Research in Developmental Disabilities 30 (2009) 1248–1257
Contents lists available at ScienceDirect
Research in Developmental
Disabilities
Markers for aggression in inpatient treatment
facilities for adults with mild to borderline
intellectual disability§
Nienke H. Tenneij a,d, Robert Didden b,*,
Joost Jan Stolker c, Hans M. Koot d
a
Research and Documentation Centre (WODC), Ministry of Justice, Den Haag, The Netherlands
Behavioural Science Institute, Radboud University Nijmegen, and Trajectum, Zutphen,
P.O. Box 9104, 6500 HE Nijmegen, The Netherlands
c
Arkin, Institute for Mental Health Care, Amsterdam, The Netherlands
d
VU University, Amsterdam, The Netherlands
b
A R T I C L E I N F O
A B S T R A C T
Article history:
Received 3 April 2009
Accepted 22 April 2009
In high care settings for persons with intellectual disability (ID)
aggressive incidents often occur. Still little is known about factors
that are associated with an increased risk for aggressive behavior in
clients who are admitted to an inpatient treatment facility. In four
inpatient facilities, 108 adults with mild and borderline ID and
behavior problems were categorised into three aggressive incidents
groups (no, mild, severe) according to their actual aggressive
behavior observed for six months. The three groups were compared
with regard to background and admission characteristics, psychiatric co-morbidity and emotional and behavioral problems. Results
show that antisocial behaviors, behaviors indicative of a lack of
impulse control, psychotic behaviors, mood related behaviors, and
auto-aggressive behavior increased the likelihood of severe
aggression. The three groups did not differ with regard to client
and admission characteristics or psychiatric co-morbidity. Behaviors that are predictive of severe inpatient aggression in settings
for adults with mild to borderline ID and behavior problems closely
resemble those that are distinguished in risk assessment instruments for forensic non-disabled individuals.
ß 2009 Elsevier Ltd. All rights reserved.
Keywords:
Aggression
Risk factors
Inpatient treatment
Mild to borderline ID
§
Authors’ Note: We thank De Borg facilities for their participation.
* Corresponding author.
E-mail address: [email protected] (R. Didden).
0891-4222/$ – see front matter ß 2009 Elsevier Ltd. All rights reserved.
doi:10.1016/j.ridd.2009.04.006
N.H. Tenneij et al. / Research in Developmental Disabilities 30 (2009) 1248–1257
1249
1. Introduction
Aggressive behavior is one of the most common types of challenging behavior in individuals
with intellectual disability (ID) (see e.g., Emerson et al., 2001). Aggression may be frequently seen
in facilities for the treatment of individuals with mild to borderline ID and severe behavioral and
emotional problems (Tyrer et al., 2006). No doubt, aggressive and violent behaviors may have
severe adverse effects on the victim, the client exhibiting aggression, staff members and services
(McMillan, Hastings, & Coldwell, 2004). Identification of factors that may increase the risk for
aggression and violent behaviors is important for developing treatment programs and risk
assessment methods and for establishing referral (exclusion/inclusion) criteria for inpatient
treatment settings.
Several studies have examined factors related to aggressive behavior in persons with
ID (see e.g., McClintock, Hall, & Oliver, 2003; Sigafoos, Elkins, Kerr, & Attwood, 1994). These
studies showed that men (Sigafoos et al., 1994), persons aged between 20 and 35 years
(Tyrer et al., 2006), persons with more severe levels of ID (Tyrer et al., 2006), and persons
with a history of violence (Davidson et al., 1994) and a personality disorder (Hogue et al., 2006)
are more likely to display aggressive behaviors than others. Besides, aggressive behavior
appears to be associated with an increased prevalence of psychopathology (Hemmings,
Gravestock, Pickard, & Bouras, 2006; Linaker, 1994; Moss et al., 2000), as well as with specific
behaviors such as self-injurious behavior (Davidson et al., 1996), mood related problems
(Hemmings et al., 2006; Tyrer et al., 2006) and antisocial behaviors (Hogue et al., 2006; Lindsay
et al., 2004). In psychiatric and forensic non-disabled populations, studies have been conducted to
identify characteristics specific for inpatient aggression (Douglas, Ogloff, Nicholls, & Grant, 1999;
Wang & Diamond, 1999). Outcomes of these studies have among others resulted in the
development of risk assessment instruments, in which characteristics of persons are identified
that increase the likelihood of inpatient aggression (see Webster, Eaves, Douglas, & Wintrup,
1995).
A small number of studies have explored accuracy of risk assessment methods in
predicting aggression in clients with mild to borderline ID who were residents in a treatment
inpatient setting. For example, McMillan et al. (2004) used clinical and actuarial methods for
predicting violence in 124 clients with mild ID who were inpatients of a forensic ID hospital.
Data were collected during a period of 1 year. Clinical rating consisted of risk rating
made by members of the client’s multidisciplinary team, whereas actuarial prediction used the
number of aggressive and violent incidents during a period of 6 months. Both methods
were appropriate in predicting clients’ aggressive and violent behaviors during inpatient
treatment.
However, our knowledge about risk factors for inpatient aggression and violence remains scarce.
Several studies have compared groups of offenders with ID across groups differing in level of security.
For example, Hogue et al. (2006) compared offenders with ID in high security (n = 73), medium
security (n = 70), and low security (i.e. community service; n = 69) settings. They found that in
particular the presence of a personality disorder predicted group membership. Clients with a
personality disorder were more likely to be in the highest security group and severe violent incidents
were more common in the highest security group. Offending was best predicted by antisocial traits
and personality disorder classification.
In contrast to studies that examined correlates of aggressive behavior in persons with ID,
in the present study specifically a high-risk inpatient population was investigated. Knowledge
regarding factors associated with an increased risk of severe inpatient aggression in
particular populations is important, not only with regard to staff and client security, but
also to aid in making clinical decisions like involuntarily commitment, medication required and
the prospect of discharge (Steinert, 2002). Studies on risk factors for aggression in individuals
with mild ID and severe challenging behaviors are still scarce. The aim of the present study
was to identify client characteristics and behaviors associated with inpatient aggression in
four treatment facilities for adults with mild ID and severe behavioral and emotional
problems.
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2. Method
2.1. Participants and setting
The study was carried out in four inpatient treatment facilities for adults with mild ID and severe
behavioral and emotional problems. Persons were referred to these facilities if treatment in general
health institutions and/or units of residential settings remain ineffective. The primary purpose of
admission is to establish a psychiatric or behavioral diagnosis and to improve behavior by prolonged
treatment and rehabilitation. After a comprehensive diagnostic phase, a structured environment and
different treatment modalities were offered, including pharmacological treatment, behavior
management (e.g., cognitive behavior therapy), social skills training and vocational training. In
general, clients referred to these facilities had attended a school for special education and/or were
known to services for persons with ID. If formal IQ data were not available in the records of a client, the
Dutch version of the WAIS-III (Wechsler, van der Steene, Vertommen, Bleichrodt, & Uiterwijk, 2000)
was used to obtain an IQ score. The use of standardised information collected during admission of
clients for research purposes was approved of by the institutional review boards of the participating
facilities. One-hundred and eight clients, who gave written informed consent were included.
The sample consisted of 82 men and 26 women with an average age of 26.4 years (SD = 7.5).
Average total IQ, albeit assessed with different IQ tests, was 65.6 (SD = 10.3). Reasons for referral were
aggressive behavior (81%), oppositional behavior (70%), impulse control problems (54%), problems
with substances (44%), and sexually inappropriate behavior (31%). Almost all clients (94%) were
previously admitted to psychiatric hospitals and/or specialised units of residential settings. At the
time the study began, 81 clients had already been admitted for a certain period (average of 98.7 weeks,
SD = 130.8).
2.2. Measures
2.2.1. Aggression
Aggressive incidents were assessed with the Staff Observation Aggression Scale-Revised (SOAS-R;
Nijman & Palmstierna, 2002). In the SOAS-R an aggressive incident is defined as ‘‘any verbal, nonverbal, or physical behavior that was threatening (to self, others, or property) or physical behavior that
actually did harm (to self, others, or property).’’ A SOAS-R form was completed following each time any
staff member observed an aggressive incident in which the client was involved. The SOAS-R consists of
five columns pertaining to specific aspects of aggressive incidents, namely: (a) antecedents provoking
the incident, (b) aggressive means shown by the client during the incident, (c) target during the
incident, (d) consequence(s) for victim(s), and (e) measures taken to stop the incident. Under target,
six potential targets can be marked, viz. nothing/nobody, objects, co-clients, staff-members, other
persons (like visitors), and the person him/herself. Aggressive incidents clients directed towards
themselves were coded as ‘auto-aggressive incidents’. All incidents that were directed towards
objects, other clients, staff-members, and/or other persons were coded as ‘aggressive incidents’.
Subsequently, aggressive incidents were coded as either severe or mild, based on the following
criteria: (a) incidents with physical consequences for the victims, i.e. pain or more serious harm, were
coded severe; all other incidents were scored as mild; (b) when restrictive measures were applied to
stop an incident, including parenteral medication, seclusion/isolation, and/or restraints, the incidents
were coded as severe; if other, non-restrictive measures were applied, including no measures, a talk,
client being calmly brought away, incidents were coded as mild. The SOAS-R is often used in research
on the occurrence and causes of inpatient aggression on psychiatric wards and has proven to be a valid
and reliable instrument (see Nijman, Merckelbach, Allertz, & Campo, 1997; Shah, Chiu, & Ames, 1997;
Steinert, Wolfe, & Gebhardt, 2000).
2.2.2. Psychiatric disorders
Psychiatric axis-I DSM-IV disorders were assessed with an adapted version of the DSM-III-R
Checklist (Hudziak et al., 1993). The presence or absence of criteria of DSM-IV axis-I disorders was
judged by either a psychiatrist or clinical psychologist responsible for the client’s treatment. They all
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1251
received instructions how to use the checklist and all had extensive clinical experience with the
population under study. We distinguished seven broad groups of disorders, namely: (a) pervasive
developmental disorders, (b) oppositional disorders, (c) affective disorders, (d) anxiety disorders, (e)
psychotic disorders, (f) substance dependence disorders, and (g) presence of any DSM-IV axis-I
disorder. In another study, we found that the diagnostic information obtained with the DSM-IV
checklist showed systematic relations with another measure of psychopathology, viz. the Adult
Behavior Checklist (Achenbach & Rescorla, 2003), as an indicator for its convergent validity (Tenneij &
Koot, 2007).
2.2.3. Emotional and behavioral problems
Emotional and behavioral problems were assessed with the Adult Behavior Checklist (ABCL;
Achenbach & Rescorla, 2003). The ABCL consists of 118 behavior problem items. These were evaluated
for the preceding three months by a primary care staff member who knew the subject well. Behavior
problem statements are scored on a three-level rating scale (viz. ‘‘not true’’, ‘‘somewhat true’’, and
‘‘very true’’). In non-disabled populations, factor-analytic studies have yielded eight small-band
syndrome scales: (a) Anxious-Depressed, 14 items; (b) Withdrawn, 9 items; (c) Somatic Complaints, 9
items; (d) Thought Problems, 12 items; (e) Attention Problems, 17 items; (f) Aggressive Behavior, 16
items; (g) Rule-breaking Behavior, 13 items; (h) Intrusive, 6 items. Furthermore, two global broadband
syndromes are distinguished, labelled Internalizing (32 items) and Externalizing (35 items), and a
Total Problem Score (all 118 items) can be obtained. The ABCL has been proven a reliable and valid
measure in the general population (Achenbach & Rescorla, 2003). Recently, we found evidence for the
reliability and validity of the ABCL in adults with mild to borderline ID and severe behavior problems
(Tenneij & Koot, 2007).
2.3. Procedure
After introduction of the SOAS-R to all staff member on all participating wards, aggressive incidents
were documented with it for a period of 12 months. Documentation of incidents took place between
September 2004 and March 2006, with different start- and end-dates for each facility. During this
period 173 clients were present, of which 140 (81%) gave their written informed consent. Clients could
be admitted or discharged during the year of aggression documentation, as a result of which the actual
documentation period for each client differed. Clients who were present at least six months were
included. This concerned 108 of the 140 clients. Subsequently, for each client SOAS-R data
documented for a continuous period of six months were used for analyses.
This study is part of a larger study concerning assessment of (change in) psychopathology and
functioning in adults with mild ID and severe behavior problems that started in January 2004 (see
Tenneij, Didden, & Koot, in press). The DSM-IV checklist axis-I and ABCL were administered when a
client was present at the facility for at least three months. At the same time, reason for referral
(violent/aggressive behavior yes/no) and type of admission (voluntary yes/no) were registered.
Administration of the ABCL was repeated every six months. So, depending on the length of admission,
one or more assessments with this instrument was available. In the present study, the assessment was
used which fell in the six months of aggression documentation selected for each client.
2.4. Statistical analyses
Data were analysed with the SPSS statistical package, version 12.0. We categorised participants
into three groups on the basis of the aggressive incidents documented with the SOAS-R, namely (a) a
group causing no aggressive incidents, (b) a group causing mild aggressive incidents (i.e. none of the
incidents these clients caused was coded as severe, and (c) a group causing severe aggressive incidents
(i.e. at least one incident was coded as severe with regard to consequences and/or measures taken to
stop it). We compared these groups with regard to gender, age, treatment duration, legal status at
admission, violence/aggression as reason for referral, presence of auto-aggressive behavior, presence
of clusters of DSM-IV axis-I disorders, and scores on the ABCL scales. Depending on the type of variable
chi-square tests, univariate or multivariate analyses of variance, or Mann–Whitney U tests were used.
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Dichotomised item scores, viz. items scored 0 (=not true) or 1 (=somewhat true) versus 2 (=very
true), of ABCL scales that were different for groups were used in univariate logistic regression analyses
to predict whether a client was grouped in the severe incident group. The group causing no incidents
was used as a contrast group. Finally, to form a model with markers uniquely contributing to the
prediction of severe aggressive incidents, a stepwise regression analysis was performed with all ABCL
items that predicted severe incidents group membership and eventually other variables showing
group differences in earlier analyses. For each variable, a forward selection procedure with a 5% level
of significance was used to include variables in the model.
3. Results
During the observation period of six months, 415 aggressive incidents were documented with the
SOAS-R. Sixty clients (55.5% of all clients) were involved in these incidents, and 23 of them were
categorised into the mild and 37 into the severe aggressive incidents group. The mild and severe
aggressive incidents groups differed in average frequency of aggressive incidents, with 1.6 (SD = 1.3)
and 10.2 (SD = 11.4) incidents, respectively (U = 108.0, p < .001).
3.1. Client characteristics and admission data
For the three groups, gender, treatment duration, present age, legal status at admission, and
violence/aggression as reason for referral, are depicted in Table 1. No statistically significant
differences in any of these variables were found between groups.
3.2. Psychopathology
3.2.1. Psychiatric disorders
DSM-IV axis-I data were available for 94 clients (87% of the total sample). For 62 (66%) of these 94
clients an axis-I DSM-IV disorder was established. The three aggressive incidents groups did not differ
significantly in the percentage of clients receiving a classification (see Table 2).
3.2.2. Auto-aggression
One-hundred and forty-one auto-aggressive incidents were reported with the SOAS-R, in which 19
clients were involved. The three groups differed with regard to the proportion of clients who were
involved in auto-aggressive incidents (x2(2) = 13.8, p < .01). 4% (2/48), 17% (4/23), and 35% (13/37) of
clients in the no incidents group, the mild incidents group, and the severe incidents group,
respectively, were involved in auto-aggressive incidents.
3.2.3. Adult Behavior Checklist
Multivariate analysis with group as main factor and ABCL scales as dependent variables showed a
main effect for group, F(18, 194) = 2.95, p < .001. Subsequent univariate analyses showed significant
differences between groups for all ABCL scales, except for Anxious-Depressed and Somatic Complaints
(see Table 3). Bonferroni post hoc tests showed that clients in the severe group had a higher score, i.e.
more severe problems, on the Withdrawn and Thought Problem scale, and overall Total Problems,
than clients from the other two groups. In addition, the severe group showed higher scores on the
Attention Problems, Rule-breaking, Intrusive, and Internalizing scale, compared to clients in the no
incidents group. Clients involved in aggressive incidents, irrespective of severity, had higher
Externalizing scores than clients in the no incidents group. Finally, as could be expected, clients in the
severe group had a higher average Aggressive Behavior score than clients in the mild group who scored
higher than clients in the no incidents group.
Results of univariate logistic regression analyses with the dichotomised ABCL items and autoaggression (yes/no) comparing the severe incidents versus the no incidents group are shown in
Table 4. Items showing significant contrasts between these groups are ordered by ABCL scale. Of the
ABCL items, 25 were significantly more often strongly present (score 2) in the severe incidents group
than in the no incidents group. Furthermore, clients who caused auto-aggressive incidents had a 12.5
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Table 1
Background and admission status variables for clients in the no aggressive incidents group (no), in the mild aggressive incidents
group (mild), and in the severe aggressive incidents group (severe).
Present age in years (SD)
Percentage men
Percentage women
Treatment duration in weeks (SD)
(n = 81a)
Percentage aggression/violence
as reason for referral
Percentage voluntarily admitted
No aggression
(n = 48)
Mild aggression
(n = 23)
Severe aggression
(n = 37)
Test statistic
p
27.3 (7.5)
48.8%
30.8%
121.1 (141.6)
(n = 36)
80.4%
27.9 (8.6)
20.7%
23.1%
51.8 (31.2)
(n = 16)
76.2%
24.4 (6.4)
30.5%
46.2%
96.8 (146.4)
(n = 29)
83.8%
F(2, 105) = 2.11
x2(2) = 2.91
.13
.23
F(2, 78) = 1.58
.21
x2(2) = 0.50
.78
50.0%
47.6%
51.4%
x2(2) = 0.08
.96
a
This is only calculated for the subsample of 81 clients who were already receiving treatment when documentation of aggressive
incidents with the SOAS-R started.
Table 2
Presence of any axis I disorder and specific clusters of axis I disorders for clients in the no aggressive incidents group (no), in the
mild aggressive incidents group (mild), and in the severe aggressive incidents group (severe) (n = 94)a.
Anxiety disorders
Affective disorders
Pervasive developmental disorders
Disruptive disorders
Psychotic disorders
Substance dependence disorders
Any axis I disorder
No
(n = 41)
Mild
(n = 20)
Severe
(n = 33)
Total group
(n = 94)
x2(2)
9.8%
7.3%
24.4%
19.5%
12.2%
12.2%
65.9%
5.0%
0%
10.0%
15.0%
5.0%
25.0%
50.0%
6.1%
6.1%
31.3%
29.0%
9.1%
18.8%
76.7%
7.4%
5.3%
23.7%
21.7%
9.6%
17.2%
65.9%
–b
–b
3.09
1.62
–b
1.63
3.79
p
.21
.44
.44
.15
Note: Clients could meet criteria for more than one cluster.
a
Of 12 clients DSM-IV data were missing, resulting in a sample of 94 clients.
b
Differences between groups could not be tested because criteria for chi-square test were not met.
Table 3
Mean (SD) ABCL scale scores for clients in the no aggressive incidents group (no), in the mild aggressive incidents group (mild),
and in the severe aggressive incidents group (severe).
Anxious-Depressed
Withdrawn
Somatic Complaints
Thought Problems
Attention Problems
Aggressive Behavior
Rule Breaking
Intrusive
Internalizing
Externalizing
Total problems
Theoretical
range
No
(n = 48)
Mild
(n = 23)
Severe
(n = 37)
F (2,104)
p
0–28
0–18
0–18
0–18
0–34
0–32
0–26
0–12
0–64
0–70
0–186
10.0
7.6
2.2
3.4
14.3
8.5
6.8
3.8
19.8
19.1
70.1
10.3
6.8
2.8
3.2
15.7
12.2
9.7
4.8
19.9
27.6
80.2
11.8
10.0
3.4
6.4
18.5
16.5
11.4
5.7
25.1
33.6
101.7
1.03
7.51
1.92
10.04
5.16
17.91
8.88
3.82
4.69
10.94
13.89
.36
<.01
.15
<.01
<.01
<.01
<.01
.03
.01
<.01
<.01
(6.0)
(3.7)
(2.5)
(2.9)
(6.3)
(5.0)
(4.6)
(3.0)
(8.5)
(10.5)
(25.6)
(5.0)
(2.8)
(3.2)
(2.5)
(5.3)
(5.7)
(4.5)
(3.0)
(8.4)
(11.1)
(24.0)
(5.9)
(3.4)
(2.8)
(4.1)
(5.6)
(7.5)
(5.7)
(3.4)
(8.5)
(14.4)
(33.4)
Post hoc tests
Severe > mild & no
Severe > mild & no
Severe > no
Severe > mild > no
Severe > no
Severe > no
Severe > no
Severe and mild > no
Severe > mild and no
Note: Univariate analyses of variance of ABCL scales with group as main factor. Each significant group effect was followed up by
Bonferroni post hoc tests, comparing each group pair wise (adjusting for multiple comparisons).
times higher chance to be in the severe incidents group than clients who caused no auto-aggressive
incidents. The stepwise multivariate analysis including all univariately significant items showed that
when the ABCL items (81) ‘‘changeable behavior’’ and (116) ‘‘upset easily’’, together with autoaggressive incidents (yes/no) were included in a model, the other items did not significantly (p < .05)
improve the model.
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Table 4
ABCL items and auto-aggression associated with the grouping of severe aggressive incidents.
ABCL items
Univariate
Stepwise
ORa
p
CIb
ORa
CIb
.01
7.5
1.6–34.2
<.01
9.9
2.6–38.5
.05
6.2
1–38.9
p
c
Withdrawn (9 items)
25. Does not get along with others
48. Not liked by others
67. Trouble making/keeping friends
<.01
<.01
.02
6.3
6.3
3.1
1.6–24.8
1.6–24.8
1.2–7.6
Thought problems (9 items)
9. Cannot get mind of things
70. Sees things
85. Strange ideas
.01
.04
.02
3.1
5.4
3.5
1.3–7.5
1.0–27.6
1.3–9.9
Attention problems (17 items)
13. Confused
105. Disorganised
.03
.05
6.3
2.7
1.3–31.9
1.0–7.5
Aggressive behavior (16 items)
3. Argues
5. Blames others
16. Mean to others
55. Mood swings
81. Changeable behavior
86. Stubborn
87. Sudden mood changes
116. Upset easily
118. Impatient
<.01
.01
.01
<.01
<.01
<.01
<.01
<.01
<.01
22.6
3.2
15.1
5.8
15.8
4.4
11.2
16.1
5.3
2.8–183.7
1.3–7.8
1.8–125.6
1.7–19.9
4.2–60.1
1.7–11.3
2.9–42.6
4.8–54.2
2.0–14.3
Rule-breaking behavior (13 items)
23. Breaks Rules
41. Impulsive
76. Irresponsible
92. Behavior may cause trouble with law
117. Can’t manage money
.01
.05
<.01
<.01
.01
4.6
2.6
5.9
12.2
3.1
1.4–14.3
1.0–6.5
2.1–16.5
2.5–58.5
1.3–7.6
Intrusive (6 items)
19. Wants attention
74. Shows off
104. Loud
.02
.02
<.01
2.8
3.6
5.2
1.1–7.0
1.3–10.1
1.7–16.4
SOAS-R auto-aggression
Auto-aggressive incident(s)
<.01
12.5
2.6–59.8
Note: ABCL items are abbreviated.
a
OR = odds ratio.
b
CI = 95% confidence interval; only items with significant (p < .05) odds ratios are shown.
c
Total number of items a scale consists of.
4. Discussion
In the present study, the actual aggressive behavior prospectively assessed was used to identify
aggressive subgroups. We found that the group of clients who were involved (caused) in severe
aggressive incidents during admission appears to constitute a subgroup of extremely behaviorally
disturbed clients; in the present study 34% of the total sample. Among others, they showed more
severe problems on almost all domains of the ABCL and the highest proportion of clients involved in
auto-aggressive behavior was found in this group. This corroborates findings in psychiatric facilities
for non-disabled adults, namely that subgroups of clients which are responsible for a majority of
aggressive incidents are more behaviorally disturbed than clients not involved in – many – incidents
(see e.g., Owen, Tarantello, Jones, & Tennant, 1998; Soliman & Reza, 2001).
The analyses with individual items of the ABCL showed that at least four different types of
behaviors, across the ABCL scales, are associated with severe inpatient incidents, namely antisocial
behaviors (items like ‘‘argues’’, ‘‘blames others’’, and ‘‘mean to others’’), behaviors indicative of a lack
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of impulse control (e.g., ‘‘impulsive’’, ‘‘impatient’’, and ‘‘irresponsible’’), psychotic-like behaviors (e.g.,
‘‘sees things’’, ‘‘strange behavior’’, and ‘‘disorganised’’), and mood related behaviors (e.g., ‘‘mood
swings’’, ‘‘sudden mood changes’’, and ‘‘easily upset’’). These types of behaviors also have been found
to be related to aggressive behavior in both inpatient populations of normal intelligence and in general
samples of persons with ID (Hemmings et al., 2006; Lindsay et al., 2004; Tyrer et al., 2006; Wang &
Diamond, 1999; Woods & Almvik, 2002). Besides, they correspond with behaviors that are
distinguished by several authors in violence prediction instruments for – forensic – inpatients
(Lindsay et al., 2004; Webster et al., 1995; Woods & Almvik, 2002). For example, the HCR-20 (Webster
et al., 1995), a risk assessment instrument originally developed for forensic psychiatric inpatients with
normal intelligence, includes in its clinical scale psychotic symptoms and impulsivity. Lindsay et al.
(2004) developed a short time risk assessment instrument for forensic inpatients with ID, in which all
of the four types of behavior we found were included. So, in different high risk samples, apparently
similar behaviors identify persons who are at high risk to be involved in severe aggressive incidents.
A noteworthy finding of the present study was that auto-aggression appears to be a distinctive and
unique marker of overall incident severity over and above the types of problem behaviors indicated
above. An association between aggressive behavior towards others and auto-aggressive behavior has
also been found in other studies (Davidson et al., 1996; Hillbrand, 1995). For example, Hillbrand (1995)
showed in a forensic population of normal intelligence that auto-aggressive behavior identified a
particularly violent group of individuals. He suggested that auto-aggression needs to be evaluated
prospectively as a predictor of inpatient violence. Results of the present study appear to support his view.
None of the other characteristics we examined were related to the grouping of aggressive incidents. In
accordance with other studies in selected populations (Holden & Gitlesen, 2006; Lam, McNiel, & Binder,
2000), the proportion of male and female clients involved in aggressive incidents in the treatment
facilities appeared equal. Davis (1991) suggested that one might account for this by viewing inpatients as
a select group of disturbed, agitated individuals; hence the process of selection obscures sex role
differences normally found in the community. In contrast to the studies in which involuntarily
admission was found to be a reliable predictor of inpatient aggression (Nijman et al., 1997; Nijman,
Merckelbach, Evers, Palmstierna, & Campo, 2002), in the present sample many clients had already been
admitted for an extensive period at the time the documentation of aggressive incidents started. Possibly,
involuntary admission is a predictor of inpatient aggression especially at the start of treatment. In the
present study, aggression/violence as reason for referral was chosen as an indicator for a history of
violence, in many studies shown to be an important predictor of future aggression (Arango, Calcedo,
Gonzalez, & Calcedo, 1999; Davidson et al., 1994). In the present sample, pre-referral aggression was
highly present, i.e. in 81% of the total sample, and appeared unrelated to the grouping of aggressive
incidents. Possibly, this high prevalence of pre-referral aggression concealed its expected association
with aggressive incidents during admission. Finally, we found no significant relationship between DSMIV axis-I co-morbidity and grouping of aggressive incidents. It has been suggested that it is probably not
so much the presence of a psychiatric disorder but the stage of the illness or the type of symptoms that
are present that are arguably more useful predictors of aggressive behavior (Davis, 1991).
This study has several limitations. The distinction between clients in severity groups was based on
data collected with an incident based measure of aggression, viz. the SOAS-R. It relies on the
preparedness of staff members to document all occurring aggressive incidents. Although it cannot be
ruled out that some incidents were not reported, possibly resulting in some clients being wrongly
categorised in the no incidents or mild incidents group, meaningful relations were found between the
categorisation according to the SOAS-R and client information obtained using standardised rating
scales. Furthermore, to standardise DSM-IV axis-I classification, we used a checklist to integrate
clinical information. Although reliability of this method was not checked in the present study, its
validity has been documented in other studies (Bastiaansen, Koot, Ferdinand, & Verhulst, 2004;
Hudziak et al., 1993). Finally, because IQ was assessed by means of different IQ tests, it was not
possible to examine relationships between IQ and involvement in aggressive incidents, a relation
shown in previous studies.
This study shows that severity of aggressive incidents in persons with mild to borderline ID in
inpatient settings for severe challenging behavior is associated with overall behavioral and emotional
disturbance of the clients, and appears independent of sex, referral characteristics, and psychiatric co-
1256
N.H. Tenneij et al. / Research in Developmental Disabilities 30 (2009) 1248–1257
morbidity. The fact that signs of behavioral disturbance can be detected by standardised
questionnaires such as the ABCL, and possibly by signs of auto-aggression, suggests the usefulness
of screening on these markers before or immediately after inpatient referral and during admission.
The present findings suggest that caregivers should be especially alert when persons show autoaggressive and changeable behavior and are upset easily. Early signalling of individuals at increased
risk for aggressive incidents enhance the development of preventive measures and more effective
inpatient treatments.
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