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Thursday, October 03, 2013

The p Factor: One General Psychopathology Factor in the Structure of Psychiatric Disorders


Using the Dunedin Multidisciplinary Health and Development Study as a data source, researchers Terrie Moffitt, Avshalom Caspi, and their team examined "the structure of psychopathology, taking into account dimensionality, persistence, co-occurrence, and sequential comorbidity of mental disorders across 20 years, from adolescence to midlife."

The researchers initially explained psychopathology using three higher-order factors (Internalizing, Externalizing, and Thought Disorder). However, they found that one General Psychopathology dimension explained psychopathology even better. They called this dimension the p factor. Higher p scores are "associated with more life impairment, greater familiality, worse developmental histories, and more compromised early-life brain function."

This is an interesting approach to understanding psychopathology. However, until researchers discover what many therapists already know (i.e., that most mental illness is due some form of relational trauma), they will still be wandering off into the tall grass and missing the obvious.

General Psychopathology Factor May Describe Structure of Psychiatric Disorders


Mental disorders have traditionally been viewed as distinct categorical entities, but the high incidence of comorbid, or co-occurring, disorders challenges this view.

As researchers Terrie Moffitt, Avshalom Caspi, and colleagues observe in their new article in Clinical Psychological Science, about half of the people who meet diagnostic criteria for one disorder also meet the diagnostic criteria for another disorder at the same time.

“The high rates of comorbidity observed among mental disorders suggest that there may be a more parsimonious structure to psychopathology than implied by current nosologies that identify many separate and distinct disorders,” Moffitt, Caspi, and co-authors write.

To test this hypothesis, the researchers looked at longitudinal data collected from participants in the Dunedin Multidisciplinary Health and Development Study who were between the ages of 18 and 38. The researchers examined the participants’ mental health data, testing several possible statistical models to see which model best accounted for the data.

Confirmatory factor analysis revealed that the structure of mental disorders could be summarized by three core dimensions: an “internalizing” liability to depression and anxiety, an “externalizing” liability to antisocial and substance-use disorders, and a “thought disorder” liability to symptoms of psychosis.

Furthermore, analyses suggested that the propensity to develop any and all forms of common psychopathologies could be summarized by one general underlying dimension. Higher scores on this dimension, which the researchers call the “p factor,” were associated with greater life impairment, greater familiality, worse developmental histories, and more compromised brain function in early life.

“We propose that p influences present/absent performance on hundreds of psychiatric symptoms, which are typically aggregated into dozens of distinct diagnoses, which further aggregate into two overarching Externalizing versus Internalizing domains, which finally aggregate into one normally distributed dimension of psychopathology from low to high: p,” the researchers conclude.

One way to think about the p factor is in relation to the structure of cognitive abilities:

“These abilities are dissociable into separate abilities, such as verbal skills, visuospatial skills, working memory, or processing speed,” say the researchers. “Nonetheless, the general factor in intelligence (called the g factor) summarizes the observation that individuals who do well on one type of cognitive test tend to do well on all other types of cognitive tests.”

While there are specific factors that account for variation in each test, the g factor accounts for the positive correlation among all test scores, suggesting that there may be a common etiology that influences or contributes in some way to all cognitive functions.

The new findings suggest that, just as there is a general factor of cognitive ability, there may also be a general factor of psychopathology. This general factor may, in turn, help to explain why researchers have had difficulty finding distinct causes, biomarkers, and treatments for individual mental disorders.

Moffitt, Caspi, and colleagues hope that these initial findings generate “further tests, extensions, and discussions about the structure of common mental disorders.”


Caspi, A., Houts, R.M., Belsky, D.W., Goldman-Mellor, S.J., Harrington, HL, Israel, S., Meier, M.H., Ramrakha, S., Shalev, I., Poulton, R., & Moffitt, T.E. (2013, Aug 14). The p Factor: One General Psychopathology Factor in the Structure of Psychiatric Disorders? Clinical Psychological Science. DOI: 10.1177/2167702613497473

Here is the abstract and some of the introduction to the original article (available here):

Abstract


Mental disorders traditionally have been viewed as distinct, episodic, and categorical conditions. This view has been challenged by evidence that many disorders are sequentially comorbid, recurrent/chronic, and exist on a continuum. Using the Dunedin Multidisciplinary Health and Development Study, we examined the structure of psychopathology, taking into account dimensionality, persistence, co-occurrence, and sequential comorbidity of mental disorders across 20 years, from adolescence to midlife. Psychiatric disorders were initially explained by three higher-order factors (Internalizing, Externalizing, and Thought Disorder) but explained even better with one General Psychopathology dimension. We have called this dimension the p factor because it conceptually parallels a familiar dimension in psychological science: the g factor of general intelligence. Higher p scores are associated with more life impairment, greater familiality, worse developmental histories, and more compromised early-life brain function. The p factor explains why it is challenging to find causes, consequences; biomarkers, and treatments with specificity to individual mental disorders. Transdiagnostic approaches may improve research.
 

Introduction


A psychiatric nosology—the classification of mental disorders—is a practical tool. A nosology is useful for research because it is used to integrate and guide empirical studies. A nosology is useful for health-care delivery because it is used to make prognoses and to decide on treatment need and choice of treatment. The Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM-5; American Psychiatric Association, 2013) is the current ascendant nosology in clinical psychology and psychiatry. It may not be perfect (Sanislow et al., 2010), but it is what many of us work with in both research and clinical practice (Kupfcr, Kuhl, & Regier, 2013).

A persistent challenge to the DSM and related nosologies is comorbidity, the coexistence of two or more conditions or disorders (Hasin & Kilc-oyne, 2012; Kessler, Chiu, Demler, Merikangas, Sr Walters, 2005). Comorbidity rates are very high in psychiatry and conform roughly to the rule of 50910: Half of individuals who meet diagnostic criteria for one disorder meet diagnostic criteria for a second disorder at the same time half of individuals with two disorders meet criteria for a third disorder, and so forth (Newman, Moffitt, Caspi, & Silva, 1998). The high rates of comorbidity observed among mental disorders suggest that there may be a more parsimonious structure to psychopathology than implied by current nosologies that identify many separate and distinct disorders. This article begins by providing a brief historical review of empirical research on the structure of psychiatric disorders. It then offers an empirical update, suggesting that most common psychiatric disorders are unified by a single psychopathology dimension representing lesser-to-greater severity of psychopathology that is associated with compromised brain integrity.


Soon after the publication of the DSM-5 (American Psychiatric Association, 1994), psychological scientists noted the need for research that would examine patterns of comorbidity to "elucidate the broad, higher-order structure of phenotypic psychopathology" (Clark, Watson, & Reynolds, 1995, p. 131). We responded to this call by using confirmatory factor analysis (CFA) to evaluate alternative hypotheses about the latent structure underlying 10 common mental disorders among young adults, ages 18 to 21 years (Krueger, Caspi, Moffitt, & Silva, 1998) in contrast to the prominence of categorical models in the classification of adult psychopathologies, dimensional models had long enjoyed success in research on the classification of childhood psychopathologies, and empirical studies had converged on two primary dimensions as a way to characterize childhood disorders: Internalizing (including anxious and depression symptoms) and Externalizing (including aggressive, delinquent, and hyperactive-impulsive symptoms; Achenbach & Edelbrock, 1981). We could see no reason why this highly replicable two-dimensional structure of psychopathologies should suddenly vanish when research participants and patients suddenly turned age 18 years. Our data confirmed that a two-factor model accounted for the comorbidity of different young-adult disorders, and it bore a striking similarity to the model of childhood psychopathologies.


On the basis of this initial finding, we put forth the hypothesis that common DSM psychiatric disorders in adulthood may be characterized by two underlying core psychopathological processes: an Internalizing dimension indicating liability to experience mood and anxiety disorders, such as major depression (MDE), generalized anxiety disorder (GAD), panic disorder, and social phobia; and an Externalizing dimension indicating liability to experience substance disorders and antisocial disorders. During the past 15 years, multiple studies in different parts of the world, in different age-groups, in general community samples, and in clinical populations (e g , Forbush & Watson, 2013; Kendler, Prescott, Myers, & Neale, 2003; Krueger, 1999; Slade & Watson, 2006; Vollebergh et al., 2001) have replicated this basic finding (Krueger & Markon, 2006, 2011).
 

With the publication of the DSM-5 and debate fomenting over the need for a dimensional nosology (Insel, 2013), now is a good time to take stock of what is known about the structure of psychopathology. We have drawn on insights stemming from six recent findings about the epidemiology of mental disorders.
 

First, life-course epidemiology points to the need for longitudinal research designs to study the course of psychopathology. Previous research on the structure of psychopathology has been carried out using cross-sectional designs, focusing on individuals who report symptoms within a specified period (most often using the past 12 months as the reporting period). However, research has shown that cross-sectional snapshots mix single-episode, one-off cases with recurrent and chronic cases, which are known to differ in the extent of their comorbid conditions, the severity of their conditions, and possibly the etiology of their conditions. This is true for a variety of common disorders, including, for example, depression and alcohol-use disorders (Jackson & Sartor, in press; Monroe & Harkness, 2011), but also for psychotic experiences (van Os, Linscott, Myin-Germeys, Delespaul, & Krabbendam, 2009). That is whether manifested as recurrence or chronicity, some people are more prone than others to have persistent (as well as comorbid and severe) psychopathology. These results underscore the need to take the longitudinal course of mental disorders into account when modeling the higher-order structure of psychopathology.
 

Second, sequential comorbidity points to the need to model multiple disorders over time. Previous research has focused on comorbidity as defined by the co-occurrence of two or more disorders at the same time, but both retrospective (Kessler et al., 2011) and prospective-longitudinal (Copeland, Shanahan, Costello, & Angold, 2011) research has shown that comorbidity is also sequential. For example, longitudinal research has shown that GAD and MDE are linked to each other sequentially such that each disorder increases the likelihood of developing the other disorder in the future among individuals who presented with only one condition at one point in time (Moffitt et al.. 2007). These results underscore the need to take into account both concurrent and sequential comorbidity when evaluating the structure of psychopathology.

Third, psychotic disorders can be included in models of the structure of psychopathology. In most previous studies, researchers have omitted psychotic disorders from their evaluation of the structure of psychopathology. There are practical explanations for this omission (e g , most surveys of psychiatric disorders do not assess psychotic symptoms), but their absence from studies of the structure of psychopathology is conspicuous for three reasons: (a) New research on the dimensional model of psychosis has directed attention to the fact that psychotic symptoms are more commonly experienced in the general population than previously assumed, (b) psychotic disorders are striking in their especially high rates of comorbidity, and (c) psychotic disorders have extraordinary high economic burden. as expressed in the number of years lost due to ill health. disability, or early death (Murray et al., 2012; van Os et al., 2009). A few researchers recently have incorporated psychotic symptoms and symptoms of schizotypal personality disorders into their assessment of the structure of psychopathology, pointing to the existence of a third, distinct Thought Disorder spectrum (Kotov, Chang, et al., 2011; Kotov, Ruggero, et al., 2011). These results underscore the concern that efforts to model the structure of psychopathology without consideration of psychotic symptoms may not capture the true structure in the population.


Fourth, twin studies and risk-factor studies have suggested not only that there are substantial phenotypic correlations among pairs of psychiatric disorders but also that the liability to many disorder pairs (e g , schizophrenia and bipolar disorder; MDE and GAD; and alcohol and cannabis dependence) is influenced by the same genetic factors (Kendler, 1996; Lichtenstein et al., 2009; Sartor et al., 2010) and that many disorder pairs are characterized by shared intermediate phenotypes (Nolen-Hoeksema & Watkins, 2011). These findings imply that the causes of different disorders may be similar, highlighting the potential value of a transdiagnostic approach to psychiatric disorders. The value of a transdiagnostic approach has been further underscored by evidence that different disorders often respond to the same treatments (Barlow et al., 2011).
 

Fifth, symptom variation above and below diagnostic cut points implies modeling disorder data at the level of symptom scales. Researchers in most previous studies of the structure of psychopathology have modeled DSM disorders as dichotomous variables, although the few that have used symptom scales have generated comparable results (e g., Markon, 2010). Diagnostic thresholds increasingly have been acknowledged to be somewhat arbitrary, and it has been recognized that there is meaningful and useful clinical information both above and below diagnostic thresholds (Kessler et al., 2003; Lewinsohn, Shankman. Gau, & Klein, 2004). The DSM-5 also opted to emphasize dimensional conceptualizations of psychiatric disorders.
 

Sixth, the possibility of one General Psychopathology factor should be tested. This issue has arisen from the observation that disorders are positively correlated not just at the disorder level but substantially so at the spectrum level as well; for example, the correlation between the Externalizing and Internalizing spectra is -.5, and the correlation between the Internalizing and Thought Disorder spectra has been estimated at -.6 (Wright et al., 2013). Given high correlations at the spectrum level, Lahey et al. (2012) suggested the intriguing possibility that in addition to propensities to specific forms of psychopathology (e.g., Internalizing vs. Externalizing), there may be one underlying factor that summarizes individuals' propensity to develop any and all forms of common psychopathologies. They used confirmatory factor models to test a hierarchical bifactor model that derives a general factor from the correlation matrix between different mental disorders and found that depression, anxiety, substance use, and conduct/antisocial disorders all loaded strongly on a single factor, in addition to specific Internalizing and Externalizing spectra (Lahey et al. did not include symptoms of psychosis in their work).
 

A useful way to think about the meaning of such a general factor in psychopathology is by analogy in relation to cognitive abilities. These abilities are dissociable into separate abilities, such as verbal skills, visuospatial skills, working memory, or processing speed. Nonetheless, the general factor in intelligence (called the g factor) summarizes the observation that individuals who do well on one type of cognitive test tend to do well on all other types of cognitive tests (Decry, 2001; Jensen, 1998; Spearman, 1904). Although specific factors account for variation in each test, the g factor accounts for the positive correlation among all test scores, suggesting that all cognitive functions, to some extent, are influenced by common etiology. Just as there is a general factor of cognitive ability, it is possible that there also is a general factor of psychopathology.
Given the aforementioned new findings and insights, we used data from a comprehensive prospective longitudinal study of mental disorders; during the past 20 years, we repeatedly assessed symptoms of 11 kinds of common adult mental disorders in a representative birth cohort, from ages 18 to 38 years. The research reported here had four aims. First, we tested alternative models of the structure of psychopathology using data that take into account information about the dimensionality, persistence, co-occurrence, and sequential comorbidity of mental disorders, including psychosis. Second, we evaluated the validity of the structure of psychopathology by testing associations between the factors obtained and independent information about the study members' personality functioning and life impairment. Third, we tested the family histories and developmental histories associated with each of the factors representing the structure of psychopathology. Fourth, we tested the hypothesis that individual differences in severe and impairing psychopathology are associated with compromised brain integrity from early life.
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