The Space of Common Psychiatric Disorders in Adolescents: Comorbidity Structure and Individual Latent Liabilities

Blanco, Carlos; Wall, Melanie M.; He, Jianmei; Krueger, Robert F.; Olfson, Mark; Jin, Chelsea J.; Burstein, Marcy; Merikangas, Kathleen R.

doi:10.1016/j.jaac.2014.10.007

Cited by 73 publications

(63 citation statements)

References 43 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Numerous studies have consistently extracted two higher-order factors, often labeled internalizing and externalizing, based on the pattern of correlations among first-order dimensions expressed as loadings on the higher-order factors in children, adolescents, and adults (Achenbach & Edelbrock, 1978; Blanco et al, 2015; Cosgrove et al, 2011; Kessler, Petukhova, & Zaslavsky, 2011; Lahey, Rathouz, et al, 2008; Quay, 1986; Slade & Watson, 2006). Other studies have supported somewhat different higher-order factors of psychopathology.…”

Section: Correlational Structure Of First-order Dimensions Of Psychopmentioning

confidence: 99%

A hierarchical causal taxonomy of psychopathology across the life span.

Lahey¹,

Krueger²,

Rathouz³

et al. 2017

Psychological Bulletin

Self Cite

382

397

View full text Add to dashboard Cite

We propose a taxonomy of psychopathology based on patterns of shared causal influences identified in a review of multivariate behavior genetic studies that distinguish genetic and environmental influences that are either common to multiple dimensions of psychopathology or unique to each dimension. At the phenotypic level, first-order dimensions are defined by correlations among symptoms; correlations among first-order dimensions similarly define higher-order domains (e.g., internalizing or externalizing psychopathology). We hypothesize that the robust phenotypic correlations among first-order dimensions reflect a hierarchy of increasingly specific etiologic influences. Some nonspecific etiologic factors increase risk for all first-order dimensions of psychopathology to varying degrees through a general factor of psychopathology. Other nonspecific etiologic factors increase risk only for all first-order dimensions within a more specific higher-order domain. Furthermore, each first-order dimension has its own unique causal influences. Genetic and environmental influences common to family members tend to be nonspecific, whereas environmental influences unique to each individual are more dimension-specific. We posit that these causal influences on psychopathology are moderated by sex and developmental processes. This causal taxonomy also provides a novel framework for understanding the heterogeneity of each first-order dimension: Different persons exhibiting similar symptoms may be influenced by different combinations of etiologic influences from each of the three levels of the etiologic hierarchy. Furthermore, we relate the proposed causal taxonomy to transdimensional psychobiological processes, which also impact the heterogeneity of each psychopathology dimension. This causal taxonomy implies the need for changes in strategies for studying the etiology, psychobiology, prevention, and treatment of psychopathology.

show abstract

Section: Correlational Structure Of First-order Dimensions Of Psychopmentioning

confidence: 99%

A hierarchical causal taxonomy of psychopathology across the life span.

Lahey¹,

Krueger²,

Rathouz³

et al. 2017

Psychological Bulletin

Self Cite

382

397

View full text Add to dashboard Cite

show abstract

“…As an alternative, building off the pioneering work by Achenbach and colleagues who demonstrated dimensional factors of latent internalizing and externalizing problems (e.g., Achenbach & Edelbrock, 1978), the field increasingly has examined and found evidence for dimensional structural models to organize psychopathology at a latent level across different tiers (e.g., Blanco et al, 2015; Caspi et al, 2014; Eaton et al, 2013; Kessler, Petukhova, & Zaslavsky, 2011b; Krueger, 1999; Lahey et al, 2004; 2012; 2007; Tackett et al, 2013). …”

Section: Latent Dimensional Structural Models Of Psychopathologymentioning

confidence: 99%

Understanding comorbidity among internalizing problems: Integrating latent structural models of psychopathology and risk mechanisms

et al. 2016

View full text Add to dashboard Cite

It is well known that comorbidity is the rule, not the exception, for categorically defined psychiatric disorders, and this is also the case for internalizing disorders of depression and anxiety. This theoretical review paper addresses the ubiquity of comorbidity among internalizing disorders. Our central thesis is that progress in understanding this co-occurrence can be made by employing latent dimensional structural models that organize both psychopathology as well as vulnerabilities and risk mechanisms and by connecting the multiple levels of risk and psychopathology outcomes together. Different vulnerabilities and risk mechanisms are hypothesized to predict different levels of the structural model of psychopathology. We review the present state of knowledge based on concurrent and developmental sequential comorbidity patterns among common discrete psychiatric disorders in youth, and then we advocate for the use of more recent bifactor dimensional models of psychopathology (e.g., p factor, Caspi et al., 2014) that can help to explain the co-occurrence among internalizing symptoms. In support of this relatively novel conceptual perspective, we review six exemplar vulnerabilities and risk mechanisms, including executive function, information processing biases, cognitive vulnerabilities, positive and negative affectivity aspects of temperament, and autonomic dysregulation, along with the developmental occurrence of stressors in different domains, to show how these vulnerabilities can predict the general latent psychopathology factor, a unique latent internalizing dimension, as well as specific symptom syndrome manifestations.

show abstract

“…Among individuals with SUDs, factors that have been associated with lower rates of SUD treatment include an earlier age of SUD onset, being married, membership in an older cohort, minority racial/ethnic ancestry, and having attained less than a high school education (Alegria et al, 2002; Gee et al, 2007; Grant, 1996; Sue et al, 1991; Sussman et al, 1987; Wang et al, 2005, 2004, 2002). Although adults with SUDs commonly have comorbid of Axis II and other Axis I psychiatric disorders (Armstrong and Costello, 2002; Blanco et al, 2013b, 2015; Havassy et al, 2004; Kessler et al, 1997; Merikangas et al, 1998; Mertens et al, 2003), the effect of psychiatric comorbidity on treatment-seeking for SUD has not been previously examined. Furthermore, despite wide variation in prevalence, severity, and associated adverse consequences (Compton et al, 2007; Hasin et al, 2007), differences in treatment seeking behavior of people with alcohol abuse, alcohol dependence, drug abuse, and drug dependence have not been extensively characterized (Wang et al, 2005).…”

Section: Introductionmentioning

confidence: 99%

Probability and predictors of treatment-seeking for substance use disorders in the U.S

Blanco

Iza

Rodríguez-Fernández

et al. 2015

Drug and Alcohol Dependence

Self Cite

120

View full text Add to dashboard Cite

Background Little is known about to what extent treatment-seeking behavior varies across individuals with alcohol abuse, alcohol dependence, drug abuse, and drug dependence. Methods The sample included respondents from the Wave 2 of the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) who reported a lifetime diagnosis alcohol abuse, alcohol dependence, drug abuse, or drug dependence. Unadjusted and adjusted hazard ratios are presented for time to first treatment contact by sociodemographic characteristics and comorbid psychiatric disorders. Individuals were censored from the analyses if their condition remitted prior to seeking treatment. Results In the first year after disorder onset, rates of treatment-seeking were 13% for drug dependence, 5% for alcohol dependence, 2% for drug abuse, and 1% for alcohol abuse. The lifetime probability of seeking treatment among individuals who did not remit was also highest for drug dependence (90%), followed by drug abuse (60%), alcohol dependence (54%), and alcohol abuse (16%). Having had previous treatment contact for a substance use disorder (SUD) increased the probability of seeking treatment for another SUD. By contrast, an early age of SUD onset, belonging to an older cohort, and a higher level of education decreased the lifetime probability of treatment contact for SUD. The role of comorbid mental disorders was more complex, with some disorders increasing and other decreasing the probability of seeking treatment. Conclusions Given high rates of SUD and their substantial health and economic burden, these patterns suggest the need for innovative approaches to increase treatment access for individuals with SUD.

show abstract

The Space of Common Psychiatric Disorders in Adolescents: Comorbidity Structure and Individual Latent Liabilities

Cited by 73 publications

References 43 publications

A hierarchical causal taxonomy of psychopathology across the life span.

A hierarchical causal taxonomy of psychopathology across the life span.

Understanding comorbidity among internalizing problems: Integrating latent structural models of psychopathology and risk mechanisms

Probability and predictors of treatment-seeking for substance use disorders in the U.S

Contact Info

Product

Resources

About