Some 73 adult male offenders in both community and prison settings in South Australia participated in the devel-
opment of the SAM. Of these 49 were in prison and 24 were in the community (reporting to a probation and
parole or community corrections center). The average age of participants was 30.38 years ( SD58.55;
Range519/C060 years) and the average level of education completed was Year 10. The full scale scores exhibited a
high Cronbach alpha coefficient of .91 (cf. Boyle, 1991 ). A subgroup of participants completed the SAM twice
over a two-week interval. The test /C0retest reliability coefficient (.74) suggested that the scores were relatively
stable, but still amenable to change. Correlations between the total SAM score and the subscales of the State /C0trait
Anger Expression Inventory-2 (STAXI-2, Spielberger, 1999 ) were used to assess concurrent validity. Scores on the
total SAM score were moderately associated with those obtained from the Trait Anger subscale of the STAXI
(.33), indicating that the SAM measures a construct that is related to trait anger. Scores were also moderately
correlated with Anger Expression-Out (.58), Anger Control-Out ( /C0.52), and Anger Control-In ( /C0.39) scales of
the STAXI-2, with weaker correlations between the measure and State Anger (.39) and Anger Expression-In (.26).
Anexploratory Principal Axis Factoring with an oblimin rotation was used to assess the factor structure of the
measure. Factor analysis identified two dimensions. The correlation between factors was high (.67) and the
authors suggest that persons administering the measure should use a total scale score. This study suggests that
the SAM may be a useful screening tool for problematic anger when only brief assessment is possible, and as an
outcome measure in treatment evaluation or in assessing changes in anger over time.
FUTURE RESEARCH DIRECTIONS
The aim of this chapter was to provide an overview of some of the most widely used and emerging self-report
measures of anger/hostility in adults. Even a cursory inspection of the 16 self-report measures reviewed in this
chapter shows that in general they do live up to psychometric standards of reliability and validity and are conve-
nient to administer and score. Where the substantive differences exist are in the particular construct of interest
(e.g., anger or hostility, arousal versus expression of anger, and different subtypes of anger). The choice of which
instrument to use is also dictated by the population of interest (e.g., community, psychiatric, forensic). As well,
the selection of a scale/measure hinges on the specific question being posed, whether this be related to classifica-
tion and diagnosis, case conceptualization, making decisions about the course and efficacy of treatment, or testing
hypothesized relationships between anger and other aspects of health and human functioning.
Nevertheless, some measures are lacking in data about test /C0retest reliability. Especially with state /C0trait mea-
sures such as the STAXI-2, it would be expected that the trait scale would exhibit temporal stability whereas the
state scale would exhibit much lower test /C0retest correlations, if it is truly sensitive to situational variability. Also,
there are many different forms of anger and hostility ranging all the way from transitory emotional states,
through longer lasting mood states, through motivational dynamic traits, and finally relatively stable enduring
personality traits.
One ongoing problem is the fact that self-report scales/measures (including those reviewed in this chapter)
are prone to motivational and response distortion. Clearly, a range of factors may be responsible for biased
responding, ranging all the way from deliberate conscious dissimulation to inadequate self-insight and/or lack of
conscious awareness of one’s anger and hostility. Responses to items included in self-report measures of anger
and hostility are easily distorted, and therefore, treatments and interventions based on scores from such scales
need to be considered carefully. One avenue of possible advancement would be to develop objective (T-data) test
measures of anger and hostility, in order to minimize the impact of such conscious or unconscious motivational
biases in responding (cf. Boyle, Stankov, & Cattell, 1995, p. 435; Schuerger, 2008).
A further ongoing problem for many of the self-report anger/hostility measures presented in this chapter, is
that the application of factor analytic methods often leaves much to be desired. A recurring theme is the use of
less than optimal factor analytic methods, particularly the now essentially outmoded principal components anal-
ysis plus varimax (‘Little Jiffy’) procedure which, at best, produces somewhat crude approximations to the actual
structure of the various measures (see Cattell, 1978 ). Likewise, use of varimax rotation can be problematic in arti-
factually imposing orthogonality onto the components, when in fact, the components may be correlated in real
life. Extracting and rotating components however, rather than factors, necessarily means that both measurement
and unique error variance contaminates the resultant components. Nonetheless, advances in factor analytic meth-
ods, including use of confirmatory factor analysis have already resulted in construction of new measures of anger
and hostility some of which are described in this chapter.95 FUTURE RESEARCH DIRECTIONS
II. EMOTIONAL DISPOSITIONS