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Association of Antisocial PersonalityDisorder with Psychiatric MorbidityAmong Patients with Substance UseDisorderJoseph Westermeyer MD, MPH, PhD a b , Paul Thuras PhD b & GregoryCarlson BS ca Minneapolis VAMCb University of Minnesotac Addiction Medicine Division, Hennepin County Medical CenterPublished online: 09 Oct 2008.

To cite this article: Joseph Westermeyer MD, MPH, PhD , Paul Thuras PhD & Gregory Carlson BS(2006) Association of Antisocial Personality Disorder with Psychiatric Morbidity Among Patients withSubstance Use Disorder, Substance Abuse, 26:2, 15-24, DOI: 10.1300/J465v26n02_03

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Association of Antisocial Personality Disorderwith Psychiatric Morbidity

Among Patients with Substance Use Disorder

Joseph Westermeyer, MD, MPH, PhDPaul Thuras, PhD

Gregory Carlson, BS

ABSTRACT. Objectives: The aims were to determine among patients with Substance Use Disor-der (SUD) whether patients with Antisocial Personality Disorder (ASPD) manifest less, the same,or more of the following: (1) psychiatric symptoms, (2) family history of psychiatric disorder,(3) psychiatric disorders and morbidity, and (4) psychiatric treatment, as compared to patientswithout ASPD.

Design & Definition: Scheduled interview using DSM-III-R criteria for ASPD, with blinded in-terviewers making the ASPD classification vs. other assessments.

Settings: Alcohol-drug treatment programs located in two university medical centers.Subjects: Six hundred and six voluntary patients aged 18 and older meeting diagnostic criteria

for SUD.Results: SUD patients with ASPD reported more family history of non-SUD psychiatric diag-

noses and endorsed more hostility symptoms. Demographic characteristics, psychiatric disorder,and past psychiatric treatment did not differ in association with ASPD. [Article copies available fora fee from The Haworth Document Delivery Service: 1-800-HAWORTH. E-mail address: <docdelivery@haworthpress.com> Website: <http://www.HaworthPress.com> © 2005 by The Haworth Press, Inc. Allrights reserved.]

KEYWORDS. Substance Use Disorder, comorbidity, Antisocial Personality Disorder

INTRODUCTION

Clinicians earlier considered patients mani-festing Antisocial Personality Disorder (ASPD)as not experiencing the usual inhibitions and“neuroticism” of others. Physiologic studiesindicating less electro-dermal, facial, and star-tle responses to stress (1,2) and reduced execu-

tive regulation of normal inhibitory mecha-nisms (3,4) have supported this theoreticalviewpoint. However, considerable data overthe last 15 years have shown that patients withASPD, despite reduced inhibitory responses,have increased “neuroticism”compared to oth-ers (5-9). A possible mechanism might be fron-tal lobe lesions associated with both ASPD as

Joseph Westermeyer is Chief of Psychiatry and Director of Mental Health, Minneapolis VAMC, Professor ofPsychiatry and Adjunct Professor of Anthropology, University of Minnesota.

Paul Thuras is Statistician, Minneapolis VAMC and Research Associate, University of Minnesota.Gregory Carlson is Director, Addiction Medicine Division, Hennepin County Medical Center.Acknowledgment is expressed to Dr. James Halikas, Dr. Sheila Specker, and Mr. John Neider for their respective

roles in evaluating these patients as well as tabulating and analyzing the data. The Laureate Foundation of Tulsa pro-vided support to tabulate and analyze these data.

Substance Abuse, Vol. 26(2) 2005Available online at http://www.haworthpress.com/web/SUBA

© 2005 by The Haworth Press, Inc. All rights reserved.doi:10.1300/J465v26n02_03 15

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wellaswithmoodandanxietydisorders(10-13).Changes in the dopaminergic/adrenergic sys-tems may also occur in both ASPD and mood-anxiety disorders (14). The comorbidity ofASPD with numerous Axis 1 and 2 disordercould also contribute to this paradoxical phe-nomenon of decreased stress responses and in-creased emotional symptoms (15-18).

Despite the growing body of knowledge re-garding psychiatric comorbidity of ASPD, thepsychiatric comorbidity in patients with Sub-stance Use Disorder (SUD) and ASPD is lesswell known. Available data suggest that con-siderable psychiatric morbidity may accom-panycomorbidSUDandASPD.Hesselbrock’sstudy of young patients with SUD indicatedthat adolescent depression, in association withSUD,maypredict laterASPD(19).TheWoodyteam has shown that, among addicted patients,those with ASPD have more than the expectedrate of psychiatric symptoms and disorders(20). Alterman and coworkers have observedthat, in a methadone program, patients withASPD and depression showed a superior treat-mentresponseascomparedto thosewithASPDalone (21).

The current study was undertaken in order toassess psychiatric symptoms in a group of pa-tients being evaluated for SUD. The designa-tion of ASPD was blinded to those conductingother ratings. Research questions were asfollows:

• Would SUD patients with ASPD reportmore psychiatric symptoms?

• Would SUD patients with ASPD havehigher rates of familial psychiatric disor-der (not including SUD and ASPD)?

• Would SUD patients with ASPD havemore current Axis 1 psychiatric disorderand associated psychiatric morbidity?

• Would SUD patients with ASPD havemore lifetime psychiatric treatment?

METHOD

Sample

The original sample of 642 patients included34 patients under the age of 18 and 2 patientswho did not meet criteria for a SUD. These 36

patients were dropped from the study, leaving606 patients. Patients had been referred with analcohol and/or drug related problem to pro-grams located within Departments of Psychia-try at two university medical centers. All pa-tients were voluntary, and about 90% wereinitially assessed as outpatients. In order toeliminate effects of intoxication and with-drawalstates,patientsweresoberandnotmani-festing withdrawal signs or symptoms at thetime of evaluation. Financial categories in-cluded private fee-for-service, referrals fromHealth Maintenance Organizations, Medicare-Medicaid, and Medical Assistance (with eachgroup representing about 20 to 30% of the pa-tients). Informed consent was obtained to ana-lyze and report these findings in an anonymousfashion. Referrals came from primary medicalclinicians, mental health clinicians, substanceabuse clinicians, families, friends, and patientsthemselves.

Data Collection

Patients were categorized as having Antiso-cial Personality Disorder if they met theDSM-III-R criteria for Antisocial PersonalityDisorder (ASPD). A research associate (J.N.)obtained data from patients using a scheduledquestionnaire of ASPD diagnostic criteria and,as indicated in cases of delirium or dementia,from collateral sources while blind to the otherdata described below. This diagnosis requiredthat the patient meet criteria for Conduct Disor-der prior to age 18, so that antisocial behaviorassociated with subsequent SUD would notqualify the patient for the diagnosis of ASPD inthe absence of pre-adult ASPD behavior. Stud-ies involving various scheduled interviews forASPD have shown high reliability of DSM-based interviews (22,23). Other clinicians in-volved in the assessment were blind to theseASPD ratings.

The patient-rated 90-item Symptom Check-list (SCL-90) (24) and Beck Depression Inven-tory (BDI) (25) were used to assess self-re-ported psychiatric symptoms. The SCL-90includes a General Symptom Index or GSI forall symptoms, plus 8 subscales (Somatization,Obsessive-Compulsion, Interpersonal Sensi-tivity, Depression, Anxiety, Phobic Anxiety,Paranoid Ideation, and Psychoticism). For the

16 SUBSTANCE ABUSE

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primary analysis, the GSI was used to comparethe two groups. In a secondary analysis, the 8subscale scores were also analyzed.

A trained clinical interviewer (MSW, MSN,or MA), blind to the ASPD category, obtainedthe data on substance-related psychologicalproblemsusingthe17-itemPsycho-Behavioralsubscale of the Minnesota Substance AbuseProblem Scale or M-SAPS (26). Unlike thewidely used Addiction Severity Index, thisscale requested patients to endorse only thosesymptoms that occurred in association withsubstance use. These 17 symptoms were as fol-lows: 1. Panic attacks, 2. Nightmares (recall offrightening or horrific dreams), 3. Night terrors(crying out in sleep), 4. Abuse of telephone(e.g., calling others in the middle of the night,repetitive long distance phone calls, threaten-ing or harassing phone calls), 5. Ashamed orguilty about behavior while using substances,or about use itself, 6. Self-pity, 7. Suicidal ideas,8. Unreasonable resentments, 9. Keeping a hid-den supply of alcohol and/or drugs, 10. Suspi-cious or mistrustful of others, 11. Preoccupiedwith using alcohol and/or drugs, 12. Secretiveabout alcohol and/or drug use, 13. Needing al-cohol and/or drugs to relax, 14. Using drugsand/or alcohol alone, 15. Rapid or “priming”use (e.g., after work, before a party), 16. Antici-pates, plans, or “craves” next use, 17. Late toappointments, fails appointments. The totalM-SAPS-Psycho-Behavioral score was usedfor the primary analysis, and the individualitems were used for the secondary analysis.

This interviewer also obtained a family his-tory of (1) mood disorder and (2) any othernon-SUD disorder that warranted treatmentand/or caused considerable disability (e.g., un-able to parent, work, manage household). Gen-eral labels (“eccentric”) or unsubstantiatedconditions (“maybe depressed”) were not re-corded. Family members included mother, fa-ther, any sibling, and 4 grandparents; scorecould range from 0 to 7. Only biological rela-tives were included; adoptive, foster, and stepparents were excluded.

An addiction psychiatrist rated each patienton psychiatric symptoms in the weeks sinceachieving sobriety, using the Hamilton Anxi-ety Scale (HAM) (27), the Hamilton Depres-sion Scale (HAM-D) (28), and the Brief Psy-chiatric Rating Scale (BPRS) (29). In addition,

the same psychiatrist rated the patient for over-all function the last month using the GlobalAssessment Scale (GAS) (30), as well asDSM-III-R Axis 4 (psychosocial stressors inthe last year) and Axis 5 (psychosocial functionduring the last year). The addiction psychiatristthen made the SUD and non-SUD diagnoses. Astructured substance abuse interview includedtypesof substances,usualandmaximumdoses,frequency of use, duration of use, mode of ad-ministration, and associated biomedical andpsychosocial problems. The semi-structurednatureof the interviewin these severaldomainspermitted us to elaborate the disparate disor-ders and their courses, without being tied to arigid structured format. We did not use struc-tured interviews such as the SCAN or SCID,since we observed that these interviews re-quired as much as 4 to 6 hours in patients withextensive psychiatric and diverse drug usehistories-bothcommoninthispatientsample.

A research associate (MSW, MSN, or MA),using a scheduled interview and blind to theASPD diagnosis, obtained a lifetime psychiat-ric treatment history, which excluded the cur-rent admission to treatment. This format in-cluded the following:

• Number of separate outpatient and inpa-tient admissions to psychiatric treatment,with specific inquiries made for the fol-lowing four loci of care: outpatient or dayprogram care, general hospital inpatient,state hospital inpatient care, and otherpsychiatric treatment such as residentialtreatment;

• Number of days of psychiatric care; eachoutpatient visits (for clinics and day pro-grams) counted as a day of care;

• Number of prescribed psychotropic med-ication types from 0 to 6; specific queriesincluded the following six medications:antidepressants, antipsychotics, anxiolyt-ics, mood stabilizers, analgesics, andother medicine prescribed for psychiatricindications (e.g., beta blockers for panicattacks, antihistamines for insomnia);

• Cost of psychiatric care using an imputedcosts for types of care, so as to remove theinfluence of inflation over time, a formatthat we have used and described previ-ously (31).

Westermeyer, Thuras, and Carlson 17

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Consent

Patients provided signed informed consent.Copies of the consent were placed in the chartand the research file, and provided to the pa-tient.

Data Analysis

Non-parametric categorical data (e.g., pres-ence vs. absence of a symptom vs. ASPD) werecompared using the Chi Square test, with a cor-rection for continuity. Parametric data (e.g.,age, education) were compared between thetwo groups using the Student t test. Continuousnon-parametric data (e.g., symptom scales,treatment measures) were compared using theMann-Whitney U test. Since 19 variables werestudied, the Bonferoni correction was .0026(.05/19). This was approximately the samecut-off as indicated by the Holm rejective mul-tiple test procedure (32). Probability levels be-tween.0026and.01werereportedas trends.Ef-fect size that could be detected in a comparisonof two groups this size, using .80 power and .05alpha, is 0.4 of a standard deviation.

In the primary analysis, only the total ratingscale score for the SCL-90 and the M-SAPS-Psycho-Behavioral Scale were used. Poweranalysis and effect size were based on this pri-mary analysis. In a secondary analysis, theeight SCL-90 subscales and the seventeenM-SAPS-Psycho-Behavioral Scale were com-pared.

Three logistic regression analyses were con-ducted, using the Wald statistic with a forwardentry model. The first regression was to assessthe effect of significant demographic charac-teristics on ASPD (using p < .05 as a cut-off),since these demographic factors could con-found the data if they showed an interactive ef-fect.Thesecondregression retained the twode-mographic factors that showed a trend forassociationwithASPD(lowerageandlessedu-cation) and added significant symptom and fa-milial variables (using p < .05 as a cut-off).Third, twopsychiatricratings(Axes4and5,us-ing theDSM-III criteria)wereassessedconcur-rently. For these analyses, a .05 cut-off wasemployed.

FINDINGS

Prevalence, Demography, and FamilyHistory

Prevalence. Of these 606 patients, 54 metDSM-III-R lifetime criteria for ASPD and 552did not meet criteria for ASPD. Thus, the life-time prevalence rate of ASPD in this group was8.9%.

Demographic Characteristics. As shown inTable 1, the ASPD patients were more apt to bemale, younger, less educated, not currentlymarried, and not employed. However, none ofthesecharacteristicswas significantlydifferentin the two groups.

Family History of Non-SUD PsychiatricDisorder. As shown in Table 1, the ASPDgroup had slightly more nuclear family mem-bers with a mood disorder and with other psy-chiatric disorder; but the differences were notsignificant. When both types of disorder werecombined,however, thedifferencebetweenthetwo groups showed a trend at .004. On averagethe ASPD group had 1.7 nuclear family mem-bers with a non-SUD psychiatric disorder (s.d.1.3). The non-ASPD group had a mean of 1.0nuclear family members (s.d. 1.6).

Psychiatric Symptoms, Family History,Diagnosis, Morbidity, and Treatment

Self-Rated Beck Depression Inventory andSCL-90 Scales. Patients with ASPD hadslightlyhigher (i.e., more morbid) scores on theBeck Depression Inventory and on the GeneralSymptom Index of the SCL-90 General Symp-tom Index. However, as shown in Table 1, allscales failed to show a significant differencebetween the two groups, although the ASPDgroup had higher mean index scores on everyscale.

Interview-Based Psycho-Behavioral Prob-lems Related to Substance Abuse. Ratings onthe 17-item Psycho-Behavioral subscale of theMinnesota Substance Abuse Problem Scale(M-SAPS) did not demonstrate a significantdifference at .005, but did show a trend (seeTable 1). The ASPD group reported a mean of1.7 more symptoms (out of the total 17 symp-toms) to have been present while using sub-stances.

18 SUBSTANCE ABUSE

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Diagnosis and Morbidity. The addictionpsychiatrists made diagnoses of other non-SUD Axis 1 diagnoses in close to half of cases,with no differences between the groups (seeTable 1). Subtypes of Axis 1 diagnoses (e.g.,Mood or Anxiety Disorder) also failed to showany differences. Axis 4 Psychosocial Stressorsand Axis 5 Coping (both rated for the last year)also failed to show any differences. Almostidentical ratings for the two groups occurred onfour scales of psychopathology: i.e., Hamilton

Depression Scale, Hamilton Anxiety Scale,Brief Psychiatric Rating Scale, and Global As-sessment Scale. The first three of these scaleswere made for the current short-lived period ofsobriety and the GAS was rated for the level offunction during the last month.

Psychiatric Treatment History. The fourlifetime treatment variables, i.e., number of ad-missions to psychiatric care, number of visitsand days in psychiatric treatment, number ofprescribed psychotropic medications, and total

Westermeyer, Thuras, and Carlson 19

TABLE 1. Psychiatric Symptoms and Disorders vs. Antisocial Personality Disorder

Characteristic No ASPD, n = 552 ASPD, n = 54 Statistics

Demographic Characteristics

Gendermalefemale

307 (56%)245 (44%)

34 (63%)20 (37%)

X2 = 0.801, p = .37

Age–mean (s.d.) 31.3 (10.5) 28.7 (8.3) t = 2.121,* p = .04

Education–mean (s.d.) 12.6 (2.7) 11.9 (2.0) t = 2.435,* p = .02

Marital statussinglemarriedother

302 (55%)77 (14%)

173 (31%)

27 (51%)5 (9%)

22 (40%)

X2 = 2.0882 d.f.p = .35

Employment statusfull-timepart-timeother

115 (21%)57 (10%)

380 (69%)

7 (13%)4 (7%)

43 (79%)

X2 = 2.8652 d.f.p = .24

Socioeconomic Status Hollingshead-Redlich 3.8 (1.0) 4.0 (0.7) Z = 0.013, p = .99

Number of Nuclear Family Members with Any Non-SUD Psychiatric Disorder

Any mood disorder 0.7 (1.1) 1.3 (1.3) Z = 1.860, p = .07

Any other disorder 0.2 (0.5) 0.4 (0.8) Z = 2.430, p = .02

Any Axis 1 disorder 1.0 (1.3) 1.7 (1.6) Z = 2.911, p < .004

Patient Rated Scales (rated for recent sobriety)

Beck Depression Inv. 18.9 (12.3) 22.1 (11.9) Z = 1.847, p = .07

SCL-Genl.Sx.Index 1.02 (0.76) 1.22 (0.82) Z = 1.580, p = .11

Psychological Subscale of the M-SAPS (interview-based rating for symptoms related to using substances)

Psycho-Behavioral 10.1 (4.3) 11.8 (4.5) Z = 2.912, p < .005

Psychiatrists’ Non-SUD Diagnosis and Ratings

Non-SUD Axis 1 Dx. 280 (51%) 29 (54%) X2 = 0.076, p = .78

Axis 4–Stressors 3.9 (1.2) 4.3 (1.0) Z = 2.326, p = .02

Axis 5–Coping 4.5 (1.1) 4.8 (1.0) Z = 2.2221, p = .03

Hamilton Anxiety 13.9 (8.8) 13.5 (9.1) Z = 0.460, p = .65

Hamilton Depression 17.4 (11.1) 17.5 (10.9) Z = 0.039, p = .97

Brief Psychiatric Rating Scale 35.6 (12.2) 35.7 (10.6) Z = 0.238, p = .96

Global Assessment Scale 48.7 (14.2) 48.6 (14.2) Z = 1.256, p = .21

Lifetime Psychiatric Treatment

Number of admissions 3.2 (5.4) 3.7 (4.7) Z = 1.382, p = .17

Days of treatment 70.2 (139.5) 60.8 (100.4) Z = 0.084, p = .94

Medication types 1.9 (1.6) 2.1 (1.6) Z = 0.688, p = .49

Cost, Psychiatric Rx $35,273 (85,916) $35,408 (73,365) Z = 0.659, p = .51

* Separate variances

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cost of psychiatric care, were remarkably simi-lar among those with and without ASPD (seeTable 1). Note the large standard deviations formost treatment variables, indicating consider-able variability in treatment histories withinboth groups. Only medication had a standarddeviation less than its mean.

Secondary Analysis of Subscalesand Symptoms

SCL-90 Subscales. Among the SCL scores,one subscale showed a significant difference,usingaBonferonicorrectionof .05/8=.006: theSCL-Hostilityscorewassignificantlyhigher inthe ASPD group at p < .002; see Table 2. Therank order of the SCL subscales was similar inthe two groups. SCL-Depression, SCL-Inter-

personal Sensitivity, and SCL-Anxiety rankedfirst, second, and third, respectively, in bothgroups. SCL-Phobic Anxiety ranked the low-est.Most of the remainingsymptomcomplexesranked1or2stepsawayfromoneanother in thetwo groups, with two exceptions. Hostility was3 steps higher in the ASPD group as comparedto the non-ASPD group. And the ObsessiveCompulsion subscale was 3 steps lower in theASPD group as compared to the non-ASPDgroup.

Interview-Based Psycho-Behavioral Prob-lems Related to Substance Abuse. One item,“Abuse of telephone” (e.g., harassing others byphone, calling in the middle of the night), wassignificantly associated with ASPD at .003, us-ing a Bonferoni correction of .05/17 = .003. Asecond item, “Unreasonable resentments,”

20 SUBSTANCE ABUSE

TABLE 2. Secondary Analyses of SCL-90 Subscales and M-SAPS-Psycho-Behavioral Items

Characteristic No ASPD, n = 552 ASPD, n = 54 Statistics

Patient Rated Scales (rated for recent sobriety)

SCL-Hostility 0.87 (0.80) 1.35 (1.08) Z = 3.033, p < .002

SCL-Somatization 0.89 (0.73) 1.12 (0.73) Z = 2.386, p = .02

SCL-Interpers. Sens. 1.24 (0.92) 1.65 (1.35) Z = 1.266, p = .03

SCL-Anxiety 1.20 (0.88) 1.46 (0.91) Z = 1.968, p = .05

SCL-Depression 1.49 (0.99) 1.73 (0.85) Z = 1.845, p = .07

SCL-Paranoid Ideation 1.14 (0.91) 1.38 (0.96) Z = 1.815, p = 07

SCL-Phobic Anxiety 0.73 (0.82) 0.91 (0.94) Z = 1.232, p = 22

SCL-Psychoticism 0.90 (0.77) 1.03 (0.86) Z = 0.977, p = .33

SCL-Obsessive-Comp. 1.23 (0.93) 1.32 (0.85) Z = 0.849, p = .40

Psycho-Behavioral Subscale of the M-SAPS (rated for symptoms while using substances)

Telephone abuse 208 (39%) 32 (60%) X2 = 8.69, p < .005

Resentments 282 (52%) 38 (72%) X2 = 6.606, p < .01

Priming use 355 (66%) 43 (81%) X2 = 4.506, p = .04

Hidden supply 284 (53%) 36 (68%) X2 = 3.970, p = .05

Suicidal ideas 296 (55%) 37 (70%) X2 = 3.820, p = .05

Nightmares 207 (38%) 28 (53%) X2 = 3.697, p = .06

Appointments, late/fail 305 (57%) 37 (70%) X2 = 2.939, p = .09

Suspiciousness 312 (58%) 37 (70%) X2 = 2.410, p = .12

Night terrors 163 (30%) 22 (42%) X2 = 2.380, p = .12

Panic attack 248 (46%) 29 (55%) X2 = 1.192, p = .28

Uses substance alone 476 (88%) 49 (93%) X2 = 0.508, p = .48

Self pity 369 (68%) 39 (74%) X2 = 0.400, p = .53

Preoccupied with use 380 (70%) 40 (76%) X2 = 0.386, p = .54

Need substance to relax 423 (78%) 44 (83%) X2 = 0.384, p = .54

Ashamed/guilty re use 415 (77%) 42 (79%) X2 = 0.050, p = .82

Craving substance 378 (70%) 38 (72%) X2 = 0.010, p = 92

Secretive regarding use 366 (68%) 35 (66%) X2 = 0.011, p = .92

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showed a trend (at p = .01). ASPD patients re-ported more of both items; see Table 2. Amongthe remaining 15 items, the ASPD group re-ported 14 items more often. Only “Secretiveabout alcohol and/or drug use” was reportedless often by the ASPD group, but the percent-age difference between the two groups wassmall (2%). The rank order of most symptomstended to be similar, despite differences in se-verity level. For example, in both groups “Us-ing drugs and/or alcohol alone” and “Needingalcohol and/or drugs to relax” were the first andsecond most frequently reported symptoms as-sociated with substance use. Likewise, “Night-mares” and “Night terrors” were the two leastfrequently reported symptoms associated withuse in both groups.

Logistic Regression Analysis

The first logistic regression combined ageand education, in order to discern whether to-gether they bore a stronger relationship toASPD. Neither demographic characteristicwas retained (for age, Odds Ratio = 0.97, 95%Confidence Interval = 0.92 to 1.01; for educa-tion, OR = 0.90, 95% C.I. = 0.78 to 1.04).

The second logistic regression includedthe SCL-Hostilityscore,M-SAPS-Psychologyscore, and number of family members with apsychiatric disorder (excluding SUD), alongwith age and education; see Table 3. On for-ward conditional analysis, the following vari-ableswereretainedinassociationwithASPD:

• More family members with a psychiatricdisorder (excluding SUD): OR of 1.30and a 95% C.I. of 1.06 to 1.60 (Wald sta-tistic = 6.415, p = .011);

• Higher SCL-Hostility score: OR of 1.57and a 95% C.I. of 1.09 to 2.25 (Wald sta-tistic = 5.998, p = .014).

The M-SAPS-Psycho-Behavioral score wasnot retained in the second analysis.

The third logistic regression involved theaddition of Axis 4 Psychosocial Stressors andAxis 5 Coping scales. Although the Axis 4 andAxis 5 variables did not reach a significancelevel in the bivariate analysis, nonetheless weentered them into an analysis along with ageand education because they showed a bivariate

associationswithASPDatp<.05.NeitherAxis4 nor Axis 5 was retained in the analysis.

DISCUSSION

Prevalence of ASPD

Prevalence rates of ASPD in various generalpopulations using DSM criteria have rangedfrom 0.2 to 3.3%, with a median of 0.8% and apooled mean prevalence of 1.6% (15). Theprevalence of ASPD in our sample (54/606, or8.9%) was several times that observed in mostcommunities.

Prevalence rates of ASPD have variedwidely in various clinical samples of SUD pa-tients. For example, Craig found a 60% preva-lence of ASPD in 443 inpatient opiate andcocaine abusers, using the Millon ClinicalMultiaxial Inventory-III (33). Most ASPDprevalence rates are half to a fourth of that un-usually high rate (20,21,34), with alcohol abus-ers manifesting less ASPD than illicit drugabusers. Our observed rate of 8.9% was lessthan usually observed in clinical samples ofSUD patients

The low ASPD rate in our study could be duein part to the high percentage of women in thissample (265/606, or 42%), since most studiesshow that men have higher rates of ASPD thanwomen(35).However,menandwomendidnotdiffer significantly in their ASPD rate in ourstudy, so that the men in this study rather thanthe women had the relatively low rateof ASPD.This may be another of the many ways in whichSUD patients differ from the general popula-tion in relation to ASPD.

Another factor in our low ASPD rate couldbe the use of strict DSM-III-R criteria for thisclassification. Many non-ASPD patients in oursample had engaged in adult-onset antisocial

Westermeyer, Thuras, and Carlson 21

TABLE 3. Logistic Regression Analysis. IncreasedRisks Associated with Antisocial Personality Disor-der Among Patients with SUD

Characteristic Exp (B) 95% C.I. for Exp (B) Significance

Relatives withnon-SUD dx.

1.30 1.06-1.30 .011

High score onSCL-Hostility

1.57 1.09-2.25 .014

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behaviors while using substances. In the ab-sence of adolescent Conduct Disorder, theseadult-onset behaviors did not qualify for anASPD diagnosis in our study. Instruments suchas the Millon Inventory used in the Craig study(32)probablyassignASPD“caseness” tomanymore subjects than the DSM-III-R criteria.

A third factor could be the method in whichwe relied on a blinded classification by a sepa-rate research associate. Utilizing only queriesregarding DSM-III-R criteria for ASPD couldhaveledtofalsenegativeASPDassignments.

A fourth factor could be the sample, comingfrom two university programs, both located indepartments of psychiatry. Most patients werereferred and seen as outpatients. The latter re-quired that they come to an appointment, andthat they arrive sober-two factors requiringplanfulness and commitment. Sampling indetoxication facilities, inpatient units, thera-peutic communities, juvenile residential cen-ters, jails, etc., may yield more patients withASPD.

A fifth explanation could be that patientswith APSD minimize or lie about their psychi-atricsymptomsor treatment. Ingeneral, studieson the reliability and validity of self-reportamongsubstanceabusershaveshownhighreli-ability and validity in regard to their substanceuse as well as their associated psychiatric symp-toms (36-39). Nonetheless, these published re-ports have not separately studied reliability andvalidity among patients with ASPD.

Family History

Family members with any non-SUD psychi-atric disorder was higher in the ASPD group, adifference thatwas retainedas significant in thelogistic regressionanalysis.Thespecificmech-anismbywhichapositivefamilyhistoryofpsy-chiatric exerts its effect in this group is uncer-tain. For example, a positive family historymight have its influence through genetic means,environmental means, or some combination ofboth means.

Psychiatric Symptoms, Disorders,and Treatment

Differences in psychiatric phenomena be-tween the ASPD and non-ASPD groups werefew.Nonetheless, the fewobserveddifferences

were informative. For example, ASPD patientshad increasedSCL-Hostilityat the timeofeval-uation (i.e., while sober). On the M-SAPS-Psy-cho-Behavioral Scale, they also reported “Abuseof telephone.” These findings suggest hostilesymptoms among ASPD patients when soberas well as when abusing substances. In addi-tion, SCL-Hostility was retained in the logisticregression as being significantly associatedwith ASPD. This associationof ASPD and hos-tilityinSUDpatients isanewfinding, insofaraswe are aware.

Samples from other studies demonstratingincreasedratesofpsychiatricdisorderoriginatefrom two sources: i.e., substance abuse treat-ment facilities (20,34) and jails and prisons(6,8,40). The relatively high rate of anxiety andmood symptoms in these latter study popula-tionscouldbedue topopulationdifferences,es-pecially between university-based treatmentand other treatment programs as well as incar-ceration for criminal behavior. Incarceration orresidential treatment in these other studies mayalso precipitate anxiety and mood symptoms inthose with ASPD.

Caveats

These findings from two university programsmay not apply to ASPD in other subgroups ofSUD patients. The finding of increased familyhistory of any non-SUD psychiatric disorderwould require replication before it can be ac-cepted as a reliable finding. Our observation ofincreased hostility related to ASPD, while con-sistent with ASPD characteristics, also war-rants replication.

Implications

If replicated, the familial finding has impli-cations regarding the genesis of ASPD in pa-tients with SUD. The finding regarding in-creased hostility among SUD patients withASPD may have implications regarding treat-ment and prognosis.

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