Portraying alcohol treatment outcomes: Different yardsticks of success

BEHAVIOR THERAPY 26, 643-669, 1995

Portraying Alcohol Treatment Outcomes: Different Yardsticks of Success

MARK B. SOBELL

LINDA C . SOBELL

Addwtton Research Foundanon and Umverstty of Toronto

DOUGLAS R. GAVIN

Addtcnon Research Foundatton and York Umverstty

An ~mportant ~ssue m the alcohol field is how to present treatment outcome findings m a way that conveys the nature of the full range of outcomes (1.e., how indwlduals fared). Results should also be presented so as to be readily understood by practlnoners. To illustrate how treatment outcome reports can be enriched by graphic portrayals of outcome findings, previously unpublished results from a study of Graded Self-Change treatment for problem drinkers are first presented in a tradmonal manner. Then, supplemental graphic methods of data reporting, including the use of frequency distributions and scatter plots, are presented. These portrayals are shown to address issues that receive little attennon in reports hmited to stansncal analyses. It is also shown that reported success rates, "yardsncks of success," are highly dependent on small changes m the criteria used to define success.

A longstanding but seldom addressed issue in the alcohol field is how to present treatment outcome findings in a way that conveys the nature of the full range of outcomes (i.e., how individuals fared) and the relationships between different outcome dimensions. In one of the few articles to seriously address these issues, Taylor and his colleagues (1985) presented 10-year drinking outcome data for 68 male alcoholic patients who were treated in the well known "treatment" versus "advice" trial (Edwards et al., 1977), The authors used sur- vival curves and life charts to depict group outcomes on a yearly basis and

The authors would hke to express their thanks to the staff of the former Assessment Follow-Up Umt at the Chnlcal Research and Treatment Insntute who conducted all of the assessments for this study and many of the follow-up interviews, and to Wayne Skinner, Joanne Spratt, Juhe Henderson, and Slmonne LeBreton who served as therapists. Gloria Leo was tremendously helpful m conducting the study, and Even Kwan and Gfl Sitaremos assisted with the statlsncal analyses Curtis Breshn provided valuable comments on the manuscript. Also, sm anonymous reviewers provided highly valuable comments.

Requests for reprints should be addressed to M.B. Sobell, Center for Psychological Studies, Nova Southeastern University, 3301 College Ave., Fort Lauderdale, Florida 33314

643 0005-7894/95/0643-066951 00/0 Copyright 1995 by Assoclanon for Advancement of Behavior Therapy

All rights of reproducnon m any form reserved

644 SOBELL ET AL.

used a barycentrlc coordinate plot to present individual variation in amount of time spent in three drinking categories (abstinent, social drinking, trou- bled drinking) over the 10 years. Although subjects showed stable patterns over time, the patterns were composed of "a patchwork of drinking and abstinence" (p. 50), leading the authors to conclude that outcome is most usefully conceived as a "dynamic rather than a static concept" (p. 50). The article by Taylor and his colleagues clearly shows that presentations of treatment outcome reports can be far more informative than typically is the case. For example, innovative methods such as graphical portrayals of outcomes can convey more information and in a more comprehensible manner than can be communicated by statistical analyses alone. Such methods have not yet been applied, however, to the presentation of outcome findings for shorter intervals.

The nature of outcomes over shorter intervals is ~mportant not just from the standpoint of knowing how treated indwiduals fare, but also because shorter term outcomes are more likely to reflect treatment effects than outcomes over extended intervals (Moos & Finney, 1985). More specific knowledge of the nature of outcomes might suggest treatment improvements or shed light on treatment mechanisms. For example, assessing multiple dimensions of drinking behavior might reveal that one method of treatment leads to a reduction in the frequency of drinking but not in the amount consumed, whereas another method might affect the magnitude rather than the frequency of drinking. Reasons why this occurred could be explored, and the different methods could be matched to specific client subgroups. For instance, binge drinkers might benefit more from a treatment that affected the magnitude of consumption versus the frequency of drinking.

Because the ultimate objective of treatment research is to influence clinical practice, results should be presented in such a way that they can be readily understood by practitioners. Unfortunately, many practitioners lack the time and background to disentangle complicated statistical presentations of results (Dies, 1983). Thus, it would be valuable to present findings in a way that facilitates readers' comprehension of the nature of treatment outcomes.

This article uses an existing data set to present ways of supplementing statistical outcome reports with graphic portrayals that present a great deal of information in a relatively easily understood format. These data have not been presented elsewhere, although the treatment procedures have been described in detail as part o f a clinical guidebook (M. B. Sobell & Sobell, 1993a). Because the study has not been presented previously in the empirical literature, this article includes a brief description of the treatment rationale and procedures before discussing methods of data presentation. Findings, along with a discussion of the main conclusions emanating from that analysis, are then first presented in the traditional statistical manner. Building on this background, the remainder of the paper then explores supplemental methods of portraying outcome findings. The treatment study, therefore, can be thought of as constituting a paper within a paper, with a larger purpose than a simple research report.

PORTRAYING TREATMENT OUTCOMES 645

Methods Guided Self-Change Treatment

Problem drinkers, persons who have low severity alcohol problems (M. B. Sobell & Sobell, 1993a, 1993b), are abundant in number, greatly outnumbering those who are severely dependent on alcohol (Institute of Medicine, 1990). Historically, behavioral treatments for alcohol problems have emphasized skills training based on the assumption that individuals engage in excessive drinking as an inappropriate coping response (M. B. Sobell, Wilkinson, & Sobell, 1990). However, it has been found that problem drinkers respond well to brief interventions involving, at the most, a few sessions (Bien, Miller, & Tonigan, 1993). The success of brief treatments calls into question whether skills training is necessary for problem drinkers. A parsimonious explanation of the efficacy of brief treatments is that the major effect of such interventions is motivational: if problem drinkers want to change, they already have the necessary skills and resources to do so. Miller (1985, 1986/87; Miller & Rollnick, 1991) has suggested that motivation can be conceptualized as a state of readiness to engage in behaviors intended to achieve some goal, rather than as a person- ality trait. Viewed as a state, motivation can be influenced by several factors. In a motivationally based treatment, a major objective is to help individuals use their existing skills to solve their problems.

Guided Self-Change (GSC) is a short-term motivationally based treatment specifically designed to appeal to and be appropriate for problem drinkers. The data presented in this article are from a randomized trial that compared the effectiveness of GSC treatment with and without a cognitive relapse prevention component. The relapse prevention component was tested as a supplement to GSC because it was hypothesized that the relapse prevention perspective would help maintain treatment gains. Because strong ties between the therapist and client would not be expected to occur in a brief treatment, an important treatment component should be to prepare clients for dealing with problems encountered after treatment. Relapse prevention, which focuses on the maintenance of treatment effects (Marlatt & George, 1984), is an obvious candidate for maintaining behavior change. The cognitive component of relapse prevention tested in this study involved encouraging the client to adopt the perspective that relapses may occur following treatment, and that how one deals with relapses is important: (1) relapses should be interrupted as soon as possible in order to minimize consequences; (2) relapses should be considered as learning experiences that identify previously unrecognized high risk situauons or inadequate methods of coping; and (3) relapses should not be attributed to personal failings (which would promote low self-efficacy), but rather to situational factors that can be dealt with in the future.

Subjects Persons seeking treatment for alcohol problems at the Addiction Research

Foundation (Toronto) who volunteered to participate in a treatment study involving a GSC treatment (M. B. Sobell & Sobell, 1993a) were screened at a

646 SOBELL ZZ At.

centralized Assessment/Follow-Up Unit. Clients were eligible if they: (1) had a primary alcohol problem; (2) read and wrote English; (3) were between 19 and 60 years of age; (4) had an Alcohol Dependence Scale (ADS; Skinner & Allen, 1982) score of ~< 21; (5) were not legally coerced to participate in treatment; (6) passed a screening to exclude possible organic brain damage; (7) lived within 100 km of Toronto; (8) had not participated in formal alcohol or drug treatment within the past year; (9) were not currently receiving psychiatric treatment or medications for major psychiatric problems; (10) had not changed residence more than four times in the preceding year; (I1) reported never having experienced major alcohol withdrawal symptoms; (12) provided the name of a collateral to be contacted for follow up; (13) reported average alcohol consumption no greater than 12 standard drinks (13 g ethanol each) on >i 5 days per week during the 6 months prior to assessment; and (14) signed an informed consent.

Eligible clients were randomly assigned to one of two GSC treatment conditions: Behavioral Counseling Only (Group BC), or Behavioral Counseling plus Cognitive Relapse Prevention (Group RP). Four female and two male experienced outpatient therapists conducted the individual treatment sessions. Randomization was blocked so that each therapist saw an equal number of subjects in each treatment condition, and gender was balanced across conditions. I f a subject failed to complete treatment, a new subject was substituted to maintain the balance among therapists, gender, and conditions.

To obtain 100 subjects (50 in each group), 129 subjects entered the study. Of the 29 who did not complete the treatment, 17 were in Group BC and 12 in Group RP. This difference between groups was not significant (p > .05), nor were there any significant differences in demographic and drinking history variables between dropouts and treatment completers. For describing the sample, data from all 100 completers have been combined.

Treatment completers had a mean (SD) age of 37.3 (8.82) years and a mean (SD) education of 14.8 (3.5) years, 49% were married, 89% were employed, and for 83% it was their first treatment experience. They had a mean (SD) ADS score of 12.8 (4.6). Their drinking was not extremely heavy, especially compared with studies of severely dependent alcohol abusers (e.g., Foy, Nunn, & Rychtarik, 1984; Ito, Donovan, & Hall, 1988; Kuchipudi, Hobein, Flick- inger, & Iber, 1990). Collectively, subjects drank on 68.2% of all days during the pretreatment year. When they drank, 38.7% of the days involved ~< 4 drinks (1 drink = 13.6g absolute ethanol), and only 16.8% of the days involved >/10 drinks. Subjects' mean (SD) drinks consumed per drinking day was 6.2 (2.7). However, subjects reported a substantial number of alcohol-related consequences. The percentages of subjects reporting various types of consequences were as follows: 21% legal, 27% health, 37% affective, 47% financial, 47.5% vocational, 56% aggression, 78°70 cognitive, and 81% interpersonal. Subjects were also asked to provide a subjective evaluation of the severity of their drinking problem over the previous year: 78% evaluated their problem as "major" or "very major," which was defined as having suffered at least one or more serious alcohol-related consequence. It should be noted that although the terms "major" and "very major" are used here because those terms were


used in the question posed to clients, the types of consequences described by these problem drinkers typically were far less serious than consequences reported by severely dependent individuals (e.g., relationship dissolutions, multiple job losses, liver disease).

Procedures

Treatment procedures are only summarized here because they have been described in great detail elsewhere (M. B. Sobell & Sobell, 1993a). The treatment protocols were specified in a therapist manual prepared for the study. They consisted of a 2-hour assessment, followed by two 90-minute structured sessions, and supplemented by readings and homework assignments. The assessment was conducted by staff uninformed about subjects' group assignments. Assessment information gathered included (a) demographic and substance abuse history information, (b) the Inventory of Drinking Situations (IDS; measures the extent to which subjects report that they drank heavily in certain types of situations in the past year; Annis, Graham, & Davis, 1987), (c) the Situational Confidence Questionnaire (SCQ; a state measure of self-efficacy or confidence to resist the urge to drink heavily for the same situations as in the IDS; Annis & Graham, 1988), (d) a Timeline Followback interview (TLFB; collected subjects' estimates of their drinking over the past year; L. C. Sobell & Sobell, 1992), and (e) a medical screening. At the assessment and at each treatment session subjects specified a self-selected goal (i.e., abstinence or reduced drinking) on a Goal Statement form. Subjects with medical contraindi- cations to drinking (n -- 4) were told that they should not drink at all. Sub- jects selecting a reduced drinking goal (n = 80) had to specify limits for quantity and frequency of consumption and had to list situations in which drinking would not occur. Although subjects choosing a reduced drinking goal initially specified their own limits for drinking, in the first treatment session advice on specific low risk drinking guidelines was provided.

At the assessment, subjects were given a short reading and a homework assignment. The reading described drinking from a behavioral perspective (e.g., antecedents, consequences) and provided a framework for subjects to orga- nize information they had reported during the assessment. The homework asked subjects to functionally analyze their three most serious problem drinking situations by identifying triggers (high-risk situations) associated with the drinking and evaluating the consequences of the drinking (good and bad, im- mediate and delayed). Thus, before the first session, subjects were familiar with the treatment orientation and had begun a detailed analysis of their problem drinking.

At the first session, subjects' homework assignment answers and their understanding of the reading were discussed. When subjects' goal statements were discussed, they were advised of the following recommendations for a reduced drinking goal: (1) consume not more than three standard drinks on any given day (Babor, Kranzler, & Lauerman, 1987); (2) drink on not more than 4 days per week (Sanchez-Craig, 1986) in order to help avoid developing excessive tolerance or habitual components to the drinking; (3) never drink in high-risk circumstances; (4) drink at a rate no faster than one drink per hour

648 SOBELL ET AL.

if there was a possibility of driving; and (5) consider imposing a 15-20 minute delay period between making a decision to drink and acting on that decision (Cummings, Gordon, & Marlatt, 1980).

At the end of the first session, subjects were given a second brief reading and a homework assignment and asked to bring the completed homework to their next session. The reading described behavioral problem solving procedures. The homework required clients to develop "options" (alternatwe ways of responding) for the problem drinking situations identified in their first homework. After identifying options, they evaluated each for its feasibility and potential effectiveness and selected the best and second best options for which they then developed "action plans" (i.e., detailed steps to be taken in order to enact the option).

At each treatment session, the therapist reviewed the rationale for the readings and explored subjects' understanding of the material. Subjects' answers to the homework assignments were discussed and elaborated upon if necessary. Subjects were also asked to discuss any personal strengths and resources they could use in dealing with their drinking problem (e.g., how they had successfully dealt with other problems in their lives, how they had quit smoking or sustained a weight loss, or activities in which they might engage to fill rime freed up by stopping or reducing drinking). Finally, they reported their drinking since the last session using the TLFB technique.

Procedures for the RP and BC treatment conditions differed in two ways. First, the RP subjects' readings contained sections on relapse management, relapse prevention, and the importance of viewing recovery from a long-term perspective. Second, during the sessions the relapse prevention components were discussed in relation to the readings. These components were absent from all BC subjects' treatment. As a quality control procedure to assure the dis- criminability between the RP and BC treatments, all sessions were tape recorded and a randomly selected session for each subject was reviewed by a research assistant for compliance with the protocol. In only one case was a protocol violation observed (a BC subject was treated with RP procedures) and that instance had been reported by the therapist. The subject was replaced by another randomly selected subject.

At both sessions, subjects were told that, although the structured treatment involved two sessions, they could contact their therapist at any time they felt they needed further treatment. In response to subjects' requests, therapists were free to conduct further sessions or refer subjects to other services.

Follow-up interviews were scheduled with subjects at 1, 3, 6, 12, 18, and 24 months, and the interviewer was to be the assessment worker who had first assessed the subject. Unfortunately, considerable staffturnover in the Assess- ment/Follow-Up Unit over the course of the study resulted in most subjects being followed by a research assistant who had not conducted the assessments. The information gathered at follow-up contacts largely paralleled that gathered at the pretreatment assessment.

After about half of the subjects had entered the follow-up phase, it became apparent that the data collection for these relatively well functioning, highly stable clients was too intense for a two-session treatment. Several of the sub-


jects who had withdrawn from the follow-up phase had told the interviewer that they did not have time to participate in follow-up. Thus, to gather data from as many subjects as possible, subjects who had withdrawn from follow- up were contacted and asked if they would agree to participate in an abbreviated follow-up interview. This increased the follow-up completion rate by about 10070. Follow-up interviews were also scheduled to be conducted with subjects' collaterals at 6-month intervals. Collaterals were asked to describe the subject's drinking over a 30-day period using a modified TLFB procedure, which involved reporting categories of drinking (L. C. Sobell et al., 1986), and to report any alcohol-related consequences experienced by the subject.

Results and Discussion: Relapse Prevention as a Component of Guided Self-Change Treatment

To illustrate the ways in which treatment outcome reports can be enriched by graphic portrayals of outcome findings, study results are first presented and discussed in a traditional manner, summarizing the major statistical analyses. Following this, suggested supplemental methods of data presentation are considered.

Follow-Up Sample At 6 months, follow up was completed on 85°7o of the subjects who com-

pleted treatment (42 in Group BC and 43 in Group RP) and on 73°7o at 12 months (37 in Group BC and 36 in Group RP). Chi-square analyses for differen- tial dropout by treatment condition indicated no significant effect. Inability to locate subjects accounted for 46.707o of the attrition at 6 months and 33.307o at 12 months; the remaining cases were located but refused to continue in follow up. Similar follow-up attrition rates have been reported in other outcome studies of problem drinkers (e.g., Alden, 1978; Anderson & Scott, 1992; Annis & Peachey, 1992; Heather, Kissoon-Singh, & Fenton, 1990; Miller, Benefield, & Tonigan, 1993; Sanchez-Craig, Annis, Bornet, & MacDonald, 1984).

A series of analyses evaluated differences between early follow-up drop outs and those for whom some follow-up data were gathered. These analyses examined demographic variables, drinking history, and pretreatment and within- treatment drinking behavior. A Bonferroni procedure was applied to correct for the multiple comparisons, but using an alpha level adjusted to .25, the mid-point of the range (.20 to .30) suggested by Winer (1971) when discussing how to form conclusions of no difference. Only one significant difference was obtained. Early dropouts had a lower percentage of limited drinking days (consumption of ~ 4 drinks) during the pretreatment year than completers [Drop- outs Mean = 12.7407o; Completers Mean = 29.81070, t = 3.50, df = 32.61 (unequal variance), p = .001]. The reason for this difference is unknown. One possibility is that the early dropouts may have tended to be binge drinkers (i.e., either drank heavily or not at all), although it is not clear why this would affect their participation in follow up. When the same procedures were applied to evaluate potential differences between the 6-month follow-up dropouts and subjects for whom 12 months of follow-up data were collected, no differ-

650 SOBELL ET AL.

ences attained statistical significance. The two groups did not differ significantly on any drinking behavior variable over the first 6 months of follow-up.

Because the 12-montfi period provides a comparison interval equivalent to the pretreatment period, the analyses presented here are for the 12-month follow-up Interval. Findings of analyses using 6-month follow-up data were consistent with those of the analyses based on 12-month follow-up.

Group Drinking Outcomes Over Time

Subjects' total number of drinks consumed over the follow-up year was 53.8% less than their reported drinking for the year prior to treatment. Similar reductions have been reported in other studies using brief interventions with problem drinkers (e.g., Graber & Miller, 1988; Sanchez-Craig, Leigh, Spivack, & Lei, 1989; Sanchez-Craig, Spivack, & Davila, 1991; M. B. Sobell et al., 1980).

Group drinking outcomes were analyzed using multivariate analyses of variance (MANOVA) for repeated measures. The dependent variables were proportion of days abstinent, proportion of drinking days in which 1 to 4 standard drinks were consumed, the proportion of drinking days in which >1 10 standard drinks were consumed and the mean number of standard drinks consumed per drinking day. Analyses for days when 5 to 9 drinks were consumed were not conducted because this variable would be fully determined by knowledge of the values of the other variables. The independent variables were occasion (within-subjects variable: pretreatment, treatment, follow-up) and condition (between-subjects variable: BC, RP). Wilk's Lambda was used as the multivariate criterion. Significant effects were probed using unlvariate tests and multiple comparison procedures, and significant interactions were examined.

The MANOVA found no significant overall effects for condition (p > .05) or condition-occasion interactions, but there was a significant overall effect for occasion, Wilk's Lamda F(8,60) = 15.60, p < .001. The occasion effect was probed using univariate tests for the dependent variables; all dependent variables showed an occasion effect. The significant univariate tests were then probed using multiple comparisons that compared pretreatment to the combined treatment and follow-up intervals, and follow-up to the treatment interval. Working within the constraints on degrees of freedom available for the comparisons, this combination of tests was preferred to testing follow up against either the pretreatment or treatment interval alone. For all of the dependent variables, these'contrasts showed that the pretreatment interval was significantly different from the combined treatment and follow-up intervals, and that the treatment and follow up intervals did not differ significantly. Table 1 displays pretreatment, treatment, and follow-up means and standard devia- tions for the two treatment conditions and the four dependent variables included in the MANOVA.

Outcome Measures Other Than Drmking

Consequence data gathered in this study covered nine areas: work problems, maj or withdrawals, physical health problems, cognitive problems, affective problems, interpersonal problems, verbal or physical aggression, legal prob-


T A B L E 1

MEANS (SD) FOR T w o TREATMENT CONDITIONS (BEHAVIORAL COUNSELING, BC, N = 36; BEHAVIORAL COUNSELING PLUS COGNITIVE RELAPSE PREVENTION, RP, N = 33),

OVER THREE INTERVALS (l YR PRETREATMENT, WITHIN=TREATMENT, 1 YR POSTTREATMENT) FOR FOUR OUTCOME VARIABLES

Interval

Treatment Condition Pretreatment Within-Treatment Posttreatment

Proportion of Total Days Abstinent

BC 0 32 (0 26) 0 58 (0.35) 0 61 (0.30) RP 0.33 (0 29) 0 45 (0 35) 0 50 (0.29)

Proportion of Drinking Days Consumed 1-4 Standard Drinks

BC 0 35 (0 33) 0.59 (0 39) 0.59 (0 38) RP 0.49 (0 30) 0.68 (0.27) 0.73 (0 29)

Proporuon of Drinking Days Consumed /> 10 Standard Drinks

BC 0 21 (0.31) 0 11 (0 21) 0 10 (0.16) RP 0 09 (0 19) 0.01 (0.03) 0.03 (0.06)

Mean Number of Standard Drinks Consumed per Drinking Day

BC 672 (3.03) 4 11 (295) 421 (261) RP 5 05 (2 20) 3 58 (1 41) 3 58 (1 72)

lems, and f inancial problems. For purposes o f s ta t is t ical evaluat ion, a consequence var iable was created by d icho tomiz ing subjec ts ' responses (i.e., yes, no), with scores ranging f rom 0 to 9. A n eva lua t ion o f scale rel iabi l i ty using the fol low-up sample (65 usable cases) y ie lded a Cronbach ' s a lpha o f .68. This value is acceptable for using the c o m b i n e d scores in research appl i - cat ions. Consequence scores were evalua ted using a 2 ( t rea tment condi t ion: BC, RP) × 2 (interval: p re t rea tment , pos t t r ea tmen t ) repeated measures analysis o f variance. This analysis found no significant effect for t r ea tment condi - t ions, and no significant in terac t ion effect. A signif icant interval effect was obtained, F(1,63) = 56.73, p < .001; subjects ' mean (SD) pretreatment consequence score o f 4.1 (1.84) decreased to 1.7 (1.82) pos t t rea tment .

A n o t h e r ou t come measure consis ted o f cl ients ' rat ings o f the severity o f their d r ink ing problems. There were five categories: (1) not a p rob lem (no consequences or worry); (2) very m i n o r p rob lem (worry, but no consequences); (3) m i n o r p rob l em (one or more consequences but none the subject cons idered serious); (4) m a j o r p rob lem (one consequence cons idered serious); and (5) very m a j o r p rob lem (more than one consequence cons idered serious). For purposes o f s ta t is t ical analysis , these categor ies were considered to const i tute a 5-poin t scale and they were subjected to a 2 ( t rea tment condi t ion : BC, RP) × 2 (interval: pretreatment , pos t t rea tment) repeated measures analysis o f variance. This analysis y ie lded no significant cond i t ion effect, but the effect for

652 SOBELL ET AL.

occasion was significant, F(1,65) = 48.81, p < .001, with mean (SD) subjective problem severity ratings significantly less following treatment [2.97 (0.97)] than prior to treatment [4.01 (0.74)]. It should be recalled that a score of 2 indicates that no negative consequences were actually experienced. The occasion effect was qualified by a significant condition × occasion interaction, F(1,65) = 4.19, p = .045, which appeared to reflect that group RP subjects changed less (mean change = -0 .72) than group BC subjects (mean change = 1.31). Because this was the only one of several outcome analyses to yield a significant interaction, and the probability attained was just below the .05 criterion, it is likely that the interaction effect was a chance occurrence.

Relattonsh(p Between Drinking and Consequences Dtmenstons

To evaluate the relationship between the number of consequences subjects experienced over the follow-up year and heavy drinking, the number of consequences was correlated with the percentage of days they consumed five or more drinks during that interval. Although the correlation between these variables was statistically significant (r= .28, n = 64, p =.025), the relationship accounted for less than 8°7o of the variance in the data.

Predwtors o f Outcome To evaluate variables potentially predictive o f outcome, multiple regression

analyses were conducted using as dependent variables the mean frequency of abstinent days, mean drinks per drinking day, mean number of drinks per week, and mean number of consequences over the follow-up year. Babor et al. (in press), using results from four studies, found that measures of drinking frequency and intensity (drinks per drinking day) were relatively uncorrelated, suggesting that they "represent independent dimensions of drinking behavior." Predictor variables were the following pretreatment and treatment factors: age, gender, years of education, marital status, employment status, pretreatment mean drinks per drinking day, ADS score, drinking goal at assessment, pretreatment alcohol consequence score, frequency of abstinent days pretreatment, pretreatment SCQ score, and end of treatment SCQ score. Multiple regression analysis was chosen over the use of discriminant analysis because it takes into account gradations in improvement.

Multiple regression analyses were performed in order to identify the best set of predictors for each of the outcome variables. Although initial analyses indicated possible collinearity between the ADS and consequence scale scores, both were retained because conceptually the sets have only partial overlap. It was decided, however, to perform the multiple regressions using a step-wise backward selection procedure because the presence of collinearity would have made the results of regular multiple regression analyses difficult to interpret. The regression procedure, therefore, first predicted the outcome using a full model containing all of the predictor variables. Each subsequent step removed the predictor that contributed least to the overall fit of the model, until the final model contained only variables that contributed independently and significantly to the solution. The analyses were conducted using SPSS version 6.0. The multiple Rs obtained in these analyses were significant: frequency


TABLE 2 SIGNIFICANT PREDICTOR VARIABLES AS IDENTIFIED BY MULTIPLE REGRESSION

ANALYSES FOR FOUR OUTCOME VARIABLES

Predictor Variable B Beta p

Frequency of Abstinent Days Posttreatment

Higher frequency of abstinence pretreatment 240.63 .614 < 001 H~gher Alcohol Dependence Scale score 4 51 188 037 More years of education 6 20 180 049

Number of Drinks per Drinking Day Posttreatment

Higher mean drinks/drinking day pretreatment 319 404 < 001 Lower end of treatment self-efficacy score - 079 - .440 < 001 Not employed pretreatment 1 27 246 004 Older age 053 218 014 Moderanon goal at assessment 1 17 .207 017 Married pretreatment .756 181 031 Male - 759 - .172 046

Number of Drinks per Week Posttreatment

Lesser frequency of abstinence pretreatment -20 70 - 481 < 001 Older age 378 276 008 Lower end of treatment self-efficacy score - 335 - 331 < 001 Male - 5 54 - .222 021

Number of Consequences Posttreatment

Higher Alcohol Dependence Scale score 112 273 .030 Lesser frequency of abstinence pretreatment - 1 78 - 273 030

o f abs t i nen t days p o s t t r e a t m e n t , m u l t i p l e R = .76, F(5,62) = 16.89, p < .001; n u m b e r o f d r inks per d r i n k i n g day p o s t t r e a t m e n t , m u l t i p l e R = .79, F(7 ,60) = 14.70, p < .001; n u m b e r o f d r inks per week p o s t t r e a t m e n t , m u l t i p l e R = .70, F(6,61) = 9.54, p = .001; and n u m b e r o f p o s t t r e a t m e n t c o n s e q u e n c e s , m u l t i p l e R = .35, F(2,61) = 4.15, p = .021. S ign i f ican t p r ed i c to r var iab les for the fou r c r i t e r i on m e a s u r e s a p p e a r in Table 2.

Discussion of Guided Self-Change Treatment W i t h respect to G S C t r e a t m e n t , the p resen t pos i t ive results in t e rms o f im-

p rovement f r o m pre t rea tment to pos t t r ea tmen t paral le l those repor ted for o ther b r i e f o u t p a t i e n t t r e a t m e n t s used w i t h p r o b l e m dr inkers . Because a con t ro l g r o u p was n o t used, it is no t poss ib le u n e q u i v o c a l l y to a t t r i b u t e the i m p r o v e - m e n t to the G S C t r e a t m e n t . Howeve r , two s tudies o f p r o b l e m dr inke r s t ha t used wa i t ing list c o n t r o l g roups (A lden , 1978; H a r r i s & Mil ler , 1990) f o u n d Improvement only in t reated subjects. Because typical f indings for cont ro l groups have been n o i m p r o v e m e n t , it is un l ike ly tha t t he i m p r o v e m e n t o b s e r v e d in

654 S O B E L L E T A L .

this study is a function of extraneous factors such as natural recovery, or of measurement artifacts such as regression toward the mean (Kazdin, 1986).

Although both groups showed improvement, the study provided no evidence of added value for including cognitive relapse prevention procedures as part of GSC treatment for problem drinkers. In this regard, it joins the ranks of mixed results in the evaluation of relapse prevention approaches (reviewed in Rawson, Obert, McCann, & Marinelli-Casey, 1993; M. B. Sobell & Sobell, 1993a). When positive findings have occurred in relapse prevention programs, they usually included explicit skills training procedures rather than cognitive relapse prevention procedures alone as tested in the present study. One possible explanation for the tack of effect in this study is that problem drinkers may already have a perspective congruent with a relapse prevention approach. That is, because their drinking typically includes many days when they consume just a few drinks, problem drinkers may view an excessive drinking day as unfortunate but not fateful. Although the cognitive relapse prevention component did not receive support in terms of treatment outcomes, it was incor- porated into the treatment protocol without adding additional length to the treatment. Furthermore, the therapists reported they found it slightly awk- ward and difficult to conduct treatment without reference to relapse preven- uon concepts (M. B. Sobell & Sobell).

Because the reductions in drinking found in this study are of the same general magnitude as in previous studies, an issue that must be addressed is how the GSC approach differs from other approaches. The answer lies not in differen- tial effectiveness but in appeal to clients (i.e., minimizing intrusion upon clients' lifestyles and empowering clients, rather than therapists, to take responsibility and credit for changes). As early interventions gain increasing priority in health care, an important issue in service delivery is how to devise treatments that appeal to problem drinkers. Miller et al. (1993) recently demonstrated that problem drinkers not only appear to be resistant to traditional directive and confrontational treatments versus a nonthreatening, motivational intervention, but that such resistance is associated with poorer outcomes. As reported elsewhere, the GSC treatment was well liked by the vast majority of subjects in this study (M. B. Sobell & Sobell, 1993, January).

As regards the role of GSC treatment as an element of the health care system, it is an early treatment approach that is likely to have appeal for self-identified problem drinkers who want to assume major responsibility for changing their behavior. Persons who do not successfully change, and those who desire a more directed approach, could be referred to treatments with other orienta- tions or to more intensive interventions. As with other health care areas, the more intensive and costly treatments would be kept in reserve for cases that do not respond to less intensive approaches, or where there are more serious treatment needs (e.g., shelter, health, vocational training). Such a tiered or stepped care approach to treatment, similar to the principles guiding provi- sion of health care for other problems (e.g., hypertension, hypercholesterol- emia), would make for a cost-effective, comprehensive, and responsive health care system that could greatly reduce the costs of alcohol problems to individuals and to society (M. B. Sobell & Sobell, 1993b).


This traditional method of analysis thus allows at least tentative conclusions about the success of GSC and the need to amplify relapse reduction interventions in order to achieve additional success. It does not, however, address many of the questions that clinicians and clinical researchers might have regarding patterns of change, which can be better described graphically than statistically, as illustrated in the next section.

Results: Alternative Portrayals of Outcomes In preparing this report of a treatment trial for publication, we noted that

although traditional analyses address issues of whether statistically significant change occurs from pre- to posttreatment, or whether one treatment has a greater effect than another, they do not provide information on many aspects of outcome likely to be of interest to treatment agencies and clinicians. For example, although traditional reports may present mean values for groups of clients, they typically provide no indication of individual differences within the group. Thus, a group for which some individuals showed dramatic improvement and a smaller number of individuals showed dramatic failure could theoretically have the same mean change score as a group where nearly all members improved somewhat. Clinically it would be useful to know whether the typical response to the treatment was likely to be either a marked improvement or a setback versus a smaller improvement distributed across most clients. There would also be scientific value in knowing about different patterns of outcomes because such a split outcome pattern would suggest that the overall group consisted of subgroups of good responders and poor responders. This would lead to research attempting to characterize those subgroups and, pos- sibly, to a client-treatment matching study.

In addition to leaving certain treatment outcome issues (e.g., individual differences) relatively unaddressed, traditional statistical outcome analyses may also be difficult for clinicians to interpret. Although it would not be advisable to oversimplify the presentation of results, graphic portrayals of findings may facilitate readers' appreciation of how change occurs within groups of clients and for individual clients. In the remainder of this paper we present and discuss alternative ways of presenting outcome findings. These methods can be used to supplement statistical reports and to communicate the richness of an outcome data set more fully than is typically accomplished by descriptive statistics.

Yardsticks of Success

An initial example of the value of alternative portrayals of outcomes con- cerns a type of descriptive statistic often found in traditional outcome reports, the presentation of "success rates." Some experts suggest that the ability to document treatment success improves the likelihood that one will be selected for and maintained on managed health care panels (Gilson, Prince, & Mont- gomery, in press), and thus rate of success may become an important clinical as well as research entity. Calculating success rates is valued for its simplicity, but there are three notable limitations with such an approach. First, there are no consensual criteria regarding what outcome variable should be used nor the cut-off for separating successful from unsuccessful cases. Second, in the

656 SOBELL ET AL.

TABLE 3 YARDSTICKS OF SUCCESS SUCCESS RATES FOR THE PRESENT STUDY AS A FUNCTION

OF THE DEFINITION OF SUCCESS EMPLOYED

Percent of Cases Success Criterion Successful

Never > 4 Drinking Days/Week & Never > 3 Drinks/Day d'b Never > 3 Drinks/Day a'~ Never > 12 Drinks/Week a'd Never > 4 Drinking Days/Week a h Never > 17 Drinks/Week a'e Mean Drinking Days/Week ~< 4 & Mean Drinks/Drinking Day ~< 3 b Never > 21 Drinks/Week a't Mean Drinks/Drinking Day ~< 3 ~ Mean Drinks/Week ~< 12 ~

4 Drinking Days per Week b Mean Drinks/Week ~< 17 e Mean Drinks/Week ~ 21 ¢

87 116 174 24 6 29 0 30 4 39 1 42 0 60 9 66 7 75.4 82 6

a For these variables, weeks were calculated as consecuU~e 7 day blocks beginning with the day following the last treatment session b Present study

Present study, Anderson et al , 1993; Babor et al , 1987 d Addiction Research Foundation and Canadian Centre on Substance Abuse, 1993 e Hams & Miller, 1990

Anderson et al., 1993, Babor et al , 1987

a b s e n c e o f a c o n s e n s u a l s t a n d a r d , t h e p u r p o r t e d success r a t e s will ref lect t h e n a t u r e (1.e., t ype o f o u t c o m e v a r i a b l e , l e n i e n c y o r s t r i c t n e s s ) o f t h e c r i t e r i a b e i n g u s e d fo r a g iven s tudy. T h i r d , a d i c h o t o m o u s c h a r a c t e r i z a t i o n o f o u t - c o m e s conveys ve ry l i t t le i n f o r m a t i o n a b o u t w h a t c a n o t h e r w i s e be a r i ch d a t a set. M o s t i m p o r t a n t l y , u s i n g d a t a f r o m t he p r e s e n t s tudy, Table 3 i l l u s t r a t e s h o w rela t ively smal l dif ferences m cr i te r ia c a n yield m a r k e d differences in success rates .

T h e y a r d s t t c k s o f success p r e s e n t e d in Tab le 3 a re b a s e d o n g o a l c r i t e r i a p r o v i d e d to s u b j e c t s in t h e p r e s e n t s tudy, a n d o n w e e k l y c u t - o f f s t a n d a r d s t h a t have b e e n s u g g e s t e d in t he l i t e ra tu re . I n t e r m s o f q u a n t i t y a n d f r e q u e n c y o f d r i n k i n g , t he s t r i c t e s t tes t o f a d v i c e p r o v i d e d to s u b j e c t s in t he p r e s e n t s t u d y r e q u i r e d t h e m to n e v e r c o n s u m e m o r e t h a n t h r e e d r i n k s in a d a y a n d n e v e r to d r i n k o n m o r e t h a n 4 days pe r week. Al te rna t ive ly , o n e c o u l d eva lua t e genera l c o m p l i a n c e w i t h t h e r e c o m m e n d e d l imi t s by e x a m i n i n g h o w m a n y s u b j e c t s r e s t r i c t e d t h e i r average w e e k l y d r i n k i n g to n o m o r e t h a n t h r e e d r i n k s pe r d r i n k i n g day a n d n o m o r e t h a n 4 d r i n k i n g days p e r week. Also , b e c a u s e q u a n - t i t y a n d f r e q u e n c y c a n v a r y i n d e p e n d e n t l y , o n e c a n e x a m i n e t h e m as s e p a r a t e d i m e n s i o n s to e v a l u a t e s u b j e c t s ' success , as a p p e a r s in Tab le 3.

A p o p u l a r way o f e x p r e s s i n g success ra tes h a s b e e n in t e r m s o f week ly al- c o h o l c o n s u m p t i o n . Tab le 3 i n d i c a t e s h o w success ra tes c h a n g e w i t h r e l a t ive ly m i n o r c h a n g e s in t h e l imi t , a n d h o w they c h a n g e as a f u n c t i o n o f w h e t h e r

P O R T R A Y I N G T R E A T M E N T O U T C O M E S 657

100% . . . . . . . . . . . . . . . . . . . . . . . ~'" ~ " ' ~ " i . . . . . . ~ ' - - ' -

80% " / ' (/) i " I a)

O ~t~ . . . . . . . . ./..i " 80%

G,IO~ / 'If i /

"~) 40% .~ " - - pretreatment . . . . posttreatment

~ 20% )/lr

0%

0 20 40 60 80

M e a n w e e k l y s t a n d a r d d r i n k s

FIG. 1 Cumu]atwe frequency d]stnbunons of subjects' (n = 69) pre- and posttreatment mean number of standard dnnks consumed per week. The dotted hnes indicate improvement from pre- to posttreatment applying criteria of 12 and 40 standard drinks per week

the limit is expressed as an absolute boundary or as a mean value. For example, success can be reflected as the percentage of subjects who never ex- ceeded 12 drinks per week, or more leniently as the percentage of subjects whose average consumption did not exceed 12 drinks per week. Similarly, a cut-off value of 17 standard drinks per week could be used, as suggested by Harris and Miller (1990; 17 drinks as defined here is equivalent to 20 of Harris and Miller's standard ethanol content units). Finally, one could adopt a criterion of 21 standard drinks per week as suggested by Babor, Kranzler, and Lauerman as a limit for nonhazardous drinking (1987; see also Anderson, Cremona, Paton, Turner, & Wallace, 1993). Using these different criteria, the presentation of success rates at the 12 month follow-up in Table 3 shows that rather small changes in criteria result in considerable differences in success rates. In short, the use of single criterion success rates, although convenient, requires careful attention to the specific criterion reported in order to be meaningful, and comparability among studies is limited to those that report an equivalent criterion.

An alternative to presenting a single success rate is to present a cumulative frequency distribution of clients' outcomes along various dimensions. For example, if mean weekly alcohol consumption is considered important, as with

658 SOBELL ET AL

studies referenced in Table 3, a cumulative frequency distribution of clients' outcomes along that dimension can be prepared as shown in Figure 1. Figure 1 also shows the cumulative frequency distribution for subjects' pretreatment mean weekly alcohol consumption, permitting a visual pre-posttreatment comparison. To facilitate the presentation of results, findings for the two treatment conditions have been combined because there was no significant difference between conditions.

An advantage of presenting frequency distributions, such as shown in Figure 1, is that this allows readers to apply whatever weekly drinks criterion they wish to evaluate success. For example, the dotted lines in Figure 1 indicate that approximately 18% of the subjects were consuming a mean of 12 or fewer drinks per week prior to treatment, whereas approximately 60% were drinking this amount or less during follow-up, more than a three-fold increase. Simi- larly, approximately 19% of the subjects were consuming more than 40 drinks per week before treatment, but only about 2% were drinking that heavily during follow-up.

Graphical presentations of outcome data can substantially enhance presentations of treatment outcome findings and inform readers of relationships in the data that are not apparent from statistical presentations. The shapes of the curves convey to readers how change was distributed within the group. For example, if, as in Figure I, approximately 60% of the subjects were consuming 12 or fewer drinks per week after treatment, but most of the remaining 40% were consuming large amounts, such as 50 or more drinks per week, the frequency distribution would have an S-shape rather than the current steadily increasing curve. Such a marked difference in distributions would not be apparent from simply reporting a single success rate, but it could be clinically ~mportant by suggesting there was a subgroup of subjects who had little response to treatment.

Needless to say, number of drinks consumed per week is only one of several "yardsticks" of success that could be displayed in a frequency distribution format. Although distributions for other variables will not be presented here due to space considerations, visual comparison of distribution shift curves for different measures of drinking, such as percentage of days abstinent, mean drinks consumed per drinking day, and percentage of clays drinking above or below various criterion levels, would provide clinicians with a picture of how clients' drinking was most likely to change. For example, it might be found that most problem drinkers are better able to refrain from drinking entirely for a day (i.e., to reduce their frequency of drinking) than to reduce the quantity they consume on drinking days. Moreover, if frequency distributions were regularly presented for a standard set of outcome variables (e.g., frequency of drinking, mean drinks consumed per drinking day), this would allow meaningful comparisons of findings between studies. Lack of comparability among outcome studies has long been noted as a serious deficiency in the alcohol treatment outcome literature (Longabaugh, 1989).

How Do Indtvldual Chents Fare Af ter Treatment?

An important matter for clinicians is how many clients actually show improvement from pre- to posttreatment, for example in meeting a criterion of


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l • I A ~ 8 0 % :

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• RP 2O%

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0% 0% 20'% 40'% 66%0 86°1o 100%

Pretreatment days consumed 0-4 drinks FIG. 2 Scatter plot showing individual subjects' (n --- 69) pre- and posttreatment mean per-

centage of days consumed 0 to 4 standard drinks for two treatment conditions. Cases to the left of the diagonal reflect ~mprovement following treatment.

consuming four or fewer drinks per day (including abstinent days). Statistical group outcome reports convey very little about what types of individual change are typical. Further, although correlational techniques can suggest the general correspondence between two or more measures, they do not communicate certain features of outcomes that might be important to clinicians. For example, in statistical analyses, atypical cases, or outliers, may weaken the statistical association and may even be omitted from the analyses because they are aber- rant. From a clinical perspective, however, it can be important to know that a small proportion of cases might show a radically different response to treatment.

Distribution shift curves also convey little information about change among individual clients. However, for a given variable, change among individual clients can be illustrated using scatter plots comparing pre- and posttreatment status. For example, Figure 2 presents a scatter plot from the present study comparing the pre- and posttreatment percentage of days drinking 0 to 4 drinks for individual clients. This figure shows that on this measure only three clients (cases markedly to the right of the diagonal in Figure 2) were worse after treatment, with the vast majority evidencing substantial posttreatment increases. In

660 SOBELL ET AL,

100%

.~ 80%

60%

"6 40% g

20%

1 5 9 13 17 21 29 25 33 37 41 4'5 29 53 5'7 6'1 6'5 69

Cases rank ordered by percentage of days • 10 or more drinks consumed 0 to 4 drinks, posttreatment • 5 to 9 drinks

] 1 to 4 drinks

] 0 drinks

F m 3 P o s t t r e a t m e n t m d ~ l d u a l subjec t (n = 69) o u t c o m e d a t a r ank o rde red by the per-

cen tage o f da}s tha t subjec ts c o n s u m e d 0 to 4 s t a n d a r d d r inks

fact, the clumping of clients near the 100% mark posttreatment may weaken the value of statistical analyses in this case because the variance for one of the variables is highly constrained. Another facet of the outcome that would not be readily apparent from a statistical presentation, but that can be observed from Figure 2, is that many of the subjects who had relatively few abstinent or light drinking days pretreatment (e.g., from 10% to 40%) were substan- nally improved after treatment. Figure 2 also presents data by treatment condition, indicating that the pattern of results was similar among subjects in both conditions.

What Were Subjects" Drinking Repertowes Lzke?

Although scatter plots are useful for single variables, they cannot convey the sense of subjects' entire drinking repertoires. An important question for chnicians working with problem drinkers might be whether successful outcomes tend to consist of two distinct subgroups of individuals, some who become totally abstinent and some who mainly consume limited amounts of alcohol, or whether the majority of cases involve a mix of abstinent and limited drinking days. Using bars to represent each subject's posttreatment status, with drinking divided into categories (e.g., abstinent, I to 4 drinks, 5 to 9 drinks, 1> 10 drinks), individual subjects' drinking outcomes are portrayed in Figure 3. Subjects are rank ordered by their percentage of days drinking 0 to 4 drinks during the follow-up year. Figure 3 not only illustrates that most


100%.

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~ 40%.

• 20% a.

0% 1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69

Cases in identical order as in Figure 5 [ B 10 or more drinks

5to9 drinks

] 1 to 4 drinks

] 0 drinks

FIG. 4 Pretreatment mdiwdual subject (n = 69) data for subjects rank ordered by the percentage of days that subjects consumed 0 to 4 standard drinks during the posttreatment year (1 e, subjects are m the same rank order as m Figure 3, but F~gure 4 displays their pretreatment data).

subjects showed a mix of light drinking and abstinent days in follow up, but also reflects the fact that light drinking constituted a substantial part of their treatment outcomes.

Were Subjects" Pretreatment Patterns o f Drinking Simdar to Their Posttreatment Patterns?

Because simultaneous presentation of pre- and posttreatment individual subject data can be difficult to follow, especially when data are presented for a large number of subjects, the findings presented in Figure 3 are limited to posttreatment drinking dispositions. Clinicians might be interested, however, in how well the treatment outcomes paralleled subjects' pretreatment patterns of drinking. That is, are subjects with highly successful treatment outcomes those who already had a large number of abstinent and light drinking days in their patterns prior to treatment? Figure 4 presents a variation of Figure 3 that addresses this question. In Figure 4, instead of cases being rank ordered in terms of their pretreatment drinking, they are presented in the same order as in Figure 3. For example, case 10 in Figures 3 and 4 is the same individual, with Figure 3 presenting posttreatment data and Figure 4 presenting that same individual's pretreatment data. In this case, the subject was one of a few who were abstinent over the entire follow-up year. By comparing Figures 3 and 4, one can see that the relationship between patterns of pretreatment and post-

662

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S O B E L L E T A L .

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@ a. 10%

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/ "

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8 7 6 5 4 3 2 1 0

N u m b e r of c o n s e q u e n c e s

Frequency dlsmbunons of subjects' (n = 69) pre- and posttreatment number of alcohol- related negative consequences reported The shaded area indicates the improvement m terms of percentage of subjects reporting zero or one consequence over follow up

t rea tment d r ink ing is not strong. H a d the re la t ionship been strong, F igure 4 would have closely resembled Figure 3 in form, a l though the overall height o f the abs t inent and l ight dr inking por t ions o f the bars would have been lower.

What Types o f Shtfts Are Seen m Drinking Consequences After Treatment?

Alternative ways of presenting outcome findings are not restricted to drinking measures. A n o t h e r var iable typica l ly repor ted m ou tcome studies involves a lcohol - re la ted consequences exper ienced pre- and pos t t rea tment . A l t h o u g h a statistical compar i son can suggest whether a reduct ion in consequences from pre- to pos t t rea tment was unl ikely to occur by chance, such a compar i son does not in fo rm cl inicians abou t whether they should expect their clients to experience consequences, and, i f so, how many may remain. Figure 5 presents subjects ' pre- and pos t t r ea tmen t consequence scores as f requency d is t r ibu- nons. A l t h o u g h the figure shows tha t the curve shifts to the right, reflecting improvement , in this case the shape o f the curve also changes, reflecting a change in the relative d i s t r ibu t ion o f consequences within the sample. Dur ing the p re t rea tment interval the m o d a l number o f consequences exper ienced by subjects was a round four to five, with few subjects repor t ing only one or no consequences. In contrast, at pos t t rea tment the moda l number of consequences exper ienced was zero, with one consequence being the second mos t f requent ou tcome (the shaded area in Figure 5 indicates the increase in cases repor t ing zero or one consequence) . Figure 5 suggests that it would be reasonable for


100%

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£ a .

80%

60%

40%

20%

pretreatment . . . . posttreatment

"J ~ ' / f •

. J o/° •

0%

Not a Very Minor Major Very problem minor Major

Subject ive prob lem severity rating

FIG 6. Frequency dlstribuuons of subjects' (n = 68) pre- and posttreatment subjectwe ratings of their problem seventy

clinicians to expect that more than half of problem drinkers treated by GSC will experience one or no consequences during the year following treatment.

How Do Subjects Perceive Their Improvement?

Another variable that illustrates the value of distribution shift curves is subjects' subjective ratings of the severity of their problem. Figure 6 shows frequency distributions of problem severity ratings for the combined groups at pre- and posttreatment. In contrast to the frequency distribution for consequence scores in Figure 5, Figure 6 shows that for this variable the extent of change appears to have occurred rather evenly throughout the sample (i.e., the curve shifts to the left, but the shape is relatively unchanged). Again, although the earlier presented statistical comparison indicated a significant reduction in perceived problem severity from pre- to posttreatment, the frequency distribution makes clear that the most likely outcome was not a full remedia- tion of the problem, but rather that individuals generally did not consider any consequences they experienced to be serious, whereas the vast majority of subjects reported that prior to treatment they had experienced one or more serious consequence of their drinking.

664

8

SOBELL ET AL.

c "

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u) 0 6 "

o r - -

o- ~ 4-,, • ffl

o 1

f . . .

° I

; I

E I I

Z 0 0% 20% 40% 60'%

90 % confidence Ltrnd

RegresSio n L)ne

99% conhdence Limit

80'% 1 O0 %

Percen tage of days c o n s u m e d 5 or more dnnks, p o s t t r e a t m e n t

F]G 7 Scatter plot shorting the relauonshlp of individual subjects' (n = 64) heav:~ drinking day posttreatment and the number of consequences they experienced posttreatment The figure also ~ho~s the regression hne for the relaUonshlp and the 90% confidence limits for the hne

Did SubJects Who Drank Less Also Report Fewer Consequences?

Another aspect of individual subject outcomes that can be meaningfully examined through graphic methods is relationships between outcome dimensions. Figure 7 is a scatter plot showing the number of consequences subjects experienced over the follow-up year plotted against the percentage of days of heavy drinking (i.e., days when they consumed five or more drinks). What stands out in Figure 7 is that the relationship between engaging in heavy drinking and experiencing consequences is relatively weak. This conclusion is reinforced by the regression line drawn in Figure 7, which also shows the 90% confidence limits for the line. For any given value of the percentage of days subjects consumed/> 5 drinks after treatment, the corresponding point on the regression line represents the most likely number of consequences that would have occurred posttreatment. The distance between the confidence limits represents the range within which a value from the regression line would fall 90% of the time. Thus, allowing a 10% chance of error (the 95% confidence interval would have been even broader), the predicted number of consequences experienced by a person who drank >/5 drinks on 30% of the posttreatment days would range from 0 to 5, whereas the predicted range for a person who never drank /> 5 drinks posttreatment is from 0 to 4.5. In other words, one

P O R T R A Y I N G T R E A T M E N T OUTCOMES 665

would predict nearly the same amount of consequences for a person who had substantial heavy drinking days as for a person who had no heavy drinking days. This aspect of the findings would not be apparent from a correlational analysis, yet it has clinical importance because it means one cannot assume that just because a client's drinking is mostly light that the client will not en- counter drinking-related problems. In this regard, one other study has suggested that heaviness of drinking is not necessarily associated with consequences (i.e., alcohol dependence scores were lower in patients with cirrhosis than in those with precirrhotic liver disease; Wodak, Saunders, Ewusi-Mensah, Davis, & Williams, 1983). Taken together these findings suggest that the relationship between consequences and drinking behavior needs further study.

Discussion The main intent of this article is to illustrate how nontraditional ways of

presenting outcome data can supplement traditional methods, provide valuable information about the nature of outcomes, and facilitate comparisons among studies. Hypothetically, it is possible that the information conveyed in this manuscript could be more parsimoniously and appropriately communicated by limiting presentations to existing statistical tools. However, it seems unlikely that available statistical methods could readily communicate the richness of information contained in the graphic portrayals. Moreover, even if statistical methods could summarize the information, limiting presentations to statistics begs the following question: To whom are the findings to be communicated, and is there a preferred way of communicating these findings?

The audience to which published clinical research is directed should include practitioners and researchers. Publication of clinical research should not only inform peers about findings, it should also serve to disseminate research. For publications to have a dissemination impact, they need to be understood by the readership. It is unreasonable to expect practitioners to be experts in ad- vanced statistical techniques. In fact, we have contended that it is the responsibility of clinical scientists to present issues and findings to practitioners in a manner that facilitates their understanding and assimilation of the material (L. C. Sobell, 1994). Clearly the comprehension of graphic portrayals, such as presented here, requires some thought and effort on the part o f the reader, but it does not require specialized training. Moreover, many of the graphs cap- ture in a single picture information that it would be quite complicated to ex- tract from statistical displays. It is incumbent upon authors using these techniques, however, to accompany the graphic presentations with sufficient linguistic interpretation to allow them to be understood by the average reader.

Predictors of outcome was the one area where we were not able to identify a method of graphical presentation of findings that would add meaningfully to the statistical presentation. However, the statistical analyses presented in Table 2 do reflect some of the subtleties of outcome analyses. In particular, the extent to which predictor variables account for variance in outcomes differs depending upon the specific outcome measure being predicted. That is, some outcomes for particular variables have varying relationships to other outcome

666 SOBELL ET AL.

variables (also see Babor et al., 1994) and to premorbid criteria. For example, ADS scores were significantly related to posttreatment consequences and posttreatment abstinent days, but not to quantitative measures of drinking, such as number of drinks per week. Lower self-efficacy scores at the end of treatment were related to quantitative measures of drinking but not to posttreatment frequency of abstinence or consequences. The fact that type of goal was only significantly related to posttreatment mean drinks per drinking day is not surprising, because subjects seeking abstinence would be expected to engage in less drinking than those seeking a reduced drinking outcome. Al- though pretreatment drinking levels tended to predict posttreatment drinking, pretreatment consequences did not significantly predict posttreatment consequences. Collectively, these findings demonstrate the importance of concep- tualizing treatment outcome as truly multidimensional. Such an approach has imphcatlons for research design. From a multidimensional perspectwe, it can be hypothesized that different types of patient-treatment matching might be expected to affect certain outcome dimensions more than others.

With regard to scientific communication, it is important to consider the present state of alcohol treatment research. For decades, outcome reports have been valued for the conclusions they provide about treatment effectiveness, but the field has failed to explore the richness of information that can be provided about patterns of behavior and related change over time. Jacob Cohen (1994), an eminent psychological statistician, recently asserted that before we attempt to generahze from our data, "we must seek to understand and improve them" (p. 1001). He also suggested that we should seek standardization of measurement, and the use of"simple, flexible, informal, and largely graphic techniques" (p. 1001) for understanding data. Although the examples provided here are not exhaustive of alternative ways of presenting findings, they exem- plify the value of supplemental data presentations for increasing our understanding of clinical research phenomena. They also demonstrate that with some effort on the part of authors and readers, the value of treatment outcome research reports for clinicians can be meaningfully increased. Increased emphasis on the use of empirically based treatments as part of cost containment in the health care sector requires a greater dialogue between researchers and clinicians, and increased accountability for research funding emphasizes the need for clinical research to have a demonstrable impact on clinical practice. This attention by researchers and clinicians to each others' needs is a foundation of behavior therapy. We hope the present paper has demonstrated that the relationship can be enhanced in our publications.

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RECEIVED" December 23, 1994 ACCEPTED May 15, 1995

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