Fig. 12.1 Dynamics of well-being
Validation of psychiatric classifications: The psychobiological model of personality as an exemplar
C. Robert Cloninger
Confidence in current psychiatric classifications has fallen sharply because they fail to identify the underlying psychobiological causes of syndromes and fail to guide specific prescriptions for treatment. The operational checklist approach has proliferated from 14 useful diagnoses in 1972 (Feighner et al. 1972) to more than 300 sets of criteria for the highly overlapping disorders in DSM-5 (APA, 2013). It had been hoped that the number of atypical cases would be reduced by the addition of more categories, but that has not happened, suggesting that the added categories are redundant and doubtful in utility and validity (Feighner et al. 1972; Kendell and Jablensky 2003; Martin et al. 1985a, b).
In fact, the putative mental disorders in current classifications do not have sharp natural boundaries with points of rarity separating them, so they are not validated as discrete disease entities or taxa (Cloninger 2007; Kendell and Jablensky 2003; Kendell 1982). Some evidence of partial separation has been presented, but even in these cases the separation is weak and inconsistent (Cloninger et al. 1985; Cloninger et al. 1984). The partial separation observed can be explained as the consequences of meta-stable configural states of complex multidimensional systems (Cloninger 2007).
The occurrence of meta-stable configural states is a consistent feature of the dynamics of complex adaptive systems (Waldrop 1992), and has an important implication that mitigates the criticism of categorical classification systems by advocates of purely dimensional systems: self-organizing interactions among dimensions of complex adaptive systems lead to syndromes that are dysfunctional and relatively stable with fuzzy boundaries (Cloninger et al. 1997). Essentially people get stuck in a local optimum rather than the global optimum of well-being, as illustrated in Figure 12.1. There is no direct path to global well-being. For example, in order to advance in well-being, people often have to tolerate deprivation and give up local benefits (e.g., transient intoxication for an addict, or transient positive emotions from binging for a bulimic, illusory entitlement for a narcissist). In other words, no pain, no gain aptly summarizes the dynamics of the “rugged landscape” of complex psychobiological systems. Consequently, many people resist change and persist in poorly adapted lives, causing much suffering for themselves and/or others.
Fig. 12.1 Dynamics of well-being
Much useful person-centered clinical information is lost if such meta-stable configural states are ignored and people are only described in terms of quantitative dimensions (Cloninger et al. 2012). Consequently, multiple approaches to case descriptions are needed, including dimensions, configural profiles, and narrative accounts of development over the course of a person’s life. In other words, something like categories are useful in classifications, even though they are not discrete disease-entities. However, criteria for category-like prototypes also need to be understood systematically in terms of underlying dimensions and described in part in terms of narratives of the life course of development, which has not been included in current classifications. When underlying dimensions, meta-stable configural states, and life narratives are simultaneously considered as aspects of an integrated system of description and classification, focus can return to the health promotion of the developing person who has self-organizing goals and values, rather than focusing on abstract definitions of heterogeneous syndromes (Cloninger 2013a).
Unfortunately, the developers and users of categorical classification systems often seem to believe that they are dealing with discrete disease entities. Despite the acknowledgment of extensive overlap among disorders, the categories in current classifications have often been reified and misused as if they were homogeneous and discrete disease entities despite the lack of precise natural boundaries between conditions or between what is considered normal and abnormal. The specious reification is facilitated by the clinician’s focus on abstract criteria for syndromes rather than on the developing person as a whole and by the lack of a systematic understanding of the underlying causal processes that underlie the development of personality and psychopathology. The number of disorders enumerated continues to proliferate from 106 in DSM-I in 1952 to 297 in DSM-IV and more than 300 in DSM-5 in 2013 (Rosenberg 2013). As the range of disorders has widened, estimates of the prevalence of mental disorders has risen to nearly half of the U.S. population, but are much lower when impairment criteria are carefully applied (Narrow et al. 2002).
The developers of the DSM have acknowledged that “no definition adequately specifies precise boundaries for the concept of mental disorder” (APA 1994). DSM-5 defines a mental disorder as “a syndrome characterized by clinically significant disturbance in an individual’s cognition, emotion regulation, or behavior that reflects a dysfunction in the psychological, biological, or developmental processes underlying mental functioning.” It further notes that disorders are “usually” associated with significant distress or disability, and that “expectable or culturally approved response to a common stressor or loss, such as the death of a loved one, is not a mental disorder.” However, the definition appears to be an afterthought added as a loose generalization rather than a set of strict requirements because each element of these supposedly “required” features has exceptions in practice. For example, in DSM-5 Somatic Symptom Disorder can involve only a single symptom, so it is not a syndrome (i.e., a group of consistently associated symptoms). Nevertheless, previously accepted criteria for Somatization Disorder were omitted from DSM-5 despite their having well-established validity from longitudinal, family, and adoption studies (Cloninger et al. 1986; Cloninger et al. 1984). Bereavement (i.e., loss of a loved one) is not an exclusion criterion for Major Depressive Disorder in DSM-5, even though there are well-established differences between these conditions (Clayton 1990; Clayton et al. 1974). Of course, a single specific phobia could also be a mental disorder and syndromes can be loosely defined to include judgments about distress and impairment, but the APA Task Force is correct that it does not have a “consistent operational definition that covers all situations (APA 1994, 2013).” Without clear guidance from a precise definition of mental disorder or standards of scientific evidence for what is a useful and valid distinction within the classification system, decisions to add or subtract a diagnosis have often degenerated to non-scientific political discussions of what groups of users like.
As a result of an unmanageable number of redundant criteria, clinicians tend to justify their initial unreliable impressions based on presenting complaints by listing symptoms that fit their impression; and they often fail to obtain a thorough person-centered life narrative (Cloninger et al. 2006). Consequently, the quality of life histories has been impoverished inadvertently by the emphasis on cross-sectional checklists in DSM-III through 5, leading to poorer understanding of the full course of development of illness by many recently trained clinicians. Perhaps the large number of redundant criteria sets accounts for the disappointingly low reliability observed for most diagnoses in DSM-5 field trials (Regier et al. 2013).
These developments call into question the adequacy of the natural history approach to validation of mental disorders that Robins and Guze (1970) modeled on the work of Sydenham in the seventeenth century and Kraepelin in the eighteenth century (Cloninger 1989). Robins and Guze recommended what they regarded as an atheoretical empirical approach in which valid diagnoses could be established by studies involving five phases: clinical description to describe a syndrome of associated signs and symptoms, exclusion of other disorders, laboratory studies to identify causes and distinguishing biological processes, follow-up studies to characterize outcome and show the stability of diagnoses, and family studies to show familial aggregation of people with the same disorders in families (Robins and Guze 1970). Originally, 14 categories were distinguished on the basis of four of these phases. No laboratory test reliably distinguished among the disorders in the early classifications and that remains true to this day (APA 2013), despite the perennial promise that such laboratory findings will be shortly forthcoming (de Freitas Araujo 2011; Moreira-Almeida and Santos 2011).
Robins and Guze (1970) emphasized the importance of exclusion criteria so that their approach would be person-centered and allow only one diagnosis of mental disorder per person (except for depressions that could be secondary to a pre-existing illness). Unfortunately, exclusion criteria have been systematically weakened or dropped in DSM with the initial justification that classifications should be comprehensive and provide a label for anyone with a mental disorder if at all possible (Cloninger 1990, 2002; Maser and Cloninger 1990. This has led to extensive “comorbidity” with overlap between redundant criteria sets, which is so extensive that DSM-IV and DSM-5 explicitly acknowledge that the lack of discriminant validity means that the putative disorders cannot be regarded as discrete disease-entities (APA 1994, 2013). In practice, under the current diagnostic rules, people who qualify for one diagnosis usually satisfy criteria for multiple disorders (Cloninger 2002). There is so much heterogeneity within categories and overlap among categories that neurochemical, genetic, and brain imaging findings have failed to distinguish putative mental disorders from one another reliably, primarily because of a lack of specificity (Craddock and Owen 2005).
What does the disappointing state of psychiatric classification mean for future work at establishing the validity of psychiatric assessments? Why has it been so difficult to develop a valid psychiatric classification? The fundamental challenge is that common mental disorders are complex phenomena that result from non-linear interactions among multiple biological, mental, social, and spiritual processes that influence development (Arnedo et al. 2013; Cloninger 2004; Svrakic et al. 2013). These interactions are complex in the sense that specific combinations of the same antecedent causes can lead to different clinical outcomes (“multi-finality”) and different antecedent can lead to the same outcome through common developmental pathways (“equi-finality”) (Cicchetti and Rogosch 1996; Cloninger et al. 1997). Reciprocal feedback interactions are pervasive characteristics of psychobiological processes, so that models are inadequate if they assume linearity (i.e., consider unidirectional chains of causes whose effects are additive). Linear thinking from “top-down” (i.e., phenotype to cause) or “bottom-up” (i.e., cause to phenotype) has never and can never prove an accurate understanding of the pathophysiology of the reciprocal feedback interactions among the underlying causes of mental disorders, despite the illusory promises of reductionist materialism (de Freitas Araujo 2011).
Nevertheless, psychiatry now has the tools needed to systematically begin to understand the processes that lead to both well-being and ill-being. The work over the last two decades on the validation of the psychobiological model of personality illustrates the way an integrative understanding of biological, psychological, and social processes underlying health can permit the development of valid methods for assessing personality and its disorders. Extensive research has shown that understanding the structure, function, and development of personality provides a framework for understanding the determinants of health as well as vulnerability to personality disorders and psychopathology (Cloninger 2013a; Cloninger, Salloum, et al. 2012). Although this is a sweeping claim, at a minimum, consideration of the psychobiological model of personality provides an example of a systematic way to validate psychiatric classifications and points out key observations that have been neglected in alternative approaches, thereby leading to the inadequacies of current and recently proposed systems for personality and its disorders.
Many approaches that have been advocated for personality assessment have failed to produce models and theories that account for the facts about personality that will be discussed here. Personality models have been based on factor analysis of descriptors (Eysenck and Eysenck 1969; Thomas et al. 2012), lexical content of languages to describe personality (Benet and Waller 1995; Goldberg 1990), prototypic descriptions (Samuel and Widiger 2004), and a wide range of reductive approaches emphasizing biology, emotionality, cognition, or socialization. Consequently, much can be learned from the way an integrative psychobiological approach allows the establishment of validity. Of course, meaningful approaches to theoretical and practical understanding require integration of intuition, observation, and tests of predictions, so that many divergent facts are carefully considered. People always want to find systematic methods that can be applied as algorithms with little creative thinking or understanding; consequently, they end up relying excessively on methods that are inadequate to deal with all the hidden complexities of natural phenomena. Albert Einstein warned us about such hidden complexities when he said, “There is, of course, no logical way leading to the establishment of a theory, but only groping, constructive attempts controlled by careful considerations of factual knowledge” (Shankland 1964).
It is useful in my experience to begin any effort at understanding a phenomenon to try to define its properties clearly and precisely. In the simplest definition, personality is the distinctive way that an individual learns to adapt (Cloninger 2004). Personality can also be defined more specifically as the characteristics of the self plus the internal and external forces that pull on the self. After exhaustive consideration of hundreds of suggested definitions, Gordon Allport offered the following definition: “Personality is the dynamic organization within the individual of those psychophysical systems that determine his unique adjustments to his environment” (Allport 1937). In order to more fully recognize self-directed processes in development (Rogers 1995), Allport’s definition can be revised to “the dynamic organization within the individual of the psychobiological systems by which the person both shapes and adapts uniquely to an ever-changing internal and external environment” (Cloninger and Cloninger 2011). Thus personality is not a set of fixed differences between people as construed by trait theory, but is a complex set of functions by which a person both shapes and adapts to experience in the proactive development of his or her life narrative.
The foregoing definition of personality entails that assessment should be directed toward mechanisms of learning and memory that occur within the person, rather than merely superficial behaviors that differ between people (Cervone 2005). Jeffrey Gray pointed out that Eysenck’s personality models derived by factor analysis described the architecture of between-person differences but did not correspond to the underlying learning processes within the person (Cloninger 1986). For instance, Eysenck’s neurotic extraverts (i.e., novelty seekers) learn best in response to reward conditioning, whereas neurotic introverts (i.e., harm-avoidant individuals) learn best in response to aversive conditioning (Cloninger 1986, 1987; Corr et al. 1997. The effects of behavioral conditioning interact with personality type (that is, specific combinations of personality and conditioning have unique effects): a person who is highly harm avoidant (i.e., worried, fearful, and shy) has an augmented startle when they are thinking of something unpleasant, whereas a person who is low in harm avoidance (i.e., risk-taking, relaxed, and outgoing) has a reduced startle when they are thinking of something pleasant (Corr et al. 1997; Corr, Pickering, et al. 1995; Corr, Wilson, et al., 1995).
However, pleasant thoughts do not reduce the startle responses of people who are high in harm avoidance, and unpleasant thoughts do not augment the startle responses of people low in harm avoidance. Nevertheless, most personality psychologists were trained to rely on the traits that emerge from linear factor analysis and persist in this practice despite the questionable validity of using only additive traits to understand the interactive processes underlying personality (Cloninger 2008). In other words, most people think of traits as composed of separate units that can be added together to describe a total personality, whereas traits interact with each other and with the person’s situation in ways that are not additive. The whole of personality is more than the sum of its parts, so personality cannot be reduced to a set of individual parts. Statistical methods that assume such additivity, as does linear factor analysis, produce distorted models of personality structure that are not true to life and impede understanding of the learning processes within a person by which he or she adapts to their situations in life.
A fundamental question about personality is whether abnormal traits are extremes of normal variation or results of particular combinations of traits in situations for which they are poorly adapted. The decisive fact is the observation that the (correlational) structure of personality traits is the same in clinical samples as it is in the general population, whether or not the test is designed to measure normal traits (Bayon et al. 1996; Cloninger 2008; Strack 2006; Svrakic et al. 1993) or abnormal traits (Fossati et al. 2013). In other words, abnormal personality profiles are more prevalent in clinical samples than in the general population, but the correlations among these traits are the same regardless of the average values of scores. Therefore, abnormal personality traits must be extreme combinations of normal variation in personality. Even schizotypal, cyclothymic, and depressive personality traits are fully accounted for by variation in normal personality traits (Cloninger 1999). This finding supports the view that personality traits involve adaptive functions that enable people to learn how to deal with the full range of life functions, including sexuality, materiality, emotion, intellect, and spirituality (Cloninger 2004). Consequently, much can be learned about personality in relation to health by considering facts related to its function, structure, evolution, and development. In fact, emphasis on abnormal extremes may be therapeutically counterproductive, thereby undermining the therapeutic utility of personality assessment (Cloninger and Cloninger 2011).
What we have learned about personality helps us to understand the relations between personality and health. These useful observations can be divided into information about its functions, structure, evolution, and development. Here the key observations that have been evaluated and confirmed are listed, and the process that led to their discovery will be discussed in the next section.
(1) Personality refers to adaptive processes of learning and memory within individuals (Cloninger 2004):
(a) There are three major systems of learning and memory in human beings: behavioral conditioning of habits and skills, semantic learning of facts and propositions, and self-aware learning of intuitions and narratives (Tulving 1987, 2002).
(b) These three systems of learning distinguish among the properties of three distinct domains of human personality (temperament, character, and the narrative self) (Cloninger 1994, 2004). Specifically, temperament varies quantitatively in terms of strengths of habits and irrational emotional drives (e.g., fear, anger), whereas character varies qualitatively in terms of the concepts that organize our goals and values in a more or less rational way. The narrative self develops in self-aware consciousness in a way that is more or less self-organizing and creative in that people can develop in ways that are not fully predictable by temperament and character.
(c)Temperament, character, and the narrative self represent the corporeal, mental, and spiritual components of personality respectively and have distinctive functional properties (Cloninger 2004).
(2) Adaptive functions of personality are strongly related to individual differences in activation of brain circuitry (Cloninger 2009; Cloninger and Kedia 2011; Sussman and Cloninger 2011).
(3) Specific functions can be measured as facets of personality (personality subscales) that involve adaptation in specific situations of life (Cloninger 2009; Cloninger and Kedia 2011).
(4) Variation in personality traits varies quantitatively along multiple dimensions:
(a) Personality traits are weakly to moderately correlated, thereby influencing one another during development.
(b) There are no sharp boundaries separating people into taxa or discrete personality subtypes (Cloninger 2007).
(5) Personality prototypes or clusters of people with similar personality profiles occur as meta-stable configurations of extremes on multiple dimensions (Cloninger and Cloninger 2011).
(6) The correlations within domains of temperament or character are weak but there are strong interactions (i.e., reciprocal feedback) among these domains during development (in other words, the emotional drives of temperament influence the development of character, and vice versa) (Cloninger et al. 1997).
These structural relationships are depicted in Figure 12.2.
Fig. 12.2 Cycle of reciprocal interactions among the domains of personality
(7) Components of personality in the psychobiological model are summarized in Figure 12.3. Behavioral conditioning of habits underlying four temperament dimensions evolved in a stepwise fashion and was well developed in early vertebrates (fish to reptiles) (Cloninger and Gilligan 1987). These temperament dimensions are called Harm Avoidance (i.e., anxious, shy vs. risk-taking, outgoing), Novelty Seeking (i.e., impulsive, disorderly vs. rigid, orderly), Reward Dependence (i.e., warm, attached vs. aloof, detached), and Persistence (i.e., determined, ambitious vs. easily discouraged, vacillating). Earlier questionable speculations about such evolutionary paths have recently been tested and refined empirically. This has been possible by means of detailed studies that integrate molecular phylogenetics and the comparative neuroanatomy of the ancestors of human beings (Cloninger 2009; Cloninger and Kedia 2011). The coincident changes in structure and function of brain organization in the unique chain of ancestors leading to human beings provides a solid foundation for understanding structure–function relations in the evolving human brain. This evolutionary basis for organization of human brain structure–function relations has also been tested by results of functional brain imaging, which show strong interactions among circuits that instantiate distinct functions measured by different personality dimensions (Cloninger, Zohar, et al. 2012; Gusnard et al. 2001; Gusnard et al. 2003; Pezawas et al. 2005).
(8) In mammals, the structures and functions of semantic learning evolved with the neocortical control of the reptilian brain to regulate emotional drive (which underlies coope rativeness) and analytical reasoning (which underlies self-directedness); later self-transcendence emerged with self-aware consciousness in modern human beings (Cloninger 2009; Cloninger and Kedia 2011).
(9) The development of personality in human beings is a complex adaptive system whose dynamics is shaped by reciprocal feedback relations among multiple processes interacting with one another differentially in various situations (Cloninger et al. 1997; Josefsson, Jokela, et al. 2013).
Fig. 12.3 Schematic summary of the psychobiological model of personality
(10) Personality traits strongly modulate susceptibility to the full range of psychopathology (Cloninger 1999; Cloninger et al. 2010).
(11) Personality traits strongly modulate susceptibility to physical disorders, particularly the major chronic diseases such as atherosclerosis (Cloninger 2013a; Rosenstrom et al. 2012).
(12)A healthy personality is characterized by average temperaments and strong character development (high Self-directedness, Cooperativeness, and Self-transcendence) (Cloninger 2013b). Self-directedness and Cooperativeness are insufficient for optimal health, at least under current world conditions (Cloninger 2013b). Self-transcendence is also needed for flourishing of the narrative self with creative functioning, plasticity, and fulfilling values (Cloninger and Cloninger 2011; Seligman 2011).
The psychobiological model of personality was developed in three major steps. Initially, personality was limited to four temperament dimensions that were based on individual differences in behavioral conditioning of habits or emotional drives. The model was based on extensive research in operant learning, experimental manipulation of brain systems, and twin studies of the genetic structure of personality (Cloninger 1986, 1987). The temperaments were called Harm Avoidance, Novelty Seeking, Reward Dependence, and Persistence. The identified traits were called temperaments because they were presumed to be moderately heritable and developmentally stable from an early age, which was later consistently confirmed (Heath et al. 1994; Josefsson, Jokela, et al. 2013; Stallings et al. 1996).
The temperament dimensions were able to distinguish variants of personality disorder in terms of profiles (i.e., configurations of extremes of the dimensions) (Cloninger 1987) (see Figure 12.4). For example, the antisocial type of personality profile is high in Novelty Seeking (i.e., impulsive, quick-tempered), low in Harm Avoidance (i.e., risk-taking, uninhibited), and low in Reward Dependence (i.e., cold, aloof). However, this same profile could occur in people who were mature and responsible citizens despite their adventurous emotional style. So other features were needed to specify whether someone had a personality disorder or not, and to quantify how mature or immature the person was.
Fig. 12.4 The temperament cube
An empirical search was first carried out to identify any personality traits that could not be explained by the four temperament dimensions. This yielded clues to three traits that were then elaborated into character traits of Self-directedness (i.e., resourceful, purposeful, responsible), Cooperativeness (i.e., tolerant, helpful, empathic), and Self-transcendence (i.e., intuitive, imaginative, spiritual), each expressed in somewhat different ways in five types of life situations (i.e., sexual, material, emotional, intellectual, and spiritual) (Cloninger 2004; Cloninger et al. 1993). Studies of the resulting Temperament and Character Inventory (TCI) were then carried out in both the general population and in clinical samples of psychiatric in-patients and outpatients for purposes of validation (Bayon et al. 1996; Cloninger et al. 1994; Cloninger et al. 1993; Svrakic et al. 1993). Findings showed that the three character dimensions allowed measurement of whether someone had a personality disorder and how severe the immaturity of personality was (Svrakic et al. 1993). Specifically, low scores in Self-directedness and Cooperativeness provide a measure of the DSM concept of personality disorder, which has subsequently been confirmed consistently in many studies in many cultures. In fact, high Self-directedness and Cooperativeness were recently proposed by the DSM-5 Personality Disorder Study Group to be indicators of a healthy personality (APA 2013; Cloninger 2010).
Nevertheless, two surprises were observed about character. First, character traits were found to be as heritable as temperament traits (Gillespie et al. 2003). This finding called into question the hypothesis made in 1993 that character was less heritable and more influenced by sociocultural influences than temperament (Cloninger et al. 1993). The distinction between temperament and character cannot be based on the heritability of the dimensions, so I suggested that it was based on differences in the mechanism of learning. Subsequent research has confirmed that character traits are regulated by differences in the activation of specific zones of the human neocortex, particularly components of the semantic and self-aware systems of learning and memory (Cloninger 2004, 2008). For example, individual differences in Self-directedness are strongly correlated with activation of the medial prefrontal cortex, Cooperativeness with activation of the orbitofrontal cortex, and Self-transcendence with activation of the anterior frontal polar cortex (Cloninger 2004; Cloninger and Kedia 2011). In contrast, temperament dimensions are regulated by differences in activation of zones for regulation of habits and emotion in the limbic system (Gardini et al. 2009; Gusnard et al. 2003; Pezawas et al. 2005).
In addition to character being related to more recently evolved brain regions than temperament, character is also distinguished from temperament by its greater sensitivity to the effects of parental care-taking and sociocultural influences. Longitudinal studies from childhood through adulthood have confirmed the original hypothesis that character development is influenced by parental care-taking and social norm-favoring (Josefsson, Jokela, Cloninger, et al. 2013; Josefsson, Jokela, Hintsanen, et al. 2013). Temperament dimensions do not have a consistent direction of change over the life course; average scores stay the same because equal numbers of individuals increase or decrease as a result of individual differences in conditioning. In contrast, character traits develop in the direction favored by social norms.
Longitudinal studies also revealed a second surprise about character development (Cloninger et al. 1997). When character did change, the correlations among temperament and character dimensions allowed prediction of the direction of those changes as a complex adaptive process (Cloninger et al. 1997). However, it was not possible to foretell who would change, and most people did not change substantially.
What accounted for the capacity of some people to mature and to increase in well-being, others to become less well, and others to stay the same? The answer required an appreciation of the distinction between semantic and self-aware learning. Semantic learning is analytical and logical, so it is based on assumptions from which conclusions are deduced. Most people are as resistant to changing their assumptions and their outlook on life as they are to changing their habits. In contrast, self-aware learning has been called “mental time-travel” and involves the unique human capacity to change one’s perspective rapidly and freely by imagining and contemplating future developments in our personal narratives of life (Cloninger 2004; Tulving 2002).
Interactions among the three character traits produce meta-stable profiles with distinctive clinical features, as depicted in Figure 12.5. The relationship between the three character traits to learning can be understood by thinking of them as branches of mental self-government. Self-directedness is the executive branch, pursuing accomplishment of goals in a purposeful and responsible manner. Cooperativeness is the legislative branch, making the rules by which we get along with one another in a considerate and principled manner. Self-transcendence is the judicial branch, using its capacity for imagination, contemplation, and insight to recognize and understand when the rules apply. From this perspective, the capacity to identify with what is beyond one’s individual self (i.e., Self-transcendence) also allows us to imagine and contemplate change in outlook (i.e., perspective shifting). Self-transcendence, then, would have a key role in the theoretical thinking of scientists, the appreciation of artistic beauty, as well as the philosophical contemplation of values and the meaning of life. Could self-transcendence, then, be an indicator of who would grow and mature in character? In fact, longitudinal studies of people between 20 and 45 years of age have now shown that personality change is most likely to occur in people who are high in Self-transcendence, Novelty Seeking, and Persistence (Josefsson, Jokela, et al. 2013).
Fig. 12.5 The character cube
Self-directedness and Cooperativeness are consistently associated with maturity, health, and happiness, but the role of Self-transcendence is more complex because it depends on the full configuration of character traits. If Self-directedness is low, a person is unrealistic (i.e., represses true facts that are unpleasant and inconvenient). If a person has a vivid imagination (i.e., is high in Self-transcendence) and is unrealistic (i.e., is low in Self-directedness), then they have schizotypal traits with prominent magical thinking (Smith et al. 2008). Self-transcendence is always associated with increasing positive affect regardless of whether a person is high or low in the other two character traits. Therefore, the healthiest character profile results when all three character traits are elevated, a profile described as creative or enlightened (Cloninger 2013b; Cloninger and Cloninger 2011). A creative character profile is realistic, helpful, and flexibly adaptive.
Ongoing research is evaluating the mechanisms by which this combination of traits facilitates psychobiological coherence and well-being (Cloninger and Zohar 2011; Cloninger, Zohar, et al. 2012; Zohar et al. 2013). A review of the TCI correlates of psychopathology is available elsewhere (Cloninger et al. 2010).
The most obvious difference between the psychobiological model and other modern personality models is the distinction between temperament and character, which are confounded in factor-analytic models. Factor analysts argue that the distinction between temperament and character is both unnecessary and mistakenly produces a more complex structure than is obtained under the simplifying assumption of linearity (Cloninger 2008). However, this simplified model is itself based on the false assumption of additivity. It does not account for the incontrovertible facts of personality development, such as sudden stepwise growth at critical tipping points and the phenomena of multi-finality and equi-finality (Cloninger et al. 1997).
The consequences of using invalid simplifying assumptions for clinical assessment can be seen by considering the heterogeneity of the content within the traits identified in factor-analytic models. The most consistent trait in factor-based personality models is usually called Neuroticism or Negative Affectivity, and it is strongly correlated with both High TCI Harm Avoidance and Low TCI Self-directedness. That means that Neuroticism confounds two traits with different genetic influences, different brain circuitry, and different roles in learning and adaptation.
Psychiatrists and psychologists recognize that personality disorders are not the same as anxiety disorders, but these patients groups are both described as high in Neuroticism in factor-analytic models. Specifically, high Harm Avoidance is correlated with augmented startle responses and Mismatch Negativity, but not with dysfunctional cognitive attitudes (Corr et al. 1997; Hansenne et al. 2003). In contrast, low Self-directedness is associated with dysfunctional attitudes but not with augmented startle or Mismatch Negativity (Luty et al. 1999; Richter and Eisemann 2002). Hence factor-analytic models falsely assume homogeneity in whatever is correlated, an error that can be avoided by attention to extra-statistical information about biology and development that are crucial for valid psychiatric classification.
The criteria proposed by the DSM-5 working group on personality disorder were not accepted, because the APA’s Scientific Review Committee regarded the scientific evidence as insufficient for the major changes proposed and the APA’s Clinical and Public Health Review Board regarded the criteria as too unwieldy for routine clinical use.
The proposed criteria were not merely complex; they were made up of three components that were developed separately and are not coherently related to one another. The three components of the proposed criteria were a reduced list of personality disorder types, a description of healthy personality, and a list of five pathological traits like those derived by factor-analysis (APA 2013). However, the categories were not systematically derived from the set of quantitative traits, as is done in the psychobiological model of personality. Likewise, the healthy personality traits were not healthy poles of the pathological personality traits. In fact, the description of healthy personality included measures closely related to Self-directedness and Cooperativeness. Self-directedness is not the healthy pole of Negative Affectivity because Negative Affectivity includes low Self-directedness combined with high Harm Avoidance.
As a result of the apparent inconsistencies, the subcommittees tried to integrate the components of the proposed criteria. Unfortunately, the result that is listed in Section III of DSM-5 is obviously an awkward effort at retrofitting disparate elements to one another. The absence of a coherent theory and the use of analytic methods that make invalid simplifying assumptions about personality (specifically linear factor-analysis) reflects the scientific disarray afflicting psychiatric classification and the field of abnormal personality in particular (Cloninger 2007).
Personality develops as a complex adaptive system, thereby leading to sudden stepwise growth, multi-finality, and equi-finality. This means that development is a non-linear process in which individuals are often stuck in a meta-stable “attractor” state (Cloninger 2004), as depicted in Figure 12.1. They stay in these states for long periods of stasis until they reach a critical tipping point, at which time they may rapidly shift into another attractor state with higher or lower well-being. Once in this state, they remain there even if the factors that led to the transition subside. This provides a precise quantitative account of the dynamics of personality development, and it also provides a bridge to prototypic models of personality.
In essence, configurations of multiple temperament or character traits define particular profiles that correspond to traditionally recognized personality prototypes like the example of antisocial personality disorder given earlier. Hence multidimensional profiles are a person-centered approach to description similar to prototypes (Cloninger 2004; Cloninger and Cloninger 2011). Dividing each dimension at its median into high and low extremes is sufficient to cluster individuals to the prototype they most resemble, thereby providing remarkably more information than linear analyses can provide (Cloninger and Zohar 2011; Cloninger, Zohar, et al. 2012).
The psychobiological model provides both quantitative measurements and prototypic profiles in a person-centered perspective, thereby providing an explanation for the power of prototypic formulations. Perhaps this is what Robins and Guze sought to recognize by insisting that a person could have only one diagnosis, which they found adequate in 80 percent of mental patients. Relaxing exclusion criteria in DSM created the appearance of comorbidity as a result of what are overly loose and redundant criteria.
In addition, the psychobiological model provides a way to recognize the great importance of both traits and situations. A person’s behavior varies more between situations than between persons (Fleeson 2001). The facets of the dimensions correspond to the expression of similar functions in different situations (Cloninger 2004). Hence extreme high and low scores in particular facets identify outstanding strengths and weaknesses that a person has in particular situations, much as is done in schema-based cognitive therapy and in narrative therapy. The emphasis in the integrative approach to treatment guided by the psychobiological model is on reflection and contemplation of goals and values so that a person takes the initiative to accept their situation and commits to work toward valued actions, as in evidence-based third-wave psychotherapies (Vowles et al. 2011).
The development and validation of the psychobiological model of personality shows that there is no purely empirical or purely logical way that consistently leads to establishing the validity of a system of assessment and classification. All approaches to valid knowledge require the use of intuition, reasoning, and observations to test, correct, and refine partial insights (Cloninger 2004; Godel 1981). Algorithmic approaches vary in their adequacy for understanding different phenomena under particular conditions. No system of classification should be regarded as a “bible” because they are certainly not infallible and have limited reliability and validity in practice. Because they stifle creative investigation of alternative approaches, requiring use of certain criteria like the DSM-5 or the Research Domain Criteria of the National Institute of Mental Health in the USA for funding in research is a seriously flawed science policy.
Psychiatry now has remarkable bioinformatic tools for the development of valid classifications (Arnedo et al. 2013; Arnedo et al. in press), but the complexity of nature is humbling. We must approach human nature with creativity and humility, avoiding rigid preconceived protocols and adapting ourselves to what we can observe, interpret, and contemplate about the inexhaustible mysteries of human nature.
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