5.1. Treatment process
Three aspects of the treatment environment were assessed: the level of support, structure (clarity), and directedness (spirituality). These indices were based on two subscales (support and clarity) drawn from the Community Programs Environment Scale (
Moos, 1996) and a newly developed measure of program emphasis on spirituality. Each of these three constructs was assessed by patients’ perceptions of 10 true–false items.
Support (α = .69) measures the extent to which patients are encouraged to support each other and how much staff supports patients (e.g., “Patients are given a great deal of individual attention here”).
Clarity (α = .63) measures the extent to which patients understand the day-to-day routine of the program and the rules and procedures (e.g., “The patients always know when the staff will be around”).
Spirituality (
α = .77) was measured by the Treatment Spirituality/Religiosity Scale, which contains 10 true–false items that assess a program’s emphasis on spirituality or spiritual practices (“Staff encourage patients to attend religious services”;
Lillis et al., 2008).
Satisfaction with treatment (
α = .92; range = 0–33) was measured by 11 items adapted from the Client Satisfaction Questionnaire (
Attkinson & Zwick, 1982). Participants responded to each item (e.g., “How would you rate the quality of the treatment you received”) on a 4-point scale ranging from 0 to 3.
Intensity of treatment To measure the extent of treatment provided for DD and SUD patients, we assessed the intensity of treatment by the sum of individual therapy or counseling sessions patients attended during treatment.
5.2. Proximal outcomes at discharge
Perceived benefits of quitting substance use (
α = .85; range = 0–24) were measured by the sum of six items from the outcomes expectancies scale (
Solomon & Annis, 1989,
1990). Each item (e.g., “If you quit using substances, you expect your future to look good”) was rated on a scale from 1 (
strongly disagree) to 5 (
strongly agree); higher scores reflect more positive expectancies for quitting substance use.
Substance-related self-efficacy (
α = .96; range = 0–5) was measured by patients’ self-efficacy related to their ability to control their drinking and drug use in tempting situations. This variable is composed of the average rating of 14 items (e.g., “If something good happened and I felt like celebrating”) responded to on a scale from 0 (
0% confident) to 5 (
100% confident). Items were adapted from the Situational Confidence Scale (
Annis & Davis, 1988;
Miller, Ross, Emmerson, & Todd, 1989).
Substance-specific coping (
α = .88; range = 0–60) measures the extent to which patients engage in various behaviors when they want to refrain from using alcohol and/or drugs. It was assessed by the sum of 15 items from the Process of Change Inventory (
DiClemente & Prochaska, 1982;
Fitzgerald & Prochaska, 1990). Participants rated each item (e.g., “Tell myself I am able to quit if I want”) on a scale from 0 (
never) to 4 (
often). Higher scores reflect more coping directed toward refraining from substance use.
Approach coping (approach;
α = .85; range = 0–36) assessed a general approach orientation to coping with stressful life circumstances. The sum of 12 items from the positive reappraisal and problem-solving subscales of the Coping Responses Inventory (CRI;
Moos, 1993) comprises this scale. Participants rated each item (e.g., “Tell yourself things to feel better”) on a scale of 0 (
no) to 3 (
yes, fairly often). Higher scores reflect higher levels of approach coping.
Avoidance coping (avoid;
α = .78; range = 0–36) assessed a general avoidance orientation to coping with stressful life circumstances. It was based on 12 items from the cognitive avoidance and emotional discharge subscales of the CRI (
Moos, 1993). Participants rated each item (e.g., “Deny how serious the problem really was”) on a scale of 0 (
no) to 3 (
yes, fairly often). Higher scores reflect higher levels of avoidance coping.
5.3. One-year and 5-year outcomes
Three outcomes were assessed at baseline and at the 1-and 5-year follow-ups.
Maximum alcohol use is the largest amount of alcohol consumed on any one day in the last 3 months. Patients were asked, “During the past 3 months, what was the largest amount you drank of each of the following beverages in any one day?” Responses, obtained for beer, wine, and hard liquor were multiplied by their ethanol content and summed to provide a total score. We chose this measure because we have generally found that it is a sensitive index of change during and after treatment and tends to be relatively well correlated with other measures of alcohol consumption.
Substance use problems were assessed by a 15-item scale developed for this overall project to reflect the negative consequences of substance use. The items measure a comprehensive array of problems that may result from alcohol or drug use, including health problems, legal problems (e.g., “Problems with the police,” “Been arrested”), money problems, occupational problems (e.g., “Problems with your job,” “Lost a job or nearly lost one”), residential problems (e.g., “Lost a place to live”), and interpersonal problems (e.g., “Arguments with your spouse/partner,” “Problems with friends”). Each item is assessed according to how often the substance use problem occurred in the previous 3 months as rated on a 5-point Likert scale (0 = never, 4 = often; alpha at baseline = .84; range = 0–60).
Psychiatric symptoms (symptoms) were measured by 22 items from the Brief Symptom Inventory (
Derogatis, 1993). The items refer to psychiatric symptoms (e.g., “Feelings of worthlessness,” “Spells of terror and panic”) that occurred in the previous 3 months and were rated on a 5-point scale (0=
not at all, 4 =
extremely; alpha at baseline = .94; range = 0–88).
5.4. Analytic plan
We used analyses of covariance (ANCOVAs) to examine whether DD and SUD patients differed in their perceptions of and intensity of treatment and had different proximal outcomes at discharge or longer term outcomes following SUD treatment. Patient status (DD vs. SUD) was the independent variable predicting each of the criteria. The ANCOVAs controlled for the demographic variables that significantly differentiated the two groups (i.e., race/ethnicity, education, employment), the intake value of the dependent variable (see for comparison of intake values of proximal and distal outcomes), and program treatment orientation (12-step or cognitive–behavioral). Because initial analyses showed that DD and SUD patients responded similarly to the 12-step and cognitive–behavioral programs, we combined them in subsequent analyses.
| Table 2DD and non-DD (SUD) patients’ status on intake values of proximal and substance use and psychiatric distal outcomes |
To examine the extent to which patients’ perceptions of treatment predicted proximal outcomes at discharge and to find out whether DD and SUD patients differed on the strength of association between patients’ perceptions of treatment and discharge outcomes, we conducted hierarchical linear regressions (HLRs) in which patient status and the indices of patients’ perceptions of treatment were the predictors and each of the proximal outcomes were the criteria. In each HLR, control variables (i.e., demographic factors, intake value of the outcome, program orientation) were entered in Step 1; patient status (DD or SUD) and patients’ perceptions of treatment were entered in Step 2; and the interaction of patient status and perceptions of treatment were entered in Step 3.
A final set of analyses was conducted to investigate whether patients’ perceptions of treatment and proximal outcomes at discharge were associated with 1- and 5-year outcomes and whether any such associations differed by patient group. To examine this issue, we conducted HLRs in which patient status (DD or SUD), patients’ perceptions of treatment and proximal outcomes at discharge, and the interaction of patient status and these perceptions of treatment and discharge outcomes predicted 1- and 5-year outcomes. We used the same method described earlier except that in Step 1, we entered intake values of both proximal and distal outcomes, along with demographic factors and program orientation.