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The relationship between alcoholism and crime: autonomic and neurpsychological factors

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The relationship between alcoholism and crime: autonomic and neurpsychological factors

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Content The Relationship Between Alcoholism and Crime:
Autonomic and Neuropsychological Factors
by
Susan Elizabeth Bihrle
A Thesis Presented to the
FACULTY OF THE GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
in Partial Fulfillment o f the
Requirements for the Degree
MASTER OF ARTS
(Psychology)
August 1995
UNIV ERSITY O F S O U T H E R N C A LIFO R N IA
T H E G R AD U A TE SC H O O L
U N IV ER SITY PARK
L O S A N G E L E S. C A L IF O R N IA 8 0 0 0 7
This thesis, written by
. .. . .?u ? an. .El i ? e t h . Mhr l e .....................................
under the direction of h.$T.....Thesis Committee,
and approved by all its members, has been pre
sented to and accepted by the Dean of The
Graduate School, in partial fulfilhnent of the
requirements for the degree of
MASTER OF ARTS
Dean
THESIS COMMITTEE
A "
Chairman
Abstract
No prospective studies have thus far addressed the relationship between biological
factors and alcoholism and crime. This study examined whether abnormalities in
arousal, orienting, and impulsivity would differentiate alcoholics who commit crime
from those who do not. A frontal lobe dysfunction theory was proposed to account
for these predicted differences. One hundred and ninety sons of alcoholics and
controls were assessed with an extensive battery of variables at age 18 to 21 in
Denmark. This included measures of autonomic arousal and orienting, impulsivity
ratings, and neuropsychological measures of frontal functioning. One hundred sixty-
three o f these subjects were reassessed at age 30 to 33 to obtain evaluations for
alcoholism and criminal behavior. In general, the alcoholic group and the criminal
alcoholic group were not significantly different on the three measures. Possible
reasons for nonsignificant results and directions for future research are discussed.
iii
Table of Contents
Abstract ii
List of Tables iv
Introduction 1
Alcoholics: Arousal, Orienting, Impulsivity 3
Criminals: Arousal, Orienting, Impulsivity 5
Criminal Alcoholics: Arousal, Orienting, Impulsivity 6
Frontal Lobe Dysfunction: Arousal, Orienting, Impulsivity 7
Method 9
Subjects 9
Assessment of Alcohol Abuse/Dependence 11
Assessment of Criminal Behavior 12
Arousal Measures 13
Orienting Measures 14
Impulsivity Measures 15
Measures o f Frontal Lobe Functioning 15
Results • 18
Risk Group Comparisons 18
Risk and Crime Group Comparisons 19
Alcoholism Group Comparisons 20
Alcoholism and Crime Group Comparisons 20
Discussion 23
Risk Group Comparisons 23
Risk and Crime Group Comparisons 24
Alcoholism Group Comparisons 25
Alcoholism and Crime Group Comparisons 27
Strengths and Limitations o f the Study 28
Directions for Future Research 31
References 40
List of Tables
Table 1: Subject Breakdown by Group Membership and Risk Status
Table 2: Risk Group Comparisons - Means, Standard Deviations,
and Significant Effects
Table 3: Risk and Crime Group Comparisons - Means, Standard
Deviations, and Significant Effects
Table 4: Alcoholism Group Comparisons - Means, Standard Deviations,
and Significant Effects
Table 5: Alcoholism and Crime Group Comparisons - Means, Standard
Deviations, and Significant Effects
1
The Relationship Between Alcoholism and Crime:
Autonomic and Neuropsychological Factors
A relationship between alcohol use and criminal activity is widely known.
Alcohol is present in a significant proportion o f crimes, and alcohol problems have
been found disproportionately among criminal offenders (Collins, 1981; Farrington,
1990). Nevertheless, understanding o f the mechanisms underlying this relationship has
been limited. It is possible that both alcoholism and criminal behavior are somehow
derived from a common predisposing factor. However, limitations in the research
literature have prevented a more complete understanding of the association between
alcoholism and crime.
One important problem is the limited number of prospective, longitudinal
studies of alcoholism. Most o f the research on alcoholism has examined
characteristics of alcoholics as compared to nonalcoholics. However, abnormalities
found in alcoholics in these studies could be interpreted as either antecedents or
consequences of the disorder. Prospective longitudinal studies, on the other hand,
examine subjects prior to the development of alcoholism, thereby allowing causal
relationships to be explored. A number of prospective studies of alcoholism have been
conducted, primarily focussing on personality and behavioral characteristics. These
studies have consistently found that adult alcoholics were impulsive and rebellious
prior to the onset of alcoholism (Jones, 1968; Loper, Kammeier, and Hoffmann,
1973). However few, if any, o f the prospective studies of alcoholism have examined
biological factors, nor have they distinguished between alcoholics who do and do not
commit crime.
Extensive evidence implicates genetic and biological factors in the etiology of
both alcoholism (Goodwin, 1985); and crime (Moffitt and Mednick, 1988).
Consequently, research on potential biological markers o f alcoholism and crime has
been an area of increasing interest. Studies of autonomic arousal and orienting have
found some support for increased arousal (Laberg, 1986) in alcoholics, as well as
greater skin conductance response amplitudes in sons o f alcoholics (Finn, Zeitouni,
and Pihl, 1990). However, no prospective research on autonomic factors and
alcoholism has been conducted. Prospective longitudinal studies of crime, however,
have found lower autonomic arousal (Raine, Venables, and Williams, 1990a) and
reduced frequency of skin conductance orienting (Raine, Venables, and Williams,
1990b) in adolescent boys who later became criminals.
The present study is part of a prospective, high risk project on alcoholism.
High risk was defined as young men who have alcoholic fathers, because they are three
to four times more likely to develop alcoholism than sons o f nonalcoholics (Cotton,
1979; Goodwin et al., 1974). Data were collected from 18 to 21 year old sons of
alcoholics and some findings from this premorbid assessment are reported elsewhere
(Drejer, Theilgaard, Teasdale, Schulsinger, and Goodwin, 1985; Knop, Teasdale,
Schulsinger, and Goodwin, 1985; Schulsinger, Knop, Goodwin, Teasdale, and
Mikkelsen, 1985). Subjects were followed up at age 30 to 33 to determine whether
they had developed alcoholism and also whether they had engaged in criminal activity.
This study attempted to address some of the limitations of previous research
described above by examining variables in several domains: autonomic, behavioral,
and neuropsychological. More specifically, premorbid measures o f arousal, orienting,
and impulsivity were assessed to determine whether they might be precursors that
differentiate criminal alcoholics from noncriminal alcoholics. A frontal lobe
dysfunction was thought to be the key factor underlying these disturbances in criminal
alcoholics. Therefore, neuropsychological measures of frontal functioning were also
used to help determine whether frontal lobe dysfunction could account for these
premorbid differences. A review of some relevant research findings is presented
below:
Alcoholics: Arousal. Orienting, and Impulsivity
Research on autonomic factors and alcoholism has produced inconsistent
results. For example, men with a family history o f alcoholism have been shown to
have abnormally high levels of arousal, marked by a higher resting heart rate (Hill,
Steinhauer, and Zubin, 1992). This study compared male siblings over the age of 30
who were members of either alcoholic or nonalcoholic families, as defined by first- and
second-degree relatives. The results showed that members o f alcoholic families had
higher baseline heart rates, regardless o f whether they were alcoholics or not. In
addition, Laberg (1986) found that severely dependent alcoholic subjects showed
higher general arousal than moderately- and non-dependent subjects, as measured by
skin conductance level. Such findings provide support for stress response dampening
theory (Sher, 1987), which proposes that some individuals develop alcohol problems
because they are highly aroused and drink to dampen stress and anxiety. Other
studies, however, have not shown differences between sons of alcoholics and controls
with respect to resting heart rate or skin conductance levels (Finn and Pihl, 1987;
Levenson, Oyama, and Meek, 1987; Finn et al., 1990).
With respect to orienting, Finn et al. (1990) found that males at high risk for
alcoholism, defined as having an alcoholic father and paternal grandfather, gave
significantly larger skin conductance orienting responses and shorter response latencies
to orienting stimuli than low risk males. This study is significant, because it suggests
that increased orienting is not an effect of alcoholism, but possibly a
psychophysiological risk factor for later alcoholism. However, no prospective studies
of alcoholism have been conducted to test this pattern.
These somewhat discrepant findings may be due to the fact that previous
studies failed to distinguish between alcoholics who do and do not commit crime.
Since there appears to be a strong link between alcohol and crime, this study examined
a subgroup of alcoholics who commit crime in an attempt to better understand this
relationship.
Research on impulsivity has shown more consistent results than research on
autonomic measures. Numerous studies have suggested that poor impulse control
distinguishes alcoholics from controls prior to the onset o f alcoholism (Cloninger,
Sigvardsson, Reich, and Bohman, 1988; Jones, 1968). More specifically, related
constructs such as hyperactivity and inattention, along with impulsivity, have been
found to characterize sons o f alcoholics (Pihl, Peterson, and Finn, 1990) and predict
fixture alcohol problems (Windle, 1990; 1993). According to Sher (1991), impulsive
individuals may have difficulty inhibiting responses likely to lead to immediate reward
but later punishment. Therefore, if drinking becomes problematic, highly impulsive
individuals may be less likely to control their drinking behavior. However, not all
studies have reported a clear relationship between impulsivity and risk for alcoholism
(Sher, Walitzer, Wood, and Brent, 1990). By focussing on a subgroup of criminal
alcoholics, this study attempted to clarify these findings by more specifically
characterizing impulsivity as a predictor of criminal behavior among alcoholics.
Criminals: Arousal. Orienting, and Impulsivity
Research has found evidence that criminals also exhibit disturbances in these
three measures. Specifically, prospective research has demonstrated that reduced
heart rate and skin conductance arousal measured at age 15 in normal boys predicts
criminal activity at age 24 (Raine et al., 1990a). The significant skin conductance
arousal differences in this study were only found for nonspecific skin conductance
responses, not skin conductance levels. Other studies have also found evidence for
lower arousal in criminals (Hinton, O'Neill, and Dishman, 1979). Theoretically,
chronic under-arousal may drive the individual to seek out stimulation through the
commission of antisocial acts to increase arousal levels to normal.
With respect to orienting, reduced frequency of skin conductance orienting
responses at age 15 has also been found to predict criminal behavior at age 24 (Raine
et al., 1990b). Such findings support the idea that a deficit in the allocation of
attentional resources to external stimuli is a predisposition to crime (Raine and
Venables, 1984).
A number of personality theorists view impulsivity as a stable dimension of
personality that appears to be highly correlated with criminal activity (Barratt and
Patton, 1983; Eysenck and McGurk, 1980; Zuckerman, 1989). Moreover, researchers
have consistently found evidence for increased impulsivity as a predictor o f later
criminal behavior (Magnusson, 1987; Robins, 1978). More specifically, the related
constructs o f hyperactivity-impulsivity-attention deficit have been found to predict
criminal offending (Farrington, 1990). According to Moffitt (1993), impulse control
problems increase the risk of long-term criminal behavior by interfering with an
individual's ability to control his behavior and consider the consequences o f antisocial
acts.
Criminal Alcoholics: Arousal. Orienting, and Impulsivity
As noted above, disturbances in arousal, orienting, and impulsivity have been
found to characterize criminals but with alcoholics, the data have been less clear-cut.
Conceivably, the heterogeneity in alcoholism research is due to a lack of distinction
between alcoholics who commit crime and those who do not. Therefore, a specific
subgroup o f alcoholics who also commit crime may be more consistently characterized
by these disturbances. Theoretically, the criminal alcoholic could be described as a
sensation seeker who drinks to facilitate arousing, antisocial experiences through the
disinhibitory effect o f alcohol on behavior (Quay, 1965), whereas a noncriminal
alcoholic may be over-aroused and drink to reduce stress and anxiety (Sher, 1987).
To the author's knowledge, there is no prospective research on autonomic
arousal and orienting with respect to individuals at risk for alcoholism who commit
crime. Limited research on impulsivity has found that impulsivity is more strongly
correlated with criminal behavior than with a family history o f alcoholism (Hesselbrock
and Hesselbrock, 1992). Consequently, by integrating all three of these factors, this
study attempted to elucidate factors that predict which alcoholics are more likely to
commit crime.
Frontal Lobe Dysfunction: Arousal, Orienting, and Impulsivity
Frontal lobe dysfunction may be the fundamental concept that helps explain
why these three disturbances might be more strongly associated with a sub-group of
alcoholics who are criminal. Separate studies have found evidence for a relationship
between the frontal lobes and arousal, orienting, and impulsivity.
With respect to arousal, a magnetic resonance imaging study of normal humans
reported higher arousal in subjects with larger prefrontal areas, as measured by right
hand skin conductance levels (Raine, Reynolds, and Sheard, 1991). Using functional
brain imaging, Mathew (1989) found that experimental manipulations to increase
arousal led to an increase in regional cerebral blood flow in the frontal lobes. Both
studies suggest a relationship between arousal and frontal functioning using different
techniques.
Autonomic orienting has long been related to the frontal lobes (Luria, 1966),
with evidence that they facilitate orienting activity in both animals (Grueninger,
Kimble, and Grueninger, 1965; Kimble, Bagshaw, and Pribram, 1965) and humans
(Luria and Homskaya, 1970). A study by Raine et al. (1991) also found a significant
positive relationship between prefrontal area and skin conductance orienting in normal
humans.
The frontal lobes have also been associated with impulsivity. Clinical studies
have shown that lesions in the orbital region o f the frontal lobes may result in
increased impulsiveness (Beaumont 1983; Blumer and Benson, 1975). In addition,
Sternberg (1992) found that impulsivity was related to lower frontal EEG arousal,
suggesting a link between frontal dysfunction and impulsive behavior.
Empirical findings also provide some evidence for a relationship between
frontal lobe dysfunction and both alcoholism and crime. While not all research is
supportive, numerous studies have found impairments among alcoholics on
neuropsychological tests thought to measure frontal functioning, such as the
Wisconsin Card Sorting Test, the Necker Cube, and the Trail Making Test
(Gorenstein, 1987; Grant, 1987). Neuropsychological studies have also implicated
frontal lobe dysfunction in criminals (Gorenstein, 1982; Yeudall and Fromm-Auch,
1979).
Taken together, the above findings demonstrate some support for frontal lobe
dysfunction as a possible explanation for criminal behavior among alcoholics. This
study tested the proposition that frontal dysfunction represents the principal
mechanism underlying arousal, orienting, and impulsivity deficits in criminal alcoholics.
More specifically, the following hypotheses were tested, stemming from this frontal
dysfunction theory:
9
1. Arousal, orienting, and impulsivity abnormalities will characterize sons o f alcoholics
relative to sons of nonalcoholics.
2. These three abnormalities will more specifically characterize sons of alcoholics who
commit crime relative to those who do not commit crime.
3. This pattern o f disturbances in sons of alcoholics who commit crime can be
accounted for by frontal lobe dysfunction (as measured by neuropsychological testing).
In addition, the above hypotheses pertaining to sons of alcoholics and controls
at age 18 to 21 were tested using the outcome data that divide subjects into alcoholic
and nonalcoholic groups. Therefore, a total of six hypotheses were tested in this
study.
Method
Subjects
The subjects in this study were selected from a Danish birth cohort including
9125 consecutive deliveries at Rigshospitalet in Copenhagen between October 1959
and December 1961. Hospital records identified the fathers in 8440 cases. In order to
select a high risk group, these fathers were screened for alcoholism in 1978-1979
through the National Psychiatric Register, as well as the Municipal Alcohol Treatment
Clinic in Copenhagen. A total o f 488 fathers were identified as alcoholics in one or
both of these registers. Only sons of alcoholic fathers were examined because of the
reduced risk for developing alcoholism in women. Among the children born to these
alcoholic fathers, there were 223 sons who were potential subjects. The high risk
subjects were matched in pairs according to age, birth order, mother's age and marital
10
status at delivery, and paternal social class. A single low risk control was matched to
each high risk group pair according to these criteria. A total of 107 control subjects
were selected from the remaining pool o f males whose fathers had not been diagnosed
with alcoholism. O f the 223 high risk and 107 low risk subjects who were selected for
the study, 134 and 70, respectively, completed the initial assessment procedure.
Although some attrition occurred after the sample was selected, statistical comparison
of high risk and control groups on the five matching variables did not indicate any
significant differences between them (Schulsinger et al., 1986).
One hundred twenty-nine high risk and 67 low risk subjects completed the
psychophysiological protocol in 1979-1980 when they were age 18 to 21. However,
data from six of these subjects could not be used due to equipment problems, and an
additional subject was removed because his twin was also in the study. The present
study, therefore, includes data from 190 subjects, 127 high risk and 63 low risk, who
were assessed in 1979-1980. None of the 190 subjects were alcohol abusers or
alcohol dependent.
Subjects were psychiatrically reassessed in 1991-1993 at age 30 to 33. At this
time, 30 subjects were lost due to attrition (twelve refused, seven died, seven did not
respond, two emigrated, one was not contacted, one unknown). However, three of
these missing subjects were found to have alcoholism diagnoses through the Central
Psychiatric Register so their data were included in the follow-up. As a result, the
outcome analyses include data from 163 subjects, 108 high risk and 55 low risk.
11
Gender and Minority Status o f Subjects
Only male subjects were examined in 1979-1980, and therefore females cannot
be included in this study which seeks to extend findings on the sons o f alcoholic
fathers. Subjects in the study were recruited in Copenhagen, Denmark, and constitute
a relatively homogeneous group in terms o f ethnicity. Consequently, it is not possible
to assess differential predictions regarding ethnicity.
Assessment o f alcohol abuse/dependence at age 30 to 30
During 1991-1993, a psychiatrist administered the Psychiatric Diagnostic
Interview - Revised (PDI-R, Othmer, Penick, Powell, Read, and Othmer, 1989) to all
available subjects. The PDI-R is a structured diagnostic instrument used to assess 17
basic syndromes, including alcoholism. A major supplemental interview to the PDI-R
(Psychosocial, Medical, Psychiatric, and Family Histoiy Interview) was also
administered to obtain more detailed information on alcohol and drug use,
psychosocial variables, medical history, and family history of psychiatric disorders.
Using these instruments, subjects were assessed for alcohol abuse and dependence
according to DSM-IIIR criteria (APA, 1987). In addition, diagnoses could also be
made through the Danish National Central Psychiatric Register for those subjects who
were not available for the follow-up assessment.
Based on these diagnoses, an alcoholic group was created that included 57
subjects, 39 high risk and 18 low risk. Twenty subjects had a primary DSM-IIIR
diagnosis of alcohol dependence, 24 subjects had a primary DSM-IIIR diagnosis of
alcohol abuse, three received a PDR diagnosis of alcoholism, and three subjects who
12
did not participate in the 30 year follow-up were diagnosed with alcoholism according
to the Central Psychiatric Register. In addition, seven subjects received a secondary
diagnosis of alcohol abuse (three had primary diagnoses o f cannabis dependence, two
had primary diagnoses of major depression, single episode, one had a primary
diagnosis o f panic disorder, and one had a primary diagnosis o f post-traumatic stress
disorder). More detailed information about subject diagnosis at the follow-up
assessment is presented in Table 1.
Assessment of criminal behavior at age 30 to 33
Criminal status was assessed by collecting records from the Danish National
Register for Criminal Offenses. Number and type o f offense were recorded for each
subject, as well as the subject's age at the first offense. All subjects who had been
arrested at least once for committing an "index" offense were classified as criminal.
Index offenses are synonymous with more serious criminal acts, and do not include
minor offenses, such as traffic violations. These offenses include murder, attempted
murder, assault, rape, armed robbery, illegal possession o f a weapon, threats of
violence, theft, breaking and entering, shoplifting, fraud, forgery, blackmail,
embezzlement, sexual offenses, and drug offenses.
Using these criteria, 81 subjects were classified as criminal, 57 high risk and 24
low risk. It is important to note, however, that 51 of the criminals committed an
offense prior to, or around the same time as, completing the measures of arousal,
orienting, and impulsivity at age 18 to 21. Consequently, these measures can only be
considered potential correlates o f criminal behavior, rather than predictors.
13
Due to attrition at the 30 year follow-up, eleven o f these criminals were excluded from
the outcome analyses because information was not available to determine whether they
belonged in the alcoholic or nonalcoholic group. Therefore, the outcome analyses of
alcoholism and crime include 70 criminals, 48 high risk and 22 low risk (see Table 1).
Arousal measures at age 18 to 21
Skin conductance. Subjects were seated in a darkened room and instructed to
relax, and try not to fall asleep. Bilateral skin conductance was recorded using
Beckman silver/silver chloride electrodes placed on the distal phalanges o f the first and
second fingers o f both left and right hands. The recording electrolyte consisted o f
0.5% KC1 in 2% agar-agar (Venables and Christie, 1973). Skin conductance was
recorded with a Beckman Type R dynograph using a chart speed o f 3 mm/sec, and
amplified using a constant voltage system (Venables and Christie, 1980). Only right
hand skin conductance data were analyzed for this study due to missing left hand data
for some subjects.
Skin conductance levels (SCLs) were scored at the start of the two minute rest
period. Non-specific skin conductance responses (NS-SCRs) were recorded in the
two-minute rest period prior to the onset o f the first orienting stimulus. Non-specific
SCRs were defined as any increase in SC activity greater than .01 microsiemens
occurring during this rest period. The total number of NS-SCRs was divided by 2 to
obtain NS-SCRs per minute.
14
Heart rate. The electrocardiogram was recorded using a standard Lead I
configuration from Beckman silver/silver chloride electrodes and using forehead as
ground. Electrolyte consisted o f Cambridge electrode jelly.
Resting heart rate level (HRL) was calculated from (a) the first 30 sec o f the
two minute resting period and (b) the last 30 sec of the resting period. Number of
heart beats were counted during each 30 sec period and multiplied by 2 to yield HRL
in beats per minute (BPM).
Orienting measures at age 18 to 21
Skin conductance. Stimuli were delivered binaurally to subjects through a pair
of headphones. The stimulus tape presented included a sequence o f 15 orienting
tones. These were stimuli of 75 dB intensity, 25 ms rise time, and 1 sec duration. The
first three tones had a frequency of 1000 Hz, the next nine tones had a frequency of
1311 Hz, and the last three tones had a frequency of 500 Hz. Interstimulus intervals
were randomized (mean = 42 sec, range = 35-50 sec) and white noise at 55 dB was
used to mask out extraneous sounds.
A skin conductance response (SCR) was defined as any increase in response
greater than .01 microsiemens occurring within a latency window o f 1-3 sec post
stimulus. Skin conductance frequency consisted o f the number of responses to the 15
stimuli. Skin conductance amplitude was defined as the point of maximal response
relative to the pre-stimulus baseline. A dichotomy was constructed by dividing
subjects into those who had no skin conductance responses to any o f the stimuli
(nonresponders) and those who had at least one response.
15
Impulsivity measures at age 18 to 21
Teacher rated impulsivity. A teacher questionnaire was developed from a
rating scale o f school behavior created by Baker and Mednick (1984). This
questionnaire was completed by the teacher who was best acquainted with each
subject. It included 85 items, each rated on a 4-point scale. A nine item scale was
constructed from this questionnaire to measure impulsivity by selecting items with face
validity. This scale was then analyzed using Cronbach's alpha coefficient, a measure of
internal-consistency reliability. The nine items included: poor concentration, easily
distracted, difficulty working on same thing for very long, fidgeting, restless, gives up
easily, speaks without thinking, poor emotional control, and impulsive (alpha = .91).
Although some o f these items may not measure impulsivity specifically, all nine items
were included in the scale because they were found to contribute significantly to it.
The resulting scale, therefore, measures the related constructs of attention deficit,
hyperactivity, and impulsivity. Subjects were rated from 0 to 3 on each of the nine
items. Scores for each item were then summed to obtain a total impulsivity score
ranging from 0 to 27.
Measures of frontal lobe functioning at age 18 to 21
An extensive neuropsychological evaluation was given to all subjects. The
following tests were selected from the battery to be of relevance to this study because
they provide indexes of frontal lobe functioning.
Porteus Maze. Execution of this maze tracing task is considered to be
dependent on the frontal function of planning ability and foresight (Lezak, 1995). To
16
achieve a successful trial, the subject must trace the maze without entering any "blind
alleys." The Vineland revision contains twelve mazes for ages 3 through 12, age 14,
and adult. The mazes for ages 9,14, and adult were used in this study. Two trials are
allowed for the age 9 maze, four trials for the age 14 maze, and four trials for the adult
maze. Therefore, up to ten trials may have been administered to each subject. Two
types of scores were used: (1) total time to completion for all three mazes (in
seconds) and (2) number o f incorrect trials (0-10).
Halstead Category Test. This test is a measure o f frontal function, assessing
the ability to perceive relationships, as well as implicit organizational skills, concept
formation, and learning experience (Reitan, 1964). The test includes 208 slides
divided into seven subtests, each of which reflects a common idea or principle. The
subject watches the slides and is asked to depress one o f four levers on a response
panel. Immediate feedback is provided by a bell ringing for a correct response and a
buzzer sounding for an incorrect response. The score for the test is the total number
o f incorrect responses for all seven categories.
Word Fluency. This test is used to assess verbal production, which is
associated with the frontal lobes (Lezak, 1995). The subject is asked to name, within
a one minute interval, as many different items as possible from among (1) things one is
likely to see in the street, and (2) animals. The test score is the total number o f items
named.
WAIS Vocabulary. The vocabulary subtest of the WAIS (in Danish) was
selected as a control measure to confirm that any deficits on the frontal lobe
17
neuropsychological measures exceed those attributable to general performance deficits
among subjects. Vocabulary was selected for this purpose because (a) it is highly
correlated with Full-Scale IQ (.81); (b) it is relatively unaffected by frontal lobe
damage (McFie, 1975); and (c) it has high reliability (internal .96, test-retest .93;
Wechsler, 1981). Since there are no Danish norms for the WAIS for the age range of
these subjects, raw scores were analyzed rather than scaled scores. The test score is
the total raw score, with a maximum score o f 70.
Statistical Analyses
Analysis o f variance (ANOVA) was used to analyze all variables with two
exceptions: (1) For heart rate arousal analyses, a repeated measures multivariate
analysis o f variance (MANOVA) was used to test group differences at the start and
end o f the rest period. MANOVA was used instead o f ANOVA in these repeated
measures analyses because the assumption o f sphericity is frequently violated when
repeated measures ANOVA is used with psychophysiological data, leading to an
increased likelihood of Type I errors (Vasey and Thayer, 1987); (2) Chi square and
logistic regression analyses were used to compare skin conductance responders and
nonresponders. To test all six hypotheses, the following four sets o f comparisons
were analyzed: risk group comparisons, risk and crime group comparisons, alcoholism
group comparisons, and alcoholism and crime group comparisons. Each comparison
included analysis o f variables measuring arousal, orienting, impulsivity, and frontal
lobe functioning.
18
Results
Risk Group Comparisons
These results concern comparisons between high risk and low risk subjects.
Means and standard deviations for all comparisons are presented in Table 2. In cases
o f significant results, E and p values are also noted.
Arousal. No significant differences between high and low risk groups were
obtained for SCL (p > .24), NS-SCR (p > .35), or HRL (p > .20).
Orienting. No significant differences between high and low risk groups were
obtained for SCR frequency (p > . 48) or average amplitude (p > .69). The
relationship between risk status and lack of skin conductance response was also
nonsignificant (p > .62). Nineteen of 63 low risk subjects (30%) were skin
conductance nonresponders on the right hand, compared to 34 of 127 high risk
subjects (27%).
Impulsivitv. Scores for the high and low risk groups on the impulsivity scale
did not significantly differ (p > .06).
Frontal Lobe Function. The high risk group made significantly more errors on
both the Halstead Category test (p < .05) and the Porteus Mazes (p < 05). In
addition, the high risk group scored significantly lower on the WAIS Vocabulary
(p < . 05). In order to assess whether these group differences might be due to
generalized cognitive function, ANCOVAs were conducted for the two significant
frontal measures using Vocabulary score as a covariate. The results o f these analyses
were both nonsignificant (p > . 10), suggesting that differences on the frontal measures
19
could be due to a more generalized cognitive deficit in the high risk group. No
significant differences were found for Word Fluency (p > .62) or Porteus Maze time
(p> .61).
Risk and Crime Group Comparisons
These results concern interactions between risk and crime status. Comparison
groups are the following: (1) high risk, criminal; (2) high risk, noncriminal; (3) low
risk, criminal; and (4) low risk, noncriminal. Means and standard deviations for all
comparisons are presented in Table 3, along with significant F and p values.
Arousal. No significant interactions were found for SCL (p > .63), NS-SCR
(p > .40), or HRL (p > .54). However, a main effect of crime was found, such that
criminals had significantly higher skin conductance levels at the start of rest, regardless
o f risk status (p < . 05).
Orienting. No significant interactions were obtained for SCR frequency (p >
.60) or average amplitude (p > .48). A logistic regression analysis also revealed a
nonsignificant risk by crime interaction on skin conductance nonresponding (p >. 65).
Impulsivitv. No significant interactions o f risk and crime were found (p >. 94).
However, there was a main effect o f crime status on impulsivity, with the criminal
group scoring significantly higher on the impulsivity scale (p < .001).
Frontal Lobe Function. There were no significant risk by crime interactions on
Word Fluency (p > .55), Halstead Category (p >. 14), or Porteus Mazes (p > .44).
20
Alcoholism Group Comparisons
These results concern comparisons between alcoholic and nonalcoholic
subjects. Means and standard deviations for all comparisons are presented in Table 4.
In cases of significant results, F and p values are also noted.
Arousal. No significant differences between alcoholic and nonalcoholic groups
were obtained for SCL (p > .85), NS-SCR (p > .44), or HRL (p > 31).
Orienting. No significant differences were found for SCR frequency.
However, alcoholics did evidence a trend towards significantly fewer responses to the
orienting tones than nonalcoholics (p = .05). No significant differences between
groups were obtained for average amplitude (p > .26). The relationship between
alcoholism diagnosis and lack of skin conductance response was also nonsignificant
(p > .40). Twenty-seven of 106 nonalcoholics (26%) were skin conductance
nonresponders on the right hand, compared to 18 o f 57 alcoholics (32%).
Impulsivity. The alcoholic group scored significantly higher than the
nonalcoholic group on the impulsivity scale (p < . 05).
Frontal Lobe Function. Alcoholics scored significantly lower than
nonalcoholics on Word Fluency (p < .05), and made significantly more errors on the
Porteus Mazes (p < .05). No significant differences were found for Halstead Category
(p > .24), or Porteus Maze time (p > .62).
Alcoholism and Crime Group Comparisons
These results concern interactions between alcoholism and crime. Comparison
groups are the following: (1) alcoholic, criminal; (2) alcoholic, noncriminal; (3)
21
nonalcoholic, criminal; and (4) nonalcoholic, noncriminal. Means and standard
deviations for all comparisons are presented in Table 5, along with significant F and p
values.
Arousal. No significant interactions were obtained for SCL (p > . 11), NS-SCR
(p > .14), orH R L(p> .89).
Orienting. No significant interactions were found for SCR frequency (p > .38)
or average amplitude (p > .89). A logistic regression analysis also revealed a
nonsignificant risk by crime interaction on skin conductance nonresponding (p > .61).
Impulsivity. No significant interactions were found (p > .38). However, a main
effect of crime was reported. The criminal group scored significantly higher on the
impulsivity scale, regardless of alcoholism diagnosis (p < .001).
Frontal Lobe Function. A significant interaction between alcoholism diagnosis
and criminal status was found for the Halstead Category test (p < .05). To determine
which of the four groups were significantly different from each other, post hoc t-tests
were performed. Results revealed that nonalcoholic criminals made significantly more
errors than nonalcoholic noncriminals (t, one-tailed = 1.91, p < .05). Alcoholic
noncriminals also made significantly more errors than nonalcoholic noncriminals (t,
two-tailed = 2.10, p < .05). No other group differences were found. In order to test
whether the reported differences might be attributable to generalized cognitive
dysfunction, an ANCOVA was conducted for the Halstead Category score using
WAIS Vocabulary score as covariate. The result was nonsignificant (p > .09),
suggesting that this interaction effect may be due to differences in general cognitive
22
functioning. No significant interactions were found for Word Frequency (p > .61) or
Porteus Mazes (p > .13).
Mediating Effects o f Frontal Lobe Function
It was hypothesized that differences in arousal, orienting, and impulsivity
would be mediated by frontal lobe function. Alcoholics performed more poorly than
nonalcoholics on two frontal measures: Word Fluency and Porteus Mazes.
Alcoholics also evidenced greater impulsivity and a trend toward reduced SCR
frequency compared to nonalcoholics. In order to determine whether frontal lobe
functioning mediated these relationships, ANCOVAs were conducted for the
impulsivity and orienting variables, using the two frontal measures as covariates. After
covarying out the frontal measures, the ANCOVAs were significant (p < .05),
suggesting that both frequency o f skin conductance responding and impulsivity may be
independent o f frontal functioning.
Exclusion of Mentally 1 1 1 Control Subjects
Although 25 nonalcoholic subjects were diagnosed with other mental illnesses,
including eight with other substance abuse diagnoses, these subjects were included in
the nonalcoholic group. This was done to maintain consistency with the alcoholic
group. The majority of the subjects who received an alcohol diagnosis also had a
comorbid diagnosis. Although analyses were conducted including control subjects
who were mentally ill, all analyses were redone after removing the 25 subjects from
the nonalcoholic group. The results were virtually identical to those of the primary
analyses.
23
Risk, Alcoholism, and Crime Group Comparisons
Additional three-way analyses (risk x alcohol group x crime group) were
conducted to determine whether any two-way effects were a function o f risk status.
However, none o f the three-way analyses were significant.
Discussion
The six hypotheses tested in this study were largely unsupported. Relevant
findings are described below, along with possible explanations for insignificant results,
and directions for future research.
Risk Group Comparisons
It was predicted that abnormalities in arousal, orienting, and impulsivity would
characterize sons o f alcoholics relative to sons o f nonalcoholics. This hypothesis was
not supported, in contrast to studies that have found higher resting heart rate (Hill et
al., 1992) and increased skin conductance orienting (Finn et al., 1990) in males with a
family history of alcoholism. However, both of these studies defined family history
differently from each other, as well as from the present study. For example, Hill
defined a family history of alcoholism as having a first- and second-degree relative
who is alcoholic, and included both alcoholic and nonalcoholic subjects in this positive
family history group. Finn et. al defined family history as having both an alcoholic
father and paternal grandfather. Perhaps only high risk individuals with a
multigenerational family history demonstrate abnormalities in arousal and orienting. In
addition, the evidence for both o f these findings is both limited and inconsistent (Finn
and Pihl, 1987; Finn et al., 1990; Levenson et al., 1987).
24
With respect to impulsivity, previously published findings using this same
sample reported that high risk subjects scored higher on an impulsivity scale than low
risk subjects (Knop et.al.,1985). These inconsistent results could be due to the fact
that the present study used a different impulsivity scale than the previous study.
Although both studies derived their impulsivity scales from the same questionnaire, the
items used were not the same. The previous study created an impulsive-restless scale
which could not be replicated due to loss of information about how the scale was
created. Therefore, the present study created a different impuslvity scale, one that
measured impuslvity-hyperactivity-inattention. Perhaps this more specific measure of
impulsivity related constructs does not discriminate between sons of alcoholics and
controls.
Additional results showed that high risk subjects performed significantly poorer
than low risk subjects on the Halstead Category test, the Porteus Maze test, and
WAIS Vocabulary (previously reported by Drejer et al., 1985). However, when the
frontal measures were reanalyzed while controlling for Vocabulary score, the
differences were no longer significant. This suggests that the poorer performance by
the high risk group may be due to a more generalized cognitive deficit. In order to
further test specificity of function, it would be useful to compare groups on measures
of other brain areas, such as temporal or parietal lobe functioning.
Risk and Crime Group Comparisons
It was predicted that abnormalities in arousal, orienting, and impulsivity would
more specifically characterize sons of alcoholics who commit crime relative to other
25
comparison groups. In addition, it was hypothesized that this pattern of disturbances
in criminal sons of alcoholics could be accounted for by frontal lobe dysfunction.
These hypotheses were not supported. However, two significant findings emerged
from these analyses. Although it was not predicted, criminals, regardless of risk
status, had higher skin conductance levels at the start of the resting period, indicating
higher baseline arousal. This finding is inconsistent with results of other studies, which
have found evidence for skin conductance underarousal in criminals (Hinton et al.,
1979; Raine, 1990a). However, both o f these studies found evidence for low arousal
as measured by nonspecific skin conductance responses, not skin conductance level.
Nevertheless, there is no support in the literature for higher arousal in criminals and it
is difficult to account for this anomalous finding.
Criminals were also found to be more impulsive than noncriminals, but this
result was independent o f risk status. The finding that criminals are highly impulsive
has received consistent support in the research literature (Eysenck and McGurk, 1980;
Farrington, 1990; Zuckerman, 1989). However, these studies did not address family
history of alcoholism in subjects so it is difficult to determine whether there is specific
support for the above hypothesis regarding criminal sons o f alcoholics.
Alcoholism Group Comparisons
It was predicted that abnormalities in arousal, orienting, and impulsivity would
characterize alcoholics relative to nonalcoholics. This hypothesis received partial
support. With respect to arousal, no significant results were reported. This finding
was somewhat expected due to limited support for arousal disturbances in sober
26
alcoholics (Laberg, 1986). With respect to orienting, there was evidence for a trend
showing that alcoholics made fewer skin conductance responses to tones than
nonalcoholics. However, this result should be viewed with caution, because it did not
actually reach significance (p=.05) and was only one of several measures o f orienting
that were analyzed. With respect to impulsivity, alcoholics were found to be more
impulsive than nonalcoholics, as predicted.
In addition, alcoholics performed more poorly than nonalcoholics on two of
the measures of frontal functioning: Word Fluency and Porteus Mazes. This finding
corroborates previous research on neuropsychological correlates of alcoholism (Grant,
1987). However, both the orienting trend and impulsivity finding described above
appeared to be independent o f frontal functioning, as indicated by scores on the
neuropsychological measures. Although orienting, impulsivity, and the
neuropsychological tests are considered to be generally related to frontal functioning,
it is possible that these measures are associated with different aspects of frontal
functioning. For example, impulsive behavior has been related to the orbitofrontal
cortex (Blumer and Benson, 1975), while cognitive activities are associated with the
dorsolateral frontal area (Lezak, 1995). Skin conductance orienting is considered a
basic attentional process that has been linked to the preffontal area, but it is less clear
which specific area mediates this activity (Raine et al., 1991; Tranel and Damasio,
1994).
27
Alcoholism and Crime Group Comparisons
It was predicted that abnormalities in arousal, orienting, and impulsivity would
more specifically characterize alcoholics who commit crime relative to other
comparison groups. In addition, it was hypothesized that this pattern of disturbances
in criminal alcoholics could be accounted for by frontal lobe dysfunction. These
hypotheses were not supported. There were no significant findings with respect to
arousal and orienting among criminal alcoholics, and no other research exists in this
area with which to compare these results. Criminals, regardless of whether or not they
were diagnosed with alcoholism, were found to be more impulsive than noncriminals.
This supports the extensive previous research relating impulsivity to criminal behavior
(Eysenck and McGurk, 1980; Farrington, 1990; Zuckerman, 1989). However, it does
not support the prediction that criminal alcoholics would be more impulsive than
noncriminal alcoholics. Perhaps criminals are so impulsive that a diagnosis of
alcoholism does not have an additive effect. These findings case doubt on the
proposed theory, but additional research must be done before it is abandoned. The
theory may need to be refined, possibly to include more precise definitions of
alcoholism and crime. The only other significant finding for criminal alcoholics was an
interaction between alcoholism and crime on the Halstead Category Test. The result
was that among nonalcoholics, criminals made more errors than noncriminals, and
among the noncriminals, alcoholics made more errors than nonalcoholics. However,
when WAIS Vocabulary score was covaried out, the group differences were no longer
28
significant, suggesting that differences in general cognitive functioning were
accounting for the initial finding.
Strengths and Limitations of the Study
There are several possible reasons for the general lack of support for the
study's hypotheses. One reason might be that both alcoholism and criminal behavior
need to be more strictly defined for the purpose o f these hypotheses. In the present
study, both alcoholics and criminals were defined rather loosely, in order to maximize
group size. However, this strategy may have resulted in the groups being too
heterogeneous, and not providing a pure sample of the group of interest. For example,
the alcoholism group could have been restricted to subjects with an alcohol
dependence diagnosis, rather than combining both alcohol dependence and abuse.
Another alternative would be to exclude alcoholics with a comorbid diagnosis. More
than half o f the subjects in the alcoholic group had some type o f coexisting mental
disorder that may have weakened effects.
Several researchers have addressed the heterogeneity o f alcohol use disorders,
by creating different subtypes to separate different forms o f alcoholism based on age of
onset, family history, clinical characteristics, or comorbidity. For example, Cloninger
(1987) has suggested two types o f alcoholism based on differences in underlying
personality pattern. Type 1 alcoholics are characterized by later age o f onset, are less
likely to have familial alcoholism, have relatively mild alcohol-related problems, and
are more responsive to environmental influences. Type 2 alcoholics, on the other
hand, have early age o f onset, a strong genetic component, and have more severe
29
problems, often related to antisocial behavior. Similarly, Penick, Read, Crowly, and
Powell (1978) have distinguished between familial and nonfamilial alcoholism, such
that familial alcoholism is related to earlier age o f onset and more severe social and
psychological problems. Others, such as Finn and Pihl (1987) have made further
distinctions based on the depth and density o f family history. Perhaps one o f these
subtypes would have more clearly differentiated the alcoholics in the present study
than dividing them into criminal and noncriminal groups.
The criminal group could have also been more clearly defined, for example, by
using only recidivistic offenders, rather than one-time offenders. Other options include
distinguishing between violent and nonviolent crime, or psychopaths and more
common criminals. However, it is possible that these other definitions would produce
very small numbers. In the present study, criminal status was defined by arrest record,
rather than conviction record, so it is possible that some of the subjects were not
actually found guilty o f committing the crime, which could have contaminated results.
An additional option would be to use self-report data along with official data, to assess
criminal behavior. Finally, dimensional measures o f alcoholism and criminality, as
opposed to dichotomous groups, could have been used. This would allow
examination o f different levels o f drinking behavior or varying degrees of antisocial
behavior.
Another potential factor related to the insignificant results is that the
hypotheses were partly based on limited research findings, particularly with respect to
autonomic factors and alcoholism. Much of the research in this area focuses on
30
changes in psychophysiologica! measures in response to alcohol (Finn and Pihl, 1987;
Finn et al., 1990; Levenson et al., 1987). Additional prospective research is needed in
the area o f arousal and orienting in sober alcoholics, before any firm conclusions can
be drawn about this population. In addition, there is only limited support relating
autonomic arousal and orienting specifically to the frontal lobes in normal humans
(Raine et al., 1991). Therefore, the theory on which this study was based may have
lacked adequate support.
Another related problem concerns the limitations o f the frontal measures that
were used in this study. Most importantly, the Halstead Category Test has been
criticized for being too time consuming, taking many normal control subjects up to an
hour to complete (Lezak, 1995). This is particularly a drawback when assessing a
subject population known to have attention difficulties. In addition, total time to
complete the Porteus Maze test did not significantly differentiate any of the
comparison groups. A better alternative might have been the Wisconsin Card Sorting
Test (Berg, 1948). It is a widely used, well researched measure o f frontal lobe
functioning and impaired performance on it has been found to characterize alcoholics
(Gorenstein, 1987).
Finally, the issue of Type I error cannot be overlooked. The present study
involved numerous analyses, so it is possible that the few significant findings reported
were simply due to chance. However, the fact that several significant results were
noted for both impulsivity and frontal measures indicates that these probably were
valid findings. In addition, similar findings have received strong support in the
31
research literature for both alcoholism and crime (Cloninger et al., 1988; Grant, 1987;
Gorenstein, 1982; White et al., 1994). On the other hand, several measures of arousal
and orienting were tested for each hypothesis and therefore, the one significant arousal
finding and single orienting trend should be viewed with caution. In the future, it
would be more informative to address hypotheses separately, since some were
generally exploratory.
The major advantage o f this study involves its prospective longitudinal design,
which can help tease apart cause and effect relationships by unraveling temporal
relationships between predisposing variables. In addition, the study attempted to
address an important societal problem in a relatively unresearched area. A relationship
between alcohol abuse and crime is widely known, yet most of the alcohol research
fails to address the heterogeneity of alcoholism and differentiate between criminal and
noncriminal alcoholics.
Directions for Future Research
Future research should take into account the limitations o f this study, as
discussed above, in order to better assess the role of psychophysiological, behavioral,
and neuropsychological factors in the development of alcoholism and its relationship
to criminal behavior. Directions for future research, therefore, point towards the
continued use of prospective longitudinal designs. These studies are potentially useful
in identifying early markers o f alcohol-related problems. Such findings could help
inform future interventions that may prevent those problems from fully developing.
32
Additional prospective studies could focus on the effects o f alcohol on
autonomic arousal, orienting, and responses to aversive stimuli. There is a significant
amount of support for the idea that alcohol reduces these psychophysiological
responses in individuals at risk for alcoholism (Finn and Pihl, 1987; Finn et al., 1990;
Levenson et al., 1987). However, no prospective research has yet been conducted to
determine how well this common biological risk factor actually predicts future
alcoholism. Additional research should also define alcoholism and crime more strictly,
or use subtypes in order to more adequately address the heterogeneity o f these
conditions. Alternatively, dimensional measures could be used to assess levels of
drinking and criminal activity.
This biologically based study undoubtedly addressed only part o f the
explanation for the mechanisms underlying the relationship between alcohol and crime.
Numerous social and environmental variables, such as unstable home environment,
personality features, or life stress, may also contribute to this relationship. Future
research should therefore focus on the interaction between biological and situational
factors contributing to criminal behavior among alcoholics.
33
Table 1
Subject Breakdown bv Group Membership and Risk Status
Numbers in each risk group are also expressed as a percentage of the total risk group. Criminals after
attrition refers to the criminal group used in the alcoholism by crime analyses, which excluded the 27
people for whom alcoholism diagnoses were not known due to attrition.
Initial Assessments at Age 18-21
Total N High Risk Low Risk (N1 High Risk(%~) Low Risk(%)
190 127 63 67% 33%
Follow-Up at Age 30-33
Attrition
27 19 8 15% 13%
Alcoholic Group
57 39
Nonalcoholic Group
106 69
No Diagnosis
81 51
Other Diagnosis
17 10
Other Substance Disorders
8
Criminal Status
Criminals
81
Criminals after attrition
70
8
57
48
18 31% 29%
37 54% 59%
30 40% 48%
8% 11%
6% 0%
24 45% 38%
22 38% 35%
Risk Group Comparisons - Means. Standard Deviations, and Significant Effects
Measure
Arousal
SCL
NS-SCR
HRL start rest
HRL end rest
Group
Low Risk
High Risk
Low Risk
High Risk
Low Risk
High Risk
Low Risk
High Risk
Mean (SD)
4.249(1.862)
4.646(2.251)
2.070(1.771)
2.369 (2.106)
62.455 (9.012)
60.339(10.042)
61.667 (9.259)
60.500 (9.633)
Orienting
SCR frequency
SCR average amplitude
Impulsivity
Impulsivity scale score
Frontal Lobe Function
Word Fluency
Halstead Category-errors ‘
Porteus Mazes-total time
Porteus Mazes-errors1
WAIS Vocabulary ‘
Low Risk
High Risk
Low Risk
High Risk
Low Risk
High Risk
Low Risk
High Risk
Low Risk
High Risk
Low Risk
High Risk
Low Risk
High Risk
Low Risk
High Risk
1.984 (2.036)
2.228 (2.348)
0.007 (0.015)
0.008 (0.014)
8.533 (8.242)
11.189 (7.426)
35.286 (9.960)
34.587 (8.921)
37.365 (23.498)
45.349 (23.534)
207.180 (85.111)
213.853 (85.460)
0.645 (0.832)
0.944(1.002)
43.476(10.767)
39.373 (11.413)
“ Main effect of risk: F (1,188) = 4.839, p < .05
b Main effect of risk: F (1,186) = 4.105, p < 05
cMain effect of risk: F (1,188) = 5.634, p < .05
35
Table 3
Risk and Crime Group Comparisons - Means. Standard Deviations, and Significant Effects
Measure Group Mean CSDi N
Arousal
SCL° Low Risk, Noncriminal 3.890(1.705) 35
Low Risk, Criminal 4.795(1.993) 23
High Risk, Noncriminal 4.390 (2.274) 62
High Risk, Criminal 4.964(2.204) 50
NS-SCR Low Risk, Noncriminal 2.294 (2.008) 34
Low Risk, Criminal 1.739(1.322) 23
High Risk, Noncriminal 2.371 (2.383) 62
High Risk, Criminal 2.367(1.716) 49
HRL start rest Low Risk, Noncriminal 63.727(7.954) 33
Low Risk, Criminal 60.546(10.299) 22
High Risk, Noncriminal 60.400(10.270) 60
High Risk, Criminal 60.265(9.861) 49
HRL end rest Low Risk, Noncriminal 62.029 (8.650) 34
Low Risk, Criminal 61.130(10.270) 23
High Risk, Noncriminal 60.295(10.241) 61
High Risk, Criminal 60.740 (8.932) 50
Orienting
SCR frequency Low Risk, Noncriminal 2.026 (1.881) 38
Low Risk, Criminal 1.920(2.290) 25
High Risk, Noncriminal 2.437(2.703) 71
High Risk, Criminal 1.964 (1.789) 56
SCR average amplitude Low Risk, Noncriminal 0.009 (0.018) 38
Low Risk, Criminal 0.004 (0.006) 25
High Risk, Noncriminal 0.009(0.015) 71
High Risk, Criminal 0.007(0.012) 56
Impulsivity
Impulsivity scale scoreb Low Risk, Noncriminal 6.310 (6.772) 29
Low Risk, Criminal 12.563 (9.316) 16
High Risk, Noncriminal 8.611 (7.059) 54
High Risk, Criminal 15.056(6.256) 36
Frontal Lobe Function
Word Fluency Low Risk, Noncriminal 35.632(10.383) 38
Low Risk, Criminal 34.760 (9.466) 25
High Risk, Noncriminal 35.743(10.202) 70
High Risk, Criminal 33.143 (6.818) 56
36
Table 3 continued
Risk and Crime Group Comparisons - Means. Standard Deviations, and Significant Effects
Measure Group Mean (SDi
Frontal Lobe Function
Halstead Category-errors Low Risk, Noncriminal 39.079 (25.528)
Low Risk, Criminal 34.760 (20.249)
Fligh Risk, Noncriminal 42.443 (23.042)
High Risk, Criminal 48.982(23.843)
Porteus Mazes-total time Low Risk, Noncriminal 220.270 (96.248)
Low Risk, Criminal 187.000 (60.802)
High Risk, Noncriminal 219.353 (96.520)
High Risk, Criminal 206.926 (69.347)
Porteus Mazes-errors Low Risk, Noncriminal 0.676 (0.709)
Low Risk, Criminal 0.600(1.000)
High Risk, Noncriminal 0.884 (0.978)
Fligh Risk, Criminal 1.018(1.036)
WAIS Vocabulary Low Risk, Noncriminal 42.737 (10.877)
Low Risk, Criminal 44.600 (10.720)
High Risk, Noncriminal 41.257(11.678)
Fligh Risk, Criminal 37.018(10.714)
‘ Main effect of crime: F (1,169) = 19.489, g < .05
b Main effect of crime: F (1,134) = 25.813, g < .001
N
38
25
70
56
37
24
68
54
37
25
69
56
38
25
70
56
37
Table 4
Alcoholism Group Comparisons - Means. Standard Deviations and Significant Effects
Measure Group Mean tSDl N
Arousal
SCL Nonalcoholic 4.565 (2.172) 94
Alcoholic 4.636 (2.278) 53
NS-SCR Nonalcoholic 2.064(1.888) 94
Alcoholic 2.327 (2.149) 52
HRL start rest Nonalcoholic 60.294 (8.581) 92
Alcoholic 61.880 (10.141) 50
HRL end rest Nonalcoholic 60.130 (8.918) 92
Alcoholic 61.396 (9.712) 53
Orienting
SCR frequency Nonalcoholic 2.425 (2.503) 106
Alcoholic 1.684(1.794) 57
SCR average amplitude Nonalcoholic 0.008 (0.013) 106
Alcoholic 0.006 (0.011) 57
Impulsivity
Impulsivity scale score * Non-Alcoholic 9.000 (7.735) 81
Alcoholic 12.865 (7.406) 37
Frontal Lobe Function
Word Fluencyb Nonalcoholic 36.076 (9.765) 105
Alcoholic 32.877 (8.550) 57
Halstead Categorv-errors Nonalcoholic 40.200 (23.508) 105
Alcoholic 44.649 (22.300) 57
Porteus Mazes-total time Nonalcoholic 203.019(74.181) 103
Alcoholic 209.259 (77.988) 54
Porteus Mazes-errorsc Nonalcoholic 0.692 (0.860) 104
Alcoholic 1.088(1.154) 57
WAIS Vocabulary Nonalcoholic 41.533 (10.964) 105
Alcoholic 39.491 (10.249) 57
9 Main effect of alcoholism: F (l,l 17)==6.510, p<.05
b Main effect of alcoholism: F(l,161)=4.317, p<.05
c Main effect of alcoholism: F( 1, 160)=6.073, p<.05
38
Table 5
Alcoholism and Crime Group Comparisons - Means. Standard Deviations, and Significant Effects
Measure Group Mean (SD) N
Arousal
SCL Nonalcoholic, Noncriminal 4.199(1.706) 64
Nonalcoholic, Criminal 5.346 (2.807) 30
Alcoholic, Noncriminal 4.716(3.360) 18
Alcoholic, Criminal 4.595 (1.511) 35
NS-SCR Nonalcoholic, Noncriminal 2.000(1.976) 64
Nonalcoholic, Criminal 2.200(1.710) 30
Alcoholic, Noncriminal 2.889(2.149) 18
Alcoholic, Criminal 2.029(1.714) 34
HRL start rest Nonalcoholic, Noncriminal 60.807(8321) 62
Nonalcoholic, Criminal 59.233 (9.149) 30
Alcoholic, Noncriminal 62.177(8.487) 17
Alcoholic, Criminal 61.727(11.018) 33
HRL end rest Nonalcoholic, Noncriminal 59.677(9.217) 62
Nonalcoholic, Criminal 61.067(8.337) 30
Alcoholic, Noncriminal 61.389(8.147) 18
Alcoholic, Criminal 61.400(10.539) 35
Orienting
SCR frequency Nonalcoholic, Noncriminal 2.575(2.635) 73
Nonalcoholic, Criminal 2.091 (2.185) 33
Alcoholic, Noncriminal 1.550 (1.761) 20
Alcoholic, Criminal 1.757 (1.832) 37
SCR average amplitude Nonalcoholic, Noncriminal. 0.009(0.014) 73
Nonalcoholic, Criminal 0.006(0.011) 33
Alcoholic, Noncriminal 0.007(0.013) 20
Alcoholic, Criminal 0.005 (0.009) 37
Impulsivity
Impulsivity scale score ° Nonalcoholic, Noncriminal 6.983 (6.765) 57
Nonalcoholic, Criminal 13.792(7.913) 24
Alcoholic, Noncriminal 10.333 (7.575) 15
Alcoholic, Criminal 14.591 (6.933) 22
Frontal Lobe Function
Word Fluency Nonalcoholic, Noncriminal 36.319(10.256) 72
Nonalcoholic, Criminal 35.546 (8.725) 33
Alcoholic, Noncriminal 34.450(10.952) 20
Alcoholic, Criminal 32.027 (6.950) 37
39
Table 5 continued
Alcoholism and Crime Group Comparisons - Means. Standard Deviations, and Significant Effects
Measure Group Mean tSDl
Frontal Lobe Function
Halstead Category-errorsb Nonalcoholic, Noncriminal 37.278 (22.493)
Nonalcoholic, Criminal 46.476 (24.745)
Alcoholic, Noncriminal 49.150 (22.082)
Alcoholic, Criminal 42.216(22.335)
Porteus Mazes-total time Nonalcoholic, Noncriminal 203.535 (80.999)
Nonalcoholic, Criminal 201.875 (57.350)
Alcoholic, Noncriminal 236.474 (94.731)
Alcoholic, Criminal 194.486 (63.964)
Porteus Mazes-errors Nonalcoholic, Noncriminal 0.648 (0.776)
Nonalcoholic, Criminal 0.788(1.023)
Alcoholic, Noncriminal 1.200(1.152)
Alcoholic, Criminal 1.027(1.166)
WAIS Vocabulary Nonalcoholic, Noncriminal 42.931 (10.647)
Nonalcoholic, Criminal 38.485 (11.189)
Alcoholic, Noncriminal 39.400(11.208)
Alcoholic, Criminal 39.541 (9.853)
8 Main effect of crime: F (1,117) = 17.774, g < .001
b Alcoholism x Crime interaction: F (1,161) = 4.151, p < 0 5
M
72
33
20
37
71
32
19
35
71
33
20
37
72
33
20
37
40
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A thesis

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Creator Bihrle, Susan Elizabeth (author)

Core Title The relationship between alcoholism and crime: autonomic and neurpsychological factors

School Graduate School

Degree Master of Arts

Degree Program Psychology

Degree Conferral Date 1995-08

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag OAI-PMH Harvest,psychology, behavioral,psychology, clinical,psychology, physiological,sociology, criminology and penology

Language English

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Advisor Raine, Adrian (committee chair), [illegible] (committee member), Earleywine, Mitchell (committee member)

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