The Characterization

of Inconsistencies

in

Self-Reports of Alcohol and Marijuana Use in a

Longitudinal Studyof Adolescents* SUSAN L. BAILEY, PH.D., ROBERT L. FLEWELLING,

PH.D., AND J. VALLEY RACHAL, M.S.

ResearchTriangleInstitute,Centerfor SocialResearchand PolicyAnalysis,P.O. Box 12194,ResearchTrianglePark, North Carolina

27709-2194

ABSTRACT. The reliability of self-reportedmeasuresremains an important issue for researchon adolescentalcohol and drug use. Many studieshave concludedthat adolescents'self-reportsare valid and reliable, but few studies have excluded consistent nonusers from

their reliabilityestimates,and no studyhas examinedin detail the reliabilityof reportedage at first use of substances. This studyexploresthe consistencyof self-reportsof frequencyof use and age of first use of alcoholand marijuanain a sampleof 5,770 secondary schoolstudentsin a southeastern U.S. county.Two wavesof data were collectedbetween1985 and 1988 usingstate-of-the-artdata collectionprocedures and self-administered instruments. Consistency of reportswas examinedby comparingreportsat Tl and T2, approxi-

OSTOFWHATIS KNOWN about adolescent drug

and alcohol use is based on self-reportsof use, which are often retrospectiveand, hence,subjectto recall and other types of errors. Studiesfocusingon the prevalence and frequencyof use, ages of first use, sequences and patterns, and predictors of drug and alcohol use among adolescentsall rely on self-reportedmeasures (e.g., Bailey and Hubbard, 1990; Johnstonet al., 1989; Kandel and Faust, 1975; National Institute on Drug Abuse, 1990; Newcomb and Bentlet, 1986; Rachal et al., 1976; Yamaguchi and Kandel, 1984). Because of the

heavyrelianceon self-reportedmeasuresand the sensitive natureof substance use in general,a considerableamount of attentionhasbeendevotedto determiningthe degreeof validity and reliability of these measures(Akers et al., 1983; Martin and Newman, 1988; Nurco, 1985; Single et al., 1975; Smart, 1975; Whitehead and Smart, 1972). The

mately I year apart. Resultsshowedthat when consistentnonusers were droppedfrom the analysis, consistencyrates of lifetime frequencyof use droppedfrom 82.7% to 74.7% for alcohol and from 95.6% to 83.2% for marijuana. Reportswere more consistentfor lifetime marijuanausethanfor alcoholuse, but theseresultsmustbe interpretedwith cautiongiven differencesin the measuresfor the two substances. Reliabilityof reportedageof first usewasvery low for both substances. When consistentnonuserswere droppedfrom the analysis,only 27.8% of respondents made consistentestimatesof their age at first alcoholuseand 34.4% for their age at first marijuana use. Implicationsand recommendationsfor this area of researchare discussed.(J. Stud. Alcohol 53: 636-647, 1992).

reports emerge. For example, in spite of considerable attentiongivento sequencing and stagetheoryresearchin adolescentdrug use, no identified studieshave investigated the reliability of data on age at first use. Most of these studies, in addition, included consistentnonusersin

their analysesof the reliabilityof data on frequencyof use. This inclusioninflates the proportionof consistent and reliable reports,especiallyfor drugsthat have been used by few respondents.When the consistentnonusers are excluded,the proportionof userswho report consistently may be much smaller. The analysespresentedin this studyfocuson patterns of inconsistencies amongadolescents who reportedsome type of use on at least one of the measuresexamined.Unlike mostprior studies,this one excludesconsistent nonusersfrom examinationsof patternsof consistencies and

inconsistencies. A greatdealof attentionis givento characterizingthe patternsof inconsistencies. The longitudinal designof the studypermitsthesepatternsto be assessed over time (external consistency)as well as within each survey(internalconsistency).This studyis also the first

general conclusionmade by these studiesis that selfreportsof substanceuse among adolescentsare valid and reliable.

In a careful review of these studies, however, some im-

portantunresolvedissuesrelatedto the reliabilityof self-

to examinepatternsof inconsistencies in measuresof both frequencyof use and age at first use. The goalsof this study,therefore,are to (1) characterize patternsof external inconsistencies; (2) measureand comparerates of inconsistentself-reportsof alcoholand marijuanause;(3) measureandcompareratesof inconsistent self-reportsof lifetime frequencyand ageat first use;

Received:December21, 1990. Revision:April 2, 1991. *The analysisreportedin this studywas supportedby NationalInstitute on Alcohol Abuseand AlcoholismgrantAA07666-03. Data collection was supported by NationalInstituteon Drug AbusegrantDA37971 (RobertL. Hubbard,Ph.D., principalinvestigator). 636

BAILEY

and (4) measureand comparerates of internaland external inconsistencies.

Reviewof Approachesto Assessing Self-ReportedData Internal validityrefersto how reliablyor consistently a behaviorof interestis measured.Internal validity (i.e., reliability) has beenassessed with a variety of strategies.A minimumrequirementfor the validityof a conceptis that it can be reliablymeasured.Thus, it is often usefulto examine reliability as a first step in assessing measurement validity. Analysesreportedin this studyhave focusedon the reliability of self-reporteddrug use in a cohort of adolescents.

Two of the morecommonmethodsof assessing reliability of psychometric measuresare test-retestreliabilityand interitemreliability.The latter is usedto assessreliability of items within a unidimensionalscale. This approachis not generallyviable for drug use studies,which typically useindividualquestionsratherthan scales(seeGrahamet al., 1984, for an exampleof this approach).Test-retestreliability relieson the assumptionthat the conceptof interest is inherentlystable.For manydrug usemeasures,such as currentuse, this assumptiondoesnot hold. In confronting this issue,O'Malley et al. (1983) employedstatistical methodsthat adjustedfor estimatedinstabilityin measures of current use. Other studiesemployingtest-retestdesigns either have examined measures that allow detection of im-

possibleor incongruousresponsepatterns,or have used short enoughtest-retestintervals that stability could be assumed.

Consistencyin responsepatternsover time has beenreferred to as external consistency.Alternatively, internal consistencyis assessedby examiningwhether response patternsto relateditemswithin the sameadministration of the surveyinstrumentare consistent.Althoughsomestudies haveexaminedonly internalconsistency(Swadi, 1990) or only externalconsistency(Czarneckiet al., 1990; Sobell et al., 1988), many have evaluatedboth aspectsof consistency of self-reporteddrug use (Barnea, 1987;Needle et al., 1983; Needle et al., 1989; O'Malley et al., 1983; Singleet al., 1975; Williams et al., 1985). A number of thesestudieshavealso includedan analysisof nonresponserates and self-reporteduse of fictitious drugs, both of whichprovidefurther informationconcerningthe validity of their drug use measures. Most of the aforementionedstudies, the majority of which were conductedon adolescents or high schoolstudents,concludedthat self-reported drugandalcoholuseis reliablymeasured.Thesefindingsechothe conclusions of earlier studiesreviewedby Smart (1975) and Smart and Jarvis (1981). Most of these identified studiesemployed correlationcoefficients(e.g., the test-retestcorrelation)to quantify the level of externalconsistency. Althoughcommonly usedin psychometrics, correlationcoefficientsare

ET AL.

637

not easily translatedinto a clear and usefulunderstanding of how unreliabilitymay impact studyresults.This is especially problematicfor studieswhosemeasuresare not inherentlystable. An even more troublesomeaspectof previousstudiesis that very few make any adjustmentfor prevalenceof nonuse whenmeasuringreliability.When basedon the whole sample,correlationsor other measuresof consistencyof items for seldom-reported drugs are mathematicallyconstrainedto be high becausethey reflect a consistentpattern of reported nonuse. This would explain why some studiesof adolescentdrug use report higherresponseconsistencyamong illicit drugs than among the more commonly used substances of beer and wine. For example, Needle et al. (1983) reportedthat the percentageof consistentresponsesfrom pretestto posttestwas 85.1% for beer, 87.7% for wine and 96.1% for marijuana. Similarly, Barneaet al. (1987) reportedconsistencyof lifetime use between Times 1 and 2 as 80.6% for beer, 79.4% for wine

and over 99% for rarely usedsubstances suchas hashish, amphetamines and opiates. In contrast, Single et al. (1975) did report rates of consistentand inconsistentresponsesover time for both the total sampleand for drug usersonly. When basedon only self-reportedusers,rates of consistentresponsesfor marijuanawere similar to thosefor beer/wineand for distilled spirits. The rates of consistentreporting of less commonlyused illicit drugs, however,were considerably lower than the rates for both alcohol and marijuana. In general,therefore,if consistentnonusersare excluded,responseconsistencymight be considerablyless than when they are includedand may not necessarilybe the highest for illicit drugs. This concern about inflated estimates of reliability whenincludingconsistentnonusersin analysesfollowsthe conclusionsof Maisto et al. (1990). These authors reviewed a number of studiesthat assessedthe validity of self-reportedmeasuresamongsamplesof substanceabusers and concludedthat "the typical degreeof reliability and accuracyof samplesof drug abusers'self-reportsof drug use is not high" (p. 127). Inasmuchas a primary goal of many studiesof adolescentdrug use is to identify and studydrug users,the high estimatesof measurement reliability based on entire samples,includingconsistent nonusers,may in fact be misleading. Method

Data collectionprocedures

The data usedin this analysiswere collectedas part of two studies:the Study of Multilevel SubstanceAbuse Preventionfor High Risk Youthand the Studyof Sequencing of Alcohol, Drugs, and TobaccoAmong Youth. The major objective of the first study was to examine the

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effectsof preventionprogramsfor more than7,500 urban and rural sixth to ninth grade studentsin a southeastern U.S. county, basedon the resultsof data collected from 1985to 1988. The objectiveof the secondstudy,currently underway, is to extendcurrentknowledgeaboutthe developmentand maintenanceof substanceuse patterns. Eight urban and five rural schoolshave participatedin both studies.

All of the studentsin the gradesof interestwere interviewed using school-basedself-administeredquestionnaires at baseline(T1) and a follow-up approximately1 year later (T2). The baselinesessionresultedin a 90% rate of completion.A makeupsessionyieldedanother5% for a final completionrate of 95.3%. Parentsof approximately 1.5% of the studentsdid not wish to have their childrenparticipatein the survey,and another1% of the studentschosenot to participate.Participationrateswere similar for all of the schoolsin the survey. Attemptswere made to locate and interview all of the baselinestudentsfor the follow-upapproximately1 year later. Follow-upquestionnaires were completedby over 75% of the studentsstill enrolled in the 13 secondary schools.Most of the studentswho transferredduring data collection

to schools not included in the baseline data col-

/ NOVEMBER

1992

The lifetime frequencyof use measuresfor alcoholand marijuana, on the other hand, were not identical. The marijuanaitem asked: "How many times have you ever usedmarijuana(pot, grass)?"Responsecategorieswere: never used, one time, 2-5 times, 6-10 times, 11-49 times and 50 or more times. The alcohol item asked: "How

much

beer,wine or liquor did you ever drink at one time?" Responsecategorieswere: I never had a drink, 1 drink or less, 2 drinks, 3 drinks, 4 drinks, 5 drinks, 6 drinks, 7-11 drinks and 12 or more drinks. Thus, the lifetime fre-

quencymeasures for alcoholand marijuanaare conceptually differentandhaveimplicationsfor comparisons in the consistency of self-reportsof usingthesetwo substances. Sample characteristicsand resultsof the attrition analysis

Only studentswho completedthe baselineand followup questionnairesare includedin the analysis.Of 4,748 studentsin eight urban schoolswho completedthe baseline questionnaire in December1985, 3,534 completedthe follow-upquestionnaire in May 1987. Of 2,814 studentsin five rural schoolswho completedthe baselinequestionnaire in October 1986, 2,236 completedthe follow-up questionnairein February 1988. The baseline/follow-up

lection(i.e., countyhigh schools)were tracedand reinterviewed. (Resultsof the attrition analysisare presentedin

attrition rates, therefore, are 25.6% for the urban schools

a later section.)

Generally, the studentswere in grades six, seven or eight at baselineand gradesseven,eight or nine at followup. Approximatelyone-thirdof the studentswere in each of the three grades;51% were male; 69% were white and

Questionnaireadministrationat each school was con-

ductedby professionally trainedsurveyinterviewers.Ques tionnaireswith preassigned numberswere distributedto each student named on the class roster, but names were

never enteredon the questionnaires.Interviewersread instructionsand a summaryof the study to the students, guaranteedthe confidentialityof responses, and explained how students' names would never be linked to their an-

swers.Studentsthen read and respondedto the questions themselves,at their own pace. As the studentscompleted the questionnaires, they placedthem in a large envelope kept by the interviewer;the interviewerthen sealedthe envelopeat the end of the sessionin the presenceof the students.

Measures

Measuresusedin this analysiswere takenfrom both the baselineand follow-up questionnaires developedfor the Studyof Multilevel SubstanceAbusePreventionfor High Risk Youth.The measureswere self-reportsof agesat first alcoholand marijuanause and lifetime frequenciesof alcoholand marijuanause. The age at first usemeasuresfor alcoholand marijuanawere identical. Both asked:"About how old were you when youfirst tried.... (marijuana) (beer,wine or liquor [notjust a sip or taste])?" A "never tried" responsecategorywas includedin additionto age choices.

and 20.6%

25%

for the rural schools.

were black.

The

13 urban and rural

schools were

heterogeneousin terms of predominantsocioeconomic composition. Analysisof selectbaselinemeasurescomparingstudents who completedthe baselineand follow-upquestionnaires to those who completedonly the baselinequestionnaire showsthat the responsesdiffered for the two groups.T testsreportedin Table 1 demonstrate that the respondents who completedonly the baselinequestionnairereported greater lifetime frequenciesof alcohol and marijuanause and slightly lower academicgrades comparedto those who completed both questionnaires.Respondentswho completedonly the first questionnairewere also more likely than the othersto be non-white.The mean differencesin sex, gradesand race/ethnicitywere not particularly large, but they were statistically significant. The mean differencesin the lifetime frequencymeasures,on the other hand, were substantial.

The baselinerespondents who did not participatein the follow-up data collection reported consuminga greater numberof alcoholicdrinksand reporteda greaterlifetime use than did those who completed both questionnaires. Thesefindingssuggestthat test-retestreliabilitymay have beenoverestimatedby previousstudiesthat basedassessmentson all respondents (includingconsistentnonusers). These findings are also of interestbecausethey demon-

BAILEY

ET AL.

639

TABLE1. T-testcomparison of students who participatedin bothroundsof datacollectionto thosewho participatedin only the first round Studentswho participated in both rounds of data collection

Variable

Male (1 =Male) Grades(l=mostly D's and F's to 8=mostly A's) White (1 =white) Greatest number of drinks

Lifetime frequencyof marijuanause

Studentswho participated in only the first round

Mean (+ SD)

N"

Mean (-+ SD)

N"

0.51 -+0.50 5.76-+ 1.61 0.69-+0.46 1.31-+2.19 1.02 -+5.67

5,770 5,729 5,738 5,692 5,689

0.54-+0.50 5.20-+ 1.81 0.64-+0.48 2.01 -+2.92 2.72 -+9.70

1,780 1,765 1,773 1,735 1,729

Prob>

ITI

0.04 0.00 0.00 0.00 0.00

"Samplesizesvary becauseof missingvaluesacrossvariables.

strate a general tendencyfor study dropouts(i.e., the chronicallyabsent,truants,frequentmovers,etc.) to be at a higher risk for alcohol and drug use than the general studentpopulation.For this study,the major concernfor attrition bias is whether the reliability of self-reportsof marijuanaand alcoholuserswho were not followeddiffers from thosewho were followed. Using TI data only, this questionis addressedempiricallyin the next section. Results

older than the respondent's self-reportedage at T2). Otherwise, inconsistencies can be characterized as the same

typesof errors(logicaland estimation)as in the frequency measures.The patternsof consistencies and inconsistencies for the age measuresare presentedin Figure 2. Logicalerrorsare represented by cellsb, d, e, and k in Figure2. Theseare casesin which patternsof reported agesof first useof alcoholand marijuanaare impossible. Casesfoundin cell b reportedno useat TI and an initiation age at T2 that was eitheryoungerthan or the sameas

the self-reported ageat T1.I Students included in cell d

Characterizationof external inconsistencies

reportedan initiation age at T2 that was older than their

The first goal of this analysiswas to characterizethe externalinconsistencies in self-reportedlifetime frequencies of alcohol and marijuanause and in self-reported agesat first use of thesesubstances. The possiblepatterns of inconsistencies for frequencymeasuresare different from thosepatternsfor age measures.The frequencymeasuresare examinedfirst, with the possiblepatternsof external inconsistencies in this type of measureillustratedin Figure 1. Frequency measures. Because these are measuresof lifetime use (i.e., numberof times ever used marijuana and greatestnumber of drinks ever consumedat one time), thereare two possibletypesof obviousinconsistencies. First, studentscould report somefrequencyof life-

was a logical error. Casesin cell e denied use at T2 that

age at T2. Regardless of what they reportedat T1, this

time use at T1 and no lifetime use at T2. Second, students

could report somelevel of lifetime use at T1 and a lower level of use at T2. Thesetwo typesof inconsistencies can be characterizedas logical errors and estimationerrors, respectively.Logical errorsproducedistortionsin the estimatedprevalenceof lifetime use, whereasestimationerrors causedistortionsof the estimatedintensityof lifetime use. These two typesof errors are representedby cells c and d in Figure 1. Age measures.Determiningthe patternsof inconsistencies in the age at first use measuresis morecomplicated than determiningthe patternsfor the frequencymeasures becauseone more pieceof data is availablefor constructing the age patterns--theself-reportedage of the respondentat T1 andat T2. In somecaseswherereportingseems to be consistent (i.e., no age, meaningno use, is reported at T1 and an age is reportedat T2), the agereportedmay be an obviouserror (e.g., the age at first use is 2 years

they had reportedat TI, and casesin cell k reportedan ageof initiationat T1 that was olderthantheir age at T1. Theseare all considered logicalerrorsbecausetheyrepresentimpossiblesituations. Estimationerrorsare represented by cells g, h andj in Figure 2. Casesin cell g are studentswho reportedan initiation age at T1 that was youngerthan their current age and, at T2, reportedtheir T 1 age or their age between T I and T2. Studentsin cell h reportedtheir T1 age at T1 and a pre-T1 age at T2, and thosein cell j reportedtheir T1 age at T1 and their age between T1 and T2 at T2.

Theseare all casesin whichthe two reportedagesdiffer by I or more years.The reportedagesare not logically impossible,nor do they reflectconflictingreportsof ever having used marijuanaor alcohol;they are simply not consistent.

It shouldbe notedthatapparently consistent patternsof self-reportingmay in fact containinconsistencies that simply cannotbe detected.This is probablymore likely to occurwith the frequencyof use measuresbecausethe requirementsfor consistency in the frequencymeasuresare slightly less strict than those for age at first use. Conversely,the stricterrequirements for consistency in reported age at first use might increasethe likelihood of finding inconsistent reportsfor that measure. Comparisonanalyses

Consistentand inconsistentpatterns in the frequency measures.Percentagesand ratios of studentswith the con-

sistentand inconsistent patternsillustratedin Figure 1 are

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Lifetime Use at T2 Compared to T1 No Use

Use at T2 < T1

-- T1

No Use

a

Use

c

d

Consistent

Nonuse

Consistent

Estimation

> T1

b

Lifetime Use at T1

e

f

= a

= b+e+f

Logical Error - c Estimation

Error = d

FIGUREI. Possiblepatternsof consistent and inconsistent reportingof lifetimefrequencies of alcoholand marijuanauseat Tl andT2

presentedin Table 2. Percentages and ratios are reported for both the alcohol and marijuana lifetime frequency measures.The ratios comparenot only percentageswith consistentestimationto thosewith any type of error (logical or estimation), but also percentageswith logical to estimationerrors.Thosereportingconsistentnonusewere not includedin theseratios becausethey were not consideredto be at risk for makingan error in reporting,unless, of course,they deniedactualuse at both data collection points.This potentialdenialof use,however,couldnot be examinedwith thesedata. For the samereason,adjusted percentages, in which consistentnonusersare excluded from the denominator,are also presentedin the tables. Thesepercentages indicatethe relativelevelsof consistent andinconsistent reportingonly amongthosewho reported some involvement

at either T1 or T2.

For the alcohollifetime frequencymeasures,the largest percentageof students(51.1%) made consistentestimations of their frequenciesof use. Nearly 32% were consistent nonusers.Over 17% made either type of error--

11% made logical errors and 6.3% made estimation

errors.Among usersonly, 16.1% madelogicalerrorsand 9.2% made estimation

errors. The ratios indicate that stu-

dents who used alcohol were nearly three times more likely to make consistentestimationsthan to make either type of error; if they did make an error, they were 1.7 TABLE2. Percentages with eachtype of patternof consistent and inconsistentreportingof lifetime frequenciesof alcoholand marijuanause at TI

and T2

Alcohol (n•- 5,564)

Patterns

Marijuana (n=5,575)

%

Adj. %

%

Adj. %

Consistent nonuse Consistent estimation

31.6 51.1

74.7

73.8 21.8

83.2

Logical error

11.0

16.1

Estimation error Total

6.3 100.0

9.2 100.0

2.7. 1.7 100.0

10.3 6.5 100.0

Ratios

Consistent estim.: Error

2.9

4.9

Logicalerror: Estim. error

1.7

1.6

Note: Caseswith missingvalueson either measureat either data collection pointare excludedfrom this table.

BAILEY

ET AL.

641

Age Reported at T2 Before

No Use No Use

Age Reported at T1

Between

T1

a

At T1

b

h

At T1

T2

c

f

Before T1

T1 & T2

After

g

i

j

d

e

Between T1 &T2

k After T2

Consistent

Nonuse = a

Consistent

Estimation

= c+f+i

Logical Error = b+d+e+k EstimationError = g+h+j

FIGURE 2. Possible patterns of consistent andinconsistent reporting of ageat firstuseof alcoholandmarijuana at TI andT2 (usingknowledge of respondent's age at TI)

times more likely to make a logical than an estimation error.

For the marijuanameasures,the largestpercentageof students(73.8%) were consistentnonusers.Still, nearly 22% made consistentestimationsof their lifetime frequencies of use. Only 4.4% made any type of error--2.7% made logical errors and 1.7% made estimationerrors. However, among self-reportedusers, these percentages were 10.3% and 6.5%, respectively.The ratios indicate that studentswho usedmarijuanawere nearly five times

more likely to make consistent estimationsof their frequenciesof usethanto makeeithertype of error;if they did make an error, they were moderately(1.6 times) more likely to makea logicalerror than an estimationerror. The secondgoal of this analysiswas to compareinconsistenciesin self-reportsof alcohol and marijuanause. Becauseof the large differencein the percentages of consistentnonusersfor alcoholand marijuana,the mostdirect

comparisons are betweenthe ratiosfor thesetwo drugs. Thesecomparisons showthat studentsweremore likely to be inconsistentin reportingtheir alcohol use than they were in reportingtheir marijuanause, evenwhenconsistent nonuserswere droppedfrom the comparison.There was little difference, however, in the ratios of logical to estimationerrors for the two types of drugs. Both were only modestlygreaterthan 1. This greater inconsistencyin self-reportsof alcohol

comparedto marijuanause shouldbe interpretedwith caution,however,becausesomeportion of the difference maybe relatedto the differences in thesemeasures. Recall that the marijuanameasurequeriedthe numberof times studentsever used the drug, while the alcohol measure askedfor the greatestnumberof drinkseverconsumed at onetime. Argumentscan be madebothwaysas to which would be easier to recall or define--total

lifetime

use or

greatestuse at one time. In any event, the apparently

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TABLE3. Percentages with eachtypeof patternof consistent andinconsistentreportingof ageat first useof alcoholandmarijuanaat TI and T2 (usingknowledge of respondent's self-reported ageat TI) Alcohol (n=5,518)

Patterns

Marijuana (n=5,554)

%

Adj. %

%

Adj. %

Consistent nonuse Consistent estimation

41.0 16.4

27.8

74.4 8.8

34.4

Logicalerror

23.2

39.3

9.9

38.7

19.4 100.0

32.9 100.0

6.9 100.0

26.9 100.0

Estimation error Total Ratios

Consistent estim.: Error

0.4

0.5

Logicalerror:Estim.error

1.2

1.4

Note:Caseswith missingvalueson eithermeasure at eitherdatacollection pointare excludedfrom thistable.

greaterdifficultyin consistently reportingfrequencies of alcoholusecomparedto marijuanausemay be, in part, a result of the differences in these measures.

The variabilityin the responsechoicesin thesemeasuresmayalsoaccountfor someof thisdifference.For the marijuanameasure,use episodesare groupedin categories (e.g., 2-5 times, 6-10 times, 11-49 times);however, for the alcoholmeasure,mostof the choicesinvolve a discrete number of drinks (e.g., 2 drinks, 3 drinks, 4 drinks). Consideringthe differences,it may have been

easierto consistently reportor to comecloseto reporting the correctnumberof use episodesin wide categoriesof numbers(the marijuanameasure)thanin discretenumbers (the alcohol measure).

Althoughit is not appropriateto comparethe magnitudesof estimationerrors for the two drugs(i.e., it is not

appropriate to compare thenumberof drinksof alcoholto the numberof occasions in whichmarijuanawas used),it is enlighteningto simply note the magnitudes of error (data not shown). For alcohol, 49.7% of studentswho madeestimationerrorsunderestimated their frequencyof useby onedrink at T2 compared to T1; 23.1% underestimatedby two drinks;and 27.1% underestimated by three or more drinks. For marijuana, 66.3% of studentswho madeestimationerrorsunderestimated their frequencyof lifetime use by one use episodeat T2 comparedto T1; 25% underestimated by two episodes;and 8.7% underestimatedby threeor moreepisodes. Consistent and inconsistentpatterns in the age measures.Percentages andratiosof students with the consistentand inconsistent patternsillustratedin Figure2 are

presented in Table3. Percentages andratiosarepresented for measuresof age at first use for both alcohol and marijuana. Looking first at the alcoholmeasure,the greatestpercentageof students(41%) was consistentnonusers.Surprisingly,greaterpercentages of studentsmade logical errors (23.2%) and estimationerrors (19.4%) than made consistentestimations(16.4%) of their agesat first alco-

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hol use. In fact, the ratio of consistentestimationto any typeof error is 0.4, meaningthat studentswho usedalcohol were 2.5 times more likely to make an error than to make consistentestimationsin reports of ages at first alcohol use. Studentswere only slightly (1.2 times) more likely to make logical errors compared to estimation errors.

The majority of students(74.4%) reportedconsistent nonuseon the marijuana age at first use measure.The secondlargest percentage(9.9%) made logical errors. Slightly fewer (8.8%) made consistentestimationsand still fewer (6.9%) made estimation errors. Still, the ratio of consistentestimations to any type of error is 0.5, meaningthat studentswho usedmarijuanaweretwo times more likely to make errorsthan consistentestimationsin their ages.Studentswere modestly(1.4 times)morelikely to make logical errors than estimationerrors. A comparisonof the ratios for the alcohol and marijuana measuresshowslittle differencesfor the two types of drugs.Studentswere more likely to make any type of error thanto makeconsistentestimationsfor both typesof drugs,but they were slightlymore likely to makean error in reportingtheir age at first alcoholuse than marijuana use. They were only very slightlymore likely to make a logicalerror comparedto an estimationerror in their age reportsfor marijuanathan for alcohol.Thesedifferences in ratios, however,are very small and do not suggestsignificantdifferencesin students'ability to consistentlyreport agesat first use for thesetwo drugs. The magnitudesof estimationerrors were also comparedfor the two types of drugs (data not shown).The possibletypesof estimationerrorsinvolvedreportinga credibleage at T1 and an age at T2 that was 1 year older or younger,2 yearsolder or youngeror 3 or more years older or youngerthan the age reportedat T1. For both typesof drugs, studentswere most likely to report older ratherthan youngeragesat T2 and to err by 1 year rather than2 or moreyearsof age. A comparison of the sizesof the percentagesfor the two drugs, however,showedan importantdifference.Generally,there was considerably more variationin the rangeof estimationerrorsmadefor the alcoholcomparedto the marijuanameasure.Among thosewho made estimationerrors, 46.6% erred by 1 year on the alcoholmeasure,31.3% by 2 yearsand22.1% by 3 or moreyears.For the marijuanameasure,60.8% of those who madeestimationerrorserred by 1 year,24.8% by 2 yearsand 14.4% by 3 or more years.Percentages, therefore, were more evenly distributedacrossthe typesof errors for the alcohol measure than for the marijuana measure.Theseresultssuggestthat the errorsfor the alcohol measuremay be more random than those for the marijuana measure. Comparisons of patternsfor the lifetimefrequencyand age measures. The third goalof thisstudywasto compare inconsistencies in the measuresfor lifetime frequencyand

BAILEY

ET AL.

age at first use.The mosttellingcomparison of the patternsfor thetwo typesof measures is theratio of consistent estimation to error (see Tables 2 and 3). For the

frequencymeasures,the ratios are considerably greater than 1 (2.9 for alcoholand 4.9 for marijuana);for the age measures,the ratios are considerableless than 1 (0.4 for

alcoholand 0.5 for marijuana).Students,therefore,had a mucheasiertime consistently estimatingtheirlifetimefre-

quencies of usethantheiragesat first usefor bothdrugs. The ratiosof logicalto estimationerrors,however,did not differ substantially for the two typesof measures. Students were slightlyto moderatelymore likely to make logical errors than estimationerrors for both types of measures.

The big differencefor the two typesof measuresis the proportionmakingbothtypesof errors.Theseproportions are two to three times larger for the age measurescomparedto the frequencymeasures. Another interestingcomparisonis the percentages re-

porting consistentnonusefor the two typesof alcohol measures. The percentages of students with thisconsistent patternwasnearly32% for the frequencymeasurebut as much as 41% for the age measure.This differencesuggeststhat a prevalenceestimateof alcoholusemay vary dramaticallydependingon the type of measureusedto

643

items. To evaluateinternal consistency,the responsesto questionsabout lifetime use and age at first use were compared.Becauseone possibleresponseto the age at first use questionswas "never tried," consistencybe-

tweent,he two itemscouldbe evaluated.Percentages of studentswith patternsof internalconsistencies and inconsistenciesare reportedin Table 4. In this table, responses to the measuresfor lifetime frequencyand age for each drug during each time periodare compared. The percentagesindicatethat studentswere more consistentin their reportsof marijuanathan alcoholfrequencies of useand agesat first use. Between97% and 98% of studentswere consistentin their reportsof marijuanause at T1 and at T2, even thoughthe percentageof nonusers decreasedbetweenthesetwo time periods.For the alcohol measures, on the other hand, 79.1% of studentswere consistent at T1 and 85.5%

were consistent at T2.

Most of

the inconsistency in the alcoholmeasuresis found in the "never tried (age)-use (frequency)"pattern. Nearly 20% of studentsat T1 and nearly 10% at T2 were foundin this pattern.

the internal inconsistencies across items used in the anal-

Further examinationof this pattern identified an actual inconsistency in the wordingof the measuresfor alcohol frequencyand age. At T1, 80.5% of the students with the "never tried (age)-use(frequency)"patternreportedconsumingone drink or less in their most frequentuse episode (data not shown). At T2, the figure was 78.1%. These results suggesta confusionin the definitions of what constitutesa drink or drinking in the two measures. Recall that the age measurequeried age at first use of "beer, wine or liquor (notjust a sip or taste)." In the frequencymeasure,on the otherhand, respondents could report use as constitutedby one drink or less. It appears, therefore,that manystudents who had consumed just a sip or taste reportednever having tried alcoholaccordingto the definitionoffered in the age measureand reportedone drink or less in the undefinedfrequencymeasure.These were probablynot inconsistencies in self-reportsby the students;instead, they were more likely consistentresponsesto two measuresthat employedslightly different

ysismightindicateanyproblems or incomparability of the

definitions

make the estimate. (Note that this differenceis not found

in the marijuanameasures.)Part of this differencein the alcoholmeasuresmay be due to a difficulty students had in remembering theiragesat first useanda consequential denialof use. Said anotherway, somestudentswho may have had difficulty rememberingtheir ages at first use may havefoundit easierto respondthat they had never usedalcoholon the age measure.Anotherlikely reason for the differencein the estimatedprevalenceof consistent nonusers is the slightlydifferentwordingusedfor the frequencyandagemeasures. Thesedifferences are discussed in the next sectionof this study. Patternsof internalconsistency and inconsistency. The fourth goal of this studywas to comparethe patternsof internal and external inconsistencies. An examination of

of use.

TABLE4. Percentages with internallyconsistent andinconsistent self-reports of ageat firstuseandlifetimeuseof alcoholandmarijuana at TI andT2 TI

Patternsof ageand frequencymeasurecombinations

Alcohol (n=5,608)

T2

Marijuana (n=5,632)

Alcohol (n=5,537)

Marijuana (n=5,587)

Consistent

Nevertried (age)/nouse(frequency) Reportedage/use

46.1 33.0

>79.1

19.5 1.4

>20.9

85.6 12.3

>97.9

37.6 47.9

>85.5

75.2 21.9

>97.1

Inconsistent

Nevertried (age)/use(frequency) Reportedage/nouse Total

100.0

1.4 0.7

>2.1

100.0

Note:Caseswith missingvalueson eithermeasure in eachpairof measures are excluded fromthistable.

9.7 4.8

100.0

> 14.5

1.6 1.3

100.0

>2.9

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Assumingthat a large proportionof what appearedto be internal

inconsistencies

in the alcohol measures was

actuallyconsistency affectedby incongruous definitionsof what constituted use between measures, it is concluded

that the problemof internal inconsistencies is not large. The problemis especiallyminor for the marijuanameasures. A tentative conclusion, therefore, is that there were

no major problemswith the data collectionproceduresor the validity of responsesto items that resultedin a large percentage of internalinconsistencies. The mostidentifiable causewas an inconsistency in the definitionsof what constitutedan alcohol use episodebetween the measures for frequencyand age at first use. When we comparethe percentages with patternsof internal and external inconsistencies,therefore, it appears generallythat externalinconsistencies were not a resultof poor internal consistency.Percentageswith patternsof external inconsistencies were greaterthan those with internal inconsistencies, and especiallylarge for external patternson the age measures.Thesedifferencessuggest that external inconsistencieswere not due to typical sourcesof internal inconsistency (suchas a lack of comprehensionor a minimal degreeof effort by the respondent to report accurately). Effectsof studyattrition Earlier discussionsof the attrition analysis results

pointedout a needto look for potentialdifferencesin consistencyof self-reporteduse betweenthose who did and did not drop out of the studybeforeT2. Percentages of studydropoutswith inconsistent reportsat T1 were 21.7% for alcohol and 4.2% for marijuana (data not shown). Thesepercentages are comparedto thosefor studentswith

/ NOVEMBER

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assessconsistency,studyresultsare not strictly comparable. Nevertheless, the attenuated reliabilities observed

amongself-reportedusers,particularlyfor marijuana,are noteworthy.They suggestthat researchfindings concerning adolescentdrug use may not be as free from measurement error as previousstudieshave implied. It should alsobe notedthat reliability assessment doesnot necessarily detect other sourcesof measurementerror, such as consistentreportingof nonuseby respondents who are in fact users.

On a more positive note, these findings indicate that the substantialmajority of adolescentself-reportedalcohol and marijuanausersdo report consistentlytheir levels of use over time. Internal consistencywas also very high, especially for marijuana use. Approximately 97% had consistentreports for the marijuana measures,and between 79.1% and 85.5% reported consistentlyin the alcohol measures. Much of the diminished

internal consis-

tency for alcohol was probably due to dissimilaritiesin the items used to assesssimilarity rather than to respondent factors. In addition to information

about the overall level of in-

consistenciesin these measures, three conclusions,based on the results reported herein, about inconsistenciesin

self-reportsof alcohol and marijuana use among adolescentscan be drawn. First, self-reportsof lifetime alcohol use appear to be more inconsistentthan self-reportsof lifetime marijuana use. Second, self-reportsof ages at first useof alcoholand marijuanaseemto be more inconsistentthan self-reportsof lifetime frequenciesof use of both substances.Third, for both types of measuresand both typesof substances,logical errors appearto be more common

than estimation

errors.

use. However, these rates reduce to 74.7% and 83.2%,

The conclusionthat self-reportsof lifetime frequencies of alcoholuse are more inconsistentthan self-reportsof marijuana use supportsthe findings of Needle et al. (1983) and Barnea et al. (1987). This finding is particularly significant because, unlike these prior studies, consistentnonuserswere excludedfrom the comparison analyses.The hypothesisthat use of more "deviant" substances(i.e., marijuanacomparedto alcohol)is more easily rememberedand, therefore,more consistentlyreported (Single et al., 1975) is supportedby the analysisof frequency of use data reported in this study. Episodesof marijuanause are presumablymore "watershed"typesof events than are episodesof alcohol use. Most students who usedalcoholand/ormarijuana,in addition,usedmarijuana less frequentlythan alcohol, so it may have been easierfor them to rememberthe numberof use episodes and the first occurrenceof use of marijuanathan alcohol. The greaterconsistencyof self-reportsof marijuanacompared to alcohol use, however,does not appear to be a resultof the fact that marijuanais usedby fewer adoles-

respectively,when based only on self-reportedusers.

cents than is alcohol because consistent nonusers were ex-

Because different

cludedfrom the comparisons.

both waves of data--20.9%

for alcohol and 2.1% for mar-

ijuanaat T1 (seeTable 4). Thus, there appearsto be very little effect of attrition on the reliability of self-reported alcohol use. For self-reportsof marijuana use, however, the percentage of internallyinconsistent responses is twice as high amongstudydropouts,even thoughthe absolute percentages are small. If the samepatternholdsfor external consistency,it is likely that the effect of attrition is to overestimateslightly the external consistencyof selfreportedmarijuanause. Discussion

When basedon the total sample,ratesof consistent responsesover time that were reportedin this studyare similar to resultsreported in previousstudies.Consistency rates here were 82.7% for lifetime maximumepisodicuse of alcohol and 95.6% for lifetime frequencyof marijuana

items have been used across studies to

BAILEY

It should be noted that some of the difference in rates

of consistency for the two typesof substances may have been a result of differences in the measures. The alcohol

measurequeriedthe greatestnumberof drinks ever consumed at one time, and the marijuana measureasked about the greatestnumberof times marijuanawas ever used.The categoriesfor the marijuanameasure,in addition, were grouped,but the categoriesfor the alcohol measurewere discrete.It may havebeeneasierto remember consistently the total numberof uses(marijuana)than the episodeof greatestuse(alcohol).It wasalsolikely to have been easier to be consistentwithin categoriesof use episodes(marijuana)thanacrossdiscretecategories(alcohol). More researchis neededto make a firm conclusion about the differencesin consistentself-reportingof frequencyof use of thesetypesof drugs.Consistentnonreporters should be excludedfrom the comparison,and measuresshouldbe as similar as possible. Another significantfinding is that the age at first use data were much more inconsistent than were the lifetime

frequencydata. The rates of inconsistencies in the age data, in addition, differed little for the two typesof drugs. These findings do not supportthe deviancehypothesis postulatedby Single et al. (1975). The relative deviance of the drug did not appearto affect students'ability to rememberconsistentlyage at first use. Rates of inconsistency were fairly high for both alcohol and marijuana, and the rates were only slightly higher for alcohol than for marijuana. However,it is true that estimationerrors for age of initiation were larger for alcohol than for marijuana. Reasonsfor these relatively high rates of inconsisten-

ciesin the agemeasures must,for the mostpart, be left to speculationat this point. Part of the reasonfor the higher rates for the age data comparedto the frequencydata is likely dueto the greaterprecisionrequirements for the age measures.The responsesfor the age at first use measures were checkedfor reliabilityagainstthe agesof the respondentsat the two data collectionpoints.No similarchecks were availablefor the frequencymeasures. Other potentialreasonsfor the high ratesof inconsistenciesin the age measuresare randomresponsepatterns, willful misrepresentation and errors in recall (Single et al., 1975). Single and colleaguesconcludedthat mosterrorsare likely due to errorsin recall;however,the results reportedheresuggestthat otherfactorsare alsoat work. In particular,it wasfoundherethat the ratiosof logicalto consistenterrors were greater than 1 for both types of measuresand for both types of drugs. Logical errors resultedin longitudinalpatternsthat were impossible(i.e., denyinguse at T2 that was reportedat TI, reportingan ageat first usethat wastoo youngor too old to be possible giventhe age at datacollection).Someof theseerrors may have resultedfrom random responsestyles (especially for the measures of age at first alcoholuse)or the

ET AL.

645

resultof willful misrepresentation by the students(i.e., reportingan age at first use that was older than the respondent was at T2). The only way that someof the logical errors could have been the result of errors in recall

is if

studentsforgotthey useda particulardrug at T2 that they rememberedusing at T1. They also may have changed their definition

of what constitutes

"use"

from T1 to T2.

More researchis neededto discoverthe particular reasonsbehind inconsistenciesin adolescentself-reports,especiallyfor the age at first usedata. At the very least, the analysesof age measuresreportedin this studyshouldbe replicatedwith other data sourcesto see if thesepatterns of inconsistencies are typical with age data. Laboratory and pretestadministrations shouldincludecognitiveanalysesthat focuson the thoughtprocesses behindresponses to drug use and age at first use measures.Respondents shouldbe askedto give their definitionsof "use" of different substances,to describe the process they went throughto recall a particularage and to recountthe mathematicalapproachthey usedto estimatetheir lifetime frequenciesof use. Resultsof thesecognitiveanalyseswould direct future efforts to redesignself-reporteditems. Other analysesshouldcompareratesof inconsistencies for adolescentsof different ages and socioeconomic groups.Possiblequestionscould be: Are the items culturally biased?Are items that are appropriatefor, say, ninth graderstoo complicatedfor sixth graders?Theseanalyses should exclude consistentnonreportersso that rates of consistencyare not inflated for groups with lower rates of use. Resultsof theseanalysesmay identify items that are not appropriatefor different age and socioeconomic groups.

Short of these neededanalyses,the resultsreported in this study suggestsome potential improvementsto selfreported items. First, definitionsof use should be provided and kept consistentacrossmeasures.The provision of these definitions may counteractstudents'presumed tendencyto changedefinitionsof "use" as they grow older, which is especiallyimportantfor the less "deviant" drugssuchas alcohol.Second,if feasible,groupedrather that discreteresponsecategoriesshouldbe used.Grouped categoriesmight be less challengingto respondentsand, thus, would elicit more reliable responses than choicesrequiring very preciseestimations.This strategymay counteract the effects of estimation errors for distorting estimatesof the intensityof use or under/overestimating agesof initiation. Third, itemsthat may jog the memory or pinpointeventsin time shouldbe includedin the questionnaires.Calendarsof eventscan be createdto pinpoint the timing of use and to put the behaviorin a contextthat might stimulatethe memory. Implicationsfor the generalfield of drug and alcohol abuseresearchcan alsobe drawnfrom the resultsreported in this study.The mostconsequentialimplicationsof these findingsare for researchthat relieson self-reportedage of

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initiation for variousdrugs.Age at first use is an important variablefor investigatingsequencing patternsof drug use, and early agesof first use have been associatedwith a likelihoodof a more seriouspatternof use at later ages. In this study,agesof first use of both alcoholand marijuana were inconsistently reportedby the majority of users. Self-reportedages of initiation may be even more inconsistentamong samples of older respondentswho have a greaterrange of yearsfor potentialerror than did the youngrespondents includedin this study. The problemof inconsistent reportingand unreliability may be even more seriouswhen older respondents,such as diagnosedalcoholics,are askedto pinpointthe first occurrenceof a relatively subjectiveevent suchas the early developmentof alcoholism.The reliability of their responsesmay be furthercompromised by any cognitiveimpairmentthey may be experiencingas a result of their alcoholism.Any study that relies on age at first occurrencedata shouldexplore, to the extentpossible,the reliability of these data and shoulddraw implicationswith caution.

The discrepancies in self-reportedages amongadolescentsincludedin this sample, however,were small (usually I year). The impact of small discrepanciesin selfreportedage at first use on researchresultsin this area is uncertain, although large discrepanciescould cause substantial distortion. Clearly, more researchon this topic is warranted, and the overall consistencyof self-reported drug and alcoholuse amongboth adolescentsand adults must be continuallymonitoredas historicalfactors(i.e., variable levelsof acceptanceof use in society)impacton respondents'willingnessto provide honest answersto thesesensitivequestions. Acknowledgments We wish to thank Dr. Michael L. Dennis for his idea on categorizing inconsistencies,the late Teresa D. Crotts for her contribution in data

analysisandDr. ChristopherL. Ringwalt,Dr. Karl E. Baumanand Richard S. Straw for their commentsand editorial adviceconcerningearlier drafts of this study. Note

i. To presentthe mostconservativeestimateof consistency in the age measures,no use reportedat Ti and initiation reportedat T2 during the TI age was assumedto be an inconsistency.In fact, a student who turned 13 shortly beforeTi, for example, and tried marijuana after Ti (but while he/she was still 13) would have reported consistently. Unfortunately,such casescould not be identified because there was no way to tell preciselywhen they tried marijuanafor the first time. If it had beenassumedthat all of thesecaseswere really consistentreporters,the percentage differenceswouldhavebeenonly 3.5% for the marijuanameasureand 6.2% for the alcohol measure. In otherwords,the percentage of consistent reporterswouldhaveincreasedby 3.5 for the marijuana measureand 6.2 for the alcohol measure. If it had been assumed that half of these cases were consis-

/ NOVEMBER

1992

tent and half were inconsistent, the differencewould havebeenonly i.8 for the marijuanameasureand 3.1 for the alcoholmeasure.The differencesare small enoughthat the conservative assumption does not seemto influencesignificantlythe resultsand interpretations. References AKERS, R.L.,

MASSEY, J., CLARKE, W. AND LAUER, R.M.

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reportsof adolescentdeviancevalid? Biochemicalmeasures,randomized responses and the boguspipeline in smokingbehavior.Social Forces 62: 234-251,

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BAILEY,S.L. ANDHUBBARD,R.L. Developmentalvariation in the context of marijuanainitiationamongadolescents. J. Hlth socialBehav. 31: 58-70, 1990.

BARNEA,Z., RAHAv,G. ANDTEICHMAN,M. The reliabilityandconsistency of self-reportson substanceuse in a longitudinalstudy.Brit. J. Addict. 82: 891-898, 1987.

CZARNECKI, D.M., RUSSELL, M., COOPER,M.L. riND SALTER,D. Five-yearreliabilityof self-reportedalcoholconsumption. J. Stud. Alcohol 51: 68-76, 1990.

GRAHAM, J.W., FLAY, B.R., JOHNSON,C.A., HANSEN, W.B., GROSS-

MAN,L. ANDSOBEL,J.L. Reliabilityof self-reportmeasures of drug usein prevention research: Evaluationof the projectSMART questionnairevia the test-retestreliabilitymatrix. J. Drug Educ. 14: 175193, 1984.

JOHNSTON, L.D., O'MALLEY, P.M. AND BACHMAN,J.G. Illicit Drug Use, Smoking, and Drinking by America's High School Students, CollegeStudents,and YoungAdults:1975-1987,DHHS Publication No. (ADM) 89-1602, Washington:GovernmentPrinting Office, 1989.

KANDEL,D. ANDFAUST,R. Sequence and stagesin patternsof adolescent drug use. Arch. gen. Psychiat.32: 923-932, 1975. MAISTO,S.A., McKAY, J.R. ANDCONNORS, G.J. Self-reportissuesin substance abuse: State of the art and future directions. Behav. As-

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MARTIN, G.L. AND NEWMAN, I.M. Assessingthe validity of selfreportedadolescentcigarettesmoking.J. Drug Educ. 18: 275-284, 1988.

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SINOLE,E., KANOEL,D. ANDJOHNSON, B.D. The reliabilityandvalidity of druguseresponses in a largescalelongitudinal survey.J. Drug lssues 5: 426-443, 1975.

BAILEY SMART, R.G. Recent studies of the validity and reliability of selfreporteddrug use, 1970-1974.Canad.J. Criminal. Corrections17: 326-333, 1975.

SMART,R.G. ANDJARVIS,G.K. Do self-reportstudiesof drug use really give dependable results?Canad.J. Criminal. 23: 83-92, 1981. SOBELL,L.C., SOBELL,M.B., RILEY, D.M.,

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D.S., CANCILLA,A., KLAJNER,F. ANDLEO G.I. The reliabilityof alcoholabusers'self-reports of drinkingandlife eventsthat occurred in the distantpast. J. Stud.Alcohol49: 225-232, 1988. SWADI, H. Validating and improvingthe validity of self-reportsin

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'WHITEHEAD,P.C. AND SMART,R.G. Validity and reliability of selfreporteddrug use. Canad.J. Criminal. Corrections14: 83-89, 1972. WILLIAMS,G.D., AITKEN, S.S. AND MALIN, H. Reliability of selfreportedalcoholconsumption in a generalpopulationsurvey.J. Stud. Alcohol 46: 223-227, 1985.

YAMAGUCHI, K. ANDKANDEL,D.B. Patternsof drug use from adolescenceto young adulthood:III. Predictorsof progression.Amer. J. pub. Hlth 74: 673-681, 1984.

Jellinek Memorial Award, 1992 The Boardof Directors of the Jellinek Memorial Fund is pleasedto announcethat Dr.JorgeMardonesofthe Universityof Chile,Santiago, Chile,hasbeenawardedthe Jellinek Memorial Award for 1992. This award was made in recognition of Dr. Mardones'distinguished recordof scholarship in biologicalresearchon alcohol sincethe early1940s.Hiscontributionshavebeenveryextensive,but of particular importanceishisoriginationof the techniqueof selectivelybreedinganimalsto be either high or low alcoholconsumers.Thistechniquehasbeen usedby numerous scientiststo identifythe neurobiologicalbasisof toleranceto and dependenceon alcoholand to illuminatethe influenceof geneticfactorsin alcoholconsumption andon susceptibilityto dependence.Our scientificadvisorypanel noted that he is "renowned and universallyrespectedfor the inspirationgiven to many scientists, includingJellinek himself."

The JellinekAward consistsof $5,000 (Canadian) togetherwith a bust of the late E.M.Jellinek.The awardwaspresentedby Dr. Harold Kalantat the banquetof the InternationalSocietyfor BiomedicalResearchon Alcoholism(ISBRA) Conference in Bristol, U.K., in June 1992. The Board of the Jellinek Memorial Fund also wishes to announce that the

SelectionCommitteefor the 1993 and 1994 awardswill be chairedby Drs. Klaus M'akelaandG. AlanMarlatt,respectively. The specificcategoryfor the 1993 award is"Socialandculturalstudies"; for 1994thecategoryis"Behavioral (experimental or clinical) studies."Nominationsfor these awards can be forwarded to the followingchairpersons. For 1993: Dr. KlausM'akela,ResearchDirector, Finnish Foundation for Alcohol Studies,Kalevankam 12, 00100 Helsinki 10, Finland. For

1994: Dr. G. Alan Marlatt, Professorand Director, Department of Psychology, AddictiveBehaviorsResearchCenter,NI-25, Universityof Washington,Seattle,WA 98195, U.S.A.

JELLINEK MEMORIAL FUND

33 Russell Street, Toronto, Ontario, Canada M5S 2S1