1. In search of data for treatment of DUI’s
Anders Andren (1)
, Jan-Håkan Hansson (2)
, Hans Bergman (1)
(1) M.A. Psychologist, Doctoral Student, Department of Clinical Neuroscience, Karolinska Institute,
Stockholm, Sweden and Institute for Evidence-Based Social Work Practice at the National Board of Health
and Welfare, (2) Vice-Chancellor at Ersta Sköndal University College, Stockholm, Sweden. (3) Professor at
Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden.
Abstract
Previous research has clearly shown that the population of DUI-offenders is heterogeneous. However,
descriptions of DUI´s have been made using many different assessment methods of varying reliability and
validity. The same is also true of efforts to classify DUI-populations. In order to build typologies suitable
for treatment matching and evaluation of treatment it seems necessary for the research community to
agree upon what assessment instruments should be used. We simply need a “gold standard” for this
purpose. It will be proposed that only standardized instruments with high reliability and validity should
be used because we need the same kind of spectacles when judging outcomes of different treatments
worldwide. Using assessment instruments like the Addiction Severity Index, AUDIT, NEO-PI-R and SCL-
90 together with register data will be sufficient to cover most aspects valid for treatment matching and
evaluation of treatment, as will be demonstrated in this article.
Keywords: DUI, Psychosocial characteristics, Classification, Matching, Evaluation.
Introduction
The concepts of “Drunken Driving”, “Drink Driver” or “Drinking Driving” are usually
denoted as “DUI” that stands for “Driving Under the Influence” (of alcohol) whereas “DWI”
stand for “Driving While Intoxicated” which is also applicable when drivers are intoxicated
by narcotic drugs. For reasons of simplicity we will mainly limit this article to DUI-problems
related to alcohol.
Previous DUI research has clearly shown that DUI offenders come from a heterogeneous
population composed of many different subgroups (1,2,3.4,5,6,7,8,9) Recognition of this fact
calls for the development of DUI classification systems. The reason for this is that DUI-
offenders have been driving under the influence for a number of different reasons, have
various psychosocial prerequisites and different needs. Accordingly they should be treated in
different ways to prevent relapse. Few DUI descriptive studies have been undertaken from a
treatment perspective based on classification studies.
Perrine (1990) proposed a classification system defining three groups of DUI-offenders:
“The Quick,” i.e. drinking drivers who have never been arrested for alcohol-involved
problems; “The Caught” are motorists who are apprehended and convicted of driving under
the influence of alcohol (DUI); “The Dead” are fatally injured drivers who have positive
blood alcohol concentrations (10).
Vingilis (2000) proposed another somewhat more elaborate classification system, also out of a
treatment perspective, by describing DUI-populations in four main categories: 1.Demo-
graphic, 2. Lifestyle behaviours, 3. Personality, motivation and emotion and 4.Cognition and
information processing. This system will be used in the present article. “Demographic”
variables include sex, age, socio-economic status, ethnicity, educational and occupational
status, social integration and similar. Lifestyle behaviours include current and previous
1

2. substance abuse and problems related to alcohol and substance abuse like involvement in
traffic accidents, criminality and other kinds of risk-taking behaviours (11).
Personality, motivation, emotion, cognition and information processing are factors that are not
as well explored in DUI-treatment research as demographic variables and lifestyle behaviours.
They are, however, important from a treatment perspective. One recent study (Greenberg et
al. 2004), for example, seems to confirm that beliefs concerning the risk, social acceptability,
and immorality of driving under the influence of alcohol have significant associations with
behavioural control (12).
Other multi-dimensional classification schemes with implications for treatment planning have
been proposed by Cavaiola and Wuth (13) and Pisano et al. (14) judging the risk for relapse in
DUI-offences using different assessment methods.
The methods used in the development of classification systems are either a priori
classifications based on single variables like the ones above, or post hoc data analysis using
cluster analyses [CA]) for many variables. Vieczorek and Miller (14) advocate the use of
multidimensional techniques like cluster analysis to find taxonomies suitable for treatment
matching and are together with Brown (15) the only researchers to date that have presented an
analysis out of this framework using CA.
Brown (2005) found that a cluster characterized by delinquency, a family history of alcohol
use and early age of onset for alcoholism, suggesting a neurogenetic basis for DUI, that
coincides with Cloninger’s Type 2 alcoholism (16). The conclusion is that this typology may
be useful for understanding the persistence of DWI behaviour in some individuals, and how
interventions may be better targeted to improve outcomes (15).
A problem with previous a priori classifications as well as post hoc data analysis is that re-
searchers mostly have used different domains as well as various instruments to describe
DUI’s. Even describing the same domains, researchers also have used a variety of assessment
instruments, making it hard to compare findings in a systematic way. This can be seen in
Table 1. Out of 13 studies only four used the same instruments (MMPI and Alcohol Use
Inventory). The same observation has been made by Popkin and colleagues (1988) and
Beirness (1991) who reviewed 20 instruments used in DWI assessement. They suggested that
future research needs to provide normative statistics and to evaluate the predictive validity of
instruments used for DWI populations (17,18)
In conclusion we need some kind of “gold standard” regarding which domains to include and
what assessment instruments to use, in order to evaluate DUI-treatment, facilitate treatment
planning and treatment matching, otherwise it will be very hard to evaluate and compare
treatments and treatment outcomes for drunken drivers worldwide.
Aims
The specific aim, in this article, using a material of 980 DUI offenders in Sweden, is to
demonstrate how a description of a DUI-population with the help of standardized instruments
will cover most aspects used in previous research. These aspects will easily be combined in a
taxonomy based on cluster analysis, useful for programme evaluation, treatment planning and
matching of clients to treatment, following the classification system proposed by Vingilis
(11).
2

3. Table 1: Summary of DUI cluster analytic work found 1978 – 2005
Authors Reference Instruments used Variables Clusters
Mulligan, Steer and Fine (1978) 19 Minnesota Multiphasic Personality Inventory (MMPI) Personality 1.Normal 2. personalities
2.Neurotic personalities
3.Psychotic symptoms
Steer et al. (1979) 20 BAC at arrest
Alcohol Impairment Index
Psychoneurotic Stability Scale
BAC at detection
Alcohol use
Alcohol impairment
Neuroticism
1.A low alcohol problem group
2. A low psychological impairment group
3.A self medicating group
4.A high alcohol problem group
5.A high psychological impairment group
Sutker, Brantley and Allain (1980) 21 Minnesota Multiphasic Personality Inventory (MMPI) Personality 1. High levels of depression, 2. acting-out behaviour and 3. high
levels of alcohol use
Donovan and Marlatt (1982) 22 Non-standardized questionnaire Demographic data
Drinking behaviour
Driving attitudes
Personality
1.Low levels of depression and an elevated level of tension-
reduction driving
2. High levels of driving-related aggression, competitive speed,
sensation seeking, and hostility.
Wells-Paker et al. (1986) 23 Traffic and criminal records
Mortimer-Filkins Questionnaire
Traffic and criminal data
Demographic data
Alcohol use
1. Low offence group
2. Mixed group with more DUI offences
3. The traffic group with the highest number of moving
violations
4. Public Drunkenness Group with chronic DUI offenders and
habitual violators of other laws as well
5.The License Group with the highest number of license and
equipment violations
Wieczorek et al. (1992) 14 Diagnostic Interview Schedule
SCL-90-R
Locus of Control
Alcohol related questions
Bad Driving Index
Alcohol dependence severity, Psychiatric
severity
Social stability
1. Moderate Severity Drivers, 2.High Risk Drivers, 3. High
Problem Severity Drivers without social instability, 4. Low
Problem Drivers and 5. High Problem Severity Drivers with
high social instability
Chalmers et al. (1993) 24 The Problem Drinker Trait List (PDTL) Gender
Personality
1. (Men): Emotionality/Depressiveness, Impulsivity, and Low
Self-Confidence
2. (Women): Depressiveness, Overcontrol, and Alienation
Nolan et al. (1994) 25 Court Reporting Network Interview (CRN)
Hogan Personality Inventory (HPI)
Demographic variables
Personality
1. Impulsive-Extravert, 2. Normal,
3. Neurotic-Introvert, 4. Neurotic-Hostile and 5. Unassertive-
Conformist
Rychtarik et al. 1998, 1999 26 Socio-demographic data
Alcohol Use Inventory
Social background, cognitive functioning,
psychosocial functioning, history of alcohol
use, and pre-treatment drinking behaviour;
1. Low severity, gregarious drinkers; 2. Low severity, steady
drinkers; 3. Overall moderate–low severity drinkers; 4.
Moderate severity, solitary, mental enhancement drinkers; 5.
Moderate severity, gregarious drinkers; 6. Steady, solitary,
moderate impairment drinkers; 7. Higher severity, mental
enhancement drinkers; 8. High severity, compulsive, mood
management drinkers.
Siegal et al. (2000) 27 Diagnostic Interview Schedule (DIS - IV)
questionnaire constructed by the authors
Psychiatric characteristics
Socio-demographic characteristics
1. Contemporary Alcohol Dependent” containing clients
without antisocial personality disorder
2. Alcohol dependent (but not drug dependent) clients with a
history of psychiatric illness without antisocial personality
disorder
3.Anti-social Poly-substance Dependent
Siegrist & Bächli-Biétry (2000) 28 Non-standardized questionnaire Knowledge about traffic regulations
Attitudes towards DUI
1. Socially established people with “problematic” opinions
rejecting more traffic regulations.
2. Juvenile group with problematic opinions and attitudes.
3.Unproblematic group with favourable attitudes towards traffic
regulations and police work.
Chang, Lapham and Wanberg, (2001) 29 Socio-demographic data
Alcohol Use Inventory (AUI)
Alcohol preoccupation
Anxiety
Effects of drinking
1. The Low-Profile , 2. Alcohol-Preoccupation , 3. Enhanced ,
4. Enhanced-Disrupt, 5. Anxious-Disrupt , 6. High-Profile.
Brown (2005) 15 Addiction Severity Index (ASI)
Composite International Diagnostic Interview (CIDI)
The Michigan Alcoholism Screening Test (MAST)
Drug Abuse Screening Test (DAST).
The Timeline Follow-Back (TLFB)
Register data
The Barratt Impulsivity Scale
The Millon Clinical Multiaxial Inventory III
SCL-90
Salivary cortisol
Socio-demographic data
Diagnosis of substance use and determination
of age of onset.
Current alcohol- and drug use
(MAST & DAST).
Instances of drinking or substance use on a
daily basis over the past 90 days.
The number of past DWI convictions and
history of adherence to mandatory programs
for license re-acquisition
Three dimensions of impulsive behaviour.
Axis I and Axis II disorders
Psychiatric comorbidity
Salivary cortisol1)
1. Type A/ I
2. Transition
3. Type B / II
3

4. Population sample characteristics
In 1994 changes in the legislation about drunken driving were made in Sweden and legal
consequences were sharpened. The limit for coarsely drunken driving was lowered from a
blood alcohol concentration (BAC) of 1.5 to1.0 and the maximum penalty was increased up to
two years imprisonment and it was recommended that this should be combined with
treatment. The limit over which there was a risk of imprisonment was set at 1.0 BAC. As a
result of the new legislation two new special prisons for DUI’s (Rostorp and Östragård) were
created in Sweden. These prisons offered three treatment programmes.
During the years 1997 to 1998 6,105 persons of both sexes were sentenced to prison in
Sweden because of one or several DUI offences. Of these, 6,049 (99 percent) were male and
56 (1 percent) female. Nine hundred and eighty (16.2 percent) males were sent to the two new
DUI-specialist prisons. Here they were expected to participate in any of three rehabilitation
programs - an educational programme called “The Wheel Trap” (30), the Minnesota 12-step
model (31,32) and Dynamic Cognitive Behaviour Modification (33). The average length of stay
was six weeks. Decisions about what prison should be used were made by local authorities all
over Sweden and no systematic selection of clients to the special prisons for DUI’s was
implemented1
. However, no females were sent to these facilities.
The intention was to investigate all clients sent to the DUI-specialist prisons during 1996 –
1998, with respect to their psychosocial situation, personality and psychiatric status at intake.
Nine hundred and twelve (93 percent) of the 980 convicted DUI’s agreed to participate in the
survey.
Assessment methods
The psychosocial background and present situation were investigated using the Addiction Se-
verity Index (ASI). Alcohol problem level was ascertained with the Alcohol Use Disorder
Identification Test (AUDIT) assessing the gravity of use with regard to the general
population. Psychiatric comorbidity was assessed through the Symptom Check List (SCL-90).
Personality profiles were collected using the NEO Personality Inventory and additional
information about previous criminality, including DUI offences, was obtained from the
National Police Register (NPR).
Addiction Severity Index (ASI).
The Addiction Severity Index (ASI) is a semi-structured interview covering seven areas of life
(medical status, employment and support, drug use, alcohol use, legal status, family/social
status, and psychiatric status). The ASI can be used: to assess the problem severity and
necessary level of help of the interviewee; for periodic repeated administrations to monitor
and quantify change in problems associated with substance abuse: to evaluate substance abuse
programs or to monitor changes over time in life areas related to substance abuse for
aggregated groups or subpopulations (34,35).
In the ASI there are four comprehensive measures that can be used: 1.Severity indexes,
2.Number of problem days during the past month, 3.Client judgements about need of help
and, 4. Interviewer ratings of clients’ need of help. The severity indexes are based on some
objective questions while client and interview ratings are fully subjective. McLellan and his
-----------------------------------------------------------------------------------------------------------------
1) Private communication: Frans Schlyter, Swedish Prison and Probation Service, Norrköping, 2004,
4

5. colleagues (2005) in cooperation with European Monitoring Centre for Drugs and Drug
Addiction (EMCDDA) have proposed a framework for standardized descriptions of ASI-data
that will be used here1
. ASI has not been used as a data-gathering instrument in DUI-research
before but the Swedish
The Swedish Prison and Probation Service (SPPS) has been using the ASI on a regular basis
since 2001. The aim is that every inmate with alcohol or drug problems should be interviewed
using the ASI at intake.
NEO PI-R
NEO PI-R is a personality inventory based on research about personality since 1932. It measures
“the big five” personality domains: 1.Neuroticism, 2.Extraversion-Introversion, 3.Openness to
experience, 4.Agreeableness and 5.Conscientiousness. It does not separate different kinds of
psychiatric disorders, but does well in classifying people in general. It can differentiate between
normal and personality disordered individuals (36). The Swedish version used in this study is
valid and reliable. Data from the Swedish general population are available (37).
Symptom Check List (SCL-90)
The Symptom Check List-90 (SCL-90) is a self-rating scale with 90 items that documents
psychiatric symptoms (38). The SCL-90 has ten subscales: somatization, obsessions,
interpersonal sensitivity, depression, anxiety, aggressiveness, phobic anxiety, paranoid
thoughts, psychotism and an additional scale covering symptoms not belonging to other
dimensions. There is also a global scale, General Severity Index (GSI), summarizing all
subscales. The version used in this study is valid and reliable. Data from the Swedish general
population are available (39).
Alcohol Use Disorder Identification Test (AUDIT)
AUDIT was constructed in 1982 in order to identify persons with a risky or harmful alcohol
consumption, symptoms of dependency and alcohol-related problems due to high alcohol
consumption (40). The Swedish version used in this study is reliable, valid and there are data
available from the general Swedish population (41,42).
National Police Records (NPR)
The Swedish police compile records regarding detection of drunken drivers. Among other
things, blood alcohol concentrations (BAC) are documented.
Data analysis
For data analysis purposes we have used frequencies, cross tabulation, t-tests, ANOVA and
Cluster Analysis (CA) in the computer program “Statistical Package for the Social Science” –
SPSS (43) applying the K-means technique which is recommended (44). CA is a way to
investigate if there are subgroups in a sample. CA has frequently been used for classification
of alcoholics but not as much in classifications of DUI’s.
-----------------------------------------------------------------------------------------------------------------
1) In press 2005.
5

6. Description of subjects
Demographic data
Compared to the general population of Swedish men, DUI-clients in this sample were
younger, more often single, not employed, retired or receiving disability pension to a higher
extent than the average population of Swedish men. DUI’s also had less years of education
(Table 2).
Lifestyle behaviours and characteristics.
ASI composite scores indicated enhanced problem levels regarding physical health and
alcohol use (Table 3). In total, 656 clients (72 percent) met one to five criteria of ill health and
only 28 percent (n = 256) could be considered to be in good health. About 67 percent had
started to drink alcohol on a regular basis at a mean age of 26 years and 13 percent started to
drink alcohol on a regular basis at ages under 18 years. Regarding previous drug use, 27.7
percent (n = 253) had used illegal drugs. Almost 42 percent (i.e. 106, 11.6 percent of total
sample) had used drugs intravenously. About 13 percent (n = 32) that had used illegal drugs
had received institutional care for detoxification between 1 - 15 times (M = 3.03, SD=3.57)
and 63 (24.9 percent) of these had received treatment for their drug problems between 1 – 16
times (M = 2.84, SD = 3.66).
Almost 14 percent (n = 123) of all clients had been treated in hospital due to psychiatric or
psychological problems 1 to 50 times (M = 3.04, SD= 5.43) and 177 (19.4 percent) had
received outpatient treatment or non-institutional care 1 – 70 times (M = 6.1, SD: 10.8) for
psychiatric problems. In total, 250 clients (27.4 percent) had received either institutional care
or outpatient treatment due to psychiatric or emotional problems between 1 and 70 times (M =
5.8, SD= 10,6). Accordingly 237 (26 percent) had earlier in life been prescribed psychotropic
drugs for their problems and 32 (3.5 percent) had disability pensions due to psychiatric
problems.
Using the ASI it was established that the clients had five drinking days in the month prior to
intake during which they consumed more than five standard drinks on each drinking occasion.
Since we currently do not have ASI-data from the general population we have to use other
data sources to compare the drinking behaviour of DUI’s with the level of alcohol
consumption in the general population. In this respect we can use data from AUDIT.
Applying international guidelines in evaluating AUDIT, 8 - 15 points is a sign of medium
level of alcohol problems and 16+ points of high level of alcohol problems. For a sub-sample
of 545 (59.8 percent) clients we have data from AUDIT at intake. About 35 percent (n = 192)
of the DUI’s in our sample had no alcohol problems, 33 percent (n = 182) had medium
alcohol problems and 31 percent had a high level of alcohol problems. The corresponding
figures for males in the general population is “no alcohol problems” 81.6 percent, “medium
alcohol problems” 14.4 percent and “high level of alcohol problems” 4 percent (42).
Data about BAC-level at detection for actual DUI-crime were collected for 694 clients
showing a mean BAC-level of M = 1.76 (SD= .60).
Regarding criminality, 94 percent (n = 922) had been convicted between 1 – 6 times (MD =
1.00)2
of DUI-offences and other types of criminality in the five-year period before intake
6

7. according to the police department client-register (NPR). Every conviction concerned one or
more crimes. The majority of clients (N = 838, 91.9 percent) had committed 2 – 40 DUI
offences before intake (MD: 3.0)1
, Only 74 (8.1 percent) clients had not committed any DUI-
offence before intake according to the NPR.
For 499 (54.8 percent) there is a wide variety of other types of criminal offences including
theft, vandalism, financial crimes, violence (including murder), drug crimes, weapon
violations, molestations and threats. The conclusion is that at least half the sample of
Table 2: Demographic data 19972
----------------------------------------------------------------------------------------------------------------
1) Since the distribution is skewed we use the median instead of mean here. 2) Figures about the average population of men aged between 16
– 64 years (1998 – 1999) are compiled from the official home page of Statistics Sweden at http://www.scb.se/ also obtainable in English. 3)
No ASI-data from the Swedish population are yet available, 4) Swedish and American school systems are not easily compared which is why
we also tried to define school grades by years in school.
Demographics General
population
Total
sample
(N = 912)
Age and gender (18 – 64 years)
Age Mean for men (SD)
Gender (%) = Men: 18-65
Women: 18-65
59
41.5
58.2
417 (12.39)
100
0
Ethnicity (men: 18 – 64)
% Swedish Descent
% Other Nordic Descent
% Other European Descent
% Non-European countries
% Unknown
99.5
.02
.23
.02
.02
74
14
1
-
11
Marital Status and family problems (men: 18 -
64)
% Never Married
% Married or living as married
% Separated/Divorced
% Widowed
Mean index of family problems in ASI (SD)3
Mean days of family problems in ASI (SD) 3
16.4
42.8
45.6
1.8
-
-
43.0
19.0
35.0
2.0
.24 (.20)
.87 (5.9)
Usual Occupation - Past Year
(men: 18-64)
% Working
% Homemaker
% Student
% Military service
% Retired
% Unemployed
39.5
1.1
1.3
.2
3.32
7.3
60.2
0.0
2.4
-
12.3
20.9
Years of Education (men: 18-64 years)4
% Less than 6 yrs
% <= 9 years
% >=6 but <12 yrs
% Graduate (12 - 13 yrs)
% 2 Yrs. College/Tech. (14-15 yrs)
% College or Post Graduate (16 yrs +)
% Unknown
-
16.4
18.4
11.4
14.4
6.4
33.0
0.5
76.0
18.0
3.0
1.4
0.7
-
7

8. Table 3: Lifestyle behaviours and characteristics1
Total
sample
(N = 912)
Personal health in ASI
Mean medical composite (SD)
Mean days of medical problems (SD)
Disease affecting life quality (%)
Mean psychiatric composite (SD)
Mean days of psychiatric problems (SD)
Reporting depression (%)
Reporting anxiety (%)
0.25 (.33)
8.4 (12.2)
42
0.09 (.16)
0.07 (.15)
11.0
14.0
Alcohol and drug use in ASI
Mean alcohol composite (SD)
Mean Days of Alcohol Drinking (+ 5 drinks) last month (SD)
Mean drug composite (SD)
Mean days of opiate use (SD)
Mean days of cocaine use (SD)
Mean days of amphetamine use (SD)
Mean days of cannabis use (SD)
0.24 (.24)
5.1 (8.7)
0.05 (.13)
0.92 (4.8)
0.04 (.99)
0.41 (2.7)
.82 (4.1)
Legal problems in ASI
Mean legal composite (SD)
Mean days with criminal activity last month (SD)
0.08 (.16)
0.95 (6.1)
drunken drivers in this study are also habitual criminals where DUI crimes are only one part
of a much broader spectrum of criminality.
Personality and psychiatric symptoms
About 798 (87.5 percent) clients that were interviewed using the ASI also responded to the
NEO-PI-R. Here values are transformed to a T-scale (M = 50, SD = 10) based on a norm
group of Swedish men in the general population (40). In our sample DUI’s are significantly
more neurotic (t = 3.50, Df= 1224, p <.0005), and less conscientious (t = 5.10, Df= 1224,
p<.0001) than the average Swedish man. Persons with high values on the personality
dimension of “neuroticism” are emotionally “unstable” and might be vulnerable for mental
problems.
Persons with low degree of conscientiousness can be described as easygoing, not very well-
organized, careless, not planning ahead.
Seven hundred and two clients (76.9 percent) responded to the Symptom Check List (SCL90).
Raw data were transmitted to a T-scale based on 933 men and women in the general Swedish
population. (26). DUI’s in this sample have statistically higher values regarding somatization,
depression, anxiety, phobic anxiety and psychotism. The General Symptom Index (GSI) that
is a
----------------------------------------------------------------------------------------------------------------
1. No ASI-data from average Swedish population is yet available
8

9. summary index of other subscales (M = 55.3, SD= 14.7) differs significantly (t = 8.55, Df=
1631, p < .0001) from values obtained in the general population (M = 50.03, SD = 9.97).
Summary of empirical findings
In summary, we obtain a picture from our sample of socio-economically deprived, neurotic
and less conscientious, criminal DUI’s with psychiatric problems above the average of the
general population.
Results from the Cluster Analysis
In a first step we used the CA for 848 (93 percent) clients with complete data sets in the ASI
together with data from NPR that is used by the SPPS for documentation and matching
purposes. The best solution appeared to be a three-group solution when indexes for work-
related and drug problems were removed. In this sample all groups had about the same level
of work-related problems and drug abuse differentiated only between clients with a low
degree of multiple problems and clients having a high degree of multiple problems.
Significant differences between groups, for all scores used, as measured by one-way ANOVA
were necessary for a satisfactory solution. The cluster groups found could be classified with
regard to ASI-problem areas, for clients having low values in all domains (normals), clients
having especially high degree of legal problems (criminals) and clients having a combination
of problems with alcohol and mental health (dual diagnosis group).
Table 4: Cluster groups found in ASI
Cluster 1: Normals 648,000
Cluster 2: Criminals 83,000
Cluster 3: Dual Diagnosis 117,000
Valid 848,000
Missing 176,000
Figure 1 shows the profiles for composite scores in the ASI transformed to t-values (M = 50,
SD= 10) showing a within-group profile for the DUI’s under investigation, with respect to all
composite measures completed with data from NPR showing criminality during the past five
years. There are significant differences between groups as measured by one-way ANOVA
(p<.0.05) in most aspects, except for the ASI index of Work and Income. Criminal DUI’s and
Dual Diagnosis DUI’s have very similar profiles but differ with respect to legal problems,
family problems, mental health as measured by the ASI and criminality as documented by the
NPR.
Other measurements (AUDIT, SCL-90 and NEO-PI-R) that are transformed to a t-scale (M =
50, SD = 10) based on men in the average population give a profile that differs between the
clusters (Figure 2). Normal DUI’s are close to the general population of Swedish men in all
respects but physical health; the latter being worse. They also have a tendency to be more
extravert in their personality than the average Swedish man. Criminal and Double Diagnosis
DUI’s do not differ regarding alcohol problems as measured by the ASI but they have
significant different levels of alcohol problems as measured by AUDIT. Both groups also
have a high degree of psychiatric comorbidity, are more labile in their personality and have a
low degree of conscientiousness, indicating a personality prone to mental problems, having
an easygoing lifestyle with less ability for planning compared to the average Swedish man.
9

10. Criminal and dual diagnosis DUI’s differ in two respects. Criminal DUI’s have committed
more crimes and are less agreeable in their personality than Double Diagnosis DUI’s,
indicating a more anti-social personality among criminal DUI’s.
Figure 1: Effect of cluster analysis on ASI and NPR-data
30 40 50 60 70 80 90 100 110ASI
Index of Physi-
cal health
Index of Work
And income
Index of
Alcohol use
Index of Drug
use
Index of Legal
Problems
Index of Family
Problems
Index of Mental
health
NPR
DUI Crimes
Trffic Viola-
tions
Other Crimes
***
***
***
***
***
***
***
***
***
*** p < .005
Figure 2: Effect of cluster analysis on data from AUDIT, SCL-90 and NEO-PI-R
30 40 50 60 70 80 90 100 110
AUDIT
SCL90:
GSR
NEO-PI-R
Lability
Extraversion
Openess
Agreableness
Consciousness
***
***
***
***
***
***
*** p < .005
Summary of findings
A cluster analysis (CA) showed that the material can be divided in three main groups:
Extravert and normal personalities without apparent psychiatric problems, small to moderate
legal problems and without pronounced psychosocial problems (Normal DUI’s). The second
group is somewhat more neurotic, have more psychiatric problems and more psychosocial and
pronounced legal problems (Criminal DUI’s). A third group is characterized by less friendly,
conscious and more neurotic clients, having a high degree of alcohol and psychiatric problems
(Double Diagnosed DUI’s).
10
Normal DUI’s (n = 648)
Criminal DUI’s (n = 83)
Dual Diagnosis DUI’s (n = 117)
Normal DUI’s :
AUDIT: n = 482
SCL-90: n = 461
NEO-PI-R: n = 611
Criminal DUI’s
AUDIT: n = 59
SCL-90: n = 48
NEO-PI-R: n =71
Dual Diagnosis DUI’s
AUDIT: n = 634
SCL-90: n = 83
NEO-PI-R: n = 105

11. Discussion
Previous research has clearly shown that DUI offenders are a heterogeneous population
composed of many different subgroups. In the vast body of previous classifications regarding
DUI populations, the focus has often been directed towards BAC levels at detection and signs
of alcohol and/or drug problems whilst disregarding other important factors.
Of course, without the use of alcohol there could be no drunken driving. However, drunken
driving is often treated as a primary symptom while in some cases it can be seen as a
secondary sign of a mixture of other phenomena such as being young – not yet capable of
recognizing the blood alcohol concentration (BAC). It might also be so that young DUI’S are
part of a culture or subculture where risky behaviour like drinking and driving are considered
to be ”tough” or ”brave”. Attitudes and cultural factors might also be of importance in
descriptions of DUI populations. Personality might also be a factor of importance as well as
psychiatric co-morbidity, which also may affect other areas of lifestyle behaviours like
criminality other than DUI offences. However, a good portion of drunken drivers are
alcoholics and DUI offences can be an indicator of alcohol problems.
Recognition of this heterogeneity in DUI populations calls for the need of developing a multi-
factorial classification system for DUI’s taking all important factors into account. The reason
for this is that DUI-offenders drive under the influence for a number of different reasons, and
have different abilities and needs. It seems apparent that effective treatment should be
personalized according to the needs of the clients.
In order to build such typologies suitable for treatment matching and evaluation of treatment
it seems necessary for the research community to agree upon what dimensions and what
instruments, or at least what classes of instruments, should be used.
In this study we used the Addiction Severity Index (ASI), AUDIT, NEO-PI-R, Symptom
Check List and register data about criminality. All instruments are well known worldwide and
are considered to be reliable and valid. They work well together covering most aspects of
Vingilis’ classification scheme (1). Using CA in this study, we also found that the
psychosocial situation coincides with personality factors, psychiatric comorbidity, severity of
alcohol use and previous DUI criminality as well as other types of criminality, giving us three
distinct groups of DUI’s with different levels of psychosocial, legal and alcohol problems.
These groups also differ in terms of their capability to handle their problems or benefit from
treatment. This might be affected, among other things, by personality and psychiatric
comorbidity.
The typology found in this article will be used in three future studies. It will be tested as to
whether this typology will work as a matching tool and if it is useful in the prediction of
relapse in DUI and other criminality or if other typologies or variables will do the job better.
We hypothesize that the clusters found will interact with type of treatment and that clients in
cluster group two and three will relapse in DUI and other criminality to a higher extent than
clients in cluster group one. It will also be hypothesized that Criminal DUI’s will relapse in
crime other than DUI offences to a higher extent than Double Diagnosis DUI’s that will
relapse in DUI criminality and traffic violations to a higher extent than the other two groups.
It will also be hypothesized that DUI’s receiving treatment will relapse less than clients in a
matched control group not receiving treatment.
11

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