JOURNAL OF DUAL DIAGNOSIS, 11(1), 75–82, 2015 C Foundations Recovery Network Copyright ISSN: 1550-4263 print / 1550-4271 online DOI: 10.1080/15504263.2014.993263
Differences Between Older and Younger Adults in Residential Treatment for Co-Occurring Disorders Siobhan A. Morse, MHSA, CRC, CAI, MAC,1 Cayce Watson, MSW,2 Samuel A. MacMaster, PhD, MSW,3 and Brian E. Bride, PhD, MSW, MPH4
Objective: The purpose of this study was to examine differences between older and younger adults who received integrated treatment for co-occurring substance use and mental disorders, including differences on demographic and baseline characteristics (e.g., substance use, readiness for change, mental health symptoms, and severity of problems associated with substance use), as well as predictors of retention in treatment. Methods: This study included 1400 adults who received integrated substance abuse and mental health treatment services at one of two private residential facilities offering residential and outpatient services. Initial analyses consisted of basic descriptive and bivariate analyses to examine differences between older (≥ 50 years old) and younger (< 50 years old) adults on baseline variables. Next, three ordinary least squares regression models were employed to examine the influence of baseline characteristics on length of stay. Results: Three main findings emerged. First, older adults differed from younger adults on pretreatment characteristics. Older adults used more alcohol and experienced greater problem severity in the medical and alcohol domains, while younger adults used more illicit drugs (e.g., heroin, marijuana, and cocaine) and experienced problems in the drug, legal, and family/social domains. Second, while readiness to change did not differ between groups at baseline, older adults remained enrolled in treatment for a shorter period of time (nearly four days on average) than younger adults. Third, the pattern of variables that influenced length of stay in treatment for older adults differed from that of younger adults. Treatment retention for older adults was most influenced by internal factors, like psychological symptoms and problems, while younger adults seemed influenced primarily by external factors, like drug use, employment difficulties, and readiness for change. Conclusions: The results of this study add to the limited knowledge base regarding older adults receiving integrated treatment for co-occurring substance use and mental health disorders by documenting that age-based differences exist in general and in the factors that are associated with the length of stay in residential treatment. (Journal of Dual Diagnosis, 11:75–82, 2015)
Keywords co-occurring disorders, residential treatment, older adults, retention, addiction severity, mental health, substance use
With the aging of the baby boom generation, older adults have become the fastest-growing segment of the U.S. population. The population aged 50 and older, in particular, is estimated to increase 52% by 2020 over 1999 to 2001 estimates (Neve, Lemmens, & Drop, 1999; Colliver, Compton, Gfroerer, & Condon, 2006). High rates of substance abuse have been identified among older adults and are expected to increase (Wetterling, Veltrup, John, & Dreiessen, 2003; Colliver et al., 2006; Han, Gfoerer, Colliver, & Penne, 2009; Moos, Schutte, Brennan, & Moos, 2011; Cooper, 2012; Wang & Andrade, 2013). Colliver et al. (2006) estimate the number of illicit drug users aged 50 and older will increase to over 3 million by 2020. Current estimates of illicit drug use appear to be 1Foundations
Recovery Network, Brentwood, Tennessee, USA of Social Work and Sociology, Lipscomb University, Nashville, Tennessee, USA 3University of Tennessee, College of Social Work-Knoxville, Nashville, Tennessee, USA 4Georgia State University, School of Social Work, Atlanta, Georgia, USA Address correspondence to Siobhan A. Morse, MHSA, CRC, CAI, MAC, Foundations Recovery Network, 5409 Maryland Way, Suite 320, Brentwood, TN 37027, USA. E-mail: [email protected] 2Department
consistent with such predictions. Over the past decade, illicit drug use among adults aged 50 to 64 more than doubled from 3.4% to 7.2% (Substance Abuse and Mental Health Services Administration, 2013). From 2002 to 2012, non-medical use of prescriptions increased significantly among adults aged 50 to 59 and marijuana use significantly increased among adults aged 50 to 64 (Substance Abuse and Mental Health Services Administration, 2013). The higher substance use rates of this generation in tandem with the volume of the cohort suggest that special attention should be given to the treatment needs of this population. The most commonly abused substance is alcohol (Lin, Zhang, Leung, & Clark, 2011), and a number of studies have attempted to characterize problem alcohol use in older adults. Alcohol abuse in older adults is often referred to as either early-onset or late-onset, a distinction that accounts for differences in characteristics, comorbidity, and impairment associated with alcohol abuse in this population (Wetterling et al., 2003). Christie et al. (2013) have further identified a subgroup of problem drinkers aged 60 and older, referred to as “late-onset reactors,” who do not self-identify as having a drinking problem until their late 50s. Despite that alcohol
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intake tends to decrease with advancing age, a high proportion of older adults drink in excess of recommended guidelines (McEvoy, Kritz-Silverstein, BarrettConnor, Bergstrom, & Laughlin, 2013). In addition, older adult problem drinkers consume alcohol in comparable amounts to their younger counterparts (Christie, Bamber, Powell, Arrindell, & Pant, 2013). Older adults with substance use disorders are at risk for a range of emotional, functional, financial, social, and health problems (Blazer, 2013). They accrue risk of injury, death, and other adverse events at lower consumption levels than younger counterparts (Fink et al., 2002; Sorock, Chen, Gonzalgo, & Baker, 2006). In addition, problem drinkers who are older evidence declines in functional status particularly in cognitive ability, depression, and comorbidity (Fink et al., 2002). Older adults are also more sensitive to treatment barriers and less likely to recognize symptoms of addiction and therefore are less likely to receive treatment (Cooper, 2012). Older adults are also less likely to perceive the need for treatment or to be sensitive to barriers to treatment, such as stigma, lack of information and transportation, and cultural barriers (Eden, Maslow, Le, & Blazer, 2012). In addition to having high rates of substance use disorders, older adults often present with mental health issues that further complicate the diagnosis, treatment, and referral process. Twenty percent of older adults in the general population have a psychiatric disorder, most commonly depression or anxiety (Bartels, Blow, Brockmann, & Van Citters, 2005; Lin et al., 2011). Adults aged 50 and older account for 16% of individuals reporting mental illness (Substance Abuse and Mental Health Services Administration, 2013). The Centers for Disease Control and Prevention (CDC) estimate that seven million adults experience depression during later life (CDC, 2012). Further, the higher incidence of chronic health conditions among older adults population elevates risk of depression (CDC, 2012). The relationship between substance abuse and mental illness in older adults is such that a history of one is associated with increased risk of the other (Bartels et al., 2005; Pennay et al., 2011; Salmon & Forester, 2012). Most commonly, substance abuse co-occurs with depression and anxiety (Devanand, 2002). Older adults who are depressed are up to four times more likely to have alcohol-related problems than their counterparts who are not depressed (Devandad, 2002). Rates of lifetime substance abuse are also high among individuals with bipolar disorder (Cassidy, Ahearn, & Carroll, 2001), and bipolar depressive episodes may intensify with age (Coryell, Fiedorowicz, Solomon, & Endicott, 200). Among patients hospitalized with bipolar disorder, Cassidy et al. (2001) found that 43.9% had problems with drug abuse. Given the likelihood of comorbidity, it is important that older adults who present for mental health treatment be assessed for substance abuse (Salmon & Forester, 2011). Growing demographics, gaps in service delivery, and increasing demands for mental health services have resulted Journal of Dual Diagnosis
in depression often going untreated in older adults (Bartels & Smyer, 2002). Further, the treatment of depression is often complicated by multiple presenting problems including comorbid mental health disorders and psychosocial stressors (Proctor, Hasche, Morrow-Howell, Shumway, & Snell, 2008). Older adults presenting with co-occurring mental health diagnoses are at risk for poorer physical and behavioral health outcomes and are less likely to have positive responses to therapy and medication management (Wuthrich & Rapee, 2013). In addition to these risks, older adults with depression may experience declines in memory (Deluca et al., 2005). Wuthrich and Rapee (2013) suggest that higher rates of comorbidity, risk of worsening health-related outcomes, and competing diagnostic symptoms in older adults prompt the need for special consideration during treatment planning, specifically for older adults presenting with co-occurring disorders. Further, engaging the older adult population in mental health treatment is challenging due to their reticence to prioritize treatment among multiple overwhelming life stressors including chronic health conditions and other cognitive, emotional, or social issues (Proctor et al., 2008). As such, it is increasingly important that older adults be assessed and treated for co-occurring substance use and mental health disorders. Research has consistently demonstrated that retention in addiction treatment is positively associated with a range of post-treatment outcomes, including increased abstinence, greater participation in continuing care, higher levels of employment, and lower rates of relapse and readmission (Chi, Sartre, & Weisner, 2006; Claus et al., 2007; Greenfield et al., 2004; Luchansky, Brown, Loghi, Stark, & Krupski, 2000; Wallace & Weeks, 2004; Zarkin, Dunlap, Bray, & Wechsburg, 2002). Unfortunately, research also indicates that clients with co-occurring disorders have lower rates of treatment completion, shorter stays in treatment, and higher rates of relapse and readmission (Compton, Cottler, Jacobs, Ben-Abdallah, & Spitznagel, 2003; Weisner, Matzger, & Kaskutas, 2003). Consequently, a central goal in treating clients with co-occurring disorders is to increase treatment retention. Successful development or implementation of strategies to increase retention requires more knowledge regarding factors that influence patient length of stay in treatment, as well as differences in said influences across subgroups. Unfortunately, little is known regarding predictors of treatment retention among individuals seeking treatment for co-occurring disorders. The purpose of this study was to examine differences between older and younger adults who received integrated treatment for co-occurring substance use and mental disorders. In particular, we examined differences on demographic and baseline characteristics including recent substance use, readiness for change, mental health symptoms, and severity of problems associated with substance use. In addition, we examined predictors of retention in treatment and differences between older and younger adults in patterns of said predictors.
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METHODS
University of Rhode Island Change Assessment (URICA)
Sample and Procedure This study utilized data from 1400 adults who received integrated substance abuse and mental health treatment services between 2009 and 2011 at either of two private residential facilities operated by Foundations Recovery Network (FRN), a private for-profit treatment provider offering residential and outpatient services. Though the facilities are located in Tennessee and California, service recipients are drawn from across the United States and Canada. Treatment was delivered within an integrated model of evidence-based mental health and substance abuse services consisting of individual and group interventions (FRN, 2010). The study was conducted in accordance with the Declaration of Helsinki and was approved and monitored by the Foundations Recovery Network Humans Subjects Committee. Trained intake professionals located at each facility described data collection to and obtained written informed consent from study participants following a complete discussion of the study. Baseline data on recent substance use, readiness for change, mental health symptoms, and substance use severity was collected within 72 hours following admission by a master’s-level clinician. Retention data were collected through a retrospective review of discharge records. Instruments Addiction Severity Index (ASI) Recent substance use, addiction severity, and mental health indicators were measured with the ASI (McLellan, Luborsky, Woody, O’Brien, & Druley, 1983; McLellan et al., 1992). For recent substance use, participants indicated how many days in the past month they used a range of specific substances. Addiction severity was measured with the ASI’s composite severity indices in each of seven potential problem areas: medical, employment, alcohol, drug, legal, family/social, and psychiatric problems. In order to ensure that each question within a given problem area is given the same weight in calculation of the composite index, each item is divided by its maximum value and by the total number of questions assigned to each composite problem area. This scoring yields a score from 0 to1 for each composite index, with higher scores indicating greater severity. As mental health indicators, we used 10 individual items from the psychiatric status section of the ASI. Eight of these items indicate whether a respondent has had a significant period of time in which they have experienced symptoms not as a result of substance use in the following domains: depression, anxiety, hallucinations, cognitive difficulties (trouble understanding, concentrating, or remembering), violence (trouble controlling violent behavior), suicidal ideation, attempted suicide, and medication prescribed for psychological or emotional problems.
The URICA (DiClemente & Hughes, 1990) is a measure of readiness to change that has been studied with a variety of populations. It consists of 32 statements that participants endorse on a 5-point scale from strongly agree to strongly disagree. The URICA yields scores on each of four subscales corresponding with the stages of change (precontemplation, contemplation, action, and maintenance) described by Prochaska, DiClemente, and Norcross (1992). A readiness to change composite score can be derived by adding the contemplation, action, and maintenance subscales and subtracting the precontemplation subscore (Project MATCH Research Group, 1997). The readiness to change composite score was used as the measure for readiness to change.
Treatment Retention Treatment retention was operationalized as length of stay and calculated by the total number of days between program start date and discharge date.
Data Analysis Initial analyses consisted of basic descriptive statistics and bivariate analyses to examine differences between older (50 + years of age) and younger (less than 50 years of age) adults on pre-treatment demographic, substance use, addiction severity, and mental health variables. Next, three ordinary least squares regression models were employed to examine the influence of baseline characteristics on length of stay. Model 1 employed the entire sample and included group membership (older versus younger adult) as a variable to determine whether there was a difference between groups on length of stay after controlling for demographic and baseline characteristics including recent substance use, readiness for change, mental health symptoms, and addiction severity. Models 2 and 3 were run on the subsamples of younger and older adults respectively in order to determine whether the predictors of retention were the same for older and younger adults. These models regressed length of stay on the same demographic and baseline characteristics included in model 1.
RESULTS Table 1 displays results of bivariate analysis of study variables comparing younger and older adults. There were no differences between groups on gender, with 60% (n = 844) of the sample being male. The most frequently used substance in the past 30 days was alcohol (M = 12.21 days, SD = 11.74) followed by opiates other than heroin and methadone (M = 5.84 days, 2015, Volume 11, Number 1
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TABLE 1 Bivariate Analyses of Study Variables Comparing Younger and Older Adults (N = 1400) Younger Adults (n = 1168) Variable Gender (male) Substance use1 Alcohol Cocaine Heroin Non-Rx Methadone Other opiates Marijuana Barbiturates Sedatives Amphetamines Addiction Severity Index1 Medical Employment/Support Alcohol Drug Legal Family/Social Psychiatric Mental health indicators1 Depression Anxiety Hallucinations Cognition Violence Suicidal ideation Suicide attempt Psych medication Problem frequency Bothered by problems Readiness for change Length of stay
n, M (SD)
Older Adults (n = 232)
n (%)
n, M (SD)
713 (61.0%)
n (%) 131 (56.5%)
Statistic χ 2 = 1.65
1166, 11.63 (11.58) 1148, 3.28 (7.48) 1144, 2.71 (7.83) 1139, 0.85 (4.37) 1143, 6.16 (10.69) 1143, 5.12 (9.77) 1138, 0.65 (3.87) 1140, 4.15 (8.76) 1144, 1.22 (5.06)
229,15.07 (12.08) 219, 1.90 (5.95) 217, 0.27 (2.78) 216, 0.72 (4.10) 216, 4.00 (9.15) 217, 2.10 (6.89) 215, 0.77 (4.35) 215, 2.92 (8.09) 216, 0.51 (3.36)
t = −4.07∗∗∗ t = 2.57∗∗ t = 4.53∗∗∗ t = 0.39 t = 2.79∗∗ t = 4.35∗∗∗ t = −0.41 t = 1.92 t = 1.97∗
1153, 0.264 (0.361) 1149, 0.421 (0.277) 1063, 0.365 (0.344) 1042, 0.191 (0.168) 1145, 0.136 (0.232) 1117, 0.326 (0.264) 1113, 0.497 (0.215)
227, 0.402 (0.398) 225, 0.393 (0.261) 196, 0.456 (0.353) 203, 0.114 (0.146) 226, 0.067 (0.170) 221, 0.270 (0.276) 225, 0.474 (0.218)
t = −5.15∗∗∗ t = 1.43 t = −3.40∗∗∗ t = 6.13∗∗∗ t = 4.27∗∗∗ t = 2.86∗∗ t = 1.43
840/1155 (72.7%) 953/1157 (82.4%) 84/1158 (7.3%) 640/1159 (55.2%) 232/1158 (20.0%) 211/1161 (18.2%) 63/1161 (5.4%) 702/1151 (61.0%) 1143, 21.95 (11.26) 1149, 2.85 (1.38) 1168, 10.94 (1.59) 1168, 31.26 (17.62)
168/229 (73.4%) 186/231 (80.5%) 18/230 (7.8%) 118/229 (51.5%) 25/229 (10.9%) 43/230 (18.7%) 15/230 (6.5%) 141/231 (61.0%) 230, 21.53 (11.47) 231, 2.67 (1.42) 232, 10.77 (1.85) 230, 27.50 (13.79)
χ 2 = .040 χ 2 = 0.45 χ 2 = 0.09 χ 2 = 1.05 χ 2 = 10.53∗∗∗ χ 2 = 0.04 χ 2 = 0.44 χ 2 = 0.00 t = 0.52 t = 1.76 t = 1.40 t = 3.06∗∗
Note. 1Time frame is past month. < .05; ∗∗ p < .01; ∗∗∗ p < .001.
∗p
SD = 10.50), marijuana (M = 4.65 days, SD = 9.43), sedatives (M = 3.99 days, SD = 8.70), and cocaine (M = 3.09 days, SD = 7.32). Older adults used alcohol more frequently than younger adults, while younger adults used cocaine, heroin, other opiates, marijuana, and amphetamines more frequently than older adults. Indicators of baseline addiction severity, mental health, and readiness for change were also compared for younger and older adults. Statistically significant differences were found between younger and older adults on five of the seven ASI composite indices. Older adults had higher composite scores on the medical and alcohol indices, while younger adults had higher composite scores in the drug, legal, and family indices. No differences were found between groups on the employment and psychological indices. In addition, younger and older adults did not differ on the measure of readiness for change. Most participants reported experiencing anxiety (82%, 1139/1388) and/or depression (73%, 1008/1384) during the Journal of Dual Diagnosis
month prior to entry, and more than half (55%, 758/1388) reported experiencing cognitive difficulties such as trouble understanding, concentrating, or remembering. Psychiatric medications were prescribed to 61% of patients (843/1388) during the baseline period. About one-fifth of patients reported difficulty controlling violent behavior (19%, 257/1387) and/or suicidal ideation (18%, 254/1391) at baseline. Seven percent of patients (102/1388) reported hallucinations and 6% (78/1391) reported suicide attempts during the baseline period. On average, patients reported experiencing these psychological or emotional problems on 22 of the past 30 days (SD = 11.29). Only 1 of the 10 mental health indicators was found to differ significantly between groups. Nearly twice as many (20% versus 11%) younger adults than older adults experienced trouble controlling violent behavior at baseline. For the sample as a whole, the mean length of stay was 30.7 days (SD = 17.22). In comparing younger and older adults on length of stay, a statistically significant difference
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TABLE 2 Ordinary Least Squares Regression of Length of Stay on Study Variables (n = 10851)
Variable Gender (male) Substance use2 Alcohol Cocaine Heroin Non-Rx methadone Other opiates Marijuana Barbiturates Sedatives Amphetamines Addiction Severity Index2 Medical Employment/support Alcohol Drug Legal Family/social Psychiatric Mental health indicators2 Depression Anxiety Hallucinations Cognition Violence Suicidal ideation Suicide attempt Psych medication Problem frequency Bothered by problems Readiness for change Older adult
Full Sample (n = 1085)
Younger Adults (n = 912)
β (SE)
β (SE)
p Value
β (SE)
p Value
p Value
Older Adults (n = 173)
−3.56 (1.08)
.001
−4.02 (1.22)
.001
−0.67 (2.28)
.770
0.07 (0.10) 0.18 (0.09) 0.07 (0.09) −0.25 (0.13) −0.16 (0.07) 0.02 (0.07) −0.22 (0.13) −0.02 (0.07) 0.14 (0.12)
.490 .055 .411 .054 .022 .828 .096 .762 .257
0.07 (0.12) 0.15 (0.10) 0.09 (0.09) −0.35 (0.15) −0.17 (0.07) −0.04 (0.07) −0.32 (0.15) 0.01 (0.08) 0.15 (0.13)
.559 .140 .335 .015 .026 .625 .031 .931 .265
0.21 (0.24) 0.39 (0.26) 0.05 (0.20) −0.24 (0.38) −0.04 (0.30) −0.24 (0.20) 0.19 (0.28) −0.09 (0.18) −0.08 (0.37)
.371 .133 .796 .524 .906 .226 .501 .605 .825
2.53 (1.69) 7.02 (2.19) −2.79 (4.00) 5.80 (7.68) 3.03 (2.67) 2.42 (2.38) −0.44 (31.33)
.135 .001 .484 .451 .258 .310 .989
−3.33 (2.76) 6.32 (4.11) −4.87 (8.53) −1.51 (18.00) 12.12 (6.54) 2.62 (4.20) 131.73 (48.94)
.230 .127 .569 .933 .066 .534 .008
−1.40 (3.45) 3.85 (3.74) 3.77 (3.71) 2.64 (3.19) −2.07 (3.22) 4.03 (3.25) 6.60 (4.01) 0.49 (3.24) −0.52 (0.12) −1.04 (1.30) 1.06 (0.39) —
.685 .303 .310 .407 .520 .215 .101 .881 .674 .423 .007
−14.18 (5.82) −6.88 (5.82) −17.38 (6.65) −10.94 (5.08) −17.29 (5.73) −8.43 (5.60) −18.80 (7.57) −10.03 (5.12) −0.40 (0.20) −5.00 (2.18) 0.77 (0.67) —
.016 .239 .010 .033 .003 .135 .014 .052 .051 .024 .255
1.59 (1.47) 7.19 (1.94) −2.66 (3.60) 3.09 (6.99) 4.84 (2.43) 2.31 (2.08) 22.79 (27.02) −3.42 (3.00) 1.10 (3.20) −0.06 (3.25) 0.09 (2.76) −4.96 (2.81) 1.82 (2.83) 1.86 (3.54) −1.30 (2.80) −0.12 (0.11) −1.58 (1.14) 0.96 (0.34) −3.12 (1.42)
.165
Differences Between Older and Younger Adults in Residential Treatment for Co-Occurring Disorders Siobhan A. Morse, MHSA, CRC, CAI, MAC,1 Cayce Watson, MSW,2 Samuel A. MacMaster, PhD, MSW,3 and Brian E. Bride, PhD, MSW, MPH4
Objective: The purpose of this study was to examine differences between older and younger adults who received integrated treatment for co-occurring substance use and mental disorders, including differences on demographic and baseline characteristics (e.g., substance use, readiness for change, mental health symptoms, and severity of problems associated with substance use), as well as predictors of retention in treatment. Methods: This study included 1400 adults who received integrated substance abuse and mental health treatment services at one of two private residential facilities offering residential and outpatient services. Initial analyses consisted of basic descriptive and bivariate analyses to examine differences between older (≥ 50 years old) and younger (< 50 years old) adults on baseline variables. Next, three ordinary least squares regression models were employed to examine the influence of baseline characteristics on length of stay. Results: Three main findings emerged. First, older adults differed from younger adults on pretreatment characteristics. Older adults used more alcohol and experienced greater problem severity in the medical and alcohol domains, while younger adults used more illicit drugs (e.g., heroin, marijuana, and cocaine) and experienced problems in the drug, legal, and family/social domains. Second, while readiness to change did not differ between groups at baseline, older adults remained enrolled in treatment for a shorter period of time (nearly four days on average) than younger adults. Third, the pattern of variables that influenced length of stay in treatment for older adults differed from that of younger adults. Treatment retention for older adults was most influenced by internal factors, like psychological symptoms and problems, while younger adults seemed influenced primarily by external factors, like drug use, employment difficulties, and readiness for change. Conclusions: The results of this study add to the limited knowledge base regarding older adults receiving integrated treatment for co-occurring substance use and mental health disorders by documenting that age-based differences exist in general and in the factors that are associated with the length of stay in residential treatment. (Journal of Dual Diagnosis, 11:75–82, 2015)
Keywords co-occurring disorders, residential treatment, older adults, retention, addiction severity, mental health, substance use
With the aging of the baby boom generation, older adults have become the fastest-growing segment of the U.S. population. The population aged 50 and older, in particular, is estimated to increase 52% by 2020 over 1999 to 2001 estimates (Neve, Lemmens, & Drop, 1999; Colliver, Compton, Gfroerer, & Condon, 2006). High rates of substance abuse have been identified among older adults and are expected to increase (Wetterling, Veltrup, John, & Dreiessen, 2003; Colliver et al., 2006; Han, Gfoerer, Colliver, & Penne, 2009; Moos, Schutte, Brennan, & Moos, 2011; Cooper, 2012; Wang & Andrade, 2013). Colliver et al. (2006) estimate the number of illicit drug users aged 50 and older will increase to over 3 million by 2020. Current estimates of illicit drug use appear to be 1Foundations
Recovery Network, Brentwood, Tennessee, USA of Social Work and Sociology, Lipscomb University, Nashville, Tennessee, USA 3University of Tennessee, College of Social Work-Knoxville, Nashville, Tennessee, USA 4Georgia State University, School of Social Work, Atlanta, Georgia, USA Address correspondence to Siobhan A. Morse, MHSA, CRC, CAI, MAC, Foundations Recovery Network, 5409 Maryland Way, Suite 320, Brentwood, TN 37027, USA. E-mail: [email protected] 2Department
consistent with such predictions. Over the past decade, illicit drug use among adults aged 50 to 64 more than doubled from 3.4% to 7.2% (Substance Abuse and Mental Health Services Administration, 2013). From 2002 to 2012, non-medical use of prescriptions increased significantly among adults aged 50 to 59 and marijuana use significantly increased among adults aged 50 to 64 (Substance Abuse and Mental Health Services Administration, 2013). The higher substance use rates of this generation in tandem with the volume of the cohort suggest that special attention should be given to the treatment needs of this population. The most commonly abused substance is alcohol (Lin, Zhang, Leung, & Clark, 2011), and a number of studies have attempted to characterize problem alcohol use in older adults. Alcohol abuse in older adults is often referred to as either early-onset or late-onset, a distinction that accounts for differences in characteristics, comorbidity, and impairment associated with alcohol abuse in this population (Wetterling et al., 2003). Christie et al. (2013) have further identified a subgroup of problem drinkers aged 60 and older, referred to as “late-onset reactors,” who do not self-identify as having a drinking problem until their late 50s. Despite that alcohol
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intake tends to decrease with advancing age, a high proportion of older adults drink in excess of recommended guidelines (McEvoy, Kritz-Silverstein, BarrettConnor, Bergstrom, & Laughlin, 2013). In addition, older adult problem drinkers consume alcohol in comparable amounts to their younger counterparts (Christie, Bamber, Powell, Arrindell, & Pant, 2013). Older adults with substance use disorders are at risk for a range of emotional, functional, financial, social, and health problems (Blazer, 2013). They accrue risk of injury, death, and other adverse events at lower consumption levels than younger counterparts (Fink et al., 2002; Sorock, Chen, Gonzalgo, & Baker, 2006). In addition, problem drinkers who are older evidence declines in functional status particularly in cognitive ability, depression, and comorbidity (Fink et al., 2002). Older adults are also more sensitive to treatment barriers and less likely to recognize symptoms of addiction and therefore are less likely to receive treatment (Cooper, 2012). Older adults are also less likely to perceive the need for treatment or to be sensitive to barriers to treatment, such as stigma, lack of information and transportation, and cultural barriers (Eden, Maslow, Le, & Blazer, 2012). In addition to having high rates of substance use disorders, older adults often present with mental health issues that further complicate the diagnosis, treatment, and referral process. Twenty percent of older adults in the general population have a psychiatric disorder, most commonly depression or anxiety (Bartels, Blow, Brockmann, & Van Citters, 2005; Lin et al., 2011). Adults aged 50 and older account for 16% of individuals reporting mental illness (Substance Abuse and Mental Health Services Administration, 2013). The Centers for Disease Control and Prevention (CDC) estimate that seven million adults experience depression during later life (CDC, 2012). Further, the higher incidence of chronic health conditions among older adults population elevates risk of depression (CDC, 2012). The relationship between substance abuse and mental illness in older adults is such that a history of one is associated with increased risk of the other (Bartels et al., 2005; Pennay et al., 2011; Salmon & Forester, 2012). Most commonly, substance abuse co-occurs with depression and anxiety (Devanand, 2002). Older adults who are depressed are up to four times more likely to have alcohol-related problems than their counterparts who are not depressed (Devandad, 2002). Rates of lifetime substance abuse are also high among individuals with bipolar disorder (Cassidy, Ahearn, & Carroll, 2001), and bipolar depressive episodes may intensify with age (Coryell, Fiedorowicz, Solomon, & Endicott, 200). Among patients hospitalized with bipolar disorder, Cassidy et al. (2001) found that 43.9% had problems with drug abuse. Given the likelihood of comorbidity, it is important that older adults who present for mental health treatment be assessed for substance abuse (Salmon & Forester, 2011). Growing demographics, gaps in service delivery, and increasing demands for mental health services have resulted Journal of Dual Diagnosis
in depression often going untreated in older adults (Bartels & Smyer, 2002). Further, the treatment of depression is often complicated by multiple presenting problems including comorbid mental health disorders and psychosocial stressors (Proctor, Hasche, Morrow-Howell, Shumway, & Snell, 2008). Older adults presenting with co-occurring mental health diagnoses are at risk for poorer physical and behavioral health outcomes and are less likely to have positive responses to therapy and medication management (Wuthrich & Rapee, 2013). In addition to these risks, older adults with depression may experience declines in memory (Deluca et al., 2005). Wuthrich and Rapee (2013) suggest that higher rates of comorbidity, risk of worsening health-related outcomes, and competing diagnostic symptoms in older adults prompt the need for special consideration during treatment planning, specifically for older adults presenting with co-occurring disorders. Further, engaging the older adult population in mental health treatment is challenging due to their reticence to prioritize treatment among multiple overwhelming life stressors including chronic health conditions and other cognitive, emotional, or social issues (Proctor et al., 2008). As such, it is increasingly important that older adults be assessed and treated for co-occurring substance use and mental health disorders. Research has consistently demonstrated that retention in addiction treatment is positively associated with a range of post-treatment outcomes, including increased abstinence, greater participation in continuing care, higher levels of employment, and lower rates of relapse and readmission (Chi, Sartre, & Weisner, 2006; Claus et al., 2007; Greenfield et al., 2004; Luchansky, Brown, Loghi, Stark, & Krupski, 2000; Wallace & Weeks, 2004; Zarkin, Dunlap, Bray, & Wechsburg, 2002). Unfortunately, research also indicates that clients with co-occurring disorders have lower rates of treatment completion, shorter stays in treatment, and higher rates of relapse and readmission (Compton, Cottler, Jacobs, Ben-Abdallah, & Spitznagel, 2003; Weisner, Matzger, & Kaskutas, 2003). Consequently, a central goal in treating clients with co-occurring disorders is to increase treatment retention. Successful development or implementation of strategies to increase retention requires more knowledge regarding factors that influence patient length of stay in treatment, as well as differences in said influences across subgroups. Unfortunately, little is known regarding predictors of treatment retention among individuals seeking treatment for co-occurring disorders. The purpose of this study was to examine differences between older and younger adults who received integrated treatment for co-occurring substance use and mental disorders. In particular, we examined differences on demographic and baseline characteristics including recent substance use, readiness for change, mental health symptoms, and severity of problems associated with substance use. In addition, we examined predictors of retention in treatment and differences between older and younger adults in patterns of said predictors.
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Older and Younger Adults in Residential Treatment
METHODS
University of Rhode Island Change Assessment (URICA)
Sample and Procedure This study utilized data from 1400 adults who received integrated substance abuse and mental health treatment services between 2009 and 2011 at either of two private residential facilities operated by Foundations Recovery Network (FRN), a private for-profit treatment provider offering residential and outpatient services. Though the facilities are located in Tennessee and California, service recipients are drawn from across the United States and Canada. Treatment was delivered within an integrated model of evidence-based mental health and substance abuse services consisting of individual and group interventions (FRN, 2010). The study was conducted in accordance with the Declaration of Helsinki and was approved and monitored by the Foundations Recovery Network Humans Subjects Committee. Trained intake professionals located at each facility described data collection to and obtained written informed consent from study participants following a complete discussion of the study. Baseline data on recent substance use, readiness for change, mental health symptoms, and substance use severity was collected within 72 hours following admission by a master’s-level clinician. Retention data were collected through a retrospective review of discharge records. Instruments Addiction Severity Index (ASI) Recent substance use, addiction severity, and mental health indicators were measured with the ASI (McLellan, Luborsky, Woody, O’Brien, & Druley, 1983; McLellan et al., 1992). For recent substance use, participants indicated how many days in the past month they used a range of specific substances. Addiction severity was measured with the ASI’s composite severity indices in each of seven potential problem areas: medical, employment, alcohol, drug, legal, family/social, and psychiatric problems. In order to ensure that each question within a given problem area is given the same weight in calculation of the composite index, each item is divided by its maximum value and by the total number of questions assigned to each composite problem area. This scoring yields a score from 0 to1 for each composite index, with higher scores indicating greater severity. As mental health indicators, we used 10 individual items from the psychiatric status section of the ASI. Eight of these items indicate whether a respondent has had a significant period of time in which they have experienced symptoms not as a result of substance use in the following domains: depression, anxiety, hallucinations, cognitive difficulties (trouble understanding, concentrating, or remembering), violence (trouble controlling violent behavior), suicidal ideation, attempted suicide, and medication prescribed for psychological or emotional problems.
The URICA (DiClemente & Hughes, 1990) is a measure of readiness to change that has been studied with a variety of populations. It consists of 32 statements that participants endorse on a 5-point scale from strongly agree to strongly disagree. The URICA yields scores on each of four subscales corresponding with the stages of change (precontemplation, contemplation, action, and maintenance) described by Prochaska, DiClemente, and Norcross (1992). A readiness to change composite score can be derived by adding the contemplation, action, and maintenance subscales and subtracting the precontemplation subscore (Project MATCH Research Group, 1997). The readiness to change composite score was used as the measure for readiness to change.
Treatment Retention Treatment retention was operationalized as length of stay and calculated by the total number of days between program start date and discharge date.
Data Analysis Initial analyses consisted of basic descriptive statistics and bivariate analyses to examine differences between older (50 + years of age) and younger (less than 50 years of age) adults on pre-treatment demographic, substance use, addiction severity, and mental health variables. Next, three ordinary least squares regression models were employed to examine the influence of baseline characteristics on length of stay. Model 1 employed the entire sample and included group membership (older versus younger adult) as a variable to determine whether there was a difference between groups on length of stay after controlling for demographic and baseline characteristics including recent substance use, readiness for change, mental health symptoms, and addiction severity. Models 2 and 3 were run on the subsamples of younger and older adults respectively in order to determine whether the predictors of retention were the same for older and younger adults. These models regressed length of stay on the same demographic and baseline characteristics included in model 1.
RESULTS Table 1 displays results of bivariate analysis of study variables comparing younger and older adults. There were no differences between groups on gender, with 60% (n = 844) of the sample being male. The most frequently used substance in the past 30 days was alcohol (M = 12.21 days, SD = 11.74) followed by opiates other than heroin and methadone (M = 5.84 days, 2015, Volume 11, Number 1
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TABLE 1 Bivariate Analyses of Study Variables Comparing Younger and Older Adults (N = 1400) Younger Adults (n = 1168) Variable Gender (male) Substance use1 Alcohol Cocaine Heroin Non-Rx Methadone Other opiates Marijuana Barbiturates Sedatives Amphetamines Addiction Severity Index1 Medical Employment/Support Alcohol Drug Legal Family/Social Psychiatric Mental health indicators1 Depression Anxiety Hallucinations Cognition Violence Suicidal ideation Suicide attempt Psych medication Problem frequency Bothered by problems Readiness for change Length of stay
n, M (SD)
Older Adults (n = 232)
n (%)
n, M (SD)
713 (61.0%)
n (%) 131 (56.5%)
Statistic χ 2 = 1.65
1166, 11.63 (11.58) 1148, 3.28 (7.48) 1144, 2.71 (7.83) 1139, 0.85 (4.37) 1143, 6.16 (10.69) 1143, 5.12 (9.77) 1138, 0.65 (3.87) 1140, 4.15 (8.76) 1144, 1.22 (5.06)
229,15.07 (12.08) 219, 1.90 (5.95) 217, 0.27 (2.78) 216, 0.72 (4.10) 216, 4.00 (9.15) 217, 2.10 (6.89) 215, 0.77 (4.35) 215, 2.92 (8.09) 216, 0.51 (3.36)
t = −4.07∗∗∗ t = 2.57∗∗ t = 4.53∗∗∗ t = 0.39 t = 2.79∗∗ t = 4.35∗∗∗ t = −0.41 t = 1.92 t = 1.97∗
1153, 0.264 (0.361) 1149, 0.421 (0.277) 1063, 0.365 (0.344) 1042, 0.191 (0.168) 1145, 0.136 (0.232) 1117, 0.326 (0.264) 1113, 0.497 (0.215)
227, 0.402 (0.398) 225, 0.393 (0.261) 196, 0.456 (0.353) 203, 0.114 (0.146) 226, 0.067 (0.170) 221, 0.270 (0.276) 225, 0.474 (0.218)
t = −5.15∗∗∗ t = 1.43 t = −3.40∗∗∗ t = 6.13∗∗∗ t = 4.27∗∗∗ t = 2.86∗∗ t = 1.43
840/1155 (72.7%) 953/1157 (82.4%) 84/1158 (7.3%) 640/1159 (55.2%) 232/1158 (20.0%) 211/1161 (18.2%) 63/1161 (5.4%) 702/1151 (61.0%) 1143, 21.95 (11.26) 1149, 2.85 (1.38) 1168, 10.94 (1.59) 1168, 31.26 (17.62)
168/229 (73.4%) 186/231 (80.5%) 18/230 (7.8%) 118/229 (51.5%) 25/229 (10.9%) 43/230 (18.7%) 15/230 (6.5%) 141/231 (61.0%) 230, 21.53 (11.47) 231, 2.67 (1.42) 232, 10.77 (1.85) 230, 27.50 (13.79)
χ 2 = .040 χ 2 = 0.45 χ 2 = 0.09 χ 2 = 1.05 χ 2 = 10.53∗∗∗ χ 2 = 0.04 χ 2 = 0.44 χ 2 = 0.00 t = 0.52 t = 1.76 t = 1.40 t = 3.06∗∗
Note. 1Time frame is past month. < .05; ∗∗ p < .01; ∗∗∗ p < .001.
∗p
SD = 10.50), marijuana (M = 4.65 days, SD = 9.43), sedatives (M = 3.99 days, SD = 8.70), and cocaine (M = 3.09 days, SD = 7.32). Older adults used alcohol more frequently than younger adults, while younger adults used cocaine, heroin, other opiates, marijuana, and amphetamines more frequently than older adults. Indicators of baseline addiction severity, mental health, and readiness for change were also compared for younger and older adults. Statistically significant differences were found between younger and older adults on five of the seven ASI composite indices. Older adults had higher composite scores on the medical and alcohol indices, while younger adults had higher composite scores in the drug, legal, and family indices. No differences were found between groups on the employment and psychological indices. In addition, younger and older adults did not differ on the measure of readiness for change. Most participants reported experiencing anxiety (82%, 1139/1388) and/or depression (73%, 1008/1384) during the Journal of Dual Diagnosis
month prior to entry, and more than half (55%, 758/1388) reported experiencing cognitive difficulties such as trouble understanding, concentrating, or remembering. Psychiatric medications were prescribed to 61% of patients (843/1388) during the baseline period. About one-fifth of patients reported difficulty controlling violent behavior (19%, 257/1387) and/or suicidal ideation (18%, 254/1391) at baseline. Seven percent of patients (102/1388) reported hallucinations and 6% (78/1391) reported suicide attempts during the baseline period. On average, patients reported experiencing these psychological or emotional problems on 22 of the past 30 days (SD = 11.29). Only 1 of the 10 mental health indicators was found to differ significantly between groups. Nearly twice as many (20% versus 11%) younger adults than older adults experienced trouble controlling violent behavior at baseline. For the sample as a whole, the mean length of stay was 30.7 days (SD = 17.22). In comparing younger and older adults on length of stay, a statistically significant difference
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TABLE 2 Ordinary Least Squares Regression of Length of Stay on Study Variables (n = 10851)
Variable Gender (male) Substance use2 Alcohol Cocaine Heroin Non-Rx methadone Other opiates Marijuana Barbiturates Sedatives Amphetamines Addiction Severity Index2 Medical Employment/support Alcohol Drug Legal Family/social Psychiatric Mental health indicators2 Depression Anxiety Hallucinations Cognition Violence Suicidal ideation Suicide attempt Psych medication Problem frequency Bothered by problems Readiness for change Older adult
Full Sample (n = 1085)
Younger Adults (n = 912)
β (SE)
β (SE)
p Value
β (SE)
p Value
p Value
Older Adults (n = 173)
−3.56 (1.08)
.001
−4.02 (1.22)
.001
−0.67 (2.28)
.770
0.07 (0.10) 0.18 (0.09) 0.07 (0.09) −0.25 (0.13) −0.16 (0.07) 0.02 (0.07) −0.22 (0.13) −0.02 (0.07) 0.14 (0.12)
.490 .055 .411 .054 .022 .828 .096 .762 .257
0.07 (0.12) 0.15 (0.10) 0.09 (0.09) −0.35 (0.15) −0.17 (0.07) −0.04 (0.07) −0.32 (0.15) 0.01 (0.08) 0.15 (0.13)
.559 .140 .335 .015 .026 .625 .031 .931 .265
0.21 (0.24) 0.39 (0.26) 0.05 (0.20) −0.24 (0.38) −0.04 (0.30) −0.24 (0.20) 0.19 (0.28) −0.09 (0.18) −0.08 (0.37)
.371 .133 .796 .524 .906 .226 .501 .605 .825
2.53 (1.69) 7.02 (2.19) −2.79 (4.00) 5.80 (7.68) 3.03 (2.67) 2.42 (2.38) −0.44 (31.33)
.135 .001 .484 .451 .258 .310 .989
−3.33 (2.76) 6.32 (4.11) −4.87 (8.53) −1.51 (18.00) 12.12 (6.54) 2.62 (4.20) 131.73 (48.94)
.230 .127 .569 .933 .066 .534 .008
−1.40 (3.45) 3.85 (3.74) 3.77 (3.71) 2.64 (3.19) −2.07 (3.22) 4.03 (3.25) 6.60 (4.01) 0.49 (3.24) −0.52 (0.12) −1.04 (1.30) 1.06 (0.39) —
.685 .303 .310 .407 .520 .215 .101 .881 .674 .423 .007
−14.18 (5.82) −6.88 (5.82) −17.38 (6.65) −10.94 (5.08) −17.29 (5.73) −8.43 (5.60) −18.80 (7.57) −10.03 (5.12) −0.40 (0.20) −5.00 (2.18) 0.77 (0.67) —
.016 .239 .010 .033 .003 .135 .014 .052 .051 .024 .255
1.59 (1.47) 7.19 (1.94) −2.66 (3.60) 3.09 (6.99) 4.84 (2.43) 2.31 (2.08) 22.79 (27.02) −3.42 (3.00) 1.10 (3.20) −0.06 (3.25) 0.09 (2.76) −4.96 (2.81) 1.82 (2.83) 1.86 (3.54) −1.30 (2.80) −0.12 (0.11) −1.58 (1.14) 0.96 (0.34) −3.12 (1.42)
.165
