Population heterogeneity of trait anger and differential associations of trait anger facets with borderline personality features, neuroticism, depression, Attention Deficit Hyperactivity Disorder (ADHD), and alcohol problems
Introduction
Anger is an emotion consisting of feelings of variable intensity ranging from mild irritation to intense fury or rage (Spielberger et al., 1983). Anger can be either suppressed or directed at self (anger-in) or expressed outwardly through aggressive or confrontational behavior (anger-out). High levels of trait anger are associated with a range of psychiatric, interpersonal, and health problems, and in some cases anger can lead to aggression and violence (McDermut et al., 2009, Owen, 2011). Although clinically relevant in its own right, high levels of anger are significantly associated with a range of psychiatric disorders, including mood disorders, anxiety disorders, personality, and substance use disorders (DiGiuseppe et al., 2012, Kassinove and Tafrate, 2006, McDermut et al., 2009). Furthermore, anger is a central feature and diagnostic criterion for borderline personality disorder (American Psychiatric Association, 2013).
Anger has been described in terms of cognitive, emotional, and behavioral features, and several anger questionnaires attempt to capture these different aspects (Eckhardt et al., 2004, Owen, 2011, Smith et al., 2004). However, most investigations of the clinical correlates of anger have limited their focus to those correlates of aggregate measures of trait anger, failing to examine whether there are specific aspects of anger that show differential relations to common psychiatric problems. The present study focuses on aspects of anger measured by the Spielberger Trait Anger Scale (STAS, Spielberger et al., 1983). The STAS measures the disposition to have angry feelings. Factor analyses of the STAS have consistently shown that this scale is not unidimensional, but consists of two distinct facets, namely anger temperament and anger reaction. The STAS items measuring anger temperament are designed to refer to more frequent and intense feelings of anger that occur in a broader range of situations whereas anger reaction more narrowly refers to experiencing anger when negatively evaluated or mistreated by others (Spielberger et al., 1983). Analyses of the Dutch version point to the possibility of a third factor measuring the immediacy of an anger response, which is most likely due to the fact that the Dutch version is not a literal translation (van der Ploeg et al., 1982). Three items of the English STAS have been replaced, and two of these items are designed to tap into the immediacy of an anger response (van der Ploeg et al., 1982). The developers report a two-factor structure of the Dutch STAS, with a distinction between anger-temperament and anger-reaction, and suggest the two items concerning the immediacy of an anger response to be part of anger-temperament for subjects with high levels of Trait Anger but part of anger-reaction for subjects with low levels Trait Anger (van der Ploeg et al., 1982). These differences between subgroups were not directly investigated since statistical methods designed for this purpose were not available at the time, however, this issue is addressed in the current study.
One aim of the present study is to explore potentially different associations of the different STAS anger factors with a selection of psychiatric problems that are known to co-occur with anger, or feature anger as a symptom. Specifically, we investigated whether the anger factors show differential associations to a range of psychiatric problems from each of the following domains: externalizing and internalizing problems (ADHD and depression, respectively), substance use (alcohol problems), and maladaptive personality (borderline personality affect instability, identity problems, self-harm, negative relations, and neuroticism). Although by no means comprehensive, this selection provides an excellent opportunity to investigate the potentially differential associations of anger temperament, anger reaction, and the immediacy of an anger response. Since neuroticism is highly associated with a total score of borderline personality features (Distel et al., 2009), we also included neuroticism to further explore similarities and differences in the association with anger factors compared to the different aspects of borderline personality features.
Our second goal was to investigate potential heterogeneity. Population heterogeneity refers to the presence of different clusters in the population that differ qualitatively (e.g., differential profiles on aspects of anger, differential comorbidities) and/or quantitatively (e.g., severity of symptomology) (Lubke and Muthén, 2005). Studies of population heterogeneity of anger are very limited (but see He et al. (2013)). Given the importance of anger as a health risk factor (Chida and Steptoe, 2009), a detailed understanding of the presentation of anger is critical for clinical research. To investigate population heterogeneity of the different aspects of anger it is necessary to carry out item-level analyses rather than using total scores. In this study we modeled item-level data of the Dutch version of the STAS with factor mixture models, and assessed differential associations of the different anger facets in each of the latent classes. Factor mixture modeling is a recently developed statistical framework that permits estimating a specific factor structure within different clusters (aka latent classes) of subjects in the population (Tueller and Lubke, 2010). Factor mixture modeling combines latent class analysis and factor analysis in a single modeling framework (Lubke and Muthén, 2005). Latent class analysis attributes overall covariation between questionnaire items entirely to mean differences between latent classes while constraining within class covariances of items to be zero. Factor analysis attributes overall covariation to continuous underlying factors that represent severity, and assumes a single homogeneous population. Factor mixture models are hybrids that permit mean differences between latent classes as well as severity differences in factors within each class. Most importantly, the clusters or classes reflect a grouping of subjects with similar response profiles that is data-driven. The factor structure and the response profiles of the items can differ across clusters. The classes can be compared with respect to qualitative differences (characteristic response profiles, differential associations with covariates), and quantitative differences (severity of symptomology).
In summary, in order to examine the differential associations of a range of psychiatric problems with different aspects of anger, we assessed the heterogeneity of anger, as measured by the STAS, using factor mixture modeling in a large population sample drawn from the Netherlands Twin Register (NTR) (Willemsen et al., 2013). We also addressed the question whether the Dutch version of the STAS is more adequately modeled with two or with three factors. Next, we investigated differences between classes regarding the association of the different STAS anger factors with borderline personality features, ADHD, depression, neuroticism, and alcohol problems.
Section snippets
Participants
The subjects were participants of the Netherlands Twin Register (NTR), a population-based sample, which is ascertained based on the presence of twins or higher-order multiples in the family (Willemsen et al., 2013). Data collection in 2 to 5-year intervals started 25 years ago. Most data included in the present study were collected between 2004 and 2005 (survey 7), with the exception of depression, which was collected in survey 8 (between 2009 and 2012, see below). The total number of
Analysis part 1: Population heterogeneity of anger
The results of the models that were fitted to select the best fitting model using a subset of the data (N=2499) are presented in Table 4. As expected, latent class analysis models (LCA models) did not fit the data as well as the factor mixture models, which allow for severity differences in anger.
All factor mixture models were fitted with class-specific factor variances and covariances. We also permitted class-specific loadings and thresholds to allow for deviations from measurement invariance,
Discussion
To our knowledge this is the first study that explores the associations between the different STAS anger factors and PAI-BOR subscales, neuroticism, depression, ADHD, and alcohol problems in more detail in a population sample. These behaviors are known to be associated with anger, and were chosen as examples of personality problems, externalizing and internalizing problems, and substance use problems. Comparing the overall correlations of these behaviors with the STAS total score (see Table 3)
Acknowledgments
GH Lubke was supported by NIH DA-018673. MHM de Moor was supported by the Netherlands Organization for Scientific Research (NWO) (VENI-016-115-035). We acknowledge funding for data collection from the Netherlands Organization for Scientific Research (NWO) and MagW/ZonMW: Twin family database for behavior genomics studies (480-04-004); Genetic determinants of risk behavior in relation to alcohol use and alcohol use disorder (ZonMw Addiction-31160008); Genotype/phenotype database for behavior
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