CASE PUZZLES AND RESEARCH DESIGNS

LETTERS TO THE EDITOR

continue to emphasize therapy in trammg, research, and journal articles so that other child and adolescent psychiatrists seize these moments also. Please continue to publish articles such as Dr. Ablon's to promote positive thinking about play and play therapy. Ronald T. Stachler, M.D. Tri-County, The Center for Family Counseling Carmel , IN To the Editor:

I applaud the evolution of the Journal, manifested in the April 1996 issue, beginning with the special article on pharmacotherapy by Spencer et al. and concluding with the refreshing article on play by Ablon in Clinical Perspectives. A comment on Ablon's article: It is most refreshing to read such a perspective on the value of therapeutic play. Undoubtedly, one would have difficulry getting managedcare approval ofAblon 's therapeutic approach. However, isn't it time that we child psychiatrists promote such therapeutic interventions and stand up for ourselves? Alex Weinrrob, M.D. New York

CASE PUZZLES AND RESEARCH DESIGNS To the Editor:

Joseph M. Strayhorn's clever statistical case puzzle (Strayhorn, 1996) was a delight , but I wish to challenge one point in his ranking of the six designs. He ranked the nonequivalent control group design (No.5) third, ahead of the time series design (No.1, ranked fourth), because the latter does not protect well against events that happen to all subjects as a group, such as good economic news for the town or the town's team winning the championship. He argued that if such an event occurred just as the treatment was given, it could show spurious changes temporally linked to treatment in the repeated measures. This would indeed be a problem if all subjects received the treatment at precisely the same time. However, the practicalities of clinical treatment research make it very difficult to accumulate a large enough group of patients quickly enough to begin a research treatment with all simultaneously. Availabiliry of therapist time might even make it logistically unfeasible. Unless the treatment requires group sessions, subjects are ordinarily started as they become available, and the entry into treatment of a sizable sample may extend over a year or two, often with the first subjects finishing before the last are recruited. In the time series example given, assessments were monthly

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AM . ACAD . CHILD ADOL ESC. PSYCHIATRY , 36 :1 , JAN UAR Y 199 7

and the treatment was given between the fourth and fifth assessments, hypothesized to be effective in a month. If the treatment months were spread evenly over a year's recruitment, only \112 of the subjects would have the event fall dur ing their treatment month. This 8% risk seems tolerable to me. Thus the practicalities of clinical research, while posing many problems otherwise, seem to solve this one. I submit that resolution of this problem makes the time series design more statistically attractive than the nonequivalent control group design. I hope that Dr. Strayhorn will agree, and I hope that he will write more of these interesting and thought-provoking pieces. I also wish he had ranked a retrospective chart review with retrospective estimates of improvement (not offered by the genie) as No.7, in last place. Although he does not claim to be a genie, perhaps he could make these three wishes come true? 1. Eugene Arnold, M.D., M.Ed. Ohio State University, Columbus Strayhorn ]M (1996). The case of the editor's genie. JAm Acad Child Adolesc Psychiatry 35:686-688

Dr. Strayhorn replies:

I appreciate Dr. Arnold's insightful and kind words. I agree with Dr. Arnold that time series designs are underrated and would add that they seem to fit most unobtrusively into clinical practice. Only selected patients are willing to be randomized to treatment groups; probably hundreds of times more patients are willing to try various treatments in succession while clinical outcome is repeatedly measured. This is what usually happens in clinical practice anyway, in less standardized fashion. Successfully organizing and extracting the information available from repeatedly measuring clinical outcomes over time as different treatments are applied could drastically increase the rate with which our field accumulates knowledge. If this happens, time series designs will occupy a more prominent place in future volumes of psychiatric journals than they have in past ones. In some behaviorist journals the time series design has been a mainstay; the "multiple baseline across subjects" is similar to the one to which Dr . Arnold refers. Cook and Campbell (1979) write of the "interrupted time series quasi-experimenr' t-s-rhe word "interrupted" signifies that the intervention interrupts the baseline series of measurements. As Dr. Arnold points out, staggering the intake of patients does solve the problem of discrete extraneous causal events I mentioned, which Cook and Campbell call "history." There are a few other problems , though. The interrupted time series allows placebo treatment if it is felt to be necessary; it can be given during the baseline period ,

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LETTERS TO THE EDITOR

and the switch to active treatment can be " blind." But if the subjects know they are in this type of study, they will not be blind to the fact that the first few measurements will be with placebo and the last few will be with active treatment. This is a greater problem if outcome measurement relies on self-report, and patients' expectancies about treatment efficacy can bias measurement. My own biggest problem with these designs is how to do the statistics. Most introductory statistics books will adequately explain how to analyze nonequivalent control group comparisons. the competitor of time series designs in this discussions. But with time series analyses, what do you do when preintervention baselines aren't flat: when temporal trends in the observations exist independent of the intervention? In other words, the condition for our particular set of subjects may tend to get better or worse over time, and the question is whether the intervention makes a change in that trend. Cook and Campbell called these trends "maturation" ; we might here call them the " natu ral history of the disorder," or even " response to factors other than the official intervent ion," such as the effects of a growing relationship with the clinician over time. These effects are different from, but may be confused with, changes due to regression to the mean, wherein subjects who selected themselves for treatment in response to a randomly fluctuating downturn in their course tend to improve by random fluctuation in the other direction. In a design with two groups , the correction for " matu rational" change occurs when our statistical calculations can be considered to "adjust" the scores of the experimental group by comparing them with those of the control group , e.g., by subtracting the control mean from the experimental mean. The maturational changes are assumed present in both groups, and in the subtraction we hope they cancel out. For the time series designs we speak of, we have the temporal trends as inferred from the preintervention slope as our only information on which to base a correction for these trends. Perhaps the best way to correct for such trends is to regress the outcome measure on time for the preintervention data points only, and use the resulting regression equation to construct a "derrending" adjustment to be applied to all data points; analysis of variance could then be carried out on the adjusted scores. But I've never seen this technique used in a study, nor found it advocated in my fledgling and distinctly nongenie-esque forays into statistical writings on analysis of time series (e.g., Box and Jenkins , 1976; McCain and McCleary, 1979; Koch et al., 1988). Joseph M. Strayhorn. M.D. Wexford, PA Box GEP . Jenkins GM (1976). Time-Series Analysis: Forecasting and Control. San Francisco: Holden-Day

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Cook TD. Campbell DT (1979). Quasi-Exptrimtntarion: Design andAnalysis [SSUtS fOr Fitld Stttings. Boston: Houghton Mifflin Koch GG . ElashofTJD. Amara IA (1988) . Repeated measurements: design and analysis. In: Encyclopedia of Statistical Sciences, Vol 8. Korz S. Johnson NL. ed. New York: Wiley. pp 46-73 McCain LJ. McCleary R (1979). The statistical analysis of the simple interrupted time-series quasi-experiment . In: Quasi-Expmmtntation: Design and Analysis [SSUtS fOr Field Smings. Cook TD. Campbell DT. Boston: Houghton Mimin. pp 233- 294

NALTREXONE FOR ALCOHOL ABUSE To the Editor: The use and abuse of alcohol among adolescents is of great concern because of its serious short-term and longterm effects on the individual, his or her family, social circle, and the community. There is a deficit of empirical research in the literature on treatment of alcohol use disorders among adolescents. It is imperative to advance knowledge by investigating innovative psychosocial and psychopharmacological treatments. The opiate antagon ist naltrexone has been found to be safe and effective in the treatment of adult problem drinkers (Bohn et al., 1994) and adult alcoholics with concomitant psychosocial interventions (O'Malley et aI., 1992) and without (Volpicelli et aI.• 1992). An oral daily dosage of 50 mg reduced risk of relapse, levelsof craving, and number of drinking days. A minority of patients experienced nausea, headache, and dizziness early in treatment. Also, elevated hepatic transaminase levels were observed in a limited number of patients when dosage exceeded six times the recommended daily oral dosage of 50 mg. There has not been any report regarding the use of naltrexone for adolescent alcohol use disorders. It is hypothesized that naltrexone may produce similar benefits among adolescents. Naltrexone is no stranger to child and adolescent psychopharmacology, and it has been reported to be safe in the treatment of autistic patients with self-injurious behavior (Campbell et al., 1996). We would like to report about the feasibility. safety, and potential efficacy of treatment with naltrexone in a 17-year-old African-American male patient with alcohol dependence. The patient was admitted to an adolescent partial hospitalization program for the treatment of alcohol dependence and marijuana dependence diagnosed according to DSMIV criteria. The patient had had no previous treatments; he reported a 6-year history of daily drinking that most recently included three to four 40-oz beers and approximately onehalf pint of gin. No seizures, head injury, or blackouts were reported . The patient 's immediate family included father. mother, and two adult brothers. all of whom were alcoholdependent. He had legal problems due to assaultive behavior while intoxicated. and he had dropped out of school and had joined a local gang. The patient's last use of alcohol

J. AM . ACAD . C H I L D ADOLES C. PSYCHIATRY. 36: \, JANUARY 1997