Gender differences in detoxification: predictors of completion and re-admission

Journal of Substance Abuse Treatment 23 (2002) 399 – 407

Regular article

Gender differences in detoxification: predictors of completion and re-admission Russell C. Callaghan, M.A.a,*, John A. Cunningham, Ph.D.b a

Department of Psychology, University of Toronto, Toronto, ON, Canada M5S 2S1 Centre for Addiction and Mental Health and Department of Psychology, University of Toronto, Toronto, ON, Canada M5S 2S1

b

Received 13 November 2001; received in revised form 29 August 2002; accepted 29 August 2002

Abstract This study examined the medical records of 2595 consecutive admissions over a 3-year period to an inpatient mixed-gender, hospitalbased alcohol and drug detoxification unit. Women reported a significantly different pattern of primary drug use, a younger age, a different pattern of referral sources, and higher rates of parenting status and unemployment. In addition, females were administered prescription medication and medical evaluation tests at a significantly higher rate than males. Multiple regression analyses demonstrated that an opiate as a primary drug of choice was a significant risk factor for dropout. Risk factors for re-admission to inpatient detoxification included: alcohol as a primary drug of choice, residential instability, multiple drug use, single marital status, unemployment, an older age ( > 37 years), and treatment dropout at Time 1 in the study. For both the final prediction models, gender was not a significant factor. The treatment implications of these findings are discussed. D 2002 Elsevier Science Inc. All rights reserved. Keywords: Detoxification; Gender; Drugs; Alcohol; Relapse

1. Introduction Examining gender differences in addiction treatment, many researchers have found that women enter substance abuse programs with greater psychological distress, more medical problems, more family/social difficulties and greater addiction severity than men (Alterman, Randall, & McLellan, 2000; Arfken, Klein, di Menza, & Schuster, 2001; Marsh & Miller, 1985; McLellan et al., 1992). Researchers and clinicians have also found that women enter treatment with different areas of concern (e.g., issues of parenting, dependency, low self-esteem, sexual and physical victimization, social support) (Comfort, Zanis, Whiteley, Kelly-Tyler, & Kaltenbach, 1999; Dodge & Potocky, 2000; Grella, Polinsky, Hser, & Perry, 1999). As a result, gender-specific treatment programs have sought to increase treatment efficacy by tailoring treatment programs to meet women’s needs and by eliminating gender-specific obstacles to treatment entry and retention (e.g., Camp & * Corresponding author. Centre for Addiction and Mental Health, 33 Russell Street, Toronto, ON, Canada M5S 2S1. Tel.: +1-416-535-8501, ext. 6599; fax: +1-416-595-6899. E-mail address: [email protected] (R.C. Callaghan).

Finkelstein, 1997; Hien & Scheier, 1996; Whiteside-Mansell, Crone, & Conners, 1999). Even though most studies have shown that women present to treatment with greater problem severity, most studies on gender-specific and mixed-gender treatment have found that women and men have similar outcomes (e.g., Alterman et al., 2000; Fiorentine, Anglin, Gil-Rivas, & Taylor, 1997; Toneatto, Sobell, & Sobell, 1992; Wickizer et al., 1994). Some research, however, has found poorer treatment outcomes for women than men (e.g., Arfken et al., 2001; Blume, 1990). Most studies of gender differences have focused upon outpatient or long-term residential/inpatient treatment, and an understanding of the gender differences in inpatient detoxification treatment remains scant. Thus, the present study aims to examine gender differences among individuals undertaking inpatient drug and alcohol detoxification at a hospital-based treatment center. In comparison to other substance abuse research, the rarity of studies on inpatient detoxification is striking. In addition, the few studies available on alcohol and drug detoxification tend not to present an analysis of gender differences (e.g., Broers, Giner, Dumont, & Mino, 2000; Chutuape, Katz, & Stitzer, 2001; c.f., Toneatto et al., 1992). This lack of knowledge of the detoxification process espe-

0740-5472/02/$ – see front matter D 2002 Elsevier Science Inc. All rights reserved. PII: S 0 7 4 0 - 5 4 7 2 ( 0 2 ) 0 0 3 0 2 - 1

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cially holds true in the Canadian context, even though provincial rates of withdrawal management (inpatient detoxification) can reach approximately 20% of all those accessing addiction treatment services (Ministry for Children & Families, 2000). In British Columbia, for example, 8,391 patients were admitted to inpatient detoxification programs in the Provincial 1999-2000 fiscal year (Ministry for Children & Families, 2000) and yet little is known about patient characteristics or program effectiveness. By identifying elements associated with treatment outcome, appropriate interventions and programs might be developed for both men and women in order to increase completion rates. In addition, studies of inpatient detoxification treatment often do not evaluate clients’ post-treatment functioning, and those few articles examining aspects of relapse suffer from small sample sizes (which do not easily allow for gender comparisons), low response rates, and short time intervals between treatment and post-treatment measures (e.g., Gossop, Green, Phillips, & Bradley, 1989; Broers et al., 2000; Chutuape, Jasinski, Fingerhood, & Stitzer, 2001). Clinicians have noticed that many clients access detoxification treatment multiple times during the course of their substance abuse problem (McCarty, Caspi, Panas, Krakow, & Mulligan, 2000; Rossow & Skretting, 2001), but 1-, 3-, or 6-month follow-up measures do not adequately capture this pattern. In contrast, the present study examines gender differences in readmission to inpatient detoxification treatment among 1454 individuals presenting to treatment over a 3-year period. This project provides a unique window into the utilization of inpatient detoxification not only because individual-level data was collected on re-admission rates, but also because the treatment site under study provides the only hospitalbased detoxification treatment program in the northern half of the province. In this way, re-admission rates in this study probably reflect a more accurate estimate of acute relapse leading to detoxification for the total population.

2. Method 2.1. Participants The sample consisted of 2595 consecutive inpatient admissions to the Prince George Detoxification/Assessment Unit between January 4, 1999 and January 30, 2002. In this group of inpatient Detox/Assessment admissions, there were 1454 distinct individuals: 980 males and 474 females. See Table 1 for a description of the sample. The Research Review Committee of the Prince George Regional Hospital vetted the research design and gave ethical approval for the current study. 2.2. Treatment setting Affiliated with the Prince George Regional Hospital, the Detox/Assessment Unit offers a 20-bed, mixed-gender

inpatient detoxification program for both alcohol and drugs in Prince George, British Columbia. Located approximately 500 miles north of Vancouver, British Columbia, Prince George serves as the goods-and-services hub for communities in the northern half of the province. The Detox/Assessment Unit serves as a hospital-based, province-wide resource, with a majority of patients drawn from the northern half of British Columbia. Admissions were voluntary, and length of stay could range from 3 –30 days. Inpatient medical detoxification treatment can be accessed free of charge by anyone registered with a provincial medical services plan. In this way, there were no financial barriers to treatment. Detoxification treatment exclusion criteria included: more than five admissions in one calendar year to the Unit, and violent or criminal behavior against staff or other patients during current or previous detoxification treatment at the Unit.

Table 1 Gender differences among patients admitted to inpatient detoxification treatment Variable

Valid n (M, F)

Demographic Age (years) (971, Fixed address (No) (980, Unemployed (977, Marital status (single) (979, Education (high school) (980, Dependent child (yes) (980, Aboriginal (980, Treatment/Diagnostic Current IV drug use (980, First admission (yes) (960, Detoxification completion (980, Polydrug use (yes) (980, Referral source (self ) (980, Length of stay (hours) (980, Number of admits (980, Medical Problems Hepatitis B (630, Hepatitis C (668, HIV(+) (623, Cardiac problems/angina (648, Cirrhosis (644, Hypertension (678, Asthmatic (649, Gastritis (679, Diabetic (634, Pregnant (618, Protocols Administered Phenobarbitol (980, Clonidine (980, Ativan (980, HIV protocol (980, Psychotropics (980, Antibiotics (980, Antidepressants (980, Medical evaluation test(s) (980, * p < .01. ** p < .001.

M

F

t / c2

468) 474) 474) 474) 473) 474) 474)

39.6 (11.4) 19.5% 78.2% 56.3% 34.5% 51.9% 46.4%

35.2 (10.9) 7.0** 14.1% 6.3 85.4% 10.7** 51.9% 5.7 29.6% 3.5 62.0% 13.1** 62.4% 32.8**

474) 463) 474) 474) 474) 474) 474)

20.1% 41.4% 84.1% 57.1% 52.2% 110.5 (76.7) 1.8 (1.75)

21.3% 0.3 39.5% 0.4 76.2% 13.3** 59.1% 0.5 41.1% 22.6** 107.8 (84.5) 0.05 1.7 (1.5) 1.1

306) 340) 306) 307) 308) 320) 331) 321) 307) 301)

6.5% 20.7% 1.1% 9.6% 6.7% 19.0% 11.7% 18.3% 6.2% 0.0%

4.4% 25.9% 2.9% 5.9% 6.7% 11.9% 22.4% 15.6% 4.7% 2.7%

1.8 3.5 4.0 3.7 .01 8.0* 19.1** 1.1 0.9

474) 37.8% 474) 7.4% 474) 3.1% 474) 0.2% 474) 2.0% 474) 5.7% 474) 12.4% 474) 15.9%

38.2% 6.4% 3.4% 0.0% 3.4% 11.0% 21.9% 24.3%

0.02 0.5 0.1 4.1 2.3 12.8** 21.9** 14.7**

R.C. Callaghan, J.A. Cunningham / Journal of Substance Abuse Treatment 23 (2002) 399–407

The staff comprised a multidisciplinary team, consisting of a physician, registered nurses, Detox Workers, and a Native (Aboriginal) liaison worker. Registered nurses have earned a 4-year undergraduate degree in Nursing (or equivalent), along with the fulfillment of registration requirements demanded by the provincial authority. To qualify as a Detox Worker, individuals must have a 2-year social-services college diploma including an addictions-treatment component (or equivalent). During the course of the current study period, 20 Detox Workers and 19 nurses were engaged in data collection. Every new nurse or Detox Worker on the Unit participated in a 4-day on-the-job orientation program providing additional hands-on training in the processes involved in detoxification diagnoses, treatment and medical-chart procedures. Medical opiate detoxification treatment included methadone tapering, a2-agonists (Clonidine), and Phenobarbitol as an adjunct if needed, along with simple pain relief medication as warranted. Non-benzodiazepine sleep medication was prescribed as necessary. Patients with alcohol dependence receive a barbiturate protocol (usually phenobarbitol) during the withdrawal stage. For clients who were withdrawing from benzodiazepines an individual protocol was provided, using decreasing doses of phenobarbitol commensurate with the daily intake of benzodiazepines prior to admission. For cocaine detoxification, the medical protocols were dictated by the symptomatic withdrawal response of the client. 2.3. Data collection The data collection procedure followed a standardized three-pronged protocol. First, at admission an initial intake interview collected only basic demographic (e.g., name, address, date of birth, marital status) and initial drug use information. A Detox Worker performed this interview. If the patient presented in a state of severe intoxication, the Detox Worker was advised to employ any or all of the following strategies to complete this intake interview: either to check the Unit’s rolodex file of patients previously admitted to the Unit (this file contained the basic demographic information gathered at the previous admission, along with previous admission dates); to collect information from a personal identification card (e.g., driver’s license, Social Insurance card); or to complete the face-to-face intake interview later in the patient’s stay. Second, a registered nurse was asked to complete a standard, general physical assessment of the patient usually within 30 min after the initial intake interview. The nurse would also confirm the initial drug use information given during the patient’s initial intake interview with the Detox Worker. Given that some patients left within a 24-hr span after admission, the general physical assessment might not have been done. In addition, for severely intoxicated patients, the general physical assessment could only reliably record physiological or observational measures, not perti-

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nent self-reported medical history or drug use history. If a patient stayed more than a 24-hr period, a registered nurse usually could gather any incomplete information from the general physical assessment, and also cross-check any possibly unreliable information gathered from the Detox Worker’s initial intake interview. Third, a physician would meet with the patient within 24 hr of admission and assign a detoxification diagnosis and medication protocol (if needed). The primary drug of choice was determined by the detoxification diagnosis. This information would be included in the medical chart. To ensure a greater accuracy of the patient self-report in the data set, however, patients with a length of stay less than 24 hr were excluded from analyses in the study (N = 234; M = 166, F = 67). In addition, all treatment protocols and medical conditions diagnosed during the patient’s stay were noted in the patient’s medical records. Treatment completion status was assigned when a patient was discharged from the Unit in a non-intoxicated state (as judged by a registered nurse or physician). Usually a registered nurse assigned ‘‘treatment complete’’ status after the discharge interview with the patient. The nurse’s assessment of ‘‘treatment complete’’ status was based upon the functioning of the patient during the discharge interview, along with an understanding of the standard detoxification period associated with each detoxification diagnosis and the physician’s length-of-stay recommendation noted in the detoxification diagnosis protocol. Relapse was defined as re-admission to the Detox Unit during the 3-year course of the study. When a patient was admitted multiple times, only treatment data from the earliest admission during the study period was used. 2.4. Medical-chart review Once the patient was discharged, the medical chart was organized for chart abstraction and data entry, according to a standardized protocol. The initial screening interview, general physical assessment, medications administered, medical evaluative procedures administered were each highlighted in a specified section of the medical chart. In this way, relevant data could be abstracted quickly and reliably. A single data entry clerk entered almost all of the data in this 3-year medical-chart review. This clerk had 7 years of experience in a data administration position at the detoxification treatment center. After the data were entered, the first author used traditional data-cleaning techniques to spot possible data entry errors. In these cases, the medical charts were cross-checked. 2.5. Statistical analyses Chi-square analyses were used to examine gender differences on variables measured as a function of frequency count, while t-tests were used to test differences between

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Table 2 Primary drug of choice reported at admission Primary drug of choice

Men (947)

Women (443)

Alcohol Cocaine Opiates Benzodiazepines Other

62.9% 20.6% 9.0% 1.3% 6.2%

53.5% 22.8% 14.7% 4.5% 4.5%

c2 (4, 1390) = 29.6, p < .0001.

genders on continuous variables. Multiple logistic regression analyses were used to identify a set of predictors of a dichotomous treatment outcome variable (treatment completion or treatment dropout). Variables were entered into the hierarchical logistic regression procedure in two steps (Step 1: main predictor variables, Step 2: Predictor  Gender two-way interaction variables). The interaction terms were entered into the last step in order to assess their additional contributions. The predictor variables were chosen because of a demonstrated significant bivariate

difference between genders in the present study (see Table 1), or the findings of previous research (e.g., Armenian, Chutuape, & Stitzer, 1999; Araujo et al., 1996; Franken & Hendriks, 1999). In addition, we performed a multivariate survival analysis using the Cox proportional hazards regression procedure to identify risk factors of re-admission while controlling for censoring effects due to differential length of follow-up for each patient. The Cox regression procedure considers the effect of multiple survival predictors simultaneously and, unlike traditional multiple regression, allows for the inclusion of censored survival times (Singer & Willett, 1991; Willett & Singer, 1993). Prior to conducting the Cox Regression procedure, we performed a series of graphical procedures to ensure that the proportionality-of-hazards assumption was met for the predictor variables across censored and non-censored cases (SPSS Inc., 1999). Censored survival data occurred when a patient was admitted after January 4, 1999, but not re-admitted to detoxification treatment as of January 31, 2002.

Table 3 Multiple logistic regression models predicting detoxification dropout Best Model Variable (Referent) Male (Female) Medical problems (2 or more)a Multiple drug use (3 or more)b Opiates (alcohol) Cocaine (alcohol) Age (>37 years)c Unemployed (no) Parenting Status (yes) Antidepressants Prescribed (yes) Referral source (self)d Ethnicity (Aboriginal) Gender  Medical Problems (2 or more) Gender  Multiple Drug Use (3 or more) Gender  Opiates (Alcohol) Gender  Cocaine (Alcohol) Gender  Age (>37 years) Gender  Unemployed (Yes) Gender  Parenting Status (Yes) Gender  Antidepressants (Yes) Gender  Referral Source (Self ) Gender  Ethnicity (Aboriginal) 2 Log Likelihood: Likelihood Ratio Test: Pseudo R 2: a

b .32 .33 .24 1.6 .23 .32 .45 .14 .20 .34 .32

Full Model SE

Wald

Exp(b)

p

.18 .20 .19 .23 .22 .18 .26 .17 .24 .17 .18

3.1 2.7 1.5 46.6 1.0 3.2 3.0 .67 .73 3.9 3.3

.73 .72 1.3 4.8 1.3 1.4 1.6 1.1 1.2 .71 1.4

.08 .10 .22 .0001** .31 .08 .08 .41 .39 .052 .07

920.6 c2 (11, 1060) = 88.4, p < .0001 0.13

b

SE

Wald

Exp(b)

p

.68 .50 .37 1.7 .62 .38 1.2 .09 .19 .34 .18 .32

1.0 .32 .32 .38 .36 .32 .64 .28 .34 .28 .30 .41

.49 2.4 1.4 21.0 3.0 1.4 3.7 .11 .31 1.5 .37 .59

2.0 .60 1.5 5.7 1.9 1.5 3.4 1.1 1.2 .71 1.2 1.3

.49 .12 .24 .0001** .08 .24 .055 .74 .58 .23 .54 .44

.23

.40

.31

.80

.57

.24 .65 .15 .99 .09 .06 .01 .22

.48 .46 .39 .70 .35 .48 .36 .37

.26 2.0 .14 2.0 .06 .01 .001 .34

.78 .52 .86 .16 1.1 .94 .99 1.2

.61 .16 .71 .37 .80 .91 .98 .56

915.0 c2 (10, 1060) = 5.6, p > .05 0.14

The number of medical problems were collapsed into two categories (0 – 1, 2 or more). The number of drugs the client reported as ‘‘problematic’’ at admission was reduced into 2 categories (1 – 2 drugs, 3 or more drugs). c Age was divided into 2 categories based on a median split of the sample on age ( < 37 years, >37 years). d Referral source was categorized as ‘‘self-referred’’ or ‘‘other-referred’’. * p < .05. ** p < .001. b

R.C. Callaghan, J.A. Cunningham / Journal of Substance Abuse Treatment 23 (2002) 399–407

Variables were entered into the Cox regression procedure in two steps (Step 1: predictor variables, Step 2: Predictor  Gender two-way interaction variables). The interaction terms were entered into the last step in order to assess their additional contributions. The predictor variables were chosen because of a significant bivariate difference between genders in this study (see Table 1), or because previous research has demonstrated such variables to be predictive of symptom exacerbation after treatment or re-admission to treatment for substance abusers (Moos, Mertens, & Brennan, 1994; Moos, Nichol, & Moos, 2002).

3. Results A number of significant differences were detected between men and women (see Table 1). Along with a different pattern of primary drug use (see Table 2), women reported a younger age, a different pattern of referral sources, and higher rates of parenting status, unemployment and Aboriginal ethnicity. Women were administered prescription medication (i.e., anti-depressants, antibiotics) and medical evaluation tests (e.g., X-rays, blood tests) at a higher rate than men. Across a variety of self-reported medical problems, men and women did not differ on most;

403

but women did report proportionately more asthma and less hypertension than men. Results of the multiple logistic regression analyses to predict detoxification treatment dropout appear in Table 3. The final regression model produced a significant goodness-of-fit statistic for likelihood ratios, c2 (11, 1060) = 88.4, p < .0001. An opiate as a primary drug of choice was the only significant predictor of dropout. The Predictor  Gender interaction terms as a group did not contribute significantly to the regression equation above and beyond the original main effects model [c2 (10, 1060) = 5.6, p > .05] and, as a result, these were dropped from the final regression model. Results of the Cox regression analyses to predict treatment re-admission appear in Table 4 and Fig. 1. The final Cox regression model produced a significant goodness-of-fit statistic for likelihood ratios, c2 (9, 1402) = 108.1, p < .0001. Significant predictors of detoxification re-admission were: residential instability, alcohol as a primary drug of choice, single marital status, unemployment, multiple drug use, an older age (>37 years), Aboriginal ethnicity and treatment incompletion at Time 1. The Gender  Predictor interaction terms as a group did not contribute significantly to the regression equation above and beyond the original main effects model [c2 (8, 1402) = 3.1, p > .05] and, as a result, these were dropped from the final regression model.

Table 4 Cox regression model predicting re-admission to inpatient detoxification Best Model Variable (Referent) Female (Male) Fixed Address (Yes) Single (Other)a Unemployed (Yes) Multiple Drug Use (Yes)b Treatment Completion at Time 1 (Yes) Age (>37 years)c Primary Drug (Alcohol)d Ethnicity (Aboriginal) Fixed Address  Gender Gender  Single Gender  Unemployed Gender  Multiple Drug Use Gender  Treatment Completion at Time 1 Gender  Age Gender  Primary Drug (Alcohol) Gender  Aboriginal 2 Log Likelihood: Likelihood Ratio Test: a

b .20 .30 .45 .58 .36 .47 .27 .23 .22

Full Model SE

Wald

Exp(b)

p

b

.10 .11 .10 .15 .10 .11 .10 .10 .10

3.7 7.4 21.2 14.6 12.7 18.2 7.4 4.6 5.4

.82 1.4 .64 .55 .70 1.6 .76 .80 .80

.054 .007** .0001** .0001** .0001** .0001** .006** .03* .02*

.04 .45 .27 .13 .50 .12 .62 .17 .30 .12 .44 .14 .29 .12 .22 .13 .27 .11 .13 .25 .17 .22 .25 .37 .22 .22 .08 .23 .10 .23 .05 .23 .16 .22 6227.5 c2 (8, 1402) = 3.1,

6230.6 c2 (9, 1402) = 108.1, p < .0001

SE

Wald

Exp(b)

p

.01 4.3 18.4 13.2 5.9 10.6 6.1 3.0 5.7 .26 .62 .48 1.0 .10 .19 .05 .53

.96 1.3 .61 .53 .74 1.6 .74 .80 .76 1.1 1.2 .78 .80 1.1 1.1 .95 1.2

.92 .04* .0001** .0001** .02* .001** .013* .08 .02* .61 .43 .49 .31 .75 .67 .83 .47

p > .05

Marital status was collapsed into two categories (single, other). b The number of drugs the client reported as ‘‘problematic’’ at admission was reduced into 2 categories (1 – 2 drugs, 3 or more drugs). c Age was divided into 2 categories based on a median split of the sample on age ( < 37 years, >37 years). d The primary drug of choice was categorized into 2 groups (alcohol, other drug). * p < .05. ** p < .01.

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Fig. 1. Survival curves of men and women for re-admission to inpatient detoxification treatment.

Based on these findings, a single main-effects regression model was chosen as the best model for our data set. This approach proposes that the influence of the main effects is not conditional upon gender. This rationale also applies to the findings of the Cox regression analyses as well.

4. Discussion This study had a number of goals: (a) to examine gender differences among those admitted to an inpatient detoxification (see Table 1); (b) to construct a multiple logistic regression model for men and women predictive of detoxification dropout; and (c) to build a statistical model predicting re-admission to the detoxification treatment program. A number of studies have demonstrated that women present to treatment with greater medical problem severity than men (e.g., McLellan et al., 1992). Across 10 common medical problems observed in detoxification patients (e.g., angina/cardiac problems, gastritis, cirrhosis, Hepatitis C), the data in the present study revealed only two differences: men reported a significantly higher rate of hypertension and women indicated a higher rate of asthma-related problems. Hence, men and women appeared more similar than different. Unfortunately, however, the study design did not allow for comparisons across medical problem severity, but rather only a binary coding (yes/no) of problem presence or absence. Even though men and women generally manifested more similarity than difference across medical problems, women in detoxification generally utilized more health

care resources (cf., Bertakis, Azari, Helms, Callahan, & Robbins, 2000). This pattern has been seen in other inpatient treatment settings (Rowan-Szal, Chatham, Joe, & Simpson, 2000). In the present study, for example, women were administered more prescription drugs (i.e., Clonidine, anti-depressants, antibiotics) at a significantly higher rate than men (c.f., Sclar, Robison, Skaer, & Galin, 1998), and they received more medical evaluative tests (e.g., X-rays, blood tests, urinalysis) during their stay than men. This trend may result from a number of possibilities: (a) women may find it more socially acceptable to discuss symptoms, illnesses and treatment (c.f., Hoffman & Tarzian, 2001); (b) women’s medical/psychiatric problems were more severe but not adequately captured by the study design; or (c) as the pattern of referral sources indicate, women may have received some form of medical or mental health evaluation before entering detoxification treatment. Confirming trends found in a number of large-scale substance abuse treatment research reports (Brennan, Moos, & Kim, 1993; Weisner, Greenfield, & Room, 1995; Weisner & Schmidt, 1992), this study found that men and women accessed detoxification treatment by different means. In the present study, even though self-referral represented the highest percentage of referral sources for men and women (M:F = 52.2%:41.1%), women were more likely to have drawn referrals from hospital services (M:F =15.8%:20.3%), mental health providers (M:F = 17.6%:19.0%) and physicians (M:F = 5.7%:7.6%). In this way, it appears that women draw upon a wider range of health-related services before entering detoxification treatment than do men, and

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these wide-ranging health-related services appear to play an important role in the initial stages of detoxification referral and admission for women. According to the results of the multiple regression analyses, an opiate as the primary preferred drug of choice was the only significant predictor of detoxification dropout. Even though a number of studies have examined predictors of outcome for inpatient detoxification, to distill common findings across such studies poses difficulties because some report on general drug-and-alcohol detoxifications (Armenian et al., 1999; Franken & Hendriks, 1999), while others focus on inpatient opiate detoxification (e.g., Backmund, Meyer, Eichenlaub, & Schu¨tz, 2001; Broers et al., 2000; Chutuape et al., 2001; San, Cami, Peri, Mata, & Porta, 1989), alcohol-only detoxification (John, 1987; Martı´nezRaga, Marshall, Keaney, Ball, & Strang, 2002), or drug-only treatment (McCusker, Bigelow, Luippold, Zorn, & Lewis, 1995). For those studies reporting results from drug-andalcohol treatment programs similar to ours, severity of drug use and medical problems (Franken & Hendriks, 1999), a younger age, a shorter history of cocaine use, and being an opiate dependent patient treated with Clonidine were predictive of a negative treatment outcome (Armenian et al., 1999). Our study suggests that those who report opiates as their primary drug of choice are at greater risk of detoxification dropout than other patients admitted to general alcohol-and-drug detoxification. Drug use severity (operationalized as the number of drugs the client reported as using in a ‘‘problematic’’ way) and self-reported medical problems were not significantly predictive of treatment dropout, as a previous study has shown (Franken & Hendriks, 1999). Previous studies have shown that parenting issues can pose a barrier to treatment entry and retention for women (Conners, Bradley, Whiteside-Mansell, & Crone, 2001; Finkelstein, 1994; Killeen & Brady, 2000). In our study, self-reported parenting status, either as a main-effect or in interaction with gender in our regression models, did not significantly predict detoxification dropout (See Table 3). This finding suggests that parenting status is not significantly associated with detoxification dropout for either men or women. It is important to note, however, that the value of the variable was the patient’s yes-or-no answer to the following question, ‘‘Do you have a dependent child?’’ The variable did not measure whether the child was in the permanent care of the patient, extended family or social service organization and, as a result, in our data set it is difficult to assess more precisely the pull of parental responsibilities on treatment outcome. A number of studies have attempted to identify predictors of detoxification dropout, but only recently have researchers attempted to provide a risk index associated with symptom exacerbation and relapse after substance abuse treatment (Moos et al., 1994, 2002; Moos, Moos, & Finney, 2001). In a similar way, our study has attempted to provide a prognostic model for re-admission to inpatient

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detoxification. The final Cox regression model demonstrated a number of significant predictors of re-admission to inpatient detoxification treatment: alcohol as the primary preferred drug of choice, residential instability (i.e., lack of a fixed address at admission), unemployment, single marital status, an older age (>37 years), multiple drug use (defined as the self-reported ‘‘problematic’’ use of 3 or more drugs), Aboriginal ethnicity and treatment incompletion at Time 1 in the study. Previous research has uncovered a strikingly similar set of variables predicting symptom exacerbation and re-admission to treatment (Moos et al., 1994, 2002). For example, a younger age, residential instability, non-married status, prior alcohol treatment, more severe self-rated drug problems, and psychiatric problems were significant risk factors for substance use symptom exacerbation after treatment (Moos et al., 2002). In our study, however, an older age may serve as a proxy for a more chronic and longstanding substance abuse problem. This study has a number of implications for treatment. Since an opiate as a primary drug of choice was predictive of detoxification incompletion, it may be appropriate for general alcohol and drug detoxification programs to evaluate the barriers to treatment completion for opiate users. In addition, given that identification of patients at risk of re-admission is essential for tailoring treatment and discharge planning, the set of predictors derived in our study can serve as a prognostic index for the early identification of possible readmission to inpatient detoxification care. It may be helpful to identify those who manifest a high number of predictors so that appropriate treatment and continued care regimens can be provided. For example, residential instability (defined in our data set as the lack of a fixed address) was a significant predictor of re-admission to the detoxification unit. The provision of stable housing has been shown to be a central component in substance abuse recovery and rehabilitation (e.g., Huebner, Perl, Murray, Scott, & Tutunjian, 1993), and detoxification treatment services may need to focus on residential stability as an important component in the discharge and referral process. In our data set, it appeared that there were two groups of clients accessing detoxification services: those that entered detoxification treatment once or rarely over a lengthy period, and those that utilized these services relatively frequently. Of all the admissions to inpatient detoxification treatment in this study, 68.8% of female admissions (n = 326) and 65.5% (n = 642) of male admissions were admitted only once for detoxification treatment during the 3-year naturalistic study. Those women and men admitted multiple times during the study period, however, accounted for 63% of the total admissions, while only accounting for 33% of the total sample. This finding resonates with an often-seen pattern in detoxification: a revolving-door minority of inpatient detoxification clients account for a disproportionately high number of admissions (c.f., McCarty et al., 2000; Rossow

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& Skretting, 2001). Previous research has demonstrated that this revolving-door subpopulation has unique needs, not only in the areas of stable alternative housing (Rossow & Skretting, 2001), but also specialized psychiatric services (Moos et al., 1994; Tomasson & Vaglum, 1998). It is both striking and clear that Aboriginal people bear a disproportionate burden of illness, substance abuse, and disease in Canadian society (MacMillan, MacMillan, Offord, & Dingle, 1996; Health Canada, 1999). In a similar way, for example, First Nations individuals comprise a disproportionately large number in our sample, especially since First Nations individuals (living both on and off reserve) account for only 3% of the British Columbia provincial population (British Columbia Ministry of Health, 1998), but 51.7% of individuals admitted for detoxification during the course of our study. In addition, Aboriginal ethnicity was a significant predictor of detoxification readmission. To address the implications of such a finding in relation to detoxification treatment can easily invite unhelpful generalizations or stereotypes and, given our medicalchart data, the causal factors of Aboriginal re-admission patterns remain unclear. At the very least, however, it should be noted that First Nations individuals are at a significantly greater risk for re-admission to detoxification treatment, and as a result, further research and treatment options need to explore ways to reduce such risk.

2001). However, among drug users who reported having HCV, the confirmed accuracy of their reports reached 98% (Stein et al., 2001). In addition, the sample included approximately 50% Caucasians and 50% First Nations (Aboriginal) individuals primarily from northern British Columbia. Many patients were drawn from rural areas outside of the city-center treatment location. While the findings may generalize to other treatment centers in Canada, the results may not extend to other areas where different ethnic and urban patient compositions are prevalent.

5. Limitations

References

This study has a number of limitations. Even though vigilance was taken to ensure the veracity of patient selfreports, either through subsequent interviews, clinical observations, or reviews of previous medical records, this study did rely upon the self-reports of many patients under the influence of drugs or who were experiencing the effects of drug withdrawal. In addition, patient reports of primary preferred drug of choice were not confirmed through the use of urinalysis, but rather through clinical observations of withdrawal symptoms. Also, the duration, frequency, and intensity of primary drug use and other problematic drug use were not collected. In this way, it is difficult to assess the addiction severity of the primary drug of choice or the use severity of other currently problematic drugs reported by the patient. Nonetheless, previous research has shown that that patients’ self-reports of drug use are reasonably reliable and valid, especially when events are recent and patients do not face negative consequences for their answers (Darke, 1998; Zanis, McLellan, & Randall, 1994). In light of the infectious-disease frequencies reported in this study, especially Hepatitis C (HCV), it is important to view patients’ self-reports of infectious-disease status with a measure of caution. Previous studies have shown that drug users’ knowledge of their own infectious-disease status is somewhat unreliable, especially given their tendency to report false-negative status (Stein, Maksad, & Clarke,

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