Journal of the Neurological Sciences 338 (2014) 122–127

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Alcohol and substance use in multiple sclerosis☆ Meghan Beier a,⁎, Vanessa D'Orio b,c, Jessica Spat b,c, Melissa Shuman b,c, Frederick W. Foley b,c a b c

Department of Rehabilitation Medicine, University of Washington School of Medicine, Box 359612, 325 9th Ave., Seattle, WA 98104, United States Ferkauf Graduate School of Psychology, Yeshiva University, 1300 Morris Park Ave., Bronx, NY 10468, United States Multiple Sclerosis Center of Holy Name Medical Center, 718 Teaneck Rd., Teaneck, NJ 07666, United States

a r t i c l e

i n f o

Article history: Received 16 May 2013 Received in revised form 3 December 2013 Accepted 17 December 2013 Available online 27 December 2013 Keywords: Multiple sclerosis Alcohol use Drug abuse Depression Anxiety Disability

a b s t r a c t Background: Few studies have examined the prevalence of alcohol and drug use in individuals with multiple sclerosis (MS). The current study sought to examine the prevalence and associated demographic, disease-related, and psychological correlates of substance use in an East Coast United States outpatient MS sample. Methods: 157 individuals with MS completed questionnaires prior to, during or after their visit with an MS neurologist. These questionnaires included: the Alcohol Use Disorders Identification Test—Consumption (AUDIT-C), CAGE, CAGE—Adapted to Include Drugs (CAGE-AID), Patient Health Questionnaire—9 item (PHQ-9), Beck Depression Inventory—Second Edition (BDI-II) and Hospital Anxiety and Depression Scale—Anxiety (HADS-A). Results: On the AUDIT-C, 40% of individuals with MS met or exceeded the cutoff for excessive alcohol use. They were more highly educated and younger than non-drinkers. Utilizing the CAGE, 6% of the sample met criteria for a lifetime history of excessive alcohol use and men endorsed higher rates of alcohol use than women. Only a small portion of the sample endorsed a history of drug use (CAGE-AID, 4%). Drug use was associated with greater disability and depression symptoms, but lower self-reported anxiety. Conclusions: Current alcohol use was prevalent in this sample, and excessive use was associated with men, younger age, and more education. Reported drug use was minimal and associated with greater disability, more self-reported depression, but fewer anxiety symptoms. © 2013 Elsevier B.V. All rights reserved.

1. Introduction Substance use disorders are defined as maladaptive patterns of alcohol or drug use that lead to clinically significant impairment or distress [1]. Excessive consumption of alcohol has been linked to many health conditions including but not limited to: cancer (lip, oropharyngeal, oesophageal, liver, laryngeal, and breast), epilepsy, hypertension, coronary heart disease, cardiac arrhythmia, stroke, liver cirrhosis, acute pancreatitis, spontaneous abortion, low birth weight and psoriasis [2]. Furthermore, even minimal consumption is associated with increased risk of dementia, coronary heart disease, hypertension and obesity [3]. Screening questionnaires can help clinicians assess for alcohol problems such as excessive and risky use (e.g., AUDIT-C) or abuse and dependence (e.g., CAGE) [4]. In 2008, a national epidemiological study by SAMHSA reported that 8% of the general population (12 and older) was currently using illicit drugs and 2.5% were using prescription drugs (tranquilizers, stimulants and sedatives) for nonmedical purposes. Marijuana was found to be the

☆ Source of support: There was no funding source, sponsor or grant for this research. ⁎ Corresponding author at: Box 359612, Department of Rehabilitation Medicine, University of Washington School of Medicine, 325 9th Ave, Seattle, WA 98104, United States. Tel.: +1 206 221 5688. E-mail address: [email protected] (M. Beier). 0022-510X/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.jns.2013.12.029

most common. Marijuana was used by 75.7% of current drug users and for 57.3% of them, it was the only substance used [5]. Illicit drug use is associated with a number of negative health consequences including: increased mortality, blood-borne infections (e.g., HIV, hepatitis C, and hepatitis B), cardiovascular disease, cirrhosis, pulmonary disease and mental health diagnoses [6]. Similar to alcohol, questionnaires such as the CAGE-AID (Adapted to Include Drugs) [7] were developed to help clinicians screen for use of drugs that could impact health. While much is known about substance use in the general population, only a limited number of studies assessed the drinking and drug use habits of individuals with multiple sclerosis (MS). Multiple sclerosis (MS) is a chronic and progressive disease of the central nervous system (CNS), characterized by inflammatory demyelination and neurodegeneration, which results in destruction of both white and gray matter in the brain and spinal cord. Thus, disease presentation is considerably heterogeneous, with a wide range of motor, cognitive, and psychiatric symptoms [8]. The disease, which affects approximately 1 in 1000 individuals residing in western countries, is the most common cause of disability outside of traumatic injury in early adulthood [9]. In the general population, heavy alcohol consumption increases in the late teens, peaks around age 25 or 26, and then slowly decreases [10]. There is a similar pattern with drug use [6]. This is especially important when thinking about multiple sclerosis. MS is usually diagnosed between the ages of 20 and 40 [9], when the rate of substance use is at its highest. This is particularly problematic because alcohol and

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drug use may cause further neurologic damage to an already compromised central nervous system [11–14]. However, there is considerable variability in findings of substance use among individuals with MS. Several studies suggest that consumption of alcohol may be more common in individuals with multiple sclerosis [12,13,15] than in the general population; 13.6–22.8% in MS as compared to 9% in the general population (12-month prevalence) [11–14,16,17]. Others suggest the opposite and report that consumption decreases after diagnosis [18,19]. In terms of demographics, two studies (one of veterans with MS and one of community-dwelling individuals with MS) found that excessive alcohol use was more prevalent in individuals who were younger, employed, and in better physical health [12,13]. Conversely, a Canadian study found no significant differences in demographics between excessive and normal drinkers [14]. Similarly, in some studies mental health diagnoses such as anxiety and depression were reported as more prevalent in excessive drinkers [12,14], but this was not found in other studies [13]. The way alcohol use was assessed may provide an explanation for this lack of consistency. We know from studies in the general population that measures used to assess for hazardous drinking may not accurately assess abuse and dependence and vice versa [4]. The measure used to assess alcohol can impact the reported rate of consumption, associated demographics and make comparisons between study samples difficult. A few examples of survey measures used in MS studies include: select questions from the National Institute of Alcohol Abuse and Alcoholism [18], the National Health and Nutrition Examination Survey [18], the Alcohol Use Disorders Identification Test—Consumption Questions (AUDIT-C) [13], select questions from the Patient Health Questionnaire [12], and the Structured Clinical Interview for the Diagnostic and Statistical Manual of Mental Disorders—Fourth Edition (SCID-IV) [14]. Like alcohol consumption, the study of illicit drug use among individuals with MS is limited and much of the research focuses on the use of marijuana for symptom relief. However, it has been suggested that individuals with multiple sclerosis who use drugs are more likely to screen positive for excessive alcohol use [12], are at higher risk for mental health disorders [14], and demonstrate slower processing speed than individuals with MS that do not use illicit drugs [20]. The data on alcohol and drug use in multiple sclerosis is limited. There is inconsistency in how substance use is assessed, rates of consumption, demographics and many available studies were done with populations that are not easily generalizable (e.g., United States Veterans). The main aim of this study was to enhance our knowledge of substance use in individuals with multiple sclerosis by examining the demographic (age, education, gender), disease-related (disease severity, time since diagnosis), and common psychosocial (pain, depression) correlates of alcohol and drug use utilizing several common screening instruments (e.g., CAGE, CAGE-AID, AUDIT-C) in an East Coast outpatient clinic MS sample. 2. Methods

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asked to participate in the study when they arrived for an appointment at the MS Center. Upon consent, each participant was given a packet of questionnaires that they completed prior to, during, or after their office visit. The packet was collected prior to their departure from the clinic. The Albert Einstein College of Medicine Institutional Review Board for Human Subjects Research approved all procedures and consent forms. 2.3. Measures 2.3.1. Alcohol use 2.3.1.1. Alcohol Use Disorders Identification Test—Consumption (AUDIT-C). This three-item validated screen is used to assess the quantity and frequency of current alcohol use. It has been used to screen for active alcohol use disorders, but performs best when screening for hazardous drinking (≥ 16 drinks per week for men or ≥ 12 drinks per week for women). Scores range from 0 to 12. A recent US general population validation study of past-year drinkers examined how well the AUDIT-C performed in detecting hazardous drinking. For men, a cut-off score ≥4 yielded a sensitivity of 99.0 and specificity of 79.1 [21]. For women, a score of 3 or more yielded a sensitivity of 96.3 and specificity of 79.5 [21]. In a study of individuals with MS, Turner and colleagues [13] broke down the scoring into four categories: non-drinkers (0), low-level, non-clinical drinkers (1–3 for men and 1–2 for women), mild-moderate drinkers (4–7 for men and 3–7 for women), and severe alcohol misuse (8 or above for both men and women). 2.3.1.2. CAGE. This four-item questionnaire was developed to screen for alcohol abuse [22,23]. Scores range from 0 to 4. When used to screen for heavy drinking (score ≥ 2), the sensitivity and specificity of the CAGE ranged from 49 to 69% and 75 to 95%, respectively. When used to screen for alcohol abuse or dependence with a cutoff score of 2, the sensitivity ranged from 21 to 94% and specificity ranged from 77 to 97%. With a cutoff score of 1, studies report a sensitivity of 60–71% and specificity of 84–88% [4]. 2.3.2. Drug use 2.3.2.1. CAGE—Adapted to Include Drugs (CAGE-AID). This four-item questionnaire is identical to the original CAGE for alcohol use except “drinking” has been replaced by “drinking or drug use” [7]. The CAGE-AID was validated in primary care. A score of one or more indicates a positive screen with a sensitivity of 0.79 and specificity of 0.77. A score of two or more yields a sensitivity of 0.7 and specificity of 0.85. However, this study wanted to separate alcohol and substance use, so we included only “drug use.” Justification for adapting the CAGE for drug use only comes from substance use literature in traumatic brain injury, where researchers compared the drug adapted CAGE to the SCID. The drug adapted CAGE accurately classified 78% of drug users and yielded a sensitivity of 68% and specificity of 82% [24].

2.1. Participants A convenience sample of individuals with MS was recruited from the Multiple Sclerosis Center at Holy Name Medical Center in Teaneck, New Jersey. Inclusion criteria were [1]: a definite diagnosis of MS [2], ability to speak and read English [3], over the age of eighteen, and [4] capacity and willingness to sign the research consent form. Exclusion criteria included any physical (e.g., legal blindness or deafness) problem rendering individuals incapable of completing questionnaires. A total of 157 individuals were enrolled in the study.

2.3.2.2. National Household Survey Drug Abuse Question (NHSDA). This single question, “Have you used drugs or medication for nonmedical purposes (that is, for recreational use, using a drug that was not prescribed for you, using a drug in greater amounts, or more often than prescribed or using drugs to get high?)” is answered dichotomously with either a yes or no response. This question was originally developed as part of the 1992 National Household Survey on Drug Abuse [25] and used by Bombardier and colleagues [12] with multiple sclerosis patients. 2.3.3. Depressive symptomology

2.2. Procedure Research personnel and staff from the Multiple Sclerosis Center at Holy Name Medical Center completed recruitment. Individuals were

2.3.3.1. Patient Health Questionnaire—9 item (PHQ-9). The PHQ-9 is the depression subscale from the Patient Health Questionnaire (PHQ). Each of the nine questions coincide with one of the nine criteria listed

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in the American Psychiatric Association's Diagnostic and Statistical Manual of Mental Disorders Fourth Edition (DSM-IV) for major depressive disorder. The questions are answered using a Likert scale ranging from zero to three (0 = not at all, 1 = several days, 2 = more than half the days and 3 = nearly every day). Depression severity is determined using the total score of all endorsed questions. Symptoms are considered minimal if the total score is 1 to 4, mild if 5 to 9, moderate if 10 to 14, moderately severe if 15 to 19, and severe if 20 to 27. The PHQ-9 was validated on a sample of 3000 primary care patients and 3000 obstetrics–gynecology patients. The overall sensitivity and specificity of the questionnaire was 84% and 72%, respectively [26]. 2.3.3.2. Beck Depression Inventory—Second Edition (BDI-II). The BDI-II is a 21-item self-report measure used to assess for the presence and severity of depressive symptoms. This second edition of the BDI was significantly revised and reworded to more accurately align items with the DSM-IV criteria. Each question is answered using a four-point Likert scale ranging from 0 to 3. Two of the items (sleep and appetite) list seven options to allow the reporting of increased or decreased appetite/sleep. Severity of depression symptomology is determined by using a total score. A score of 0 to 13 indicates minimal depression symptoms, 14 to 19 indicates mild, 20–28 indicates moderate depression, and a total score between 29 and 63 indicates severe depressive symptomology. The BDI-II yields high reliability in an outpatient population (Cronbach's alpha = .94). Total item correlations indicated good internal consistency and ranged from .54 to .74. 2.3.4. Symptoms of anxiety 2.3.4.1. Hospital Anxiety and Depression Scale—Anxiety (HADS-A). The HADS-A is a 7-item subscale of a larger 14-item questionnaire measuring anxiety and depression. It is scored on a 0 to 3 Likert scale, with higher scores indicating greater self-reported anxiety. The measure was originally developed and validated for use in medically ill patients; therefore it does not include somatic items. A recent validation study in MS suggests that the anxiety subscale is best used for screening individuals with generalized anxiety disorder (GAD) [27]. When considering only GAD patients, a cut-off score of ≥8 yielded a sensitivity of 88.5% and specificity of 80.7%. Including all anxiety diagnoses, a cut-off score ≥7 yielded a sensitivity of 78% and specificity of 77.8% [27]. 2.3.5. Disease severity 2.3.5.1. Incapacity Status Scale (ISS). This scale was developed in the 1980s as part of the Minimal Record of Disability (MRD) to help grade MS related disability [28]. It consists of 16 items including: stair climbing, ambulation, toilet/bed/chair transfer, bowel function, bladder function, bathing/dressing, grooming, feeding, vision, speech and hearing, medical conditions, mood and thought disturbance, mentation, fatigue, and sexual dysfunction. Each of the 16 items has a corresponding Likert scale ranging from 0 (normal function) to 4 (loss of function). The ISS can be used by nursing staff or trained research assistants and takes approximately 20–30 min to administer [29–31]. 2.3.6. Presence and intensity of pain Enrolled participants were asked by nursing staff to rate their current pain based on a 0 (no pain) to 10 (worst possible pain) numerical rating scale. This single item numerical rating scale has been validated in a variety of patient populations, including multiple sclerosis [32,33]. 2.4. Data analysis Descriptive statistics and frequencies were used to determine the prevalence rates of substance use, as well as demographic, psychosocial and disease-related variables. Individuals with and without substance use problems (heavy drinking or drug use) were compared using

t-tests for continuous variables and Fisher's Exact Tests for categorical or dichotomous variables. For the AUDIT-C, alcohol users were broken down into three categories (Group 1: non-drinkers, Group 2: low-level drinkers, Group 3: clinically significant alcohol use). A one-way between-group analysis of variance was conducted to explore the variability in scores between all three groups. 3. Results Of the 157 participants recruited, most were female (72%), married or living with a civil union partner (66%), Caucasian (82%), and employed full or part-time (51%). The mean age of the sample was 48.6 years (SD = 10.3) and the mean education of the sample was 14.6 years (SD = 2.5). In terms of disease characteristics, the average number of years since diagnosis was 12.9 (SD = 8.3). As a group, individuals did not report substantial pain (M = 2.3, SD = 3.2; on a 1 to 10 scale). The mean physical disability rating (Incapacity Status Scale; ISS) was also quite low at 8.7 (SD = 5.7). The ISS is a 16-item measure of overall functioning, mobility, and self-care that can be administered by a trained medical provider or research assistant. The total score can range from 0 to 64. Lower scores indicate better functioning [31]. 3.1. Prevalence and correlates of substance use 3.1.1. CAGE According to the CAGE questionnaire, 6% (8 of 128) of the collected sample endorsed a lifetime prevalence of excessive alcohol use or abuse (total score ≥ 2). Seventeen individuals (13%) in the collected sample obtained a score of one or higher on the questionnaire. Almost a fifth of the total participants (19%) refused to complete this questionnaire. Independent samples t-tests were used to determine if there were significant differences between excessive or abusive drinkers and non-problem drinkers in terms of age, education, disease severity, disease duration, pain, anxiety symptoms, and depressive symptomology. Utilizing Levene's Test for Equality of Variances it was determined that there was no violation of the assumption of equal variance for any of the following data. There were no significant differences between excessive or abusive drinkers (CAGE total score ≥ 2) and non-problem drinkers for any of the demographic, disease, or psychological variables. Categorical variables gender, race, relationship, and employment were dichotomized into male or female, white or not white, married/in a civil union partnership or single, and employed or not employed. Due to small expected frequencies (b5) the Fisher's Exact Test was used in place of the Pearson chi-square test. No significant differences were found between excessive or abusive and non-excessive drinkers in terms of race, marital status, or employment. However, there was a significant difference in gender, with males having a higher frequency of excessive or abusive alcohol consumption than females (p = .009). (See Table 1.) 3.1.2. CAGE-AID Endorsement of drug use (CAGE-AID) was lower than reported alcohol use (CAGE). Only 5 individuals (4%) in the sample endorsed two or more drug use items. Eight of 116 (7%) of the collected sample endorsed at least one drug use on the CAGE-AID. A quarter of the collected sample left this questionnaire blank (N = 41, 26%). Independent samples t-tests were used to determine if there were significant differences between endorsed drug use (score of 1 or higher) and no drug use (score of 0) in terms of age, education, disability, pain, anxiety symptoms, and depression scores. Utilizing Levene's Test for Equality of Variances it was determined that there was no violation of the assumption of equal variance for any of the following data. There was no significant difference in age, education, disease duration, or pain between drug users and non-users. However, individuals with multiple sclerosis that used drugs reported more depression symptoms

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on both the PHQ-9 and BDI-II and were rated by medical staff to have greater disease severity (ISS) than non-drug users. There was also a significant difference in endorsed anxiety between drug users and non-users. Endorsed drug use was associated with fewer anxiety symptoms than non-drug users. Fisher's Exact Test revealed no significant differences with regards to gender, race, marital status, or employment between drug users and non-users (see Table 1). 3.1.3. AUDIT-C The AUDIT-C rendered significantly higher rates of excessive alcohol consumption than the CAGE questionnaire, the general population, and previous research on drinking among individuals with multiple sclerosis. Using the AUDIT-C criteria, 40% of the sample met criteria for excessive drinking. For men, 39% (N = 12) of individuals obtained a score of 4 or higher. For women, 41% (N = 34) obtained a score of 3 or higher. One individual fell into the “severe” category. Like the CAGE questionnaires, a large number of participants opted to leave this questionnaire blank. More specifically, 42 participants (27%) did not complete any of the 3 AUDIT-C items. Three one-way multivariate analyses of variances (MANOVA) were conducted to explore the association of alcohol use with psychological (depression and anxiety), disease-related (pain, disease duration, and disease severity), and demographic (age and years of education) variables. Using the AUDIT-C, subjects were divided into three groups based on their level of alcohol use (Group 1: non-drinkers, Group 2: low-level drinkers, Group 3: clinically significant alcohol use). Because only one individual met criteria for severe alcohol misuse, the moderate and severe categories of drinking were combined. (See Table 2.) Using Wilks' lambda, alcohol consumption was not related to anxiety and depression, L = .94, F (6, 196) = 1.12, p = .36. Similarly, using Wilks' lambda alcohol consumption was not associated with disease-related variables (pain, disease duration, and disease severity), L = .88, F (6, 112) = 1.21, p = .31. However, demographic variables were significantly associated with alcohol consumption (Wilks's lambda), L = .84, F (4, 176) = 4.13, p = .003. Separate univariate ANOVAs revealed that age F (2, 89) = 3.87, p = .024 and education F (2, 89) = 6.18, p = .003 varied significantly across the three alcohol consumption groups. Tukey HSD post-hoc analysis revealed a statistically significant difference in the mean age between non-drinkers and low-level drinkers (8.18, 95% CI [.92 to 15.45], p = .023). Non-drinkers were older than low-level drinkers. For education, Tukey HSD post-hoc analysis revealed a statistically significant difference between non-drinkers and low-level drinkers (2.29, 95% CI [.69 to 3.89], p = .003) as well as non-drinkers and excessive drinkers (1.95, 95% CI [.33 to 3.57], p = .014). Nondrinkers had fewer years of education compared to the low-level drinkers and excessive drinkers. The three AUDIT-C categories were used in conjunction with dichotomous demographic variables in chi-square tests for independence. There was no significant association between drinking status and gender χ2 (2) = .12, p = .94, marital status χ2 (2) = .54, p = .76, employment χ2 (2) = 3.66, p = .16, or race χ2 (2) = 5.02, p = .08. 3.1.4. National Household Survey Drug Abuse Question (NHSDA) After a preliminary review of the data (N = 121) it was noted that individuals were not always answering the CAGE-AID questionnaire. To clarify our definition of “drug use” we added a single question based on the research by Bombardier et al. [12] and the 1992 National Household Survey on Drug Abuse [25,34]: “Have you used drugs or medication for nonmedical purposes (that is, for recreational use, using a drug that was not prescribed for you, using a drug in greater amounts, or more often than prescribed or using drugs to get high?).” A sub-sample of 34 participants completed this question (N = 2, missing). Of those 34, 23.5% (N = 8) of the individuals answered this question in the affirmative; a much larger proportion than endorsed lifetime drug

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use on the CAGE-AID. Therefore, it is likely that, the CAGE-AID alone underestimates the prevalence of lifetime substance abuse. Chi-square tests for independence indicated no significant association between drug use and gender, race, marital status, or employment. Independent samples t-tests were done to compare demographic, disease-related, and psychological variables with self-reported drug use. Utilizing Levene's Test for Equality of Variances, it was determined that there was no violation of the assumption of equal variance for any of the variables. There was no significant difference in age, years of education, disease severity (ISS), disease duration, self-reported pain, and self-reported anxiety symptoms between history of drug use and denied drug use. A significant difference was noted in depression with drug users presenting with higher rates of self-reported depression than non-users (see Table 1). 4. Discussion The primary goal of this study was an examination of the psychosocial correlates of alcohol and drug use in an outpatient multiple sclerosis population. Three questionnaires and the NHSDA Drug Abuse Question (AUDIT-C, CAGE-A and CAGE-AID) were utilized for this purpose [25]. The current sample of individuals with MS endorsed higher rates of excessive alcohol use on the AUDIT-C (40%) than the general population and other MS studies. One study examining alcohol use in a primary care sample using the AUDIT-C found that 35.5% of men and 14% of women met criteria for clinically significant drinking [35]. Turner et al. [13], used the AUDIT-C for their study and reported that 13.9% of their veteran population of MS individuals met criteria for excessive drinking (11.9% were in the mild-moderate category and 2% were in the severe category). One possible explanation for this finding is the sampled population. It was noted in the literature that excessive drinkers tend to be younger, employed and less disabled than their non-drinking peers. Similar to these previous findings, excessive drinkers were more highly educated and younger than non-drinkers in our sample. The average age of the current clinic sample was ten years younger (M = 48.6) than that found in the Turner et al. [13] paper (M = 56.7). This sample was also less disabled and had lower rates of depression than the individuals sampled by Bombardier et al. [12]. Unlike the AUDIT-C, the CAGE questionnaire found much lower rates of excessive or abusive drinking (6%) than those found in the general population. However this prevalence rate was similar to what was found in MS by Bombardier and colleagues with an adapted CAGE (6.5%). Similar to the general population, this study found that men with multiple sclerosis more frequently endorsed excessive drinking than women. Again, Bombardier's study found a similar, but nonsignificant trend [12]. Some researchers have suggested that the CAGE is a poor screener and other available measures such as the AUDIT-C should be used in its place [36]. As previously stated, in the general population, men tend to drink more alcohol than women. Men are also more likely to obtain a diagnosis of alcohol abuse or dependence. However, the sample in the current study (and MS in general) consisted of a majority of women; consistent with the prevalence of MS. Bradley, Boyd-Wickizer, Powell and Burman [37] mentioned that the perception of substance use questionnaires can vary based on demographic information (e.g. gender, race, ethnicity, etc.). They state that excessive drinking in women may not be captured by the normal cut off scores and they suggest using a cut off score of 1 on the CAGE. It is suggested that future studies should explore these comparisons within a larger and more varied sample. Another difficulty with the CAGE questionnaire is the manner in which the questions are formatted. Three out of four questions ask about the person's perception of their own drinking (Have you ever felt you should cut down on your alcohol use? Have people annoyed you by criticizing your alcohol use? Have you ever felt bad or guilty about your alcohol use?). The questionnaire does not quantify social, vocational,

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Table 1 Means (SD) or percentages for demographic, MS disease-related, and psychological variables of participants associated with NHSDA and CAGE questionnaires. Demographic variable

Gender Female Male Race White Not White Relationship Married/partner Single Employment Employed Not employed Age (SD) Education (SD) Disease severity; ISS (SD) Disease duration (SD) Pain (1–10); (SD) PHQ-9 (SD) BDI-II (SD) HADS-A

Total sample N = 157

CAGE (total ≥ 2) Excessive alcohol use or abuse

No excessive use

CAGE-AID (total ≥ 1)

72% 28%

2% 16%

98% 84%

FE

82% 18%

6% –

94% 100%

FE

66% 34%

5% 5%

95% 95%

FE

51% 49% 48.6 (10.3) 14.6 (2.5) 8.7 (5.7)

6% 3% 44.8 (9) 14.8 (2.6) 9.9 (7.4)

94% 97% 49.1 (9.7) 14.7 (2.5) 8.3 (5.7)

FE t = 1.07 t = −.1 t = −.65

12.9 (8.3)

17 (12.5)

12.8 (8.5)

t = -.83

2.3 (3.2) 6.5 (5.5) 13.1 (9.4) 11.6 (2.5)

3.9 (3.9) 6.3 (3.2) 13.3 (11.4) 11.5 (2)

2.1 (3.1) 6.1 (5.4) 12.6 (9.1) 11.8 (2.5)

t t t t

Statistical test

p-Value

No drug use

Statistical test

.009

4% 14%

96% 86%

FE

.59

5% –

95% 100%

FE

5% 3%

95% 97%

FE

.68 .29 .92 .52

3% 6% 51 (5.3) 14.3 (2.6) 15 (6.2)

97% 94% 48.5 (9.6) 14.9 (2.4) 8 (5.6)

FE t = −.57 t = .54 t = −2.71

.41

12.3 (7.6)

12.5 (8.5)

t = .06

.18 .95 .85 .76

4.2 (2.4) 11.6 (5.8) 23.6 (11.5) 8.9 (1.8)

2.3 (3.2) 6 (5.2) 12.4 (8.9) 11.8 (2.5)

t t t t

1

= −1.35 = −.06 = −.19 = .31

NHSDA

Used drugs

= −1.31 = −2.98 = −3.4 = 3.3

p-Value

Used drugs

No drug use

Statistical test

16% 44%

84% 56%

FE

1

29% 17%

71% 83%

FE

1

25% 21%

75% 79%

FE

.57

.67 .57 .59 .008

25% 23% 51.4 (5.6) 14.3 (2.7) 14.9 (4.8)

75% 77% 49.1 (9.7) 14 (2.4) 10.1 (6.2)

FE t = .6 t = .2 t = 1.8

.6 .54 .81 .08

.95

13 (3.2)

13.5 (9.3)

t = −.1

.92

.2 .004 .001 .001

5.8 (3.1) 12.8 (5.8) 26 (11.5) 11.9 (3.5)

2.9 (3.5) 6.9 (5) 13.1 (7.7) 12.1 (2.9)

t t t t

.08 .008 .001 .87

.1

= = = =

p-Value

.17

1

1.8 2.8 3.7 −.2

Abbreviations: FE, Fisher's Exact Test; BDI-II, Beck Depression Inventory—Second Edition; PHQ-9, Patient Health Questionnaire—9 item; HADS-A, Hospital Anxiety and Depression Scale—Anxiety; ISS, Incapacity Status Scale; CAGE-AID, CAGE—Adapted to Include Drugs; NHSDA, National Household Survey Drug Abuse Question.

or medical consequences of drinking. Without objective quantifying information, the questionnaire is merely asking for one's own opinion, which may underestimate problematic alcohol use. The CAGE-AID faces similar difficulties. It also asks for the person's own opinion of their drug use. If an individual only used drugs once or does not view their drug use as a problem, they might screen negative for problem drug use. Additionally, the term “drug use” can be vague and should be further clarified. Becker, Sullivan, Tetrault, Desai and Fiellin [38] found that 4.5% of community dwelling adults abuse prescription drugs. However, when using a questionnaire like the CAGE-AID, research participants might not consider prescription drug misuse as “drug use.” The NHSDA question helps to clarify what is meant by “drug use.” It also captures all drug use (“have you ever used…”) rather than capturing only individuals that believe they have a problem. A larger percentage of participants endorsed the question (23.5%), “Have you ever used drugs or medications for non-medical purposes (that is, for recreational use, using a drug that was not prescribed for you, using a drug in greater amounts or more often than was prescribed or using drugs to get high)?” than the

Table 2 Means and standard deviations for the three AUDIT-C alcohol consumption categories.

Disease-related Disease severity (ISS) Disease duration Pain [1–10] Psychological BDI-II PHQ-9 HADS-A Demographic Age Years of education

Non-drinkers M (SD)

Low-level drinkers M (SD)

Excessive drinkers M (SD)

9.79 (6.95) 17.25 (10.14) 3.79 (4.13)

8.48 (6.12) 10.81 (7.95) 2.33 (3.17)

7 (4.62) 12.68 (9.19) 2.02 (2.86)

13.22 (10.47) 5.39 (5.15) 11.83 (3.26)

13.53 (9.86) 7.02 (6.46) 11.6 (2.21)

10.65 (7.68) 5.1 (3.95) 11.73 (2.46)

53.21 (9.84) 13.05 (2.22)

45.03 (12.47) 15.34 (2.5)

49.46 (9.37) 15 (2.34)

Abbreviations: BDI-II, Beck Depression Inventory—Second Edition; PHQ-9, Patient Health Questionnaire—9 item; HADS-A, Hospital Anxiety and Depression Scale—Anxiety; ISS, Incapacity Status Scale.

CAGE-AID questionnaire (4%). The obtained rate is also higher than the 7.4% that was found in the original article by Bombardier et al. [12]. Unfortunately, the NHSDA was added in the midst of the study so it could not be compared across the whole sample. However, it seems (from the limited data available) that the CAGE-AID was not capturing endorsed drug use as well as the NHSDA. Therefore, history of drug use may be underestimated in our sample. Thus, this literature suggests that the NHSDA question – along with additional inquiries into the type of drugs used as well as the length of time and frequency of use – may better capture substance abuse. 4.1. Study limitations In addition to the study limitations already discussed, there are a number of factors that could have impacted the study data. First, a large portion of the sample refused or left blank the alcohol and drug surveys (percent of participants that refused each questionnaire: CAGE 19%, CAGE-AID 26%, AUDIT-C 27%) but completed the rest of the questionnaire packet. Therefore, it is likely that drinking and drug use is underestimated in our sample. It is unclear why this occurred. Although assured of confidentiality in the consent process, it is possible that participants feared their physician or nurse would review their answers to the questions. It is also possible that participants found the questionnaires stigmatizing. Additionally, there was overall low endorsement of any alcohol or drug use on both CAGE questionnaires which likely limited our power to detect differences in demographic, disease-related, and psychological variables. On the AUDIT-C, only one person fell into the “severe” excessive alcohol use category, which also limits our ability to determine if severe alcohol use could impact these factors. Furthermore, some research suggests that moderate alcohol use is associated with better health outcomes [39]. This may also be true in MS and should be explored in future studies. Future studies in MS should also aim to gather a larger number of moderate to heavy drinkers. Finally, there is much variability in how alcohol and drug use has been assessed in studies of MS patients. Certain measures are more effective at screening for abuse and dependence, while others might

M. Beier et al. / Journal of the Neurological Sciences 338 (2014) 122–127

perform best when screening for risky consumption. Variability in our findings, as well as those in the literature, may be attributed to the chosen assessment. Furthermore, to our knowledge, these screening measures are not validated in this population. Future research should establish which questionnaires are most reliable and valid in the MS population. One consideration might be to compare a gold standard structured interview (like the SCID) with the self-report questionnaires to determine if they are truly capturing the actual rate of drinking and drug use in MS. Conflict of interest Frederick W. Foley has received honoraria for speaking for Acorda, Bayer, Biogen, Teva, and Novartis. He received an investigator grant from Bayor, has been a consultant for Acorda and Bayer, and is a patent holder in conjunction with a project from Biogen. References [1] Latvala A, Castaneda AE, Perala J, Saarni SI, Aalto-Setala T, Lonnqvist J, et al. Cognitive functioning in substance abuse and dependence: a population-based study of young adults. Addiction 2009;104(9):1558–68. [2] Rehm J, Room R, Graham K, Monteiro M, Gmel G, Sempos CT. The relationship of average volume of alcohol consumption and patterns of drinking to burden of disease: an overview. Addiction 2003;98(9):1209–28. [3] Dawson DA, Li TK, Grant BF. A prospective study of risk drinking: at risk for what? Drug Alcohol Depend 2008;95(1–2):62–72. [4] Fiellin DA, Reid MC, O'Connor PG. Screening for alcohol problems in primary care: a systematic review. Arch Intern Med 2000;160(13):1977–89. [5] http://www.samhsa.gov/data/nsduh/2k8nsduh/2k8Results.htm#Ch2 2012. Available from: http://www.samhsa.gov/data/nsduh/2k8nsduh/2k8Results.htm#Ch2. [6] Degenhardt LHW. Extent of illicit drug use and dependence, and their contribution to the global burden of disease. Lancet 2012;379(9810):55–70. [7] Brown RLRL. Conjoint screening questionnaires for alcohol and other drug abuse: criterion validity in a primary care practice. Wis Med J 1995;94(3):135–40. [8] Brodkey MB, Ben-Zacharia AB, Reardon JD. Living well with multiple sclerosis. Am J Nurs 2011;111(7):40–8 [quiz 9–50]. [9] Anderson DW, Ellenberg JH, Leventhal CM, Reingold SC, Rodriguez M, Silberberg DH. Revised estimate of the prevalence of multiple sclerosis in the United States. Ann Neurol 1992;31(3):333–6. [10] Chen C, Dufour M, Yi H-Y. Alcohol consumption among young adults ages 18–24 in the United States: results from the 2001–2002 NESARC survey. Epidemiol Bull 2004/2005;28(4):269–80. [11] Chwastiak LA, Ehde DM. Psychiatric issues in multiple sclerosis. Psychiatr Clin North Am 2007;30(4):803–17. [12] Bombardier CH, Blake KD, Ehde DM, Gibbons LE, Moore D, Kraft GH. Alcohol and drug abuse among persons with multiple sclerosis. Mult Scler 2004;10(1):35–40. [13] Turner AP, Hawkins EJ, Haselkorn JK, Kivlahan DR. Alcohol misuse and multiple sclerosis. Arch Phys Med Rehabil 2009;90(5):842–8. [14] Quesnel S, Feinstein A. Multiple sclerosis and alcohol: a study of problem drinking. Mult Scler 2004;10(2):197–201. [15] Marrie R, Horwitz R, Cutter G, Tyry T, Campagnolo D, Vollmer T. High frequency of adverse health behaviors in multiple sclerosis. Mult Scler 2009;15(1):105–13.

127

[16] Friedmann P. Clinical practice. Alcohol use in adults. N Engl J Med 2013;368(4):365–73. [17] Grant BF, Dawson DA, Stinson FS, Chou SP, Dufour MC, Pickering RP. The 12-month prevalence and trends in DSM-IV alcohol abuse and dependence: United States, 1991–1992 and 2001–2002. 2004;74(3):223–34. [18] Foster M, Zivadinov R, Weinstock-Guttman B, Tamano-Blanco M, Badgett D, Carl E, et al. Associations of moderate alcohol consumption with clinical and MRI measures in multiple sclerosis. J Neuroimmunol 2012;243(1–2):61–8. [19] Brown TR. Measuring up rates for adverse health behaviors in MS. Mult Scler 2009;15(5):647 [author reply 248]. [20] Ghaffar O, Feinstein A. Multiple sclerosis and cannabis: a cognitive and psychiatric study. Neurology 2008;71(3):164–9. [21] Dawson DA, Grant BF, Stinson FS, Zhou Y. Effectiveness of the derived Alcohol Use Disorders Identification Test (AUDIT-C) in screening for alcohol use disorders and risk drinking in the US general population. Alcohol Clin Exp Res 2005;29(5):844–54. [22] McPherson TL, Hersch RK. Brief substance use screening instruments for primary care settings: a review. J Subst Abuse Treat 2000;18(2):193–202. [23] Ewing JA. Detecting alcoholism. The CAGE questionnaire. JAMA 1984;252(14):1905–7. [24] Ashman TA, Schwartz ME, Cantor JB, Hibbard MR, Gordon WA. Screening for substance abuse in individuals with traumatic brain injury. Brain Injury: [BI] 2004;18(2):191–202. [25] United States Department of Health and Human Services. Substance Abuse and Mental Health Services Administration. Office of Applied S. National Household Survey on Drug Abuse, 1992. Inter-university Consortium for Political and Social Research (ICPSR) [distributor]; 2008. [26] Kroenke K, Spitzer RL, Williams JB. The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med 2001;16(9):606–13. [27] Honarmand K, Feinstein A. Validation of the Hospital Anxiety and Depression Scale for use with multiple sclerosis patients. Mult Scler 2009;15(12):1518–24. [28] Slater RJ. Criteria and uses of the Minimal Record of Disability in multiple sclerosis. Acta Neurol Scand Suppl 1984;101:16–20. [29] Sharrack B, Hughes RA. Clinical scales for multiple sclerosis. J Neurol Sci 1996;135(1):1–9. [30] Pittock SJ, Mayr WT, McClelland RL, Jorgensen NW, Weigand SD, Noseworthy JH, et al. Disability profile of MS did not change over 10 years in a population-based. Neurology 2004;62(4):601–6. [31] Burks JS, Johnson KP. Multiple sclerosis: diagnosis, medical management, and rehabilitation. New York, NY: Demos Medical Publishing, Inc.; 2000. [32] Alschuler KN, Jensen MP, Ehde DM. Defining mild, moderate, and severe pain in persons with multiple sclerosis. Pain Med 2012;13(10):1358–65. [33] Jensen MP, Turner JA, Romano JM, Fisher LD. Comparative reliability and validity of chronic pain intensity measures. Pain 1999;83(2):157–62. [34] United States Department of Health and Human Services. Substance Abuse and Mental Health Services Administration. Office of Applied Studies. National Household Survey on Drug Abuse, 1995. ICPSR06950-v2. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2013-05-06. [35] Bradley KA, DeBenedetti AF, Volk RJ, Williams EC, Frank D, Kivlahan DR. AUDIT-C as a brief screen for alcohol misuse in primary care. Alcohol Clin Exp Res 2007;31(7):1208–17. [36] Rubinsky ADKD, Volk RJ, Maynard C, Bradley KA. Estimating risk of alcohol dependence using alcohol screening scores. Drug Alcohol Depend 2010;108(1–2):29–36. [37] Bradley KA, Boyd-Wickizer J, Powell SH, Burman ML. Alcohol screening questionnaires in women: a critical review. JAMA 1998;280(2):166–71. [38] Becker WC, Sullivan LE, Tetrault JM, Desai RA, Fiellin DA. Non-medical use, abuse and dependence on prescription opioids among U.S. adults: psychiatric, medical and substance use correlates. Drug Alcohol Depend 2008;94(1–3):38–47. [39] Lopes MAFE, Ferrioli E, Litvoc J, Bottino CM. Prevalence of alcohol-related problems in an elderly population and their association with cognitive impairment and dementia. Alcohol Clin Exp Res 2010;34(4):726–33.