Journal of Anxiety Disorders 28 (2014) 830–835

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Journal of Anxiety Disorders

Evaluation of the Dimensions of Anger Reactions-5 (DAR-5) Scale in combat veterans with posttraumatic stress disorder David Forbes a,∗ , Nathan Alkemade a , Dale Hopcraft b , Graeme Hawthorne c , Paul O’Halloran b , Jon D. Elhai d , Tony McHugh e , Glen Bates f , Raymond W. Novaco g , Richard Bryant h , Virginia Lewis a,i a

Australian Centre for Posttraumatic Mental Health and Department of Psychiatry, University of Melbourne, Melbourne, VIC, Australia School of Public Health, La Trobe University, Melbourne, VIC, Australia c Department of Psychiatry, University of Melbourne, Melbourne, VIC, Australia d Department of Psychology, University of Toledo, Toledo, OH, USA e Veterans’ Psychiatry Unit, Austin Health, Heidelberg, VIC, Australia f Swinburne University of Technology, Faculty of Life and Social Sciences, Hawthorn, VIC, Australia g Department of Psychology and Social Behavior, University of California, Irvine, Irvine, CA, USA h School of Psychology, University of New South Wales, Sydney, NSW, Australia i Australian Institute for Primary Care & Ageing, La Trobe University, Melbourne, VIC, Australia b

a r t i c l e

i n f o

Article history: Received 1 August 2014 Accepted 25 September 2014 Available online 5 October 2014 Keywords: Anger Trauma DAR Assessment

a b s t r a c t After a traumatic event many people experience problems with anger which not only results in significant distress, but can also impede recovery. As such, there is value to include the assessment of anger in routine post-trauma screening procedures. The Dimensions of Anger Reactions-5 (DAR-5), as a concise measure of anger, was designed to meet such a need, its brevity minimizing the burden on client and practitioner. This study examined the psychometric properties of the DAR-5 with a sample of 163 male veterans diagnosed with Posttraumatic Stress Disorder. The DAR-5 demonstrated internal reliability (˛ = .86), along with convergent, concurrent and discriminant validity against a variety of established measures (e.g. HADS, PCL, STAXI). Support for the clinical cut-point score of 12 suggested by Forbes et al. (2014, Utility of the dimensions of anger reactions-5 (DAR-5) scale as a brief anger measure. Depression and Anxiety, 31, 166–173) was observed. The results support considering the DAR-5 as a preferred screening and assessment measure of problematic anger. © 2014 Published by Elsevier Ltd.

1. Introduction In recent years there has been an increased focus on anger as a common mental health sequelae in people exposed to a potentially traumatic event such as sexual and physical assault (Feeny, Zoellner, & Foa, 2000, 2002; Zoellner, Goodwin, & Foa, 2000), motor vehicle accidents (Mayou, Ehlers, & Bryant, 2002), torture (Ekblad, Prochazka, & Roth, 2002), and exposure to human rights violations (Silove et al., 2009). Difficulties with anger have also been observed in refugees (Hinton, Rasmussen, Nou, Pollack, & Good, 2009) and in 9/11 disaster relief workers (Jayasinghe, Giosan, Evans, Spielman, & Difede, 2008). The prominence of anger as an outcome following traumatic events has been particularly evident in combat veterans, where anger has also been associated with aggression

∗ Corresponding author. Tel.: +61 3 9035 5599/+61 3 9035 5455. E-mail address: [email protected] (D. Forbes). http://dx.doi.org/10.1016/j.janxdis.2014.09.015 0887-6185/© 2014 Published by Elsevier Ltd.

and interpersonal violence (Elbogen, Beckham, Butterfield, Swartz, & Swanson, 2008; McManus, Grey, & Shafran, 2008). Anger and anger-related cognitions also appear to play a significant role in the development and maintenance of key posttraumatic mental health disorders such as posttraumatic stress disorder (PTSD) (Jayasinghe et al., 2008; Koenen, Stellman, Stellman, & Sommer, 2003) with evidence of it attenuating gains in PTSD treatment, most notably in combat veterans (Forbes, Creamer, Hawthorne, Allen, & McHugh, 2003; Forbes et al., 2008). In this context, it is critical to consider screening for anger as part of routine mental health assessment following exposure to potentially traumatic events. Routine assessment of anger requires brief psychometrically robust measures that can be easily inserted into screening batteries and included in longitudinal tracking and surveillance of mental health outcomes following trauma exposure, guiding targeted intervention where appropriate. Major psychometrically established measures of anger, such as the State-Trait Anger Expression Inventory (STAXI: Spielberger,

D. Forbes et al. / Journal of Anxiety Disorders 28 (2014) 830–835

1996) and the Novaco Anger Scale (Novaco, 2003), both extensively validated with clinical populations, are too long to include in routine screening and assessment batteries. To address the need for a brief anger screening tool, the Dimensions of Anger Reactions (DAR) scale, developed by Novaco (1975), was validated by Forbes et al. (2004) against the STAXI in a combat veteran sample. Novaco, Swanson, Gonzalez, Gahm, and Reger (2012) demonstrated its concurrent, discriminant, and incremental validity with behavioral health data for 3528 treatment-seeking soldiers who had been in combat in Iraq and Afghanistan. Forbes et al. (2004) found that the DAR was able to demonstrate sensitivity to change in anger as an outcome of PTSD treatment and that two of its seven items could be removed without compromising psychometric properties. Further, the measure’s 9-point response scale was considered excessive, and a burden for respondents’ decisionmaking (Hawthorne, Mouthaan, Forbes, & Novaco, 2006). Using the five items identifed by Forbes et al. (2004), Hawthorne et al. (2006) reduced the number of response categories from nine to five and reported improved psychometric strength of the modified measure. The shortened scale was referred to as the DAR-5 (5 items and 5 response categories). Forbes et al. (2014) recently validated the DAR-5 in a sample of 486 college students with and without a history of trauma exposure. In this study the DAR-5 demonstrated strong internal reliability and convergent validity with the STAXI-2. Confirmatory factor analysis supported a single factor model of the DAR-5 for the trauma-exposed and non-trauma exposed subsamples. Discriminant validity was evident with depression symptom scores. In order to target the use of the DAR-5 as a screening measure, a screening cut-point score was developed against the STAXI as a marker of anger likely to interfere with function. A screening cut-point of 12 on the DAR-5 successfully differentiated high and low scorers on STAXI-2 Trait Anger and PCL posttraumatic stress scores (Forbes et al., 2014). Results of Forbes et al. (2014) provide support for the use of the DAR-5 in screening for anger when a short and effective scale is required. However given the study tested the DAR-5 in college students, validation of the DAR-5 is needed in a trauma-affected clinical sample to ensure its applicability to patients with psychiatric disorders. Given the prominence of anger associated with PTSD, particularly combat-related PTSD, this study sought to examine the psychometric properties of the DAR-5 in a sample of combat veterans with a lifetime history of PTSD who presented for care at a veterans’ clinical service.

2. Method 2.1. Participants Participants were 163 male veterans who had participated in a hospital based treatment program for combat-related PTSD. Veterans currently engaged in PTSD treatment programs were excluded to avoid response resistance as they were already completing evaluation protocols. Respondents’ ages ranged from 25 to 81 years (M = 59.9; SD = 5.7). Seventy-six percent of the sample was married or in a de-facto relationship, 4% were employed, 11% were retired with the remaining 85% receiving a full incapacity payment. All participants were diagnosed with PTSD upon entering the treatment program using the clinician administered PTSD schedule (CAPS: Blake et al., 1998). At the date of this study one-fifth of the sample no longer met criteria for diagnosis. Participants also reported high levels of comorbidity with depression (65%), another anxiety disorder (58%) and a substance use disorder (31%). Approval was obtained from the relevant University and hospital Ethics Committees.

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2.2. Procedure and measures A mail-out list was created by the treating hospital staff and eligible veterans were mailed a study package. To maintain confidentiality and minimize demand characteristics questionnaires were returned to an independent research centre, where the data were entered into IBM SPSS Statistics 18. 2.2.1. PTSD Checklist (PCL; Weathers, Litz, Herman, Huska, & Keane, 1993) The PCL assesses the presence of trauma-related DSM-IV PTSD symptoms over the past month (Weathers et al., 1993). Symptoms are rated on a Likert scale (1 = not at all, 2 = a little bit, 3 = moderately, 4 = quite a bit, and 5 = extremely). The PCL is reported to have adequate reliability and validity (McDonald & Calhoun, 2010). 2.2.2. Dimensions of Anger Reactions Scale-5 (DAR5, Forbes et al., 2014; based on Novaco’s DAR, 1975) The DAR-5 measures anger with five items which address anger frequency, intensity, duration, aggression and interference with social functioning. Items are scored on a 5-point Likert scale (1 = none of the time, 2 = a little of the time, 3 = some of the time, 4 = most of the time, and 5 = all of the time) generating a scale score ranging from 5 to 25 with higher scores indicative of worse symptomatology (see Table 1). The DAR-5 has high internal consistency with Cronbach’s alpha ranging from .88 to .90 (Forbes et al., 2014; Hawthorne et al., 2006). Additionally, previous studies have established convergent validity against STAXI subscales and discriminant validity against a measure of depression (Forbes et al., 2004, 2014; Hawthorne et al., 2006; Proctor et al., 2009). Novaco et al. (2012) established the validity of the full DAR for combat veterans with multiple self-rated measures of psychological distress, functional difficulties in multiple domains, and violence risk. 2.2.3. State Trait Anger Expression Inventory (STAXI) The STAXI is a 44 item self-report inventory with six scales to assess experience, expression and control of anger (Spielberger, 1988). Items are scored using a 4-point Likert scale (1 = almost never, 2 = sometimes, 3 = often and 4 = almost always). Spielberger found good to very good reliability across the STAXI scales and subscales and good convergent and divergent validity. Spielberger (1988) provides normative adult data for the STAXI: State Anger (14.10), Trait Anger (19.88), Anger-In (15.95), Anger-Out (15.68) and Anger-Control (23.19). No clinical cut-point scores are defined. 2.2.4. Hospital Anxiety and Depression Scale (HADS) The HADS (Zigmond & Snaith, 1983) is a 14-item self-report inventory which assesses anxiety and depression symptoms. Items are scored on a 4-point Likert scale from 0 (not at all) to 3 (very much indeed). The HADS depression scale was used in the present study and ranges in score from 0 to 21. The HADS depression scale has strong psychometric properties, with high internal consistency (˛ = .90) (Zigmond & Snaith, 1983).The HADS anxiety scale was omitted from analyses due to the potential overlap between anger and the arousal properties of anxiety. 2.2.5. Alcohol Use Disorder Identification Test (AUDIT) The AUDIT measures current hazardous and harmful alcohol use and dependence symptoms (Saunders, Aasland, Babor, De la Fuente, & Grant, 1993). The test contains a total of 10 items measured with a Likert-scale. Eight items rated along a 5-point scale (0–4) and two items rated along a 3-point scale (0, 2 and 4). It has high internal consistency, (˛ = .90), and a high test–retest reliability of .86 (Babor, Higgins-Biddle, Saunders, & Monteiro, 2001). Scoring

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D. Forbes et al. / Journal of Anxiety Disorders 28 (2014) 830–835

Table 1 The DAR-5. Thinking over the past four weeks, circle the number under the option that best describes the amount of time you felt that way.

1 2 3 4 5

I found myself getting angry at people or situations When I got angry, I got really mad When I got angry, I stayed angry When I got angry at someone I wanted to hit them My anger prevented me from getting along with people as well as I’d have liked to

None or almost none of the time

A little of the time

Some of the time

Most of the time

All or almost all of the time

1

2

3

4

5

1 1 1

2 2 2

3 3 3

4 4 4

5 5 5

1

2

3

4

5

is through summation yielding a total score range of 0–40, where higher scores indicate more problematic drinking behavior. 2.2.6. Kessler Psychological Distress Scale (K10) The K10 is a global measure of non-specific psychological distress experienced in the previous four weeks (Floyd & Widaman, 1995). The 10-item questionnaire provides a general measure of distress calculated from questions about anxiety and depressive symptoms within the previous four weeks. Response options are 1 = none of the time, 2 = a little of the time, 3 = some of the time, 4 = most of the time and 5 = all of the time. It has high internal consistency (˛ = .93) and very good clinical discrimination (Kessler et al., 2002). 2.2.7. Assessment of Quality of Life (AQoL) The AQoL measures health-related quality of life (Brown, 2006; Hawthorne & Richardson, 2001). The AQoL contains 12 items, each with four levels (ranging from normal health to worst health state) and forms four dimensions; independent living, social relationships, physical senses and psychological well-being. The resulting four dimension scores are then combined into a single score, which is re-weighted, and presented as a utility score on a life-death scale, where the endpoints are −.04 (worse than death equivalent state), .00 (death equivalent state) and 1.00 (best state). A difference of .06 or more between utility scores represents a minimal important difference while a difference of .13 or greater may reflect important differences between groups (Hawthorne & Osborne, 2005). 2.3. Data analysis Missing values (less than 1% of the data) were estimated by calculating the series mean. The level for significance was defined as p < .05 for all statistical analyses and all correlations were calculated using Spearman’s Rho to account for potential skewness. Reliability and validity analyses were conducted using IBM SPSS Statistics 21. The internal properties of the DAR-5 were established through analysis of internal reliability including Cronbach’s alpha and item-total reliability correlations. Next the study examined the convergent, concurrent and discriminant validity of the DAR-5. We examined convergent validity by assessing the correlations of the DAR-5 total score with the STAXI and its subscales. We examined concurrent validity by assessing the relationships between the DAR-5 and STAXI total scores, comparing high and low scorers on the PCL using a cut-point of 50. A cut-point score of 50 on the PCL has been found to optimize diagnostic accuracy in a veteran sample comparable to that of the present study (Forbes, Creamer, & Biddle, 2001), however other cut-points have been previous employed in research (Blanchard, Hickling, Barton, & Taylor, 1996). Given the established relationship between anger and PTSD (Orth & Wieland, 2006), it was expected that the total scores on the DAR-5 and STAXI would be significantly higher where PTSD was present (the high score group).

Discriminant validity was assessed through use of Hotelling’s t-tests for dependant correlations to compare the correlations between the DAR-5 and the STAXI to the correlations between the DAR-5 and measures of depression (HADS depression) and alcohol use (AUDIT). Significant but lower correlations were expected between measures of different constructs (anger and depression or alcohol use) than between measures of the same construct (anger). The last series of analyses sought to test the previously derived cut-point score on the DAR-5 for problematic anger (Forbes et al., 2014). This was done through dividing the participants into high and low scorers on the DAR-5 based on this cut-point of 12, and using t-test analyses to compare scores on the STAXI and associated mental health and quality of life outcome measures. 3. Results The means and standard deviations for the DAR-5 and the STAXI subscales have been provided in Table 2. 3.1. Reliability For the overall sample, the internal consistency for the PCL was ˛ = .88, the STAXI was ˛ = .88, and HADS was ˛ = .83. For the sample, the internal consistency of the DAR-5 was high (˛ = .86). Item-total correlations ranged from .62 to .73. The strongest item-total correlation was for the “intensity” item while the lowest was for the “social relations” item. 3.2. Convergent, concurrent and discriminant validity 3.2.1. Convergent validity Table 3 reports the correlations between the DAR5 and the STAXI. All correlations were highly significant and apart from State Anger (p = .002) all correlations were p < .001. Importantly the correlation with PCL remains strong with the PCL anger item removed. The strongest correlations were found with the STAXI Anger Expression and Trait Anger. As expected, negative correlations were obtained between the DAR-5 and the STAXI-2 Anger Control subscales. 3.2.2. Concurrent validity Participants were divided into two groups based on PCL scores; a High PCL group with scores scoring equal to and greater than 50; and a Low PCL group with scores less than 50. The Low PCL group represented 22% of the sample. The High PCL group had a mean of 62.7 (SD = 7.5) indicating a moderate–severe level of PTSD. The Low PCL group had a mean of 41.9 (SD = 6.2) indicating still significant subclinical symptoms. As seen in Table 2, the Low and High PCL groups were significantly different on each individual DAR-5 item and the DAR-5 total, with scores always higher in the High PCL

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Table 2 Mean scores for DAR-5, STAXI (including subscales) and PCL, for Overall sample (N = 163), Low PCL (N = 36) and High PCL (N = 127). Measure

Overall M (SD)

Low PCL M (SD)

High PCL M (SD)

t-Test

p

DAR-5 Item 1—angry frequency Item 2—anger intensity Item 3—anger duration Item 4—antagonism towards others Item 5—social relations DAR-5 Total

3.6 (.9) 3.4 (1.1) 2.9 (1.1) 2.7 (1.3) 3.2 (1.2) 15.7 (4.4)

3.0 (.8) 2.8 (1.1) 2.5 (.9) 1.9 (.9) 2.4 (.9) 12.6 (3.8)

3.7 (.9) 3.5 (1.1) 3.1 (1.1) 2.9 (1.3) 3.5 (1.1) 16.7 (4.2)

−4.5 −3.5 −3.1 −4.0 −5.5 −5.2