Reliability of a drug history questionnaire (DHQ)

Addictive Behaviors. Vol. 20. No. 2. pp. 233-241, 1995 Copyright 0 1995Elsevier Science Ltd Printed in the USA. All rights reserved 0306-4603195 $9.50 + .oo

Pergamon

0306-4603(94)00071-9

RELIABILITY

OF A DRUG HISTORY QUESTIONNAIRE

LINDA C. SOBELL,*I

(DHQ)

EVEN KWAN,* and MARK B. SOBELL*t

*Addiction Research Foundation, Toronto, Canada, iDepartments of Psychology, Family and Community Medicine, and Behavioural Science, University of Toronto, Toronto, Ontario, Canada Drug abusers’ self-reports are vital to clinical and research endeavors, yet few studies have explicitly examined the test-retest reliability of drug abusers’ reports of their pretreatment drug use. The present study evaluated the test-retest reliability of drug abusers’ reports of (a) lifetime drug use using a drug history questionnaire (DHQ), and (b) demographic and drug-related events. Intraclass and Pearson correlation coefficients revealed reasonably good reliability for most reports of drug use and related events. Further research needs in this area are discussed. Abstract -

Few instruments exist for assessing drug abusers’ lifetime drug use (Sobell, Sobell, & Nirenberg, 1988; Sobell, Toneatto, & Sobell, in press). Unlike alcohol and tobacco use, assessment of other drug use faces unique and difficult measurement problems (Darke, et al., 1991; Wilkinson et al., 1987). First, most drugs are illicit, a feature which could discourage honest reporting of their use. Second, since the purity (i.e., strength) of street drugs varies considerably, knowing the amount consumed is difficult at best, impossible at worst. Third, route of administration (e.g., nasal vs. intravenous) can influence the speed of onset of the drug effect. Fourth, it is difficult to capture the complexity of polydrug use because of the multitude of drugs available and the ways they are combined. There are several reasons for obtaining a profile of a client’s drug use history. First, assessment of drug use is the sine qua non for diagnosis and treatment planning. Second, assessment of drug use before and after treatment is necessary for evaluating treatment efficacy. Third, since decreased use of one drug has been associated with increased use of other drugs (Biernacki, 1986; Judson et al., 1980; Shaffer & Jones, 1989), it is important to know where change is occurring for continued treatment planning. While no single drug use questionnaire has been adopted by the drug field, investigators typically use some type of questionnaire that obtains information about a number of different drug classes (for example, see Hubbard et al., 1986; Martin & Wilkinson, 1989; Wilkinson et al., 1987). For each drug class reported as ever having been used, some combination of the following information is usually sought: (a) age first used, (b) year last used, (c) total years used, (d) frequency of use (using coded categories such as daily, once a month), and (e) route of administration (e.g., oral, nasal). Unfortunately, the lack of a standardized reporting format for drug use greatly hinders comparison of results among studies. Two major reviews of the literature published from 1967 through 1988 have identified 21 studies examining the reliability and validity of drug abusers’ self-reports of The views expressed in this paper are those of the authors and do not necessarily reflect those of the Addiction Research Foundation. Reprint requests should be addressed to L. Sobell, Ph.D.. Addiction Research Foundation, 33 Russell Street, Toronto, Ontario, M5S 2S1, Canada. 233

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drug use. In the first review (Magura, et al., 1987), 11 of 13 studies compared drug abusers’ self-reports with urinalyses, one with clinic records, and one with counselors’ reports. In the second review (Maisto, McKay, & Connors, 1990), four of the eight studies compared drug abusers’ self-reports with reports from significant others, two with urinalyses, and two evaluated subjects’ reports on two occasions (test-retest). Based on these two reviews, most drug abusers’ self-reports have been validated by urinalysis (62%; 13121). In contrast, only two studies (9.5%; 2121) have examined the stability (test-retest reliability) of drug abusers’ reports of their drug use. One of the two test-retest studies in the above reviews deserves mention because of its extensive reliability evaluation (Pompi & Shreiner, 1979). Drug abusers in a drug-free therapeutic community were asked about their regular use (yes/no) of 11 classes of drugs over their lifetime and in the last year. The test-retest interval ranged from 5.0 to 13.5 months (mean = 7.8 months). The lowest agreement for lifetime use occurred for hallucinogens (77.5%) and the highest agreement occurred for other drugs (100%) and heroin (94.5%). For use in the last year, the lowest agreement occurred for barbiturates (77.5%) and the highest for other drugs (100%) and heroin (94.5%). Generally, subjects reported less use at the first interview (i.e., at intake). Since the publication of these reviews, two further test-retest reliability studies have been published. One study examined a “recent use episodes” method, adapted from the measurement of alcohol use, for obtaining self-reports for several different drug classes (Darke et al., 1991). A subsample (50 of 290) of opioid users were retested a week after their initial interview. Pearson correlations were significant (p < .005) for all 11 drug classes and were in the moderate to high range (r = .63 to r = 1.00). Lowest agreement occurred for tranquilizers (r = .63) and cannabis (r = .66). The correlations for reports of heroin use (r = .90) and other opiates (r = .80) were higher. Collateral validation and urinalysis supported the accuracy of the subjects’ reports. Unfortunately, the “recent use episodes” method is restricted to the month before the interview and such use may not be representative of longer pretreatment intervals. In the second recent test-retest study face-to-face interviews were conducted over a lo-year interval with 439 narcotic addicts (Anglin, Hser, & Chou, 1993). The same data were collected from subjects for an overlapping period of 4 to 5 years. The frequency of daily use for narcotics, marijuana, and nonnarcotics yielded correlations of .63 (p < .Ol), .26, and .20, respectively. Taken together the reliability studies published to date show that “there is considerable variation in reliability and accuracy both within (e.g., as a function of drug or drug class) and across studies” (Maisto et al., 1990 p. 127; also see Magura et al., 1987). For most studies, though, there appears to be very good agreement for reports of heroin use, perhaps because it has often been the subjects’ primary drug of abuse. Although there are several alternatives to self-reports of drug use (e.g., hair analysis, Magura et al., 1992; urinalysis, Magura et al., 1987; official records, Maisto, Sobell, & Sobell, 198211983; reports from significant others about the subjects’ drug use, Magura et al., 1987; Maisto et al., 1990), none of these alternatives provide foolproof validation of drug use (Maisto et al., 1990; Schwartz, 1988). For example, one of the most commonly used alternatives, urinalysis, can only detect recent use which can range from one day up to several weeks depending on the drug (Schwartz, 1988). Since drug abusers’ self-reports are vital to a range of clinical and research endeavors (e.g., diagnosis, treatment planning, outcome evaluations), establishing their reliability should be a high priority for the drug field.

A drug history questionnaire

235

The present study evaluated the test-retest reliability of a drug history questionnaire (DHQ) that captures information about the extent and frequency of the use of different drugs. The reliabilities of drug abusers’ reports of their demographic and past drug-related events (e.g., arrests, hospitalizations) were also evaluated. METHOD

Subjects

Potential subjects were initially told of the study by staff members of the drug-free residential therapeutic community (Nashville, TN). Clients interested in participating in the study were asked to sign up on posted lists. The study was approved by the Vanderbilt University Ethics Committee and the Meharry Medical Center Ethics Committee. To be eligible for the study subjects had to (a) sign an informed consent, (b) be 18 through 50 years of age, (c) have a primary substance abuse diagnosis of other than alcohol, (d) have no evidence of a positive blood alcohol level as confirmed by a breath test (Sobell & Sobell, 1975), and (e) have resided in the therapeutic community for more than 7 but less than 30 days, excluding days in detoxification. All potential subjects were told that their participation would not affect their treatment. Interviewers who were not from the treatment facility screened potential subjects. Although 32 subjects completed the first interview, 12 could not be reinterviewed because they left the treatment facility prior to the second interview. A high early attrition rate is not unusual for residential drug treatment facilities (Hubbard et al., 1989). The final sample consisted of 20 drug abusers (6 females, 14 males). Demographic and drug abuse history data for subjects were gathered at the first interview. Subjects reported having had a drug problem for a mean (SD) of 6.7 (3.9) years. Slightly over half (55%) were not married when interviewed, and 90% were white. Subjects had a mean (SD) age of 23.8 (5.2) years and a mean (SD) of I I .O (2.3) years of education. Prior to entering the treatment program, almost all subjects (90%) had been employed in a blue-collar occupation, and in the year prior to treatment they had been employed full-time for a mean (SD) of 134 (136) days, or (about 27 weeks based on 5 working days/week). Subjects’ annual reportable income ranged from $3,000 to $4,000 dollars and their annual nonreportable (i.e.. illicit) income ranged from $5,000 to $10,000. Procedures

Subjects were individually interviewed at the residential treatment facility. Each subject was given an explanation (a) of the reasons for the study, (b) of how the data would be collected, and (c) was assured that all information would be kept confidential and would not be communicated to treatment facility staff. Similar explanations have been reported as helpful in gathering accurate self-reports from drug abusers (Darke et al., 1991; Maisto et al., 1990; Nurco, 1985). The mean (SD) interval between the two interviews in which subjects participated was 19.5 (4.5) days (range: 14-29). At both the first and second interview, the Drug History Questionnaire (DHQ) and a questionnaire covering demographic and other related drug events (e.g., arrests) were administered to all subjects. Seven interviewers conducted the sessions. The interviewer who conducted the second session was blind to the subject’s data from the first session. Drug History Questionnaire

(DHQ)

The Drug History Questionnaire (DHQ), a one-page form that takes about 5 to 10 minutes to complete, collected data for nine different drug classes: alcohol, canna-

236

L. C. SOBELL etal.

bis, hallucinogens, depressants, inhalants, narcotics, stimulants, tranquilizers, and other drugs. For each drug class, the following information was collected: was the drug ever used, and if so: (a) number of years used; (b) whether the drug was ever prescribed; (c) year last used; and (d) frequency of past use during a typical month (e.g., 2-3 times a week, once a month, daily). A revised version of the DHQ appears in Appendix A. This version has been updated to include drug classes that are currently used in major drug treatment studies (e.g., cocaine is now listed separately from other stimulants, Rounsaville, Tims, Horton, & Sowder, 1993). It is also recommended that the frequency of use column be left open to ask for a specific time period rather than a typical month of use as was the case in the present study. Two additional variables have been added to the revised DHQ. The first, agejirst used, although similar to total years used provides additional information for clients who have had intervening abstinent periods. Second, route of administration provides information about the way the drug enters the body and presumably the speed with which the drug takes effect. Lastly, since drinking and other drug use have a very high rate of co-occurrence with smoking (80%-90% see Sobell, Toneatto, & Sobell, 1990), tobacco/nicotine has been included as a drug class. RESULTS

Demographic and drug use history variables for the 12 subjects who could not be reinterviewed were compared with those for the 20 subjects who completed both interviews. Independent t-tests found no significant (p > .05) differences between the two groups on any variable. Table 1 shows the correspondence between subjects’ Interview 1 and Interview 2 answers for nine demographic questions and nine drug-related events. Two measures of reliability are presented: (a) intraclass correlation coefficients (ICCs) defined as the proportion of total variance of an observation that is associated with the class to which it belongs (Winter, 1971); and (b) Pearson product-moment correlation coefficients, included because they are typically reported in studies of this nature and thus allow comparisons between this and similar studies. Use of ICCs is preferred to Pearson correlations because they are unbiased and are more sensitive to changes in test-retest means (Cordingley, Wilkinson, & Martin, 1990; Maisto et al., 1990; Rounsaville et al., 1981). Of the 16 variables in Table 1 where a Pearson correlation or ICC could be computed, the results for all but one variable were significant (93.8%, 15/16). The significant correlations were all in the moderate to high range. For most variables in Table 1 where both Pearson correlations and ICCs could be calculated, the values were identical or quite similar. The percentages of subjects who gave identical Interview I and Interview 2 answers for each variable are shown in Table 1. Table 2 presents summary statistics for the correspondence between Interview 1 and Interview 2 answers from the Drug History Questionnaire. Since only three subjects reported “other drug” use, this category was excluded from further analysis. For two variables, number of years used and frequency of past use during a typical month, ICC and Pearson correlations were computed. Since correlations could not be computed for the other three variables (drug ever used, drug ever prescribed, year last used), Table 2 reflects the percentage of subjects’ Interview 1 and 2 answers that were in agreement. With one exception, there was high to very high agreement between Interview 1 and Interview 2 answers for the variables “ever used,” “ ever prescribed,” and “year last used.” For hallunicogens, while agree-

A drug history questionnaire

237

Table 1. Pearson correlation coefficients (r), intraclass correlation coefficients (ICC), and number of cases with exact correspondence between Interview 1 (II) and Interview 2 (12) answers for demographic and drug-related event variables

No. of cases Variable Demographic Marital status Race Age Highest status job ever held No. fulltime jobs past year Highest grade completed Reportable income past year No. days employed full-time past year Illicit income past year Drug-Related Events No. times fired/laid off past year due to drug use No. drug use/possession arrests No. residential treatment stays No. arrests for selling drugs No. years problem with drugs No. drug-related hospitalizations No. times ever fired/laid off due to drug use No. times quit/left job past year due to drug use No. days missed work past year due to drug use “Not applicable as correlations

n

r

ICC

II = 12 (%) -

19 19 20 20 20 19 20

N/A” N/A” 0.99*** 0.94*** 0.94*** 0.86*** 0.80***

N/A” NIAa 0.99*** 0.93*** 0.94*** 0.86*** 0.80***

19 t 100) 19 (100) 18 (90) 18 (90) 17 (85) II (58) 14 (70)

I9 20

0.71*** 0.54*

0.73*** 0.55*

8 (42) II (55)

20 20 I8 20 19 18

0.94*** 0.89*** 0.88*** 0.84*** 0.79*** 0.69***

0.94*** 0.87*** 0.88*** 0.82*** 0.79*** 0.46*

17 (85) 13 (65) I4 (78) 13 165) 8 (42) 9 (50)

18

0.66**

0.57*

13 (72)

20

0.65**

0.50*

13 (65)

20

0.24

0.22

8 (40)

_

cannot be performed on categorical data.

*p < .05. **p I .Ol. ***p 5 .ool.

ment for year last used was only 35.7%, 78.6% (1 l/14) of the subjects reported either the same year (n = 5) or were discrepant by only one year (n = 6). For two drug categories - alcohol and cannabis - there was perfect agreement for all subjects for whether the drug was ever used, for the year last used, and for every prescribed. For the variable “year last used” for the remaining five drug classes, as noted in Table 2, when subjects that reported either the same year or were discrepant by only one year are combined, agreement increases to 100% in four cases and to 94.1% in the other. Pearson correlations and ICCs for the variables “number of years used” and “frequency of past use in a typical month” were all statistically significant (p < .05) and moderately high, with the exception of frequency of past cannabis (ICC only) and stimulant use (r and ICC). In both cases, when data from two subjects were removed because of extreme scores (different subjects were removed for each drug), the r and ICC values increased [stimulants: .53 (p = .042) and .57 (p = .027); cannabis: .75 (p < .OOl) and .71 (p < .OOl), respectively]. DISCUSSION

In the present study subjects’ past drug use, both lifetime and current, was captured using a drug history questionnaire (DHQ). With certain exceptions, the results

238

L. C. SOBELL et al.

Table 2. Correspondence

between Interview 1 and Interview 2 answers on the Drug History Questionnaire

% agreement for interview 1 and 2 (Yes/Yes and No/No)

Drug class

Ever used

Alcohol Cannabis Narcotics Tranquilizers Hallucinogens Inhalants Depressants Stimulants

100.0 100.0 100.0 100.0 95.0 90.0 80.0 85.0

Year last used 100.0

100.0 86.7b 70.6’ 35.7d 80.0b 92.9b 73.3b

Ever prescribed 100.0 100.0 72.2 94.1 94.4 100.0 77.8 83.3

Number of years used

Frequency of past use in typical month

r

ICC

r

ICC

0.89*** 0.74*** 0.93*** 0.81*** 0.64**e NA’ 0.77*** 0.81***

0.87*** 0.73*** 0.93*** 0.80*** 0.66**’ I

0.66** 0.49*a 0.85*** 0.67** 0.18***’ NA’ 0.67** 0.379

0.39” 0.85*** 0.61** 0.79***e NA’ 0.69** 0.39e

0.k 0.80***

0.64**

“Inspection of the scatterplot of the raw data suggested that 2 of the 17 subjects had extreme scores. When these extreme scores were removed, the r and ICC values increased to .75 (p 5 .OOl) and .71 (p 5 .OOl), respectively. blOO%agreement occurred for subjects who reported either the same year or were discrepant by only one year. ‘94.1% agreement occurred for subjects who reported either the same year or were discrepant by only one year. dl 1of 14 (78.6%) cases either reported the same year (n = 5) or were discrepant by only one year (n = 6). ‘One subject’s data were removed from this analyses because inspection of the data revealed that group statistics were affected by this subject’s very discrepant reports. ‘Not applicable; these correlations could not be calculated as only 5 subjects reported any inhalant use. 8Inspection of the scatterplot of the raw data suggested that 2 of the 17 subjects had extreme scores. When these extreme scores were removed, the r and ICC values increased to .53 (p = ,042) and .54 (p = .027), respectively. *p < .05. **p 5 .Ol. ***p 5 .OOl.

suggest that drug abusers in treatment can reliably report information about their past drug use, demographic variables, and drug-related events. The present results are consistent with those of the few past studies examining the test-retest reliability of reports of drugs abusers’ drug use. In particular, some drug categories were reported more accurately than others. Interestingly, three of the four test-retest reliability studies with drug abusers (i.e., Aiken, 1986; Anglin et al., 1993; Pompi & Shreiner, 1979), and most of the validity studies (reviewed in Magura et al., 1987) have reported greater consistency for heroin and other narcotics compared to other drug classes. Correlations in the present study were also highest for narcotics. For the two drug classes with the lowest overall agreement (hallucinogens, stimulants) in the present study, similar findings occurred in two other studies. In one (Pompi & Shreiner, 1979), reports of amphetamine use in the prior year and reports of lifetime use of hallucinogens and amphetamines showed poor agreement over time compared to several other drug classes. The second study (Wilkinson et al., 1987), which used a questionnaire similar to the present study’s, found very low agreement between drug abusers and their collaterals’ reports of frequency of stimulant use in the past year (ICC = .29). In the present study and others (e.g., Anglin et al., 1993), better recall occurs for more frequently used drugs or the subjects’ primary problem drug (i.e., opiates). Research with drug abusers with different primary problem drugs (e.g., cannabis vs. heroin) could shed further light on this issue.

A drug history questionnaire

239

In previous studies, when subjects have been told that the information they provide will be confidential and not communicated to treatment staff, such instructions have resulted in more accurate self-reports (see Maisto et al., 1990; Nurco, 1985). In the present study similar instructions are thought to have contributed to the highly reliable reports by drug abusers. Presently, generalization of these results is limited to drug abusers in residential treatments and given strong assurances of confidentiality. An important research question is whether similar reliability can be achieved when treatment staff are aware of the reports, since such reports have obvious value for treatment. Despite finding that most drug abusers reliably report most aspects of their drug use and related events, unreliable reports from a small number of individuals can seriously affect the reliability of group findings. For example, in the present study when data for two subjects with highly discrepant reports of cannabis and stimulant use were removed from the analyses, the correlations increased and were statistically significant. Unfortunately, it is not possible to predict which drug abusers will provide the least reliable self-reports. In the present study, for example, no single subject was responsible for the majority of discrepancies across all or even most variables. Although the number of subjects in this study is not large, the study’s merit is that it is the first to report examining the test-retest reliability of treated drug users’ selfreports of lifetime and current use across several drug categories using a structured drug history questionnaire. Clearly, additional studies with more drug abusers in different treatment settings (e.g., outpatient) are needed. Future studies should also attempt to identify variables predictive of inconsistent reports. Further research in this area is necessary because (a) very little research has explicitly examined the accuracy of drug abusers’ self-reports of their use of different drugs prior to and following treatment, (b) drug abusers’ self-reports are essential for clinical management and treatment planning, (c) drug abusers’ self-reports are vital to evaluating treatment outcomes, and (d) currently there is no economically feasible alternative to self-reports. Since no data source appears error free, multiple data sources (e.g., urines, collaterals) should continue to be used to corroborate drug abusers’ selfreports both pre- and posttreatment (Magura et al., 1987; Maisto et al., 1990; Van Hasselt, Milliones, & Hersen, 1981).

REFERENCES Aiken, L. S. (1986). Retrospective self-reports by clients differ from original reports: Implications for the evaluation of drug treatment programs. Internafional Journal ofthe Addictions, 21, 767-788. Anglin, M. D., Hser, Y. I., & Chou, C. P. (1993). Reliability and validity of retrospective behavioral selfreport by narcotics addicts. Evaluation Review, 17, 91-108. Biernacki, P. (1986). Pathways from heroin addiction recovery Mirhoa/ treatmenf. Philadelphia: Temple University Press. Cordingley, J., Wilkinson, D. A., & Martin, G. W. (1990). Corroborating multiple drug users’ posttreatment self-reports by collaterals. Behavioral Assessment, 12, 253-264. Darke. S., Heather, N., Hall, W., Ward, J., & Wodak, A. (1991). Estimating drug consumption in opiod users: Reliability and validity of a “recent use” episodes method. British Journal of Addiction. 86. 1311-1316.

Hubbard, R. L., Bray, R. M., Craddock, S. G., et al. (1986). Issues in the assessment of multiple drug use among drug treatment clients. In National Institute on Drug Abuse (Ed.), Research Monogruph Series 68 (DHHS Publication No. ADM 86-1453, pp. 15-40). Rockville. MD: National Institute on Drug Abuse. Hubbard, R. L., Marsden, M. E., Rachal, J. V., Cavanaugh, E. R., & Ginzburg, H. M. (1989). Drug ahuse treatment: A national survey of effecriueness. Chapel Hill: University of North Carolina Press.

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Judson, B. S., Ortiz, S., Crouse, L., Carney, T. M., & Goldstein, A. (1980). A follow-up study of heroin addicts five years after first admission to a methadone treatment program. Drug & Alcohol Dependence,

6, 295-313.

Magura, S., Freeman, R. C., Siddiqi, Q., & Lipton, D. S. (1992). The validity of hair analysis for detecting cocaine and heroin use among addicts. International Journal of the Addictions, 27, 51-69. Magura, S., Goldsmith, D., Casriel, C., Golstein, P. J., &Lipton, D. S. (1987). The validity of methadone clients’ self-reported drug use. International Journal of the Addictions, 22, 727-749. Maisto, S. A., McKay, J. R., & Connors, G. J. (1990). Self-report issues in substance abuse: State of the art and future directions. Behavioral Assessment, 12, 117-134. Maisto, S. A., Sobell, L. C., & Sobell, M. B. (198211983). Corroboration of drug abusers’ self-reports through the use of multiple data sources. American Journal ofAlcohol and Drug Abuse, 9, 301-308. Martin, G. W. & Wilkinson, D. A. (1989). Methodological issues in the evaluation of treatment of drug dependence. Advances in Behavioural Research and Therapy, 11,133-150. Nurco, D. N. (1985). A discussion of validity. In B. A. Rouse, N. J. Kozel, & L. G. Richards (Eds.), Self report methods of estimating drug use: Meeting current challenges to validity. (National Institute on Drug Abuse Research Monograph No. 57, pp. 4-11). Rockville, MD: National Institute on Drug Abuse. Pompi, K. F. & Shreiner, S. C. (1979). The reliability of biographical information obtained from courtstipulated clients newly admitted to treatment. American Journal of Drug and Alcohol Abuse, 6, 7995.

Rounsaville, B. J., Kleber, H. D., Wilber, C., Rosenberger, D., & Rosenberger, P. (1981). Comparison of opiate addicts’ reports of psychiatric history with reports of significant-other informants. American Journal

of Drug and Alcohol Abuse,

8, 51-69.

Rounsaville, B. J., Tims, F. M., Horton, A. M., Jr., & Sowder, B. J. (1993). Diagnostic source book of drug abuse research and treatment. Rockville, MD: National Institute on Drug Abuse. Schwartz, R. H. (1988). Urine testing in the detection of drugs of abuse. Archives of Internal Medicine, 148,2407-2412. Shaffer, H. J. & Jones, S. B. (1989). Quitting cocaine: The struggle against impulse. Lexington, MA: Lexington Books. Sobell, L. C., Sobell, M. B., & Nirenberg, T. D. (1988). Behavioral assessment and treatment planning with alcohol and drug abusers: A review with an emphasis on clinical application. Clinical Psychology Review, 8, 19-54. Sobell, L. C., Toneatto, A., & Sobell, M. B. (1990). Behavior therapy (Alcohol and other substance abuse). In A. S. Bellack & M. Hersen (Eds.), Handbook of comparative treatments for adult disorders (pp. 479-505). New York: John Wiley. Sobell, L. C., Toneatto, A., & Sobell, M. B. (in press). Behavioral assessment and treatment planning with alcohol and other drug abusers: A review with an emphasis on clinical application. Behavior Therapy.

Sobell, M. B. & Sobell, L. C. (1975). A brief technical report on the Mobat: An inexpensive portable test for determining blood alcohol concentration. Journal of Applied Behavior Analysis, 8, 117-120. Van Hasselt, V. B., Milliones, J., & Hersen, M. (1981). Behavioral assessment of drug addiction: Strategies and issues in research and treatment. International Journal of Addictions, 16, 43-68. Wilkinson, D. A., Leigh, G. M., Cordingley, J., Martin, G. W., & Lei, H. (1987). Dimensions of multiple drug use and a typology of drug users. British Journal of Addiction, 82, 259-287. Winer, B. J. (1971). Statistical principles in experimental design. New York: McGraw-Hill.

A drug history

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241

APPENDIX

Ever Used’ DRUG

A% Fir*1 Used

Total Y&XI? Clsed

CATEGORY

51~ Typical Ruuw of Adm~msrrarw I = Old1 2 = rnllicd 3 = m,cctcd

I =No 2=Yrs

YtXlf L‘lSl 11wd

1 = ,“,,,ked 5 = ,“h,dcd 6 = olhcr

Frequency of uw I” Past _ Day\-”

Ever Prcxnhed

I = N,, 2 = YC\

IO_

ALCOHOL

xxxxx

CANNABIS:

Mx~Ju~“~. hashish. hash “11

STIMULANTS:

xxxxx

Coca,neKrack

xxxxx

STIMULANTS. Methamphetamlnc-speed. KX. crank

xxxxx

AMPHETAMINES /OTHER STIMULANTS. R”alm. Beneednne, Dexedrlnr

xxxxx

BENZODIAZEPINES/MlNOR TRANQUILIZERS.

INHALANTS:

V&urn.

Lihnum.

Clue. gasohne. derosols. pant xxxxx

BARBITURATES/OTHER SLEEPING PILLS. Seconal. Nemhutal. Phenobarbital

I

HALLUCINOGENS LSD. PCP. STP. MDA. DAT. mescalme. pstlocyhm. peyote. mushrooms, ecstasy

I

II

1

1

j

I:::::

SEDATIVES/HYPNOTICS. Donden. Dalmane. Quaalude. Amytal. Fmrinal I

llwar~ne.

MAJOR TRANQUILIZERS. Stelaz~ne, Llthlum. Mellanl.

Haldol

NICOTINE

xxxxx

OTHER PSYCHOACTIVE

NOIC,

DRUGS: (Speafy)

1

*If “EVER USED” is NO (I for any given line. the remainder of the hne should he left blank

** Freauencv

Code\

I =< Ix/month 2 = Ix /month

Fig. Al.

Revised

Drug

History

Questionnaire

3 I\ /week 4=?toix/week 5 = 4 10 hx iweck

(DHQ).

Ikid‘l!

h= 7 = > I X/d.,)