Criminal Behaviour and Mental Health (2015) Published online in Wiley Online Library (wileyonlinelibrary.com) DOI: 10.1002/cbm.1955
Predicting inpatient aggression by self-reported impulsivity in forensic psychiatric patients
ANNELEA M. C. BOUSARDT1, ADRIAAN W. HOOGENDOORN2, ERIC O. NOORTHOORN1,3, JACOBUS W. HUMMELEN1,4 AND HENK L. I. NIJMAN3,5, 1Forensic Psychiatric Department ‘de Boog’, GGNet, Warnsveld, Netherlands; 2Department of Psychiatry and the EMGO+ Institute for Health and Care Research, VU University Medical Center Amsterdam, Amsterdam, Netherlands; 3Altrecht Aventurijn, Den Dolder, Netherlands; 4Department Criminal Law and Criminology, University of Groningen, Groningen, Netherlands; 5Radboud University Nijmegen, Behavioural Science Institute, Nijmegen, Netherlands ABSTRACT Background Empirical knowledge of ‘predictors’ of physical inpatient aggression may provide staff with tools to prevent aggression or minimise its consequences. Aim To test the value of a self-reported measure of impulsivity for predicting inpatient aggression. Methods Self-report measures of different domains of impulsivity were obtained using the Urgency, Premeditation, Perseverance, Sensation seeking, Positive urgency (UPPS-P) impulsive behaviour scale with all 74 forensic psychiatric inpatients in one low-security forensic hospital. Aggressive incidents were measured using the Social Dysfunction and Aggression Scale (SDAS). The relationship between UPPS-P subscales and the number of weeks in which violent behaviour was observed was investigated by Poisson regression. Results The impulsivity domain labelled ‘negative urgency’ (NU), in combination with having a personality disorder, predicted the number of weeks in which physical aggression was observed by psychiatric nurses. NU also predicted physical aggression within the first 12 weeks of admission. Conclusions and implications for practice The results indicate that NU, which represents a patient’s inability to cope with rejection, disappointments or other undesired feelings, is associated with a higher likelihood of becoming violent while an inpatient. This specific coping deficit should perhaps be targeted more intensively in therapy. Selfreported NU may also serve as a useful adjunct to other risk assessment tools and as an indicator of change in violence risk. Copyright © 2015 John Wiley & Sons, Ltd.
Copyright © 2015 John Wiley & Sons, Ltd.
(2015) DOI: 10.1002/cbm
Bousardt et al.
Introduction Inpatient aggression may pose a serious threat to the physical and mental wellbeing of psychiatric caregivers and/or other patients. In extreme cases, it may cause severe injury and staff sick leave (Nijman et al., 2005). Furthermore, aggression is often followed by coercive measures. Vruwink et al. (2012) showed that more than 40% of the aggressive incidents were followed by seclusion. Reduction of inpatient aggression may, therefore, reduce both emotional and physical harm. The identification of predictive factors for aggression may provide staff with tools to prevent it. Links between impulsivity and aggression are well established (Gordon and Egan, 2011), in particular, when emotional arousal is increasing, the inability to resist acting on one’s impulses may trigger serious aggressive incidents. This may explain why impulsivity is one of the most investigated constructs in forensic psychiatry (Lynam and Miller, 2004), but impulsivity is multi-faceted, and it is not clear whether some specific aspects of it rather than others are particularly linked to aggression. Whiteside and Lynam (2001) conducted a factor analysis on some of the more commonly used impulsivity measures. This revealed a four-factor structure to which Cyders et al. (2007) later added a fifth. The factors were negative urgency (NU), lack of premeditation (Prem), lack of perseverance (Pers), sensation seeking (SS) and positive urgency (PU). These underpinned the five dispositions leading to impulsive behaviour of the UPPS-P scale which are NU, which covers a tendency to experience strong impulses under conditions of negative affect; (lack of) Prem, which encompasses the (in)ability to think and reflect on the consequences of an act before engaging; (lack of) Pers, implying an individual’s (in) ability to remain focused on a task that may be boring or difficult; SS, which relates to the tendency to enjoy and pursue exciting or new activities that may or may not be dangerous and PU, which covers a tendency to act rashly or maladaptively in response to positive mood. NU and PU may reflect a state of heightened arousal; Prem and Pers are both dimensions of impaired executive functions, and SS reflects an enhanced need for thrills. Some studies have found strong ties between NU and PU and Prem and Pers (Derefinko et al., 2011; Billieux et al., 2012). An enhanced state of arousal, impaired executive functioning and need for thrills all seem to increase the susceptibility to become aggressive. Repeatedly, UPPS-P scales – especially NU – have been found to be related to outwardly directed aggression (NU – Miller et al., 2003; NU, Prem, SS – Derefinko et al., 2011; NU, SS – Miller et al., 2012; NU, PU – Dvorak et al., 2013). These results, however, are based on non-clinical, mostly student, samples with a self-report measure of aggression rather than actual physical violence. Our aim was to explore the predictive power of the five domains of selfreported impulsivity on physical and non-physical aggressive behaviour by patients resident in a specialist forensic low-security hospital unit. The main research question was the following: What is the association between severe
Copyright © 2015 John Wiley & Sons, Ltd.
(2015) DOI: 10.1002/cbm
Predicting aggression by self-reported impulsivity
physical and non-physical aggression and five different aspects of self-reported impulsivity as measured with the UPPS-P scale? We were particularly interested in prediction of serious physical violence – during the first 12 weeks of admission to the unit as well as longer term. Methods Sample All detained patients resident in a forensic psychiatric hospital, with 78 beds over eight wards, were included. The instruments The Dutch UPPS-P
We translated the original UPPS-P from Whiteside and Lynam (2001) and Cyders et al. (2007) into Dutch. We are currently investigating the psychometric properties of the translated scale in a Dutch sample. Scoring was performed in such a way that higher scores on each subscale reflect more impulsivity. The UPPS-P was included within routine psychological screening. When patients were unable to complete the rating on their own for any reason, including low intelligence, staff provided support for them to do so. The response rate was 95% in testable patients. The Social Dysfunction and Aggression Scale (SDAS-11) Aggression and violence was measured by the SDAS-11 (Wistedt et al., 1990; see also Kobes et al., 2012), which is an 11-item instrument to aid systematic recording of staff observations of socially inappropriate and/or aggressive behaviours along a 4-point scale ranging from not present to extremely severe. The Dutch version of the SDAS was found to have a good convergent validity and moderate inter-rater reliability in a study with maximum security hospital patients in the Netherlands (Kobes et al., 2012). We made two adjustments in order to customise the SDAS-11 to our setting, by adapting scoring principles as formulated in the manual of the SDAS-21 (European Rating Aggression Group, 1992) to the SDAS-11. The first adjustment was that nurses scored every item twice instead of once – first on behaviour in general and secondly on the most extreme behaviour. The second adjustment was that we wrote a manual in which we provided detailed guidance on the scoring rules 0, 1, 2, 3 or 4 for each item and clarified how to make the general and peak scores. In this way, we tried to reduce subjectivity. We were only interested in serious violence and therefore restricted our analyses to SDAS scores of 3 (severe) and 4 (very severe). At the end of every week, nurses entered scores into a central database. Programming was performed
Copyright © 2015 John Wiley & Sons, Ltd.
(2015) DOI: 10.1002/cbm
Bousardt et al.
in a way that forms could not be saved with any missing or erroneous data. Every week, the database was checked and in case of a missing patient, nurses were asked to complete a record for him/her. The SDAS was completed weekly from 2nd July 2012 until 8th December 2013. Over the same period, we produced patient-oriented three monthly output graphs for the staff that could be used in treatment planning, thus motivating completion of data collection. Illustrative items from the UPPS-P and the SDAS are shown in the appendix. Data organisation Two samples were analysed. The first contained all patients who completed the UPPS-P and used all available SDAS assessments of that patient after the administration date of the UPPS-P. The second sample was a subsample of the first, consisting only of newly admitted patients and SDAS assessments gathered for a maximum of 12 weeks after the UPPS-P administration. This allowed investigation of the predictive value of the UPPS-P for the first period of admission, which has a predominantly clinical value for inpatient management. We aggregated SDAS information to a measure of physical aggression at a patient level, by computing the number of assessments on which a patient scored at least once a 3 or 4 as peak value SDAS items 7, 8 or 10. These three items are measuring outwardly directed physical aggression to staff, other people and/or things and had previously been found to form a separate (physical aggression) factor in the factor analysis performed by Kobes et al. (2012) on Dutch SDAS data. Similarly, aggregated counts of non-physical aggression were calculated using the peak value of the SDAS items 1–6. Also, the total number of SDAS questionnaires gathered was counted. This information was merged into background information including age, gender, ethnic minority, mental disorders and medication. Statistical analysis In both conditions (all patients and newly admitted patients), we performed a Poisson regression multivariable analysis with all UPPS-P scales and background characteristics (with at least 20 cases in the lowest cell) as predictors. Two outcome variables were included: the number of weeks with severe physical violence as well as the number of weeks with severe non-physical aggression. The total number of weeks was used as offset in the Poisson regression model, allowing correction for the time at risk (resident in the hospital). We used forward entry and backward deselection regression procedures to create the best model for both severe physical and non-physical aggression. This procedure, similar to the method described by Hosmer and Lemeshow (2000), entails performing the Poisson analysis with one predictor at the time (bivariate), relating it to the previously mentioned outcome variables. Variables with a maximum p-value of 0.25 were
Copyright © 2015 John Wiley & Sons, Ltd.
(2015) DOI: 10.1002/cbm
Predicting aggression by self-reported impulsivity
considered to be relevant for the initial model in the backward deselection procedure. The next step is removing the predictor with the highest p-value from the model repetitively until all predictors showed p-value of under 0.05. The model fit was investigated with the McFadden pseudo R2. While including variables into the model, we inspected possible co-linearity. Results General characteristics Table 1 displays the general characteristics of the total sample, which consisted of 74 forensic psychiatric patients and of the subsample of 27 newly admitted forensic psychiatric patients. The following characteristics were sufficiently present in our total sample (lowest cell at least 20) and were further considered in the total sample analyses: psychotic disorder, substance abuse disorder, pervasive developmental disorder, personality disorder, under treatment with antipsychotics, and under treatment with benzodiazepines. 2472 SDAS weekly assessments were collected, providing an average of 34 (range 1–70) per patient. In the admission subsample, 181 weekly SDAS assessments were collected, providing an average of 7 per patient (range 1–12). Impulsivity and aggression measures Table 2 shows the number of patients scoring at least 3 on any of the nonphysical aggression items or the physical violence items during all weeks as well as the means and standard deviations of scores for these acts. In order to understand the distribution of the UPPS-P subscale scores, we calculated the number of patients scoring at least 3.00 on the UPPS-P subscales; this threshold is not used in any further analyses. The table shows that non-physical aggression was approximately 10 times as prevalent as physical violence in the full sample but just seven times as prevalent in the admission subsample. Poisson regression analyses Tables 3 and 4 show the final Poisson regression models for serious non-physical and physical violence respectively, and in each for the total sample and for the subsample of newly admitted patients separately. In the total sample, all UPPSP subscales, substance abuse disorder and personality disorder were statistically significant predictors for serious non-physical aggression. Pers and SS were inversely related, indicating that the more perseverance and the less sensation seeking behaviour a person reported, the more likely it was that this person (on average) would commit at least one serious act of non-physical aggression. The incidence rate ratio (IRR) of 0.55 indicates that for every additional point
Copyright © 2015 John Wiley & Sons, Ltd.
(2015) DOI: 10.1002/cbm
Bousardt et al.
Table 1: Background characteristics of the investigated samples
Mean age (SD) [range] Males Ethnic minority Mental disorder axis I Psychotic disorder Substance abuse disorder Pervasive developmental disorder Impulse-control disorder and ADHD Mental disorder axis II Mental retardation Personality disorder Medication use None Antidepressants Mood stabilisers Antipsychotics Benzodiazepines Stimulant medication Other medication and medication p.r.n. (including non-psychiatric medication) Number of SDAS assessments
Total sample (n = 74)
Newly admitted patients (n = 27)
n
n
%
35 (12) [18–69] 65 88 16 22
%
34 (13) [18–63] 24 89 7 26
27 36 23 14
37 49 31 19
7 17 7 6
26 63 26 22
18 35
24 47
7 14
26 52
9 15 9 42 30 11 49
12 20 12 57 41 15 66
3 7 2 14 6 6 16
11 26 7 52 22 22 59
2472
181
SD, Standard Deviation; ADHD, Attention Deficit Hyperactivity Disorder; p.r.n, when necessary; SDAS, Social Dysfunction and Aggression Scale.
on Pers, the person was estimated to go for 0.55 fewer weeks of serious nonphysical aggression, when keeping all other variables constant. Each additional point on NU, Prem and PU would be expected to be accompanied by 1.30– 1.67 more weeks of severe non-physical aggression, assuming the other variables to be stable. Finally, a patient who had a substance abuse or personality disorder was estimated to show serious non-physical aggression 1.44–1.67 times more often than patients without such disorders, assuming other variables to be stable. For the subsample of newly admitted patients, only NU predicted serious non-physical aggression, with an IRR of 1.46; here, background characteristics could not be included because of the small sample size. In the total sample, serious physical violence was significantly related to NU (IRR: 3.18) and with personality disorder (IRR: 1.74). For newly admitted patients alone, NU remained significantly related, with an IRR of 3.07; once again, for this subsample, background characteristics could not be included because of the small sample size. The results suggest that an increase of one point on NU
Copyright © 2015 John Wiley & Sons, Ltd.
(2015) DOI: 10.1002/cbm
Copyright © 2015 John Wiley & Sons, Ltd.
(1–4) (1–3) (1–3) (1–4) (1–4)
Negative urgency (NU) Lack of premeditation (Prem) Lack of perseverance (Pers) Sensation seeking (SS) Positive urgency (PU)
n assessments above thresholda
5.42 (5.76) 663 (27%) 0.18 (0.89) 66b (2.7%) Total sample Range n weeks Mean amount of weeks (SD) 0-44 9.35 (10.0) 0-10 0.93 (1.73) 1-69 34.3 (20.4) Mean (SD) Cases above thresholda 2.41 (0.74) 19 (26%) 1.95 (0.47) 1 (1%) 2.05 (0.49) 3 (4%) 2.40 (0.75) 17 (23%) 1.95 (0.74) 5 (7%)
Mean (SD) sum of scores
Total sample
27 27 27 27 27
27 27 27 n
n
181 181
n
n assessments above thresholda
7.64 (6.35) 70 (39%) 0.30 (1.16) 10c (5.5%) Newly admitted patients Range n weeks Mean amount of weeks (SD) 0-9 2.59 (2.50) 0-3 0.37 (0.84) 1-12 6.70 (2.74) Mean (SD) Cases above thresholda 2.59 (0.80) 10 (37%) 2.08 (0.45) 1 (4%) 2.09 (0.49) 1 (4%) 2.34 (0.79) 7 (26%) 2.05 (0.81) 3 (11%)
Mean (SD) sum of scores
Newly admitted patients
The threshold for the SDAS scales holds that at least 1 week during the whole period, at least one of the subitems had a score of 3 or 4. The threshold for the UPPS-P scales holds that someone had an average item score of at least 3.00. b Of the 66 assessments of severe physical aggression 38% were because of or including severe aggression towards people. The other 62% of severe aggression were solely addressed towards things. c Of the 10 assessments of severe physical aggression, 40% were because of or including severe aggression towards people. The other 60% of severe aggression were solely addressed towards things. SDAS, Social Dysfunction and Aggression Scale; UPPS-P, Urgency, Premeditation, Perseverance, Sensation seeking, Positive Urgency; SD, Standard Deviation.
a
Range 74 73 74 74 73
74 74 74 n
Severe non-physical aggression Severe physical aggression Exposure time UPPS-P subscale (average per item)
2472 2472
n
n
(0–24) (0–12)
Range sum of scores
Non-physical aggression (item 1–6) Physical aggression (item 7 + 8 + 10) Patient level SDAS subscales
SDAS subscales
Assessment level
Table 2: Descriptive statistics of the SDAS and UPPS-P subscales
Predicting aggression by self-reported impulsivity
(2015) DOI: 10.1002/cbm
Copyright © 2015 John Wiley & Sons, Ltd.
1.30 p = 0.002 1.67 p < 0.001 0.55 p < 0.001 0.71 p < 0.001 1.36 p < 0.001 1.44 p < 0.001 n/a 1.67 p < 0.001 McFadden R2 = 0.23
1.48 p < 0.001 1.58 p < 0.001 1.22 p = 0.008 0.89 p = 0.034 1.38 p < 0.001 0.88 p = 0.110 1.64 p < 0.001 0.91 p = 0.253 1.64 p < 0.001 0.79 p = 0.002 1.14 p = 0.089
1.46 p = 0.015 1.55 p = 0.072 1.11 p = 0.666 0.89 p = 0.449 1.11 p = 0.503 n/a n/a n/a n/a n/a n/a
Bivariate analysis Severe non-physical aggr.
1.46 p = 0.015 n/a n/a n/a n/a n/a n/a n/a n/a n/a McFadden R2 = 0.05
Multivariate analysis Severe non-physical aggr.
Newly admitted patients (n = 27)
Predictors were not applicable (n/a) when the bivariate regression analysis yielded a p-value of more than 0.25. Background characteristics were not applicable for the 12 weeks sample because of a low n. A hyphen means that the predictor was excluded during the backward deselection procedure. aggr., aggression; develop., developmental.
Negative urgency (NU) Lack of premeditation (Prem) Lack of perseverance (Pers) Sensation seeking (SS) Positive urgency (PU) Psychotic disorder Substance abuse disorder Pervasive develop. disorder Personality disorder Antipsychotics Benzodiazepines
Predictor
Multivariate analysis Severe non-physical aggr.
Bivariate analysis Severe non-physical aggr.
Total sample (n = 74)
Table 3: Incidence rate ratios (IRR) and p-values of the bivariate analyses and the final model of the multivariate Poisson regression analyses for severe nonphysical aggression
Bousardt et al.
(2015) DOI: 10.1002/cbm
Copyright © 2015 John Wiley & Sons, Ltd.
Multivariate analysis Severe physical aggr. 3.18 p < 0.001 n/a 1.74 p = 0.034 n/a McFadden R2 = 0.23
Bivariate analysis Severe physical aggr.
3.43 p < 0.001 2.57 p < 0.001 2.40 p < 0.001 1.27 p = 0.157 2.41 p < 0.001 1.08 p = 0.758 1.79 p = 0.019 0.65 p = 0.128 2.17 p = 0.003 0.88 p = 0.583 1.54 p = 0.076 3.07 1.93 2.65 1.94 1.98
p = 0.021 p = 0.301 p = 0.149 p = 0.096 p = 0.066 n/a n/a n/a n/a n/a n/a
Bivariate analysis Severe physical aggr.
3.07 p = 0.021 n/a n/a n/a n/a n/a n/a n/a McFadden R2 = 0.15
Multivariate analysis Severe physical aggr.
Newly admitted patients (n = 27)
Predictors were not applicable (n/a) when the bivariate regression analysis yielded a p-value of more than 0.25. Background characteristics were not applicable for the 12 weeks sample because of a low n. A hyphen means that the predictor was excluded during the backward deselection procedure. aggr., aggression; develop., developmental.
Negative urgency (NU) Lack of premeditation (Prem) Lack of perseverance (Pers) Sensation seeking (SS) Positive urgency (PU) Psychotic disorder Substance abuse disorder Pervasive develop. disorder Personality disorder Antipsychotics Benzodiazepines
Predictor
Total sample (n = 74)
Table 4: Incidence rate ratios (IRR) and p-values of the bivariate analyses and the final model of the multivariate Poisson regression analyses for severe physical aggression
Predicting aggression by self-reported impulsivity
(2015) DOI: 10.1002/cbm
Bousardt et al.
corresponds to three times the number of weeks with serious physical violence aggression, regardless of time frame. The models for the total sample fit equally well for non-physical aggression and physical violence. For the newly admitted patient sample, the fit was better for the model including physical violence than for the model containing non-physical aggression. Post hoc analyses A post hoc analysis was performed to understand why the positive relationship between Pers and severe non-physical aggression apparent in the bivariate model turned into a negative relationship in the final model. This analysis showed that adding NU and Prem together explained most of the change in this relationship: the IRR of Pers changed from IRR of 1.22 (p = 0.008) in the bivariate model to an IRR of 0.736 (p = 0.001) when controlling for these two factors. Discussion In this study, we investigated which aspects of impulsivity – as measured with the UPPS-P self-report scale – were associated with seriously non-physical aggression and/or physical violence in a sample of forensic psychiatric inpatients. NU alone proved to be a good predictor for serious physical violence early and later in an admission to a secure hospital. Its longer term predictive value was slightly enhanced when personality disorder was brought into the equation. For serious non-physical aggression, all UPPS-P subscales added predictive power as well as the diagnoses ‘substance abuse disorder’ and ‘personality disorder’. High scores on NU reflect an inability to cope with rejection, disappointment and undesired feelings, which patients with cluster B-personality characteristics, such as narcissistic and borderline traits, may find particularly difficult. Therapeutically, this could mean that cognitive-behavioural therapy strongly focusing on management of disappointment and feelings of rejection may help reduce aggression by such patients. Against expectation, Pers and SS were associated with less non-physical aggression rather than more. Although serious non-physical aggression within the first 12 weeks after admission was predicted by NU, the model fit implied a weak association. These findings are partly in line with other studies, already highlighted in the introduction (NU – Miller et al., 2003; NU, Prem, SS – Derefinko et al., 2011; NU, SS – Miller et al., 2012; NU, PU – Dvorak et al., 2013), but in the Miller group’s study, SS was associated with an increase in aggression, not a decrease. Then, too, in their meta-analytic review, Wilson and Scarpa (2011) found that SS was either positively associated with aggression or not related at all, depending on the population, so we did not expect it to be inversely related to serious non-physical aggression. The difference between our
Copyright © 2015 John Wiley & Sons, Ltd.
(2015) DOI: 10.1002/cbm
Predicting aggression by self-reported impulsivity
study and these earlier studies is that our study participants were all seriously ill people resident in a secure hospital rather than mostly healthy subjects. It may be that forensic psychiatric inpatients showing high SS before admission may, at least temporarily, not be interested in SS because of the impact of the admission on their state of mind. Another important difference between our study and most previous work is that we measured aggression through direct observation rather than self-report. Pers has not yet been linked to aggressive behaviour. Our findings imply a complex association between this domain and others for forensic psychiatric patients. When considered in isolation, this trait was associated with an increased risk of serious non-physical aggression, but when NU and Prem were included in the model, Pers was associated with a reduction in serious non-physical aggression. An explanation may be that, in general, patients without perseverance are more verbally aggressive because they are frustrated by being unable to finish projects they have started. Among those with high NU, however, frustration may be related to other variables, like rejection. In that case, failure to persevere may protect against becoming non-physically aggressive. A similar explanation may apply to patients who show little or no premeditation for their actions, perhaps reflecting flexibility or a more carefree attitude. Clinically, the most important UPPS-P scale for people resident in forensic mental health services seems to be NU. This trait incorporates responses like ‘I often make matters worse because I act without thinking when I am upset’, ‘Sometimes when I feel bad, I can’t seem to stop what I am doing even though it is making me feel worse’ and ‘When I feel rejected, I will often say things that I later regret’. These are items that reflect an inability to cope with rejection, disappointment and undesired feelings. It seems reasonable to assume that when patients are rating themselves according to this scale, they will take their past aggressive outbursts as a reference point. In this way, past aggressive behaviour is indirectly explaining future aggressive behaviour. Physically violent outbursts often emerge in the context of inability to cope with rejection, disappointments or negative feelings, and our findings offer further weight to that observation – suggesting that it is important clinically to meet needs arising to address this coping deficit. A strength of our study was the thorough measurement of our outcome variable, aggression. By digitally incorporating the SDAS-11 in our treatment setting, we could use weekly aggression data for each patient that had been collected for up to a year. We thus managed to limit missing values to a minimum and distinguish clearly and consistently between forms of aggression. A possible disadvantage of the UPPS-P is its reliance on self-report, which could increase the risk of invalid scores because of poor insight and/or socially desirable scoring. Among involuntarily admitted psychiatric patients, as in forensic psychiatry, this may be a limiting problem (Junger-Tas and Marshall, 1999). Even so, answers that patients gave predicted serious physical violence. The
Copyright © 2015 John Wiley & Sons, Ltd.
(2015) DOI: 10.1002/cbm
Bousardt et al.
predictive value of the UPPS-P might be improved with control for self-reporting bias, particularly with subgroups of patients with more difficulty reflecting on themselves than others, for example, those with psychosis or intellectual disability who may be too cognitively impaired to do so. In the future too, a larger sample will be needed to allow stratification on diagnosis, and diagnostically sensitive cutoff score guidance may be possible. The converse may also, however, be true – that patients recognise traits in themselves that are not obvious to others – so ideally, self-report and observations might be combined.
Conclusion We found a moderately robust relationship between self-reported negative urgency (UPPS-P NU scale) and later serious physical violence in a sample of forensic psychiatric patients, which would help identify the most risky patients within the first 12 weeks of admission as well as later in their hospital career. Our future work will focus on creating accurate cut-off scores to help clinicians in their risk management.
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Predicting aggression by self-reported impulsivity
Miller J, Flory K, Lynam D, Leukefeld C (2003) A test of the four-factor model of impulsivity-related traits. Personality and Individual Differences 34: 1403–1418. DOI: 10.1016/S0191-8869(02)00122-8 Miller JD, Zeichner A, Wilson LF (2012) Personality correlates of aggression: evidence from measures of the five-factor model, UPPS model of impulsivity, and BIS/BAS. Journal of Interpersonal Violence 27: 2903–2919. DOI: 10.1177/0886260512438279 Nijman H, Bowers L, Old N, Jansen G (2005) Psychiatric nurses’ experiences with inpatient aggression. Aggressive Behavior 31: 217–227. DOI: 10.1002/ab.20038 Vruwink FJ, Noorthoorn EO, Nijman HLI, Van Der Nagel JEL, Hox JJ, Mulder CL (2012) Determinants of seclusion after aggression in psychiatric patients. Archives of Psychiatric Nursing 26: 307–315. DOI: 10.1016/j.apnu.2011.10.004 Whiteside SP, Lynam DR (2001) The five factor model and impulsivity: using a structural model of personality to understand impulsivity. Personality and Individual Differences 30: 669–689. DOI: 10.1016/S0191-8869(00)00064-7 Wilson LC, Scarpa A (2011) The link between sensation seeking and aggression: a meta-analytic review. Aggressive Behavior 37: 81–90. DOI: 10.1002/ab.20369 Wistedt B, Rasmussen A, Pedersen L, Malm U, Träskman-Bendz L, Wakelin J, Bech P (1990) The development of an observer-scale for measuring social dysfunction and aggression. Pharmacopsychiatry 23: 249–252. DOI: 10.1055/s-2007-1014514
Address correspondence to: Annelea M. C. Bousardt, Forensic Psychiatric Department ‘de Boog’, GGNet, Postbus 2003, 7230 GC, Warnsveld, Netherlands. Email: [email protected] Appendix: Examples of UPPS-P items NU 17. When I feel bad, I will often do things I later regret in order to make myself feel better now. Prem 28. I tend to value and follow a rational, ‘sensible’ approach to things. Pers 9. I tend to give up easily. SS 31. I welcome new and exciting experiences and sensations, even if they are a little frightening and unconventional. PU 5. When I am very happy, I can’t seem to stop myself from doing things that can have bad consequences. SDAS-11 items Non-physical aggression 1. Non-directed verbal aggressiveness (general shouting, screaming, swearing) 5. Dysphoric mood (angry, quick to misinterpret) Physical aggression 7. Physical violence to personnel (kicking, beating, etc.) 10. Physical violence to things (kicking furniture, destroying things)
Copyright © 2015 John Wiley & Sons, Ltd.
(2015) DOI: 10.1002/cbm
Predicting inpatient aggression by self-reported impulsivity in forensic psychiatric patients
ANNELEA M. C. BOUSARDT1, ADRIAAN W. HOOGENDOORN2, ERIC O. NOORTHOORN1,3, JACOBUS W. HUMMELEN1,4 AND HENK L. I. NIJMAN3,5, 1Forensic Psychiatric Department ‘de Boog’, GGNet, Warnsveld, Netherlands; 2Department of Psychiatry and the EMGO+ Institute for Health and Care Research, VU University Medical Center Amsterdam, Amsterdam, Netherlands; 3Altrecht Aventurijn, Den Dolder, Netherlands; 4Department Criminal Law and Criminology, University of Groningen, Groningen, Netherlands; 5Radboud University Nijmegen, Behavioural Science Institute, Nijmegen, Netherlands ABSTRACT Background Empirical knowledge of ‘predictors’ of physical inpatient aggression may provide staff with tools to prevent aggression or minimise its consequences. Aim To test the value of a self-reported measure of impulsivity for predicting inpatient aggression. Methods Self-report measures of different domains of impulsivity were obtained using the Urgency, Premeditation, Perseverance, Sensation seeking, Positive urgency (UPPS-P) impulsive behaviour scale with all 74 forensic psychiatric inpatients in one low-security forensic hospital. Aggressive incidents were measured using the Social Dysfunction and Aggression Scale (SDAS). The relationship between UPPS-P subscales and the number of weeks in which violent behaviour was observed was investigated by Poisson regression. Results The impulsivity domain labelled ‘negative urgency’ (NU), in combination with having a personality disorder, predicted the number of weeks in which physical aggression was observed by psychiatric nurses. NU also predicted physical aggression within the first 12 weeks of admission. Conclusions and implications for practice The results indicate that NU, which represents a patient’s inability to cope with rejection, disappointments or other undesired feelings, is associated with a higher likelihood of becoming violent while an inpatient. This specific coping deficit should perhaps be targeted more intensively in therapy. Selfreported NU may also serve as a useful adjunct to other risk assessment tools and as an indicator of change in violence risk. Copyright © 2015 John Wiley & Sons, Ltd.
Copyright © 2015 John Wiley & Sons, Ltd.
(2015) DOI: 10.1002/cbm
Bousardt et al.
Introduction Inpatient aggression may pose a serious threat to the physical and mental wellbeing of psychiatric caregivers and/or other patients. In extreme cases, it may cause severe injury and staff sick leave (Nijman et al., 2005). Furthermore, aggression is often followed by coercive measures. Vruwink et al. (2012) showed that more than 40% of the aggressive incidents were followed by seclusion. Reduction of inpatient aggression may, therefore, reduce both emotional and physical harm. The identification of predictive factors for aggression may provide staff with tools to prevent it. Links between impulsivity and aggression are well established (Gordon and Egan, 2011), in particular, when emotional arousal is increasing, the inability to resist acting on one’s impulses may trigger serious aggressive incidents. This may explain why impulsivity is one of the most investigated constructs in forensic psychiatry (Lynam and Miller, 2004), but impulsivity is multi-faceted, and it is not clear whether some specific aspects of it rather than others are particularly linked to aggression. Whiteside and Lynam (2001) conducted a factor analysis on some of the more commonly used impulsivity measures. This revealed a four-factor structure to which Cyders et al. (2007) later added a fifth. The factors were negative urgency (NU), lack of premeditation (Prem), lack of perseverance (Pers), sensation seeking (SS) and positive urgency (PU). These underpinned the five dispositions leading to impulsive behaviour of the UPPS-P scale which are NU, which covers a tendency to experience strong impulses under conditions of negative affect; (lack of) Prem, which encompasses the (in)ability to think and reflect on the consequences of an act before engaging; (lack of) Pers, implying an individual’s (in) ability to remain focused on a task that may be boring or difficult; SS, which relates to the tendency to enjoy and pursue exciting or new activities that may or may not be dangerous and PU, which covers a tendency to act rashly or maladaptively in response to positive mood. NU and PU may reflect a state of heightened arousal; Prem and Pers are both dimensions of impaired executive functions, and SS reflects an enhanced need for thrills. Some studies have found strong ties between NU and PU and Prem and Pers (Derefinko et al., 2011; Billieux et al., 2012). An enhanced state of arousal, impaired executive functioning and need for thrills all seem to increase the susceptibility to become aggressive. Repeatedly, UPPS-P scales – especially NU – have been found to be related to outwardly directed aggression (NU – Miller et al., 2003; NU, Prem, SS – Derefinko et al., 2011; NU, SS – Miller et al., 2012; NU, PU – Dvorak et al., 2013). These results, however, are based on non-clinical, mostly student, samples with a self-report measure of aggression rather than actual physical violence. Our aim was to explore the predictive power of the five domains of selfreported impulsivity on physical and non-physical aggressive behaviour by patients resident in a specialist forensic low-security hospital unit. The main research question was the following: What is the association between severe
Copyright © 2015 John Wiley & Sons, Ltd.
(2015) DOI: 10.1002/cbm
Predicting aggression by self-reported impulsivity
physical and non-physical aggression and five different aspects of self-reported impulsivity as measured with the UPPS-P scale? We were particularly interested in prediction of serious physical violence – during the first 12 weeks of admission to the unit as well as longer term. Methods Sample All detained patients resident in a forensic psychiatric hospital, with 78 beds over eight wards, were included. The instruments The Dutch UPPS-P
We translated the original UPPS-P from Whiteside and Lynam (2001) and Cyders et al. (2007) into Dutch. We are currently investigating the psychometric properties of the translated scale in a Dutch sample. Scoring was performed in such a way that higher scores on each subscale reflect more impulsivity. The UPPS-P was included within routine psychological screening. When patients were unable to complete the rating on their own for any reason, including low intelligence, staff provided support for them to do so. The response rate was 95% in testable patients. The Social Dysfunction and Aggression Scale (SDAS-11) Aggression and violence was measured by the SDAS-11 (Wistedt et al., 1990; see also Kobes et al., 2012), which is an 11-item instrument to aid systematic recording of staff observations of socially inappropriate and/or aggressive behaviours along a 4-point scale ranging from not present to extremely severe. The Dutch version of the SDAS was found to have a good convergent validity and moderate inter-rater reliability in a study with maximum security hospital patients in the Netherlands (Kobes et al., 2012). We made two adjustments in order to customise the SDAS-11 to our setting, by adapting scoring principles as formulated in the manual of the SDAS-21 (European Rating Aggression Group, 1992) to the SDAS-11. The first adjustment was that nurses scored every item twice instead of once – first on behaviour in general and secondly on the most extreme behaviour. The second adjustment was that we wrote a manual in which we provided detailed guidance on the scoring rules 0, 1, 2, 3 or 4 for each item and clarified how to make the general and peak scores. In this way, we tried to reduce subjectivity. We were only interested in serious violence and therefore restricted our analyses to SDAS scores of 3 (severe) and 4 (very severe). At the end of every week, nurses entered scores into a central database. Programming was performed
Copyright © 2015 John Wiley & Sons, Ltd.
(2015) DOI: 10.1002/cbm
Bousardt et al.
in a way that forms could not be saved with any missing or erroneous data. Every week, the database was checked and in case of a missing patient, nurses were asked to complete a record for him/her. The SDAS was completed weekly from 2nd July 2012 until 8th December 2013. Over the same period, we produced patient-oriented three monthly output graphs for the staff that could be used in treatment planning, thus motivating completion of data collection. Illustrative items from the UPPS-P and the SDAS are shown in the appendix. Data organisation Two samples were analysed. The first contained all patients who completed the UPPS-P and used all available SDAS assessments of that patient after the administration date of the UPPS-P. The second sample was a subsample of the first, consisting only of newly admitted patients and SDAS assessments gathered for a maximum of 12 weeks after the UPPS-P administration. This allowed investigation of the predictive value of the UPPS-P for the first period of admission, which has a predominantly clinical value for inpatient management. We aggregated SDAS information to a measure of physical aggression at a patient level, by computing the number of assessments on which a patient scored at least once a 3 or 4 as peak value SDAS items 7, 8 or 10. These three items are measuring outwardly directed physical aggression to staff, other people and/or things and had previously been found to form a separate (physical aggression) factor in the factor analysis performed by Kobes et al. (2012) on Dutch SDAS data. Similarly, aggregated counts of non-physical aggression were calculated using the peak value of the SDAS items 1–6. Also, the total number of SDAS questionnaires gathered was counted. This information was merged into background information including age, gender, ethnic minority, mental disorders and medication. Statistical analysis In both conditions (all patients and newly admitted patients), we performed a Poisson regression multivariable analysis with all UPPS-P scales and background characteristics (with at least 20 cases in the lowest cell) as predictors. Two outcome variables were included: the number of weeks with severe physical violence as well as the number of weeks with severe non-physical aggression. The total number of weeks was used as offset in the Poisson regression model, allowing correction for the time at risk (resident in the hospital). We used forward entry and backward deselection regression procedures to create the best model for both severe physical and non-physical aggression. This procedure, similar to the method described by Hosmer and Lemeshow (2000), entails performing the Poisson analysis with one predictor at the time (bivariate), relating it to the previously mentioned outcome variables. Variables with a maximum p-value of 0.25 were
Copyright © 2015 John Wiley & Sons, Ltd.
(2015) DOI: 10.1002/cbm
Predicting aggression by self-reported impulsivity
considered to be relevant for the initial model in the backward deselection procedure. The next step is removing the predictor with the highest p-value from the model repetitively until all predictors showed p-value of under 0.05. The model fit was investigated with the McFadden pseudo R2. While including variables into the model, we inspected possible co-linearity. Results General characteristics Table 1 displays the general characteristics of the total sample, which consisted of 74 forensic psychiatric patients and of the subsample of 27 newly admitted forensic psychiatric patients. The following characteristics were sufficiently present in our total sample (lowest cell at least 20) and were further considered in the total sample analyses: psychotic disorder, substance abuse disorder, pervasive developmental disorder, personality disorder, under treatment with antipsychotics, and under treatment with benzodiazepines. 2472 SDAS weekly assessments were collected, providing an average of 34 (range 1–70) per patient. In the admission subsample, 181 weekly SDAS assessments were collected, providing an average of 7 per patient (range 1–12). Impulsivity and aggression measures Table 2 shows the number of patients scoring at least 3 on any of the nonphysical aggression items or the physical violence items during all weeks as well as the means and standard deviations of scores for these acts. In order to understand the distribution of the UPPS-P subscale scores, we calculated the number of patients scoring at least 3.00 on the UPPS-P subscales; this threshold is not used in any further analyses. The table shows that non-physical aggression was approximately 10 times as prevalent as physical violence in the full sample but just seven times as prevalent in the admission subsample. Poisson regression analyses Tables 3 and 4 show the final Poisson regression models for serious non-physical and physical violence respectively, and in each for the total sample and for the subsample of newly admitted patients separately. In the total sample, all UPPSP subscales, substance abuse disorder and personality disorder were statistically significant predictors for serious non-physical aggression. Pers and SS were inversely related, indicating that the more perseverance and the less sensation seeking behaviour a person reported, the more likely it was that this person (on average) would commit at least one serious act of non-physical aggression. The incidence rate ratio (IRR) of 0.55 indicates that for every additional point
Copyright © 2015 John Wiley & Sons, Ltd.
(2015) DOI: 10.1002/cbm
Bousardt et al.
Table 1: Background characteristics of the investigated samples
Mean age (SD) [range] Males Ethnic minority Mental disorder axis I Psychotic disorder Substance abuse disorder Pervasive developmental disorder Impulse-control disorder and ADHD Mental disorder axis II Mental retardation Personality disorder Medication use None Antidepressants Mood stabilisers Antipsychotics Benzodiazepines Stimulant medication Other medication and medication p.r.n. (including non-psychiatric medication) Number of SDAS assessments
Total sample (n = 74)
Newly admitted patients (n = 27)
n
n
%
35 (12) [18–69] 65 88 16 22
%
34 (13) [18–63] 24 89 7 26
27 36 23 14
37 49 31 19
7 17 7 6
26 63 26 22
18 35
24 47
7 14
26 52
9 15 9 42 30 11 49
12 20 12 57 41 15 66
3 7 2 14 6 6 16
11 26 7 52 22 22 59
2472
181
SD, Standard Deviation; ADHD, Attention Deficit Hyperactivity Disorder; p.r.n, when necessary; SDAS, Social Dysfunction and Aggression Scale.
on Pers, the person was estimated to go for 0.55 fewer weeks of serious nonphysical aggression, when keeping all other variables constant. Each additional point on NU, Prem and PU would be expected to be accompanied by 1.30– 1.67 more weeks of severe non-physical aggression, assuming the other variables to be stable. Finally, a patient who had a substance abuse or personality disorder was estimated to show serious non-physical aggression 1.44–1.67 times more often than patients without such disorders, assuming other variables to be stable. For the subsample of newly admitted patients, only NU predicted serious non-physical aggression, with an IRR of 1.46; here, background characteristics could not be included because of the small sample size. In the total sample, serious physical violence was significantly related to NU (IRR: 3.18) and with personality disorder (IRR: 1.74). For newly admitted patients alone, NU remained significantly related, with an IRR of 3.07; once again, for this subsample, background characteristics could not be included because of the small sample size. The results suggest that an increase of one point on NU
Copyright © 2015 John Wiley & Sons, Ltd.
(2015) DOI: 10.1002/cbm
Copyright © 2015 John Wiley & Sons, Ltd.
(1–4) (1–3) (1–3) (1–4) (1–4)
Negative urgency (NU) Lack of premeditation (Prem) Lack of perseverance (Pers) Sensation seeking (SS) Positive urgency (PU)
n assessments above thresholda
5.42 (5.76) 663 (27%) 0.18 (0.89) 66b (2.7%) Total sample Range n weeks Mean amount of weeks (SD) 0-44 9.35 (10.0) 0-10 0.93 (1.73) 1-69 34.3 (20.4) Mean (SD) Cases above thresholda 2.41 (0.74) 19 (26%) 1.95 (0.47) 1 (1%) 2.05 (0.49) 3 (4%) 2.40 (0.75) 17 (23%) 1.95 (0.74) 5 (7%)
Mean (SD) sum of scores
Total sample
27 27 27 27 27
27 27 27 n
n
181 181
n
n assessments above thresholda
7.64 (6.35) 70 (39%) 0.30 (1.16) 10c (5.5%) Newly admitted patients Range n weeks Mean amount of weeks (SD) 0-9 2.59 (2.50) 0-3 0.37 (0.84) 1-12 6.70 (2.74) Mean (SD) Cases above thresholda 2.59 (0.80) 10 (37%) 2.08 (0.45) 1 (4%) 2.09 (0.49) 1 (4%) 2.34 (0.79) 7 (26%) 2.05 (0.81) 3 (11%)
Mean (SD) sum of scores
Newly admitted patients
The threshold for the SDAS scales holds that at least 1 week during the whole period, at least one of the subitems had a score of 3 or 4. The threshold for the UPPS-P scales holds that someone had an average item score of at least 3.00. b Of the 66 assessments of severe physical aggression 38% were because of or including severe aggression towards people. The other 62% of severe aggression were solely addressed towards things. c Of the 10 assessments of severe physical aggression, 40% were because of or including severe aggression towards people. The other 60% of severe aggression were solely addressed towards things. SDAS, Social Dysfunction and Aggression Scale; UPPS-P, Urgency, Premeditation, Perseverance, Sensation seeking, Positive Urgency; SD, Standard Deviation.
a
Range 74 73 74 74 73
74 74 74 n
Severe non-physical aggression Severe physical aggression Exposure time UPPS-P subscale (average per item)
2472 2472
n
n
(0–24) (0–12)
Range sum of scores
Non-physical aggression (item 1–6) Physical aggression (item 7 + 8 + 10) Patient level SDAS subscales
SDAS subscales
Assessment level
Table 2: Descriptive statistics of the SDAS and UPPS-P subscales
Predicting aggression by self-reported impulsivity
(2015) DOI: 10.1002/cbm
Copyright © 2015 John Wiley & Sons, Ltd.
1.30 p = 0.002 1.67 p < 0.001 0.55 p < 0.001 0.71 p < 0.001 1.36 p < 0.001 1.44 p < 0.001 n/a 1.67 p < 0.001 McFadden R2 = 0.23
1.48 p < 0.001 1.58 p < 0.001 1.22 p = 0.008 0.89 p = 0.034 1.38 p < 0.001 0.88 p = 0.110 1.64 p < 0.001 0.91 p = 0.253 1.64 p < 0.001 0.79 p = 0.002 1.14 p = 0.089
1.46 p = 0.015 1.55 p = 0.072 1.11 p = 0.666 0.89 p = 0.449 1.11 p = 0.503 n/a n/a n/a n/a n/a n/a
Bivariate analysis Severe non-physical aggr.
1.46 p = 0.015 n/a n/a n/a n/a n/a n/a n/a n/a n/a McFadden R2 = 0.05
Multivariate analysis Severe non-physical aggr.
Newly admitted patients (n = 27)
Predictors were not applicable (n/a) when the bivariate regression analysis yielded a p-value of more than 0.25. Background characteristics were not applicable for the 12 weeks sample because of a low n. A hyphen means that the predictor was excluded during the backward deselection procedure. aggr., aggression; develop., developmental.
Negative urgency (NU) Lack of premeditation (Prem) Lack of perseverance (Pers) Sensation seeking (SS) Positive urgency (PU) Psychotic disorder Substance abuse disorder Pervasive develop. disorder Personality disorder Antipsychotics Benzodiazepines
Predictor
Multivariate analysis Severe non-physical aggr.
Bivariate analysis Severe non-physical aggr.
Total sample (n = 74)
Table 3: Incidence rate ratios (IRR) and p-values of the bivariate analyses and the final model of the multivariate Poisson regression analyses for severe nonphysical aggression
Bousardt et al.
(2015) DOI: 10.1002/cbm
Copyright © 2015 John Wiley & Sons, Ltd.
Multivariate analysis Severe physical aggr. 3.18 p < 0.001 n/a 1.74 p = 0.034 n/a McFadden R2 = 0.23
Bivariate analysis Severe physical aggr.
3.43 p < 0.001 2.57 p < 0.001 2.40 p < 0.001 1.27 p = 0.157 2.41 p < 0.001 1.08 p = 0.758 1.79 p = 0.019 0.65 p = 0.128 2.17 p = 0.003 0.88 p = 0.583 1.54 p = 0.076 3.07 1.93 2.65 1.94 1.98
p = 0.021 p = 0.301 p = 0.149 p = 0.096 p = 0.066 n/a n/a n/a n/a n/a n/a
Bivariate analysis Severe physical aggr.
3.07 p = 0.021 n/a n/a n/a n/a n/a n/a n/a McFadden R2 = 0.15
Multivariate analysis Severe physical aggr.
Newly admitted patients (n = 27)
Predictors were not applicable (n/a) when the bivariate regression analysis yielded a p-value of more than 0.25. Background characteristics were not applicable for the 12 weeks sample because of a low n. A hyphen means that the predictor was excluded during the backward deselection procedure. aggr., aggression; develop., developmental.
Negative urgency (NU) Lack of premeditation (Prem) Lack of perseverance (Pers) Sensation seeking (SS) Positive urgency (PU) Psychotic disorder Substance abuse disorder Pervasive develop. disorder Personality disorder Antipsychotics Benzodiazepines
Predictor
Total sample (n = 74)
Table 4: Incidence rate ratios (IRR) and p-values of the bivariate analyses and the final model of the multivariate Poisson regression analyses for severe physical aggression
Predicting aggression by self-reported impulsivity
(2015) DOI: 10.1002/cbm
Bousardt et al.
corresponds to three times the number of weeks with serious physical violence aggression, regardless of time frame. The models for the total sample fit equally well for non-physical aggression and physical violence. For the newly admitted patient sample, the fit was better for the model including physical violence than for the model containing non-physical aggression. Post hoc analyses A post hoc analysis was performed to understand why the positive relationship between Pers and severe non-physical aggression apparent in the bivariate model turned into a negative relationship in the final model. This analysis showed that adding NU and Prem together explained most of the change in this relationship: the IRR of Pers changed from IRR of 1.22 (p = 0.008) in the bivariate model to an IRR of 0.736 (p = 0.001) when controlling for these two factors. Discussion In this study, we investigated which aspects of impulsivity – as measured with the UPPS-P self-report scale – were associated with seriously non-physical aggression and/or physical violence in a sample of forensic psychiatric inpatients. NU alone proved to be a good predictor for serious physical violence early and later in an admission to a secure hospital. Its longer term predictive value was slightly enhanced when personality disorder was brought into the equation. For serious non-physical aggression, all UPPS-P subscales added predictive power as well as the diagnoses ‘substance abuse disorder’ and ‘personality disorder’. High scores on NU reflect an inability to cope with rejection, disappointment and undesired feelings, which patients with cluster B-personality characteristics, such as narcissistic and borderline traits, may find particularly difficult. Therapeutically, this could mean that cognitive-behavioural therapy strongly focusing on management of disappointment and feelings of rejection may help reduce aggression by such patients. Against expectation, Pers and SS were associated with less non-physical aggression rather than more. Although serious non-physical aggression within the first 12 weeks after admission was predicted by NU, the model fit implied a weak association. These findings are partly in line with other studies, already highlighted in the introduction (NU – Miller et al., 2003; NU, Prem, SS – Derefinko et al., 2011; NU, SS – Miller et al., 2012; NU, PU – Dvorak et al., 2013), but in the Miller group’s study, SS was associated with an increase in aggression, not a decrease. Then, too, in their meta-analytic review, Wilson and Scarpa (2011) found that SS was either positively associated with aggression or not related at all, depending on the population, so we did not expect it to be inversely related to serious non-physical aggression. The difference between our
Copyright © 2015 John Wiley & Sons, Ltd.
(2015) DOI: 10.1002/cbm
Predicting aggression by self-reported impulsivity
study and these earlier studies is that our study participants were all seriously ill people resident in a secure hospital rather than mostly healthy subjects. It may be that forensic psychiatric inpatients showing high SS before admission may, at least temporarily, not be interested in SS because of the impact of the admission on their state of mind. Another important difference between our study and most previous work is that we measured aggression through direct observation rather than self-report. Pers has not yet been linked to aggressive behaviour. Our findings imply a complex association between this domain and others for forensic psychiatric patients. When considered in isolation, this trait was associated with an increased risk of serious non-physical aggression, but when NU and Prem were included in the model, Pers was associated with a reduction in serious non-physical aggression. An explanation may be that, in general, patients without perseverance are more verbally aggressive because they are frustrated by being unable to finish projects they have started. Among those with high NU, however, frustration may be related to other variables, like rejection. In that case, failure to persevere may protect against becoming non-physically aggressive. A similar explanation may apply to patients who show little or no premeditation for their actions, perhaps reflecting flexibility or a more carefree attitude. Clinically, the most important UPPS-P scale for people resident in forensic mental health services seems to be NU. This trait incorporates responses like ‘I often make matters worse because I act without thinking when I am upset’, ‘Sometimes when I feel bad, I can’t seem to stop what I am doing even though it is making me feel worse’ and ‘When I feel rejected, I will often say things that I later regret’. These are items that reflect an inability to cope with rejection, disappointment and undesired feelings. It seems reasonable to assume that when patients are rating themselves according to this scale, they will take their past aggressive outbursts as a reference point. In this way, past aggressive behaviour is indirectly explaining future aggressive behaviour. Physically violent outbursts often emerge in the context of inability to cope with rejection, disappointments or negative feelings, and our findings offer further weight to that observation – suggesting that it is important clinically to meet needs arising to address this coping deficit. A strength of our study was the thorough measurement of our outcome variable, aggression. By digitally incorporating the SDAS-11 in our treatment setting, we could use weekly aggression data for each patient that had been collected for up to a year. We thus managed to limit missing values to a minimum and distinguish clearly and consistently between forms of aggression. A possible disadvantage of the UPPS-P is its reliance on self-report, which could increase the risk of invalid scores because of poor insight and/or socially desirable scoring. Among involuntarily admitted psychiatric patients, as in forensic psychiatry, this may be a limiting problem (Junger-Tas and Marshall, 1999). Even so, answers that patients gave predicted serious physical violence. The
Copyright © 2015 John Wiley & Sons, Ltd.
(2015) DOI: 10.1002/cbm
Bousardt et al.
predictive value of the UPPS-P might be improved with control for self-reporting bias, particularly with subgroups of patients with more difficulty reflecting on themselves than others, for example, those with psychosis or intellectual disability who may be too cognitively impaired to do so. In the future too, a larger sample will be needed to allow stratification on diagnosis, and diagnostically sensitive cutoff score guidance may be possible. The converse may also, however, be true – that patients recognise traits in themselves that are not obvious to others – so ideally, self-report and observations might be combined.
Conclusion We found a moderately robust relationship between self-reported negative urgency (UPPS-P NU scale) and later serious physical violence in a sample of forensic psychiatric patients, which would help identify the most risky patients within the first 12 weeks of admission as well as later in their hospital career. Our future work will focus on creating accurate cut-off scores to help clinicians in their risk management.
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Predicting aggression by self-reported impulsivity
Miller J, Flory K, Lynam D, Leukefeld C (2003) A test of the four-factor model of impulsivity-related traits. Personality and Individual Differences 34: 1403–1418. DOI: 10.1016/S0191-8869(02)00122-8 Miller JD, Zeichner A, Wilson LF (2012) Personality correlates of aggression: evidence from measures of the five-factor model, UPPS model of impulsivity, and BIS/BAS. Journal of Interpersonal Violence 27: 2903–2919. DOI: 10.1177/0886260512438279 Nijman H, Bowers L, Old N, Jansen G (2005) Psychiatric nurses’ experiences with inpatient aggression. Aggressive Behavior 31: 217–227. DOI: 10.1002/ab.20038 Vruwink FJ, Noorthoorn EO, Nijman HLI, Van Der Nagel JEL, Hox JJ, Mulder CL (2012) Determinants of seclusion after aggression in psychiatric patients. Archives of Psychiatric Nursing 26: 307–315. DOI: 10.1016/j.apnu.2011.10.004 Whiteside SP, Lynam DR (2001) The five factor model and impulsivity: using a structural model of personality to understand impulsivity. Personality and Individual Differences 30: 669–689. DOI: 10.1016/S0191-8869(00)00064-7 Wilson LC, Scarpa A (2011) The link between sensation seeking and aggression: a meta-analytic review. Aggressive Behavior 37: 81–90. DOI: 10.1002/ab.20369 Wistedt B, Rasmussen A, Pedersen L, Malm U, Träskman-Bendz L, Wakelin J, Bech P (1990) The development of an observer-scale for measuring social dysfunction and aggression. Pharmacopsychiatry 23: 249–252. DOI: 10.1055/s-2007-1014514
Address correspondence to: Annelea M. C. Bousardt, Forensic Psychiatric Department ‘de Boog’, GGNet, Postbus 2003, 7230 GC, Warnsveld, Netherlands. Email: [email protected] Appendix: Examples of UPPS-P items NU 17. When I feel bad, I will often do things I later regret in order to make myself feel better now. Prem 28. I tend to value and follow a rational, ‘sensible’ approach to things. Pers 9. I tend to give up easily. SS 31. I welcome new and exciting experiences and sensations, even if they are a little frightening and unconventional. PU 5. When I am very happy, I can’t seem to stop myself from doing things that can have bad consequences. SDAS-11 items Non-physical aggression 1. Non-directed verbal aggressiveness (general shouting, screaming, swearing) 5. Dysphoric mood (angry, quick to misinterpret) Physical aggression 7. Physical violence to personnel (kicking, beating, etc.) 10. Physical violence to things (kicking furniture, destroying things)
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(2015) DOI: 10.1002/cbm
