Patient Optimism and Mastery—Do They Play a Role in Cancer Patients' Management of Pain and Fatigue?
Article Outline
Abstract
In the present study, we investigated longitudinally (baseline, 10 weeks, 16 weeks) whether patient personality traits, such as dispositional optimism and mastery, play a role in patients' ability to effectively control the severity of their pain and fatigue in the context of a symptom control intervention among patients with cancer. Two hundred fourteen patients currently undergoing chemotherapy received a baseline interview followed by a 10-week, nurse-assisted symptom control intervention. At 10 weeks, patients received a second interview to assess the effectiveness of the intervention, with a final follow-up interview at 16 weeks. Random effects regression models were used to investigate the effects of mastery and optimism on the severity of pain and fatigue, adjusting for the effects of other important covariates, such as age, gender, cancer site, stage of disease, and comorbidity. Patients who were older, more optimistic, suffered from fewer comorbid conditions, or reported higher levels of mastery tended to report less severe pain, whereas higher levels of mastery and fewer comorbid conditions predicted lower fatigue severity scores. These findings underscore the need for physicians and nurses involved in the care of cancer patients to recognize, encourage, promote, and take advantage of these traits in their patients to help them more effectively manage their cancer care, so that they ultimately can achieve a better quality of life during the sequelae of the cancer experience.
Key Words: Symptom control, cancer, intervention, mastery, optimism
Introduction
Pain and fatigue are among the most frequently occurring symptoms experienced by patients with cancer, and numerous studies have described the impact these symptoms can have on patients' physical and psychological functioning, as well as quality of life, throughout the trajectory of the cancer experience.1, 2, 3, 4, 5 The severity of symptoms may be a function of the site and stage of the cancer, comorbidity, treatment regimen, or patient characteristics, and may change over time.1, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16 For example, Given et al.1 found in their study of patients with breast, colon, lung, or prostate cancer, that stage of disease, more comorbidity and lung cancer were related to both pain and fatigue, whereas Degner and Sloan7 noted greater levels of symptom distress among adults with lung cancer as compared to other adults with cancer. Yoon et al.8 have observed that, among breast cancer patients, older women were less likely to report severe symptoms, and the number of comorbid conditions was positively associated with reporting symptoms. Again among breast cancer patients, Bower et al. noted that cardiovascular problems are an important predictor of fatigue. The case for gender differences is less clear-cut. On the one hand, both Redeker et al.14 and Pater et al.15 reported that among heterogeneous groups of cancer patients, women reported higher fatigue scores than men, on the other hand, Stone et al.16 reported no gender differences in fatigue severity among advanced cancer patients receiving palliative care.
Recent research has focused on clinical and cognitive behavioral interventions designed to assist patients in gaining better control of these distressing symptoms.17, 18, 19 These intervention studies primarily sought to explain which strategies worked and which did not. Less attention has been paid to what psychological/emotional resources patients bring to these interventions, such as perceptions of being in control of their life, for example, being able to master challenges in their lives, or their degree of optimism, or generalized positive expectations about their future, and how these variables may contribute to the success of the intervention.
Mastery, or sense of control, is defined as the extent to which a person feels that he or she has control over his or her environment.20 The construct of mastery has also been referred to as perceived control, efficacy and autonomy in the research literature.21 Several studies have identified positive associations of mastery with physical and emotional well-being, and mastery has also been shown to facilitate adaptation under stressful life situations, including medical events.22, 23 For example, Vallerand et al.,24 in a study of cancer patients and their caregivers, concluded that perceived control over pain is an important aspect of the pain response in the homecare setting. Surtees et al.25 found in the EPIC-Norfolk prospective cohort study involving 20,323 participants, that a strong sense of mastery was associated with lower rates of mortality from all causes, cardiovascular disease and cancer, whereas Jang et al.26 found that higher levels of mastery had significant direct affects on depression and also buffered the adverse effect of disability on depression.
Dispositional optimism is a relatively stable personality trait that can be thought of as a generalized expectancy of good outcomes, even in the face of adversity.27 A review by Scheier28 revealed a large body of research demonstrating that optimism has beneficial effects on people's well-being and health. A recent study by Allison et al.29 found that optimism was associated with better quality of life in head and neck cancer patients both before and after treatment, whereas Lauver and Tak30 found that optimism was associated with less delay and anxiety in care seeking and with expectations of positive outcomes of care seeking among women with self identified breast cancer symptoms (lesion or discharge). Carver et al.31 suggest that optimists may be using different coping strategies when confronting stressful events than pessimists. Several studies have found that the mechanisms for dealing with stressful events preferred by optimists are more often acceptance and active coping and less often avoidance or denial, when compared with persons with pessimistic outlooks.32, 33, 34 However, the literature regarding the role of optimism in disease is mixed, as a recent study of lung cancer patients concluded there was no evidence that a high level of optimism prior to treatment enhanced survival in patients with nonsmall cell lung cancer,35 whereas Allison et al. found that optimists reported less pain and fatigue, and better global health-related quality of life, both before and after treatment than did pessimists, among patients with head and neck cancers.36
In the present study, we investigated longitudinally (baseline, 10 weeks, 16 weeks) whether patient personality traits, such as dispositional optimism and mastery, play a role in patients' ability to effectively control the severity of their pain and fatigue in the context of a symptom control intervention among patients with cancer currently undergoing chemotherapy. In doing so, we also take into account the effects of important covariates, such as age, gender, comorbidity, cancer site and stage of disease. Specifically, we examined the following research hypotheses:
Methods
Sample
This study uses data from a larger multifaceted longitudinal symptom control intervention involving cancer patients. This larger study involved a random controlled trial comparing a Nurse Assisted Symptom Management (NASM) intervention with an automated telephone symptom management intervention, as well as a patient/caregiver intervention. Patients were recruited simultaneously for these studies from two comprehensive cancer centers, one community oncology program, and six hospital affiliated community oncology centers. Nurses were subcontracted from the participating institutions and trained to implement the recruitment and intervention protocols. To be eligible for the study, patients had to be (1) 21 years of age or older, (2) have a diagnosis of a solid tumor cancer or nonHodgkin's lymphoma, (3) be currently undergoing chemotherapy (patients concurrently undergoing radiation therapy or surgery were excluded), (4) have a touchtone telephone, and (5) be able to speak and read English. In addition, candidates for the patient/caregiver trial were required to have a designated family caregiver who was willing to participate with the patient. Based on information in their medical records, 1,605 cancer patients were eligible for the combined studies and were approached by nurse recruiters. Eight hundred fifteen expressed their willingness to participate by signing an informed consent form. Their sociodemographic information was entered into a web-based tracking system.
An automated voice response version of the M. D. Anderson Symptom Inventory was used during the recruitment phase to screen patients for symptom severity.37 According to established guidelines, a score of two or higher suggests a need for monitoring. Patients scoring two or higher on severity of at least one symptom (range, 0–10) were accepted into the study. Patients not scoring two or higher on any of the symptoms were called twice weekly for up to six weeks. Those failing to report a severity score of two or higher on any symptom were sent a letter thanking them for participation and were not entered into any of the studies. Of the 806 patients remaining, 257 had designated family caregivers and thus entered the patient/caregiver trial, 78 dropped out prior to entry, and another 34 dropped out prior to the baseline interview, leaving 437 patients who completed the baseline interview. Of these, 219 were randomly assigned to the automated telephone symptom management intervention and the remaining 218 to the NASM. The 218 patients in the NASM arm of the controlled trial were selected as the sample for the current study. Four patients were excluded due to incomplete data on key study variables at baseline, resulting in a final sample of 214 patients. Figure 1 shows the accrual process and attrition in more detail.
Fig. 1
Flowchart of study accrual and attrition.
Informed consent procedures for the clinical intervention were approved by the appropriate university committee on research involving human subjects, as well as the institutional review boards of the individual recruitment sites.
Intervention
Patients accepted into the NASM intervention underwent an intake interview and received a copy of the symptom management guide. Patients received a telephone call from a nurse in each of the first four weeks, skipped Week 5, were called in Week 6, skipped Week 7, and received a final call in Week 8. At 10 weeks patients received a second interview to assess their status and measure the effectiveness of the intervention. The patients received a final follow-up interview at 16 weeks to assess whether the intervention showed any lasting effects, or whether any improvements observed were more transient in nature.
As this study focused on the symptoms of pain and fatigue, we describe the intervention as it relates to these two symptoms. At each contact with the nurse, patients reporting pain or fatigue severity scores of four or higher (threshold) were selected for intervention. For each symptom reaching the threshold, the nurse delivered an appropriate intervention, stepped according to the severity of the symptom and supplemented with references to the symptom management guide. For example, for moderate pain (severity Levels 4–6), the nurse intervened in the areas of teaching, prescribing, communication with the health care provider and counseling and support (see Fig. 2 for details). At each subsequent contact, previously assigned strategies were evaluated. If a strategy was not tried, or tried but not found to be helpful, then the strategy was altered and a new one proposed. Successful strategies were reinforced and continued.
Fig. 2
Typical strategies to address moderate pain or fatigue (severity levels 4–6).
Measures
Age, gender, cancer site, and stage of disease were obtained from an audit of patients' records, entered into the tracking system, and confirmed during the baseline interview. Comorbid conditions were assessed at baseline as a count of comorbid conditions present, selected from a list of 15 comorbid conditions (diabetes, hypertension, cardiovascular disease, etc.).38 In the case of cancer site, because there were nine different cancer sites involved (plus the “other” cancers), most involving small numbers of patients, it was deemed impractical to use the full categorical variable in the models. For this reason, and in view of the literature pointing to more severe symptom distress among patients with lung cancer,1, 7 the cancer site variable was dichotomized into lung cancer vs. other cancers.
For this study, we used the Tumor, Node, Metastasis Staging System promulgated by the American Joint Committee on Cancer in the United States. Determination of the stage involves consideration of a number of variables which are important for prognosis (e.g., extent of the tumor, histological type, differentiation, metastasis), and classifies tumors on a scale of 0–IV (0
=localized…IV=distant metastasis).39, 40 To minimize the problem of small or empty cells in the analysis, stage was dichotomized into two groups: “early” (Stages 0, I, II) and “late” (Stages III, IV).
Severity of the symptoms pain and fatigue was scored by patients on a scale ranging from 0 (not present) to 10 (worst possible) at the baseline interview, each of the six telephone contacts, the 10-week interview and the follow-up interview at 16 weeks.
Patient mastery was assessed using a modified version of the Pearlin Mastery Scale.41 This scale includes seven items such as “I am usually certain about what to do in relation to my cancer care,” “In general, I am able to handle most problems in my cancer care,” “I feel I have a great deal of influence over the things that happen in my cancer care.” Several items in the scale were phrased negatively, and thus were reverse scored. Scoring was on a scale of 1–5 with higher scores indicating greater mastery. The composite mastery scale was formed by summing the scores for the individual items (range, 7–35). Patient mastery was assessed at baseline, 10 weeks, and 16 weeks.
Patient optimism was assessed with the Life Orientation Test developed by Scheier and Carver.42 This scale consists of eight items assessing typical outcome expectancies such as “I am always optimistic about my future,” “In uncertain times I usually expect the best,” “I always look on the bright side of things.” Several items were presented negatively to balance the scale, and as a result were reverse scored. Scoring was on a scale of 1–4, with higher scores indicating greater optimism. The composite score was computed as the sum of the individual item scores (range, 8–32). As dispositional optimism is considered to be a relatively stable personality trait, it was measured only at baseline.
Analysis
As an initial step, basic descriptive statistics were computed for the sociodemographic variables as well as means, standard deviations and pairwise correlations for all scale variables used in the study.
Given the panel nature of the data, the analysis needs to be able to accommodate several data characteristics. First, it must take into account all available information, which, under conditions of panel attrition, means a declining number of cases with available information from baseline (n=214) to 10 weeks (n=181) to 16 weeks (n=181). Secondly, to make maximum use of the available information, the analysis should include all cases that provide the relevant patient information for at least one wave of data collection. Thirdly, the analysis must be able to capture both within-subjects effects, that is, changes in predictors and outcomes over time, as well as between-subjects effects (e.g., variations across individual study participants). Finally, among the predictors are both time-independent variables (e.g., sociodemographic characteristics and diagnostic information) as well as time-dependent variables (e.g., symptom severity, which changes over the observation period). Statistical models that can accommodate these demands are variously known as “generalized estimating equations,” pooled time series regression, or random-effects regression.43, 44 All analyses were carried out with the random effects regression procedure “xtreg” of the STATA 6.0 software.45
Results
Descriptive statistics for demographic data and other variables measured only at baseline are presented in Table 1. The average patient was 57 years old and suffered from 2.1 comorbid conditions, whereas 73.8% were women and 85.8% suffered from late stage disease. Breast cancer accounted for 41.6% of cases, lung cancer 16.4%, colon cancer 13.1%, and the remaining 28.9% suffered from genital/urinary cancer, gastrointestinal cancer, gynecological cancer, pancreatic cancer, nonHodgkin's lymphoma, mesothelioma, or other cancers. Thirty-three patients were lost to attrition between baseline and 10 weeks, but there was no further attrition between 10 weeks and 16 weeks. Paired t-tests were used to compare continuing patients' baseline scores on all relevant study variables to those of patients who were lost to attrition after baseline. There were no differences between the two groups on severity of pain, severity of fatigue, age, optimism, or mastery, however, patients lost to attrition reported more comorbid conditions (mean=2.76, SD=1.52) than those remaining in the study (mean=1.95, SD=1.52) (P=0.008). There was no relationship of attrition to gender, stage of disease, or cancer site.
Table 1. Patient Sociodemographic Characteristics, Optimism, Comorbidity, Cancer Site, and Stage of Disease (n=214)
| Characteristic | n | % |
|---|---|---|
| Gender | ||
| Male | 56 | 26.2 |
| Female | 158 | 73.8 |
| Stage of disease | ||
| Early | 30 | 14.2 |
| Late | 182 | 85.8 |
| Cancer site | ||
| Breast | 89 | 41.6 |
| Colon | 28 | 13.1 |
| Lung | 35 | 16.4 |
| Genital/urinary | 13 | 6.1 |
| Gastrointestinal | 9 | 4.2 |
| Gynecological | 15 | 7.0 |
| Pancreatic | 7 | 3.3 |
| NonHodgkins Lymphoma | 11 | 5.1 |
| Mesothelioma | 3 | 1.4 |
| Other | 4 | 1.9 |
| Mean | Standard deviation | |
| Age | 57.0 | 11.8 |
| Comorbiditya | 2.1 | 1.6 |
| Optimismb | 24.5 | 2.9 |
aScale 0–15. |
bScale 8–32. |
Means and standard deviations for pain, fatigue, and mastery at each of the three interview waves are presented in Table 2. A preliminary examination of baseline, 10-week, and 16-week values for these variables revealed a consistent decrease in the severity of fatigue, but no consistent trend was observed for pain severity scores. We investigated this further by separating out the early and late stage patients, discovering in the process that there was a consistent decrease in pain severity scores over the three waves for patients with early stage disease (means 2.27, 2.15, and 1.31), whereas for patients with late stage disease, a drop in pain severity scores at 10 weeks was followed by an increase at 16 weeks (means 1.99, 1.32, 2.03). Because 85.8% of the patients had late stage disease, this latter pattern carried over for the whole group. Simultaneously, a modest increase in mastery scores was noted. The possible effects of mastery on pain and fatigue were analyzed more closely in the random effects regression models.
Table 2. Descriptive Statistics for Pain, Fatigue, and Mastery, by Time
| Baseline (n=214) | 10 Weeks (n=181) | 16 Weeks (n=181) | ||||
|---|---|---|---|---|---|---|
| Mean | SD | Mean | SD | Mean | SD | |
| Paina | 2.03 | 2.80 | 1.45 | 2.25 | 1.9 | 2.74 |
| Fatiguea | 4.40 | 2.73 | 3.46 | 2.76 | 2.99 | 2.72 |
| Masteryb | 26.10 | 3.96 | 27.72 | 4.39 | 28.38 | 4.32 |
aScale 0–10. |
bScale 7–35. |
The baseline correlation results (see Table 3) revealed that mastery was negatively correlated with both pain and fatigue as expected, whereas optimism was negatively correlated with pain. Comorbidity was positively correlated with fatigue and negatively correlated with mastery, also as expected, but was not significantly correlated with pain. Finally, patient age was correlated only with comorbidity.
Table 3. Correlations at Baseline for Pain, Fatigue, Mastery, Optimism, Age, and Comorbidity (n=214)
| Pain | Fatigue | Mastery | Optimism | Age | |
|---|---|---|---|---|---|
| Fatigue | 0.372a | ||||
| Mastery | −0.183a | −0.261a | |||
| Optimism | −0.174b | −0.108 | 0.366a | ||
| Age | −0.086 | −0.029 | −0.051 | 0.052 | |
| Comorbidity | 0.058 | 0.171b | −0.225a | −0.117 | 0.428a |
aCorrelation is significant at the 0.01 level. |
bCorrelation is significant at the 0.05 level. |
The random effects regression analyses for pain and fatigue (see Table 4) revealed that patients who were older, more optimistic, suffered from fewer comorbid conditions, or reported higher levels of mastery tended to report less severe pain. Overall, severity of pain did not vary significantly between baseline and 16 weeks, however, pain severity scores did decrease somewhat between baseline and 10 weeks (P=0.053), and the rebound at 16 weeks was also significant (P=0.044). A more detailed investigation of this phenomenon revealed that this rebound in pain severity levels at 16 weeks was present among patients with late stage disease, but not among those with early stage disease. Thus this rebound in pain severity levels can clearly be attributed to the experiences of those patients (85.8%) diagnosed with late stage disease.
Table 4. Random Effects Regression Analyses for Pain and Fatigue (n=214)
| Pain | Fatigue | |||
|---|---|---|---|---|
| Coefficient | Significance | Coefficient | Significance | |
| Gender (1=male, 2=female) | 0.543 | 0.098 | 0.730 | 0.023 |
| Cancer site (1=lung, 2=other) | 0.285 | 0.472 | −0.233 | 0.551 |
| Stage of disease (1=early, 2=late) | −0.146 | 0.715 | −0.518 | 0.187 |
| Age | −0.036 | 0.009 | −0.003 | 0.852 |
| Comorbidity | 0.252 | 0.010 | 0.219 | 0.024 |
| Mastery | −0.068 | 0.023 | −0.168 | 0.000 |
| Optimism | −0.108 | 0.029 | −0.165 | 0.736 |
| Time | ||||
| 10 Weeks vs. baseline | −0.434 | 0.053 | −0.656 | 0.005 |
| 16 Weeks vs. baseline | 0.041 | 0.863 | −1.102 | 0.000 |
| R2=0.097 | R2=0.150 | |||
Higher levels of mastery and fewer comorbid conditions also predicted lower fatigue severity scores, but optimism had no apparent effect on patients' severity of fatigue. Fatigue severity scores at both 10 and 16 weeks were significantly lower than their baseline values, and the drop between 10 and 16 weeks also approached significance (P=0.067), confirming the observed trend seen in Table 2. Finally, women reported higher levels of fatigue than men. This was primarily evident at baseline.
Discussion
The patients in our study were quite ill, with 85.8% being diagnosed with late stage disease and nearly 60% suffering from two or more comorbid conditions. In spite of this, their overall baseline optimism and mastery scores averaged 24.5 (scale 8–32) and 26.1 (scale 7–35), respectively. When we further investigated these baseline scores, we found very little difference in average baseline optimism and mastery scores for those patients diagnosed with early vs. late stage disease (24.4 and 27.0 vs. 24.5 and 25.9), or according to the number of comorbid conditions (27.4 and 25.3 for no comorbid conditions, 26.3 and 24.7 for one comorbid condition, 25.7 and 24.2 for two or more comorbid conditions).
The baseline correlation results, which revealed that levels of both mastery and optimism were negatively correlated with severity of pain, were consistent with our hypothesis that greater mastery and optimism should lead to a reduction in severity of pain. This point was confirmed by the random effects regression analysis. A logical explanation for this finding could be that persons who had in general a more optimistic outlook and felt more confident in their abilities to effectively master issues associated with their cancer care may have had the ability to more effectively take advantage of the strategies delivered by the nurses, and thus were more successful in controlling their pain. This point of view is supported by the work of Friedman et al.,46 who have associated optimism with greater use of problem-focused strategies to cope with health-related stressors such as cancer. In a similar vein, Carver et al.47 reported that among women undergoing breast cancer treatment, optimism was associated with more active planning and acceptance as well as with less behavioral disengagement, such as giving up, and less denial during initial treatment.
The case for fatigue was quite similar, with higher levels of mastery being associated with lower severity of fatigue. However, patient optimism was neither correlated with severity of fatigue (at baseline), nor was it a significant predictor of severity of fatigue. Again, we conjecture that the same mechanism is operating here, namely, that patients who are more confident in their abilities to master their cancer care are better able to benefit from the intervention and achieve better control over their fatigue. A similar effect was noted by de Ridder et al.,48 who observed in their study of chronically ill patients (multiple sclerosis and diabetes), that positive efficacy expectancies encouraged self-care behaviors. These findings are also supported by the work of Fredrickson and Levenson,49 who reported that a sense of mastery, optimism, and emotional vitality had positive effects on health outcomes that included increasing odds of recovery from disability (from stoke, heart attack, or hip fracture).
In summary, our hypotheses concerning the role of patients' sense of mastery as a predictor of reduced severity of pain and fatigue in the context of a symptom control intervention were supported, whereas the role of dispositional optimism was supported only in the context of reducing severity of pain. These findings underscore the need for physicians and nurses involved in the care of cancer patients to recognize, encourage, and take advantage of these traits in their patients to help them more effectively manage their cancer care, so that they ultimately can achieve a better quality of life during the sequelae of the cancer experience. In the context of the clinical setting, for example, for the characteristic mastery, the physician may observe a consistent pattern of patient responses/behaviors indicating a confidence in their ability and willingness to deal with the various patient responsibilities in implementing their symptom control regimen. Building on this recognition, the physician could discuss the benefits of this characteristic in the application of symptom management, encouraging, and empowering their patients to help them achieve more effective symptom control.
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This work was supported in part by National Cancer Institute Grant # RO1 CA030724, Automated Telephone Monitoring for Symptom Management, Charles Given, PI, Barbara Given, Co-PI, and in affiliation with the Walther Cancer Institute, Indianapolis, Indiana.
PII: S0885-3924(08)00058-4
doi:10.1016/j.jpainsymman.2007.08.010
© 2008 U.S. Cancer Pain Relief Committee. Published by Elsevier Inc. All rights reserved.
