Reactivity to alcohol assessment measures: an experimental test.

Abstract

Previous research has suggested that alcohol screening and assessment may affect drinking.
This study was a randomized test of reactivity to alcohol assessment questionnaires among a group of heavy drinking college students.
A total of 147 university students completed a screening questionnaire and were randomized to either immediate assessment or delayed assessment. The immediate assessment group completed a set of drinking questionnaires at baseline, 3, 6 and 12 months, while the delayed assessment group completed questionnaires only at 12 months.
Primary outcomes included overall volume of drinking, risky drinking and use of risk reduction behaviors.
We found a significant effect of assessment on measures of risky drinking and risk reduction behaviors, but not on overall volume of drinking. Specifically, at 12 months, participants who had previously completed drinking assessments had a lower peak blood alcohol concentration (BAC) (d = -0.373), were more likely to report a low score on the Alcohol Use Disorders Identification Test (AUDIT; odds ratio = 2.55) and tended to use more strategies to moderate their alcohol consumption (d = 0.352). Risk reduction behaviors that were affected tended to be those that limited alcohol consumption, rather than those that minimized consequences.
These results may have implications for the development of brief interventions.

Full text

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Reactivity to alcohol assessment measures: an
experimental testadd_2632 1305..1310
Scott T. Walters1, Amanda M. Vader1, T. Robert Harris1& Ernest N. Jouriles2
University ofTexas School of Public Health, Dallas,TX, USA1and Southern Methodist University, Dallas,TX, USA2
ABSTRACT
Aims
study was a randomized test of reactivity to alcohol assessment questionnaires among a group of heavy drinking
collegestudents.Settingandparticipants
Atotalof 147universitystudentscompletedascreeningquestionnaireand
were randomized to either immediate assessment or delayed assessment. The immediate assessment group completed
a set of drinking questionnaires at baseline, 3, 6 and 12 months, while the delayed assessment group completed
questionnaires only at 12 months. Measurements
Primary outcomes included overall volume of drinking, risky
drinking and use of risk reduction behaviors. Findings
We found a significant effect of assessment on measures of
risky drinking and risk reduction behaviors, but not on overall volume of drinking. Specifically, at 12 months, partici-
pants who had previously completed drinking assessments had a lower peak blood alcohol concentration (BAC)
(d = -0.373), were more likely to report a low score on the Alcohol Use Disorders Identification Test (AUDIT; odds
ratio = 2.55) and tended to use more strategies to moderate their alcohol consumption (d = 0.352). Risk reduction
behaviors that were affected tended to be those that limited alcohol consumption, rather than those that minimized
consequences. Conclusions
These results may have implications for the development of brief interventions.
Previous research has suggested that alcohol screening and assessment may affect drinking. Design
This
Keywords
Alcohol, assessment, brief interventions, college students.
Correspondence to: Scott T. Walters, University of Texas School of Public Health, 5323 Harry Hines Boulevard, 8.112, Dallas, TX 75390-9128, USA.
E-mail: scott.walters@utsouthwestern.edu
Submitted 24 November 2008; initial review completed 10 February 2009; final version accepted 25 March 2009
INTRODUCTION
In the field of alcohol treatment research, there has long
been interest in whether the assessment of drinking
reduces drinking behavior. A number of intervention
researchers have speculated that the assessment of
drinking contributes to the positive effects of drinking
interventions [1–5]. For instance, Sobell & Sobell [6]
hypothesized that their follow-up interviews might be
operating as a de facto treatment, and thus might be con-
tributing to reductions in drinking behavior. Similarly, in
light of the failures to find differences between conditions
in Project MATCH [1], there was speculation that the
substantial assessment procedures, among other fea-
tures, might have reduced drinking across experimental
conditions.Inotherstudies,assessmentreactivityiscom-
monly invoked to explain intervention findings when
there is a downward trend in both the intervention and
control groups [7]. Unfortunately, only a handful of
investigators have used an experimental design to test
directly the hypothesis that assessment of drinking
reduces drinking behavior.
Onewaytotestforeffectsof assessmentondrinkingis
through the use of a delayed (or minimal) assessment
control. In this design, participants are screened into a
research study, with one group completing only minimal
assessments during the research period and another
group completing more extensive assessments. In a
recentstudy,collegestudentswhoreceivedascoreof 8or
more on the Alcohol Use Disorders Identification Test
(AUDIT) were randomized to complete or not complete a
10-minute drinking assessment [8]. Assessment ques-
tions included a 14-day drinking calendar, alcohol prob-
lems and perceived drinking norms. At 12 months,
students who completed the assessment battery showed
lower overall drinking and heavy episodic drinking. Simi-
larly, McCambridge & Day [9] randomized a group of
college students to either complete or not complete the
RESEARCH REPORT
doi:10.1111/j.1360-0443.2009.02632.x
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AUDIT as part of a demographic and health survey. At a
2-month follow-up, those who had completed the AUDIT
reported lower levels of hazardous drinking (but not
overall drinking). Additionally, in a study of college stu-
dents, Carey et al. [10] found that an extensive time-line
follow-back(TLFB)interviewwasmoreeffectiveinreduc-
ing drinking at 1 month than a briefer assessment.
However, the TLFB condition did not reduce drinking-
related problems more than the shorter assessment.
These studies provide experimental evidence that drink-
ing assessment can reduce self-reported drinking behav-
ior, with effect sizes on risky drinking that are similar to
those reported in studies of brief interventions [11].
However, there are exceptions to these findings, with
some investigators failing to find an effect of assessment
on drinking [2,12].
Understanding the effects of assessment on drinking
behavior is potentially of great significance. First, identi-
fying the contribution of the assessment to outcome
allows us to estimate more effectively the incremental
effect of the treatment being tested in intervention trials.
If assessmentdoesindeedaffectdrinking,researchresults
might be overestimating the effect of the treatment rou-
tinely, when it is delivered without a substantial assess-
ment battery. It might also help to explain the large
number of treatment trials in which participants in all
groups show improvement. Secondly, if assessment itself
has a meaningful effect on drinking, such knowledge
might be helpful in developing efficacious and cost-
effective brief interventions for drinking. Indeed, there
has been a frequent call for brief treatments that can be
implemented with minimal time and effort [7].
The present study was designed to build upon previ-
ous assessment literature. Specifically, this was among
the first studies to employ an experimental design to
examine assessment effects on three types of drinking
outcomes: overall volume of alcohol consumption (i.e.
drinks per week), risky drinking (i.e. peak blood alcohol
level and AUDIT score) and risk reduction behaviors (e.g.
alternating alcoholic and non-alcoholic drinks). This
study differs from past studies that have examined assess-
ment effects on drinking [2,9,12], in that our assessment
condition involved repeated assessments over time. This
was also the first study to our knowledge to examine the
affect of assessment on risk reduction behaviors.
METHODS
Participants
In Autumn 2006 and Spring 2007, we recruited partici-
pants from a medium-sized private university in the
southern United States. Participants were recruited as
part of a larger clinical trial comparing motivational
interviewing and feedback interventions [13].The evalu-
ation of assessment effects was a secondary aim that was
built into the larger clinical trial. Several methods were
used to reach potential participants, including brief
announcements in undergraduate psychology and
health courses, invitation e-mails to students enrolled in
undergraduate psychology courses and flyers posted on
campus. To be eligible, participants had to be at least 18
years of age and report at least one heavy-drinking
‘binge’ episode (i.e. five or more drinks for men, four or
more drinks for women, in a single episode) in the past 2
weeks. For completing assessments, participants could
receive either psychology course extra credit or payment
($20 at baseline, 3 months and 6 months; $40 at 12
months). For the parent study, 363 eligible students con-
sented to participate; the present analyses used 147 par-
ticipantsallocatedtooneof theassessmentgroups.Other
study conditions have been described elsewhere [13].
To determine eligibility, students answered two
screening questions about age and frequency of heavy
drinkinginthepast2weeks.Thescreeningandallassess-
ments were completed online via a secure website. Eli-
gibleparticipantswererandomizedusingacomputerized
algorithm (stratified by sex and heavy drinking fre-
quency) to immediate assessment (IA; n = 72) or delayed
assessment (DA; n = 75). At baseline, both groups com-
pleted a short set of demographic questions and the IA
group completed an additional set of questions focused
upon alcohol consumption, alcohol-related problems,
protective behaviors, readiness to change and beliefs
about campus drinking norms.The demographic compo-
nent took approximately 5 minutes and the alcohol-
related component took approximately 25 minutes. The
IA group also completed the full set of questions (demo-
graphic and alcohol-related, taking approximately 30
minutestocomplete)at3,6and12months,whiletheDA
group did not complete any additional assessments until
12 months. The informed consent and other documents
explained the project as a research study looking at
college student drinking; participants were told that they
might or might not receive an intervention as part of the
project. Neither of the groups in the present analyses
received any formal intervention as part of their partici-
pation in this study. Eighty-seven per cent of participants
completed the 12-month follow-up (IA, n = 63; DA,
n = 66),withnosignificantdifferencesbetweengroupsin
terms of follow-up rate. There were no adverse events
reported in either group.
Participants were 66.0% female, 85.7% white and
had a mean age of 19.8 years. Freshmen represented
41.5% of the sample, sophomores 24.5%, juniors 21.8%
and seniors 12.2%. The majority of students reported
living in dormitories/residence halls on campus (47.6%)
and off-campus housing (43.5%). On the baseline
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screener, participants reported an average of 3.1 heavy
drinking episodes in the previous 2 weeks.There were no
significant differences between the groups in the number
of heavydrinkingepisodesoranyof themeasureddemo-
graphic variables (all Ps > 0.05).
Measures
Volume of alcohol consumption was estimated using a
7-daydrinkingcalendarmodifiedfromtheDailyDrinking
Questionnaire[14].Participantsestimatedthenumberof
drinks they consumed on each day in a typical week in
the past month. The number of drinks per week was cal-
culated by summing the drinks reported on all 7 days.
Riskydrinkingwasmeasuredintwoways.Toestimate
peak blood alcohol concentration (BAC), participants
wereaskedtothinkof thetimewhentheydrankthemost
in the past month and then report the number of drinks
they had and the number of hours over which they were
drinking. The number of drinks and number of hours
wereusedalongwiththeparticipant’sweightandgender
to estimate a peak BAC in the past month. As a second
measure of risky drinking we used the AUDIT question-
naire [15], which has shown good reliability and validity
among college drinkers [16–18]. Consistent with past
research [9], we examined the AUDIT both as a continu-
ousscore(rangingfrom0to40)aswellasadichotomized
score (0–7 versus 8 or more). Previous research has typi-
cally used a cut-off of 8 as a measure of risky drinking
[19].
To measure risk reduction behaviors, we used the
15-item Protective Behavioral Strategies Survey (PBSS;
[20]. We chose this measure because we believed that
many of the items would be related closely to risky drink-
ing behaviors. Participants were asked to what extent
they had used various protective behaviors while drink-
ing in the past 3 months. Responses were given on a
five-point Likert scale of ‘never’ to ‘always’. Examples of
these behaviors include alternating alcoholic and non-
alcoholic drinks, avoiding drinking games and using a
designated driver. Martens et al. [20] divided the PBSS
scaleintothreesubscalesbasedonfactoranalysis(limited
drinking, changing manner of drinking, using harm
reduction strategies), while Walters et al. [21] found that
for heavy drinking college students, the limited drinking
subscale could be subdivided further (mixing beverages
more weakly, planning ahead).
Data analysis
We used all available cases for analysis (i.e. those who
completed the 12-month follow-up). Assessment effects
were analyzed by regressing each outcome (logistic
regression in the case of the dichotomized AUDIT score)
onthetwogroupsof interest,adjustingforthenumberof
binge episodes reported on the baseline screener. Adding
gender and age (the other screening variables) as covari-
ates did not change the pattern of results, and were thus
not used in analyses. We used Cohen’s d as a measure of
effect size [22].
RESULTS
Table 1 shows the means and standard deviations for the
binge variable at screening and drinks per week, peak
BAC, AUDIT and PBSS at the 12-month follow-up.
Table 2 shows the effect of assessment on drinking and
related outcomes. In terms of overall consumption, there
were no significant differences between groups on drinks
per week (t = -0.673, P = 0.502). For risky drinking,
thereweresignificantdifferencesbetweengroupsonpeak
BAC(t = -2.108,P = 0.037,effectsize = -0.373)andthe
dichotomizedAUDITscore(Waldc2= 5.457,P = 0.019).
At12months,theIAgroupreportedameanpeakBACof
96 mg/dl, whereas the DA group reported a mean peak
BAC of 120 mg/dl, a between-group difference of
28 mg/dl after adjusting for the number of heavy epi-
sodesreportedonthescreener.Fifty-sixpercentof theIA
group scored less than 8 on the AUDIT, whereas 39% of
the DA group scored less than 8 on the AUDIT, which
Table 1 Screening and 12-month follow-up data by group.
Immediate assessment
(n = 63), mean (SD)
Delayed assessment
(n = 66), mean (SD)
Screening question
Heavy drinking (binge) episodes
12-month follow-up
Drinks per week
Peak BAC
AUDIT
Dichotomized AUDIT score (% < 8)
Protective behaviors score
3.24 (1.85)2.94 (1.63)
9.52 (9.98)
96 mg/dl (75)
7.98 (4.63)
56%
50.10 (10.97)
9.98 (7.97)
120 mg/dl (84)
9.26 (5.34)
39%
46.92 (9.74)
AUDIT: Alcohol Use Disorders Identification Test; BAC: blood alcohol concentration; SD: standard deviation.
Reactivity to alcohol assessment
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means that the IA group was 2.55 times more likely to
report a low AUDIT score when adjusting for the number
of heavy episodes reported on the screener. The effect on
the continuous AUDIT score fell just short of the conven-
tional 0.05 significance level (t = -1.916, P = 0.058). In
terms of risk reduction behaviors, there was a significant
difference between the groups on the PBSS (t = 1.992,
P = 0.049, effect size = 0.352), with assessment increas-
ing the PBSS score by approximately 3.6 units when
adjusting for the number of heavy episodes reported on
the screener. Assessment had a significant effect on one
PBSS subscore (limiting amount of drinking by mixing
beverages more weakly) and a nearly significant effect on
another subscore (changing manner of drinking). In post
hoc analyses, we found that participants who had com-
pleted the assessment were more likely to alternate
betweenalcoholicandnon-alcoholicbeverages,putextra
ice into drinks and avoid drinking games.
DISCUSSION
This study was a randomized test of effects of the assess-
ment of drinking behavior on heavy drinking college
students. We found a significant assessment effect on
measures of risky drinking and risk reduction behaviors,
but not on overall volume of drinking. Specifically, par-
ticipants who completed drinking assessments at base-
line, 3 and 6 months reported reduced peak BAC and
AUDIT scores, and tended to use more strategies to mod-
eratetheiralcoholconsumptionat12months,compared
with participants in the delayed single assessment group.
Specifically, assessment reduced peak BAC by 28 mg/dl,
and more than doubled the odds of having a low AUDIT
score.
As noted previously, examination of assessment
effects was a secondary aim of the parent study, which
was designed to detect ‘medium’ effect sizes (d = 0.5) of
Table 2 Effect of assessment on drinking and related outcomes, adjusted for baseline binge drinking.
MeasureBtPd
95% CI
Lower Upper
Overall drinking
Drinks per week
Risky drinking
Peak BAC
AUDIT (continuous)
AUDIT (dichotomized, lower category)
Risk reduction
Protective behavior score
Subscale 1: limiting drinkingc
Part 1a. mixing beverages more weakly
Item 3: alternate alcoholic and non-alcoholic drinks
Item 11: drink water while drinking alcohol
Item 12: put extra ice in your drink
Part 1b. Planning ahead
Item 2: determine not to exceed a set number of drinks
Item 4: have a friend let you know when you have had
enough to drink
Item 6: leave the bar/party at a predetermined time
Item 10: stop drinking at a predetermined time
Subscale 2. Changing manner of drinking
Item 5: avoid drinking games
Item 9: drink shots of liquor
Item 13: avoid mixing different types of alcohol
Item 14: drink slowly, rather than gulp or chug
Item15: avoid trying to ‘keep up’ or ‘out-drink’ others
Subscale 3. Using harm reduction strategies
Item 1: use a designated driver
Item 7: make sure that you go home with a friend
Item 8: know where your drink has been at all times
-1.007
-0.673 0.502
-0.119
-3.9671.953
-0.028
-1.585
-2.108
-1.916
5.457a
0.037
0.058
0.019
-0.373
-0.339
2.553b
-0.055
-3.223
1.163
-0.002
0.052
5.604
3.568
1.708
1.400
0.535
0.308
0.557
0.307
0.308
0.120
1.992
1.631
2.802
2.491
1.473
2.683
0.460
1.597
0.502
0.049
0.105
0.006
0.014
0.143
0.008
0.646
0.113
0.617
0.352
0.288
0.495
0.440
0.260
0.474
0.081
0.282
0.089
0.023
-0.365
0.411
0.110
-0.106
0.146
-1.014
-0.074
-0.354
7.114
3.780
2.389
0.960
0.723
0.968
1.629
0.691
0.595
-0.065
-0.057
1.365
0.923
0.034
-0.010
0.354
0.064
0.496
0.096
0.195
0.204
-0.319
-0.281
1.940
4.002
0.197
-0.047
2.023
0.339
1.199
0.546
0.957
1.183
0.750
0.779
0.055
0.000
0.844
0.963
0.045
0.735
0.233
0.586
0.341
0.239
-0.056
-0.050
0.343
0.708
0.035
-0.008
0.358
0.060
0.212
0.097
0.169
0.209
-0.465
-0.457
-0.027
0.467
-0.311
-0.437
0.008
-0.311
-0.322
-0.253
-0.208
-0.138
0.335
0.343
2.757
1.379
0.380
0.417
0.699
0.440
1.314
0.445
0.599
0.546
aWald c2;bodds ratio;csubscale 1: limiting drinking, divided into subscores 1a and 1b as suggested by Walters et al. [21]. AUDIT: Alcohol Use Disorders
Identification Test; BAC: blood alcohol concentration; CI: confidence interval.
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interventions. In this arm of the trial, we found signifi-
cant effects with effect sizes greater than 0.35. In com-
parison, in their meta-analysis, Moyer et al. [11] reported
an average effect size of 0.263 for brief intervention
studies at 6–12 months post-intervention. In our study,
IA had an estimated effect greater than this on four addi-
tional outcomes beyond those we reported as significant:
continuous AUDIT, two protective behavior subscores,
and one protective behavior item. Thus, there may be
additional assessment effects beyond those reported here.
Our pattern of results on drinking is consistent with
previous research on assessment reactivity, which tends
to find more of an effect on risky drinking than on overall
quantity [8,9]. Also consistent with previous work is our
patternof findingsontheAUDITquestionnaire.Asinour
study, McCambridge & Day [9] reported more significant
effects when the AUDIT was dichotomized. This may be
due in part to the scoring of the AUDIT; three of its items
pertain to volume and frequency of heavy drinking, such
that frequent bingeing virtually guarantees a score of 6
or more, even in the absence of adverse consequences.
Thus, it is possible that lower AUDIT scores are more
reflective of overall drinking patterns, while higher
AUDIT scores are more indicative of dependence or
adverse consequences.
To our knowledge, we are the first to test the effect of
assessment on measures of risk reduction behaviors.
Importantly, the kind of items that showed the most
improvement in our study tended to be behaviors that
limitedalcoholconsumption,suchasmixingdrinksmore
weakly, alternating beverages and avoiding drinking
games. Other behaviors that were more related to mini-
mizingtheconsequencesof drinking,suchasleavingwith
friends and knowing where your drink had been at all
times, tended not to be affected. Indeed, in previous
researchsomeriskreductionitems(e.g.knowwhereyour
drinkhasbeenatalltimes)seemtobeunrelatedtooverall
drinking or peak BAC, whereas other items (e.g. use a
designated driver) may actually increase the amount of
drinking[21].However,anotherexplanationmaybethat
we encountered a ceiling effect in some risk reduction
questions. For instance, ‘using a designated driver’ and
‘knowingwhereyourdrinkhadbeenatalltimes’tendedto
be highly endorsed, even at baseline (used frequently by
73.6% and 86.1% of IA participants, respectively). In
contrast, items such as alternating alcoholic and non-
alcoholic drinks and using extra ice were endorsed much
lessoftenatbaseline(usedfrequentlyby20.8%and22.2%
of participants,respectively).Thus,itispossiblethatthere
was little room for improvement on some items that were
already used quite often. At the same time, this may
suggestthatviewingthelessendorsedbehaviorsservedas
prompts or reminders for those who were completing the
questionnaires and had not yet adopted these behaviors.
Our study was strengthened by the use of a random-
ized prospective design, a long-term follow-up and an
excellentretentionrate.Ourstudywaslimitedintermsof
the selectivity of the sample and the self-report nature of
our questionnaires. Our sample was relatively young,
mainly female and white. In addition, because drinking
was self-reported, it is impossible to tell whether the effect
of the assessment is a reporting bias or a true effect on
drinking. Future research might help to determine the
natureof theeffectbycomparingself-reportstocollateral
interviews or biochemical measures. Finally, our IA
group included repeated assessments of drinking, conse-
quencesandriskreductionbehaviorsatbaseline,3and6
months.This schedule makes our study somewhat differ-
ent from past studies that used a single assessment point.
It also makes it impossible to determine whether we
would have found similar effects as a result of a single
assessment point or whether the effects will persist for
longer than 6 months from the final follow-up point.
Future studies might consider varying the content,
lengthandnumberof assessmentpointstodeterminethe
contribution of each element.
Moos [23] has thoughtfully summarized some of the
mechanisms by which assessment might affect drinking.
Onepossiblemechanism,basedonself-regulationtheory,
involves a process by which people monitor and compare
their own behavior to some personally held standard or
norm;accordingtothistheory,focusedattentiononone’s
drinking may cause an individual to alter his or her
behavior to be more in line with a personally held stan-
dard or norm [24]. This perspective is consistent with
social learning theory, which suggests that behavior is
influenced by actual consequences of behavior, as well as
observations and self-reflection about potential conse-
quences [25].Through reminding people about potential
consequences and possible strategies to reduce risk,
assessment may help them to not only adopt new behav-
iors, but also to remember behaviors that they observe in
others. In addition, self-determination theory [26] sug-
geststhatpeoplearemorelikelytomakechangesthatare
perceived as having been chosen freely (autonomy),
when they believe that they are competent to make
changes (competence), and when those changes are sup-
ported by others (relatedness). Assessment batteries
which facilitate self-reflection, while at the same time
avoiding direct appeals to change, would seem to further
the perception of autonomy. Many young adults are
already optimistic about changes [27], and providing a
menu of strategies for reducing heavy drinking may
further their perception of competence.
In conclusion, we found that an assessment battery
served as a de facto intervention, reducing levels of heavy
drinking and increasing risk reduction behaviors. We
foundbetween-groupeffectsthatweresimilartoprevious
Reactivity to alcohol assessment
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studiesof assessment(aswellasbrief interventions).Sub-
sequent intervention studies might consider including
delayed or minimal assessment groups in order to deter-
mine how generalizable the observed effects will be to
settings in which there is not a substantial assessment
component. Our results might also have implications for
thedevelopmentof brief cost-effectiveinterventions.That
is, it might be possible to create effective interventions for
drinking behavior that involve only the assessment or
monitoring of drinking behavior. Assessment interven-
tions may be especially well suited for younger drinkers,
whotendtobemoreconcernedaboutnormativecompari-
sons and less practiced in strategies for safe drinking.
Clinical trial registration
This
Protocol Registration System (ClinicalTrials.gov ID:
NCT00374153).
studyis registeredwith ClinicalTrials.gov
Declarations of interest
None.
Acknowledgements
This project was supported by R01 AA016005-01
funded by the National Institute of Alcohol Abuse and
Alcoholism.
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