Nursing and Social Education Research Unit, University of Bern Psychiatric Services, Berne, Switzerland
Clinic for Forensic Psychiatry, Centre of Psychiatry Rheinau, Rheinau, Switzerland
Department of Nursing Science, Humboldt University, Berlin, Germany
Maastricht University, Maastricht, The Netherlands
University of Zurich and Psychiatric Hospital Schloessli, Oetwil am See, Switzerland
Mannheim Institute of Public Health, Mannheim Medical Faculty, University of Heidelberg, Germany
Correspondence: Christoph Abderhalden, Nursing and Social Education Research Unit, University Bern Psychiatric Services, Bolligenstrasse 111, CH-3000 Berne 60, Switzerland. Email: Abderhalden{at}puk.unibe.ch
None. Funding detailed in Acknowledgements.
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There is a lack of research on the possible contribution of a structured risk assessment to the reduction of aggression in psychiatric in-patient care.
Aims
To assess whether such risk assessments decrease the incidence of violence and coercion.
Method
A cluster randomised controlled trial was conducted with 14 acute psychiatric admission wards as the units of randomisation, including a preference arm. The intervention comprised a standardised risk assessment following admission with mandatory evaluation of prevention in high-risk patients.
Results
Incidence rates decreased substantially in the intervention wards, whereas little change occurred in the control wards. The adjusted risk ratios suggest a 41% reduction in severe aggressive incidents and a 27% decline in the use of coercive measures. The severity of aggressive incidents did not decrease.
Conclusions
Structured risk assessment during the first days of treatment may contribute to reduced violence and coercion in acute psychiatric wards.
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Study area and eligibility of wards
In the German-speaking part of Switzerland, 32 psychiatric hospitals
provide psychiatric in-patient treatment for approximately 75% (5 376 800
persons) of the Swiss population on 324 wards. To be eligible for
participation, a psychiatric ward had to meet the following criteria:
Eighty-six wards satisfied these criteria.
Recruitment and design
The 86 acute wards were invited to partake in a large intervention trial,
of which one arm was a structured risk assessment. Sixty-two wards declined to
participate, including ten wards predominantly treating private patients with
few involuntary admissions. Nineteen wards consented to be randomised within
the trial, and five wards preferred to introduce the study protocol of
structured risk assessment without randomisation. Randomisation was carried
out prior to inclusion on the basis of a computer-generated random-number
list. Here, we report on the four wards randomised to structured risk
assessment, the five wards randomised to the waiting-list control arm, and the
five wards of the preference group (Fig.
1). After enrolment, wards collected baseline data during a
3-month period (phase 1), followed by the 3-month intervention period (phase
2). The first ward was enrolled in June 2002 and the last ward completed the
study in April 2004.
![]() View larger version (16K): [in a new window] [as a PowerPoint slide] |
Fig. 1 Recruitment and follow-up.
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Based on empirical data from the instrument validation study, raw scores of 0–12 have been translated to four risk levels.5,6,8 In order to facilitate interpretation and communication of the risk level, the risk is expressed as natural frequencies based on empirical data: score 0–3, fewer than 1 in 100 patients with this score will physically attack another person during the next shift; score 4–6, about 1 in 100 patients will do so; score 7–9, 1 in 10 patients will do so; and score 10–12, 1 in 4 patients will do so.
Ratings were carried out twice daily. We assisted the clinical application of the scores by explicit recommendations. For patients obtaining scores of 7–9 we suggested to staff that they discuss possible prevention measures from a list provided on the risk assessment form (see Appendix). For patients with scores of 10 or above we recommended a multidisciplinary team consultation to discuss the need for immediate measures. The organisational implementation and adherence with these recommendations were left to the discretion of wards without systematic data collection.
Outcome measures
The main outcome measures were the changes in incidence rates of severe
aggressive events and coercive measures, comparing the baseline period with
the intervention period. Aggressive incidents were recorded by means of the
revised Staff Observation Aggression Scale
(SOAS–R).10,11
This scale records provoking factors, means used by the patient, target of the
aggression, consequences for the target, and measures taken to terminate the
aggression. The scale was completed by staff members who witnessed the
patients aggressive behaviour. Aggression was defined as any verbal,
non-verbal or physical behaviour that was threatening (to self, others or
property), or physical behaviour that actually caused harm (to self, others or
property). The severity of the incidents was measured using the SOAS–R
scoring system, ranging from 0 to 22 points. Following the recommendation of
the authors of the SOAS–R, incidents with a score of 9 or more points
were regarded as severe (T. Palmstierna, personal communication, 2003).
Coercive measures were recorded on a standardised form developed and
pre-tested on the basis of existing formats in general use in the
area.7 The form
covered a wide range of measures, from forced injection of psychotropic
medication to seclusion and mechanical restraint. For this study coercive
measures were recoded into dichotomous data (present/absent).
Data collection
In order to control for possible recruitment bias, we conducted a survey of
all wards within the study area prior to our investigation using a
questionnaire enquiring about size of the wards, staffing and the facilities
for managing aggression and
violence.12 In
addition, we asked the ward leaders to rate the severity of the problem and
the resources for aggression management
(Table 1). During both study
periods, all aggressive incidents were registered using the SOAS–R form.
Coercive measures were recorded on the purpose-designed study form. Physical
attacks were considered if the SOAS–R description of the incident met
both the following criteria:
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View this table: [in a new window] | Table 1 Ward characteristics |
To estimate possible underreporting of aggressive incidents, two investigators (C.A. and I.N.) regularly visited the study wards on randomly selected dates. During these site visits, all patient records were hand-reviewed for the preceding 3 days to detect any evidence of an aggressive incident. After termination of the study, each incident as abstracted from the patient records was compared with the available SOAS–R report forms. This made it possible to estimate the extent of underreporting and to assess the severity of those incidents for which no corresponding SOAS–R form was available. The same investigators abstracted additional patient data in a standardised format from the hospitals databases. These data included admission and discharge dates, age, gender, type of admission (voluntary v. involuntary) and main ICD–10 psychiatric diagnosis.13
Data analysis
For each study period and ward, we calculated the incidence rate of events
per 100 hospitalisation days. For this analysis, we included all aggressive
incidents directed towards other persons or objects, but excluded pure
aggression to self. The primary outcome was the rate of severe incidents with
a SOAS–R score of 9 or more. Secondary outcomes were the rate of
physical attacks and the rate of coercive measures. Ninety-five per cent
confidence intervals for rates were calculated assuming independence of the
probability of an incident for individual hospitalisation days (no correction
for autocorrelation). From these raw incidence rates we calculated the risk
ratios (RRs) for an event for each of the three study arms. The change in
incidence rates between the intervention and control groups was tested using a
test for the difference between two proportions (Statistica version 6). We
used the number of patients not the number of treatment days for the
calculation of the degrees of freedom. This is equivalent to the
Geisser–Greenhouse lower-bound test for repeated-measures designs to
control for
sphericity.14
Owing to the non-normal distribution of data, comparisons between
participating and non-participating wards were conducted using the
Mann–Whitney U-test for independent samples and the chi-squared
test or Fishers exact test. Unless otherwise stated, data are reported
as means and standard deviations. For all analyses, statistical significance
was determined as a two-sided error probability of
=0.05. Data were
analysed using SPSS version 10.0 and Confidence Interval Analysis version 2.1
(University of Southampton, UK) for Windows.
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Of the 2364 patients (46.6% females; mean age=39.5 years, s.d.=14.2, range 14–95), 56% were admitted on a voluntary basis. The involuntary admission rate of 44% is typical for wards within German-speaking Switzerland. The median length of stay was 9 days, with an average of 19 days (s.d.=26.8, range 1–265). The ICD–10 diagnoses of the patients were as follows: organic, including symptomatic, mental disorders (F0), n=78 (3.3%); disorders due to psychoactive substance use (F1), n=574 (24.3%); schizophrenia, schizotypal and delusional disorders (F2), n=734 (31.0%); mood (affective) disorders (F3), n=382 (16.2%); neurotic, stress-related and somatoform disorders, behavioural syndromes associated with physiological disturbances and physical factors (F4), n=339 (14.3%); personality disorders of adult personality and behaviour (F6), n=76 (3.2%); others (e.g. mental retardation, disorders of psychological development, behavioural and emotional disorders with onset occurring in childhood and adolescence, n=66 (2.8%); and missing, n=115 (4.9%).
Aggressive incidents and coercive measures
Over both phases of the study, 770 aggressive incidents were reported
involving 314 patients (13.3% of all patients) and 632 coercive measures were
recorded. The difference between these numbers is attributable to the fact
that not all aggressive incidents were followed by coercive measures.
Additionally, coercive measures were sometimes employed to prevent aggression.
Of the 770 aggressive incidents, 418 (54%) had a SOAS–R score of 9 or
above and 258 (34%) incidents were physical attacks. The overall incidence
rate of severe aggressive events during the baseline period was 1.09 (95% CI
0.96–1.24) per 100 hospitalisation days. The overall incidence rate of
coercion during baseline was 1.57 (95% CI 1.41–175) per 100
hospitalisation days. Further rates are provided in
Table 2.
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View this table: [in a new window] | Table 2 Main outcome measures |
Intervention
From baseline to the intervention period, the rate of severe aggressive
events with a SOAS–R score of 9 or more declined both in the control arm
and in the intervention arm. The decline in the intervention wards (RR=0.59,
95% CI 0.41–83) was significantly larger (P<0.001) than the
decline in the control arms (RR=0.85, 95% CI 0.64–1.13). Raw and
calculated data are presented in Table
2. Likewise, all rates declined more in the intervention wards
compared with the control wards for all secondary outcomes: attacks 41%
v. 7% (P<0.001) and coercive measures 27% v.
increase by 10% (P<0.001). Finally,
Fig. 2 illustrates that for all
outcomes the effects were larger in the preference wards compared with the
wards randomised to intervention or control. Similar results were obtained
when analysing the data as to the occurrence of days with any aggressive
incident on the ward v. incident-free days (data not shown).
![]() View larger version (15K): [in a new window] [as a PowerPoint slide] |
Fig. 2 Main outcome measures. (a) Incidents with a Staff Observation Aggression
Scale – Revised score of 9 or above; (b) physical attacks; (c) coercive
measures.
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Estimation of underreporting
In contrast to the reduction in the rates of incidents and coercive
measures, the mean severity of all recorded incidents increased in both the
intervention group and the control group
(Table 3). We had anticipated
the possibility of an increasing underreporting of less severe events as the
study progressed. Therefore, two investigators (C.A. and I.N) manually
searched on randomly assigned dates the entire patient documentation and shift
reports for 115 patients covering 460 treatment days. The search identified
five incidents not registered with a corresponding SOAS–R form, with an
estimated severity of the non-reported incidents ranging from 1 to 5 points.
This suggests that predominantly minor incidents (<9 points) escaped
reporting, whereas few severe incidents (
9 points) remained unreported.
Figure 3 compares the frequency
of events stratified by score for each study period between the intervention
and the control group.
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View this table: [in a new window] | Table 3 Severity of aggressive incidents |
![]() View larger version (21K): [in a new window] [as a PowerPoint slide] |
Fig. 3 Event severity across study periods. SOAS–R, Staff Observation
Aggression Scale – Revised. (a) intervention group; (b) control group.
Each histogram shows the frequency of aggressive events standardised to the
number of hospitalisation days during the intervention period. The comparison
reveals that the intervention predominantly affected mild to moderately severe
incidents; no reduction was seen for the most severe events.
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Mechanisms of effectiveness
Strictly speaking, the intervention in this study consisted of three
elements. First, there was the repeated structured determination of the risk
in the first 3 days of each patients hospital stay. Second, in cases of
a high or very high risk, staff were encouraged to discuss preventive measures
from a list provided on the risk assessment form. Third, in cases of very high
risk, the teams were prompted to plan and implement preventive measures.
Although related to each other, each of these elements might have been
independently effective. For example, identification of patients with a high
risk score allows allocating staff time spent during group meetings for
discussion of preventive measures to a small subgroup of high-risk patients.
Thus, there are several possible explanations for the observed overall
effects. The obligation to assess all patients twice a day might have
increased general awareness of potential dangers. This awareness itself might
have fostered a more cautious approach and de-escalating staff behaviour. The
risk assessment form might also have facilitated the intra- and
interprofessional communication of risk. These factors, in combination with
the obligatory discussion of high-risk situations, might have resulted in a
more consistent team response to potentially dangerous patients. It is
conceivable that the crucial factor might have been an improved intra- and
interprofessional collaboration and unité de doctrine.
Finally, part of the risk assessment form was a list of simple, practical
prevention measures. The visibility of these measures might have acted as a
constant reminder of possible ways to prevent escalation of aggressive
situations or as a source of inspiration for aggression-related care planning.
Taken together, the current intervention appears to be an example of a simple
strategy to influence complex staff–patient interactions, in particular
where patients are responsive to intervention. This is underscored by the
finding that the intervention did not reduce the incidence rate of the
severest aggressive events, which are probably not as amenable to staff
interventions such as de-escalation. Although the systematic registering of
aggression using the SOAS–R has been reported to be per se an
effective mechanism to reduce
aggression,15 we
exclude this explanation given the stable aggression rates in the control
wards.
Several design features of the study warrant discussion. In line with published research, we designed the study to combine risk assessment with elements of risk management, forgoing the possibility of delineating the effect of pure risk assessment alone. We purposely included a preference arm in the study to simulate a patient preference randomised controlled trial paradigm or the comprehensive cohort design.16 In our study, the effect in the preference arm exceeded the effect observed in the group randomised to intervention. We offer several possible explanations for this. The patient population in the preference wards included a smaller proportion of people with a schizophrenic disorder; this raises the possibility that, beyond a preference effect,17 wards with fewer patients with schizophrenia may particularly benefit from the intervention. Alternatively, the more favourable results in the preference wards could also be seen as manifestation of staff characteristics and their preference for introducing risk assessment. This finding would then be independent of the patient population.
Limitations
In interpreting the findings of our study, several limitations must be
considered. We relied on randomisation of wards to minimise bias. However,
although the intervention and control wards were comparable with respect to
most of the characteristics considered, we still had baseline differences in
important aspects. All four of the intervention wards rated patient aggression
as a big or very big problem, in contrast to two out of five control wards.
Correspondingly, the baseline rates of aggression were higher on the
intervention wards compared with the controls. This might have led to a higher
sensitivity and perceived need to improve the situation, which might have
increased the effect of the intervention. Because of the small number of
wards, randomisation might not have been fully adequate to determine equality
of the study groups. Additionally, a larger number of participating wards
would have allowed the use of more sophisticated statistical models that
simultaneously control for clustering and autocorrelation, i.e. a three-level
model with days/events nested within patients nested within wards. Moreover,
the nature of the intervention rendered masking impossible. A further
limitation is the absence of data on the interventions actually implemented as
a consequence of the risk assessment. Finally, data on the frequency of
aggression or patient characteristics from the non-participating wards were
unavailable. Caution is therefore warranted in generalising our data beyond
the present study population. However, the aggression rates found in this
study are comparable with rates found in other studies on psychiatric acute
wards.11
Clinical and practical implications
Our finding that a simple and low-cost intervention, consisting of a risk
assessment twice daily for the first 3 days of hospitalisation in acutely
admitted psychiatric patients combined with a communication of risk scores as
natural frequency numbers (e.g. 1 out of 10 patients instead of 10%, 1 out of
1000 patients instead of
0.1%),18 and a
recommendation for action tailored to the risk level, reduced the incidence
rate of coercive measures and severe aggressive incidents, suggesting that
structured risk assessment may be a simple and cost-effective way of
diminishing the problem of violent incidents in acute psychiatric wards.
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Careful observation
General conversation (directed to reduce aggression)
Walk outdoors, one to one (directed to reduce aggression)
Walk outdoors in a group (directed to reduce aggression)
Reduction of demands (e.g. participation in activities)
Relaxation exercise
Confrontation with ward rules
Discussion of risk with patient
Talk down (to de-escalate)
Transfer to intensive area within ward
One-to-one observation for several hours
Increase of medication dosage
Pro re nata medication given orally (psychotropic drugs)
Open seclusion in the patients own room (time out)
Preventive seclusion (closed seclusion room)
Injection of psychotropic drugs (forced/voluntary)
Physical restraint (indicate number of points)
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