CRITERION VALIDITY AND PERSON PERCEPTION OF MALADAPTIVE PERSONALITY TRAITS  By   Matthew Michael Yalch              A DISSERTATION   Submitted to Michigan State University in partial fulfillment of the requirements for the degree of  Psychology  Doctor of Philosophy  2016         ABSTRACT CRITERION VALIDITY AND PERSON PERCEPTION OF MALADAPTIVE PERSONALITY TRAITS  By   Matthew Michael Yalch  Recent research has emphasized the importance of maladaptive personality traits, which are associated with a number of clinically relevant behaviors. There is a large literature on maladaptive traits and a number of maladaptive trait models. Drawing from this literature, the American Psychiatric Association (2013) recently published the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5; American Psychiatric Association, 2013), which includes a formal model of twenty-five maladaptive traits for the diagnosis of personality disorder. There have been a number of studies examining the traits within this model in terms of validity, although these studies have often not included additional maladaptive traits that may provide incremental criterion validity. This research has also been largely limited to self-report studies, which neither take into account the perspective of informants, who may be privy to information about traits that are unavailable to the targets of trait ratings, nor the role of insight on the part of targets or informants about how others might perceive these traits (i.e., meta-perception). In this study, I intended to cover some of the gaps in the maladaptive trait literature in two ways. First, I examined the incremental criterion validity of maladaptive traits not included in the benchmark DSM-5 trait model on a series of clinically relevant behaviors. Second, I examined the degree to which the ratings of maladaptive traits provided by knowledgeable informants corresponded to the ratings provided by targets of these ratings. Results indicated additional maladaptive traits provided incremental criterion validity over and above the traits of the formal DSM-5 model on all clinically relevant behaviors. Results further   suggested that targets and informants provided unique perspectives on maladaptive traits, and that the role of meta-perception on target-informant agreement on trait ratings was modest. However, these results differed depending on the trait rated and the relationship of the informant to the target. These findings have implications for future research on maladaptive traits (e.g., how many traits should be included in a model of maladaptive traits) as well as for clinical personality assessment (e.g., who is best poised to provide information about which personality traits). iv                        To cold, black coffee Not my preferred beverage But one I needed   v  ACKNOWLEDGEMENTS    I owe thanks to many people who have helped and guided me before and throughout graduate school, and without whom this dissertation would not have been possible. My mother encouraged my intellectual curiosity and was never stingy when it came to buying books or bringing a computer home from her school during the summers for my sister and I to use until we could afford to buy our own. She was more excited than I was when I passed my dissertation defense.  I found a second home at Cornell, one in which I was able to grow tremendously, intellectually and otherwise. My two undergraduate academic advisors there, Harry Segal and Jane Marie Law, helped me to both expand and deepen my interests. Harry in particular served as an early role model of an intellectually interested and clinically active psychologist, and would eventually suggest that I apply for graduate school.  When I arrived at Michigan State, I was fortunate enough to be received by two more mentors. I found in Alytia Levendosky a warm and supportive holding environment in which I could both further explore and develop my interests, and which I continue to use as a model for my own relationships. Chris Hopwood remains for me an exemplar of the clinical scientist, walking the razor-thin line of participant and observer, advisor and friend, engaged but objective. Alytia and Chris continue to serve as role models I to try to emulate in many aspects of my life.  At Michigan State and later at the San Francisco VA, I was fortunate to have been able to work with a host of excellent supervisors who taught me both directly and through their example how to translate psychological theory and research into clinical practice. Natalie Moser, Lee vi  June, David Rockwell, Stuart Doneson, Tim Goth-Owens, Brooke Ingersoll, Diana Osborn, and Luke Hyde in East Lansing, and Kellie Rollins, Kris Burkman, Russell Lemle, Johannes Rothlind, Sam Wan, John McQuaid, and Megan McCarthy in San Francisco have all been formative in my development as a psychologist in general and a clinician in particular. It is possible that I have learned just as much (socially and emotionally for sure, and perhaps intellectually as well) from my fellow graduate students as from my formal teachers, both in the basement of the psychology building at Michigan State and at the San Francisco VA. I thought about listing each one, noting how each has affected and sustained me through my graduate school experience, but I thought better of it for two reasons. First, I doubt that any will read this dissertation (and indeed I would urge them not to do so) and so the ink would be spent for naught. Second, the time I would spend writing could be better spent giving them a phone call, writing an e-mail, or working on a collaboration.  I hope and expect many of the friendships I made in graduate school will continue for many years to come. Nonetheless, I must acknowledge Kate, who has been my strongest and most consistent source of love and support (communal and agentic) throughout graduate school.     vii  TABLE OF CONTENTS   LIST OF TABLES ...........................................................................................................x  LIST OF FIGURES .........................................................................................................xi  INTRODUCTION ...........................................................................................................1  STUDY 1: CRITERION VALIDITY ..............................................................................4  Models of maladaptive traits ..........................................................................4   Trait-based models ...................................................................................5   Inductive models ......................................................................................6    Maladaptive traits in DSM-5 .............................................................6   Synthesis ..................................................................................................9  Criterion validity ............................................................................................11   Self-destructive behavior .........................................................................12   Hypochondriasis ......................................................................................12   Aggressive and rule-breaking behavior ...................................................13   Autocratic behavior ..................................................................................13   Behavioral rigidity ...................................................................................13   Workaholic behavior ................................................................................14   Dissociative symptoms ............................................................................14   Cognitive dysfunction ..............................................................................15  Current study ..................................................................................................15   Hypothesis 1.1..........................................................................................15   Hypothesis 1.2..........................................................................................15   Hypothesis 1.3..........................................................................................15   Hypothesis 1.4..........................................................................................15   Hypothesis 1.5..........................................................................................15   Hypothesis 1.6..........................................................................................15   Hypothesis 1.7..........................................................................................16   Hypothesis 1.8..........................................................................................16  Method .................................................................................................................16   Participants .....................................................................................................16   Measures ........................................................................................................17    Maladaptive traits.....................................................................................17    Criterion variables ....................................................................................18    Suicide risk.........................................................................................18    Non-suicidal self-injury .....................................................................18    Hypochondriasis ................................................................................18    Aggressive and rule-breaking behavior .............................................18    Autocratic behavior ............................................................................19 viii     Behavioral rigidity .............................................................................19    Workaholic behavior ..........................................................................19    Dissociative symptoms ......................................................................20    Cognitive dysfunction ........................................................................20   Procedures ......................................................................................................21    Data analysis ............................................................................................21  Results ..................................................................................................................23   Preliminary analyses ......................................................................................23    Convergent and discriminant correlations ...............................................23    Principal components analyses ................................................................25   Clinician selection of traits ............................................................................25   Criterion validity ............................................................................................26   Post hoc analyses ...........................................................................................27  Discussion ............................................................................................................28                          STUDY 2: PERSON PERCEPTION AND MALADAPTIVE TRAITS ........................31   Evaluativeness and observability ...................................................................32   Relationship of target to informant ................................................................34   Meta-perception .............................................................................................35   Current study ..................................................................................................37    Hypothesis 2.1..........................................................................................37    Hypothesis 2.2..........................................................................................37    Hypothesis 2.3..........................................................................................38  Method .................................................................................................................38   Participants .....................................................................................................38   Procedures ......................................................................................................39   Measures ........................................................................................................40   Data analysis ..................................................................................................41  Results ..................................................................................................................41   Reliability and validity of single-item trait assessments................................41   General target-informant agreement ..............................................................43    Meta-perception .......................................................................................43   Target-informant agreement by relationship .................................................44   Effects of meta-perception within relationships ............................................45   Post hoc analyses ...........................................................................................45  Discussion ............................................................................................................47  GENERAL DISCUSSION ..............................................................................................53  Criterion validity ..................................................................................................53  Person perception .................................................................................................55  Future directions ..................................................................................................57  Strengths and limitations......................................................................................59  Conclusion ...........................................................................................................61  APPENDICES .................................................................................................................62 Appendix 1: Tables ..............................................................................................63 ix  Appendix 2: Figures .............................................................................................100 Appendix 3: Single-trait rating scale (self-report version) ..................................101 Appendix 4: Excerpt from clinician panel survey ...............................................104  REFERENCES ................................................................................................................105   x  LIST OF TABLES   Table 1. Comparison of proposed DSM-5 traits, PID-5 traits, and CAT-PD traits ........63  Table 2. Correlations between traits ...............................................................................65  Table 3. Traits selected by clinician panel to predict criterion variables .......................71  Table 4. Traits selected by clinician panel to predict criterion variables (updated) ......74  Table 5. Correlations between traits and criterion variables..........................................77  Table 6. Results of hierarchical regression analyses examining effects of clinician-selected traits on clinically relevant behaviors ...............................................................80  Table 7. Results of hierarchical regression analyses examining effects of all maladaptive traits on clinically relevant behaviors.........................................................82  Table 8. Composite score of informant ICCs, convergent validity, and target-informant agreement listed by trait ..................................................................................................84  Table 9. Target-informant agreement with and without meta-perception .......................85  Table 10. Target-informant agreement broken down by relationship .............................86  Table 11. Target-informant agreement with and without meta-perception broken down by relationship ........................................................................................................................87  Table 12. Target-informant agreement with and without meta-perception (calculated using regression) .........................................................................................................................92  Table 13. Differences in maladaptive trait levels between targets nominating informants by relationship ........................................................................................................................96   xi  LIST OF FIGURES   Figure 1. The Johari Window applied to distress associated with maladaptive traits ....100   1  INTRODUCTION   Personality traits, describesignify stable and meaningful aspects of a person (Allport, 1937; Clark & Watson, 2008; McCrae & Costa, 1996, 2008; Eysenck, 1967, 1987; Tellegen, 1985, 1991), such as how the person interacts with other people (Costa & McCrae, 2011; Wiggins & Trapnell, 1996) and how he or she responds to stress (McCrae & Costa, 2008; M. Miller, 2003). Traits are associated with a number of important psychosocial outcomes, including physical health, mortality, functioning in professional and romantic relationships, criminal behavior, and overall level of satisfaction with life (Lahey, 2009; Ozer & Benet-Martinez, 2006; Roberts, Kuncel, Shiner, Caspi, & Goldberg, 2007). Traits are also associated with a number of behavioral problems, ranging from symptoms of common mental disorders (Kotov, Gamez, Schmidt, & Watson, 2010) to more pervasive problems in interpersonal functioning (Samuel & Widiger, 2008; Saulsman & Page, 2004; see also Widiger & Smith, 2008). Traits also influence the course (Cain et al., 2010, 2012; Przeworski et al., 2011; Thomas et al., 2014) and expression (M. Miller et al., 2003; M. Miller & Resick, 2007) of these problems.  Clinically focused personality assessment typically focuses on maladaptive personality traits, measures of which focus on assessing the maladaptive tails of normal trait distributions (Samuel et al., 2010; Suzuki, Samuel, Pahlen, & Krueger, 2015). For example, the maladaptive trait Mistrust captures an aspect of low Agreeableness and Perfectionism captures an aspect of high Conscientiousness. Maladaptive traits generally correlate more strongly with clinically important outcomes because of their focus on the maladaptive expression of personality (Morey et al., 2007, 2012). There are a number of different models of maladaptive traits. Research 2  suggests that higher order factors of the traits within these models are similar to those of the Five Factor Model (FFM) of normative personality traits (e.g., Markon, Krueger, & Watson, 2005; Wright & Simms, 2014; for review see Krueger & Markon, 2014; Widiger & Simonsen, 2005). This is important because it suggests the potential of translating basic personality science to clinical practice. However, research findings are less clear regarding the lower order structure of maladaptive traits (i.e., the precise number of maladaptive traits and what they are). For the clinician one important determinant in the nature and number of maladaptive traits is which trait(s) might predict specific clinically significant behaviors over and above other traits. In psychometric terms, this is referred to as incremental criterion validity.  Research is similarly unclear about the role of person perception in the assessment maladaptive traits. The perception of a person changes based on the specific aspect of the person being perceived and the person who is perceiving (Heider, 1967; Jones, 1964, 1990; Schneider, Hastorf, & Ellsworth, 1979; Zebrowitz, 1990). With respect to the assessment of traits, this entails that information about a trait reported by one person (e.g., the object or target of the trait rating) may differ from the information reported by another person (e.g., an informant, such as the perception and assessment of traits is the possibility of insight on the part of raters about how others might rate these traits (i.e., an ability known as meta-perception). For example, the target -reducing the dissonance between self- and informant-ratings of traits. It is not yet clear how self-reports and informant-reports of a comprehensive array of maladaptive traits differ from and are similar to each other, and how meta-perception might influence these differences and similarities. 3  Knowledge of the criterion validity of maladaptive traits and how different people perceive these traits may inform the multi-method assessment of personality pathology and may aid in the case formulation of people presenting with personality pathology. Examining the criterion validity and target-informant agreement of traits was thus the focus of this study, the general goal of which was to contribute to the growing literature on the assessment of maladaptive traits through two specific aims. The first aim of this study was to evaluate the clinical utility of lower order maladaptive traits. This aim was comparative in nature and involved assessing the incremental criterion validity of a comprehensive 33-trait model of maladaptive traits vis-à-vis the 25-trait model of traits that holds benchmark status as per its designation as an alternative method for diagnosing personality disorder (PD) symptoms in the Diagnostic and Statistical Manual of Mental Disorders (DSM-5; American Psychiatric Association [APA], 2013). Specifically, I examined the degree to which the traits within this more comprehensive model may have advantages for predicting specific clinically relevant behaviors. The second aim of this study has to do with how research on person perception can inform the applied problem of how to approach multi-method assessment in clinical practice. Specifically, I will examine whether traits of different levels of observability are rated differently by rated persons (targets) and people who know these rated persons well (informants) and whether any differences may be mitigated by meta-perception.    4  STUDY 1: CRITERION VALIDITY In contemporary theories of personality (e.g., Five Factor Theory; McCrae & Costa, 2008), maladaptive traits are thought to signify a tendency for certain kinds of maladaptive 2003, 2008). Characteristic maladaptations are thought to be the result of an interactional process in which maladaptive traits influence a person to respond in a characteristically problematic way to certain events in his or her environment (Harkness, Reynolds, & Lilienfeld, 2014; Watson & Clark, 1994; Yalch, Hopwood, & Zanarini, 2014; see also McAdams & Pals, 2006). In this way, maladaptive traits are thought to be enduring dimensions whereas characteristic maladaptations are more context-dependent (Durbin & Hicks, 2014; Lilienfeld & Harkness 1997). For example, Harkness and colleagues (2014) note that although instrumental aggression is associated with trait Antagonism, the former is a fleeting behavior performed in response to environmental cues and the latter is a longstanding disposition for engaging in that behavior. Thus, by knowing how d of being aggressive in social situations (although the specific kind of social situation in which a person may behave . Thinking along these lines, clinicians can use maladaptive traits to provide a framework for lives (Widiger, 1997; Widiger, Samuel, Mullins-Sweatt, Gore, & Crego, 2012).  Models of maladaptive traits Several evidence-based models of maladaptive traits currently exist. These models vary in part according to the approach researchers took to their development and the number and type 5  of traits they contain (Krueger & Markon, 2014; Widiger & Simonsen, 2005, 2006). In general, developers of maladaptive trait models have taken one of two approaches. One approach is to extend general theories of normal traits to try to capture maladaptive variants of personality. The second is to apply psychometric techniques to existing conceptualizations of PD. Examples of each of these approaches are described in detail below.  Trait-based models. One path to the development of maladaptive trait models involves using extant normative trait models as a framework to guide the development of maladaptive trait models. A number of researchers (e.g., Lynam et al., 2011; Samuel, Riddell, Lynam, Miller, & Widiger, 2012; for review see Widiger, Lynam, Miller, & Oltmanns, 2012) have developed trait models explicitly derived from the normative FFM traits (i.e., Agreeableness, Conscientiousness, Extraversion, Neuroticism, and Openness) and facets (Costa & McCrae, 1985, 1992). There now exist maladaptive versions of normal range instruments to measure these traits (e.g., Haigler & Widiger, 2001; Trull, Widiger, & Burr, 2001), as well as FFM-based measures of specific personality disorder categories (Widiger et al., 2012b).  Alternatively, Clark (1993) developed the Schedule for Nonadaptive and Adaptive Personality (SNAP) model based on Tell-factor model of temperament. The SNAP contains 12 lower-order maladaptive traits nested within 3 higher-order temperament Clark & Watson, 2008; Eysenck, 1967; Tellegen, 1985, 1991). Although the theory underlying the SNAP suggests fewer higher order domains, empirically the SNAP model can be understood as combining maladaptive Agreeableness and Conscientiousness into a single Disinhibition trait (Markon et al., 2005), and offering a somewhat narrower conception of maladaptive Openness (i.e., schizotypy) in the form of a single primary trait, eccentric perceptions.  6  Harkness and McNulty (1994) proposed the Psychopathology-5 (PSY-5) model based on their review of biobehavioral systems relevant to psychopathology. Although this model shares five maladaptive traits (Aggressiveness, Disconstraint, Introversion, Negative Emotionality/Neuroticism, and Psychoticism). It also has the advantage of being embedded within the widely used MMPI, making it one of the more commonly used maladaptive trait systems in routine clinical use. However, unlike the FFM and SNAP models, primary facet scales have not been articulated for the PSY-5.  Inductive models. Another path to developing maladaptive trait models begins with PD symptoms as represented in diagnostically focused systems (e.g., models of psychopathology, diagnostic manuals, etc.). For instance, Livesley and Jackson (1992, 2009) initiated a project designed to evaluate the validity of the PD system in the (then) current Diagnostic Manual of Mental Disorders (DSM-III; APA, 1980). Having failed to validate the DSM-III model, they offered the Dimensional Assessment of Personality Pathology (DAPP) as a trait-based system for depicting variation in maladaptive personality features. The DAPP contains 18 primary traits that map onto a higher-order four-factor structure consisting of Compulsivity, Dissocial Behavior, Emotional Dysregulation, and Inhibition (Maruta, Yamate, Iimori, Kato, & Livesley, 2006; Zheng et al., 2002). Traits related to maladaptive Openness/Psychoticism (the fifth factor in models like the PSY-5) were purposefully excluded from the DAPP based on the assumption that such traits were genotypically more related to psychosis than to personality (Livesley & Jackson, 1992).  Maladaptive traits in DSM-5. The most recent guidelines for the diagnosis of PD include an alternative system of diagnosis based in part on maladaptive traits (Zachar & First, 2015). In 7  this alternative system, a person qualifies for a PD diagnosis if they exhibit at least moderate impairment in self/interpersonal functioning (APA, 2013). Having met this criterion, specific variation in the expression of PD is diagnosed on the basis of their standing on lower-order maladaptive traits as represented on the Personality Inventory for DSM-5 (PID-5; Krueger et al., 2012), a specific instrument that the Personality and Personality Disorder Work Group developed based on a review of DSM PD symptoms. For example, avoidant personality disorder is characterized by high standing on Anhedonia, Anxiousness, Intimacy Avoidance, and Withdrawal (APA, 2013). The model is listed as an alternative model because, while proposed by the Personality and Personality Disorder Work Group, the board of trustees of the American Psychiatric Association did not vote to list it in the official diagnostic scheme. However, clinicians can use the model as a true alternative, if they wish, in making PD diagnoses. It is likely that a model along these lines will eventually replace the categorical model of PD in DSM-5 Section II (for review of future directions of dimensional PD classification, see First, 2005; Widiger & Trull, 2007).  The type and number of maladaptive traits that should be included in this alternative scheme is a topic of ongoing inquiry. In the construction of the PID-5, Krueger et al. generated item content via expert consensus based on the 37 DSM-5 maladaptive traits that the Personality and Personality Disorder Work Group originally proposed would capture comprehensively the variability in PD criteria (Hopwood & Sellbom, 2013; Krueger et al., 2011a; Skodol, 2012; Widiger, 2012). Item and scale level factor analyses using data from three rounds of data collection indicated that some pairs of traits could be collapsed (e.g., Self Harm collapsed into Depressivity) to provide a more parsimonious model. The results of these analyses yielded 25 maladaptive traits, which reflect a broad range of personality-related problems.  8  Since its development, the traits in the DSM-5 alternative model have been the subject of intensive study (for review, see Al-Dajani, Gralnick, & Bagby, 2016; Hopwood & Sellbom, 2013; Rodriguez-Seijas, Eaton, & Krueger, 2015). Structural research on the PID-5 indicates that the 25 traits in the model conform to a higher-order FFM structure in non-clinical (Anderson et al., 2013; Gore & Widiger, 2013; Thomas et al., 2013; Wright & Simms, 2014; Wright et al., 2012b; Zimmerman et al., 2014; see also DeYoung, Carey, Krueger, & Ross, 2016), clinical (Bastiaens et al. 2016; Wright & Simms, 2014; Zimmerman et al., 2014), adolescent (Mage = 14 years; De Clercq et al., 2014), and non-English speaking (Bach, Lee, Mortensen, & Simonsen, 2015; Bastiaens et al. 2016; De Clercq et al., 2014; De Fruyt et al., 2013; Fossati, Krueger, Markon, Borroni, & Maffei, 2013; Van den Broeck et al. 2014; Zimmerman et al., 2014) samples. The results of these studies confirmed that the higher order factors of DSM-5 traits represent maladaptive variants of FFM domains, with six traits loading primarily on Detachment (low Extraversion), five traits each on Negative Affect (Neuroticism), Disinhibition (low Conscientiousness), and Psychoticism (Openness), and four traits on Antagonism (low Agreeableness; see Table 1).  An increasing number of studies suggest that the DSM-5 traits are associated with a range of clinically important behaviors (Al-Dajani, Gralnick, & Bagby, 2016; Krueger & Markon, 2014). For example, studies in both U. S. and European samples indicated that these traits are strongly and systematically associated with symptoms of common mental health problems (e.g., symptoms of anxiety, depression, alcohol abuse) and PDs (Bach, Anderson, & Simonsen, 2016; Creswell, Bachrach, Wright, Pinto, & Ansell, 2015; Few et al., 2013; Fossati et al., 2013; Hopwood, Thomas, Markon, Wright, & Krueger, 2012; Hopwood et al., 2013; James et al., 2015; Morey, Benson, & Skodol, 2016; Yalch & Levendosky, 2014; Yam & Simms, 2014; 9  Zimmerman et al., 2014). Research also indicates that DSM-5 traits are associated with other aspects of personality pathology such as psychopathy (Anderson, Sellbom, Wygant, Salekin, & Krueger, 2014; Strickland, Drislane, Lucy, Krueger, & Patrick, 2013; Wygant et al., 2016) and maladaptive narcissism (J. Miller et al., 2013, 2014; Wright et al., 2013b), as well as a broad range of interpersonal problems (Bach, Lee, Mortensen, & Simonsen, 2015; Williams & Simms, 2015; Wright et al., 2012a) and deficits in moral reasoning (Noser et al., 2016). Research further suggests that the DSM-5 traits can be used in clinical case conceptualization, both in the classroom (Yalch, Vitale, & Ford, in press) and in clinical practice (Bach, Markon, Simonsen, & Krueger, 2015). However, there is some evidence suggesting that clinicians may prefer traits other than those identified by previous theory and research to predict clinical outcomes (e.g., PD diagnoses). For example, Crego et al. (2015) found that when assessing the personality of their clients, clinicians generally preferred more comprehensive lists of traits maladaptive traits (e.g., the original 37 traits proposed by the Personality and Personality Disorder Work Group) as well as normative traits to the more restrictive 25 traits of the final DSM-5 trait model. This study notwithstanding, initial research suggests that the DSM-5 maladaptive trait model provides a relatively comprehensive and clinically useful assessment of maladaptive traits, thus making it the current benchmark in maladaptive trait research.  Synthesis. In contrast to the models above, development of the Computerized Adaptive Test of Personality Disorder (CAT-PD; Simms et al., 2011) model of maladaptive traits was informed by both trait theory and PD criteria. Simms and colleagues began with 53 traits described in previous trait research organized around the FFM (see Widiger & Simonsen, 2005), which included a broa broad 10  sampling of personality and PD experts to capture any constructs associated with maladaptive traits that may not have been captured in existing measures. This method yielded an additional 6 traits, bringing the total number of candidate traits to 59.  Simms and colleagues (2011) then generated items to measure these candidate traits using two different methods. First, they pulled 2,413 items from the International Personality Item Pool (IPIP; Goldberg et al., 2006), an online database of personality trait items. They cond, because the IPIP trait items were designed to assess normal range personality traits whereas the goal of the CAT-PD was to provide an assessment of personality pathology, Simms et al. generated an additional 2,000 items to encompass gaps and severity, again sorted into each bin. After deleting and combining items on the basis of wording and redundancy, the initial item pool was narrowed down to 2,589 items.  Simms and colleagues administered these items to community and clinical samples using a balanced incomplete block design in which each participant filled out roughly 860 questions and the responses of all participants were subjected to combined analyses. Results of these analyses indicated that the items factored into 33 lower-order traits, with broad range of severity within each trait scale. This broad range of severity enabled each trait to provide a comprehensive measurement of the constructs they were designed to assess. Initial research on the structure of the CAT-PD indicates that its traits conform to a higher-order FFM structure (Wright & Simms, 2014; see Table 1), providing seven traits each with primary loadings on Negative Affect, Antagonism, and Disinhibition factors, and six traits each loading on Detachment and Psychoticism. This research also suggested that many CAT-PD traits resembled those of the DSM-5 maladaptive traits system. For example, CAT-PD Depressiveness exhibited 11  similar factor loading patterns as did the similarly named DSM-5 Depressiveness, which was also the case for CAT-PD and DSM-5 Irresponsibility, and so on. Also like the DSM-5 traits, most of the CAT-PD traits had substantial interstitial cross-loadings, which suggested that these traits were not simple facets of maladaptive FFM traits. One way in which the CAT-PD was distinct from a structural perspective was that it contained some traits that had no obvious counterpart in the DSM-5 system (e.g., Self Harm, Health Anxiety).  There is also initial research indicating that the traits contained within the CAT-PD model are associated with a number of clinically important outcomes. For example, Williams and Simms (2014) found that CAT-PD traits were associated with a broad range of interpersonal problems. Harrison and colleagues (2015) further found that the CAT-PD Callousness, Domineering, Grandiosity, Hostile Aggression, Manipulativeness, Norm Violation, Self Harm, Unusual Beliefs, and Unusual Experiences traits are strongly associated with specific aspects of aggressive behavior (physically aggressive, socially aggressive, and rule-breaking behavior). These studies are preliminary, however, and the criterion validity of these and other CAT-PD traits have not yet been examined vis-à-vis the traits of the benchmark DSM-5 model. Criterion validity An important question moving forward involves how many primary traits should be included in maladaptive trait models. It would be particularly important to identify any traits that are not currently included in the DSM-5 model, so that revisions of that model can incorporate those traits in order to enhance the utility of DSM-5 personality assessment. The broader and more systematic approach Simms and colleagues (2011) took in developing the CAT-PD may explain why it has 33 primary traits, in contrast to the 25 traits of the benchmark DSM-5 model. This broader representation of primary traits may provide benefits in terms of the clinical 12  assessment of certain kinds of clinically relevant behaviors (i.e., characteristic maladaptations) for the CAT-PD relative to the PID-5. If so, the CAT-PD could inform the literature regarding how to expand the DSM-5 model to balance parsimony with predictive utility most effectively. The degree to which the CAT-PD traits provide incremental information over the traits in the DSM-5 model in predicting certain kinds of behaviors is a central question for this study. The primary traits of the CAT-PD and DSM-5 models can be compared directly to identify conceptual gaps in coverage in the DSM-5 model. This comparison yields a number of behaviors in which the CAT-PD model may be at a predictive advantage (see Table 1). These behaviors were a focus of this study, in order to provide a relatively liberal test of the ability of the CAT-PD traits to describe important variation in personality-related functioning that may not be covered by the traits in the DSM-5 model. These behaviors are described in detail below.  Self-destructive behavior. Suicidal and parasuicidal (i.e., non-suicidal self-injurious) behaviors are two distinct but related behaviors that are both clinically relevant and may be associated with maladaptive traits. Indeed, research suggests that several higher-order traits are associated with suicidality (e.g., FFM Neuroticism, Impulsivity; Beautrais, Joyce, & Mulder, 1999; Chioqueta & Stiles, 2005; Yalch, Hopwood, Fehon, & Grilo, 2014). Further, Krueger (2006; Krueger et al., 2011b) noted that a lower-order maladaptive trait may be particularly useful in predicting suicidal and parasuicidal behavior. However, whereas in the DSM-5 model, self-destructive behavior is contained within a broader Depressivity trait, the CAT-PD model contains a distinct Self Harm trait in addition to Depressiveness.  Hypochondriasis. Another area in which there is a lack of coverage by the DSM-5 model is hypochondriasis, the preoccupation with something going wrong with the body. Like suicidal and parasuicidal behavior, there is some research indicating that hypochondriasis is 13  influenced by personality traits (Cox, Borger, Asmundson, & Taylor, 2000; Hollifield, Tuttle, Paine, & Kellner, 1999) as well as discussion about whether it should be considered a dimensions of personality pathology (for review see Hollifield, 2001). However, as with self-destructive behavior, although the DSM-5 model does not contain a trait associated with hypochondriasis, the CAT-PD contains a Health Anxiety trait that relates to hypochondriasis directly.  Aggressive and rule-breaking behavior. Although the DSM-5 model includes traits tapping aspects of callous, deceitful, manipulative, and generally hostile personality characteristics, it does not include traits that specifically assess aggressive acting-out. However, the CAT-PD model also includes three traits (Anger, Norm Violation, and Rudeness) conceptually associated with physically aggressive, socially aggressive, and rule-breaking behavior, which meta-analytic research indicates is associated with personality traits (Bettencourt, Talley, Benjamin, & Valentine, 2006).  Autocratic behavior. While the DSM-5 model includes traits associated with hostility (Williams & Simms, 2015; Wright et al., 2012a; cold dominance in interpersonal terms; for review see Wiggins & Trapnell, 1996), it does not contain traits associated with behavioral manifestations of excessive (but not cold) dominance (i.e., autocratic behavior). As with other aspects of behavior, excessive and inflexible autocratic behavior may be indicative of personality pathology (for review see Pincus & Hopwood, 2012). In contrast, the CAT-PD model includes a Domineering trait, which preliminary evidence suggests may be associated with maladaptive autocratic behavior (Williams & Simms, 2015).  Behavioral rigidity. In the domain of disinhibited behavior in general, the DSM-5 and CAT-PD models share a high degree of overlap. However, the traits of the CAT-PD model may 14  be at an advantage in the prediction of aspects of overly inhibited behavior. For example, in the DSM-5 model, problems of orderly and overly proprietous behavior are subsumed under a single trait, Rigid Perfectionism. However, although perfectionist and rigid behaviors are often seen together, factor analytic research suggests that they are distinct behavioral constructs (Pinto, 2011). Accordingly, in the CAT-PD model, Perfectionism and Rigidity are separated into two distinct traits, the latter of which may provide a more precise assessment of overly inhibited behavior.  Workaholic behavior. Another example of maladaptive behavior related to inhibition/disinhibition is workaholic behavior, when people are excessively unconstrained in the time and effort they devote to agentic behavior (e.g., work) at the expense of affiliative behavior (e.g., the maintenance of relationships with family and friends). Research suggests that this type of behavior is associated with maladaptive aspects of inhibition/disinhibition (Mudrack, 2004). As with overly rigid behavior, whereas the DSM-5 model does not include a trait associated with workaholic behavior, the CAT-PD includes a Workaholism trait.  Dissociative symptoms. The DSM-5 and CAT-PD models both contain traits associated with a range of odd thoughts and behavior. However, the DSM-5 model limits its conceptual coverage to odd thoughts and behaviors associated with schizotypy/psychosis (e.g., paranoid and otherwise delusional or magical thinking). Although there are several CAT-PD traits that seem to provide equivalent coverage of these types of behaviors (e.g., Unusual Beliefs, Unusual Experiences), there are additional CAT-PD traits that may overlap with other odd behaviors that may be less related to schizotypy. For example, a number of researchers have commented that dissociative symptoms may be rooted in maladaptive traits (Lynn et al., 2012, 2014), which the CAT-PD Fantasy Proneness trait may be well poised to predict. 15  Cognitive dysfunction. Other aspects of cognitive dysfunction like attention problems and other difficulties processing information may also be associated with maladaptive traits (Harkness, Lilienfeld, & McNulty, 2014; Kaspar & König, 2012; Lynn et al., 2012, 2014). However, whereas the DSM-5 model lacks traits designed to assess these other aspects of cognitive dysfunction, the CAT-PD Cognitive Problems trait may capture them.  Current study  The purpose of Study 1 was to evaluate the incremental criterion validity of the additional CAT-PD traits over the benchmark DSM-5 traits, with the expectation that the additional traits in the more comprehensive CAT-PD model would provide incremental information in the prediction of a number of clinically important behaviors. My hypotheses were as follows: Hypothesis 1.1. Self Harm would provide incremental information in the prediction of suicide risk and non-suicidal self-injury (NSSI).  Hypothesis 1.2. Health Anxiety would provide incremental information in the prediction of hypochondriasis.  Hypothesis 1.3. Norm Violation, Hostile Aggression, Anger, and Rudeness would provide incremental information in the prediction of physical and social aggression, and rule-breaking behavior. Hypothesis 1.4. Domineering would provide incremental information in the prediction of autocratic behavior.  Hypothesis 1.5. Perfectionism and Rigidity would provide incremental information in the prediction of behavioral rigidity. Hypothesis 1.6. Workaholism would provide incremental information in the prediction of workaholic behavior.  16  Hypothesis 1.7. Fantasy Proneness would provide incremental information in the prediction of dissociative symptoms. Hypothesis 1.8. Cognitive Problems would provide incremental information in the prediction of attention problems and other difficulties processing information. Method Participants Participants in this study were 1354 students enrolled at Michigan State University who participated online through the Human Participation in Research (HPR) system (see also Yalch & Hopwood, 2016). From this initial sample, responses from 179 participants were excluded for having 10% or more of their data missing. The responses of 59 additional participants were discarded due to incorrect responses on four items designed to detect inaccurate responding (e.g., For va to this question & Craig, 2012). This left a final sample of 1116 participants. To account for any remaining missing data (across the sample, each item had less than 2% of its data missing), I calculated raw scale scores as the average of all items endorsed within it. Mean age of participants was 20 years (SD = 2.24). Sex and other demographic information is as follows: female (72%), White, non-Hispanic (69%), Asian (16%), Black, non-Hispanic (8%), Latino(a) (3%), multi-racial or other (5%).  There are a number of considerations when using college samples in psychological research. For example, some suggest that by virtue of their selection into a more or less protective environment, college students may not exhibit sufficient problems to warrant inclusion in studies of serious psychopathology (e.g., Freyd, 2012). In addition, the homogeneity of problems for a variety of analyses (Fabrigar, Wegener, MacCallum, & Strahan, 1999). However, 17  there are a number of reasons to suggest that the proposed use of a college population for the samples in this study is viable. First, in general, college students are at an age at which maladaptive aspects of personality normatively reach their peak (Johnson, Cohen, Kasen, Skodol, & Oldham, 2008). Indeed, a number of studies suggest that personality problems are prevalent in college populations (Lenzenweger, Lonranger, Korfine, & Neff, 1997; Yalch & Levendosky, 2014; Yalch, Thomas, & Hopwood, 2012; see also Lenzenweger, 2008); this lends admission to college does not confer immunity to psychopathology (p. 348).  The use of online platforms is also broadly considered a viable way of administering self- and other-reports of personality (Johnson, 2010; McCrae & Weiss, 2007; Vazire, 2010a). However, there are often problems with online data collection that may compromise the integrity of data including selection bias, negative or positive reporting bias, and incomplete/random responding. In order to reduce selection bias, the survey name used in this study was neutral and conveyed little information about the purpose of 8reduce reporting bias, participation in Study 1 was anonymous, thus providing no incentive for participants to bias their response patterns negatively or positive. Measures  Maladaptive traits. I assessed maladaptive traits using two measures. The PID-5 (Krueger et al., 2012) is a 221-item instrument measuring the 25 maladaptive traits of the DSM-5 I'm not interested in making friends-point Likert-type scale ranging  = .84, range: .63 to .94). The static form of the CAT-PD (CAT-PD-SF; Simms et al., 2011) is a 216-I am emotionally 18  -point Likert-(mean trait  =.81, range: .73 to .89).   Criterion variables. I assessed criterion variables using nine empirically validated measures. Suicide risk. I assessed suicide risk using the Suicide Risk Scale (SRS; Plutchik, van Praag, Conte, & Picard, 1989). The SRS is a 26-item true-false instrument assessing suicide Have you ever told anyone you would commit suicide? = .89). Scores of 8 or higher on the SRS are indicative of high risk of suicide; 22% of participants in this study had scores above this cut-off.  Non-suicidal self-injury. I assessed NSSI using the Deliberate Self-Harm Inventory (DSHI; Gratz, 2001). The DSHI is a 17-item true-false instrument assessing deliberate self-Have you ever intentionally (i.e., on purpose) cut your wrist, arms, or other area(s) of your body (without intending to kill yourself)? = .86).  Hypochondriasis. I assessed hypochondriasis using the Short Health Anxiety Inventory (HAI; Salkovskis, Rimes, Warwick, & Clark, 2002). The HAI is a 14-item instrument assessing symptoms of hypochondriasis. For each item on this scale, respondents endorsed which of four y family/friends would say I do not my family/friends would say I am a hypochondriacer the last six months ( = .89).  Aggressive and rule-breaking behavior. I assessed aggressive and rule-breaking behavior using the Subtypes of Antisocial Behavior Questionnaire (STAB; Burt & Donnellan, 2009). The STAB is a 32-item instrument assessing aggressive behavior yielding physical 19  hit back when hit by othersmade fun of someone behind their back-broke into a store, mall, or warehousescales. On this instrument, respondents rated how often they have performed behaviors on a 5-point Likert- = .89, range: .88 to .92). Autocratic behavior. I assessed domineering behavior using the PA scale of the Inventory of Interpersonal Problems  Short Circumplex (IIP-SC; Soldz, Budman, Demby, & Merry, 1995). The IIP-SC is a 32-item instrument assessing problems people have when they interact with others. The IIP-SC is organized around eight octants of the interpersonal circumplex (IPC; Leary, 1957); the four-item PA scale assesses behaviors in the dominant octant I argue with other people too muchitems on a 5-point Likert- = .77).  Behavioral rigidity. I assessed behavior rigidity using the Rigidity subscale of the Pathological Obsessive-Compulsive Personality Scale (POPS; Pinto, 2011, 2016). The POPS Rigidity subscale is a 15-item instrument assessing rigid and inflexible behavioral tendencies people say I am critical of the way they do thingsrated items on a 6-point Likert- = .91).  Workaholic behavior. I assessed workaholic behavior using the Workaholism scale of the Mudrack Work Scales (MWS; Mudrack, 2004). The MWS Workaholism scale contains 10 items assessing time and energy spent thinking about work and excessive devotion to work. On this scale, respondents rated items on a 5-point Likert-one or not applicable to  very large amount of time and energy spent (time and energy spent thinking 20  about workthinking of ways to improve the quality of work provided to customers and/or co-workers) or from ery untrue of me to ery true of meI live, eat, and breathe my jobmaximally applicable to college students, I also wrote six additional items tapping workaholic I come to every optional review sessionI complete extra credit I e-mail course instructors follow-up questions from class discussions/lecturesI am involved in many extra-curricular groups related to my major(s)I volunteer for more academic activities (e.g., extra classes, volunteering to do research in labs) even though I am too busy in school as it isI routinely do most of if not all of group projects for classesinter-item consistency ( = .85).  Dissociative symptoms. I assessed dissociative symptoms using the Dissociative Experiences Questionnaire (DES; Bernstein & Putnam, 1986). The DES is a 28-item instrument assessing amnesia, depersonalization, and other dissociative symptoms. On this scale, respondents rated the percentage of time they experience the phenomenon depicted in each item ome people have the experience of finding themselves in a place and having no idea how they got there-point Likert-type scale rangin = .96). Scores of 45 or higher on the DES are indicative of high dissociation; 34% of participants in this study had scores above this cut-off. Cognitive dysfunction. I assessed cognitive dysfunction using 10 items from the IPIP database (Goldberg et al., 2006) assessing problems people have attending to and processing -point Likert-type scale  = .77). Of note, given that the CAT-PD 21  was informed by items drawn from the IPIP, I confirmed that there was no overlap between the items on this measurement of cognitive dysfunction and the CAT-PD-SF.  Procedures Students participated in the study in exchange for course credit. Questionnaires were administered online after the completion of a consent form. All procedures of the study were approved by the local Institutional Review Board. Personality instruments were administered first, followed by criterion measures.  Data analysis. I used a range of approaches within the General Linear Model (Kutner, Nachtsheim, Neter, & Li, 2005) to test study hypotheses, which I implemented using SPSS (version 22; IBM, 2014).  Previous research (e.g., Wright & Simms, 2014) has hinted that the CAT-PD traits overlap substantially with the traits in the benchmark DSM-5 model as well as offer additional traits that may supplement those in the model. It is thus important to establish the degree to which CAT-PD traits converge with and can be distinguished from DSM-5 traits. Accordingly, prior to testing the primary hypotheses of this study, I performed a series of preliminary analyses to evaluate the convergent and discriminant validity of CAT-PD and DSM-5 traits (as measured by the PID-5). To do this, I calculated correlations between CAT-PD and PID-5 traits and evaluated the relative magnitude of differences between convergent and average discriminant correlations.  In order to test incremental criterion validity, I sought to create multi-instrument principal component scores to represent the DSM-5 traits when this was justified by the convergent and discriminant correlation patterns. In other words, when convergent and discriminant patterns suggested that two similarly/identically named scales also had the strongest empirical 22  convergence, they were collapsed via principal components analysis into a single composite to represent the indexed trait in a manner that was free of any potential idiosyncrasies of either instrument. I planned to use PID-5 scales rather than component scores for traits where any discriminant correlation was larger than convergent correlations, given that the PID-5 most directly represents the DSM-5 system. I also used PID-5 scales in isolation to represent any DSM-5 traits without CAT-PD analogues. The goal was to have 25 DSM-5 (latent) traits represented, whenever empirically justified, by both the CAT-PD and PID-5 instruments.  Having established markers for the 25 DSM-5 traits, I tested incremental criterion validity using a series of hierarchical multiple linear regression (Cohen, Cohen, West, & Aiken, 2003). However, prior to doing this, a remaining issue concerned which traits should be selected for inclusion in the regression models. In order to maximize the clinical relevance of the findings, I selected for analysis those traits that might be most likely considered by clinicians as possibly predictive of each criterion of interest. To gage this, I obtained ratings of which maladaptive traits clinicians expected would predict clinically important behaviors by administering a brief survey (see Appendix 4) to a panel of local training clinicians (n = 16), each of whom endorsed which trait(s) he or she judged should be related to each outcome in the analysis. In order to arrive at a conservative but not overly stringent approximation of which than a majority of clinicians (operationalized here as at n  9) endorse as relevant for each behavior. However, I also considered any traits that only half of the panel (i.e., n = 8) selected, in conjunction with my doctoral advisor (Hopwood). Once traits were selected, I regressed criterion variables on these DSM-5 trait indicators in step 1 of hierarchical models, followed by CAT-PD traits not included in the DSM-5 system in step 2.  23  Results Preliminary analyses  Convergent and discriminant correlations. The vast majority of PID-5 scales correlated most highly with their anticipated CAT-PD analogues (see Table 2). The most notable exception to this was PID-5 Hostility, which correlated significantly more highly with CAT-PD Anger (r = .71) than it did with CAT-PD Hostile Aggression (r = .52). Other exceptions included PID-5 Manipulativeness, which correlated as highly with CAT-PD Domineering (r = .58) as it did with CAT-PD Manipulativeness (r = .58), and PID-5 Perceptual Dysregulation, which correlated as highly with CAT-PD Cognitive Problems (r = .69) as it did with CAT-PD Unusual Experiences (r = .68). In neither case were these differences significant. There were also no significant differences between PID--PD Non-Perseverance (r = .60) and Cognitive Problems (r = .59), or between PID-5 Unusual Beliefs and  correlation with CAT-PD Unusual Beliefs (r = .66) and Unusual Experiences (r = .65). In all other cases, the highest correlation in each PID-5 trait row (as indicated by underlined correlations in Table 2) was significantly (p < .05) higher than all other correlations in that row. In all cases, the correlations between PID-5 traits and their proposed CAT-PD analogues (i.e., convergent correlations; as indicated by italicized correlations in Table 2) were significantly higher than the discriminant correlations with all CAT-PD traits.  The majority of CAT-PD scales also correlated most highly with their anticipated PID-5 analogues. The most notable exception to this was Hostile Aggression, which correlated significantly more highly with PID-5 Callousness (r = .72) than it did with PID-5 Hostility (r = .52), and Non-Perserverance, which correlated significantly more highly with PID-5 Distractibility (r = .79) than it did with PID-5 Perseveration (r = .60). Other exceptions included 24  CAT-PD Relationship Insecurity, which exhibited its highest correlation with PID-5 Depressivity (r = .61) rather than with Separation Insecurity (r = 57) (and an equally high correlation with PID-5 Suspiciousness; r = .60), although this difference was not significant. Another exception was CAT-PD Manipulativeness, which correlated significantly more highly with PID-5 Deceitfulness (r = .72) than with PID-5 Manipulativeness (r = .58). There were also 6 instances in which CAT- correlation did not differ significantly from other traits in their respective columns, Cognitive Problems (correlated equally high with PID-5 Perceptual Dysregulation, Distractibility, and Eccentricity), Domineering (with Manipulativeness, Hostility, Grandiosity, Attention Seeking, and Deceitfulness), Fantasy Proneness (with Perceptual Dysregulation and Eccentricity), Health Anxiety (with Anxiousness, Perceptual Dysregulation, Emotional Lability, and Depressivity), Norm Violation (with Irresponsibility and Callousness), and Rudeness (with Hostility and Callousness). In all other cases, the highest correlation in each CAT-PD trait column (as indicated by boldfaced correlations in Table 2) was significantly higher than all other correlations in that column. As with PID-5 traits, the correlations between CAT-PD traits and their proposed PID-5 analogues (italicized values in Table 2) were significantly higher than the discriminant correlations with all PID-5 traits in all cases. These preliminary correlational analyses generally provided support for initial expectations about which CAT-PD traits would have analogues in the benchmark DSM-5 trait model and which would be unique. Exceptions to this included Hostility, which had an analogue in CAT-PD Anger (rather than Hostile Aggressiveness) and Distractibility, which had an analogue in CAT-PD Non-Perseverance (rather than having no analogue at all), and Perseveration, which had no analogue in the CAT-PD trait model. These preliminary analyses 25  also indicated that 10 CAT-PD traits were not direct analogues to those traits in the formal DSM-5 model: Cognitive Problems, Domineering, Fantasy Proneness, Health Anxiety, Norm Violation, Rigidity, Rudeness, Self Harm, Workaholism, and contrary to expectations, Hostile Aggression.  Principal components analyses. Based on these preliminary analyses, I conducted principal component analyses of the 23 PID-5 and CAT-PD traits identified as analogues (see diagonal of the first 23 rows in Table 2). The average amount of variance accounted for by each component was 85.47%. I used these composites as well as the PID-5 Deceitfulness and Perseveration scales as measurements of the 25 DSM-5 traits in subsequent regression analyses.  Clinician selection of traits The panel of training clinicians rated the initial set of 35 traits in terms of whether each 3. The majority of clinicians endorsed an average of 16.45 traits to predict each outcome variable (range of 9 to 21 traits). Clinicians were split (8 vs. 8) on 19 traits. The decision about whether to include these traits as predictors in the model were determined by a final expert consensus between myself and my dissertation chair, resulting in 9 traits being included and 10 excluded on these analyses (see Table 3).  Because clinicians took part in this survey prior to completion of the preliminary correlational and principal components analyses, their ratings relied on the expectation that certain CAT-PD traits were analogues to DSM-5 traits and that certain DSM-5 traits were unique. Some of these expectations were not supported by the preliminary analyses. Most importantly, CAT-PD Anger rather than CAT-PD Hostile Aggressiveness was the analogue of PID-5 Hostility, and Hostile Aggression rather than Anger was a unique to the CAT-PD. In order 26  to account for this, the selection of traits to be included in the regression analyses was updated such that DSM-5 Hostility was designated to be included if either Anger or Hostile Aggression was endorsed by the panel. The resulting change was minor and included the addition of Hostility as a predictor of three additional criterion variables (Behavioral Rigidity, Dissociative Symptoms, and Cognitive Dysfunction; see Table 4).  Criterion validity Correlations between these traits (DSM-5 traits plus unique CAT-PD traits) and criterion variables ranged from small to large (mean r = .28; see Table 5). Relative effects were clarified in regression analyses (see Table 6). DSM-5 traits provided a statistically significant portion of variance in each model (mean R2 = .36; range: .13 to .48). Unique CAT-PD traits selected by clinician panel accounted for significant additional variance over and above DSM-5 traits for all criterion variables examined (mean R2 = .09, range: .02 to .24). With few exceptions, individual unique CAT-PD traits hypothesized to incrementally predict criterion variables provided incremental main effects in virtually all cases. The exception to this was CAT-PD Fantasy Proneness, which did not provide incremental information about dissociative symptoms.  Of note, the results of this set of analyses may not be comparable to each other because each regression model contained a different number of predictors, both with respect to DSM-5 traits (ranging from 9 to 21) and unique CAT-PD traits (ranging from 1 to 6). For example, much less variance was accounted for by other traits in the prediction of cognitive dysfunction compared to suicide risk before CAT-PD Cognitive Problems was entered into the model. Additionally, controlling for only those DSM-5 traits selected by clinicians puts unique the CAT-PD traits at a comparative advantage.   27  Post hoc analyses In order to address the limitations in the primary analyses, I ran a series of post hoc analyses in which I regressed each criterion variable onto all DSM-5 and all unique CAT-PD traits. Results are listed in Table 7. As with the primary analyses, DSM-5 traits provided a statistically significant proportion of variance in each model (mean R2 = .40; range: .14 to .52), and unique CAT-PD traits accounted for significant additional variance over and above DSM-5 traits in each model (mean R2 = .08, range: .03 to .23). The sizes of the effects of most of the hypothesized CAT-PD traits were similar in these models to those effects yielded by the models of the primary analyses of the study, although some were no longer statistically significant (e.g., the effect of Norm Violation on physical aggression).  Comparison between primary and post hoc regressions yields some information about how accurate clinicians were at selecting traits for inclusion in the regression models. In all cases, clinicians selected the unique CAT-PD traits hypothesized to predict each criterion variable. In the majority of cases (i.e., for 7 out of 10 criterion variables), clinicians did not select all of unique CAT-PD traits that would predict statistically significant predictors (e.g., clinicians did not expect positive effects of Hostile Aggressiveness and Norm Violation, and negative effect of Rudeness on hypochondriasis). However, in all cases the effect sizes of these unselected traits were small ( < .20).  One potential confound in criterion validity is content overlap in the measurement of predictors and outcomes. In order to account for this, I did an item-by-item review of the items in the outcomes scales and those in the unique CAT-PD scales and identified 14 items across four scales (Domineering, Hostile Aggression, Rigidity, and Self Harm) associated with five different outcomes variables (suicide risk, NSSI, physical aggression, social aggression, and rigid 28  behavior). My criteria for identifying overlapping items was relatively liberal such that I designed items as overlapping if they had even some conceptual overlap. For example, the CAT-requently have thoughts about killing myselfwhich overlapped ave you ever thought about committing suicide?I re-ran the above post hoc regression analyses with theSE CAT-PD scales modified after removing overlapping items. For each outcome variable, the results were virtually identical to those in the original analyses. No trait that demonstrated a statistically significant effect in the initial analyses demonstrated a statistically insignificant effect when content was removed from it. Differences between effect sizes demonstrated by modified scales was also generally small, with largest being the difference between the effect of Rigidity on behavioral rigidity, which reduced from  = .39 to  = .31 when overlapping content was removed. Discussion  The results of Study 1 were generally consistent with hypotheses. Traits in the CAT-PD model that were not directly assessed by the DSM-5 model were generally able to add unique information about clinically relevant outcome variables, albeit variables selected for their potentially unique associations with those traits. In addition, there was generally strong convergent and discriminant validity for the CAT-PD and PID-5 measures of their common traits. Exceptions to this largely involved traits that were unique to the CAT-PD system. Consistent with hypotheses, results generally indicated that CAT-PD traits not represented in the DSM-5 system provide incremental validity over and above traits in the DSM-5 model for particular outcome variables. In all but one case (i.e., the association between Fantasy Proneness and dissociative symptoms) the individual CAT-PD traits yielded the hypothesized effects. These effects were present both using a set of traits selected by a panel of 29  clinicians and when using all maladaptive traits both within the CAT-PD and DSM-5 trait models. These results suggest that the somewhat more comprehensive approach to scale development and item selection taken in devising the CAT-PD trait model led to a model that may be broader in scope and thus one that may be mined for traits to add to the next iteration of the DSM-5 model.  The findings of strong convergent and discriminant validity for traits that seemed conceptually common to CAT-PD and PID-5 speaks to the general validity of both instruments. These results are in stark contrast to the generally low agreement between different measures of conventional PD diagnostic criteria (for review see Samuel, 2015). The comparatively better overlap between the two different measures of pathological traits in this study provides another reason why conceptualizing PDs in terms of dimensional traits may be advantageous to the conventional understanding of PDs as categorical symptom-based diagnoses.  On a related note of clinical utility, comparison of the primary and post hoc regression analyses indicated that the clinician panel was generally adept at selecting those traits that demonstrated the largest effects empirically. These findings may not represent clinicians more broadly, however, as the clinicians selected for inclusion in this study may have been better trained in and otherwise exposed to trait-based approaches to personality and PD assessment than the average clinician owing to their enrollment in a graduate program in which personality assessment was a mainstay of the clinical and research training. Even with this training, in most cases the panel did not select all traits that bore a statistically significant effect. These results suggest that while clinicians may be generally efficacious at using maladaptive traits to predict clinical phenomena, a more inclusive, data-driven approach to trait selection may provide more accurate information about the criterion validity of traits (see Dawes, Faust, & Meehl, 1989).  30   The results of this study provide some initial information about the degree to which additional traits provide incremental predictive information to the current maladaptive personality trait model in DSM-5. One limitation of this study was that the information about maladaptive traits was provided exclusively via self-report inventories. Given thought that self-particularly the case with maladaptive traits; Vazire, 2010b), it may also be useful to obtain information about traits from raters other than the self. This was the focus of my second study.    31  STUDY 2: PERSON PERCEPTION AND MALADAPTIVE TRAITS Although the nature and number of traits is important, who provides ratings of these traits is also important. The idea that perspective matters in rating aspects of human behavior comes from the tradition of person perception (Heider, 1967; Jones, 1964, 1990; Schneider, Hastorf, & Ellsworth, 1979; Zebrowitz, 1990), one implication of which is that other people may provide a unique perspective on the person whose personality is being assessed. Specifically, one commonly cited potential advantage of asking knowledgeable informants to provide personality data is that friends, relatives, and co-workers might be able to provide information about individuals (i.e., the targets of trait ratings) that those individuals do not recognize or willingly report themselves (Allport, 1937; Block, 1977; Dunning, 2005; Kenny, 1994; Vazire & Carlson, 2010, 2011). This notion assumes that targets and informants will agree somewhat on various target attributes, but also that informants may be able to provide additional valid variance in trait ratings because they see things somewhat differently than targets. Vazire (2010) suggested that agreement between targets will tend to be stronger for less evaluative and more observable traits. -Kenny, 2012; Simms, Zelazny, Yam, & Gros, 2010) and the nature of the relationship between target and informant (Connelly & Ones, 2010) may be other important factors influencing self-other agreement regarding personality attributes. Thus far, research on self-other agreement has not addressed the impacts of evaluativeness, observability, meta-perception, and relationship using comprehensive maladaptive trait models. However, the value of gathering multimethod data on maladaptive traits is increasingly recognized in personality research and clinical practice. In this study we examined the degree to which these factors impact self-other agreement with 32  respect to a relatively comprehensive set of maladaptive traits in order to derive conceptual principles that can be used to guide further research and practice.  Evaluativeness and observability A number of studies indicate that the degree to which targets and informants agree on their judgments of traits may depend at least in part on which traits are being assessed (e.g., Carlson & Furr, 2009; Funder, 1999, 2012; Oltmanns, Gleason, Klonsky, & Turkheimer, 2005; Oltmanns, Turkheimer, & Straus, 1998; Ready, Clark, Watson, & Westerhouse, 2002). Vazire (2010) proposed that agreement may be influenced by the degree to which traits are evaluative and observable. Evaluative traits entail a component of social desirability (or undesirability) that may lead targets to distort their ratings in a way that would lower target-informant agreement. Observable traits are those traits that influence behaviors that other people can perceive and report on relatively more easily, which should enhance agreement.  A number of studies support the idea that evaluativeness and observability influence agreement between target and informant ratings of traits. For example, with respect to evaluativeness, meta-analytic evidence suggests that target-informant agreement about Agreeableness (a socially desirable and thus evaluative trait) is relatively low compared to less evaluative traits (mean reliability-corrected  = .39; Connelly & Ones, 2010). With respect to observability, data from the same meta-analysis demonstrates that Extraversion (a trait that influences highly observable behaviors) is the most highly agreed upon of Big Five traits (mean reliability-corrected  = .51; Connelly & Ones, 2010).  Research on the influence of evaluativeness and observability on target-informant agreement has focused largely on normal-range personality traits. The generalizability of these findings to maladaptive traits is an open question to the degree that there may be differences in 33  how targets and informants perceive and subsequently rate maladaptive traits relative to normal-range traits. For instance, all maladaptive traits are to some extent evaluative by definition. It wou-informant agreement than has been observed for normal-range personality traits. This is consistent with meta-analytic data suggesting that target-informant agreement on maladaptive traits (including arrogance, impulsivity, and a range of other traits and diagnostic symptoms associated with personality disorder; r = .20) is substantially lower than that of normal-range Big Five traits (r = .38; Carlson & Kenny, 2012). In general, correlations between target- and informant- ratings of maladaptive traits tend to be small (r < .30; Cohen, 1992), with medium-sized correlations (r = .30-.50) representing relatively high target-informant agreement for such traits.  Not all maladaptive traits are equally observable. However, the reasons why maladaptive traits are observable may be different from why normal-range traits are observable. To a much greater extent than normal-range traits, high scores on maladaptive traits are associated with distress to oneself and/or to other people (APA, 2013; Bender et al., 2011). Part of what makes a maladaptive trait observable may be the degree to which targets and/or informants are aware of this distress (e.g., how much high levels of a trait bothers people). Different maladaptive traits are associated with behaviors that are likely to bother targets and informants in different ways. The Johari Window (Luft & Ingham, 1955) is a framework that may be useful for describing how maladaptive traits may be more or less observable to targets and informants. Specifically, in the Johari Window (Figure 1) a behavior may be observable to just informants (the blind area of the window), to just targets (hidden area), to both targets and informants (e.g., open area), or to neither targets nor informants (unknown area).  34  Although research on what kinds of maladaptive traits might be classified in which area of the Johari Window is limited, we can make tentative hypotheses about which general kinds of maladaptive traits might be more or less observable to targets and informants. For example, traits in the blind area of the Window may be traits that tend to bother informants more than the target sive maladaptive trait typology). Traits in the hidden area may potentially be similarly bothersome to informants more (e.g., Mistrust). Traits in the open area may be distressing for both the target and those around him or her (e.g., Anger, Affective Lability). Finally, traits in the unknown area of the Johari Window may be those traits associated with alterations in perception that, while potentially distressing, may not be readily apparent either to targets or informants (e.g., Cognitive Problems). The degree to which these traits are observable to targets and informants as evident by their placement in the Johari Window may be in part indicated by target-informant agreement. Relationship of target to informant Another important factor that may influence self-other agreement about maladaptive traits is that informants with different relationships to the target will tend to observe different aspects of the tarinformants with closer relationships to targets have overall higher agreement with targets than informants in less close relationships (e.g., Clifton, Turkheimer, & Oltmanns, 2004; Coolidge, Burns, & Mooney, 1995; Hill, Fudge, Harrington, Pickles, & Rutter, 1995; Malloy & Albright, 1990; Reno & Kenny, 1992), perhaps because they have more exposure to target behavior across a range of situations. Moreover, even when the target and informant are close to each other, the type of relationship the informant has with the target (e.g., peer vs. relative vs. romantic partner) 35  influences which traits are more highly agreed upon (Ferro & Klein, 1997; Harkness, Tellegen, & Waller, 1995). Previous research on the influence of target-informant relationship on maladaptive trait agreement has relied largely on PD diagnostic criteria rather than specific traits. Because PD categories target a more molar level of analysis than the specific traits which constitute personality disorder criteria, hypotheses about the impacts of relationship on agreement about maladaptive traits must be tentative. Understanding such patterns, as is one of the goals of the current research, is therefore critical for developing a more comprehensive understanding of the role of informant data in clinical assessment, because different informants may tend to provide different kinds of information about maladaptive traits. For example, romantic partners might be expected to agree more than other informants with targets on traits associated with anxiety about relationships (e.g., Relationship Insecurity) since they are most directly exposed to this kind of anxiety. In contrast, peers may be best positioned to agree with targets on traits associated with externalizing behaviors (e.g., Norm Violation) because it is with peers that these behaviors may most often be evoked.  Meta-perception A final factor that may impact target-informant agreement about maladaptive traits has to do with the mindset with which the target or informant approaches the assessment of these traits. Namely, research suggests that people are at least somewhat aware of differences between how they see themselves and how others see them, a concept referred to as meta-perception (Carlson & Kenny, 2012; Kenny, 1994; Laing, Phillipson, & Lee, 1966). For example, a number of studies suggest that correlations between how informants rate targets and how targets expect informants to rate them (i.e., when targets attempt to meta-perceive) are higher than correlations 36  between target- and informant-rated traits (Carlson & Furr, 2009; Solomon & Vazire, 2014). Similar results exist for meta-perception on the part of informants (Simms, Zelazny, Yam, & Gros, 2010), although research on informant meta-perception is limited with respect to maladaptive traits.  Research suggests that when targets are asked to meta-perceive how informants would rate them in terms of maladaptive characteristics, agreement is higher than when targets do not attempt to meta-perceive (e.g., Oltmanns, Gleason, Klonsky, & Turkheimer, 2005). For example, Carlson, Vazire, and Oltmanns (2011) found that informants high in narcissistic grandiosity appear to have some sense that other people view them as narcissistic when they are asked, suggesting that meta-perception on the part of targets may be most useful for those traits that are unobservable for targets but which are observable by informants (i.e., traits in blind area of the Johari Window). For these and other intrusive/bothersome traits, targets may have access to indirect information about their traits based on the reactions of informants, who may be bothered by and show their distress to people with high levels of these traits.  Meta-perception on the part of informants may also improve target-informant agreement on traits in the hidden area of the Johari Window. For these traits, informants may infer that targets hold implicit beliefs about other people that may influence their behavior. For example, Simms and colleagues (2010) found that when informants are asked to meta-perceive how depraved or odd targets say they are, their ratings provide additional information over and above conventional target-informant agreement.  There is little research on how meta-perception might influence agreement between targets and informants as a function of what relationship the target has to the informant. It is possible that certain relationships provide an advantage to targets and informants in terms of 37  observability, and that meta-perception can help to shore up agreement with targets and informants in different relationships. For example, romantic partners may have higher agreement with targets on Depressiveness than do peers, to the degree that people may be more likely to share their depressive experiences with their romantic partners than with their peers. However, targets may be able to meta-perceive that their peers see them differently on Depressiveness, leading to higher agreement on this trait with informants who are peers when targets meta-perceive than when they do not. Peers may also be able to meta-perceive that targets view themselves differently than peers view them, leading to higher target-informant agreement when informants who are peers meta-perceive than when they do not. In contrast, the influence of meta-perception on target-informant agreement on Depressiveness may be less pronounced in romantic partnerships because levels of Depressiveness are already mutually observable, leaving less room for meta-perceptual insight.  Current study In Study 2 I examined agreement between target- and informant-reported maladaptive traits. My hypotheses were as follows: Hypothesis 2.1. Target-informant agreement would vary based on the trait being assessed such that traits that are more observable to both targets and informants would be higher than agreement on traits that might be less observable to one or both parties. Hypothesis 2.2. Target-informant agreement would vary based on whether or not the targets or informants meta-perceived their trait ratings such that when either targets or informants meta-perceived their trait ratings, agreement would be higher than conventional target-informant agreement. 38  Hypothesis 2.3. Target-informant agreement would vary based on the relationship of the informant to the target, with different relationships higher agreements on different traits. However, because of the limited theory and previous research on which to base study hypotheses, these hypotheses are largely exploratory.  Method Participants  Participants in Study 2 were 623 students enrolled at Michigan State University who were recruited as targets and 664 people they nominated as informants (see also Yalch & Hopwood, under requested revisions). As in Study 1, targets were recruited via the HPR system sample, responses from 91 participants were excluded for having 10% or more of their data missing. The responses of 22 additional participants were discarded due to incorrect responses on one or more of four items designed to detect accurate responding (items to detect inaccurate responding were the same as above). This left a final sample of 510 targets. Mean age of targets was 20 years (SD = 1.86). Sex and other demographic information is follows: female (76%), White (73%), Asian (13%), Black (5%), multi-racial or other (8%).  Each target was asked to provide contact information for 3 people to serve as informants to report on the tinformant for potentially viable informants. Targets provided a total of 1109 viable informants (mean per person was 2.17). Of the 1109 informants sampled, 664 responded to the survey. From this initial sample, data from 97 informants were excluded for having 10% or more of their data missing. The responses of 19 additional participants were discarded due to incorrect responses on one or more of two items designed to detect accurate responding (n = 15; items to detect 39  inaccurate responding were the same as above; two items were used because the informant survey was much shorter than the target survey [~100 vs. ~600 items]), providing insufficient information to link their responses with the appropriate target (n = 3), or when it was discovered that the informant was actually the target responding for himself (n = 1). This left a final sample of 548 informants, whose responses corresponded to 311 targets. Of these informants, 40% (n = 217) were peers, 25% (n = 138) were mothers, 11% (n = 61) were romantic partners, 9% (n = 52) were fathers, 9% (n = 47) were siblings, and the rest were other relatives (n = 21) or other associates (classmate, n = 3; coworker, n = 2; team or club member, n = 2). Sex and ethnic percentages of informants were as follows: female (68%), White (81%), Asian (8%), Black (5%), multi-racial or other (6%).  Of note, because Study 2 relied in part on the same population for recruitment (i.e., MSU undergraduate students enrolled in HPR), it was possible that there was some overlap in samples. Targets in Study 2 (who were recruited through HPR) were asked whether they participated in (n = 32, 6%) indicated that they did. Participants in the informant-report portion of Study 2 were also asked if participants in the informant sample endorsed participating n = 16, 3%) and an n = 7, 1%). In no case did a target and informant in Study 2 mutually report on each other. Procedures Targets participated in the study in exchange for course credit. Informants were compensated with an entry into a raffle to win one of ten $50 cash prizes. Targets and informants 40  completed questionnaires online after the completion of a consent form. All procedures of the study were approved by the local Institutional Review Board.  Measures  In order to provide targets and informants with a broad array of maladaptive traits to rate, targets and informants were asked to rate the 33 maladaptive traits from the CAT-PD trait model (Simms et al., 2011). Targets and informants rated the traits using single-item trait descriptors on a 4-point Likert-Single-item descriptors and comparably brief assessments of traits are common way of assessing personality traits common way to assess personality traits (e.g., see Carlson, Vazire, & Oltmanns, 2011; Harkness, Tellegen, & Waller, 1995; Miller, Lynam, & Campbell, 2014; Yalch, Vitale, & Ford, in press) and reduce response burden, which can be useful for increasing responses from informants (Mullins-Sweatt, Jameson, Samuel, Olson, & Widiger, 2006).  Targets rated trait descriptors in three ways, in terms of (1) how much each descriptor applied to themselves, (2) how much targets thought other people in general thought each descriptor would apply to themselves, and (3) how much targets thought each specific informant they nominated thought each descriptor would apply to themselves. Informants rated trait descriptors in terms of (1) how much informants thought each descriptor applied to the targets, and (2) how much informants thought the targets would say each descriptor applied to the targets. participants who had more than one informant for some analyses (as described further below). Calculating informant responses in this way reduces the influence of idiosyncratic differences between informant responses, yielding a more generalizeable informant-report estimate.  41  In order to provide an alternative measure of personality functioning, targets (but not informants) also completed the static form of the CAT-PD (CAT-PD-SF; Simms et al., 2011), a 216-item instrument assessing 33 maladaptive traits (see description of the instrument in Study 1 for more details). As in the previous study, the trait scales of the CAT-PD-SF yielded adequate inter-item consistency (mean trait  =.81, range: .70 to .89).  Data analysis We tested whether various correlations between targets and informants were significantly between two dependent correlation coefficients. We selected a conventional criterion of p < .05 for statistical significance. However, both to highlight important effects and to address Type I error given the modest reliability of the single-item trait descriptors in this study, we only tested for differences in agreement when one or more agreement correlation was at least medium-sized (r  .3) and focused our interpretations on effect sizes.  Results As expected given that I was measuring maladaptive traits in a non-clinical sample, the variables tended to be positively skewed, with a modal trait rating of descriptive. There were no statistically significant differences in the relationships of informants nominated by male and female targets (e.g., friend, romantic partner, etc.). Reliability and validity of single-item trait assessments.  I evaluated the reliability of informant traits by calculating average measures inter-class correlation (ICC) across informants for each trait. The mean ICC was .47 across all informants for conventional informant ratings and .39 for informant ratings in which informants meta-42  perceived. We expected ICCs in this range given the low number of informants per target (maximum of three), the use of single items, and research indicating generally low inter-rater agreement on maladaptive traits (Keulen-de-Vos et al., 2011).  We also evaluated the reliability of single-item trait descriptors by comparing correlations computed using these descriptors to comparable correlations computed using the full CAT-PD-SF trait scales. This set of analyses provided information about how much variance captured by the single-CAT-PD-SF traits scales) and how much was error. Specifically, we correlated the trait profile provided by informants, as a group, with the trait profile provided by targets using single-item traits, and then computed the correlation between the informant trait profile with the target trait profile based on the CAT-PD scales. The correlation between target-informant agreement using single-item trait descriptors and target-informant agreement using target-rated CAT-PD-SF scales was .69 (p < .05), indicating that the agreement calculated using single-item trait descriptors overlaps substantially with agreement using multi-indicator target-rated trait scales. Furthermore, all 33 single-item trait scales correlated most highly with their CAT-PD-SF scale analogue (mean convergent r = .53). The correlations between single-item traits scales and all CAT-PD-SF scales except their CAT-PD-SF analogue were significantly lower than convergent correlations for all traits (mean discriminant r =.19; mean r = .34). These preliminary results suggest that the single-item trait descriptors provide relatively reliable and valid measures of maladaptive traits in this study. Of note, the profile of convergence between single-item trait descriptors and CAT-PD traits scales correlated highly with the profile of informant ICCs (r = .54). In addition, the target-informant agreement profile (see below) correlated highly both with convergent single-43  item/CAT-PD-SF correlations (r = .70) and with informant ICCs (r = .62). Overall, these results suggest differences across traits in terms of their reliaassociations at the level of individual traits by calculating a composite of convergent correlations, informant ICCs, and target-informant agreement for each trait (see Table 8). General target-informant agreement I examined general target-informant agreement across informant relationships to target by calculating correlations between target-rated single-item trait scales and informant-rated single-item trait scales. Average target-informant agreement was statistically significant but modest across all traits (mean r = .21; see Table 9). As expected, there was appreciable variability across traits. Rudeness as well as a number of traits associated with emotional distress (Anxiousness, Depressiveness, Health Anxiety, Relationship Insecurity) exhibited medium-size agreement coefficients. Most other traits exhibited small but statistically significant correlations between targets and informants.  Meta-perception. I examined the effect of target meta-perception on target-informant they thought other people in general thought each trait would apply to themselves and conventional informant trait ratings. I examined the effect of informant meta-perception on target-informant agreement across informants by calculating correlations between conventional trait would apply to themselves. Overall, meta-perception effects were modest, both when targets meta-perceived trait ratings (mean r = .22) and when informants meta-perceived trait ratings (mean r = .23). The only statistically significant difference between meta-perceived and non-meta-perceived trait agreement was for Callousness, for which target-informant agreement was 44  significantly higher when informants meta-perceived their ratings than when they did not. For all other traits, no significant differences were observed between target-informant agreement and agreement involving meta-perception on the part of either target or informant. However, agreement using target meta-perceived trait ratings were the only statistically significant correlations in ratings of Exhibitionism, Non-Perseverance, and Non-Planfulness, and agreement using informant meta-perceived ratings were the only statistically significant correlations in ratings of Rigidity and Submissiveness.  Target-informant agreement by relationship  I next examined target-informant agreement within specific informant relationships to the target. On average, target-informant agreement did not vary drastically across relationships (mean correlations ranged from .19 to .25; see Table 10). Consistent with hypotheses, differences between relationships were more pronounced when examining agreement according to individual traits. Target relationship to informant had a statistically significant influence on target-informant agreement for 22 out of 33 traits.  Peer-target agreement on Callousness was higher than father-target agreement on Callousness, although peers did not show uniquely high agreement with target-ratings (e.g., mother-target agreement was comparable to peer-target agreement, and sibling-target agreement was higher than mother-target agreement). Peers agreed more highly with targets on Grandiosity than did romantic partners, but siblings showed the highest agreement with targets on this trait. Peer-target agreement was comparably low on Hostile Aggressiveness. Romantic partners agreed the most relative to other informants with targets on Relationship Insecurity, as well as on Hostile Aggressiveness and Rudeness. Partner-target agreement was comparatively low with respect to Anxiousness and Romantic Disinterest. Mothers agreed the most relative to other 45  informants with targets on Health Anxiety and Irresponsibility. Fathers agreed the most relative to other informants with targets on Anhedonia, Anxiousness, and Unusual Beliefs. Fathers showed comparatively low agreement with targets on Callousness and Rudeness. Siblings agreed the most relative to other informants with targets on Anger, Callousness, Depressiveness, Emotional Detachment, Fantasy Proneness, Grandiosity, and Submissiveness but were comparably low on Mistrust.  Effects of meta-perception within relationships Next I examined target-informant agreement within specific informant relationships to the target. I examined the effect of target meta-perception on target-informant agreement within specific informant relationships to target how much they thought specific informants thought each trait would apply to themselves and conventional informant trait ratings.  On average, the effects of meta-perception on the part of targets (range of .22 to .33) and informants (range of .20 to .27) were modest (see Table 11). However, there were appreciable differences in the effect of meta-perception for specific traits depending on the informant relationship to the target for all traits but Health Anxiety, Mistrust, and Risk Taking. In general, target meta-perception increased agreement more often than did informant meta-perception, although this differed depending on the specific trait and the relationship of informant to target (see Table 11). Post hoc analyses Of note, it is assumed that variance between variables is equal when comparing correlations across groups. However, this assumption did not hold in these data, leading to possible bias. In order to address this, I recalculated correlations within a regression framework, 46  the results of which (standardized betas) have equal variance that can be more readily compared to each other. An additional advantage to this approach is that informant relationship can be controlled for in analyses across informant types. The results of these analyses were virtually identical. For comparisons across informant types, correlations between profiles of agreement using different methods of calculation (e.g., agreement without meta-perception, r vs. ) were virtually perfect (r  .99) even when controlling for informant relationship (see Table 12). Moreover, the effects of informant relationship were small in all cases ( < .20). For comparisons within informant types, correlations between profiles of agreement using different methods of calculation (r vs. ) were perfect (r = 1.00) and the results of comparisons between different types of agreement (both meta-perceived and non-meta-perceived, and between target-informant agreement between informants with different relationships to target) were identical.  An additional complication is that the number of informants in each different category of relationship to the target (e.g., peer, romantic partner, mother, etc.) was unequal (e.g., more peers than mothers were nominated and served as informants). This inequality raises the question of bias with respect to informant nomination, namely the effect of maladaptive traits on informant selection. I examined this in a series of post hoc analyses in which I computed differences in levels of each trait (measured via CAT-PD-SF scales) using independent-samples t-tests. Results indicated some statistically significant differences in trait levels based on whether targets did or did not nominate an informant of each relationship category (whether or not the contact information for the informant was viable; N = 510), although the sizes of these differences were generally modest (see Table 13). For example, targets who did not nominate romantic partners to serve as informants were higher in a number of antagonistic and disinhibited traits as well as higher in Romantic Disinterest (d = -.52) and Relationship Insecurity (d = -.25). 47  Discussion  The results of Study 2 indicated that target-informant agreement was generally modest, albeit with some variability depending upon the trait being rated. Meta-perception effects were also small, although these differences were more pronounced when the relationship of the informant to target was taken into account.   The results of the preliminary analyses in Study 2 indicated that the single-item trait descriptors used in this study provided reasonably reliable and valid assessments of maladaptive traits. However, it is also interesting to note the strong associations between convergent validity, inter-rater reliability, and target-informant agreement. In other words, there was an association between intra-rater reliability (convergent validity) and inter-rater reliability (target-informant agreement and informant-informant agreement). Although reliability is often understood in the context of the psychometric adequacy of a scale, it may be more meaningful in this case to understand these associations as an indication of the capacity for specific traits to be rated (i.e., the rateability of traits). For example, these preliminary results suggest that among the least rateable quartile of traits were Unusual Beliefs, Unusual Experiences, Fantasy Proneness, and Cognitive Problems. These traits all influence internal cognitive processes that may be unobservable to the informant as well as to the target in whom these processes occur (and which were generally uninfluenced by target or informant meta-perception). Within the framework of the Johari Window, these traits would be thus classified in the unknown area, unobservable to anyone. In contrast, many of the most rateable traits involved emotional distress. The examination of target-informant agreement (with and without meta-perception) add context to these initial analyses. 48  Consistent with previous research on maladaptive and otherwise evaluative traits, target-informant agreement on trait ratings were generally low. However, there were some differences in agreement depending on the traits being rated. In general, targets and informants agreed most highly on Anxiousness, Depressiveness, Health Anxiety, Relationship Insecurity, and Rudeness. We might classify these traits in the open area of the Johari Window. For Rudeness, this makes intuitive sense: rude behavior inherently bothers other people (such is the nature of rude behavior) and rude people are often aware that they are being rude to others  in other words, behaviors associated with Rudeness are mutually observable. For traits associated with emotional distress, it may also be the case that informants notice and are bothered by the emotional distress behavior with the informant) or because the target discloses his or her distress to the informant (e.g., the target reports how bad he or she is feeling).  Target-informant agreement for other traits was generally low (i.e., r < .30). However, meta-perception on the part of targets improved agreement for Exhibitionism, Non-Perseverance, and Non-Planfulness. In other words, targets were able to discern with some degree of accuracy how other people might rate them in terms of these traits, thereby rendering them more observable to the targets. It might make sense to classify these traits in the blind area of the Johari Window because targets may not initially acknowledge how exhibitionistic, non-perseverant, and non-planful they seem to other people (i.e., they are blind to how they were perceived in these respects), but can develop insight when thinking about how others might perceive them. We might speculate that traits that would be similarly intrusive (e.g., Domineering, Grandiosity, Irresponsibility, Risk Taking) would thus also fit in the blind area of the Window, although the results on meta-perception do not support this.  49  In contrast, meta-perception on the part of informants improved agreement for Callousness, Rigidity, and Submissiveness, suggesting that informants were able to discern how targets rated themselves on these traits. We might classify these traits into the hidden area of the Johari Window, since informants initially had lower agreement with targets on these traits but got better when they thought about how targets might perceive themselves. As with those traits tentatively classified in the blind area of the Window, we might also speculate that other traits associated with hostile and/or detached attitudes (e.g., Emotional Detachment, Manipulativeness, Mistrust, Social Withdrawal) might be classified in the hidden area of the Window, although again the results on meta-perception do not bear this out.  The limited impact of meta-perception makes sense for traits that we might classify in the unknown area of the Johari Window (Cognitive Problems, Fantasy Proneness, Peculiarity, Unusual Beliefs), for it may be difficult to achieve insight about traits that are minimally observed by either target or informant. However, as with previous classifications of traits into areas of the Window, these classifications should be considered tentative since meta-perception may only provide a clue as to how these traits might be classified most accurately. For example, although we might classify Exhibitionism, Non-Perseverance, and Non-Planfulness in the blind area of the Window, it may also be the case that targets see themselves as exhibitionistic, non-perseverant, and non-planful, but be able to understand that others do not see them that way, thus placing these traits in the hidden area of the Window. For still other traits (e.g., Workaholism), there is neither theoretical nor empirical reason to justify even tentative classification in the Johari Window. In any case, information about how targets and informants made their meta-perceptual ratings would be helpful for framing maladaptive traits in terms of the Johari Window, which future research on meta-perception could address by including open-ended 50  questions imploring respondents to explain any discrepancies between their meta-perceived and non-meta-perceived ratings of traits. Asking such questiand motivations for their traits ratings, which is important information that goes unmeasured in trait ratings confined to a Likert-type measurement scale. In any case, it is not clear why meta-perception improved target-informant agreement for some traits and not others seem like they may belong in the same area of the Johari Window. For example, meta-perception did not improve agreement for traits like Grandiosity and Irresponsibility, but did improve agreement for traits like Exhibitionism and Non-Planfulness, which we might expect to be similarly observable and which I tentatively placed in the blind area of the Window. One possibility is factors other than observability influence these traNon-Planfulness differ in how evaluative they are and that this influences the degree to which meta-perception may be useful in improving target-informant agreement. For example, Irresponsibility may be more evaluative than Non-Planfulness (i.e., it is worse to be knowingly irresponsible about doing something than to be too disorganized as to remember it) and that may make meta-perception less efficacious in improving agreement on Irrresponsibility. More generally, that the effects of meta-perception were less pronounced may be in part due to the specificity of meta-perception to specific relationships of the informant to the target, which is consistent with some research on the role of meta-perception in the rating narcissistic traits (Carlson, Vazire, & Oltmanns, 2011).   The findings of Study 2 indicated that target-informant agreement varied according to the le, romantic partners agreed more than other informants with targets on Relationship Insecurity, which makes sense given that it is in 51  romantic relationships that behaviors associated with this trait should be most manifest. Romantic partners also showed the highest agreement on Hostile Aggressiveness and Rudeness. These results suggest that traits that involve aggression may be particularly evoked in the context of romantic relationships. This idea is consistent with theory suggesting that disruptions in intimate relationships are a primary driver of aggression (Bartholomew & Allison, 2006; Levendosky, Lannert, & Yalch, 2012). In contrast, family members (mothers, fathers, and siblings) agreed most strongly with targets on a range of traits associated with emotional distress (Anhedonia, Anxiousness, Depressiveness, and Health Anxiety). These results imply that family members (parents in particular) may be especially attuned to the emotional functioning of their children, an idea that has long been established in the developmental literature (e.g., Bowlby, 1969; Stern, 1995).  When agreement was broken down by informant relationships, target meta-perception increased agreement somewhat more than informant meta-perception. This suggests that targets generally have more insight into how they are perceived by others than others have about how targets perceive themselves. Target meta-perception was particularly high and informant meta-perception particularly low within romantic partnerships. That comparatively better self-understanding than other-understanding is particularly pronounced in romantic relationships may indicate a tendency for people to self-monitor in romantic relationships, a tendency that may be all the more common in a young adult sample in which relationships are likely less well developed. The exception here was with traits associated with aggression: target-informant agreement is generally high among romantic partners for Hostile Aggressiveness compared to informants in other relationships, and romantic partners appear to have good insight about 52  part of romantic partners for aggression. In other words, people appear to be especially in tune with how aggressive their partners are. Given the often bidirectional nature of aggression between romantic partners (Johnson, 2008), it may be fruitful for future research to examine the role of meta-perception on agreement between aggressive and other maladaptive traits from a dyadic perspective to discern the degree to which these guardedness may be reciprocal.  Results also suggest that targets are aware of how their mothers rate their aggressive and -perception. In contrast, targets do not appear to have much insight about how their fathers rate their traits, although fathers do have insight into what targets say about themselves with respect to a number of different traits. This discrepancy between the eff-perception underscores the uniqueness of the relationships of mothers versus fathers and their children. For instance, the closeness of the mother-child relationship (Stern, 1997) may permit the child to understand how the mother sees him or her better than this closeness permits the mother to know how the child sees him or herself. Similarly, the distance between the father and child may allow for a more detached view of how the child perceives him or herself, but not vice-versa.   53  GENERAL DISCUSSION  In this study I examined the criterion validity of and the influence of person perception on a comprehensive set of maladaptive personality traits. Results generally indicated that the additional traits of the CAT-PD maladaptive trait model provide incremental predictive information over and above the traits of the benchmark DSM-5 trait model, and that informant-ratings of these traits likely provide additional information over and above target-ratings of these traits.  Criterion validity The results of Study 1 suggest that the additional traits provided by the CAT-PD trait model improve upon the criterion validity of the DSM-5 trait model. That being said, the inclusion of additional traits in the DSM-5 system, such as the unique CAT-PD scales evaluated in this study, is a complicated issue. One may question whether the incremental effects from a study like this really justify the added complexity of such a model, particularly since the outcome variables were selected to relate to unique CAT-PD traits by design. One may also argue that some of the CAT-PD scales that provided additional effects are not actually personality scales per se. For instance, Health Anxiety might be considered a scale measuring attitudes about health and well-being, which some may regard as falling outside of the personality domain. On the one hand this scale, like other CAT-PD scales, fits empirically as a neuroticism facet in an FFM framework (McCrae & Costa, 2008), suggesting strong associations to personality as it is commonly defined. On the other hand, trait models are so comprehensive that a wide range of individual differences variables in psychology could fit into that framework, including constructs e.g., DSM-al., 2011).  54  Hierarchical models of personality (e.g., Wright et al., 2012b, 2013a), in which broad lower levels by facet scales from a variety of domains including psychopathology, attitudes, or adaptations, may be a useful scheme for dealing with this issue. Hierarchical models have important implications for taxonomy and clinical practice. For instance, it is interesting that the FFM can accommodate so many constructs, including those that have not traditionally been only for personality and personality disorder, but individual differences in personality and psychopathology more generally. One implication is that the FFM could be used to reorganize the content of the entire DSM-5, as opposed to just the pathological traits involved in PD.  A second implication is morsuggesting that it depends on what level of the hierarchy is being considered. The clinician, too, may fruitfully consider different levels of personality hierarchies in their practice. For general screening contexts, the Big Five is probably a useful lens, whereas for specific formulations, lower-order facets are likely to be more helpful. From his perspective, traits like Health Anxiety  Although the as-needed assessment of specific traits to address specific concerns may be clinically expedient, it bears considering whether some of the additional CAT-PD traits in this study might be added to future editions of the DSM trait model. The addition of such traits might be warranted if the criterion variables were of sufficient clinical importance, and criterion validity of the trait in question were sufficiently large. For instance, it may be worth considering adding Self Harm to a DSM-5.1, given these findings that this trait exhibits substantial 55  incremental effects on the prediction of suicidal and parasuicidal behaviors, which are common, of obvious clinical relevance, and not currently assessed directly in other parts of the DSM. behaviors are important clinically and that a trait assessing these behaviors be considered in a maladaptive trait inventory. Similarly, Cognitive Problems demonstrated incremental effects on symptoms of dissociation and of cognitive dysfunction more generally. Given that such symptoms are important enough to be assessed in omnibus clinical inventories (e.g., the Personality Assessment Inventory; Morey, 1991) and are empirically associated with pathological traits (for review see Lynn et al., 2012, 2014), a trait like Cognitive Problems might also be worth including in future editions of the DSM. Person perception Thus far the discussion has focused primarily on traits assessed via self-report. However, the overall low levels of target-informant agreement on maladaptive traits demonstrated in Study 2 suggest the potential for informants to provide incremental information about a person in clinical personality assessment (Clark, 2007; Hopwood & Bornstein, 2014). The results of this study also suggest that the potential for incremental information varies depending on the relationship of the target with the informant. These findings could be leveraged in clinical assessment when deciding what kind of incremental information would be most useful (i.e., whom clinicians should recruit as informants in clinical personality assessment). For example, given targets comparatively high agreement with their romantic partners about Hostile Aggressiveness, Rudeness, and Relationship Insecurity, romantic partners might only provide corroborating information about these traits. However, partners may provide more unique information about Affective Lability, Manipulativeness, and Non-Planfulness. Given that 56  personality, it may be useful to recruit multiple targets in clinical assessment.  The results of Study 2 extend previous literature on target-informant of maladaptive personality characteristics, many of which used PD diagnostic characteristics as markers of personality. In addition to being more consistent with the probable direction of maladaptive personality assessment (Krueger & Markon, 2014; Widiger et al., 2012b), by assessing the perception of maladaptive personality in terms of traits, these results can be more readily compared to the broader literature of person perception on normal-range personality traits (see Funder, 1999, 2012).  From a methodological perspective, the results of Study 2 also demonstrated that single-item trait descriptors provide a reliable and valid measurement of maladaptive traits. The use of such descriptors reduces the response burden of survey respondents, permitting a relatively large sample at a relatively low cost to the researcher. However, this reduced response burden comes at some expense. For example, the low variability in the trait descriptors may have limited the ability to find statistically significant effects; indeed, this was also the case in Samuel and -informant agreement study in which they used both single-item descriptors and multi-indicator trait scales. The way that I asked targets and informants to rate descriptors was also using a unipolar scale, which may have further reduced variability relative to a bipolar scale (e.g., those who were very gregarious and more normatively gregarious would both be categorized as a 1 on the 1-4-point scale I used to measure Social Withdrawal in this study). The combined use of single-item descriptors, unipolar response format and general lack of response variability, and lack of detail about the rationale and motivation for trait ratings 57  necessarily constrains interpretations of these results. Future research should thus balance response burden with the need for variance in data obtained.  Future directions The results of this study have a number of implications for future research. For example, future work on criterion validity should incorporate a wider range of clinically important outcome variables. In Study 1, I focused on those outcomes for which I hypothesized that the CAT-PD traits would be at a predictive advantage. Future work on incremental criterion validity should thus include outcomes for which the DSM-5 traits might be at a predictive advantage. For example, given that the CAT-PD lacked clear analogues for Deceitfulness and Perseveration, such work could involve examining the possible incremental validity of the DSM-5 traits over the CAT-PD traits in the prediction of Machiavellianism (Deceitfulness) or excessive worry (Perseveration). This line of future research might also include other outcomes for which neither the formal DSM-5 traits nor unique CAT-PD traits might be at a predictive advantage. Given that the DSM-5 traits were developed as an alternative way to assess PD, diagnostic symptoms of PD may be particularly appropriate criteria, as might other outcomes associated with personality disorders (e.g., symptoms of depression, substance use). It is likely that there are other behaviors associated with PD that the traits of neither the DSM-5 nor CAT-PD models are well poised to predict. For example, the DSM-5 trait model may not be sufficient for the assessment of problematic warmth associated with dependent PD (Bornstein, 2011; Gore & Pincus, 2013), a problem demonstrated in recent research (Gore & Widiger, 2015; Williams & Simms, 2015; Wright et al., 2012a). Moreover, the CAT-PD model similarly does not contain traits specifically associated with pathological warmth (Williams & 58  Simms, 2015). Future research should thus examine which traits, if any, might be useful to assess these and possibly other problems.  In a similar vein, the results of Study 2 were also limited in the traits included in the model. For example, because neither Deceitfulness nor Perseveration have analogues in the CAT-PD trait model, these results do not provide information about the degree to which informants might provide unique information about these traits relative to targets or whether meta-perception might influence target-informant agreement on these traits. Future research should thus examine target-informant agreement (with and without meta-perception) on these traits as well as on potential traits not represented in either the DSM-5 or CAT-PD trait models (e.g., those associated with pathological warmth). Of note is that the criterion variables of Study 1 were self-reported outcomes rather than actual behavior, and the outcome of Study 2 was agreement rather than prediction. I did not examine, for example, whether target- or informant-ratings of Self Harm was more predictive of  target and informant ratings account for unique variance in the prediction of suicidal behavior. However, a primary goal of personality assessment, whether provided by the target of this assessment or an informant, is the accurate prediction of behavior (Durbin & Hicks, 2014; Wiggins, 1973). Future research should examine the influence of target- and informant-rated maladaptive traits on behaviors, although doing so may be tricky.  For many clinical outcomes assessment via self-report in this study (e.g., suicide, aggression), objective criteria are hard to come by. For example, completed suicides and objective accounts of aggression (e.g., arrests for assault) have a fairly low base rate even outside of a college sample. Studying this would require not only a substantially larger sample than this one, but also a prospective design (e.g., in order to acquire ratings relevant to suicide before 59  suicides are completed), although with a enough funding this may be possible. However, for some criterion variables examined in Study 1, there may be laboratory tasks that provide a suitable proxy for actual behavior. For example, maladaptive traits that are theoretically linked to social behavior like Domineering and Hostile Aggressiveness may influence social behavior as demonstrated in group or dyadic tasks performed in the laboratory. For other criterion variables, laboratory tasks may actually be the most optimal means of obtaining objective behavioral outcomes. For example, cognitive disturbance may perhaps be measured optimally using a battery of neuropsychological assessment measures administered in a controlled setting. Future research should thus also examine the predictive validity of target- and informant-rated maladaptive traits on actual behaviors or performance on tasks likely associated with these behaviors.  Strengths and limitations  One strength of the design of this study is its size. Both Study 1 and Study 2 have combined samples of over 1,000 participants. This provided analyses with sufficient power to detect statistically significant effects and, more importantly, to be confident about the size of these effects. In particular, the large sample of targets and informants in Study 2 also enabled me to examine target-informant agreement (with and without meta-perception) within as well as across a number of different target-informant relationships, something that was not feasible in previous research on target-trait agreement. This provided specific information about which informants are privy to and have insight about different kinds of maladaptive traits.  This study also had a number of limitations, which point to other directions for future research. One of these limitations also has to do with the sample. Although large, the entire sample of Study 1 and the target sample of Study 2 were both drawn from a student population. 60  With respect to criterion validity, a college sample almost certainty had a lower incidence of physical and socially aggressive behavior than, for example, clinical, incarcerated, or military samples. Accordingly, estimates of criterion validity in this study may differ in other samples in which the base rates of the criteria of interest are higher. With respect to Study 2, that all targets were college students had implications for the kinds of informants targets recruited. For example, few targets in this study nominated coworkers as potential informants who knew them well, presumably because most college students spend comparatively less time engaged in full-time work than most non-students of the same age. However, the context of the work environment may pull for different aspects of personality that are not observable to peers, romantic partners, or family members. In a similar vein, the romantic partnerships of college students are likely different in important ways from the romantic partnerships of non-students (e.g., in terms of maturity, intimacy, duration, etc.). For example, college students may be working harder to make a good positive impression on their (presumably relatively new) romantic relationships than people in marriages or other established partnerships, the latter of whom may be more likely to expose their less desirable characteristics, thereby providing more personality-relevant data to be observed. This may account for the particularly poor ability of informants to meta-perceive their samples in which targets and informants are likely different in important ways.  In a similar vein, participants who were targets in this study also chose their informants, not all of whom provided responses to the study. Despite efforts to reduce response bias in both studies, this method of informant recruitment embeds selection and response bias into the Study 2 (Leising, Gallrein, & Dufner, 2014). Evidence of selection bias was particularly evident in 61  Study 2 given the differences in some traits based on relationship of informants nominated. Future research could limit this bias by a more structured recruitment of informants.  Another limited of this study is its cross-sectional design. This is particularly the case for Study 1, for which a longitudinal design would have enabled the examination of predictive validity rather than more simply criterion validity, the former of which is more important from a clinical perspective. A longitudinal design would also have permitted the examination of the stability of maladaptive traits, which has been established for normative traits and some maladapative traits, but to a much lesser degree for the traits of the DSM-5 and CAT-PD. Conclusion The assessment of maladaptive traits is an important area of research that is receiving increased attention in the empirical literature. In this study I assessed not only the traits themselves and clinically important outcomes associated with them, but how different people perceived these traits, and found that different people perceive and have insight into different maladaptive aspects of personality. Results generally support the validity of maladaptive traits for clinical practice, as well as the DSM-5 model in particular, while also suggesting that the relatively more comprehensive CAT-PD model can be used as a guide for expanding the model to maximize its content coverage and clinical utility. Results also highlight the potential value of informant data in clinical personality assessment while also pointing to issues, including the nature of traits, meta-perception, and relationship between informant and target, that need to be considered when interpreting informant data.   62                       APPENDICES  63  Appendix 1: Tables  Table 1. Comparison of proposed DSM-5 traits, PID-5 traits, and CAT-PD traits.  FFM Factor Domain Proposed DSM-5 traits PID-5 traits CAT-PD traits Detachment Anhedonia Anhedonia Anhedonia Activity/Energy Exhibitionism Attention-Seeking Exhibitionism Seductiveness Dramaticism Entitlement Grandiosity Grandiosity Arrogance Social Avoidance Withdrawal Social Withdrawal Social Aloofness Emotional Detachment Restricted Affectivity Emotional Detachment Romantic Disinterest Intimacy Avoidance Romantic Disinterest Negative affect Stress Reactivity Emotional Lability Affective Lability Affective Lability Anxious Apprehension Anxiousness Anxiousness Fearfulness Depressive Dysphoria Depressivity Depressiveness Shame/Guilt Low Self-Esteem/Pessimism Non-Suicidal Self-Injury   Self-Harm Suicidality   Submissiveness Submissiveness Submissiveness Exploitability Rejection Sensitivity Separation Insecurity Relationship Insecurity Jealousy Hypochondriasis   Health Anxiety  Note: Gaps in conceptual coverage indicated by gray spaces.   64  Table 1   FFM Factor Domain Proposed DSM-5 traits PID-5 traits CAT-PD traits Antagonism Callousness Callousness Callousness Selfishness Manipulativeness Manipulativeness Manipulativeness Deceitfulness Deceitfulness Blame Externalization Domineering   Domineering Conduct Problems Depravity Norm Violation Oppositionality Rebellious Non-Conformity Aggression Hostility Hostile Aggression Hostility Anger/Irritability   Anger Social Insensitivity Rudeness (Dis-) Inhibition Urgency (Emotional Lability) (Affective Lability) Lack of Premeditation Impulsivity Non-Premeditation Lack of Concern for Consequences Lack of Perseverance Perseveration Non-Perseverance Recklessness Risk-Taking Risk-Taking Excitement-Seeking Perfectionism Rigid Perfectionism Perfectionism Orderliness Rigid Propriety Rigidity Undependability Irresponsibility Irresponsibility Excessive Achievement-Striving   Workaholism Psychoticism Magical Thinking Unusual Beliefs & Experiences Unusual Beliefs Perceptual Aberrations Perceptual Dysregulation Unusual Experiences Cognitive Dysregulation   Cognitive Problems Obliviousness Distractability Absorption   Fantasy Proneness Peculiarity Eccentricity Peculiarity Suspiciosness Suspiciousness Mistrust Cynicism 65  Table 2. Correlations between traits.      CAT-PD Traits Anhedonia Anxiousness Exhibitionism Callousness Depressiveness Non-Perseverance Peculiarity Affective Lability Grandiosity Anger Non-Planfulness Romantic Disinterest Irresponsibility Manipulativeness PID-5 Traits Anhedonia   .81 .42 -.02 .45 .73 .47 .35 .47 .32 .39 .25 .28 .47 .39 Anxiousness   .34 .79 .13 .06 .52 .45 .29 .56 .16 .41 .10 .01 .10 .12 Attention Seeking   -.01 .19 .81 .26 .06 .28 .23 .20 .49 .22 .26 -.05 .15 .38 Callousness   .46 .12 .28 .81 .34 .33 .35 .27 .62 .40 .37 .27 .50 .68 Depressivity   .67 .54 .13 .38 .77 .53 .42 .52 .32 .38 .32 .26 .46 .38 Distractibility   .38 .53 .24 .27 .45 .79 .42 .49 .26 .36 .42 .10 .39 .29 Eccentricity   .36 .37 .25 .35 .43 .48 .79 .39 .34 .34 .34 .13 .26 .35 Emotional Lability   .30 .61 .24 .13 .46 .46 .34 .71 .24 .52 .21 .02 .22 .19 Grandiosity   .20 .13 .48 .54 .13 .21 .25 .18 .76 .26 .23 .16 .25 .54 Hostility   .38 .47 .32 .44 .40 .45 .38 .54 .48 .71 .27 .09 .24 .43 Impulsivity   .22 .21 .36 .35 .25 .43 .36 .36 .31 .29 .69 .08 .40 .38 Intimacy Avoidance   .40 .16 .02 .44 .33 .26 .25 .21 .26 .19 .26 .62 .37 .31 Irresponsibility   .45 .23 .29 .54 .38 .52 .34 .39 .47 .33 .53 .25 .70 .58  Notes:  indicates r is not statistically significant at p < .05 (all other values statistically significant); italicized values indicate anticipated trait alignments (see Table 1); underlined values indicate highest correlation of a PID-5 trait; boldfaced values indicate highest correlation of a CAT-PD trait; discriminant correlations are the average of all of the correlations except the one hypothesized to be convergent.  66  Table 2 (con).      CAT-PD Traits Anhedonia Anxiousness Exhibitionism Callousness Depressiveness Non-Perseverance Peculiarity Affective Lability Grandiosity Anger Non-Planfulness Romantic Disinterest Irresponsibility Manipulativeness PID-5 Traits Manipulativeness   .15 .16 .55 .41 .15 .27 .30 .16 .52 .23 .27 .02 .19 .58 Perceptual Dysregulation   .47 .43 .30 .49 .46 .53 .51 .53 .50 .38 .44 .25 .46 .49 Restricted Affectivity   .38 .10 .13 .51 .30 .25 .31 .02 .31 .11 .22 .26 .21 .34 Rigid Perfectionism   .20 .42 .26 .17 .24 .19 .18 .34 .35 .29 -.03 .09 -.01 .18 Risk Taking   -.06 -.13 .36 .18 -.03 .06 .24 .00 .15 .07 .48 -.10 .09 .20 Separation Insecurity   .29 .46 .29 .16 .40 .43 .23 .44 .29 .31 .20 -.02 .20 .26 Submissiveness   .14 .38 .17 .02 .26 .31 .13 .26 .13 .11 .08 -.01 .08 .12 Suspiciousness   .47 .39 .16 .38 .48 .39 .40 .46 .37 .42 .27 .22 .33 .41 Unusual Beliefs & Experiences .34 .28 .31 .43 .34 .36 .52 .38 .49 .32 .35 .20 .33 .47 Withdrawal   .59 .38 -.04 .47 .55 .42 .41 .34 .32 .35 .19 .34 .32 .32 Deceitfulness   .35 .23 .49 .54 .31 .44 .34 .32 .61 .33 .36 .09 .44 .75 Perseveration   .42 .54 .28 .33 .47 .60 .43 .53 .38 .40 .35 .16 .35 .36 Discriminant   .31 .32 .25 .35 .35 .38 .33 .35 .36 .31 .28 .13 .28 .37   67  .      CAT-PD Traits Unusual Experiences Emotional Detachment Perfectionism Risk Taking Relationship Insecurity Submissiveness Mistrust Unusual Beliefs Social Withdrawal Cognitive Problems Domineering Fantasy Proneness Health Anxiety Hostile Aggressiveness PID-5 Traits Anhedonia   .40 .43 .11 .19 .55 .36 .53 .31 .64 .49 .22 .29 .37 .42 Anxiousness   .12 .24 .37 -.01 .53 .46 .39 .06 .33 .40 .27 .36 .45 .13 Attention Seeking   .26 .00 .37 .29 .22 .25 .15 .29 -.07 .24 .57 .49 .19 .33 Callousness   .55 .33 .16 .41 .35 .17 .47 .55 .41 .36 .48 .31 .29 .72 Depressivity   .47 .39 .18 .27 .61 .50 .53 .34 .54 .56 .25 .42 .41 .43 Distractability   .30 .33 .18 .22 .45 .50 .33 .20 .37 .68 .28 .55 .39 .30 Eccentricity   .38 .38 .25 .34 .42 .35 .45 .32 .43 .65 .36 .64 .32 .37 Emotional Lability   .31 .06 .26 .12 .51 .46 .36 .22 .25 .45 .31 .43 .42 .27 Grandiosity   .38 .19 .40 .29 .22 .15 .33 .46 .20 .23 .57 .38 .22 .52 Hostility   .30 .26 .37 .24 .47 .26 .48 .30 .36 .42 .58 .43 .38 .52 Impulsivity   .38 .23 .07 .52 .30 .26 .26 .32 .20 .45 .29 .41 .22 .40 Intimacy Avoidance   .37 .39 .08 .24 .29 .22 .35 .34 .43 .34 .17 .24 .20 .37 Irresponsibility   .58 .28 .03 .39 .41 .35 .40 .52 .36 .51 .34 .36 .38 .59    68  .      CAT-PD Traits Unusual Experiences Emotional Detachment Perfectionism Risk Taking Relationship Insecurity Submissiveness Mistrust Unusual Beliefs Social Withdrawal Cognitive Problems Domineering Fantasy Proneness Health Anxiety Hostile Aggressiveness PID-5 Traits Manipulativeness   .27 .17 .36 .33 .23 .21 .30 .35 .13 .25 .58 .44 .16 .45 Perceptual Dysregulation   .68 .35 .24 .42 .50 .44 .51 .57 .43 .69 .38 .65 .45 .56 Restricted Affectivity   .25 .66 .26 .31 .23 .16 .33 .25 .44 .30 .26 .32 .11 .32 Rigid Perfectionism   .16 .16 .76 .07 .31 .26 .29 .19 .23 .20 .45 .30 .28 .20 Risk Taking   .16 .08 .04 .68 .05 -.02 .09 .18 -.10 .14 .16 .27 -.05 .24 Separation Insecurity   .29 .15 .30 .14 .57 .49 .33 .20 .21 .39 .30 .34 .36 .28 Submissiveness   .06 .10 .23 .00 .28 .58 .10 .03 .16 .25 .18 .23 .19 .08 Suspiciousness   .37 .35 .23 .22 .60 .41 .72 .33 .47 .47 .31 .37 .37 .41 Unusual Beliefs & Experiences .65 .26 .28 .42 .36 .30 .45 .66 .35 .51 .42 .59 .36 .52 Withdrawal   .32 .55 .26 .18 .45 .30 .50 .31 .76 .43 .26 .38 .30 .38 Deceitfulness   .40 .29 .25 .35 .40 .32 .42 .40 .30 .43 .56 .45 .28 .56 Perseveration   .37 .33 .39 .27 .51 .53 .42 .31 .41 .59 .39 .55 .40 .39 Discriminant   .34 .26 .24 .26 .39 .32 .37 .31 .31          69  .      CAT-PD Traits Norm Violation Rigidity Rudeness Self Harm Workaholism Discriminant PID-5 Traits Anhedonia   .34 .40 .32 .52 .13 .37 Anxiousness   .01 .36 .26 .28 .26 .27 AttentionSeeking   .26 .40 .39 .12 .27 .24 Callousness   .57 .50 .59 .42 .17 .40 Depressivity   .35 .42 .41 .68 .16 .41 Distractability   .29 .43 .39 .33 .12 .35 Eccentricity   .36 .46 .55 .36 .24 .38 Emotional Lability   .16 .39 .35 .36 .19 .30 Grandiosity   .36 .54 .44 .17 .31 .31 Hostility   .33 .60 .62 .31 .28 .40 Impulsivity   .52 .30 .45 .30 .10 .31 Intimacy Avoidance   .29 .25 .32 .40 .13 .27 Irresponsibility   .58 .41 .47 .45 .06 .40    70  .      CAT-PD Traits Norm Violation Rigidity Rudeness Self Harm Workaholism Discriminant PID-5 Traits Manipulativeness   .36 .48 .46 .17 .29 .29 Perceptual Dysregulation   .48 .49 .51 .52 .22 .46 Restricted Affectivity   .30 .37 .34 .23 .25 .27 Rigid Perfectionism   .04 .45 .22 .16 .48 .23 Risk Taking   .46 .09 .28 .11 .06 .12 Separation Insecurity   .18 .39 .31 .31 .20 .28 Submissiveness   -.03 .28 .16 .15 .18 .15 Suspiciousness   .35 .40 .39 .36 .18 .36 Unusual Beliefs & Experiences .44 .46 .46 .41 .25 .39 Withdrawal   .25 .46 .36 .41 .26 .36 Deceitfulness   .49 .54 .54 .31 .18  Perseveration   .29 .55 .43 .35 .30  Discriminant           71  Table 3. Traits selected by clinician panel to predict criterion variables.      Suicide risk NSSI Hypochondriasis Physical aggression Social aggression DSM-5 traits Anhedonia       Anxiousness Attention Seeking      + Callousness       Deceitfulness   +   Depressivity + + Distractibility           Eccentricity        Emotional lability Grandiosity       Hostility   Impulsivity     Intimacy Avoidance Irresponsibility   Manipulativeness  Perceptual Dysregulation     Perfectionism      Perseveration   +    Restricted Affectivity    Risk Taking   Separation Insecurity Submissiveness         Suspiciousness Unusual Beliefs       Withdrawal   Unique CAT-PD traits Anger   Cognitive Problems +   Domineering       Fantasy Proneness +     Health Anxiety         Norm Violation +   Rigidity    Rudeness       Self Harm +   Workaholism           Notes:  indicates that the majority of the clinician panel rated trait as a predictor of criterion variable; + indicates 8 clinicians on panel rated trait as a predictor, and that trait was included per expert consensus (Yalch and Hopwood);  indicates 8 clinicians on panel rated trait as a predictor, and that trait was not included per expert consensus.  72  .      Rule-breaking Autocratic behavior Behavioral rigidity Workaholic behavior DSM-5 traits Anhedonia         Anxiousness     Attention Seeking     Callousness     Deceitfulness     Depressivity       Distractibility         Eccentricity       Emotional lability   Grandiosity   Hostility     Impulsivity       Intimacy Avoidance  Irresponsibility       Manipulativeness     Perceptual Dysregulation       Perfectionism   Perseveration     Restricted Affectivity   Risk Taking     Separation Insecurity         Submissiveness         Suspiciousness   Unusual Beliefs         Withdrawal       Unique CAT-PD traits Anger   Cognitive Problems     Domineering   Fantasy Proneness        Health Anxiety       Norm Violation     Rigidity   Rudeness     Self Harm       Workaholism        73        Dissociative symptoms Cognitive dysfunction DSM-5 traits Anhedonia   Anxiousness Attention Seeking     Callousness     Deceitfulness     Depressivity Distractibility Eccentricity   Emotional lability Grandiosity     Hostility     Impulsivity   Intimacy Avoidance   Irresponsibility   Manipulativeness     Perceptual Dysregulation   Perfectionism     Perseveration   Restricted Affectivity   Risk Taking     Separation Insecurity   Submissiveness     Suspiciousness   Unusual Beliefs   Withdrawal   Unique CAT-PD traits Anger Cognitive Problems Domineering     Fantasy Proneness   Health Anxiety     Norm Violation     Rigidity     Rudeness     Self Harm   Workaholism        74  Table 4. Traits selected by clinician panel to predict criterion variables (updated).      Suicide risk NSSI Hypochondriasis Physical aggression Social aggression DSM-5 traits Anhedonia       Anxiousness Attention Seeking      + Callousness       Deceitfulness   +   Depressivity + + Distractibility           Eccentricity        Emotional lability Grandiosity       Hostility   Impulsivity     Intimacy Avoidance Irresponsibility   Manipulativeness  Perceptual Dysregulation     Perfectionism      Perseveration   +    Restricted Affectivity    Risk Taking   Separation Insecurity Submissiveness         Suspiciousness Unusual Beliefs       Withdrawal   Unique CAT-PD traits Cognitive Problems +   Domineering       Fantasy Proneness +     Health Anxiety         Hostile Aggressiveness   Norm Violation +   Rigidity    Rudeness       Self Harm +   Workaholism           Notes:  indicates that the majority of the clinician panel rated trait as a predictor of criterion variable; + indicates 8 clinicians on panel rated trait as a predictor, and that trait was included per expert consensus (Yalch and Hopwood);  indicates 8 clinicians on panel rated trait as a predictor, and that trait was not included per expert consensus.  75  Table 4 .      Rule-breaking Autocratic behavior Behavioral rigidity Workaholic behavior DSM-5 traits Anhedonia         Anxiousness     Attention Seeking     Callousness     Deceitfulness     Depressivity       Distractibility         Eccentricity       Emotional lability   Grandiosity   Hostility   Impulsivity       Intimacy Avoidance  Irresponsibility       Manipulativeness     Perceptual Dysregulation       Perfectionism   Perseveration     Restricted Affectivity   Risk Taking     Separation Insecurity         Submissiveness         Suspiciousness   Unusual Beliefs         Withdrawal       Unique CAT-PD traits Cognitive Problems     Domineering   Fantasy Proneness        Health Anxiety       Hostile Aggressiveness     Norm Violation     Rigidity   Rudeness     Self Harm       Workaholism        76        Dissociative symptoms Cognitive dysfunction DSM-5 traits Anhedonia   Anxiousness Attention Seeking     Callousness     Deceitfulness     Depressivity Distractibility Eccentricity   Emotional lability Grandiosity     Hostility Impulsivity   Intimacy Avoidance   Irresponsibility   Manipulativeness     Perceptual Dysregulation   Perfectionism     Perseveration   Restricted Affectivity   Risk Taking     Separation Insecurity   Submissiveness     Suspiciousness   Unusual Beliefs   Withdrawal   Unique CAT-PD traits Cognitive Problems Domineering     Fantasy Proneness   Health Anxiety     Hostile Aggressiveness     Norm Violation     Rigidity     Rudeness     Self Harm   Workaholism        77  Table 5. Correlations between traits and criterion variables.      Suicide risk NSSI Hypochondriasis Physical aggression Social aggression DSM-5 traits Anhedonia .43 .22 .28 .31 .26 Anxiousness .52 .21 .32 .16 .27 Attention Seeking .13 .07 .12 .21 .28 Callousness .11 .17 .27 .49 .39 Deceitfulness .18 .18 .19 .37 .44 Depressivity .58 .33 .32 .30 .30 Distractibility .42 .21 .24 .27 .32 Eccentricity .41 .22 .23 .33 .32 Emotional Lability .42 .22 .31 .23 .30 Grandiosity .04 .04 .14 .29 .27 Hostility .38 .22 .25 .50 .48 Impulsivity .18 .12 .20 .35 .29 Intimacy avoidance .15 .15 .19 .23 .18 Irresponsibility .14 .19 .31 .41 .36 Manipulativeness .17 .12 .09 .28 .32 Perceptual Dysregulation .33 .23 .36 .37 .31 Perfectionism .26 .14 .20 .14 .18 Perseveration .39 .22 .26 .28 .31 Restricted Affectivity .22 .11 .06 .19 .14 Risk Taking .08 .08 -.01 .21 .10 Separation Insecurity .33 .18 .25 .17 .25 Submissiveness .27 .15 .06 .03 .19 Suspiciousness .30 .18 .31 .34 .29 Unusual Beliefs .27 .20 .32 .36 .26 Withdrawal .40 .22 .21 .30 .26 Unique CAT-PD traits Cognitive Problems .38 .24 .35 .39 .36 Domineering .18 .12 .20 .40 .44 Fantasy Proneness .38 .20 .24 .33 .34 Health Anxiety .21 .16 .69 .29 .33 Hostile Aggressiveness .12 .19 .35 .61 .44 Norm Violation .12 .19 .29 .47 .33 Rigidity .26 .16 .27 .42 .44 Rudeness .25 .18 .26 .56 .53 Self Harm .43 .41 .35 .36 .29 Workaholism .18 .08 .09 .17 .17  Note:  indicates r is not statistically significant at p < .05 (all other values statistically significant).  78  .      Rule- breaking Autocratic behavior Behavioral rigidity Workaholic behavior DSM-5 traits Anhedonia .30 .35 .36 .01 Anxiousness .02 .22 .23 .13 Attention Seeking .17 .33 .33 .18 Callousness .51 .57 .54 .03 Deceitfulness .37 .49 .50 .07 Depressivity .33 .37 .32 .04 Distractibility .18 .31 .30 .03 Eccentricity .23 .36 .39 .09 Emotional Lability .14 .34 .30 .11 Grandiosity .30 .43 .45 .15 Hostility .23 .51 .57 .06 Impulsivity .32 .37 .33 .09 Intimacy avoidance .29 .29 .26 .00 Irresponsibility .52 .50 .42 .05 Manipulativeness .23 .35 .44 .15 Perceptual Dysregulation .41 .48 .41 .13 Perfectionism .06 .27 .33 .29 Perseveration .22 .39 .38 .13 Restricted Affectivity .17 .23 .28 .04 Risk Taking .16 .12 .14 .04 Separation Insecurity .16 .31 .26 .14 Submissiveness -.02 .13 .09 .06 Suspiciousness .28 .34 .41 .11 Unusual Beliefs .39 .43 .41 .16 Withdrawal .24 .33 .35 .01 Unique CAT-PD traits Cognitive Problems .34 .43 .42 .03 Domineering .28 .54 .62 .18 Fantasy Proneness .23 .34 .38 .12 Health Anxiety .28 .36 .31 .05 Hostile Aggressiveness .61 .66 .58 .09 Norm Violation .56 .47 .43 .02 Rigidity .32 .58 .69 .11 Rudeness .43 .58 .60 .05 Self Harm .50 .40 .29 .01 Workaholism .12 .23 .26 .32    79  ).      Dissociative symptoms Cognitive dysfunction DSM-5 traits Anhedonia .35 .39 Anxiousness .17 .38 Attention Seeking .22 .09 Callousness .45 .17 Deceitfulness .34 .25 Depressivity .39 .41 Distractibility .31 .56 Eccentricity .39 .39 Emotional Lability .27 .39 Grandiosity .31 .00 Hostility .31 .27 Impulsivity .31 .32 Intimacy avoidance .36 .20 Irresponsibility .44 .37 Manipulativeness .24 .03 Perceptual Dysregulation .57 .40 Perfectionism .19 .04 Perseveration .38 .40 Restricted Affectivity .26 .08 Risk Taking .13 -.03 Separation Insecurity .25 .31 Submissiveness .08 .22 Suspiciousness .37 .33 Unusual Beliefs .54 .21 Withdrawal .33 .26 Unique CAT-PD traits Cognitive Problems .48 .66 Domineering .28 .13 Fantasy Proneness .39 .37 Health Anxiety .38 .39 Hostile Aggressiveness .54 .19 Norm Violation .46 .25 Rigidity .36 .25 Rudeness .40 .29 Self Harm .46 .32 Workaholism .18 -.02  80  Table 6. Results of hierarchical regression analyses examining effects of clinician-selected traits on clinically relevant behaviors.    Suicide risk NSSI Hypochondriasis Physical aggression Social aggression    R2  R2  R2  R2  R2 Clinician-selected DSM-5 traits   .48***   .13***   .27***   .40***   .33*** Cognitive Problems .01 .53*** .04 .20*** .03 .52*** .12*** .49***   .38*** Domineering             .04   .12**   Fantasy Proneness .22***   .06   -.07*           Health Anxiety         .61***           Hostile Aggressiveness -.11**   -.09       .39***   .06   Norm Violation -.01   .05       .08*   .02   Rigidity -.02   -.03   -.03           Rudeness             .15***   .26***   Self Harm .24***   .38***   .12***   .05       Workaholism                      Notes: * indicates statistical significance at p < .05; ** indicates statistical significance at p < .01; *** indicates statistical significance at p < .001.   81      Rule-breaking Autocratic behavior Behavioral rigidity Workaholic behavior Dissociative symptoms Cognitive dysfunction    R2  R2  R2  R2  R2  R2 Clinician-selected DSM-5 traits   .38***   .47***   .45***   .14***   .46***   .45*** Cognitive Problems .02 .48***   .55*** .15*** .58***   .20*** .20*** .48*** .42*** .52*** Domineering .01  .14***       -.01          Fantasy Proneness                -.04      Health Anxiety        -.01              Hostile Aggressiveness .30***  .28***                  Norm Violation .20***  .08*                  Rigidity    .16***   .50***   -.11*          Rudeness .04  .08*                  Self Harm .20***              .13***      Workaholism     .02       .28***              82  Table 7. Results of hierarchical regression analyses examining effects of all maladaptive traits on clinically relevant behaviors.    Suicide risk NSSI Hypochondriasis Physical aggression Social aggression    R2  R2  R2  R2  R2 All DSM-5 traits   .51***   .14***   .31***   .41***   .35*** Cognitive Problems -.04 .55*** .06 .21*** .05 .54*** .13** .49*** .04 .40*** Domineering .05   .05   .01   .01   .11**   Fantasy Proneness .19***   .08   -.06   .02   .05   Health Anxiety -.08**   -.01   .60***   -.01   .07*   Hostile Aggressiveness -.08*   -.06   .09*   .39***   .07   Norm Violation -.00   .07   .08*   .07   .03   Rigidity -.01   -.02   .03   .02   .05   Rudeness .01   -.06   -.08*   .14***   .22***   Self Harm .24***   .39***   .07*   .04   .03   Workaholism .06*   .01   .03   .04   .02    Notes: * indicates statistical significance at p < .05; ** indicates statistical significance at p < .01; *** indicates statistical significance at p < .001.   83  Table 7 (c.    Rule-breaking Autocratic behavior Behavioral rigidity Workaholic behavior Dissociative symptoms Cognitive dysfunction    R2  R2  R2  R2  R2  R2 All DSM-5 traits   .44***   .51***   .53***   .19***   .47***   .52*** Cognitive Problems .11** .51*** .15*** .57*** .19*** .64*** .08 .25*** .21*** .50*** .41*** .58*** Domineering .00  .14***   .16***   -.01   -.02   .04  Fantasy Proneness -.10**  -.11**   -.06   -.01   -.03   .01  Health Anxiety .01  -.01   -.04   -.04   .07*   .05  Hostile Aggressiveness .20***  .22***   .05   .09   .12**   -.11**  Norm Violation .19***  .03   .05   -.04   .09*   .05  Rigidity -.01  .17***   .39***   -.05   .00   .01  Rudeness .06  .08*   .12***   -.08   -.02   .03  Self Harm .20***  .01   -.06   -.02   .10**   .01  Workaholism .04   .02   -.02   .27***   .05   .01      84  Table 8. Composite score of informant ICCs, convergent validity, and target-informant agreement listed by trait.  Trait Composite score (z) Submissiveness -1.88 Unusual Beliefs -1.32 Exhibitionism -1.29 Unusual Experiences -1.15 Rigidity -.92 Fantasy Proneness -.85 Cognitive Problems -.81 Norm Violation -.74 Non-Perseverance -.55 Non-Planfulness -.49 Hostile Aggression -.43 Irresponsibility -.39 Romantic Disinterest -.26 Manipulativeness -.22 Self Harm -.16 Mistrust -.06 Anger -.02 Grandiosity -.01 Affective Lability .17 Domineering .23 Emotional Detachment .26 Risk Taking .29 Anhedonia .54 Perfectionism .56 Workaholism .64 Rudeness .74 Peculiarity .80 Callousness .87 Social Withdrawal 1.07 Anxiousness 1.13 Health Anxiety 1.14 Relationship Insecurity 1.41 Depressiveness 1.70    85  Table 9. Target-informant agreement with and without meta-perception.    No meta-perception Target meta-perception Informant meta-perception Comparisons Affective Lability .18 .19 .20   Anger .22 .27 .33   Anhedonia .24 .21 .29   Anxiousness .30 .36 .35   Callousness .29 .20 .37 im > tm Cognitive Problems .22 .13 .11  Depressiveness .37 .33 .33   Domineering .20 .29 .25   Emotional Detachment .22 .28 .18   Exhibitionism .10 .16 .08   Fantasy Proneness .12 .13 .14   Grandiosity .21 .19 .22   Health Anxiety .36 .29 .37   Hostile Aggression .15 .17 .15   Irresponsibility .25 .20 .23   Manipulativeness .20 .19 .25   Mistrust .20 .20 .19   Non-Perseverance .13 .17 .13   Non-Planfulness .10 .16 .06   Norm Violation .14 .26 .22  Peculiarity .29 .26 .32   Perfectionism .29 .26 .27   Relationship Insecurity .37 .38 .34   Rigidity .09 .08 .18   Risk Taking .22 .28 .16   Romantic Disinterest .28 .18 .26   Rudeness .33 .29 .34   Self Harm .14 .21 .20   Social Withdrawal .27 .31 .29   Submissiveness .09 .08 .20   Unusual Beliefs .04 .15 .17  Unusual Experiences .14 .14 .19   Workaholism .28 .31 .23   Mean .21 .22 .23   Notes: All r > .11 statistically significant at p < .05; all comparisons listed are statistically significant (p < .05); c = conventional agreement, tm = target meta-perception, im = informant meta-perception. 86  Table 10. Target-informant agreement broken down by relationship.    Peers Partners Mothers Fathers Siblings Comparisons Affective Lability .21 .21 .06 .03 .37  Anger .11 .18 .20 .31 .53 s > p, r, m, f  Anhedonia .17 .29 .28 .55 .22 f > p, r, m Anxiousness .26 .06 .29 .47 .25 f > r, s  Callousness .36 .23 .36 .07 .54 m > f; s > m, f  Cognitive Problems .15 .18 .32 .10 -.10 m > s  Depressiveness .25 .48 .35 .37 .59 s > r, f Domineering .21 .29 .25 .20 .26  Emotional Detachment .22 .07 .20 .34 .44 s > r Exhibitionism .15 .25 .03 .18 .04  Fantasy Proneness .12 .09 .07 .21 .40 s > m Grandiosity .26 .11 .11 .29 .53 s > r, m  Health Anxiety .29 .29 .44 .22 .29 m > p, f  Hostile Aggressiveness .13 .43 .27 .21 .13 r > p, m  Irresponsibility .28 .14 .36 .23 .00 p > s; m > s  Manipulativeness .24 .09 .26 .27 .28  Mistrust .20 .31 .28 .09 .12 r > s  Non-Perseverance .15 .03 .04 .05 .34  Non-Planfulness .15 .12 .14 .04 .10  Norm Violation .17 .08 .08 .04 .09  Peculiarity .33 .40 .23 -.10 .45 p, r, s > f; s > m Perfectionism .33 .20 .23 .09 .26  Relationship Insecurity .34 .59 .32 .27 .25 r > p, m  Rigidity .12 .20 .11 .01 .08  Risk Taking .25 .21 .23 .21 .03  Romantic Disinterest .24 .00 .31 .37 .09 m > r  Rudeness .25 .58 .40 .05 .42 r > p, m, f; m > f Self Harm .12 .32 .15 -.09 .27 r > f  Social Withdrawal .14 .44 .40 .46 .43 r, m, f > p Submissiveness .02 .13 .02 -.11 .34 s > f  Unusual Beliefs .09 .08 .06 .33 -.09 f > s  Unusual Experiences .20 .01 .22 -.08 -.04  Workaholism .21 .23 .19 .29 .31  Mean .20 .21 .21 .19 .25    Notes: Comparisons only reported when one or more correlation is statistically significant (p < .05); all comparisons listed are statistically significant (p < .05); p = peers, r = partners, m = mothers, f = fathers, s = siblings. 87  Table 11. Target-informant agreement with and without meta-perception broken down by relationship.    Peers Romantic partners   No meta-perception Target meta-perception Informant meta-perception Contrasts No meta-perception Target meta-perception Informant meta-perception Contrasts Affective Lability .21 .14 .25   .21 .31 .16   Anger .11 .16 .28  .18 .32 .44 im > c Anhedonia .17 .24 .34 im > c .29 .56 .24 tm > c, im Anxiousness .26 .22 .32   .06 .20 .21   Callousness .36 .30 .39   .23 .40 .52 im > c Cognitive Problems .15 .02 .02   .18 .20 .13   Depressiveness .25 .28 .25   .48 .64 .42 tm > c, im Domineering .21 .16 .27   .29 .46 .29   Emotional Detachment .22 .23 .25   .07 .18 .12   Exhibitionism .15 .14 .14   .25 .44 .08 tm > im Fantasy Proneness .12 .27 .05  .09 .22 .19   Grandiosity .26 .42 .40 tm, im > c .11 .25 .25   Health Anxiety .29 .35 .30   .29 .32 .15   Hostile Aggressiveness .13 .16 .17   .43 .36 .09 c, tm > im Irresponsibility .28 .21 .19   .14 .35 .16   Manipulativeness .24 .22 .30   .09 .27 .01   Mistrust .20 .27 .15   .31 .37 .23    Notes: All r > .15 (peers), r > .25 (romantic partners), r > .17 (mothers), r > .27 (fathers), and r > .30 (siblings) are statistically significant at p < .05; all comparisons listed are statistically significant (p < .05); c = conventional agreement, tm = target meta-perception, im = informant meta-perception.    88  .    Peers Romantic partners   No meta-perception Target meta-perception Informant meta-perception Contrasts No meta-perception Target meta-perception Informant meta-perception Contrasts Non-Planfulness .15 .18 .11   .12 .11 .05   Norm Violation .17 .36 .07 tm > c, im .08 .18 .13   Peculiarity .33 .44 .24 tm > im .40 .54 .44   Perfectionism .33 .20 .34   .20 .51 .27 tm > c, im Relationship Insecurity .34 .28 .33   .59 .45 .53   Rigidity .12 .05 .07   .20 .24 .20   Risk Taking .25 .21 .17   .21 .38 .21   Romantic Disinterest .24 .35 .23  .00 .08 -.06   Rudeness .25 .27 .30   .58 .28 .63 c, im > tm Self Harm .12 .18 .10   .32 .45 .41   Social Withdrawal .14 .17 .09   .44 .59 .40   Submissiveness .02 .17 .12   .13 .12 .21   Unusual Beliefs .09 .21 .18   .08 .27 .14   Unusual Experiences .20 .32 .21   .01 .21 .04   Workaholism .21 .18 .32 im > c .23 .31 .01  Mean .20 .22 .22   .22 .33 .22      89  Table 11    Mothers Fathers   No meta-perception Target meta-perception Informant meta-perception Contrasts No meta-perception Target meta-perception Informant meta-perception Contrasts Affective Lability .06 .14 .07   .03 .19 .12   Anger .20 .31 .33   .31 .29 .26   Anhedonia .28 .47 .24 tm > c, im .55 .17 .23 c > tm Anxiousness .29 .39 .32   .47 .39 .39   Callousness .36 .23 .29  .07 .08 .28   Cognitive Problems .32 .15 .14 c > tm, im .10 .23 .15   Depressiveness .35 .43 .24  .37 .41 .62 im > c Domineering .25 .43 .27 tm > c .20 .36 .20   Emotional Detachment .20 .32 .31   .34 .02 .38 c, im > tm Exhibitionism .03 .23 .05  .18 .24 .24   Fantasy Proneness .07 .21 .17   .21 .35 .07   Grandiosity .11 .28 -.08  .29 .03 .26   Health Anxiety .44 .39 .41   .22 .45 .30   Hostile Aggressiveness .27 .19 .09  .21 .05 .27   Irresponsibility .36 .28 .20   .23 .56 .36 tm > c Manipulativeness .26 .35 .16 tm > im .27 .10 .26   Mistrust .28 .30 .33   .09 -.01 -.03      90  Table 11    Mothers Fathers   No meta-perception Target meta-perception Informant meta-perception Contrasts No meta-perception Target meta-perception Informant meta-perception Contrasts Non-Perseverance .04 .26 .15  .05 .22 -.04   Non-Planfulness .14 .38 .14 tm > c, im .04 .02 .03   Norm Violation .08 .28 .15  .04 .05 .44 im > c, tm Peculiarity .23 .18 .33   -.10 .00 .27   Perfectionism .23 .33 .20   .09 .31 .12   Relationship Insecurity .32 .48 .19 tm > c, im .27 .31 .46   Rigidity .11 .22 .22   .01 .22 .24   Risk Taking .23 .29 .15   .21 .29 .34   Romantic Disinterest .31 .07 .27 c > tm .37 .44 .40   Rudeness .40 .43 .35   .05 -.06 .11   Self Harm .15 .36 .07 tm > c, im -.09 .12 .27  Social Withdrawal .40 .42 .39   .46 .42 .59   Submissiveness .02 .33 .10 tm > c, im -.11 .18 .28  Unusual Beliefs .06 .13 .08   .33 -.04 .30 c > tm Unusual Experiences .22 .07 .11   -.08 -.07 .39 im > c, tm Workaholism .19 .11 .16   .29 .04 .26   Mean .22 .29 .20   .18 .19 .27     91  Table 11    Siblings   No meta-perception Target meta-perception Informant meta-perception Contrasts Affective Lability .37 .08 .47 c, im > tm Anger .53 .41 .35   Anhedonia .22 .22 .32   Anxiousness .25 .45 .28 tm > c Callousness .54 .36 .39   Cognitive Problems -.10 -.07 .11   Depressiveness .59 .74 .58 tm > c Domineering .26 .50 .16 tm > c, im Emotional Detachment .44 .34 -.06 c, tm > im Exhibitionism .04 .09 .00   Fantasy Proneness .40 .20 .51  Grandiosity .53 .01 .31 c > tm Health Anxiety .29 .44 .22   Hostile Aggressiveness .13 .08 .11   Irresponsibility .00 .07 -.14   Manipulativeness .28 -.01 .10   Mistrust .12 .30 .33   Non-Perseverance .34 .62 .25 tm > c, im Non-Planfulness .10 .27 .11   Norm Violation .09 -.09 .16   Peculiarity .45 .27 .50 c > tm Perfectionism .26 .19 .19   Relationship Insecurity .25 .20 .20   Rigidity .08 .16 .33 im > c Risk Taking .03 -.04 -.18   Romantic Disinterest .09 .16 .19   Rudeness .42 .52 .32   Self Harm .27 .49 .48 tm, im > c Social Withdrawal .43 .61 .45 tm > c Submissiveness .34 .12 .14   Unusual Beliefs -.09 -.08 -.05   Unusual Experiences -.04 -.03 -.04   Workaholism .31 .42 .21   Mean .25 .24 .22   92  Table 12. Target-informant agreement with and without meta-perception (calculated using regression).    No meta-perception Target meta-perception Informant meta-perception Comparisons   Affective Lability .18 .20 .20   Anger .22 .28 .33   Anhedonia .25 .22 .29   Anxiousness .32 .37 .36   Callousness .29 .22 .37 im > tm Cognitive Problems .22 .12 .11   Depressiveness .38 .33 .35   Domineering .22 .30 .27   Emotional Detachment .22 .29 .18   Exhibitionism .10 .17 .08   Fantasy Proneness .13 .15 .15   Grandiosity .20 .19 .22   Health Anxiety .36 .31 .37   Hostile Aggression .15 .17 .15   Irresponsibility .27 .22 .23   Manipulativeness .19 .19 .24   Mistrust .21 .21 .20    Notes: Unless otherwise noted, all  > .11 statistically significant at p < .05; all comparisons listed are statistically significant (p < .05); c = conventional agreement, tm = target meta-perception, im = informant meta-perception; p = peers, r = partners, m = mothers, f = fathers, s = siblings.    93  Table 12 (contd).    No meta-perception Target meta-perception Informant meta-perception Comparisons   Non-Perseverance .14 .18 .14   Non-Planfulness .09 .16 .04   Norm Violation .16 .27 .23   Peculiarity .30 .27 .33   Perfectionism .30 .25 .29   Relationship Insecurity .38 .38 .35   Rigidity .10 .08 .18   Risk Taking .21 .28 .16   Romantic Disinterest .28 .17 .26   Rudeness .35 .31 .34   Self Harm .14 .20 .19   Social Withdrawal .29 .32 .31   Submissiveness .09 .07 .20   Unusual Beliefs .04 .17 .16   Unusual Experiences .13 .15 .18   Workaholism .26 .30 .22   Mean .22 .23 .23      94      Statistically significant moderator effects   No meta-perception Target meta-perception Informant meta-perception Affective Lability       Anger       Anhedonia       Anxiousness m ( = -.16) m ( = -.18) r ( = .11) Callousness       Cognitive Problems       Depressiveness r ( -.13) r ( = .16), f ( = -.13) s ( = .12) Domineering       Emotional Detachment m ( = .15) m ( = -.15)   Exhibitionism m ( = -.13) m ( = -.13)   Fantasy Proneness r ( = .16) m ( = .16) r ( = .13) Grandiosity     m ( = -.13) Health Anxiety       Hostile Aggression m ( = -.14) m ( = -.14)   Irresponsibility       Manipulativeness m ( = -.13) m ( = -.15)   Mistrust r ( = .13)        95      Statistically significant moderator effects   No meta-perception Target meta-perception Informant meta-perception Non-Perseverance       Non-Planfulness       Norm Violation p ( = .13)     Peculiarity     -.13) Perfectionism     p ( = .13), r ( = .12) Relationship Insecurity r ( = .11)     Rigidity       Risk Taking p ( = .13) p ( = .14)   Romantic Disinterest m ( = -.13) r ( = --.14) r ( = -.12), m ( = -.12) Rudeness f ( = -.12) -.13)   Self Harm       Social Withdrawal s ( = .15)  s ( = .13) Submissiveness       Unusual Beliefs       Unusual Experiences       Workaholism   m ( = -.16) p ( = .14), r ( = .12) Mean         96  Table 13. Differences in maladaptive trait levels between targets nominating informants by relationship.    Peers Romantic partners Mothers Fathers   t Cohen's d t Cohen's d t Cohen's d t Cohen's d Affective Lability .13   -1.31   .93   1.22   Anger -.26   0.28   .44   1.59   Anhedonia -.21   -0.36   .62   1.78   Anxiousness -1.20   0.41   1.84   .72   Callousness 2.81** .27 -1.94   -3.12* -.28 .47   Cognitive Problems 1.70   -2.07* -.21 -1.66   -.12   Depressiveness -.21   0.54   1.04   .97   Domineering 1.85   -1.39   1.36   1.70   Emotional Detachment .45   -1.71   -.94   .88   Exhibitionism 4.04*** .41 -3.87*** -.39 .43   .72   Fantasy Proneness 1.18   -1.55   1.14   2.09* .22 Grandiosity 3.88*** .37 -1.91   -2.95** -.26 .54   Health Anxiety .74   -0.89   .71   .35   Hostile Aggression 1.86   -0.52   -2.36* -.21 .19   Irresponsibility 2.59** .27 -1.47   -1.93 -.17 -.37   Manipulativeness 3.28** .35 -2.17* -.22 -3.40*** -.30 -.09   Mistrust 1.28   -1.81   .16   .83    d listed only if t-test is statistically significant; * indicates statistical significance at p < .05; ** indicates statistical significance at p < .01; *** indicates statistical significance at p < .001;  indicates t-test adjusted for unequal variance (tested using or Equality of Variances).     97      Peers Romantic partners Mothers Fathers   t Cohen's d t Cohen's d t Cohen's d t Cohen's d Non-Perseverance 1.37   -2.81** -.29 .66   .63   Non-Planfulness 3.52*** .37 -3.24** -.32 -2.21* -.20 -.35   Norm Violation 3.41*** .36 -1.22   -1.58   .05   Peculiarity 2.38* .24 -1.63   -1.13   -.48   Perfectionism -1.00   0.61      1.79   Relationship Insecurity 1.13   -2.50* -.25 -.43   -.27   Rigidity 1.63   -0.89   .29   .89   Risk Taking 4.20*** .41 -2.37* -.23 -.90   .89   Romantic Disinterest -.07   -5.45*** -.52 -.69   .75   Rudeness 3.12** .32 -2.33* -.24 -1.00   .47   Self Harm 1.03   1.07   -1.57   .12   Social Withdrawal -1.99* -.20 -0.01   .70   1.51   Submissiveness 1.76   -2.39* -.24 -1.03   -.07   Unusual Beliefs 3.78*** .35 -0.74   -2.42* -.21 -.27   Unusual Experiences 2.32* .22 -0.45   -2.31* -.20 .10   Workaholism .41   -0.17   2.42* .21 1.06      98      Siblings   t Cohen's d Affective Lability .69   Anger .34   Anhedonia -.30   Anxiousness .61   Callousness -.14   Cognitive Problems -.64   Depressiveness .17   Domineering .42   Emotional Detachment .76   Exhibitionism -.36   Fantasy Proneness -.76   Grandiosity -.04   Health Anxiety -.88   Hostile Aggression -1.72   Irresponsibility -1.16   Manipulativeness -.76   Mistrust -.02      99      Siblings   t Cohen's d Non-Perseverance -.11   Non-Planfulness -.52   Norm Violation -2.01* -.19 Peculiarity .12   Perfectionism 1.18   Relationship Insecurity -1.02   Rigidity 1.02   Risk Taking -.96   Romantic Disinterest 1.20   Rudeness -1.04   Self Harm -.21   Social Withdrawal 1.42   Submissiveness -.05   Unusual Beliefs -1.34   Unusual Experiences -1.05   Workaholism -.14     100  Appendix 2: Figures  Figure 1. The Johari Window applied to distress associated with maladaptive traits.    Target   Observed Not observed Informant Observed Open Blind Not observed Hidden Unknown  101  Appendix 3: Single-trait rating scale (self-report version)  For each item listed below, endorse the degree to which you believe the description applies to you using the following scale:   Very little or not at all descriptive Slightly descriptive Moderately descriptive Extremely descriptive 1 2 3 4   Affective Lability: the tendency to experience strong, rapid, and unpredictable shifts in emotion and mood, to have difficulty coping with both minor and major life stressors, and to act impulsively in the context of negative affect.  Anger: the tendency to experience and express emotions ranging from frustration and irritability to explosive temper and rage.  Anhedonia: general deficits in positive emotions and energy levels; difficulties experiencing joy and excitement, showing little interest in things, and exhibiting lethargy, lassitude, and psychomotor slowness.  Anxiousness: tendency to be generally tense, prone to worry, fearful, panicky, and to excessively anticipate or avoid situations or stimuli that are perceived as dangerous.  Callousness: cold-heartedness, disregard for the rights, feelings, and welfare of others, and lack of sympathy and empathy.  Cognitive Problems: a range of mental deficits, including memory problems, confusion, disorientation, and illogical/disorganized thoughts.  Depressiveness: the tendency to experience feelings of sadness, melancholy, hopelessness, inferiority, shame and guilt, as well as the tendency to hold a generally negative view of oneself, the world, and the future.  Domineering: general need for power and the tendency to be controlling, dominant, and forceful in interpersonal relationships.  Emotional Detachment: the tendency to be emotionally distant and reserved, as well as difficulties in the experience, description, and expression of feelings.  Exhibitionism: the tendency to engage in and derive pleasure from a range of overt attention-seeking behaviors, behave in an overly flamboyant and theatrical manner characterized by exaggerated displays of emotion, and act and dress in sexually provocative ways.  102  thoughts and experiences, sometimes to the extent of becoming distracted and losing sight of reality.  Grandiosity: a mixture of arrogance and entitlement; belief that one is important and superior to others, acts in condescending ways, and feels they deserve special treatment and privileges.  possible health problems.  Hostile Aggression: a pattern of hostile and violent behavior that is either instrumental (i.e., instigated by the individual to achieve a specific goal or purpose) or reactive (i.e., in response to some environmental stimulus); the tendency to be resentful, mean-spirited, vindictive, and sadistic.  Irresponsibility: the extent to which an individual fails to fulfill responsibilities, requirements, promises, and obligations in relationships and other important life roles (e.g., school, work).  Manipulativeness: frequent use of subterfuge to influence or control others; use of seduction,   Mistrust: the tendency to question the honesty, motives, fidelity, loyalty, and believability of others, as well as a general attitude of jaded negativity, especially a general disbelief in the integrity or professed motives of others.  Non-Perseverance: sensitive to difficulties remaining focused and engaged on tasks that may be perceived as boring, challenging, frustrating, or not enjoyable.  Non-Planfulness: the tendency to act on whims or on the spur of the moment without planning or concern for the consequences.  Norm Violation: general disregard for and active rejection of social rules and convention, a history of engaging in illegal or antisocial acts, and a pattern of disobedient and defiant behavior towards authority figures.  perceived as odd, unusual, or eccentric.  Perfectionism: appraises the belief that any behavior or workthat is anything less than flawless is unacceptable.  Relationship Insecurity: an interpersonal style characterized by interpersonal insecurity, fear of abandonment by significant others, jealousy, and the tendency to anxiously expect, readily perceive, and over-react to social rejection or criticism.  103  to consider the validity of alterna  Risk Taking: the tendency to pursue and enjoy activities that are stimulating, thrilling, exhilarating, and potentially dangerous.  Romantic Disinterest: a general lack of interest in, desire for, and enjoyment of sex, eroticism, and interpersonal intimacy.  Rudeness: the tendency to be blunt, overly frank, interpersonally insensitive, and tactless in interpersonal communication.  Self Harm: a range of self-injurious thoughts, feelings, and behaviors related to both non-lethal (e.g., cutting, burning, head-banging, etc.) and lethal (e.g., suicidal ideation, intentions, and acts) means.  Social Withdrawal: avoidance of interpersonal interactions and a preference for being alone that is guided either by interpersonal anxiety or a genuine disinterest in interacting with others.  Submissiveness: the yielding of power to others, over-wishes, exploitation by others, and lack of self-confidence in decision-making, often to the extent that o  Unusual Beliefs: the tendency to hold unfounded and irrational thoughts, beliefs, and ideas about the world, including beliefs about the powers of oneself, others, and objects to control and influence others and the physical world.  Unusual Experiences: a range of unusual experiences, including perceptual distortions that do or oneself.  Workaholism: general preference for and orientation toward work relative to relationships, relaxation, and other important aspects of life, as well as an excessive focus on achievement, status, and success in life.     104  Appendix 4: Excerpt from clinician panel survey  Instructions: Below and on the next few pages are a series of problems related to PD and 39 different traits (which include 25 traits of the new DSM model as well as traits others suggested). Please rate how large an association you expect each of the 39 traits to have on each problem (null, small, medium, or large association).  Hypochondriasis   Null association (e.g., r < |.10|) Small association r < |.30|) Medium association (e.g., r < |.50|) Large association (e.g., r  Affective Lability     Anger     Anhedonia     Anxiousness     Callousness     Cognitive Problems     Deceitfulness     Depressiveness     Distractability     Domineering     Emotional Detachment     Exhibitionism     Fantasy Proneness     Grandiosity     Health Anxiety     Hostile Aggression     Intimacy Avoidance     Irresponsibility     Manipulativeness     Mistrust     Non-Perseverance     Non-Planfulness     Norm Violation     Peculiarity     Perceptual Dysregulation     Perfectionism     Perseveration     Relationship Insecurity     Restricted Affectivity     Rigidity     Risk Taking     Romantic Disinterest     Rudeness     Self Harm     Social Withdrawal     Submissiveness     Unusual Beliefs     Unusual Experiences     Workaholism      105                         REFERENCES    106  REFERENCES   Al-Dajani, N., Gralnick, T. 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