can lead to tailored educational efforts to facilitate such communication. As prior research suggests27 successful interventions for fatigue should be patient-specific. While no true a priori hypotheses were postulated for this initial instrument validation study, several areas of potential interest were defined for exploration. First, it was of interest to explore the relationship between self-efficacy and communication about fatigue, as cited by patients. Because the novel scale introduced here is concerned with identifying barriers to communication about fatigue, it is important to explore whether individual levels of self-efficacy have an impact on this construct. It has been sug-
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gested that increased levels of self-efficacy are associated with greater levels of treatment adherence and increased self-care behavior.28 For this reason, self-efficacy is an important area to consider. It may well be that patients with higher levels of self-efficacy are more apt to communicate or endorse different barriers compared to patients with low self-efficacy. Ultimately, this could lead to a more tailored approach to the treatment of fatigue. Second, there is a likely relationship between depression and fatigue that needs to be addressed in any attempt to explore fatigue communication. In fact, our recent work29 has shown that a single-item taken from a depression scale can be utilized as a triage-like screen for more detailed follow-up for cancer-related fatigue, indicating some level of overlap. Indeed, some researchers30 have shown significant correlations between fatigue and depression. However, this is not to indicate that depression causes fatigue or vice versa. Past research31 has suggested that there is little evidence for such a cause-and-effect relationship and that depression and fatigue run different temporal courses in cancer patients. This issue of what role depression plays is important because such patients might have different reasons for not communicating (i.e., are more fatalistic). Third, it was of interest to explore whether an urban versus rural location created any differences in fatigue communication. Although research has shown that geographical location was unlikely to effect cancer mortality rates,32 differences between these locations do exist. Specifically, rural patients are more likely to be unstaged at diagnosis and to have more advanced disease when diagnosed, compared to urban patients.33,34 Further, a recent survey found that rural patients had lower expectations about health care and had to overcome more obstacles before reaching the care of a specialist.35 In addition, it might be expected that stoicism would play a larger role for the rural patient, again leading to potential differences in style of communication and therefore different potential barriers to discussing fatigue.
Methods Procedures Two hundred subjects were recruited from 31 (28 rural and 3 urban) sites across the Com-
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munity Cancer Care, Inc. (CCC) network of Indiana. The sample consisted of 100 subjects from urban sites (metropolitan Indianapolis and Kokomo) and 100 subjects from rural areas in Indiana. All subjects were over 18 years of age, being treated with chemotherapy for malignancy, could read and write English, and had no cognitive limitations to keep them from offering full informed consent. All patients enrolled in the study were experiencing treatment-related fatigue.
Measures Demographics. A standard demographic questionnaire was employed in the study to obtain data on age, sex, race, marital status, educational level, and disease and treatment-related variables. Fatigue Management Barriers Questionnaire (FMBQ). The FMBQ is a 28-item self-report instrument devised by experts in the field of cancerrelated fatigue (Appendix A). The FMBQ assesses the extent to which patients have concerns that are thought to be barriers to fatigue management. This instrument was initially modeled after the Barriers Questionnaire regarding patient-related concerns in pain management25 and is also in line with guidelines issued by the National Collaborating Cancer Network in the United States.36 Experts in fatigue assessment and management examined the pain-related items and modified relevant items to reflect fatigue. Additional items pertinent to fatigue were added based on focused interviews conducted with patients and their spouses. Ten sets of concerns were proposed and a minimum of two items were written to reflect each of these concerns (i.e., treatment futility, fear of disease progression, desire to be a “good patient,” fear of distracting the doctor from primary cancer treatment, lack of concern over fatigue as a symptom, fear of stigma, desire to limit medications, preference for nonmedication interventions, fear of jeopardizing cancer treatment, and lack of physicianinitiated communication). Once an initial list of items was constructed, the FMBQ was reviewed in another series of focus interviews with patients in which items were clarified, deleted, or added based on input from people with cancer. Subjects rated the extent to which
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they agreed with each of the items on a 5-point Likert scale, ranging from 1 (strongly disagree) to 5 (strongly agree). Higher scores are indicative of a higher presence of perceived barriers. Zung Self-Rating Depression Scale (ZSDS). The Zung Self-Rating Depression Scale (ZSDS)37,38 is a 20-item self-report measure of the symptoms of depression. It was included to understand the extent to which a depressed subject’s endorsement of barriers differed from that of a non-depressed subject and for construct validation. Subjects rate each item regarding how they felt during the preceding week using a 4-point Likert scale, with 4 representing the most unfavorable response. The sum of the 20 items, after correcting for the 10 items that are reverse-scored, produces a raw score that is converted into a depression score (termed the “SDS” index). These index scores are then categorized into 4 levels to offer a global clinical impression: 1—within normal range, no significant psychopathology (SDS Index: below 50); 2—presence of minimal-to-mild depression (SDS Index: 50-59); 3—presence of moderate-to-marked depression (SDS Index: 60-69); and 4—presence of severe-to-extreme depression (SDS Index: 70 and above). Scores are not meant to offer strict diagnostic guidelines but rather to denote levels of depressive symptomatology that may be of clinical significance. Overall, the ZSDS has been shown to be relatively valid and to have high internal consistency, exhibiting an alpha coefficient of 0.84.39,40 The Brief Zung Self-Rating Depression Scale (BZSDS) is an 11-item version of the ZSDS that omits 9 items concerning somatic symptoms. This abbreviated version was designed to maximize the diagnostic reliance on cognitive symptoms of depression (e.g., anhedonia, dysphoria, concentration, hopelessness), while eliminating somatic symptoms that often are confounded by cancer and its treatment (e.g., fatigue, appetite changes, and insomnia). The Brief Zung was found to yield an acceptable internal consistency (r 0.84) and is strongly correlated with the full Zung (r 0.92).39 Functional Assessment of Cancer Therapy—Fatigue (FACT-F). The Functional Assessment of Cancer Therapy—Fatigue (FACT-F) is a 40-item self-administered questionnaire focusing on the quality of life domains of physical, social
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and family, emotional, and functional wellbeing, as well as overall fatigue. Items are rated on a 5-point Likert scale, from 0 (not at all) to 4 (very much) for how true each statement has been for the patient in the past seven days. After accounting for reverse-scored items, questions are summed across the subscales as well as added for a total score, with higher scores indicative of greater overall quality of life. The instrument has acceptable levels of reliability and validity.41,42 The measure has been shown to yield adequate to high internal consistency, exhibiting coefficient alphas ranging from 0.63–0.86 on the subscales and 0.90–0.95 for the total scale.43,44 The scale has also shown high test– retest reliability (r 0.87).45 Currently in the fourth version, the measure has been deemed appropriate for use with all cancer patients. Fatigue Intervention Checklist. A checklist of medical, psychological, and complementary interventions was compiled by the experts in fatigue (Appendix B). Subjects were asked to indicate recommendations they had received from their care team regarding the management of fatigue. In addition, subjects were asked how many of these interventions they actually employed. Energy conservation strategies, nutritional interventions, stress management techniques, and medical interventions were all included on the list. The total number is summed for the purpose of analysis. Cancer Behavior Inventory (CBI-B). The Cancer Behavior Inventory—Brief (CBI-B) is a 12-item shortened version of the 43-item Cancer Behavior Inventory—Long. Items reflect activities and attitudes that a person with high self-efficacy might display while receiving treatment for cancer and are rated on a 9-point Likert scale ranging from 1 (not at all confident) to 9 (totally confident). The CBI-B is designed to have the 12 items summed to generate a total score. The scale has been shown to be reliable (Cronbach’s alpha 0.96).46 The CBI-B was included for the purpose of construct validation (i.e., to examine the extent to which expected relationships exist between self-efficacy and communication).
Statistical Analyses An a priori power analysis was conducted to determine the number of subjects needed for
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the study.47 For the correlational analyses, assuming a medium effect size (population r .30, tested against a constant of 0.00), an alpha level of 0.05 (two-tailed), and power of 0.84, 90 subjects were needed per group. A series of descriptive statistics, Pearson correlations, and reliability analyses were calculated. Frequencies were calculated for the FMBQ items for the entire sample as well as for the urban and rural subsamples. In addition, reliability analyses were conducted for the FMBQ total scale as well as for the ten concerns within the instrument. A series of one-way analyses of variance (ANOVAs) were also conducted to examine differences between the rural and urban subsamples. Correlations were determined for the self-report instruments that were administered.
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the sample, with 15 (15%) having Stage I disease, 18 (18%) with Stage II, 28 (28%) with Stage III, and 39 (39%) reporting Stage IV disease. Of those reporting disease state, 128 (84.2%) had active disease and 24 (15.8%) had stable disease. There were no statistically significant correlations between the demographic variables and any of the assessment instruments. In addition, a series of one-way ANOVAs showed no differences among the FACT-F, ZSDS, BZSDS, CBI-B, or FMBQ based on whether the patient was in a rural or urban site. Participants displayed considerable variation in their scores across measures. The FACT-F had a mean of 102.65 and standard deviation of 24.90. Both the ZSDS (mean 39.41, SD 7.88) and the BZSDS (mean 22.59, SD 5.14) had good variation. The CBI-B had a mean of 64.90 and a standard deviation of 12.56. Finally, the FMBQ had a mean of 69.42 and standard deviation of 14.07. As it is a novel scale, a reliability analysis on the total scale FMBQ as well as the 10 hypothesized concerns was conducted (Table 1). The total scale exhibited acceptable internal consistency ( 0.88). Of the ten groups of concerns, only the “Good Patient” group ( 0.56) would have been improved by deleting an item ( 0.69). The coefficient alphas for the groupings ranged from a high of 0.77 for ‘Fear of Distracting Doctor’ to a low of 0.34 for ‘Preference of Non-Medication Interventions.’ No differences for patients at either rural or urban sites were found with regard to the ten groups of concerns of the FMBQ using one-way ANOVA. Table 2 shows the frequencies of responses for the 28 items on the FMBQ. Substantial vari-
Results The average age of the sample was 59.6 years (SD 13.62). There were 114 women (57%) and 86 men (43%). The majority (41%, n 82) had a high school education, followed by those with some college (18%, n 36) or some high school (16%, n 16). The vast majority were married (69.5%, n 139) and the sample was predominantly white (89%, n 178). The most common employment status was retired (37%, n 74), followed by disabled (23%, n 46), or currently working full time (15.5%, n 31). The type of tumor varied, with lung (23%, n 45), breast (19.9%, n 39), and colon (13.8%, n 27) cancer most common, followed by lymphoma (10.2%, n 20). Stage of disease was only known by half
Table 1 Reliability Analysis of the Ten Hypothesized Factors in the FMBQ Factor Name Total scale Treatment futility Fear of disease progression “Good patient” Fear of distracting doctor Lack of concern Fear of stigma General medication concerns Preference of non-medication interventions Fear of jeopardizing cancer treatment Lack of communication aCould
be improved to 0.69 if item 12 were deleted.
Items
Alpha
Mean
SD
1–28 5, 11, 14, 24 4, 28 10, 12, 18, 25 22, 27 2, 9, 15, 19 8, 17 6, 7, 23, 26 3, 16 1, 21 13, 20
0.88 0.65 0.73 0.56a 0.77 0.71 0.63 0.65 0.34 0.37 0.63
70.44 9.95 4.45 9.08 5.32 10.42 4.61 10.20 6.51 3.80 5.53
13.63 2.52 1.60 2.50 1.90 3.15 1.66 2.82 1.75 1.26 1.94
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Table 2 FMBQ Results for the Total Sample FMBQ Items (n 200) 1. If I complain about fatigue, my doctor will think I am too weak to receive more treatment. 2. It is unnecessary to treat my fatigue because it will go away on its own. 3. I prefer to treat my fatigue without taking medicines. 4. Having fatigue means that my illness is worse. 5. There is nothing that can be done about my fatigue. 6. If I take medicine to treat fatigue now, it might not work when I really need it. 7. I am afraid that treatment for fatigue will cause problems with my other medicines. 8. I don’t talk about fatigue because people will think I am depressed. 9. Compared to the other problems I have, fatigue is not worth my attention. 10. I try not to complain to my doctor 11. My doctor is not an expert in treating fatigue. 12. I am treating my fatigue with a remedy that my doctor might disapprove of. 13. My doctor does not ask me about fatigue. 14. I don’t know of any effective treatment for fatigue. 15. My fatigue is an expected side effect of my treatment or disease so it is not necessary to treat it. 16. In general, I try to limit the number of medicines I take. 17. I don’t talk to my doctor about fatigue because I am afraid he/she will want me to take antidepressants or get counseling. 18. I try to be strong by not complaining about fatigue to my doctor. 19. Fatigue doesn’t bother me enough to require treatment. 20. My doctor has not offered me any intervention for fatigue. 21. I am afraid to tell my doctor how fatigued I am because then my doctor won’t want to continue treatment for my illness. 22. Doctors need to focus on my illness and not worry about my fatigue. 23. I am concerned about the side effects of medicines that might be given to me to treat my fatigue. 24. There is not enough time with my doctors to talk about fatigue. 25. I don’t want to bother my doctor by bringing up fatigue. 26. I am afraid of becoming addicted to medicine for fatigue. 27. It is more important for the doctor to focus on curing illness than to put time into controlling fatigue. 28. Fatigue is a sign that my illness is getting worse.
ation was observed in response to the items for all populations. Response rates of several items on the FMBQ stand out as noteworthy. 43.1% agreed or strongly agreed that they were unaware of any effective treatments for fatigue and 27.6% stated that they did not want to complain to their doctor. In addition, 40.3% of the total sample endorsed the notion that they pre-
Strongly Disagree (%)
Disagree (%)
Neutral (%)
Agree (%)
Strongly Agree (%)
38.5
39.5
16.4
5.1
.5
21.0
41.0
17.4
17.4
3.1
13.3 20.8 16.8 17.9
28.1 53.8 53.8 39.8
18.4 16.8 23.9 29.1
31.6 6.6 3.0 10.2
8.7 2.0 2.5 3.1
16.2
39.1
31.5
10.7
2.5
15.2
50.3
16.2
13.7
4.6
12.7
47.2
19.3
17.3
3.6
15.8 17.4 35.4
39.8 27.7 48.2
16.8 46.2 14.4
24.0 6.2 1.5
3.6 2.6 .5
21.4 5.6 16.8
40.3 22.8 37.6
13.8 28.4 20.8
20.4 37.6 22.3
4.1 5.6 2.5
4.5 19.3
13.1 53.8
15.7 18.3
53.5 6.6
13.1 2.0
15.7
48.7
13.7
19.8
2.0
9.6
29.4
22.3
34.5
4.1
10.2
23.9
19.3
42.6
4.1
26.3
61.6
9.1
2.5
.5
14.1
42.9
22.2
17.2
3.5
7.1
33.5
20.8
34.5
4.1
16.8
64.0
11.2
7.1
1.0
15.7
63.1
10.1
10.6
.5
14.6
52.0
16.7
12.6
4.0
7.6
39.9
23.2
24.2
5.1
15.7
52.0
21.7
8.6
2.0
ferred to treat fatigue without medications. Conversely, 80.8% disagreed or strongly disagreed with the statement that there was not enough time to talk to their doctor and 54.5% disagreed with the statement that fatigue is an expected side effect of cancer treatment. A series of one-way ANOVAs comparing the total rural and urban subsamples on the 28 FMBQ items showed significant differences for items
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18 (“I try to be strong by not complaining about fatigue to my doctor”) (F1,195 5.03, P 0.05) and 21 (“I am afraid to tell my doctor how fatigued I am because then my doctor won’t want to continue treatment for my illness”) (F1,196 6.49, P 0.05), with the urban sample indicating more agreement with the statements. It was also of interest to explore differences among the respondents from the total sample who scored at the extremes of the depression and self-efficacy spectrum. To this end, results were compared between no depression (ZSDS raw score 40) and moderate-to-extreme depression (ZSDS raw score 47). Forty-six percent of the non-depressed group agreed or strongly agreed that they preferred to treat fatigue without medications whereas only 25% of the depressed group responded similarly. Also, 53.1% of the non-depressed group agreed or strongly agreed that their doctor did not offer any interventions for fatigue, whereas only 40.6% of the depressed group responded in a similar fashion. Conversely, only 38.8% of the non-depressed group claimed ignorance regarding effective fatigue treatments, whereas 50% of the depressed group reported that they were unaware of treatments. Results were also compared for the total sample between those in the lowest quartile of
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self-efficacy (CBI-B 57) and those in the highest quartile of self-efficacy (CBI-B 72). Fifty-five percent of the low self-efficacy group reported that they were unaware of effective treatments for fatigue, and 44.3% of the high self-efficacy group reported this lack of knowledge. The high self-efficacy group reported a greater preference (45.9% vs. 34.7% for the low self-efficacy group) for treating fatigue without medications and also agreed slightly more often with the statement that their doctors had not offered interventions for fatigue (45.9% vs. 44.9% for the low self-efficacy group). The associations among the major variables were examined using Pearson’s correlations (Table 3). The FACT-F was correlated with the CBI-B (r 0.56, P 0.001), ZSDS (r 0.66, P 0.001), and the BZSDS (r 0.52, P 0.001). In addition, the CBI-B was significantly correlated with the ZSDS (r 0.50, P 0.001), the BZSDS (r 0.45, P 0.001), and the FMBQ (r 0.20, P 0.01). Finally, the number of recommendations made by the medical staff for combating fatigue was only weakly significantly correlated (r 0.15, P 0.05) with the FMBQ. The 10 FMBQ concerns were also examined using Pearson’s correlations to explore their relationships to the other scales used in the study (Table 4). Due to the quantity of correla-
Table 3 Correlations Among Study Variables
FMBQ FMBQ FACT-F Cancer Behavior Inventory—Brief Zung Self-Rating Depression Scale Brief Zung Rating Depression Scale Number of Recommendations Made
aP bP
0.01. 0.05.
r sig n r sig n r sig n r sig n r sig n r sig n
FACT-F
CBI-B
ZSDS
BZSDS
0.034 0.633 198
0.199a 0.005 198 0.561a 0.000 199
0.015 0.835 193 0.657a 0.000 199 0.502a 0.000 194
0.049 0.494 193 0.522a 0.000 194 0.445a 0.000 194 0.810a 0.000 195
Number of Recs Made
0.146b 0.040 198 0.010 0.886 199 0.076 0.289 199 0.061 0.395 195 0.024 0.741 195
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Table 4 Correlations Between the Ten Concerns of the FMBQ and the Other Study Measures Assessment Measures FMBQ Factor Name Treatment futility r sig n Fear of disease progression r sig n “Good patient” r sig n Fear of distracting doctor r sig n Lack of concern r sig n Fear of stigma r sig n General medication concerns r sig n Preference of non-medication interventions r sig n Fear of jeopardizing cancer treatment r sig n Lack of communication r sig n aP bP
FACT-F
CBI-B
ZSDS
BZSDS
Number of Recs Made
0.189a 0.008 198
0.209a 0.003 198
0.066 0.365 193
0.107 0.139 193
0.154 0.031 198
0.278a 0.000 198
0.306a 0.000 198
0.218a 0.002 193
0.229a 0.001 193
0.145 0.041 198
0.145b 0.041 198
0.215a 0.002 198
0.092 0.201 193
0.068 0.349 193
0.012 0.868 198
0.086 0.229 198
0.032 0.655 198
0.007 0.920 193
0.089 0.218 193
0.079 0.268 198
0.062 0.387 198
0.182 0.011 193
0.114 0.114 193
0.086 0.227 198
0.043 0.547 198
0.179 0.011 198
0.086 0.233 193
0.061 0.399 193
0.040 0.574 198
0.060 0.403 198
0.201a 0.004 198
0.007 0.918 193
0.015 0.840 193
0.133 0.063 198
0.033 0.640 198
0.142 0.049 193
0.136 0.060 193
0.093 0.192 198
0.148 0.040 193
0.134 0.063 193
0.008 0.915 198
0.017 0.813 193
0.003 0.969 193
0.211a 0.003 198
0.271a 0.000 198
0.118 0.098 198
0.088 0.217 198
0.222a 0.002 198
0.029 0.685 198
0.129 0.070 198
0.01. 0.05.
tions run, and to attempt to limit chance associations, only findings at the 0.01 level were considered to be significant. Several of these concerns were significantly related to the other study measures. The treatment futility concern was shown to be correlated to the FACT-F (r 0.19, P 0.01) and the CBI (r 0.21, P 0.01). The fear of disease progression concern was significantly correlated to the ZSDS (r 0.22, P 0.01), FACT-F (r 0.28, P 0.001), and the CBI (r 0.31, P 0.001). The desire to be a “good patient” concern was found to be correlated to the CBI (r 0.22, P 0.01). The lack of concern over fatigue as
a noteworthy symptom was correlated with the FACT-F (r 0.27, P 0.001). The desire to limit medications concern (r 0.20, P 0.01) was only correlated to the CBI. Finally, the fear of jeopardizing cancer treatment concern was related to the CBI (r 0.22, P 0.01). When asked whether or not subjects had spoken to their doctor about fatigue, 68 (34%) responded ‘yes’ while a majority 132 (66%) responded that they had not discussed fatigue with their physician. A series of one-way ANOVAs revealed that there were no significant differences on either the total FMBQ or its ten con-
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cerns based upon whether or not the patient had spoken to their doctor regarding fatigue. In addition, patients were asked to report the number of recommendations that were made to them regarding fatigue. After correcting for outliers (i.e., 14 subjects’ responses were eliminated as they simply went down the list and checked all of the recommendations), the patients reported a mean of 11.63 recommendations (SD 7.55, range 0–25) from medical staff. When examining the FMBQ and its 10 concerns according to the number of recommendations made, a series of one-way ANOVAs revealed that only the lack of communication concern from the FMBQ was associated with the number of recommendations made by the medical staff (F32,165 1.54, P 0.05).
Discussion Fatigue is a highly prevalent, multidimensional problem for cancer patients. It is distressing for the patient, but our clinical experience, as well as the work of others,10 suggests that it is highly treatable through a variety of treatment modalities. However, to treat this symptom, we must first be able to adequately identify fatigue in cancer patients. To accomplish this, it is necessary to understand the barriers to communication about fatigue. With this understanding, we can help patients to better report their experiences. In this study, we attempted to identify the barriers that limited patient communication with their oncologists about fatigue. To this end, the FMBQ was developed and piloted with a large sample of urban and rural cancer patients. The FMBQ exhibited good variability among respondents and was shown to be a reliable measure that may be able to identify barriers towards adequate identification and treatment of fatigue. The two most common barriers endorsed by subjects offer some insight into why patients fail to discuss fatigue with their physicians. The highest level of endorsement (46.7%) among the sample was that interventions for fatigue were not being offered. Interestingly, though, patients reported on the Fatigue Intervention Checklist that 11 recommendations, on average, were given to them. This leads to speculation that the patients may have responded to the Fatigue Intervention Checklist unsystemati-
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cally, either perceiving all recommendations made to them over time to have been orders from their doctors, or failing to properly read the instructions leading to an answering style based upon personal preferences and acknowledgement of word of mouth from other sources, in addition to clinical staff. Alternately, given the instructions on the Fatigue Intervention Checklist, it may be that interventions for fatigue were suggested by members of the team other than physicians. A large number (43.1%) claimed a lack of awareness regarding any possible treatments for fatigue. Thus, it seems that there is reticence on the part of the physician and the patient to discuss fatigue as a symptom of cancer and cancer treatment. Indeed, this is evidenced by the large number (66%, n 132) who stated they had not spoken to their doctor about fatigue when directly questioned by the researcher. This “don’t ask, don’t tell” mindset may be the most straightforward to overcome by screening regularly for fatigue. This can be accomplished simply by using a single-item screen.29 The separation of respondents who scored at the extremes of the depression and self-efficacy spectrum from the sample offer some interesting insights into the beliefs about fatigue. The depressed patients were more likely than their non-depressed counterparts to have heard about potential interventions from their doctors; they wanted medications for the treatment of fatigue, but claimed that they were unaware of any effective treatments. It may be that the depressed group received more global attention because of their depressed mood, but still retained a hopeless outlook even when attention and possible treatment options are offered. Similarly, the low self-efficacy group was more apt than their high self-efficacy counterparts to want medication interventions while also believing that there were no effective fatigue interventions. Surprisingly, few differences were noted between the urban and rural samples. Of the 28 FMBQ items, only item 18 (“I try to be strong by not complaining about fatigue to my doctor”) and item 21 (“I’m afraid to tell doctor how fatigued I am because he won’t continue treatment”) were significantly different based on the rural versus urban split. The urban patients had a mean of 2.60 (SD 1.05) on item
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18 and 2.02 (SD 0.72) on item 21. Rural patients had a mean of 2.27 (SD 1.01) on item 18 and 1.77 (SD 0.66) on item 21. This indicates that urban patients were more likely to agree with these statements, possibly indicating greater stoicism or fear in the urban sample. This study has important implications for patient education. Barriers endorsed regarding fatigue are unlike those in the pain literature in that they are not as universal as patient-related barriers to pain treatment and are more numerous. Even the most commonly endorsed barriers identified herein are not nearly as universal as those seen in pain management. The use of the FMBQ to identify fatalistic attitudes and other barriers might be a reasonable start as we continue to figure out ways to enhance patient reporting of symptoms. This study raises interesting questions that should be explored through further research that does not rely on cross-sectional data alone. It may well turn out that clinicians will experience better patient outcome by making a stronger effort to individualize patient education and tailor measures regarding fatigue definitions based on whether or not the patient is depressed.
Acknowledgments This study was supported by a grant from the Fatigue Coalition and Ortho Biotech Products, L.P. The authors wish to acknowledge the help and support of Dr. Loretta Itri.
References 1. Cella D, Peterman A, Passik SD, et al. Progress toward guidelines for the management of fatigue. Oncology 1998;12:369–377. 2. Curt GA, Breitbart W, Cella D, et al. Impact of cancer-related fatigue on the lives of patients: new findings from the Fatigue Coalition. Oncologist 2000;5:353–360. 3. Glaus A, Crow R, Hammond S. A qualitative study to explore the concept of fatigue/tiredness in cancer patients and in healthy individuals. Support Care Cancer 1996;4:82–96. 4. Vogelzang NJ, Breitbart W, Cella D, et al. Patient, caregiver, and oncologist perceptions of cancer-related fatigue: results of a tripart assessment survey. Semin Hematol 1997;34:4–12. 5. Irvine D, Vincent L, Graydon J, et al. The prevalence and correlates of fatigue in patients receiving treatment with chemotherapy and radiotherapy. A
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comparison with the fatigue experienced by healthy individuals. Cancer Nurs 1994;17:367–378. 6. Richardson A, Ream E. The experience of fatigue and other symptoms in patients receiving chemotherapy. Eur J Cancer Care 1996;5:24–30. 7. Ashbury FD, Findlay H, Reynolds B, McKerracher K. A Canadian survey of cancer patients’ experiences: are their needs being met? J Pain Symptom Manage 1998;16:298–306. 8. Richardson A, Ream E, Wilson-Barnett J. Fatigue in patients receiving chemotherapy: patterns of change. Cancer Nurs 1998;21:17–30. 9. Smets EM, Garssen B, Schuster-Uitterhoeve AL, et al. Fatigue in cancer patients. Br J Cancer 1993; 68:220–224. 10. Portenoy RK, Itri LM. Cancer-related fatigue: guidelines for evaluation and management. Oncologist 1999;4:1–10. 11. Kirk J, Douglass R, Nelson E, et al. Chief complaint of fatigue: a prospective study. J Fam Pract 1990;30:33–39. 12. Cella D. Factors influencing quality of life in cancer patients: anemia and fatigue. Semin Oncol 1998;25:43–46. 13. Pater JL, Zee B, Palmer M, et al. Fatigue in patients with cancer: results with National Cancer Institute of Canada clinical trials group studies employing the EORTC QLQ-30. Support Care Cancer 1997;5:410–413. 14. Yarbro CH. Interventions for fatigue. Eur J Cancer Care 1996;5:35–38. 15. Dimeo FC. Effects of exercise on cancer-related fatigue. Cancer 2001;92:1689–1693. 16. Dimeo FC, Rumberger BG, Keul J. Aerobic exercise as therapy for cancer fatigue. Med Sci Sports Exerc 1998;30:475–478. 17. Dimeo FC, Tilmann MH, Bertz H, et al. Aerobic exercise of cancer patients after high dose chemotherapy and autologous peripheral stem cell transplantation. Cancer 1997;79:1717–1722. 18. MacVicar MG, Winningham ML, Nickel JL. Effects of aerobic interval training on cancer patient’s functional capacity. Nursing Research 1989;38:348– 351. 19. Mock V, Ropka ME, Rhodes VA, et al. Establishing mechanisms to conduct multi-institutional research—fatigue in patients with cancer: and exercise intervention. Oncol Nurs Forum 1998;25:1391–1397. 20. Schwartz AL, Mori M, Gao R, et al. Exercise reduces daily fatigue in women with breast cancer receiving chemotherapy. Med Sci Sports Exercise 2001;33:718–723. 21. Demetri GD, Kris M, Wade J, et al. Quality of life benefit in chemotherapy patients treated with epoetin alfa is independent of disease response or tumor type: results from a prospective community oncology study. J Clin Oncol 1998;16:3412–3425.
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22. Gabrilove J, Einhorn L, Cleeland C, Livingston R, Weiner E, Waltzman RJ. Efficacy of a once-weekly dosage regimen of epoetin alpha in hematologic malignancies. International Society of Hematology 2000 Supplement 1;72:55. 23. Glaspy J. The impact of epoetin alfa on quality of life during cancer chemotherapy: a fresh look at an old problem. Semin Hematol 1997;34:20–26. 24. Glaspy J, Bukowski R, Steinberg D, et al. Impact of therapy with epoetin alfa on chemical outcomes in patients with nonmyeloid malignancies during cancer chemotherapy in community oncology practice. Procrit study group. J Clin Oncol, 1997;15:1218–1234. 25. Ward SE, Goldberg N, Miller-McCauley V, et al. Patient-related barriers to management of cancer pain. Pain 1993;52:319–324. 26. Breitbart W, Passik SD, McDonald MV, et al. Patient-related barriers to pain management in ambulatory AIDS patients. Pain 1998;76:9–16. 27. Valentine AD, Myers CA. Cognitive and mood disturbance as causes and symptoms of fatigue in cancer patients. Cancer 2001;92:1694–1698. 28. Lev EL. Bandura’s theory of self-efficacy: applications to oncology. Schol Inq Nurs Pract 1997;11:21–37. 29. Kirsh KL, Passik SD, Holtsclaw E, et al. I get tired for no reason: a single item screening for cancer-related fatigue. J Pain Symptom Manage 2001;22:931–937. 30. Redeker NS, Lev EL, Ruggiero J. Insomnia, fatigue, anxiety, depression, and quality of life of cancer patients undergoing chemotherapy. Schol Inquiry Nurs Pract, 2000;14:275–290. 31. Visser MR, Smets EM. Fatigue, depression and quality of life in cancer patients: how are they related? Support Care Cancer 1998;6:101–108. 32. Horner RD, Chirikos TN. Survivorship differences in geographical comparisons of cancer mortality: an urban-rural analysis. Int J Epidemiology 1987;16:184–189. 33. Monroe AC, Ricketts TC, Savitz LA. Cancer in rural versus urban populations: a review. J Rural Health 1992;8:212–220. 34. Liff JM, Chow WH, Greenberg RS. Rural-urban differences in stage at diagnosis. Possible relationship to cancer screening. Cancer 1991;67:1454–1459.
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35. Bain NS, Campbell NC. Treating patients with colorectal cancer in rural and urban areas: a qualitative study of the patients’ perspective. Fam Pract 2000;17:475–479. 36. Atkinson A, Barsevick A, Cella D, et al. NCCN practice guidelines for cancer-related fatigue. Oncology 2000;14:151–161. 37. Zung W. Depression in the normal aged. Psychosomatics 1967;7:287–292. 38. Zung W. Factors influencing the self-rating depression scale. Arch Gen Psych 1967;16:543–547. 39. Dugan W, McDonald M, Passik S, et al. Use of the Zung self-rating depression scale in cancer patients: feasibility as a screening tool. Psycho-Oncology 1998;7:483–493. 40. Tate D, Forchheimer M, Maynard F, et al. Comparing two measures of depression in spinal cord injury. Rehab Psychol 1993;38:53–61. 41. Cella D, Tulsky D, Gray G, et al. The Functional Assessment of Cancer Therapy Scale: development and validation. J Clin Oncol 1993;11:570–579. 42. Winstead-Fry P, Schultz A. Psychometric analysis of the Functional Assessment of Cancer TherapyGeneral (FACT-G) scale in a rural sample. Cancer 1997;79:2446–2452. 43. Brady M, Cella D, Mo F, et al. Reliability and Validity of the Functional Assessment of Cancer Therapy Breast Quality of Life Instrument. J Clin Oncol 1997;15:974–986. 44. Cella D, Bonomi A, Lloyd S, et al. Reliability and Validity of the Functional Assessment of Cancer Therapy-Lung (FACT-L) Quality of Life Instrument. Lung Cancer 1995;12:199–220. 45. Yellen S, Cella D, Webster K, et al. Measuring fatigue and other anemia-related symptoms with the Functional Assessment of Cancer Therapy (FACTG) measurement system. J Pain Symptom Manage 1997;13:63–74. 46. Merluzzi T, Sanchez M. Assessment of self-efficacy and coping with cancer: Development and Validation of the Cancer Behavior Inventory. Health Psychology 1997;16:163–170. 47. Cohen J. A power primer. Psych Bull 1992;112: 155–159.
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Appendix A The FMBQ Items FMBQ Items (n 100) 1. If I complain about fatigue, my doctor will think I am too weak to receive more treatment. 2. It is unnecessary to treat my fatigue because it will go away on its own. 3. I prefer to treat my fatigue without taking medicines. 4. Having fatigue means that my illness is worse. 5. There is nothing that can be done about my fatigue. 6. If I take medicine to treat fatigue now, it might not work when I really need it. 7. I am afraid that treatment for fatigue will cause problems with my other medicines. 8. I don’t talk about fatigue because people will think I am depressed. 9. Compared to the other problems I have, fatigue is not worth my attention. 10. I try not to complain to my doctor. 11. My doctor is not an expert in treating fatigue. 12. I am treating my fatigue with a remedy that my doctor might disapprove of. 13. My doctor does not ask me about fatigue. 14. I don’t know of any effective treatment for fatigue. 15. My fatigue is an expected side effect of my treatment or disease so it is not necessary to treat it. 16. In general, I try to limit the number of medicines I take. 17. I don’t talk to my doctor about fatigue because I am afraid he/she will want me to take antidepressants or get counseling. 18. I try to be strong by not complaining about fatigue to my doctor. 19. Fatigue doesn’t bother me enough to require treatment. 20. My doctor has not offered me any interventions for fatigue. 21. I am afraid to tell my doctor how fatigued I am because then my doctor won’t want to continue treatment for my illness. 22. Doctors need to focus on my illness and not worry about my fatigue. 23. I am concerned about the side effects of medicines that might be given to me to treat my fatigue. 24. There is not enough time with my doctor to talk about fatigue. 25. I don’t want to bother my doctor by bringing up fatigue. 26. I am afraid of becoming addicted to medicine for fatigue. 27. It is more important for the doctor to focus on curing illness than to put time into controlling fatigue. 28. Fatigue is a sign that my illness is getting worse.
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Appendix B Fatigue Intervention Checklist Please review the following list and indicate whether or not any of these recommendations were given to you by the doctors, nurses and/or other staff (i.e., social workers) in your clinic: A. Energy conservation strategies: 1. You should ask for help with chores such as cleaning or grocery shopping 2. Only do the things that are most important 3. Rest when feeling fatigued 4. Schedule periods of rest in between activities 5. Realistically plan daily activities 6. Maintain normal sleep patterns 7. Vary daily activities to prevent boredom
Y/N Y/N Y/N Y/N Y/N Y/N Y/N
B. Nutritional management strategies: 1. Eat small meals or snacks several times throughout the day 2. Drink plenty of water each day 3. Prepare extra meals and store them in the refrigerator on days you feel well 4. Ask for help when cooking and grocery shopping 5. Adjust your diet to insure adequate intake of calories 6. Consult with a dietitian to insure that you are eating a nutritionally balanced diet 7. Maintain a nutritionally complete diet that emphasizes complex carbohydrates
Y/N Y/N Y/N Y/N Y/N Y/N Y/N
C. Stress management strategies: 1. Be aware of potential causes of fatigue 2. Participate in activities you enjoy 3. Keep busy (e.g., listen to music, watch TV, read a book) instead of concentrating on tiredness, disease or treatment 4. Focus on the positive and participate in those activities you are able to complete 5. Join a support group and share feelings with others who have similar experiences 6. Your doctor or nurse put you in touch with other patients who have had the same experiences 7. Practice relaxation, hypnosis, or medication techniques
Y/N Y/N Y/N Y/N Y/N Y/N Y/N
D. Medical interventions: 1. Consider transfusion 2. Consider using erythropoetin (Procrit), if prescribed 3. Consider using stimulants, if prescribed 4. Consider using antidepressants, if prescribed 5. Consider using steroids, if prescribed 6. Consider using thyroid hormone, if prescribed
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E. Strategies to regulate daily activity and rest patterns: 1. Keep a diary of your energy levels at different times of the day 2. Plan activities for the times you feel best 3. Take several short naps throughout the day rather than one long nap 4. Try to exercise lightly or take a short walk 5. Focus on doing those activities that are important to you 6. Delegate activities that can be done by someone else
Y/N Y/N Y/N Y/N Y/N Y/N
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Original Article
Patient-Related Barriers to Fatigue Communication: Initial Validation of the Fatigue Management Barriers Questionnaire Steven D. Passik, PhD,* Kenneth L. Kirsh, PhD, Kathleen Donaghy, PhD, Elizabeth Holtsclaw, BA, Dale Theobald, MD, PhD, David Cella, PhD, and William Breitbart, MD, for the Fatigue Coalition Symptom Management and Palliative Care Program (S.D.P., K.L.K.), Markey Cancer Center, University of Kentucky, Lexington, Kentucky; Oncology Symptom Control & Research (K.D., E.H., D.T.), Community Cancer Care, Indianapolis, Indiana; Institute for Health Services Research and Policy Studies (D.C.), Northwestern University, Evanston, Illinois; and Psychiatry Service (W.B.), Memorial Sloan-Kettering Cancer Center, New York, New York, USA
Abstract Fatigue is a highly prevalent and distressing symptom of cancer and its treatment. However, cancer patients often fail to communicate with their oncologists about fatigue. In this study, we attempted to identify the patient-related barriers to communication about fatigue, as cited by patients. Two hundred patients were sampled across the Community Cancer Care, Inc. (CCC) network of Indiana using the Cancer Behavior Inventory-Brief scale (CBI-B), the Zung Self-Rating Depression Scale (ZSDS), the Functional Assessment of Cancer Inventory-Fatigue scale (FACT-F), and the Fatigue Management Barriers Questionnaire (FMBQ), a questionnaire devised by experts in the field of cancer-related fatigue. There were no significant correlations between the instrument scores and demographic variables. Scores on the instruments did not differ significantly based on whether the patient was from a rural or urban site. One hundred thirty-two patients (66%) reported that they had never spoken to their doctor about fatigue. The most frequently reported reasons for this lack of patient communication about fatigue included the doctor’s failure to offer interventions (47%), patients’ lack of awareness of effective treatments for fatigue (43%), a desire on the patient’s part to treat fatigue without medications (40%), and not wanting to complain to the doctor (28%). Patients reported that medical staff offered a mean of 11.63 recommendations for dealing with fatigue. The FMBQ was found to correlate significantly with self-efficacy (CBI-B, r 0.20, P 0.01) and correlate weakly with the number of recommendations made (r 0.15, P 0.05). The FMBQ was noted to have acceptable internal consistency ( 0.88) and validity and may prove to be a useful instrument for understanding why
*Address reprint requests to: Steven D. Passik, PhD, Symptom Management and Palliative Care, University of Kentucky, Markey Cancer Center — cc 449, 800 Rose Street, Lexington KY 40536, USA. Accepted for publication: January 19, 2002. © U.S. Cancer Pain Relief Committee, 2002 Published by Elsevier, New York, New York
0885-3924/02/$–see front matter PII S0885-3924(02)00518-3
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patients do not communicate about fatigue. Multiple barriers contribute to why cancer patients do not comment about fatigue but may be overcome if physicians screen and assess for this symptom. J Pain Symptom Manage 2002;24:481–493. © U.S. Cancer Pain Relief Committee. 2002 Key Words Fatigue, cancer, communication
Introduction Fatigue is the most common symptom reported by cancer patients.1–4 Past studies report prevalence rates ranging from 61%–90% for fatigue in various oncology samples.4–6 Cancer-related fatigue (CRF) is associated with significant impairment. A recent study by Ashbury and colleagues7 found that cancer patients with CRF were more likely to have impairment in performing normal daily activities and to more frequently use health care services than their non-fatigued counterparts. To date, the mechanisms of CRF are not fully understood, nor is there consensus on how to best identify clinically relevant fatigue.8 Perhaps the best way to characterize fatigue is to view it as a multidimensional problem involving chronic exhaustion and diminished capacity for physical activity that is not alleviated by rest.1,9 This is not to say that fatigue is solely a physical entity, however. The etiology may be physical, psychological, or pathological.1,10,11 In addition, fatigue level may be influenced by a variety of factors including cancer treatment, changes in sleeping patterns, symptom distress, mood disturbance, low hemoglobin levels, or poor performance status.5,6,12,13 In a recent survey of nearly 200 oncologists,4 80% reported that fatigue is either neglected or undertreated in cancer patients. This survey also queried patients and found that most (74%) believed fatigue to be an untreatable symptom that one had to endure as a normal part of cancer and its accompanying treatment. This perception contrasts with the reality of many potential treatments to combat fatigue. For instance, self-care activities and education for the patient and family can be useful.14 Several recent studies15–20 have shown that aerobic exercise can help to improve the physical performance of cancer patients. Recombinant human erythropoietin (r-HuEPO, epoetin alfa) has been shown to increase he-
moglobin levels and to subsequently reduce fatigue in cancer patients.21–24 Epoetin alfa improved patients’ perceived energy levels, functional status, and overall quality of life. Patient-related barriers to communicating about fatigue have not been well studied, but barriers that might be similar have been described in cancer pain25 and AIDS pain.26 Ward and colleagues25 found that patient concerns were fairly universal with regard to treatment of cancer pain. Fears of addiction, tolerance, side effects, and distracting physicians were reported as barriers by over 70% of patients. Endorsement of these barriers was related to the undermedication of the patient’s pain. Breitbart and colleagues26 reported similar findings with regard to barriers endorsed by patients with AIDS. In addition, these investigations added concerns specific to AIDS patients. They observed that patients often showed a preference for “natural” or alternative interventions and a desire to limit their overall use of medications. The present study is modeled after these prior efforts and was intended to understand specific barriers to fatigue communication commonly endorsed by cancer patients. When better understood, knowledge of the prominent barriers can lead to tailored educational efforts to facilitate such communication. As prior research suggests27 successful interventions for fatigue should be patient-specific. While no true a priori hypotheses were postulated for this initial instrument validation study, several areas of potential interest were defined for exploration. First, it was of interest to explore the relationship between self-efficacy and communication about fatigue, as cited by patients. Because the novel scale introduced here is concerned with identifying barriers to communication about fatigue, it is important to explore whether individual levels of self-efficacy have an impact on this construct. It has been sug-
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gested that increased levels of self-efficacy are associated with greater levels of treatment adherence and increased self-care behavior.28 For this reason, self-efficacy is an important area to consider. It may well be that patients with higher levels of self-efficacy are more apt to communicate or endorse different barriers compared to patients with low self-efficacy. Ultimately, this could lead to a more tailored approach to the treatment of fatigue. Second, there is a likely relationship between depression and fatigue that needs to be addressed in any attempt to explore fatigue communication. In fact, our recent work29 has shown that a single-item taken from a depression scale can be utilized as a triage-like screen for more detailed follow-up for cancer-related fatigue, indicating some level of overlap. Indeed, some researchers30 have shown significant correlations between fatigue and depression. However, this is not to indicate that depression causes fatigue or vice versa. Past research31 has suggested that there is little evidence for such a cause-and-effect relationship and that depression and fatigue run different temporal courses in cancer patients. This issue of what role depression plays is important because such patients might have different reasons for not communicating (i.e., are more fatalistic). Third, it was of interest to explore whether an urban versus rural location created any differences in fatigue communication. Although research has shown that geographical location was unlikely to effect cancer mortality rates,32 differences between these locations do exist. Specifically, rural patients are more likely to be unstaged at diagnosis and to have more advanced disease when diagnosed, compared to urban patients.33,34 Further, a recent survey found that rural patients had lower expectations about health care and had to overcome more obstacles before reaching the care of a specialist.35 In addition, it might be expected that stoicism would play a larger role for the rural patient, again leading to potential differences in style of communication and therefore different potential barriers to discussing fatigue.
Methods Procedures Two hundred subjects were recruited from 31 (28 rural and 3 urban) sites across the Com-
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munity Cancer Care, Inc. (CCC) network of Indiana. The sample consisted of 100 subjects from urban sites (metropolitan Indianapolis and Kokomo) and 100 subjects from rural areas in Indiana. All subjects were over 18 years of age, being treated with chemotherapy for malignancy, could read and write English, and had no cognitive limitations to keep them from offering full informed consent. All patients enrolled in the study were experiencing treatment-related fatigue.
Measures Demographics. A standard demographic questionnaire was employed in the study to obtain data on age, sex, race, marital status, educational level, and disease and treatment-related variables. Fatigue Management Barriers Questionnaire (FMBQ). The FMBQ is a 28-item self-report instrument devised by experts in the field of cancerrelated fatigue (Appendix A). The FMBQ assesses the extent to which patients have concerns that are thought to be barriers to fatigue management. This instrument was initially modeled after the Barriers Questionnaire regarding patient-related concerns in pain management25 and is also in line with guidelines issued by the National Collaborating Cancer Network in the United States.36 Experts in fatigue assessment and management examined the pain-related items and modified relevant items to reflect fatigue. Additional items pertinent to fatigue were added based on focused interviews conducted with patients and their spouses. Ten sets of concerns were proposed and a minimum of two items were written to reflect each of these concerns (i.e., treatment futility, fear of disease progression, desire to be a “good patient,” fear of distracting the doctor from primary cancer treatment, lack of concern over fatigue as a symptom, fear of stigma, desire to limit medications, preference for nonmedication interventions, fear of jeopardizing cancer treatment, and lack of physicianinitiated communication). Once an initial list of items was constructed, the FMBQ was reviewed in another series of focus interviews with patients in which items were clarified, deleted, or added based on input from people with cancer. Subjects rated the extent to which
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they agreed with each of the items on a 5-point Likert scale, ranging from 1 (strongly disagree) to 5 (strongly agree). Higher scores are indicative of a higher presence of perceived barriers. Zung Self-Rating Depression Scale (ZSDS). The Zung Self-Rating Depression Scale (ZSDS)37,38 is a 20-item self-report measure of the symptoms of depression. It was included to understand the extent to which a depressed subject’s endorsement of barriers differed from that of a non-depressed subject and for construct validation. Subjects rate each item regarding how they felt during the preceding week using a 4-point Likert scale, with 4 representing the most unfavorable response. The sum of the 20 items, after correcting for the 10 items that are reverse-scored, produces a raw score that is converted into a depression score (termed the “SDS” index). These index scores are then categorized into 4 levels to offer a global clinical impression: 1—within normal range, no significant psychopathology (SDS Index: below 50); 2—presence of minimal-to-mild depression (SDS Index: 50-59); 3—presence of moderate-to-marked depression (SDS Index: 60-69); and 4—presence of severe-to-extreme depression (SDS Index: 70 and above). Scores are not meant to offer strict diagnostic guidelines but rather to denote levels of depressive symptomatology that may be of clinical significance. Overall, the ZSDS has been shown to be relatively valid and to have high internal consistency, exhibiting an alpha coefficient of 0.84.39,40 The Brief Zung Self-Rating Depression Scale (BZSDS) is an 11-item version of the ZSDS that omits 9 items concerning somatic symptoms. This abbreviated version was designed to maximize the diagnostic reliance on cognitive symptoms of depression (e.g., anhedonia, dysphoria, concentration, hopelessness), while eliminating somatic symptoms that often are confounded by cancer and its treatment (e.g., fatigue, appetite changes, and insomnia). The Brief Zung was found to yield an acceptable internal consistency (r 0.84) and is strongly correlated with the full Zung (r 0.92).39 Functional Assessment of Cancer Therapy—Fatigue (FACT-F). The Functional Assessment of Cancer Therapy—Fatigue (FACT-F) is a 40-item self-administered questionnaire focusing on the quality of life domains of physical, social
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and family, emotional, and functional wellbeing, as well as overall fatigue. Items are rated on a 5-point Likert scale, from 0 (not at all) to 4 (very much) for how true each statement has been for the patient in the past seven days. After accounting for reverse-scored items, questions are summed across the subscales as well as added for a total score, with higher scores indicative of greater overall quality of life. The instrument has acceptable levels of reliability and validity.41,42 The measure has been shown to yield adequate to high internal consistency, exhibiting coefficient alphas ranging from 0.63–0.86 on the subscales and 0.90–0.95 for the total scale.43,44 The scale has also shown high test– retest reliability (r 0.87).45 Currently in the fourth version, the measure has been deemed appropriate for use with all cancer patients. Fatigue Intervention Checklist. A checklist of medical, psychological, and complementary interventions was compiled by the experts in fatigue (Appendix B). Subjects were asked to indicate recommendations they had received from their care team regarding the management of fatigue. In addition, subjects were asked how many of these interventions they actually employed. Energy conservation strategies, nutritional interventions, stress management techniques, and medical interventions were all included on the list. The total number is summed for the purpose of analysis. Cancer Behavior Inventory (CBI-B). The Cancer Behavior Inventory—Brief (CBI-B) is a 12-item shortened version of the 43-item Cancer Behavior Inventory—Long. Items reflect activities and attitudes that a person with high self-efficacy might display while receiving treatment for cancer and are rated on a 9-point Likert scale ranging from 1 (not at all confident) to 9 (totally confident). The CBI-B is designed to have the 12 items summed to generate a total score. The scale has been shown to be reliable (Cronbach’s alpha 0.96).46 The CBI-B was included for the purpose of construct validation (i.e., to examine the extent to which expected relationships exist between self-efficacy and communication).
Statistical Analyses An a priori power analysis was conducted to determine the number of subjects needed for
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the study.47 For the correlational analyses, assuming a medium effect size (population r .30, tested against a constant of 0.00), an alpha level of 0.05 (two-tailed), and power of 0.84, 90 subjects were needed per group. A series of descriptive statistics, Pearson correlations, and reliability analyses were calculated. Frequencies were calculated for the FMBQ items for the entire sample as well as for the urban and rural subsamples. In addition, reliability analyses were conducted for the FMBQ total scale as well as for the ten concerns within the instrument. A series of one-way analyses of variance (ANOVAs) were also conducted to examine differences between the rural and urban subsamples. Correlations were determined for the self-report instruments that were administered.
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the sample, with 15 (15%) having Stage I disease, 18 (18%) with Stage II, 28 (28%) with Stage III, and 39 (39%) reporting Stage IV disease. Of those reporting disease state, 128 (84.2%) had active disease and 24 (15.8%) had stable disease. There were no statistically significant correlations between the demographic variables and any of the assessment instruments. In addition, a series of one-way ANOVAs showed no differences among the FACT-F, ZSDS, BZSDS, CBI-B, or FMBQ based on whether the patient was in a rural or urban site. Participants displayed considerable variation in their scores across measures. The FACT-F had a mean of 102.65 and standard deviation of 24.90. Both the ZSDS (mean 39.41, SD 7.88) and the BZSDS (mean 22.59, SD 5.14) had good variation. The CBI-B had a mean of 64.90 and a standard deviation of 12.56. Finally, the FMBQ had a mean of 69.42 and standard deviation of 14.07. As it is a novel scale, a reliability analysis on the total scale FMBQ as well as the 10 hypothesized concerns was conducted (Table 1). The total scale exhibited acceptable internal consistency ( 0.88). Of the ten groups of concerns, only the “Good Patient” group ( 0.56) would have been improved by deleting an item ( 0.69). The coefficient alphas for the groupings ranged from a high of 0.77 for ‘Fear of Distracting Doctor’ to a low of 0.34 for ‘Preference of Non-Medication Interventions.’ No differences for patients at either rural or urban sites were found with regard to the ten groups of concerns of the FMBQ using one-way ANOVA. Table 2 shows the frequencies of responses for the 28 items on the FMBQ. Substantial vari-
Results The average age of the sample was 59.6 years (SD 13.62). There were 114 women (57%) and 86 men (43%). The majority (41%, n 82) had a high school education, followed by those with some college (18%, n 36) or some high school (16%, n 16). The vast majority were married (69.5%, n 139) and the sample was predominantly white (89%, n 178). The most common employment status was retired (37%, n 74), followed by disabled (23%, n 46), or currently working full time (15.5%, n 31). The type of tumor varied, with lung (23%, n 45), breast (19.9%, n 39), and colon (13.8%, n 27) cancer most common, followed by lymphoma (10.2%, n 20). Stage of disease was only known by half
Table 1 Reliability Analysis of the Ten Hypothesized Factors in the FMBQ Factor Name Total scale Treatment futility Fear of disease progression “Good patient” Fear of distracting doctor Lack of concern Fear of stigma General medication concerns Preference of non-medication interventions Fear of jeopardizing cancer treatment Lack of communication aCould
be improved to 0.69 if item 12 were deleted.
Items
Alpha
Mean
SD
1–28 5, 11, 14, 24 4, 28 10, 12, 18, 25 22, 27 2, 9, 15, 19 8, 17 6, 7, 23, 26 3, 16 1, 21 13, 20
0.88 0.65 0.73 0.56a 0.77 0.71 0.63 0.65 0.34 0.37 0.63
70.44 9.95 4.45 9.08 5.32 10.42 4.61 10.20 6.51 3.80 5.53
13.63 2.52 1.60 2.50 1.90 3.15 1.66 2.82 1.75 1.26 1.94
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Table 2 FMBQ Results for the Total Sample FMBQ Items (n 200) 1. If I complain about fatigue, my doctor will think I am too weak to receive more treatment. 2. It is unnecessary to treat my fatigue because it will go away on its own. 3. I prefer to treat my fatigue without taking medicines. 4. Having fatigue means that my illness is worse. 5. There is nothing that can be done about my fatigue. 6. If I take medicine to treat fatigue now, it might not work when I really need it. 7. I am afraid that treatment for fatigue will cause problems with my other medicines. 8. I don’t talk about fatigue because people will think I am depressed. 9. Compared to the other problems I have, fatigue is not worth my attention. 10. I try not to complain to my doctor 11. My doctor is not an expert in treating fatigue. 12. I am treating my fatigue with a remedy that my doctor might disapprove of. 13. My doctor does not ask me about fatigue. 14. I don’t know of any effective treatment for fatigue. 15. My fatigue is an expected side effect of my treatment or disease so it is not necessary to treat it. 16. In general, I try to limit the number of medicines I take. 17. I don’t talk to my doctor about fatigue because I am afraid he/she will want me to take antidepressants or get counseling. 18. I try to be strong by not complaining about fatigue to my doctor. 19. Fatigue doesn’t bother me enough to require treatment. 20. My doctor has not offered me any intervention for fatigue. 21. I am afraid to tell my doctor how fatigued I am because then my doctor won’t want to continue treatment for my illness. 22. Doctors need to focus on my illness and not worry about my fatigue. 23. I am concerned about the side effects of medicines that might be given to me to treat my fatigue. 24. There is not enough time with my doctors to talk about fatigue. 25. I don’t want to bother my doctor by bringing up fatigue. 26. I am afraid of becoming addicted to medicine for fatigue. 27. It is more important for the doctor to focus on curing illness than to put time into controlling fatigue. 28. Fatigue is a sign that my illness is getting worse.
ation was observed in response to the items for all populations. Response rates of several items on the FMBQ stand out as noteworthy. 43.1% agreed or strongly agreed that they were unaware of any effective treatments for fatigue and 27.6% stated that they did not want to complain to their doctor. In addition, 40.3% of the total sample endorsed the notion that they pre-
Strongly Disagree (%)
Disagree (%)
Neutral (%)
Agree (%)
Strongly Agree (%)
38.5
39.5
16.4
5.1
.5
21.0
41.0
17.4
17.4
3.1
13.3 20.8 16.8 17.9
28.1 53.8 53.8 39.8
18.4 16.8 23.9 29.1
31.6 6.6 3.0 10.2
8.7 2.0 2.5 3.1
16.2
39.1
31.5
10.7
2.5
15.2
50.3
16.2
13.7
4.6
12.7
47.2
19.3
17.3
3.6
15.8 17.4 35.4
39.8 27.7 48.2
16.8 46.2 14.4
24.0 6.2 1.5
3.6 2.6 .5
21.4 5.6 16.8
40.3 22.8 37.6
13.8 28.4 20.8
20.4 37.6 22.3
4.1 5.6 2.5
4.5 19.3
13.1 53.8
15.7 18.3
53.5 6.6
13.1 2.0
15.7
48.7
13.7
19.8
2.0
9.6
29.4
22.3
34.5
4.1
10.2
23.9
19.3
42.6
4.1
26.3
61.6
9.1
2.5
.5
14.1
42.9
22.2
17.2
3.5
7.1
33.5
20.8
34.5
4.1
16.8
64.0
11.2
7.1
1.0
15.7
63.1
10.1
10.6
.5
14.6
52.0
16.7
12.6
4.0
7.6
39.9
23.2
24.2
5.1
15.7
52.0
21.7
8.6
2.0
ferred to treat fatigue without medications. Conversely, 80.8% disagreed or strongly disagreed with the statement that there was not enough time to talk to their doctor and 54.5% disagreed with the statement that fatigue is an expected side effect of cancer treatment. A series of one-way ANOVAs comparing the total rural and urban subsamples on the 28 FMBQ items showed significant differences for items
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18 (“I try to be strong by not complaining about fatigue to my doctor”) (F1,195 5.03, P 0.05) and 21 (“I am afraid to tell my doctor how fatigued I am because then my doctor won’t want to continue treatment for my illness”) (F1,196 6.49, P 0.05), with the urban sample indicating more agreement with the statements. It was also of interest to explore differences among the respondents from the total sample who scored at the extremes of the depression and self-efficacy spectrum. To this end, results were compared between no depression (ZSDS raw score 40) and moderate-to-extreme depression (ZSDS raw score 47). Forty-six percent of the non-depressed group agreed or strongly agreed that they preferred to treat fatigue without medications whereas only 25% of the depressed group responded similarly. Also, 53.1% of the non-depressed group agreed or strongly agreed that their doctor did not offer any interventions for fatigue, whereas only 40.6% of the depressed group responded in a similar fashion. Conversely, only 38.8% of the non-depressed group claimed ignorance regarding effective fatigue treatments, whereas 50% of the depressed group reported that they were unaware of treatments. Results were also compared for the total sample between those in the lowest quartile of
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self-efficacy (CBI-B 57) and those in the highest quartile of self-efficacy (CBI-B 72). Fifty-five percent of the low self-efficacy group reported that they were unaware of effective treatments for fatigue, and 44.3% of the high self-efficacy group reported this lack of knowledge. The high self-efficacy group reported a greater preference (45.9% vs. 34.7% for the low self-efficacy group) for treating fatigue without medications and also agreed slightly more often with the statement that their doctors had not offered interventions for fatigue (45.9% vs. 44.9% for the low self-efficacy group). The associations among the major variables were examined using Pearson’s correlations (Table 3). The FACT-F was correlated with the CBI-B (r 0.56, P 0.001), ZSDS (r 0.66, P 0.001), and the BZSDS (r 0.52, P 0.001). In addition, the CBI-B was significantly correlated with the ZSDS (r 0.50, P 0.001), the BZSDS (r 0.45, P 0.001), and the FMBQ (r 0.20, P 0.01). Finally, the number of recommendations made by the medical staff for combating fatigue was only weakly significantly correlated (r 0.15, P 0.05) with the FMBQ. The 10 FMBQ concerns were also examined using Pearson’s correlations to explore their relationships to the other scales used in the study (Table 4). Due to the quantity of correla-
Table 3 Correlations Among Study Variables
FMBQ FMBQ FACT-F Cancer Behavior Inventory—Brief Zung Self-Rating Depression Scale Brief Zung Rating Depression Scale Number of Recommendations Made
aP bP
0.01. 0.05.
r sig n r sig n r sig n r sig n r sig n r sig n
FACT-F
CBI-B
ZSDS
BZSDS
0.034 0.633 198
0.199a 0.005 198 0.561a 0.000 199
0.015 0.835 193 0.657a 0.000 199 0.502a 0.000 194
0.049 0.494 193 0.522a 0.000 194 0.445a 0.000 194 0.810a 0.000 195
Number of Recs Made
0.146b 0.040 198 0.010 0.886 199 0.076 0.289 199 0.061 0.395 195 0.024 0.741 195
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Table 4 Correlations Between the Ten Concerns of the FMBQ and the Other Study Measures Assessment Measures FMBQ Factor Name Treatment futility r sig n Fear of disease progression r sig n “Good patient” r sig n Fear of distracting doctor r sig n Lack of concern r sig n Fear of stigma r sig n General medication concerns r sig n Preference of non-medication interventions r sig n Fear of jeopardizing cancer treatment r sig n Lack of communication r sig n aP bP
FACT-F
CBI-B
ZSDS
BZSDS
Number of Recs Made
0.189a 0.008 198
0.209a 0.003 198
0.066 0.365 193
0.107 0.139 193
0.154 0.031 198
0.278a 0.000 198
0.306a 0.000 198
0.218a 0.002 193
0.229a 0.001 193
0.145 0.041 198
0.145b 0.041 198
0.215a 0.002 198
0.092 0.201 193
0.068 0.349 193
0.012 0.868 198
0.086 0.229 198
0.032 0.655 198
0.007 0.920 193
0.089 0.218 193
0.079 0.268 198
0.062 0.387 198
0.182 0.011 193
0.114 0.114 193
0.086 0.227 198
0.043 0.547 198
0.179 0.011 198
0.086 0.233 193
0.061 0.399 193
0.040 0.574 198
0.060 0.403 198
0.201a 0.004 198
0.007 0.918 193
0.015 0.840 193
0.133 0.063 198
0.033 0.640 198
0.142 0.049 193
0.136 0.060 193
0.093 0.192 198
0.148 0.040 193
0.134 0.063 193
0.008 0.915 198
0.017 0.813 193
0.003 0.969 193
0.211a 0.003 198
0.271a 0.000 198
0.118 0.098 198
0.088 0.217 198
0.222a 0.002 198
0.029 0.685 198
0.129 0.070 198
0.01. 0.05.
tions run, and to attempt to limit chance associations, only findings at the 0.01 level were considered to be significant. Several of these concerns were significantly related to the other study measures. The treatment futility concern was shown to be correlated to the FACT-F (r 0.19, P 0.01) and the CBI (r 0.21, P 0.01). The fear of disease progression concern was significantly correlated to the ZSDS (r 0.22, P 0.01), FACT-F (r 0.28, P 0.001), and the CBI (r 0.31, P 0.001). The desire to be a “good patient” concern was found to be correlated to the CBI (r 0.22, P 0.01). The lack of concern over fatigue as
a noteworthy symptom was correlated with the FACT-F (r 0.27, P 0.001). The desire to limit medications concern (r 0.20, P 0.01) was only correlated to the CBI. Finally, the fear of jeopardizing cancer treatment concern was related to the CBI (r 0.22, P 0.01). When asked whether or not subjects had spoken to their doctor about fatigue, 68 (34%) responded ‘yes’ while a majority 132 (66%) responded that they had not discussed fatigue with their physician. A series of one-way ANOVAs revealed that there were no significant differences on either the total FMBQ or its ten con-
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cerns based upon whether or not the patient had spoken to their doctor regarding fatigue. In addition, patients were asked to report the number of recommendations that were made to them regarding fatigue. After correcting for outliers (i.e., 14 subjects’ responses were eliminated as they simply went down the list and checked all of the recommendations), the patients reported a mean of 11.63 recommendations (SD 7.55, range 0–25) from medical staff. When examining the FMBQ and its 10 concerns according to the number of recommendations made, a series of one-way ANOVAs revealed that only the lack of communication concern from the FMBQ was associated with the number of recommendations made by the medical staff (F32,165 1.54, P 0.05).
Discussion Fatigue is a highly prevalent, multidimensional problem for cancer patients. It is distressing for the patient, but our clinical experience, as well as the work of others,10 suggests that it is highly treatable through a variety of treatment modalities. However, to treat this symptom, we must first be able to adequately identify fatigue in cancer patients. To accomplish this, it is necessary to understand the barriers to communication about fatigue. With this understanding, we can help patients to better report their experiences. In this study, we attempted to identify the barriers that limited patient communication with their oncologists about fatigue. To this end, the FMBQ was developed and piloted with a large sample of urban and rural cancer patients. The FMBQ exhibited good variability among respondents and was shown to be a reliable measure that may be able to identify barriers towards adequate identification and treatment of fatigue. The two most common barriers endorsed by subjects offer some insight into why patients fail to discuss fatigue with their physicians. The highest level of endorsement (46.7%) among the sample was that interventions for fatigue were not being offered. Interestingly, though, patients reported on the Fatigue Intervention Checklist that 11 recommendations, on average, were given to them. This leads to speculation that the patients may have responded to the Fatigue Intervention Checklist unsystemati-
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cally, either perceiving all recommendations made to them over time to have been orders from their doctors, or failing to properly read the instructions leading to an answering style based upon personal preferences and acknowledgement of word of mouth from other sources, in addition to clinical staff. Alternately, given the instructions on the Fatigue Intervention Checklist, it may be that interventions for fatigue were suggested by members of the team other than physicians. A large number (43.1%) claimed a lack of awareness regarding any possible treatments for fatigue. Thus, it seems that there is reticence on the part of the physician and the patient to discuss fatigue as a symptom of cancer and cancer treatment. Indeed, this is evidenced by the large number (66%, n 132) who stated they had not spoken to their doctor about fatigue when directly questioned by the researcher. This “don’t ask, don’t tell” mindset may be the most straightforward to overcome by screening regularly for fatigue. This can be accomplished simply by using a single-item screen.29 The separation of respondents who scored at the extremes of the depression and self-efficacy spectrum from the sample offer some interesting insights into the beliefs about fatigue. The depressed patients were more likely than their non-depressed counterparts to have heard about potential interventions from their doctors; they wanted medications for the treatment of fatigue, but claimed that they were unaware of any effective treatments. It may be that the depressed group received more global attention because of their depressed mood, but still retained a hopeless outlook even when attention and possible treatment options are offered. Similarly, the low self-efficacy group was more apt than their high self-efficacy counterparts to want medication interventions while also believing that there were no effective fatigue interventions. Surprisingly, few differences were noted between the urban and rural samples. Of the 28 FMBQ items, only item 18 (“I try to be strong by not complaining about fatigue to my doctor”) and item 21 (“I’m afraid to tell doctor how fatigued I am because he won’t continue treatment”) were significantly different based on the rural versus urban split. The urban patients had a mean of 2.60 (SD 1.05) on item
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18 and 2.02 (SD 0.72) on item 21. Rural patients had a mean of 2.27 (SD 1.01) on item 18 and 1.77 (SD 0.66) on item 21. This indicates that urban patients were more likely to agree with these statements, possibly indicating greater stoicism or fear in the urban sample. This study has important implications for patient education. Barriers endorsed regarding fatigue are unlike those in the pain literature in that they are not as universal as patient-related barriers to pain treatment and are more numerous. Even the most commonly endorsed barriers identified herein are not nearly as universal as those seen in pain management. The use of the FMBQ to identify fatalistic attitudes and other barriers might be a reasonable start as we continue to figure out ways to enhance patient reporting of symptoms. This study raises interesting questions that should be explored through further research that does not rely on cross-sectional data alone. It may well turn out that clinicians will experience better patient outcome by making a stronger effort to individualize patient education and tailor measures regarding fatigue definitions based on whether or not the patient is depressed.
Acknowledgments This study was supported by a grant from the Fatigue Coalition and Ortho Biotech Products, L.P. The authors wish to acknowledge the help and support of Dr. Loretta Itri.
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Appendix A The FMBQ Items FMBQ Items (n 100) 1. If I complain about fatigue, my doctor will think I am too weak to receive more treatment. 2. It is unnecessary to treat my fatigue because it will go away on its own. 3. I prefer to treat my fatigue without taking medicines. 4. Having fatigue means that my illness is worse. 5. There is nothing that can be done about my fatigue. 6. If I take medicine to treat fatigue now, it might not work when I really need it. 7. I am afraid that treatment for fatigue will cause problems with my other medicines. 8. I don’t talk about fatigue because people will think I am depressed. 9. Compared to the other problems I have, fatigue is not worth my attention. 10. I try not to complain to my doctor. 11. My doctor is not an expert in treating fatigue. 12. I am treating my fatigue with a remedy that my doctor might disapprove of. 13. My doctor does not ask me about fatigue. 14. I don’t know of any effective treatment for fatigue. 15. My fatigue is an expected side effect of my treatment or disease so it is not necessary to treat it. 16. In general, I try to limit the number of medicines I take. 17. I don’t talk to my doctor about fatigue because I am afraid he/she will want me to take antidepressants or get counseling. 18. I try to be strong by not complaining about fatigue to my doctor. 19. Fatigue doesn’t bother me enough to require treatment. 20. My doctor has not offered me any interventions for fatigue. 21. I am afraid to tell my doctor how fatigued I am because then my doctor won’t want to continue treatment for my illness. 22. Doctors need to focus on my illness and not worry about my fatigue. 23. I am concerned about the side effects of medicines that might be given to me to treat my fatigue. 24. There is not enough time with my doctor to talk about fatigue. 25. I don’t want to bother my doctor by bringing up fatigue. 26. I am afraid of becoming addicted to medicine for fatigue. 27. It is more important for the doctor to focus on curing illness than to put time into controlling fatigue. 28. Fatigue is a sign that my illness is getting worse.
Strongly Disagree
Disagree
Neutral
Agree
Strongly Agree
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Vol. 24 No. 5 November 2002
The Fatigue Management Barriers Questionnaire
493
Appendix B Fatigue Intervention Checklist Please review the following list and indicate whether or not any of these recommendations were given to you by the doctors, nurses and/or other staff (i.e., social workers) in your clinic: A. Energy conservation strategies: 1. You should ask for help with chores such as cleaning or grocery shopping 2. Only do the things that are most important 3. Rest when feeling fatigued 4. Schedule periods of rest in between activities 5. Realistically plan daily activities 6. Maintain normal sleep patterns 7. Vary daily activities to prevent boredom
Y/N Y/N Y/N Y/N Y/N Y/N Y/N
B. Nutritional management strategies: 1. Eat small meals or snacks several times throughout the day 2. Drink plenty of water each day 3. Prepare extra meals and store them in the refrigerator on days you feel well 4. Ask for help when cooking and grocery shopping 5. Adjust your diet to insure adequate intake of calories 6. Consult with a dietitian to insure that you are eating a nutritionally balanced diet 7. Maintain a nutritionally complete diet that emphasizes complex carbohydrates
Y/N Y/N Y/N Y/N Y/N Y/N Y/N
C. Stress management strategies: 1. Be aware of potential causes of fatigue 2. Participate in activities you enjoy 3. Keep busy (e.g., listen to music, watch TV, read a book) instead of concentrating on tiredness, disease or treatment 4. Focus on the positive and participate in those activities you are able to complete 5. Join a support group and share feelings with others who have similar experiences 6. Your doctor or nurse put you in touch with other patients who have had the same experiences 7. Practice relaxation, hypnosis, or medication techniques
Y/N Y/N Y/N Y/N Y/N Y/N Y/N
D. Medical interventions: 1. Consider transfusion 2. Consider using erythropoetin (Procrit), if prescribed 3. Consider using stimulants, if prescribed 4. Consider using antidepressants, if prescribed 5. Consider using steroids, if prescribed 6. Consider using thyroid hormone, if prescribed
Y/N Y/N Y/N Y/N Y/N Y/N
E. Strategies to regulate daily activity and rest patterns: 1. Keep a diary of your energy levels at different times of the day 2. Plan activities for the times you feel best 3. Take several short naps throughout the day rather than one long nap 4. Try to exercise lightly or take a short walk 5. Focus on doing those activities that are important to you 6. Delegate activities that can be done by someone else
Y/N Y/N Y/N Y/N Y/N Y/N