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Determining the coping strategies of individuals with epilepsy
Epilepsy & Behavior 27 (2013) 286–291
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Epilepsy & Behavior journal homepage: www.elsevier.com/locate/yebeh
Determining the coping strategies of individuals with epilepsy Ramon Edmundo D. Bautista ⁎, Valerie Rundle-Gonzalez, Rusha G. Awad, Philip A. Erwin Comprehensive Epilepsy Program, Department of Neurology, University of Florida Health Sciences Center/Jacksonville, USA
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Article history: Received 26 November 2012 Revised 11 January 2013 Accepted 31 January 2013 Available online 17 March 2013 Keywords: Brief-COPE Coping Coping style Disengagement-type coping strategies Engagement-type coping strategies Epilepsy Racial disparity Seizure disorder
a b s t r a c t Purpose: The purpose of the present study was to determine whether the coping styles of patients with epilepsy are associated with certain demographic, clinical, and psychosocial variables. Methods: A survey of 200 patients using several tests including the Brief-COPE was conducted. Results: Nine subscales of the Brief-COPE achieved acceptable internal consistency and were employed in study analysis. Using principal component analysis, six subscales correlated well with one another, representing engagement-type coping strategies. The other three also correlated well, representing disengagement-type strategies. As a group, our patients favored engagement-type strategies. On univariate analysis, increased age, being African-American, receiving disability benefits, and work status were associated with the use of engagement-type strategies, while on multiple linear regression, only age and race were independently associated. Low BMQ-S scores, low income level, and not driving were associated with the use of disengagement-type strategies both on univariate and multivariate analyses. Conclusion: Among patients with epilepsy, certain demographic and psychosocial variables are associated with particular coping styles. © 2013 Elsevier Inc. All rights reserved.
1. Introduction Epilepsy is a common neurological disorder affecting approximately 1% of the population [1]. It has been linked to multiple psychosocial problems that include cognitive, emotional, and psychological difficulties [2,3]. Livneh and colleagues [4] enumerated four main categories of psychosocial problems as they relate to a patient's adaptation to epilepsy. These include the anxiety and concerns about the unpredictability of the disease, the stigma associated with the diagnostic label of epilepsy, the impact of epilepsy-specific life stressors, and the consequences related to denial of the condition. In general, coping describes the manner by which people deal with stressful events. It is a complex, multidimensional process determined by environmental conditions, cognitive abilities, and personality dispositions [5]. For many years now, coping reactions have been traditionally classified as being either problem-focused (aka approach or engagement coping) or emotion-focused (aka avoidance or disengagement coping) [4,6,7]. In brief, problem-focused coping strategies are employed by individuals who attempt to actively manage their medical condition. Examples of problem-focused coping strategies include active planning, positive reframing, and information seeking. On the other hand, emotion-focused coping strategies are typically an attempt to distance the individual from the source of stress by ⁎ Corresponding author at: Department of Neurology, University of Florida HSC/ Jacksonville, 580 West Eighth Street, Tower One, Ninth Floor, Jacksonville, FL 32209, USA. E-mail address: [email protected]fl.edu (R.E.D. Bautista). 1525-5050/$ – see front matter © 2013 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.yebeh.2013.01.029
employing techniques such as denial, avoidance, and wishful thinking. These are utilized when the source of stress is thought to be excessive or insurmountable [7]. Coping theories also classify reactions as being either dispositional or situational, with the former assuming that individuals generally have a habitual manner of dealing with stress while the latter supposing that an individual has a variety of coping styles tailored to a particular stressor or life event [8]. The existing literature on the coping strategies employed by patients with epilepsy is sparse. However, some studies have shown that patients with epilepsy frequently employ emotion-focused patterns of coping [9], particularly those with refractory epilepsy [10–12]; however, it is apparent that rather than helping, some of these reactions may adversely affect their quality of life [13]. In this study, we determined the coping mechanisms of patients followed at a level 4 epilepsy center in Jacksonville, Florida, USA. We determined whether certain demographic, clinical, and psychosocial variables were related to particular coping strategies. Understanding the coping mechanisms employed by various subgroups of patients with epilepsy will aid in formulating therapeutic initiatives that should help patients and caregivers manage this condition. 2. Methods This study was approved by the Institutional Review Board of the University of Florida Health Sciences Center/Jacksonville (UFHSCJ). We performed a direct survey of patients who were seen at the outpatient clinic of the UFHSCJ-Comprehensive Epilepsy Program (CEP) from June to August 2012. The UFHSCJ-CEP is a regional level
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4 epilepsy center located in downtown Jacksonville, Florida, USA. The patient demographics of our center indicate that around 42% of patients are males, 58% are Caucasians, while 31% are AfricanAmericans. A significant portion of patients seen at the UFHSCJ-CEP are from the indigent population, with 40% who are either uninsured, part of the city's indigent care program, or recipients of Medicaid/ Medicaid HMO programs. Around 5% of patients have undergone epilepsy surgery and/or VNS implantation. Physicians from the UFHSCJ serve as both primary and specialty neurologists to their patients. This allows the inclusion of a broad variety of patients with epilepsy into the study, ranging from patients with easy-to-control epilepsy to those with refractory seizures. In this study, only adult patients with an established diagnosis of epilepsy were considered. Subjects should have a diagnosis of localization-related epilepsy and should not have a history of psychogenic, nonepileptic events. They should be their own primary caregiver and able to complete the survey without assistance. We obtained the following information during the survey: 1. Demographic information a. age b. gender c. marital status d. ethnicity (Hispanic versus non-Hispanic) e. race f. educational attainment g. annual household income h. whether they drive i. whether they receive disability benefits j. current employment status 2. Disease-related information a. age at seizure onset b. seizure duration c. seizure frequency d. whether they experience convulsions e. whether they experience seizures while awake f. seizure etiology g. the number of AEDs (antiepileptic drugs) they are currently taking h. severity of side effects from their current AED regimen 3. Psychosocial data a. Neurological Institute Disorders Depression Inventory for Epilepsy (NIDDI-E) [14] b. Quality of Life in Epilepsy-10 (QOLIE-10) Inventory [15] c. Beliefs About Medicines Questionnaire—Specific (BMQ-S) [16] d. Sheehan Disability Scale (SDS) [17] e. Screening questions for health literacy f. Brief Coping with Problems Experienced (Brief-COPE) Inventory [18]. The NIDDI-E is a brief test (with 6 questions) that can be used to rapidly identify patients with clinical depression. The measure removes the potential effect of confounding variables (such as medication effects and cognitive problems) that may influence the diagnosis of depression in patients with epilepsy. A score of greater than 15 has a sensitivity of 81%, a specificity of 90%, and a positive predictive value of 62% for diagnosing a major depression [14]. The QOLIE-10 is a short-form measure derived from the widely used QOLIE-89 covering general and epilepsy-targeted aspects of physical and mental health as well as social and role functioning. Scores range from 1 to 50 with higher scores indicating lower quality of life. The test assesses health related quality-of-life issues in patients with epilepsy that fall into three distinct topics: a) medication effects, b) mental health, and c) role functioning and seizure worry. Test–retest data show significant Pearson's correlations for individual items (range, r = 0.48–0.81), and there are high negative correlations with the POMS
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Mood Scale, systemic toxicity, neurotoxicity, as well as seizure frequency [15]. The BMQ-S is a questionnaire-based method for assessing commonlyheld beliefs about medicines. Ten statements are asked regarding individual attitudes towards their own prescribed medications. These statements are answered across a 5-point Likert scale. The items of the BMQ-S reflect both patient beliefs in the necessity of their prescribed medications as well as their concern about potential adverse effects. In this study, we asked the patients to relate their responses to their seizure medications. We obtained a BMQ-S (necessity minus concerns) score, with higher scores indicating stronger patient beliefs in the importance of their seizure medications [16]. High BMQ-S scores are generally associated with good medication adherence [19]. The SDS assesses functional impairment in the inter-related domains of work/school, social, and family life. It is a self-reported tool consisting of three 10-point visual analog scales to assess disability. Total scores range from 0 to 30 with higher scores indicating increased impairment. The scores can be summed into a single dimensional measure of global functional impairment. While there is no established cut-off score, the change-over-time scores can be used to monitor response to treatment [17]. We included the following three screening questions for health literacy: “How often do you have someone help you read hospital materials?”, “How confident are you filling out medical forms by yourself?”, and “How often do you have problems learning about your medical condition because of difficulty understanding written information?”. These questions were taken from the Short Test of Functional Health Literacy in Adults (STOHFLA) [20]. Each item is analyzed in a 5-point Likert scale with lower scores indicating higher health literacy skills. A study conducted among VA patients by Chew and colleagues [21] indicated that responses to each of these three questions correlate well with the detection of inadequate health literacy using overall STOHFLA scores (AUROC of 0.87, 0.8, and 0.76 for each of these questions, respectively). In a separate study conducted by Wallace and colleagues [22], among primary care patients in a university clinic, the question “How confident are you filling out medical forms by yourself?” correlated well with STOHFLA scores in detecting patients with limited health literacy (AUROC: 0.82). The Brief-COPE is a 28-item self-reported questionnaire that determines an individual's coping strategy [18]. It is taken from the original COPE [23] and measures 14 distinct subscales of coping reactions (with 2 items each): self-distraction, active coping, denial, substance abuse, emotional support, instrumental support, behavioral disengagement, venting, positive reframing, planning, humor, acceptance, religion, and self-blame. Each item is scored from 1 (I haven't been doing this at all) to 4 (I've been doing this a lot), and we obtained the mean score; thus, there is a maximum score of 4 for every coping reaction. Higher scores indicate increased reliance on a particular coping reaction. In this study, COPE questions were structured to reflect dispositional coping. 2.1. Statistical analysis Statistical analysis was performed at a 5% level of significance using a 2-tailed test. Interval variables were transformed if necessary to satisfy the assumptions of parametric analysis. Statistical Package for the Social Sciences (SPSS) 15.0 was utilized for data normalization, determining Cronbach's alpha, and descriptive, univariate, and multivariate analyses, while Minitab 12.0 was utilized for principal component analysis. 2.1.1. Validation of the Brief-COPE In order to validate the use of the Brief-COPE in our patient population, we determined the Cronbach's alpha for the item pairs that measured each coping reaction and used a criterion of 0.5 to determine acceptability. This criterion was employed by Carver in the original formulation of the Brief-COPE [18]. A Cronbach's alpha of 0.5 or
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R.E.D. Bautista et al. / Epilepsy & Behavior 27 (2013) 286–291 Table 1 (continued)
Table 1 Descriptive data.a Number of respondents, n A. Demographic variables Age in years, mean (SD) Males, n (%) Marital status Single, n (%) Married, n (%) Divorced, n (%) Widowed, n (%) Hispanics, n (%) Race Caucasians, n (%) African-Americans, non-Hispanics, n (%) Others, n (%) Highest educational level Less than high school, n (%) High school, no college, n (%) Some college/associate's degree, n (%) Bachelor's/technical degree, n (%) Graduate/post-graduate, n (%) Annual household income Less than $10,000, n (%) Between $10,000 and $50,000, n (%) Between $50,000 and $100,000, n (%) More than $100,000, n (%) Drives a motor vehicle, n (%) Receives disability benefits, n (%) Work status Works full-time, n (%) Works part-time, n (%) Unemployed, n (%) B. Clinical variables Age of seizure onset in years, mean (SD) Seizure duration in years, mean (SD) Seizure frequency Daily, n (%) Less than daily but more than once a week, n (%) Less than weekly but at least once a month, n (%) Less than monthly but at least once a year, n (%) Less than once a year, n (%) Currently experiences convulsions, n (%) Has seizures while awake, n (%) Seizure etiology Head trauma/brain injury, n (%) Stroke, n (%) Brain tumor, n (%) Other causes, n (%) Unknown, n (%) Number of antiepileptic drugs (AEDs) currently taking None, n (%) One AED, n (%) Two AEDs, n (%) More than two AEDs, n (%) Side effects from current AED regimen None, n (%) Minor inconvenience, n (%) Major problem, n (%)
200
41.2 (14.9) 44 (36.4) 81 82 29 8 12
(40.3) (40.8) (14.4) (3.5) (6)
C. Psychosocial variables Screening questions for health literacy “How often do you have problems learning about you medical condition because of difficulty understanding written information?” Never, n (%) 58 (29.1) Occasionally, n (%) 42 (21.1) Sometimes, n (%) 52 (26.1) Often, n (%) 22 (10.6) Always, n (%) 26 (13.1) a b c d
113 (56.8) 70 (34.8) 17 (8.4) 48 81 51 16 4
(23.6) (40.7) (25.6) (8) (2)
111 57 26 6 54 104
(55.3) (28.6) (13.1) (3) (27.1) (52.3)
21 (10.6) 16 (8) 163 (81.4)
23.4 (17.2) 19.1 (16.5) 12 27 50 56 55 114 149
(6) (13.6) (25.1) (28.1) (27.1) (57.3) (74.9)
41 6 10 39 104
(20.6) (3) (5) (19.4) (51.2)
4 86 55 55
(2) (42.7) (27.6) (27.6)
104 (52.3) 70 (34.7) 26 (13.1)
C. Psychosocial variables NIDDI-Eb scores, mean (SD) 13.2 QOLIE-10c scores, mean (SD) 33.5 BMQ-Sd scores, mean (SD) 3.8 SDSe total score, mean (SD) 13 Screening questions for health literacy “How often do you have someone help you read hospital materials?” Never, n (%) 76 Occasionally, n (%) 31 Sometimes, n (%) 28 Often, n (%) 26 Always, n (%) 39 “How confident are you of filling medical forms out by yourself?” Extremely, n (%) 60 Quite a bit, n (%) 36 Somewhat, n (%) 43 A little bit, n (%) 25 Not at all, n (%) 36
(4.8) (7.1) (5.6) (9.7)
(38.2) (15.6) (14.1) (12.6) (19.6) (30.2) (18.1) (21.6) (12.1) (18.1)
e
Missing data are not included in the analysis. Neurological Institute Disorders Depression Inventory for Epilepsy. Quality of Life in Epilepsy-10 Inventory. Beliefs About Medicines Questionnaire—Specific (necessity minus concerns). Sheehan Disability Scale.
higher is considered to be acceptable criteria for internal consistency [24]. Subscales that had a Cronbach's alpha of b0.5 were excluded from further analysis. We then performed principal component analysis (PCA) with a varimax rotation on the remaining items. Those with a loading of 0.4 or greater were assigned to a given factor. In order to determine the number of factors to extract, we considered those with an eigenvalue of greater than 1. 2.1.2. Subscale analysis Subscales of the Brief-COPE with a Cronbach's alpha of 0.5 were the target variables for our study. The rest of the demographic, clinical, and psychosocial data gathered during the survey constituted the predictor variables. We first determined which individual coping strategies were strongly utilized in our patient population. We then obtained the mean scores of the various coping strategies that constituted each factor on PCA. Using this as our target, we determined the demographic, clinical, and psychosocial data that were significantly associated with each factor. We then utilized multiple linear regression to determine the predictor variables that were independently associated with each factor in the simultaneous context of other variables. 3. Results Two hundred continuously consenting patients who met the study criteria took the survey and were included in this study. Table 1 details the characteristics of our study population. Fifty-seven percent of respondents were Caucasians, while 35% were African-Americans. When examining the internal consistency of the Brief-COPE in our study population, 9 subscales (substance abuse, religion, humor, instrumental support, acceptance, denial, emotional support, positive reframing, and planning) achieved a Cronbach's alpha of at least 0.5. Six subscales (active coping, self-blame, behavioral disengagement, venting, and self-distraction) had a Cronbach's alpha of less than 0.5 and were excluded from further analysis (Table 2). Fig. 1 displays the coping reactions utilized by our study population. The three main coping reactions utilized were acceptance, religion, and emotional support, while the three reactions least utilized were substance abuse, denial, and humor. Principal factor analysis generated 5 factors with eigenvalues greater than 1.0 accounting for 68.1% of the variance (Supplementary material Table A). While 8 of the 16 variables had loadings of >0.4 in more than one factor, all variables were represented in either the first or second factor, accounting for 41.7% of the variance explained. Thus, we were able to develop a 2-dimensional model of coping for our study population (Table 3). Factor 1 showed significant positive factor loadings for the coping reactions emotional support, instrumental support, positive reframing, planning, acceptance, and religion. On the other hand, Factor 2 showed
R.E.D. Bautista et al. / Epilepsy & Behavior 27 (2013) 286–291 Table 2 Internal consistency of Brief-COPE items.
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Table 3 Summary of exploratory factor analysis of the Brief-COPE.a,b
Coping reaction
Items
Cronbach's alpha
Substance abuse Religion Humor Instrumental support Acceptance Denial Emotional support Positive reframing Planning Active coping Self-blame Behavioral disengagement Venting Self-distraction
4 & 11 22 & 27 18 & 28 10 & 23 20 & 24 3&8 5 & 15 12 & 17 14 & 25 2&7 12 & 26 6 & 16 9 & 21 1 & 19
0.791 0.786 0.661 0.601 0.588 0.571 0.535 0.521 0.517 0.489 0.485 0.437 0.399 0.395
Coping reactions with Cronbach's alpha b 0.5 were excluded from further analysis.
significant negative factor loadings for the scores of denial, substance abuse, and humor. The mean scores for the Factor 1 and Factor 2 coping reactions were 2.77 and 1.53, respectively (Fig. 2). There was a significant association between the Factor 1 coping reactions and age, race, disability benefits, and work status. Factor 1 scores directly correlated with age (r = 0.146; p = 0.04, Pearson r). Race was also significantly associated with Factor 1 scores (p b 0.01, ANOVA), with African-Americans having significantly higher Factor 1 scores compared to Caucasians (3.1 versus 2.6, p b 0.01, Bonferroni correction). Subjects receiving disability benefits had higher scores compared to those not on benefits (2.9 versus 2.6; p b 0.01, ANOVA) while unemployed subjects had higher Factor 1 scores, followed by the fully employed, and then the unemployed (2.8, 2.7, 2.3; p = 0.02, Kruskal–Wallis) (Supplementary material Table B). Factor 2 scores were associated with annual household income, driving a motor vehicle, and scores on the BMQ-S. In particular, higher Factor 2 scores were seen among lower income subjects (1.61 for those making less than $10,000/year and 1.49 for those making between $10,000 and $50,000/year) compared to those with higher income (1.28 for those making between $50,000 and $100,000/year and 1.45 for those making above $100,000/year) (p= 0.03, Kruskal–Wallis). Higher Factor 2 scores were also seen among subjects who did not drive (mean: 2.81 versus 2.65 for those who drove, p = 0.01, ANOVA). There
Fig. 1. Means of Brief-COPE coping reactions (coping reactions with Cronbach's alpha > 0.5; p b 0.01, ANOVA).
Factor 1 C3 denial C4 substance abuse C5 emotional support C8 denial C10 instrumental support C11 substance abuse C12 positive reframing C14 planning C15 emotional support C17 positive reframing C18 humor C20 acceptance C22 religion C23 instrumental support C24 acceptance C25 planning C27 religion C28 humor a b
Factor 2 −0.408 −0.757
0.538 −0.478 0.588 −0.779 0.732 0.69 0.613 0.699 −0.442 0.559 0.687 0.642 0.51 0.678 0.677 −0.6
Principal component analysis with Varimax rotation. Factors with initial eigenvalues >1 are shown.
was a negative correlation between BMQ-S scores and Factor 2 scores (r= −0.15; p = 0.03, Pearson r) (Supplementary material Table B). Interestingly, QOLIE-10 scores were not associated with either the Factor 1 (p = 0.13) or Factor 2 (p = 0.22) coping reactions. Likewise, seizure frequency was not related to the use of either the Factor 1 (p = 0.7) or Factor 2 (p = 0.49) coping reactions. Multiple linear regression indicated that race (being AfricanAmerican) and age continued to be independent predictors of Factor 1 scores (Table 4a), while household income, driving and BMQ-S scores were independently associated with Factor 2 scores (Table 4b). 4. Discussion The results of our study indicate that as a group, the main coping reactions employed by patients with epilepsy were the use of acceptance, religion, and emotional support, while the coping reactions least utilized were substance abuse, denial, and humor. As a group, our study population utilized engagement-type coping strategies over disengagement-type ones. Using principal component analysis, it is apparent that coping strategies correlate with each other; in this study, it appeared to cluster around two main groups of coping strategies. The first group (Factor 1) showed significant correlation between scores on acceptance, religion, emotional support, instrumental support, positive reframing, and planning, while the second group (Factor 2) showed
Fig. 2. Mean Factor 1 (acceptance, religion, emotional support, instrumental support, positive reframing, and planning) and Factor 2 (humor, denial, and substance abuse) scores (p b 0.01, ANOVA) taken from the Brief-COPE.
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Table 4a Multiple linear regression of variables associated with Factor 1. Variable
B
Constant Race Age Receives disability benefits Work status
Std. error
2.23 0.15 b0.01 −0.17 0.04
0.32 0.06 b0.0 0.11 0.08
95% confidence interval Sig.
Lower
Higher
b0.01 0.02 0.04 0.13 0.63
1.60 0.03 b0.01 −0.38 −0.12
2.86 0.27 0.01 0.05 0.2
Variables with p ≤ 0.05 using univariate analysis were included in the analysis. Bold entries refer to significant values.
significant correlation between scores on denial, substance abuse, and humor. Further analysis allows us to predict which of the various demographic, clinical, and psychosocial variables analyzed are significantly associated with either the Factor 1 or 2 reactions. Using multiple linear regression, our results indicate that older age and being AfricanAmerican are independently and significantly associated with the Factor 1 coping strategies. On the other hand, high scores on measures of denial, humor, and substance abuse occurred among patients with low scores on the BMQ-S, individuals with lower income, and among those who did not drive. To our knowledge, our study is the first to provide a comprehensive analysis of how individuals with epilepsy cope with their condition and what variables are significantly correlated with various coping styles. The Factor 1 variables generally consist of engagement-type coping subtypes indicating an attempt of patients to actively manage their medical condition and seek positive support from others and the environment. An exception to this would be the use of religion: this has been regarded by some authors as a disengagement-type of coping reaction [10] but not by all [4]. Hosseini and colleagues [25] considered religious belief or sentiment to be an active coping mechanism by which patients are able to accept their disease. Carver and colleagues [23] stated that many patients turn to religion for emotional support and positive reinterpretation, and this helps them actively cope with significant stressors. On the other hand, Factor 2 consists of disengagement-type of coping reactions. While a relation between denial and substance abuse is not surprising as both are considered dysfunctional forms of coping [23], the relation to humor is somewhat intriguing. In their study, Snell and colleagues [26] included humor among the group of “problem-focused” or “approach” coping factors, along with active coping, planning, positive reframing, acceptance, and religion. Some studies have shown that humor is a frequently utilized coping reaction across a variety of conditions, with well-known therapeutic effects for both patients and caregivers [27–29]. On the other hand, the use of humor has also been associated with increased stress and depression [29,30], and high cheerfulness at the age of 12 years has been associated with high mortality rates [31]. Martin [32] distinguishes between positive (affiliative and selfenhancing) and negative (aggressive and self-defeating) humor styles,
Table 4b Multiple linear regression of variables associated with Factor 2. Variable
Constant BMQ-Sa scores Income Driving status
B
1.64 −0.02 −0.11 0.18
Std. error
0.12 b0.01 0.05 0.09
95% confidence interval Sig.
Lower
Higher
b0.01 0.01 0.02 0.04
1.41 −0.31 −0.2 0.01
1.88 b−0.01 −0.19 0.35
Variables with p ≤ 0.05 using univariate analysis were included in the analysis. Bold entries refer to significant values. a Beliefs About Medicine—Specific (necessity minus concerns).
with the latter being related to increased psychological distress and dysfunction and adversely related to positive well-being. In fact, the use of negative humor often leads to increased negative emotion [33], and this may explain its relation to the use of denial and substance abuse in our study sample. This study makes a strong statement about the impact of age, race, income, and medication beliefs on coping and its consequences in populations with epilepsy. The impact of age on coping has already been reported by other authors. When comparing seniors with younger adults on the Medically Adjusted Illness Attitude Scale, BourgaultFagnou and Hadjistavropoulos [34] found that seniors with low levels of frailty had even lower levels of health anxiety when compared to young, healthy individuals. On various measures of anxiety, elderly individuals had lower levels of anxiety compared to younger adults [35]. The relation between race and coping is also interesting. It is generally believed that compared to Caucasians in the United States, African-Americans have higher rates of physical illness but have lower rates of psychiatric disorders [36]. Jackson and colleagues [37] postulated that this may be due to the fact the African-Americans have developed coping mechanisms, sometimes unhealthy ones, in order to deal with increased stress, thereby protecting their mental health. In a study of 170 trauma-exposed patients, Ghafoori and colleagues [38] found that African-Americans had lower depressive symptoms compared to Caucasians, likely due to a difference in coping styles, particularly with increased positive reframing. When compared to Caucasians, African-Americans were more likely to believe in divine intervention, whereas Caucasians tend to merge their spiritual practices with selfmanagement practices [39]. This finding contrasts somewhat with our study results that indicate that when compared to Caucasians, AfricanAmericans make more use of a greater variety of engagement-type of coping reactions, aside from religion. The association between medication beliefs, income levels, driving, and coping styles has not been extensively written about. However, the relation between low scores on the BMQ-S and higher Factor 2 scores is probably not surprising. Low BMQ-S scores indicate weak patient beliefs in the importance of their seizure medications [16] and are generally associated with poor medication adherence [19]. Our study also indicates that lower income is associated with higher use of disengagement-type coping reactions. Our study has several limitations. Patients were seen at a level 4 epilepsy center in Northeast Florida and were typical of an indigent, urban population. Thus, the demographic and clinical profiles of our study population may differ from other epilepsy programs, which may affect coping styles. Second, the data were obtained from subjects who consented to being part of the study and who provided self-reported information. Though the data were recorded anonymously, these factors make the results prone to sampling bias and increase the possibility of self-favorable responses. Third, we adopted the Brief-COPE to our study population and utilized it as a measure of coping. There are other coping tools that measure similar, but not necessarily identical, constructs of coping [5] that could have been utilized and may have influenced the study results. Lastly, the number of predictor variables evaluated was restricted, given the limited time to conduct the survey. Thus, other variables of potential interest, such as medication adherence, were not included in this study. Despite these limitations, the results of our study indicate that individuals with epilepsy cope with their condition in a variety of ways and that certain demographic, clinical, and psychosocial variables are significantly associated with particular coping styles. Future studies should focus on being able to integrate this knowledge into the everyday care of those afflicted with this condition. Being able to do so should help these individuals improve the medical management of their condition, enhance their well-being, and further their integration into society. Supplementary data to this article can be found online at http:// dx.doi.org/10.1016/j.yebeh.2013.01.029.
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Epilepsy & Behavior journal homepage: www.elsevier.com/locate/yebeh
Determining the coping strategies of individuals with epilepsy Ramon Edmundo D. Bautista ⁎, Valerie Rundle-Gonzalez, Rusha G. Awad, Philip A. Erwin Comprehensive Epilepsy Program, Department of Neurology, University of Florida Health Sciences Center/Jacksonville, USA
a r t i c l e
i n f o
Article history: Received 26 November 2012 Revised 11 January 2013 Accepted 31 January 2013 Available online 17 March 2013 Keywords: Brief-COPE Coping Coping style Disengagement-type coping strategies Engagement-type coping strategies Epilepsy Racial disparity Seizure disorder
a b s t r a c t Purpose: The purpose of the present study was to determine whether the coping styles of patients with epilepsy are associated with certain demographic, clinical, and psychosocial variables. Methods: A survey of 200 patients using several tests including the Brief-COPE was conducted. Results: Nine subscales of the Brief-COPE achieved acceptable internal consistency and were employed in study analysis. Using principal component analysis, six subscales correlated well with one another, representing engagement-type coping strategies. The other three also correlated well, representing disengagement-type strategies. As a group, our patients favored engagement-type strategies. On univariate analysis, increased age, being African-American, receiving disability benefits, and work status were associated with the use of engagement-type strategies, while on multiple linear regression, only age and race were independently associated. Low BMQ-S scores, low income level, and not driving were associated with the use of disengagement-type strategies both on univariate and multivariate analyses. Conclusion: Among patients with epilepsy, certain demographic and psychosocial variables are associated with particular coping styles. © 2013 Elsevier Inc. All rights reserved.
1. Introduction Epilepsy is a common neurological disorder affecting approximately 1% of the population [1]. It has been linked to multiple psychosocial problems that include cognitive, emotional, and psychological difficulties [2,3]. Livneh and colleagues [4] enumerated four main categories of psychosocial problems as they relate to a patient's adaptation to epilepsy. These include the anxiety and concerns about the unpredictability of the disease, the stigma associated with the diagnostic label of epilepsy, the impact of epilepsy-specific life stressors, and the consequences related to denial of the condition. In general, coping describes the manner by which people deal with stressful events. It is a complex, multidimensional process determined by environmental conditions, cognitive abilities, and personality dispositions [5]. For many years now, coping reactions have been traditionally classified as being either problem-focused (aka approach or engagement coping) or emotion-focused (aka avoidance or disengagement coping) [4,6,7]. In brief, problem-focused coping strategies are employed by individuals who attempt to actively manage their medical condition. Examples of problem-focused coping strategies include active planning, positive reframing, and information seeking. On the other hand, emotion-focused coping strategies are typically an attempt to distance the individual from the source of stress by ⁎ Corresponding author at: Department of Neurology, University of Florida HSC/ Jacksonville, 580 West Eighth Street, Tower One, Ninth Floor, Jacksonville, FL 32209, USA. E-mail address: [email protected]fl.edu (R.E.D. Bautista). 1525-5050/$ – see front matter © 2013 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.yebeh.2013.01.029
employing techniques such as denial, avoidance, and wishful thinking. These are utilized when the source of stress is thought to be excessive or insurmountable [7]. Coping theories also classify reactions as being either dispositional or situational, with the former assuming that individuals generally have a habitual manner of dealing with stress while the latter supposing that an individual has a variety of coping styles tailored to a particular stressor or life event [8]. The existing literature on the coping strategies employed by patients with epilepsy is sparse. However, some studies have shown that patients with epilepsy frequently employ emotion-focused patterns of coping [9], particularly those with refractory epilepsy [10–12]; however, it is apparent that rather than helping, some of these reactions may adversely affect their quality of life [13]. In this study, we determined the coping mechanisms of patients followed at a level 4 epilepsy center in Jacksonville, Florida, USA. We determined whether certain demographic, clinical, and psychosocial variables were related to particular coping strategies. Understanding the coping mechanisms employed by various subgroups of patients with epilepsy will aid in formulating therapeutic initiatives that should help patients and caregivers manage this condition. 2. Methods This study was approved by the Institutional Review Board of the University of Florida Health Sciences Center/Jacksonville (UFHSCJ). We performed a direct survey of patients who were seen at the outpatient clinic of the UFHSCJ-Comprehensive Epilepsy Program (CEP) from June to August 2012. The UFHSCJ-CEP is a regional level
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4 epilepsy center located in downtown Jacksonville, Florida, USA. The patient demographics of our center indicate that around 42% of patients are males, 58% are Caucasians, while 31% are AfricanAmericans. A significant portion of patients seen at the UFHSCJ-CEP are from the indigent population, with 40% who are either uninsured, part of the city's indigent care program, or recipients of Medicaid/ Medicaid HMO programs. Around 5% of patients have undergone epilepsy surgery and/or VNS implantation. Physicians from the UFHSCJ serve as both primary and specialty neurologists to their patients. This allows the inclusion of a broad variety of patients with epilepsy into the study, ranging from patients with easy-to-control epilepsy to those with refractory seizures. In this study, only adult patients with an established diagnosis of epilepsy were considered. Subjects should have a diagnosis of localization-related epilepsy and should not have a history of psychogenic, nonepileptic events. They should be their own primary caregiver and able to complete the survey without assistance. We obtained the following information during the survey: 1. Demographic information a. age b. gender c. marital status d. ethnicity (Hispanic versus non-Hispanic) e. race f. educational attainment g. annual household income h. whether they drive i. whether they receive disability benefits j. current employment status 2. Disease-related information a. age at seizure onset b. seizure duration c. seizure frequency d. whether they experience convulsions e. whether they experience seizures while awake f. seizure etiology g. the number of AEDs (antiepileptic drugs) they are currently taking h. severity of side effects from their current AED regimen 3. Psychosocial data a. Neurological Institute Disorders Depression Inventory for Epilepsy (NIDDI-E) [14] b. Quality of Life in Epilepsy-10 (QOLIE-10) Inventory [15] c. Beliefs About Medicines Questionnaire—Specific (BMQ-S) [16] d. Sheehan Disability Scale (SDS) [17] e. Screening questions for health literacy f. Brief Coping with Problems Experienced (Brief-COPE) Inventory [18]. The NIDDI-E is a brief test (with 6 questions) that can be used to rapidly identify patients with clinical depression. The measure removes the potential effect of confounding variables (such as medication effects and cognitive problems) that may influence the diagnosis of depression in patients with epilepsy. A score of greater than 15 has a sensitivity of 81%, a specificity of 90%, and a positive predictive value of 62% for diagnosing a major depression [14]. The QOLIE-10 is a short-form measure derived from the widely used QOLIE-89 covering general and epilepsy-targeted aspects of physical and mental health as well as social and role functioning. Scores range from 1 to 50 with higher scores indicating lower quality of life. The test assesses health related quality-of-life issues in patients with epilepsy that fall into three distinct topics: a) medication effects, b) mental health, and c) role functioning and seizure worry. Test–retest data show significant Pearson's correlations for individual items (range, r = 0.48–0.81), and there are high negative correlations with the POMS
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Mood Scale, systemic toxicity, neurotoxicity, as well as seizure frequency [15]. The BMQ-S is a questionnaire-based method for assessing commonlyheld beliefs about medicines. Ten statements are asked regarding individual attitudes towards their own prescribed medications. These statements are answered across a 5-point Likert scale. The items of the BMQ-S reflect both patient beliefs in the necessity of their prescribed medications as well as their concern about potential adverse effects. In this study, we asked the patients to relate their responses to their seizure medications. We obtained a BMQ-S (necessity minus concerns) score, with higher scores indicating stronger patient beliefs in the importance of their seizure medications [16]. High BMQ-S scores are generally associated with good medication adherence [19]. The SDS assesses functional impairment in the inter-related domains of work/school, social, and family life. It is a self-reported tool consisting of three 10-point visual analog scales to assess disability. Total scores range from 0 to 30 with higher scores indicating increased impairment. The scores can be summed into a single dimensional measure of global functional impairment. While there is no established cut-off score, the change-over-time scores can be used to monitor response to treatment [17]. We included the following three screening questions for health literacy: “How often do you have someone help you read hospital materials?”, “How confident are you filling out medical forms by yourself?”, and “How often do you have problems learning about your medical condition because of difficulty understanding written information?”. These questions were taken from the Short Test of Functional Health Literacy in Adults (STOHFLA) [20]. Each item is analyzed in a 5-point Likert scale with lower scores indicating higher health literacy skills. A study conducted among VA patients by Chew and colleagues [21] indicated that responses to each of these three questions correlate well with the detection of inadequate health literacy using overall STOHFLA scores (AUROC of 0.87, 0.8, and 0.76 for each of these questions, respectively). In a separate study conducted by Wallace and colleagues [22], among primary care patients in a university clinic, the question “How confident are you filling out medical forms by yourself?” correlated well with STOHFLA scores in detecting patients with limited health literacy (AUROC: 0.82). The Brief-COPE is a 28-item self-reported questionnaire that determines an individual's coping strategy [18]. It is taken from the original COPE [23] and measures 14 distinct subscales of coping reactions (with 2 items each): self-distraction, active coping, denial, substance abuse, emotional support, instrumental support, behavioral disengagement, venting, positive reframing, planning, humor, acceptance, religion, and self-blame. Each item is scored from 1 (I haven't been doing this at all) to 4 (I've been doing this a lot), and we obtained the mean score; thus, there is a maximum score of 4 for every coping reaction. Higher scores indicate increased reliance on a particular coping reaction. In this study, COPE questions were structured to reflect dispositional coping. 2.1. Statistical analysis Statistical analysis was performed at a 5% level of significance using a 2-tailed test. Interval variables were transformed if necessary to satisfy the assumptions of parametric analysis. Statistical Package for the Social Sciences (SPSS) 15.0 was utilized for data normalization, determining Cronbach's alpha, and descriptive, univariate, and multivariate analyses, while Minitab 12.0 was utilized for principal component analysis. 2.1.1. Validation of the Brief-COPE In order to validate the use of the Brief-COPE in our patient population, we determined the Cronbach's alpha for the item pairs that measured each coping reaction and used a criterion of 0.5 to determine acceptability. This criterion was employed by Carver in the original formulation of the Brief-COPE [18]. A Cronbach's alpha of 0.5 or
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R.E.D. Bautista et al. / Epilepsy & Behavior 27 (2013) 286–291 Table 1 (continued)
Table 1 Descriptive data.a Number of respondents, n A. Demographic variables Age in years, mean (SD) Males, n (%) Marital status Single, n (%) Married, n (%) Divorced, n (%) Widowed, n (%) Hispanics, n (%) Race Caucasians, n (%) African-Americans, non-Hispanics, n (%) Others, n (%) Highest educational level Less than high school, n (%) High school, no college, n (%) Some college/associate's degree, n (%) Bachelor's/technical degree, n (%) Graduate/post-graduate, n (%) Annual household income Less than $10,000, n (%) Between $10,000 and $50,000, n (%) Between $50,000 and $100,000, n (%) More than $100,000, n (%) Drives a motor vehicle, n (%) Receives disability benefits, n (%) Work status Works full-time, n (%) Works part-time, n (%) Unemployed, n (%) B. Clinical variables Age of seizure onset in years, mean (SD) Seizure duration in years, mean (SD) Seizure frequency Daily, n (%) Less than daily but more than once a week, n (%) Less than weekly but at least once a month, n (%) Less than monthly but at least once a year, n (%) Less than once a year, n (%) Currently experiences convulsions, n (%) Has seizures while awake, n (%) Seizure etiology Head trauma/brain injury, n (%) Stroke, n (%) Brain tumor, n (%) Other causes, n (%) Unknown, n (%) Number of antiepileptic drugs (AEDs) currently taking None, n (%) One AED, n (%) Two AEDs, n (%) More than two AEDs, n (%) Side effects from current AED regimen None, n (%) Minor inconvenience, n (%) Major problem, n (%)
200
41.2 (14.9) 44 (36.4) 81 82 29 8 12
(40.3) (40.8) (14.4) (3.5) (6)
C. Psychosocial variables Screening questions for health literacy “How often do you have problems learning about you medical condition because of difficulty understanding written information?” Never, n (%) 58 (29.1) Occasionally, n (%) 42 (21.1) Sometimes, n (%) 52 (26.1) Often, n (%) 22 (10.6) Always, n (%) 26 (13.1) a b c d
113 (56.8) 70 (34.8) 17 (8.4) 48 81 51 16 4
(23.6) (40.7) (25.6) (8) (2)
111 57 26 6 54 104
(55.3) (28.6) (13.1) (3) (27.1) (52.3)
21 (10.6) 16 (8) 163 (81.4)
23.4 (17.2) 19.1 (16.5) 12 27 50 56 55 114 149
(6) (13.6) (25.1) (28.1) (27.1) (57.3) (74.9)
41 6 10 39 104
(20.6) (3) (5) (19.4) (51.2)
4 86 55 55
(2) (42.7) (27.6) (27.6)
104 (52.3) 70 (34.7) 26 (13.1)
C. Psychosocial variables NIDDI-Eb scores, mean (SD) 13.2 QOLIE-10c scores, mean (SD) 33.5 BMQ-Sd scores, mean (SD) 3.8 SDSe total score, mean (SD) 13 Screening questions for health literacy “How often do you have someone help you read hospital materials?” Never, n (%) 76 Occasionally, n (%) 31 Sometimes, n (%) 28 Often, n (%) 26 Always, n (%) 39 “How confident are you of filling medical forms out by yourself?” Extremely, n (%) 60 Quite a bit, n (%) 36 Somewhat, n (%) 43 A little bit, n (%) 25 Not at all, n (%) 36
(4.8) (7.1) (5.6) (9.7)
(38.2) (15.6) (14.1) (12.6) (19.6) (30.2) (18.1) (21.6) (12.1) (18.1)
e
Missing data are not included in the analysis. Neurological Institute Disorders Depression Inventory for Epilepsy. Quality of Life in Epilepsy-10 Inventory. Beliefs About Medicines Questionnaire—Specific (necessity minus concerns). Sheehan Disability Scale.
higher is considered to be acceptable criteria for internal consistency [24]. Subscales that had a Cronbach's alpha of b0.5 were excluded from further analysis. We then performed principal component analysis (PCA) with a varimax rotation on the remaining items. Those with a loading of 0.4 or greater were assigned to a given factor. In order to determine the number of factors to extract, we considered those with an eigenvalue of greater than 1. 2.1.2. Subscale analysis Subscales of the Brief-COPE with a Cronbach's alpha of 0.5 were the target variables for our study. The rest of the demographic, clinical, and psychosocial data gathered during the survey constituted the predictor variables. We first determined which individual coping strategies were strongly utilized in our patient population. We then obtained the mean scores of the various coping strategies that constituted each factor on PCA. Using this as our target, we determined the demographic, clinical, and psychosocial data that were significantly associated with each factor. We then utilized multiple linear regression to determine the predictor variables that were independently associated with each factor in the simultaneous context of other variables. 3. Results Two hundred continuously consenting patients who met the study criteria took the survey and were included in this study. Table 1 details the characteristics of our study population. Fifty-seven percent of respondents were Caucasians, while 35% were African-Americans. When examining the internal consistency of the Brief-COPE in our study population, 9 subscales (substance abuse, religion, humor, instrumental support, acceptance, denial, emotional support, positive reframing, and planning) achieved a Cronbach's alpha of at least 0.5. Six subscales (active coping, self-blame, behavioral disengagement, venting, and self-distraction) had a Cronbach's alpha of less than 0.5 and were excluded from further analysis (Table 2). Fig. 1 displays the coping reactions utilized by our study population. The three main coping reactions utilized were acceptance, religion, and emotional support, while the three reactions least utilized were substance abuse, denial, and humor. Principal factor analysis generated 5 factors with eigenvalues greater than 1.0 accounting for 68.1% of the variance (Supplementary material Table A). While 8 of the 16 variables had loadings of >0.4 in more than one factor, all variables were represented in either the first or second factor, accounting for 41.7% of the variance explained. Thus, we were able to develop a 2-dimensional model of coping for our study population (Table 3). Factor 1 showed significant positive factor loadings for the coping reactions emotional support, instrumental support, positive reframing, planning, acceptance, and religion. On the other hand, Factor 2 showed
R.E.D. Bautista et al. / Epilepsy & Behavior 27 (2013) 286–291 Table 2 Internal consistency of Brief-COPE items.
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Table 3 Summary of exploratory factor analysis of the Brief-COPE.a,b
Coping reaction
Items
Cronbach's alpha
Substance abuse Religion Humor Instrumental support Acceptance Denial Emotional support Positive reframing Planning Active coping Self-blame Behavioral disengagement Venting Self-distraction
4 & 11 22 & 27 18 & 28 10 & 23 20 & 24 3&8 5 & 15 12 & 17 14 & 25 2&7 12 & 26 6 & 16 9 & 21 1 & 19
0.791 0.786 0.661 0.601 0.588 0.571 0.535 0.521 0.517 0.489 0.485 0.437 0.399 0.395
Coping reactions with Cronbach's alpha b 0.5 were excluded from further analysis.
significant negative factor loadings for the scores of denial, substance abuse, and humor. The mean scores for the Factor 1 and Factor 2 coping reactions were 2.77 and 1.53, respectively (Fig. 2). There was a significant association between the Factor 1 coping reactions and age, race, disability benefits, and work status. Factor 1 scores directly correlated with age (r = 0.146; p = 0.04, Pearson r). Race was also significantly associated with Factor 1 scores (p b 0.01, ANOVA), with African-Americans having significantly higher Factor 1 scores compared to Caucasians (3.1 versus 2.6, p b 0.01, Bonferroni correction). Subjects receiving disability benefits had higher scores compared to those not on benefits (2.9 versus 2.6; p b 0.01, ANOVA) while unemployed subjects had higher Factor 1 scores, followed by the fully employed, and then the unemployed (2.8, 2.7, 2.3; p = 0.02, Kruskal–Wallis) (Supplementary material Table B). Factor 2 scores were associated with annual household income, driving a motor vehicle, and scores on the BMQ-S. In particular, higher Factor 2 scores were seen among lower income subjects (1.61 for those making less than $10,000/year and 1.49 for those making between $10,000 and $50,000/year) compared to those with higher income (1.28 for those making between $50,000 and $100,000/year and 1.45 for those making above $100,000/year) (p= 0.03, Kruskal–Wallis). Higher Factor 2 scores were also seen among subjects who did not drive (mean: 2.81 versus 2.65 for those who drove, p = 0.01, ANOVA). There
Fig. 1. Means of Brief-COPE coping reactions (coping reactions with Cronbach's alpha > 0.5; p b 0.01, ANOVA).
Factor 1 C3 denial C4 substance abuse C5 emotional support C8 denial C10 instrumental support C11 substance abuse C12 positive reframing C14 planning C15 emotional support C17 positive reframing C18 humor C20 acceptance C22 religion C23 instrumental support C24 acceptance C25 planning C27 religion C28 humor a b
Factor 2 −0.408 −0.757
0.538 −0.478 0.588 −0.779 0.732 0.69 0.613 0.699 −0.442 0.559 0.687 0.642 0.51 0.678 0.677 −0.6
Principal component analysis with Varimax rotation. Factors with initial eigenvalues >1 are shown.
was a negative correlation between BMQ-S scores and Factor 2 scores (r= −0.15; p = 0.03, Pearson r) (Supplementary material Table B). Interestingly, QOLIE-10 scores were not associated with either the Factor 1 (p = 0.13) or Factor 2 (p = 0.22) coping reactions. Likewise, seizure frequency was not related to the use of either the Factor 1 (p = 0.7) or Factor 2 (p = 0.49) coping reactions. Multiple linear regression indicated that race (being AfricanAmerican) and age continued to be independent predictors of Factor 1 scores (Table 4a), while household income, driving and BMQ-S scores were independently associated with Factor 2 scores (Table 4b). 4. Discussion The results of our study indicate that as a group, the main coping reactions employed by patients with epilepsy were the use of acceptance, religion, and emotional support, while the coping reactions least utilized were substance abuse, denial, and humor. As a group, our study population utilized engagement-type coping strategies over disengagement-type ones. Using principal component analysis, it is apparent that coping strategies correlate with each other; in this study, it appeared to cluster around two main groups of coping strategies. The first group (Factor 1) showed significant correlation between scores on acceptance, religion, emotional support, instrumental support, positive reframing, and planning, while the second group (Factor 2) showed
Fig. 2. Mean Factor 1 (acceptance, religion, emotional support, instrumental support, positive reframing, and planning) and Factor 2 (humor, denial, and substance abuse) scores (p b 0.01, ANOVA) taken from the Brief-COPE.
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Table 4a Multiple linear regression of variables associated with Factor 1. Variable
B
Constant Race Age Receives disability benefits Work status
Std. error
2.23 0.15 b0.01 −0.17 0.04
0.32 0.06 b0.0 0.11 0.08
95% confidence interval Sig.
Lower
Higher
b0.01 0.02 0.04 0.13 0.63
1.60 0.03 b0.01 −0.38 −0.12
2.86 0.27 0.01 0.05 0.2
Variables with p ≤ 0.05 using univariate analysis were included in the analysis. Bold entries refer to significant values.
significant correlation between scores on denial, substance abuse, and humor. Further analysis allows us to predict which of the various demographic, clinical, and psychosocial variables analyzed are significantly associated with either the Factor 1 or 2 reactions. Using multiple linear regression, our results indicate that older age and being AfricanAmerican are independently and significantly associated with the Factor 1 coping strategies. On the other hand, high scores on measures of denial, humor, and substance abuse occurred among patients with low scores on the BMQ-S, individuals with lower income, and among those who did not drive. To our knowledge, our study is the first to provide a comprehensive analysis of how individuals with epilepsy cope with their condition and what variables are significantly correlated with various coping styles. The Factor 1 variables generally consist of engagement-type coping subtypes indicating an attempt of patients to actively manage their medical condition and seek positive support from others and the environment. An exception to this would be the use of religion: this has been regarded by some authors as a disengagement-type of coping reaction [10] but not by all [4]. Hosseini and colleagues [25] considered religious belief or sentiment to be an active coping mechanism by which patients are able to accept their disease. Carver and colleagues [23] stated that many patients turn to religion for emotional support and positive reinterpretation, and this helps them actively cope with significant stressors. On the other hand, Factor 2 consists of disengagement-type of coping reactions. While a relation between denial and substance abuse is not surprising as both are considered dysfunctional forms of coping [23], the relation to humor is somewhat intriguing. In their study, Snell and colleagues [26] included humor among the group of “problem-focused” or “approach” coping factors, along with active coping, planning, positive reframing, acceptance, and religion. Some studies have shown that humor is a frequently utilized coping reaction across a variety of conditions, with well-known therapeutic effects for both patients and caregivers [27–29]. On the other hand, the use of humor has also been associated with increased stress and depression [29,30], and high cheerfulness at the age of 12 years has been associated with high mortality rates [31]. Martin [32] distinguishes between positive (affiliative and selfenhancing) and negative (aggressive and self-defeating) humor styles,
Table 4b Multiple linear regression of variables associated with Factor 2. Variable
Constant BMQ-Sa scores Income Driving status
B
1.64 −0.02 −0.11 0.18
Std. error
0.12 b0.01 0.05 0.09
95% confidence interval Sig.
Lower
Higher
b0.01 0.01 0.02 0.04
1.41 −0.31 −0.2 0.01
1.88 b−0.01 −0.19 0.35
Variables with p ≤ 0.05 using univariate analysis were included in the analysis. Bold entries refer to significant values. a Beliefs About Medicine—Specific (necessity minus concerns).
with the latter being related to increased psychological distress and dysfunction and adversely related to positive well-being. In fact, the use of negative humor often leads to increased negative emotion [33], and this may explain its relation to the use of denial and substance abuse in our study sample. This study makes a strong statement about the impact of age, race, income, and medication beliefs on coping and its consequences in populations with epilepsy. The impact of age on coping has already been reported by other authors. When comparing seniors with younger adults on the Medically Adjusted Illness Attitude Scale, BourgaultFagnou and Hadjistavropoulos [34] found that seniors with low levels of frailty had even lower levels of health anxiety when compared to young, healthy individuals. On various measures of anxiety, elderly individuals had lower levels of anxiety compared to younger adults [35]. The relation between race and coping is also interesting. It is generally believed that compared to Caucasians in the United States, African-Americans have higher rates of physical illness but have lower rates of psychiatric disorders [36]. Jackson and colleagues [37] postulated that this may be due to the fact the African-Americans have developed coping mechanisms, sometimes unhealthy ones, in order to deal with increased stress, thereby protecting their mental health. In a study of 170 trauma-exposed patients, Ghafoori and colleagues [38] found that African-Americans had lower depressive symptoms compared to Caucasians, likely due to a difference in coping styles, particularly with increased positive reframing. When compared to Caucasians, African-Americans were more likely to believe in divine intervention, whereas Caucasians tend to merge their spiritual practices with selfmanagement practices [39]. This finding contrasts somewhat with our study results that indicate that when compared to Caucasians, AfricanAmericans make more use of a greater variety of engagement-type of coping reactions, aside from religion. The association between medication beliefs, income levels, driving, and coping styles has not been extensively written about. However, the relation between low scores on the BMQ-S and higher Factor 2 scores is probably not surprising. Low BMQ-S scores indicate weak patient beliefs in the importance of their seizure medications [16] and are generally associated with poor medication adherence [19]. Our study also indicates that lower income is associated with higher use of disengagement-type coping reactions. Our study has several limitations. Patients were seen at a level 4 epilepsy center in Northeast Florida and were typical of an indigent, urban population. Thus, the demographic and clinical profiles of our study population may differ from other epilepsy programs, which may affect coping styles. Second, the data were obtained from subjects who consented to being part of the study and who provided self-reported information. Though the data were recorded anonymously, these factors make the results prone to sampling bias and increase the possibility of self-favorable responses. Third, we adopted the Brief-COPE to our study population and utilized it as a measure of coping. There are other coping tools that measure similar, but not necessarily identical, constructs of coping [5] that could have been utilized and may have influenced the study results. Lastly, the number of predictor variables evaluated was restricted, given the limited time to conduct the survey. Thus, other variables of potential interest, such as medication adherence, were not included in this study. Despite these limitations, the results of our study indicate that individuals with epilepsy cope with their condition in a variety of ways and that certain demographic, clinical, and psychosocial variables are significantly associated with particular coping styles. Future studies should focus on being able to integrate this knowledge into the everyday care of those afflicted with this condition. Being able to do so should help these individuals improve the medical management of their condition, enhance their well-being, and further their integration into society. Supplementary data to this article can be found online at http:// dx.doi.org/10.1016/j.yebeh.2013.01.029.
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