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Review
Personality disorders, violence and antisocial
behaviour: updated systematic review and
meta-regression analysis
Rachel T.S. Chow, Rongqin Yu, John R. Geddes and Seena Fazel
Background
Links between personality disorders and antisocial outcomes
has not examined individual personality disorders, and the con-
tribution of comorbidities remain uncertain. Previous systematic
reviews are dated.
Aims
To synthesise evidence from observational studies on the risk of
antisocial outcomes and recidivism associated with personality
disorders.
Method
We searched six bibliographic databases (up to March 2024) for
observational studies examining the risk of antisocial behaviour,
interpersonal violence and recidivism in individuals diagnosed
with personality disorders, compared to controls. We explored
sources of heterogeneity using subgroup analyses and meta-
regression.
Results
We identified 21 studies involving 83 418 individuals with per-
sonality disorders from 10 countries examining antisocial and
violent outcomes (Aim 1), and 39 studies of 14 131 individuals
from 13 countries with recidivism (or repeat offending) as the
outcome (Aim 2). We found increased risks of violence
among individuals with any personality disorder (odds ratio 4.5,
95% CI 3.0–6.7), particularly antisocial personality disorder (odds
ratio 7.6, 95% CI 5.1–11.5) and borderline personality disorder
(odds ratio 2.6, 95% CI 1.8–3.9). Individuals with any personality
disorder (odds ratio 2.3, 95% CI 2.0–2.6) and antisocial personality
disorder (odds ratio 2.8, 95% CI 1.6–4.9) also demonstrated
an elevated risk of recidivism. Personality disorder types and
comorbid substance use disorder were associated with
between-study heterogeneity.
Conclusions
The assessment and management of personality disorders
should be considered as part of violence prevention strategies.
Improving identification and treatment of comorbid substance
misuse may reduce adverse outcomes in individuals with per-
sonality disorders.
Keywords
Personality disorders; forensic psychiatry; meta-analysis; sys-
tematic review; observational study.
Copyright and usage
© The Author(s), 2024. Published by Cambridge University Press
on behalf of Royal College of Psychiatrists. This is an Open
Access article, distributed under the terms of the Creative
Commons Attribution licence (http://creativecommons.org/
licenses/by/4.0/), which permits unrestricted re-use, distribu-
tion and reproduction, provided the original article is properly
cited.
The global prevalence of personality disorders in community set-
tings is approximately 8%.
1
Personality disorders are associated
with a range of adverse outcomes, including suicidality, substance
misuse and physical and psychiatric comorbidities.
2–4
A previous
meta-analysis of 14 primary studies reported a threefold increased
risk of antisocial behaviour and interpersonal violence perpetration
in individuals with personality disorders compared with the
general population.
5
However, this review included studies
reported up to 2009, and since then many new investigations
have been published.
6,7
Moreover, the previous review reported
high between-study heterogeneity but did not find explanations
for this, apart from higher odds in people with antisocial
personality disorder (ASPD). This was mainly because of the
limited number of primary studies. Notably, the risk of violence
in other personality disorders remained unclear. The link
between individual personality disorders and antisocial
outcomes may vary because of their clinical characteristics and
varying comorbidity patterns. For instance, impulsivity,
a transdiagnostic feature of both ASPD and borderline personality
disorder (BPD), has been associated with physical aggression
and recidivism.
8,9
BPDisalsocommoninforensicmental
health settings, with prevalence estimates ranging from 20% to
30%.
10–12
Other features, such as mood instability, paranoid
ideation, obsessionality and suicidality, occur in individual
personality disorders, and may be associated with specific
outcomes.
Aims of the review
We report an updated systematic review and meta-analysis of
observational studies examining the risks of antisocial behaviour
(Aim 1) and recidivism (Aim 2) in individuals with personality dis-
orders compared to control groups without personality disorders.
This could inform risk assessment and management in different
personality disorders, service provision and identify priorities for
future research.
Method
We conducted this meta-analysis following the Preferred Reporting
Items for Systematic Reviews and Meta-Analyses (PRISMA) guide-
lines (Supplementary Appendix A available at https://doi.org/10.
1192/bjp.2024.226).
13
The review protocol is registered on the
PROSPERO database (CRD42021247237). We identified observa-
tional studies (in published and grey literature) reporting the risk
estimates of antisocial behaviour and recidivism in individuals diag-
nosed with personality disorders released between 1 January 1966
and 14 March 2024. This review adopted the methodology of the
systematic review conducted by authors R.Y., J.R.G. and S.F. for
the period between 1966 and 2009.
5
We conducted an updated lit-
erature search (from 1 January 2009 to 14 March 2024) in databases
including Medline, Embase, PsycInfo, CINAHL, US National
Criminal Justice Reference System (NCJRS) and Web of Science.
The British Journal of Psychiatry (2024)
Page 1 of 11. doi: 10.1192/bjp.2024.226
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We used the same search strategy as the previous systematic review,
which comprised a combination of search terms for personality
disorders (i.e. personality disorder*, personality pathology, axis II,
personality dysfunction, personality abnormality and abnormal
personality) and antisocial behaviour (i.e. viol*, offen*, aggress*,
assault*, antisocial, anti-social, dangerous*, crim*, delinquen*
and unlawful*) and recidivism (i.e. recidi*, reoffend*, repeated
offend*, rearrest, reconvict*, reincarcerat*, revoke* and recur*).
Personality disorders are often investigated concurrently with
other psychiatric disorders for violent outcomes, but information
on personality disorders is often not mentioned in titles and
abstracts in these studies. We therefore included more general
psychiatric disorder-related terms (i.e. mental disorder*, mental
illness* and psychiatric disorder*) to enhance search sensitivity.
Non-English language articles were translated and examined for
eligibility. Reference lists of included papers were scanned to
further identify potentially eligible articles. We corresponded with
authors when clarification and additional data were required. No
informed consent from participants was required for this review
as only secondary data from existing research were collected and
analysed.
Study eligibility
We included studies that met the following criteria: (a) with a
cohort, case–control or cross-sectional design; (b) reporting on
individuals diagnosed with personality disorders, defined according
to validated diagnostic criteria using clinical and/or (semi-)struc-
tured interviews; (c) reporting the risk of antisocial behaviour in
individuals with personality disorders compared to those without
personality disorders in the general population (Aim 1) or the
risk of reoffending/recidivism in individuals with a history of
criminal behaviour with personality disorders compared to
individuals with a history of criminal behaviour but without person-
ality disorders (Aim 2); and (d) reporting the risk of antisocial
behaviour and/or reoffending in terms of study-level quantitative
data, which allows the calculation of odds ratios. Studies that
reported a specific type of antisocial behaviour (e.g. intimate
partner violence, sexual assault) and provided no appropriate
comparison data were excluded. One of the authors (R.T.S.C.) con-
ducted the initial screening, identified full texts and selected studies
for inclusion. In addition, an independent reviewer, Phoebe Homer,
independently selected studies for inclusion from a randomly
sampled 20% of the identified full texts. Any discrepancies
between R.T.S.C. and P.H. were discussed with a third author
(R.Y. or S.F.) until consensus was achieved. One study was excluded
as the study sample was limited to individuals with available data on
functional impairment, rather than violent outcomes.
14
When
multiple papers on the same dataset were retrieved, we included
the paper reporting the most complete dataset to avoid duplicated
samples. In this meta-analysis, we excluded two studies with over-
lapping samples.
7,15
Data extraction
Data extraction began on 15 February 2022. Using a standardised
extraction form, data and information on the following study char-
acteristics were independently recorded by R.T.S.C. and P.H. for
each study: publication year, study period, country, design,
sample size, diagnostic criteria for personality disorder diagnosis,
personality disorder diagnosis, method of outcome ascertainment,
adjusted variables and participants’demographic information (age
and gender). Odds ratios with 95% confidence intervals were
extracted or calculated from the number of participants with
or without personality disorder cross-classified by antisocial or
reoffending outcomes, either by direct extraction if reported or by
derivation from summary statistics and prevalence data. Risk
estimates with and without adjustments were extracted if both
were reported. We corresponded with primary study authors to
resolve uncertainties about extracted data. For interrater reliability
in effect sizes, Spearman’s correlation coefficient was 0.999, indicat-
ing almost perfect agreement between data extractors. There were
only four disagreements in the extracted raw data for effect size
and 95% confidence interval calculations, which were discussed
between extractors and consensus reached.
Data analysis
We conducted meta-analyses on extracted odds ratios and corre-
sponding 95% confidence intervals. Fixed-effects models were
used when heterogeneity was considered low to moderate, as indi-
cated by the I
2
statistic (see below for details). Random-effects
models, which assumes variance in the effect estimates between
the included studies given their varying sizes, designs and sample
characteristics, were used when heterogeneity was high. Random-
effects models account for the high overall between-study
heterogeneity by assigning similar weights to each study in the
meta-analysis, while fixed-effects models assign more weights to
larger studies assuming all studies have identical true effect
sizes.
16
When both adjusted and unadjusted risk estimates were
reported for a single association, the adjusted one was used for
the main meta-analysis. We performed sensitivity analyses on
studies examining any criminality (including violence) as an
outcome.
Heterogeneity was assessed using the I
2
statistic, which esti-
mates the observed dispersion attributable to variation rather than
chance across the pooled studies in a meta-analysis. The I
2
statistic
is expressed as a percentage, with the following recommended
thresholds: low (0–40%), moderate (30–60%), substantial
(50–90%) and considerable (75–100%).
17
We explored sources of
heterogeneity using subgroup and meta-regression analyses on a
series of pre-determined study characteristics, including publication
year, geographical region, study design, adjustment, comparison
group, diagnosis, diagnostic criteria, average age, sample size, and
ascertainment of outcomes. Subgroup analyses were carried out
using non-overlapping data. In meta-regression, categorical inde-
pendent variables were entered individually and then in multivari-
able models. To measure the incidence of violence, antisocial
behaviour and recidivism attributable to personality disorders, we
calculated the population attributable risk fraction by dividing the
difference between the base rate r(i.e. the number of individuals
involved in criminal behaviour per 1000 individuals with personal-
ity disorders) and r
0
(i.e. the number of individuals involved in
criminal behaviour per 1000 controls without personality disorders)
by the rate among individuals with personality disorders (r). We
investigated publication bias using Egger’s test (i.e. weighted regres-
sion method).
18
We also performed leave-one-out sensitivity ana-
lyses to assess the influence of outliers on the overall risk
estimates. All statistical analyses were conducted on STATA-MP,
version 17.0 for MacOS, using the metan,metareg,metabias and
metainf commands.
Quality assessments
The risk of bias and methodological quality of each included study
was assessed independently by two researchers (R.T.S.C. and inde-
pendent reviewer Phoebe Homer) using the Newcastle–Ottawa
scale (NOS).
19
Interrater reliability was calculated with a two-way
random-effects intraclass correlation coefficient,
20
which was 0.86,
indicating excellent agreement.
21
Study quality was assessed in
terms of sample selection, comparability between individuals with
and without personality disorders, ascertainment of antisocial
Chow et al
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behaviour and recidivism outcomes and the rigour of statistical ana-
lyses. For studies with a case–control or cohort design, the
maximum score was 9. For cross-sectional studies, we used an
adapted version of the NOS,
22
with a potential total score ranging
from 0 to 8.
Results
The updated systematic search yielded 9662 unique records, of
which we screened 369 full-text articles for eligibility (Fig. 1). We
identified 60 publications that reported on 71 separate relevant out-
comes. The updated search included 28 new studies (with 32
reported outcomes) while the previous review included 32 studies
(with 39 reported outcomes). Among the included cohort and
case–control studies, 14 were considered high quality (scoring ≥7
on the NOS) while the remaining studies scored 6 or lower (n=29).
The median scores for cohort studies and case–control studies were
both 6 (mean 6.1; interquartile range [IQR] 5–7 for cohort studies,
mean 6; IQR 6 for case–control studies). Most cross-sectional
studies scored 6 or lower, with a median score of 5 (mean 4.7; IQR
3–6).
Study 1: risk of violence in personality disorder
There were 16 studies reporting outcomes on the links between per-
sonality disorders and violence in 76 647 individuals diagnosed with
personality disorders (Supplementary Appendix Table B.1).
6,23–37
Of individuals diagnosed with personality disorders, 7186 (9.4%)
exhibited violent behaviour. These cases were compared with
6 441 949 individuals in the general population, of whom 127 191
(2.0%) perpetrated some form of violence.
Eligible studies provided data on all personality disorders
(k= 6),
24,29–33
ASPD (k=7)
6,23,25,28,34,35,37
and BPD (k= 3).
26,27,36
One study also reported risk estimates in other personality dis-
orders.
6
Studies were from nine countries: three each from
Denmark, the USA and the UK, two from Sweden and one each
from Canada, China, Finland, Israel and the Netherlands. Three
studies reported both antisocial behaviour and violent
outcomes.
25,28,36
Any personality disorders
There was an association between personality disorders and
increased risk of violence (random-effects odds ratio 5.4, 95% CI
3.5–8.2) with considerable heterogeneity between studies
(x2
8¼450, I
2
= 98%, P< 0.001). The odds ratios ranged from 2.4
to 17.2. Leave-one-out sensitivity analyses revealed that the most
influential outlier was Mok (2023F) with odds ratio 17.2 (95% CI
14.9–19.9).
30
After exclusion, the increased risk of violence in per-
sonality disorders remained significant (odds ratio 4.5, 95% CI
3.0–6.7) with considerable heterogeneity (x2
7¼291, I
2
= 98%,
P< 0.001) (Fig. 2). When excluding low-quality studies, the odds
ratio was 4.3 (95% CI 2.8–6.6). Although there were differences in
the reported risk of violence between studies that included ASPD
(or did not report the ASPD proportion; odds ratio 4.9, 95% CI
Records identified from database
searching
(Medline, Embase, PsycINFO, Web of
Science, and CINAHL)
(January 2009 – 14 March 2024)
(n = 18379)
Duplicate records removed before
screening
(n = 8717)
Records identified from database
searching (US NCJRS)
(January 2009 – 14 March 2024):
(n = 870)
Records with their title and
abstract screened
(n = 870)
Reports
excluded
(n = 16), with
reasons:
Inappropriate
design
(n = 2)
Inappropriate
comparison
group
(n = 2)
Different
outcome
(n = 2)
Wrong
exposure
(n = 10)
Full-text articles assessed for
eligibility
(n = 17)
Eligible articles
(n = 1)
Reports excluded (n = 342),
with reasons:
Inappropriate study design
(n = 53)
Inappropriate comparison group
(n = 21)
Different outcome
(n = 68)
Selected population
(n = 30)
Unable to extract data for
odds ratio calculation
(n = 27)
Did not use standardised diagnostic
criteria to ascertain
personality disorder diagnosis
(n = 11)
Wrong exposure
(n = 127)
Restricted to a single type of
criminality
(n = 1)
With duplicated data from included
studies
(n = 2)
Overlapped samples
(n = 2)
Total publications included
in the investigation
on recidivism (Study 2)
(n = 39)
Total publications included in the
investigation on antisocial
behaviour and violence
(Study 1)
(n = 21)
Records included in
previous version of review
(1966 – 2009)
(n = 32)
Total publications included in
review
(n = 60)
New publications included in
review
(n = 28)
Studies identified from
other sources
(n = 1)
Full-text articles not retrieved
(n = 1)
Records excluded during title
and abstract screening
(n = 5686) Records with their title and
abstract screened
(n = 9662)
Full-text articles assessed for
eligibility
(n = 369)
Fig. 1 Flowchart outlining the search strategy.
NCJRS, National Criminal Justice Reference System.
Personality disorders, violence and antisocial behaviour
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https://doi.org/10.1192/bjp.2024.226 Published online by Cambridge University Press
3.2–7.6) versus those investigations where ASPD was excluded
(odds ratio 2.6, 95% CI 1.7–4.0), the latter risk estimate was signifi-
cant. In addition, where ASPD proportions were small (three studies
with 6.2%, 6.4% and 20.0%), there was increased violence risk (odds
ratio ranged from 2.8 to 6.2).
Antisocial personality disorder
There was an increased risk of violence (odds ratio 7.6, 95% CI
5.1–11.5) associated with individuals diagnosed with ASPD com-
pared to general population controls, with considerable between-
study heterogeneity (x2
9¼83, I
2
= 90%, P< 0.001) (Fig. 3). Odds
ratios ranged widely from 2.5 to 32.8. There was no significant
difference between ASPD and all personality disorder samples in
their associated risk of violence. The population attributable risk
of violence associated with ASPD was 2 per 1000 individuals, with
13.0% of violent incidents attributable to ASPD.
Borderline personality disorder
There was an association between BPD and violence (odds ratio 2.6,
95% CI 1.8 to 3.9) with substantial heterogeneity (x2
3¼34, I
2
= 94%,
P≤0.001) with odds ratios ranging from 1.5 to 3.9 among the three
included studies. The risk of violence associated with BPD was
significantly lower than that in ASPD. The population attributable
risk for violence is 1 per 1000 individuals diagnosed with BPD,
with a population attributable risk fraction of 3.0%.
Other personality disorders
Among samples with both genders combined, from one study,
6
there was association with violence in paranoid personality disorder
(odds ratio 1.6, 95% CI 1.1–2.3). However, associations between
violence and narcissistic personality disorder (odds ratio 2.6, 95%
CI 1.0–6.8), histrionic personality disorder (odds ratio 1.7, 95% CI
0.8–3.9), schizoid personality disorder (odds ratio 1.3, 95%
CI 1.0–1.7) and obsessive–compulsive personality disorder (odds
ratio 1.3, 95% CI 0.9–1.8) were increased but did not reach statistical
significance. In contrast, there were no clear associations between
violent outcomes and avoidant personality disorder (odds ratio
0.8, 95% CI 0.5–1.2), dependent personality disorder (odds ratio
0.8, 95% CI 0.4–1.6) or schizotypal personality disorder
(odds ratio 0.8, 95% CI 0.5–1.3).
Overall (I2 = 98%, P = 0.000)
Mok et al, M (2023)
Sariaslan et al (2020)
Coid et al, M (2006)
Coid et al, F (2006)
Monahan and Appelbaum (2000)
Johnson et al (2000)
Ortmann (1981)
Study (year)
4.5 (3.0, 6.7)
11.5 (10.5, 12.5)
6.2 (5.9, 6.4)
2.8 (2.4, 3.4)
3.6 (2.7, 4.9)
6.9 (2.3, 20.5)
2.6 (1.7, 4.0)
2.4 (1.0, 5.4)
Odds ratio
(95% CI)
100.00
17.29
17.38
16.87
15.97
7.83
14.46
10.20
%
Weight
0.5 1 2 4 8 16 32
Fig. 2 Risk estimate for violence in individuals diagnosed with all personality disorders compared to the general population.
24,29–33
F, female sample; M, male sample.
Overall (I2 = 90%, P = 0.000)
Cao et al (2022)
Coid et al, M (2017)
Coid et al, F (2017)
ten Have et al (2014)
Elonheimo et al (2007)
Stueve and Link (1997)
Hodgins et al, M (1996)
Hodgins et al, F (1996)
Swanson et al (1994)
Study (year)
7.6 (5.1, 11.5)
5.0 (3.7, 6.8)
2.5 (1.7, 3.9)
4.8 (2.1, 10.5)
2.5 (0.9, 7.0)
8.4 (5.0, 14.2)
13.9 (7.7, 25.0)
7.9 (7.0, 9.0)
13.1 (9.4, 18.3)
32.8 (19.3, 55.7)
Odds ratio
(95% CI)
100.00
12.69
11.91
9.04
7.49
11.15
10.64
13.46
12.51
11.11
%
Weight
0.5 1 2 4 8
16
32
Fig. 3 Risk estimate for violence in individuals diagnosed with antisocial personality disorder compared to the general population.
6,23,25,28,34,35,37
F, female sample; M, male sample.
Chow et al
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Gender
There was no significant difference by gender in the risk of violence
associated with any personality disorder (women: odds ratio 3.6,
95% CI 2.7–4.9; men: odds ratio 4.8, 95% CI 1.8–13.2) and ASPD
(women: odds ratio 8.5, 95% CI 3.2–22.7; men: odds ratio 5.4,
95% CI 3.3–8.9).
Comorbidity with substance misuse
Among individuals with any personality disorder, the prevalence of
substance use disorder (SUD) was 28.3% in men and 10.3% in
women.
30
In ASPD samples, the prevalence of substance misuse
(i.e. alcohol misuse and drug use) ranged from 10.4% to 19.7%.
23
The prevalence of substance misuse ranged from 7.2% to 46.1% in
BPD samples.
26,36
ASPD studies that adjusted for SUDs reported
significantly smaller effect sizes for violence than studies without
adjustment (odds ratio, 3.9 [2.3, 6.4] v. 10.8 [6.8, 17.3]) (Fig. 4).
One study provided data for the calculation of violence risk
associated with any personality disorder with and without comorbid
SUDs.
30
The risk of violence associated with personality
disorder–SUD comorbidity (odds ratio 29.9, 95% CI 13.2–68.0)
was higher than personality disorder without SUD comorbidity
(odds ratio 14.0, 95% CI 9.4–20.8) but confidence intervals over-
lapped owing to the small sample size.
Other characteristics
For studies investigating links with any personality disorder, we
found differences in violence risk by study design: cohort studies
reported significantly larger effect sizes than case–control studies
and cross-sectional investigations (Table 1). No significant differ-
ence was found for ASPD studies. Subgroup analyses on BPD
were not possible due to the limited number of primary studies.
Meta-regression and publication bias
Meta-regression analyses found no study characteristic to be signifi-
cantly associated with heterogeneity. Egger’s test found no clear
evidence of publication bias in studies reporting violent outcomes
in all personality disorders (t=−0.90, P= 0.84), ASPD (t=−0.18,
P= 0.93) and BPD (t=−5.39, P= 0.15).
Sensitivity analysis: any criminality
When investigating any antisocial behaviour (including violence) as
the outcome, we found an increased risk in individuals diagnosed
with any personality disorder, ASPD and BPD compared to
general population controls, while an equivocal association was
found in schizotypal personality disorder (Supplementary
Appendix Table C.1; Appendix Figs C.1 and 2).
25,28,36,38–42
There
was moderate between-study heterogeneity in any personality dis-
order and considerable heterogeneity in ASPD and BPD studies.
In studies examining all personality disorders, studies with less
than 100 personality disorder cases reported significant higher risk
estimates than studies reporting over 1000 personality disorder
cases (Supplementary Appendix Table C.2). No subgroup analysis
was performed on individual personality disorder samples owing
to an insufficient number of primary studies (k< 5). Egger’stest
found no significant evidence of publication bias in studies reporting
any antisocial behaviour (including violence) associated with all per-
sonality disorders (t=1.01,P= 0.39) and ASPD (t=−1.02, P= 0.42).
Study 2: risk of repeat offending (recidivism) in
personality disorders
We identified 39 studies reporting recidivism data on 14 131 indivi-
duals with a history of criminal behaviour diagnosed with at least one
personality disorder (Supplementary Appendix Table B.2).
8,43–80
Eighteen additional studies were included in this
update.
8,45–47,49–51,54,57,59–61,63,66,67,72,73,80
Of individuals with a
history of criminal behaviour who had personality disorders, 6420
(45.4%) reoffended. These individuals were compared with 155 925
individuals with a history of criminal behaviour with or without psy-
chiatric disorders, among whom 61 282 (39.3%) reoffended. The dur-
ation of follow-up reported by included studies ranged from 7
months to 22 years. Studies were from 13 countries: Canada (n=
7), the USA (n= 8), the UK (n= 5), Australia (n= 3), Sweden (n=
5), two each from Brazil, Germany and Italy and one each from
Uganda, Korea, France, Japan and Spain. All but two investigations
ascertained recidivism from register-based sources. The remaining
studies used self-report measures.
51,60
Random-effects meta-analysis indicated the overall odds ratio
for repeat offending associated with any personality disorder to be
%
Weight
0.51248
16
32
Subgroup (I2 = 88%, P = 0.000)
ten Have et al (2014)
Elonheimo et al (2007)
Stueve and Link (1997)
Hodgins et al, M (1996)
Hodgins et al, F (1996)
Swanson et al (1994)
Studies without adjustment for
substance misuse
Subgroup (I2 = 71%, P = 0.030)
Cao et al (2022)
Coid et al, M (2017)
Coid et al, F (2017)
Studies adjusted for substance misuse
Study (year)
10.8 (6.8, 17.3)
2.5 (0.9, 7.0)
8.4 (5.0, 14.2)
13.9 (7.7, 25.0)
7.9 (7.0, 9.0)
13.1 (9.4, 18.3)
32.8 (19.3, 55.7)
3.9 (2.3, 6.4)
5.0 (3.7, 6.8)
2.5 (1.7, 3.9)
4.8 (2.1, 10.5)
Odds ratio
(95% CI)
100.00
10.64
16.73
15.84
20.94
19.17
16.67
100.00
41.61
36.37
22.02
Fig. 4 Risk estimates for violence in antisocial personality disorder with and without adjustment on substance use disorder.
6,23,25,28,34,37
Personality disorders, violence and antisocial behaviour
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2.3 (95% CI 2.0–2.6), with considerable heterogeneity between
studies (x2
44 ¼189, I
2
= 77%, P≤0.001) (Fig. 5). The odds ratio
was similar when low-quality studies were excluded (odds ratio
2.3, 95% CI 2.0–2.6).
Antisocial personality disorder
There was a significant association between ASPD and recidivism
(odds ratio 2.8, 95% CI 1.6–4.9), with moderate heterogeneity
(x2
10 ¼28, I
2
= 68%, P= 0.001) (Fig. 5). The odds ratio for recidiv-
ism associated with ASPD was higher when low-quality studies
were excluded (odds ratio 3.2, 95% CI 2.1–5.1). There was no signifi-
cant difference in odds ratios in studies including individuals with
ASPD compared with studies including individuals with any or
other personality disorder. The population attributable risk of recid-
ivism associated with ASPD was 54 per 1000 individuals, with 18.0%
of reoffending incidents attributable to ASPD.
Violent versus general recidivism
There was no significant difference in risk estimates by the type of
recidivism in all personality disorders (general recidivism: odds
ratio 2.3, 95% CI 1.9–2.6; violent recidivism: odds ratio 2.5, 95%
CI 2.0–3.2) and ASPD studies (general recidivism: odds ratio 2.8,
95% CI 1.6–4.9; violent recidivism: odds ratio 3.1, 95% CI 1.3–7.6).
Risk estimate by comparison groups
Most included studies (n= 33) compared recidivism risk in indivi-
duals with personality disorders with a history of criminal behav-
iour with recidivism risk in those with a history of criminal
behaviour who had other psychiatric disorders. Four studies
included individuals with a history of criminal behaviour without
psychiatric disorders as the comparison group.
8,53,66,68
One study
included individuals without personality disorders (i.e. individuals
with and without psychiatric disorders) in the comparison
group.
63
Five studies reported separate effect sizes respective to
control groups with and without other psychiatric disor-
ders.
46,49,60,75,80
We found no significant difference in risk estimates
from all personality disorder studies including individuals with
other psychiatric disorders as a comparison group (odds ratio 2.3,
95% CI 2.1–2.7) versus individuals without other psychiatric disor-
ders as comparison group (odds ratio 3.0, 95% CI 2.3–3.9). There
was also no significant difference inrecidivism risk estimates by com-
parison groups in ASPD samples: the odds ratio was 2.4 (95% CI
1.3–4.2) for studies using no psychiatric disorders as comparison
group versus an odds ratio of 3.1 (95% CI 0.6–15.7) when other psy-
chiatric disorders was the comparison group.
Other characteristics
In all personality disorders, cohort studies (odds ratio 2.4, 95% CI
2.1–2.7) (k=35) and studies that ascertained recidivism outcomes
using registers reported significantly higher risk estimates
(odds ratio 2.3, 95% CI 2.0–2.6) (k=43) than case–control studies
(odds ratio 1.3, 95% CI 0.9–1.8) (k=4) and studies using self-
report measures (odds ratio 0.8, 95% CI 0.4–1.6) (k= 2). A similar
pattern was found in ASPD samples (odds ratio, 3.8 [2.4, 6.2] v.
0.8 [0.4–1.6]). There was no significant difference in risk estimates
by other study characteristics.
Meta-regression and publication bias
For all personality disorders, there were higher odds ratios in studies
conducted in countries other than the USA and Scandinavian coun-
tries (β= 1.24, SE[β] = 0.12; P= 0.024) when variables were entered
Table 1 Risk estimates for violence in any personality disorder by study characteristics
Sample or study characteristics
Number of
studies
Number with personality disorder
(violent cases with personality disorder)
Random-effects odds ratio
(95% CI)
Study period (k=7)
Studies conducted before 1998 1 135 (6) 2.4 (1.0–5.4)
Studies conducted in and after 1998 6 35 576 (348 4) 4.8 (3.1–7.4)
Study region (k=7)
USA 2 123 (44) 3.7 (1.5–9.3)
Scandinavia 3 33 116 (298 4) 6.5 (3.7–11.2)
The rest of the world 2 2472 (462) 3.1 (2.5–3.9)
Design (k=7)
Case–control 2 238 (45) 2.5 (1.7–3.8)
Cohort 3 33 001 (298 3) 8.1 (4.7–14.2)
Cross-sectional 2 2472 (462) 3.1 (2.5–3.9)
Adjustment by sociodemographic and/or clinical variables (k=7)
With adjustment 2 2472 (462) 3.1 (2.5–3.9)
Without adjus tment 5 33 239 (302 8) 5.3 (3.4–8.4)
Adjustment by SUDs (k=7)
With adjustment 2 2472 (462) 3.1 (2.5–3.9)
Without adjus tment 5 33 239 (302 8) 5.3 (3.4–8.4)
Comparison group (k=7)
General population 4 3526 (718) 4.7 (1.7–13.1)
General population without psychiatric disorders 3 32 185 (277 2) 4.0 (2.3–7.1)
Number of cases (k=7)
<1000 cases 3 258 (50) 3.0 (1.8–4.9)
>1000 cases 4 35 453 (3440) 5.3 (3.2–8.6)
Diagnostic criteria (k=7)
DSM criteria 4 2595 (506) 3.1 (2.5–3.8)
ICD criteria 3 33 116 (298 4) 6.5 (3.7–11.2)
Data source (k=7)
Register 3 33 116 (298 4) 6.5 (3.7–11.2)
Self-report 2 2472 (462) 3.1 (2.5–3.9)
Combination of registry and self-report sources 2 123 (44) 3.7 (1.5–9.3)
SUD, substance use disorder.
Chow et al
6
https://doi.org/10.1192/bjp.2024.226 Published online by Cambridge University Press
individually. However, these effects were no longer significant in
multivariable regression. In ASPD, a similar pattern was found
with higher odds ratios in registry data studies (univariable meta-
regression: β= 0.21, SE[β] = 0.11; P= 0.018; multivariable meta-
regression: β= 0.09, SE[β] = 0.05; P= 0.009). Egger’s test found
evidence of publication bias in studies on all personality disorders
(including ASPD) (t= 2.40, P= 0.02), but not among ASPD
studies (t= 0.63, P= 0.54).
Discussion
We assessed the link between personality disorders and the risk of
violence, antisocial behaviour and recidivism in updated systematic
reviews and meta-analyses. The first review included data from
83 418 individuals diagnosed with personality disorders from 21
studies in 10 countries, nearly doubling the number of primary
%
Weight
Overall (I2 = 77%, P = 0.000)
Heterogeneity between groups: P = 0.388
Subgroup (I2 = 68%, P = 0.001)
Martin et al (2019)
Forry et al (2019)
Shepherd et al (2018)
Lim et al (2018)
Vitacco et al (2008)
Monson et al (2001)
Porporino and Motiuk (1995)
Russo (1994)
Bailey and Macculloch (1992)
Martin et al (1978)
Antisocial personality disorder
Subgroup (I2 = 78%, P = 0.000)
Cohen et al (2024)
Capuzzi et al (2024)
Yukhneko et al, M (2023)
Yukhneko et al, F (2023)
Okamura et al (2023)
Ogilvie et al (2023)
Mitchell et al (2023)
Klausing and Seifert (2023)
Forget et al (2022)
Seto et al (2018)
Krona et al (2017)
Chang et al, M (2015)
Chang et al, F (2015)
Dias et al (2014)
Lund et al (2012)
Gray et al (2011)
Grann et al (2008)
Coid et al, M (2007)
Coid et al, F (2007)
Stadtland and Nedopil (2005)
Bertman-Pate et al (2004)
Moscatello (2001)
Singleton et al, M (1998)
Singleton et al, F (1998)
Ventura et al (1998)
Harris and Koepsell (1996)
Harris et al (1993)
Komer and Galbraith (1992)
Rice et al (1990b)
Rice et al (1990a)
Yesavage et al (1986)
Tennent and Way (1984)
Quinsey et al (1975)
Ganzer and Sarason, M (1973)
Ganzer and Sarason, F (1973)
All personality disorders
Personality disorder
category and study (year)
2.3 (2.0, 2.6)
2.8 (1.6, 4.9)
9.1 (3.7, 22.4)
0.8 (0.4, 1.8)
5.3 (2.1, 13.2)
0.8 (0.2, 2.6)
2.0 (1.0, 4.0)
1.8 (0.8, 3.8)
3.1 (0.3, 31.3)
3.0 (1.0, 8.7)
6.0 (2.4, 14.8)
8.3 (1.7, 39.9)
2.2 (1.9, 2.5)
1.0 (0.7, 1.5)
1.8 (1.0, 3.2)
1.6 (1.5, 1.7)
1.5 (1.3, 1.7)
0.8 (0.2, 4.0)
3.3 (2.6, 4.1)
1.3 (1.0, 1.7)
5.4 (3.2, 8.9)
1.8 (0.4, 8.2)
3.0 (1.8, 5.0)
3.4 (1.5, 7.8)
2.2 (2.0, 2.4)
2.4 (1.8, 3.2)
3.0 (1.9, 4.6)
2.6 (1.3, 5.3)
1.9 (1.3, 2.8)
1.9 (1.3, 2.8)
2.5 (1.7, 3.8)
2.6 (0.7, 10.3)
1.5 (0.6, 3.5)
2.0 (0.8, 4.6)
2.9 (1.1, 7.6)
3.2 (2.3, 4.4)
3.3 (2.2, 5.0)
1.4 (0.8, 2.6)
4.5 (0.5, 45.9)
3.1 (2.2, 4.5)
9.3 (1.0, 90.9)
1.5 (0.9, 2.7)
3.2 (1.7, 6.2)
1.6 (1.1, 2.4)
2.4 (1.6, 3.4)
4.3 (1.7, 10.6)
1.2 (0.5, 2.9)
2.3 (1.0, 5.3)
Odds ratio
(95% CI)
100.00
12.09
1.37
1.63
1.34
0.86
1.86
1.76
0.28
1.06
1.37
0.56
87.91
3.08
2.40
4.69
4.59
0.52
4.10
4.08
2.68
0.62
2.66
1.52
4.67
3.84
3.03
1.88
3.26
3.30
3.21
0.73
1.44
1.46
1.24
3.69
3.23
2.37
0.28
3.46
0.29
2.47
2.06
3.23
3.40
1.38
1.48
1.57
0.5 1 2 4 8 16 32
Fig. 5 Risk estimates for recidivism in personality disorder-diagnosed individuals with a history of criminal behaviour compared with
individuals with a history of criminal behaviour with or without other psychiatric disorders.
8,43–80
Personality disorders, violence and antisocial behaviour
7
https://doi.org/10.1192/bjp.2024.226 Published online by Cambridge University Press
studies compared with a previous systematic review.
5
Unlike the
2012 review, this update allowed us to stratify by individual person-
ality disorder and provide more precision on risk estimates. We
found a four- to five-fold increase in the odds of violence among
individuals diagnosed with any personality disorder compared to
general population controls. In ASPD, we found a seven-fold
increase in the odds of violence. Overall, the violence risk associated
with any personality disorder is similar to that associated with
severe mental illness, while individuals with ASPD showed similar
violence risk to individuals with substance misuse.
81
In the second
systematic review, we explored the risk of recidivism in 14 131 indi-
viduals diagnosed with personality disorders compared with indivi-
duals without personality disorders. In 39 studies, we found that
individuals with personality disorders had a two to three times
increased odds of reoffending compared with those without person-
ality disorders. We also found that recidivism risk in ASPD was
similar to any personality disorder, although the risk magnitude
for any personality disorder may be partly driven by ASPD.
BPD was found to double the odds of violence compared to the
general population. While some studies attributed the risk of vio-
lence and aggression associated with BPD to comorbidity with
ASPD,
6,82
BPD appears to be associated with an increased risk of
violence independently, as most included studies controlled for
ASPD.
26,27
This is consistent with other work demonstrating a
link between BPD and violence.
83,84
One mechanism that explains
this link is emotional dysregulation.
85
The distinct risk estimates
associated with BPD and ASPD may be explained by their specific
internalising traits. Violence perpetrators with BPD were found to
be more involved in reactive aggression, whereas individuals with
ASPD engage in more instrumental and goal-directed aggression.
86
However, how and to what extent these traits moderate the extent of
violence risk is unclear. Given the conventional categorical classifi-
cations used for the diagnosis of ASPD and BPD, disentangling the
overlapping traits (i.e. instability, impulsivity and emotional dysre-
gulation) underlying their differential risk profiles remains challen-
ging.
87
Furthermore, DSM and ICD include violent behaviour (e.g.
repeated physical fights) and unlawful acts (e.g. behaviours that are
grounds for arrest or conflict with society) as indicators of ASPD,
which likely contributed to the higher odds ratios found in ASPD
studies.
88–90
Thus, risk estimates for the link between all personality
disorders and violence may be increased because of the contribution
of studies where they sampled ASPD (and BPD, where impulsive
behaviours are part of diagnostic criteria). We found some evidence
for this –personality disorder samples that included those
with ASPD had higher risk estimates. However, the analysis inves-
tigating personality disorder samples without ASPD showed
increased violence risk. Consistent with this, studies with a low pro-
portion of individuals with ASPD also showed increased risk. These
findings suggest that the association between personality disorders
and violence cannot be explained solely by the presence of ASPD
in personality disorder samples. The lack of research on other indi-
vidual personality disorders and violence, as well as the lack of lon-
gitudinal studies in the field, should be considered in interpreting
the findings. We also found paranoid personality disorder to be
associated with a one- to two-fold risk of violence, although data
was available from just one study.
6
Most included studies were of moderate and high quality, and
sensitivity analyses found that excluding low-quality studies had
only a small impact on the results. The majority of cohort studies
on recidivism did not explicitly demonstrate whether previous reof-
fending was accounted for or absent at the start of follow-up, result-
ing in lower-quality scores.
Substance misuse is reported to be the strongest risk factor
for violence across major psychiatric diagnostic categories.
81
However, in the current review focusing on violence outcomes,
only five out of the 16 included studies adjusted for substance
misuse. Our analyses also found that SUD comorbidity increased
the risk of violence in ASPD. Further research should compare vio-
lence and recidivism risks associated with ASPD and SUD to clarify
their relative contributions, and further work should account for
substance misuse. Moreover, in the three studies that examined
BPD, the comparison group may have included personality disor-
ders other than ASPD and BPD, which may have contributed to
non-significant associations.
26,27,36
Limitations
Several limitations should be noted. First, the overall risk estimates
should be interpreted with caution given the significant heterogen-
eity, particularly for violent outcomes. Second, most included
studies on antisocial behaviour and violence relied on self-report
measures from cross-sectional surveys with small and selected clin-
ical samples. Compared to studies relying on registry data, the lower
risk estimates for recidivism in ASPD reported in studies using self-
report measures may reflect potential social desirability bias. The
role of deceit, as one of the core symptoms of ASPD, may be relevant
in the underreporting of criminality outcomes in the personality
disorder group relative to controls.
89,91,92
Third, publication bias
in recidivism studies may be attributed to the small samples in
some studies. Fourth, most included studies on violent outcomes
used case–control or cross-sectional designs, which assessed per-
sonality disorder diagnosis and violent behaviour in participants
simultaneously or retrospectively, and so the temporal order is
uncertain. Furthermore, perpetration of violence is one criterion
for ASPD diagnosis, which will complicate the findings as reverse
causality is a possibility. We were unable to examine non-violent
outcomes in ASPD to test for consistency in increased
associations. Of the six cohort studies on violence,
30,31,33,36,37,41
only three had a prospective design.
31,36,37
The consistency of find-
ings across different designs suggests that there are clear associa-
tions between personality disorders and violent outcomes,
although causal inference will need triangulation of evidence with
other designs (including treatment randomised controlled trials
[RCTs]). Fifth, epidemiologic studies have reported narcissistic
and obsessive–compulsive personality disorders to be the most
prevalent personality disorders in the community setting,
93
but
we found a small amount of research on associations with violence.
Finally, included studies were predominantly conducted in high-
income countries.
Implications
This review suggests that preventing violent and antisocial out-
comes in people with personality disorders, particularly those
with clinically significant borderline and antisocial traits, should
be considered as part of routine clinical care. The risks are increased
for all personality disorders, for the outcomes investigated (violence,
antisocial behaviour and repeat offending) and the magnitude of
the risk increases were not small. Prevention will be improved
with better prediction and more evidence-based treatments, and
potentially by managing substance misuse comorbidity. Predicting
higher risk persons will allow for targeting of limited clinical
resources, and provide for personalised management. Considering
the wider move in the field towards focusing on traits and dimen-
sions, treatments for violence and offending in personality disorders
could include managing disinhibition (such as to being provoked or
its perception), violent behaviour that is based on inflated sense of
entitlement and consequences of emotion dysregulation (such as
not thinking through the consequences of one’s actions).
87,94
Recommended treatments are currently psychological, although
these do not have clear effectiveness for ASPD. England’s
Chow et al
8
https://doi.org/10.1192/bjp.2024.226 Published online by Cambridge University Press
National Institute for Health and Care Excellence (NICE) recom-
mends group-based cognitive–behavioural therapy (CBT) and dia-
lectical behaviour therapy for the management of antisocial
behaviour and offending in ASPD and BPD.
95,96
However, evidence
on the efficacy in reducing aggressive behaviour and reconviction
among individuals with personality disorders is inconclusive.
97–99
Moreover, whether CBT-based interventions reduce reoffending
in prisoners is unclear.
100
As with personality disorders, dysfunc-
tional inhibition and affective control mediate violent and aggres-
sive behaviour in SUD.
101
The success of psychosocial treatments
addressing these traits (e.g. with a community-oriented group inter-
vention) in reducing aggression and crime associated with SUD sug-
gests their potential to reduce violence in personality disorders with
comorbid substance misuse.
102
There may also be a role of medica-
tion in preventing adverse outcomes: a large population-based study
using within-individual designs to better account for confounding
has shown a large association between antipsychotic prescription
and lower rates of violent crime, which will need triangulation
with trials.
103
The role of beta-blockers and medications used for
SUD needs further exploration in trials.
104,105
In summary, links between personality disorders and increased
risks of antisocial behaviour were consistent across outcomes, time
periods and settings. Risks varied by individual personality disorder,
with the highest observed in those with ASPD and with comorbid
substance misuse. Improving identification and treatment for sub-
stance misuse could potentially reduce antisocial and violent out-
comes in individuals with personality disorders.
Rachel T.S. Chow, Department of Psychiatry, University of Oxford, Warneford Hospital,
Oxford, UK; Rongqin Yu , Department of Psychiatry, University of Oxford, Warneford
Hospital, Oxford, UK; John R. Geddes, Department of Psychiatry, University of Oxford,
Warneford Hospital, Oxford, UK; and NIHR Oxford Health Biomedical Research Centre,
Warneford Hospital, Oxford, UK; Seena Fazel , Department of Psychiatry, University of
Oxford, Warneford Hospital, Oxford, UK; Oxford Health NHS Foundation Trust, Warneford
Hospital, Oxford, UK; and NIHR Oxford Health Biomedical Research Centre, Warneford
Hospital, Oxford, UK
Correspondence: Seena Fazel. Email: seena.fazel@psych.ox.ac.uk
First received 15 May 2024, revised 17 Sep 2024, accepted 30 Sep 2024
Supplementary material
Supplementary material is available online at https://doi.org/10.1192/bjp.2024.226
Data availability
Data availability is not applicable to this article as no new data were created or analysed in this
study.
Acknowledgements
We are grateful to Phoebe Homer and Aaron Johnson for their assistance as second independ-
ent reviewers in screening, data extraction and quality assessment.
Author contributions
R.Y. and S.F. developed the main conceptual ideas and verified the methodology. R.T.S.C. per-
formed the formal analyses under the supervision of R.Y. R.T.S.C. and R.Y. wrote the manu-
script in consultation with S.F. and J.R.G.
Funding
S.F. is funded by the Wellcome Trust Senior Research Fellowship (grant number 202836/Z/16/
Z) and NIHR Oxford Health Biomedical Research Centre (BRC). J.R.G. is supported by the NIHR
Oxford Health BRC. The views expressed are those of the authors and not necessarily those of
the Wellcome Trust, NIHR or the Department of Health and Social Care.
Declaration of interest
J.R.G. is a member of the British Journal of Psychiatry Editorial Board (Editorial Advisor) but did
not take part in the review or decision-making process of this paper. The other authors reported
no conflict of interests. The funders of the study had no role in the study design, data collection,
data analysis, data interpretation or writing of this report.
Transparency declaration
R.T.S.C. is the guarantor of this review and affirms that the manuscript is an honest, accurate
and transparent account of the studies being reported; that no important aspects of the study
have been omitted; and that any discrepancies from the study as planned (and, if relevant,
registered) have been explained.
Analytic code availability
The analytic codes that support the meta-analyses in this review are available upon reasonable
request.
Research material availability
Tabular data in this review are available upon reasonable request.
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