Dimensional models of personality disorders

The "checklist" of symptoms that is currently used is often criticized for a lack of empirical support[5] and its inability to recognize personality-related issues that do not fit within the current personality disorder constructs or DSM criteria.[6] It has also been criticized for leading to diagnoses that are not stable over time, have poor cross-rater agreement and high comorbidity[7] suggesting that they do not reflect distinct disorders.[8] In contrast the dimensional approach has been shown to predict and reflect current diagnostic criteria, but also add to them.[9] It has been argued to be especially useful in explaining comorbidity which is often high for patients diagnosed with a personality disorders.[7] Following from these claims, the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) incorporates a combined categorical-dimensional approach to diagnosing personality disorders [5] based on the degree to which a person shows elevated levels of particular personality characteristics. However one of the issues in using a dimensional approach to diagnosis has been determining appropriate cut off points so as to know who belongs to the category of people requiring treatment, this is partly why both categorical and dimensional diagnoses are included.[10]

Since the categorical model is widely used in clinical practice and has a significant body of research supporting it, its common usage is compelling to laypeople when they are judging the credibility of professional opinion. Therefore, the dimensional approach is often further criticized for being difficult to interpret and less accessible. It is however widely used in some professional settings as the established approach, for example by forensic psychologists.[11]

Another suggested usage of the dimensional approach is that it can aid clinicians in developing treatment plans and assessing other mechanisms contributing to patient's difficulty in functioning within the social, personal, or occupational domains. The approach can improve treatment in two ways. Firstly it can enable development of more personalized care plans for individuals based on their adaptive and maladaptive characteristics. Secondly, it means that relevant symptomology which is not considered maladaptive can be considered when developing and evaluating general therapeutic and medical treatment.[4]

Attempts at presenting an etiological description of personality disorders have been avoided due to the influence of the DSM and its principles in psychiatric research (See history section). However some techniques are looking at potential interrelated causalities between symptoms of personality disorders and broader influences including aspects of normal personality (See integrated approaches section).

The adoption of a categorical approach to personality disorders can be understood in part due to ethical principles within psychiatry. The ‘do no harm principle’ led to Kraepelinian assumptions about mental illness and an emphasis on empirically grounded taxonomic systems that were not biased by unsubstantiated theories about etiology.[12] A taxonomic checklist based on empirical observations rather than bias prone theoretical assumptions developed. It was both categorical and hierarchical, with the diagnosis of a disorder being dependent on the presence of a threshold number categories (usually five) out of a total number (seven to nine)[12] Disorders were organized into three clusters, existing purely to make the disorders easier to remember by associating them with others that have similar symptoms, not based on any theory about their relatedness.[10]

The dimensional model was developed in response to the limitations of this standard categorical model.[9] The expectations from a Kraepelinian approach were that as systematic research into psychiatric health increased; diagnostic categories would be refined and targeted reliable treatments would be developed.[13] However this reductionist approach to diagnostic categorization has led to disorders with high comorbidity, life course instability, poor treatment effectiveness and poor diagnostic agreement.[1] In addition the findings from psychopathological research have led to an increasing body of evidence suggesting overlaps between normal and maladaptive personality and interrelatedness across disorders.[7] These findings have been further supported by genetic[14] and developmental studies[15] which have constantly pointed towards greater interrelatedness then the diagnostic categories can offer. These consistently disconformity findings, alongside the successful shift to a continuous rather than categorical approach in other areas of research, such as regarding ASD, led to consideration of alternative approaches.[16]

The development of factor analysis as a popular statistical technique in differential psychology has led to an increase in attempts at finding underlying traits. More recently this has been used in the context of personality disorders both as a means of looking at which personality traits current categorical diagnoses are related to and also as a method of looking for new psychopathological latent variables. Factor analysis has helped illustrate that the full range of relevant personality pathology is not included in the DSM psychiatry nosology. However the technique does not show information about a continuum from normal to clinically relevant personality.[9]

Dimensional classification techniques show individual multidimensional profiles and therefore they can show information about a personality continuum (from normal to atypical), one such technique is Hybrid modeling.[17] Cut off points can be introduced into these modals to show where a diagnosis may lie. However the number of different rating scales that need to be looked at and the lack of interdisciplinary research between statisticians and psychologists has meant that attempts at finding a ‘worldwide’ criteria for dimensional diagnosis using this method has been of limited success.[17]

Analyses have been conducted to test the relative fit of categorical and dimensional modals to evaluate whether single diagnostic categories are suited to either status. These types of analysis can include a range of data, including endophenotypes or other genetic or biological markers which increases their utility. Multivariate genetic analysis helps establish how well the current phenotypically developed structure of personality disorder diagnosis fits with the genetic structure underlying personality disorders. Results from these types of analysis support dimensional over categorical approaches.[10]

Network Analysis has been used as a means of integrating information about personality with personality disorders and as well as information about other genetic, biological and environmental influences into a single system and looking at interrelated causalities between them (See integrated modals).

There are different ways to ‘dimensionalize’ personality disorders, these can be summarised into two categories.

1. The first involves quantifying DSM-5 pathology. This can be done either based on the degree to which symptoms are present or on how close to a prototypic presentation a patient's presentation may be. The prototype approach includes features not present in the DSM.[18]
2. The second approach involves identification of DSM disorder traits by means of factor analysis to show underlying dimensions of the personality disorder criteria, this method may also include relevant psychopathology.[17]

The Five-Factor model of personality, which is the most dominant dimensional model,[19] has been used to conceptualize personality disorders and has received various empirical support. Under this approach, extreme levels of the basic personality traits identified by the FFM are what contributes to the maladaptive nature of personality disorders.[20] Over 50 published studies supporting this model have been identified, providing much empirical support for this approach. Most of these studies examine the relationship between scores on separate measures of Big Five trait and personality disorder symptoms.[20]

The Five-Factor model was first extended to personality disorders in the early 1990s, when it was established that a satisfactory profile of each personality disorder in the DSM-III-R could be created through various levels of Big Five traits.[5] Thomas Widiger and his colleagues have demonstrated that many of the central elements of personality disorders can be explained in terms of Big Five traits – for example, borderline personality disorder is characterized by high levels of hostility, trait anxiety and depression, and vulnerability, all of which are facets of neuroticism.[5] This approach also helps to differentiate characteristics of disorders that overlap under the current categorical model, such as avoidant and schizoid personality disorders. The Five-Factor-based approach explains much of that overlap as well as the ways in which they are different.[5] For example, both are characterized primarily by maladaptive excessive introversion, but antisocial personality disorder also includes high levels of facets of neuroticism (such as self-consciousness, anxiety, and vulnerability), while schizotypal personality disorder includes the addition of low assertiveness. The Five-Factor approach also resolves previous anomalies in factor analyses of personality disorders, which makes it a more explanatory model than the current categorical approach, which only includes three factors (odd-eccentric, dramatic-emotional, and anxious-fearful).[5]

A prototype diagnostic technique has been developed in which Five-Factor-based prototypes for each disorder were created, based on the aggregated ratings of personality disorder experts. These prototypes agree well with DSM diagnostic criteria.[20] The Five-Factor prototypes also reflected the high comorbidity rates of personality disorders. This is explained by the idea that various other disorders tap into dimensions that overlap with those of the primary diagnosis.[20]

Another Five-Factor based technique involves diagnosing personality disorders based on clinician ratings of various facets of the five factors (e.g. self-consciousness, which falls under the neuroticism factor; excitement seeking, which falls under the extraversion factor). This technique is partially based on the prototype model, as each facet's "score" is based on its rating of how prototypical it is of each personality disorder, with prototypically low facets (with a score less than 2) reverse-scored. Using this technique, diagnosis is based on an individual's summed score across relevant facets. This summed-score technique has been shown to be as sensitive as the prototype technique, and the easier computation method makes it a useful suggested screening technique.[6]

The Five-Factor assessment of personality disorders has also been correlated with the Psychopathy Resemblance Index of the NEO Personality Inventory, as well as with the individual personality dimensions of the NEO-PI-R.[21] It also resolves several issues regarding the PCL-R psychopathy assessment, as a Five-Factor-based re-interpretation of the PCL-R factor structure shows that the “Aggressive Narcissism” factor taps into facets of low agreeableness (with some contribution of facets of neuroticism and extraversion), and the “Socially deviant lifestyle” factor represents facets of low conscientiousness and low agreeableness. It has also been shown that the sex differences in personality disorders can be reasonably predicted by sex differences in Big 5 traits.[22]

The dimension of openness to experience of the Five-Factor model has been criticized for not directly relating to any of the major characteristics of personality disorders in the same way as do the other four dimensions . It has been suggested that schizotypal and histrionic personality disorders could be partially characterized by high levels of openness to experience (in the forms of openness to ideas and feelings, respectively) , while obsessive-compulsive, paranoid, schizoid, and avoidant personality disorders can all be conceptualized by extremely low levels of openness . However, there is little to no empirical support for this hypothesis, particularly with schizotypal personality disorder. Additionally, the Openness scale of the NEO-PI-R, which is one of the most widely used measures of Big Five traits, was based on research and theory which viewed openness (such as self-actualization and personal growth) as beneficial, so measurement of extreme openness using the NEO-PI-R, is actually a marker of good mental health.[5]

The Five-Factor approach has been criticized for being limited in some respects in its conceptualization of personality disorders. This limitation is due to the fact that it does not include evaluative trait terms such as “bad”, “awful”, or “vicious”. Some research has suggested that two evaluative dimensions should be added to the Five-Factor model of personality disorders. Empirical support for this approach comes from factor analyses that include the Big Five factors and evaluative terms. These analyses show that the evaluative terms contribute to two additional factors, one each for positive and negative valence. The addition of these two factors resolves much of the ambiguity of the openness dimension in the Five-Factor approach, as the openness factor changes to a conventionality factor, and adjectives such as “odd”, “strange”, and “weird” (which all characterize schizotypal personality disorder) fall onto the negative valence factor. These results indicate that the inclusion of evaluative terms and valence dimensions can be valuable for better describing the extreme and maladaptive levels of personality traits that comprise personality disorder profiles.[5]

A two-factor model of psychopathology in general has also been suggested, in which most disorders fall along internalizing and externalizing dimensions,[23][24] which encompass mood and anxiety disorders, and antisocial personality and substance use disorders, respectively.[24] Although this approach was originally developed to understand psychopathology in general, it has often been focused to apply to personality disorders, such as borderline personality disorder to help better understand patterns of comorbidity.[25]

Hungarian psychiatrist Léopold Szondi formulated in 1935 a dimensional model of personality comprising four dimensions and eight drives ("facets" in DSM V terminology). It was based on a drive theory, in which the four dimensions correspond to the independent hereditary circular mental diseases established by the psychiatric genetics of the time:[26] the schizoform (containing the paranoid and the catatonic drives), the manic-depressive (for the "contact" dimension), the paroxysmal (including the epileptic and hysteric drives), and the sexual drive disorder (including the hermaphrodite and the sadomasochist drives).[27] The Sex (S) and Contact (C) dimensions can be further grouped as representing pulsions at the border with the outer world, while the Paroximal (P) and Schizoform (Sch) dimensions at the inner part of the psyche.

Network analysis diverts most strongly from the categorical approach because it assumes that the symptoms of a disorder have a causal relationship to each other. This theoretical assumption is made because no mental disorder can currently be understood as existing independently from its symptoms, as other medical diseases can be. According to the network approach symptoms are not looked at as the product of a set of latent disorders, instead they are looked at as mutually interacting and reciprocally reinforcing elements within a wider network.[28] Therefore, a diagnosis is not needed to understand why the symptoms hang together. Clusters of densely connected symptoms can be defined as disorders, but they are inevitably intertwined with related symptoms and cannot be entirely separated. This helps explain the growing body of research showing comorbidity, co-occurring genetic markers and co-occurring symptoms across personality disorders.[29]

The therapeutic consequence of this is that treatment is targeted at the symptoms themselves and the causal relations between them, not the overarching diagnosis. This is because targeting the diagnosis is trying to treat an unspecified summary of a complex collection of causes. Adopting this attitude sits well with the therapeutic treatments in use at the moment that have the strongest evidence base.[29]

Network analysis has its roots in mathematics and physics but is increasingly being used in other areas. Essentially it is a method of analyzing mutually interacting entities by represented them as nodes which are connected to through relations called edges. Edges represent any sort of relation such as a partial correlation. Complex network analyses of other subjects have looked at tipping points, where one system suddenly transitions into another, such as when a tropical forests goes into a savannah. If these could be identified in individual's psychopathological dynamic networks then they could be used to determine when a person's network is on the brink of collapse and what can be done to alter it.[29]

There are concerns that the network modal does not have enough parsimony and is too difficult to interpret.[30]

There are concerns that the addition of dimensional models to DSM-5 may raise confusion. Carole Lieberman has stated that "As it is now, people don't really make use of the subcategories that there are to describe severity of symptoms. Instead, I see this as a tool that insurance companies could well co-opt to try to deny benefits."[33]