Slade T, Watson D. The structure of common DSM-IV and ICD-10 mental disorders in the Australian general population. Psychol Med 36: 1593-1600

School of Psychiatry, University of New South Wales at St Vincent's Hospital, Darlinghurst, NSW, Australia.
Psychological Medicine (Impact Factor: 5.94). 12/2006; 36(11):1593-600. DOI: 10.1017/S0033291706008452
Source: PubMed


Patterns of co-occurrence among the common mental disorders may provide information about underlying dimensions of psychopathology. The aim of the current study was to determine which of four models best fits the pattern of co-occurrence between 10 common DSM-IV and 11 common ICD-10 mental disorders.
Data were from the Australian National Survey of Mental Health and Well-Being (NSMHWB), a large-scale community epidemiological survey of mental disorders. Participants consisted of a random population-based sample of 10641 community volunteers, representing a response rate of 78%. DSM-IV and ICD-10 mental disorder diagnoses were obtained using the Composite International Diagnostic Interview (CIDI), version 2.0. Confirmatory factor analysis (CFA) was used to assess the relative fit of competing models.
A hierarchical three-factor variation of a two-factor model demonstrated the best fit to the correlations among the mental disorders. This model included a distress factor with high loadings on major depression, dysthymia, generalized anxiety disorder (GAD), post-traumatic stress disorder (PTSD) and neurasthenia (ICD-10 only); a fear factor with high loadings on social phobia, panic disorder, agoraphobia and obsessive-compulsive disorder (OCD); and an externalizing factor with high loadings on alcohol and drug dependence. The distress and fear factors were best conceptualized as subfactors of a higher order internalizing factor.
A greater focus on underlying dimensions of distress, fear and externalization is warranted.

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    • "The Diagnostic and Statistical Manual of Mental Disorders—Fifth Edition (DSM-5) and the International Classification of Diseases—Eleventh Edition Beta Draft (ICD-11) now incorporate dimensional spectra of psychopathology (e.g., the internalizing spectrum and the externalizing spectrum ) to account for the body of research that documents the systematic patterns of co-occurrence between larger groups of disorders . The internalizing–externalizing framework has been researched extensively; it interprets comorbidity between disorders as an indicator of stable, underlying core psychological processes (Krueger, 1999), and has been expanded to include many types of psychopathology, including depressive and anxiety disorders , posttraumatic stress disorder, obsessive–compulsive disorder , bipolar disorder, eating disorders, schizophrenia, and personality disorders (Kotov et al., 2011; Krueger, 2005; Krueger, Caspi, Moffit, & Silva, 1998; Markon, Krueger, & Watson, 2005; Slade & Watson, 2006; Watson, 2005). Sexual dysfunctions also have strong and multifaceted relationships with depressive and anxiety disorders that are consistent with a shared underlying factor of internalizing psychopathology (see Laurent & Simons, 2009 for a review), and preliminary research has shown that a dimensional model that includes sexual problems in the internalizing spectrum fits better than a categorical model that separates the disorders (Forbes, Baillie, & Schniering , 2014a; Forbes & Schniering, 2013). "
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    ABSTRACT: Sexual dysfunctions have not been included in research on the broad structure of psychopathology to date, despite their high prevalence and impact on quality of life. Preliminary research has shown that they may fit well in an internalizing spectrum, alongside depressive and anxiety disorders. This study compared dimensional and categorical models of the relationships between depression, anxiety, and sexual problems with "hybrid" models (i.e., factor mixture analyses), which combine dimensional and categorical components simultaneously. Participants (n = 1000) were selectively recruited to include a range of symptom levels, and completed a series of self-report measures online. A hybrid model that combined dimensional and categorical components fit best for men and women. Taken together, the results are consistent with a nosology that explicitly recognizes the relationships between the diagnostic chapters of depressive and anxiety disorders and sexual dysfunctions, but still maintains discrete diagnoses, which is compatible with the structure of the DSM-5 and upcoming ICD-11.
    Archives of Sexual Behavior 11/2015; DOI:10.1007/s10508-015-0613-2 · 3.53 Impact Factor
    • "Furthermore, although the two samples were demographically unique and applied distinct measures of smoking which limited direct comparisons, including both samples allowed for the ability to see whether the results replicate across the different samples, which decreases the likelihood that the findings are dependent on the specific sample or measures being used. We hypothesized that a 2-factor internalizing (happiness, anhedonia, depression, anxiety, anxious arousal) and externalizing (physical aggression, ADHD symptoms, alcohol use) model would provide the best fit for the data, based on the high consistency of support found for the 2-factor model (Cosgrove et al. 2011; Krueger and Markon 2006; Krueger 1999; Slade and Watson 2006). Furthermore, because the psychological symptom scales included in the model are significantly associated with disorders that loaded onto the internalizing and externalizing factors in these prior studies (i.e., happiness (low), anhedonia, and depressive symptoms with depressive disorders, Brown et al. 1998; Gehricke and Shapiro 2000, anxious symptoms and anxious arousal with anxiety disorders, Brown et al. 1998; Mineka et al. 1998, physical aggression with antisocial disorder, Fossati et al. 2007, ADHD symptoms with ADHD, Kessler et al. 2005a, and alcohol use disorder symptoms with alcohol use disorders , Babor et al. 2001), we speculated that these symtpom scales would demonstrate a similar 2-factor structure. "
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    ABSTRACT: Shared latent dimensions may account for the co-occurrence of multiple forms of psychological dysfunction. However, this conceptualization has rarely been integrated into the smoking literature, despite high levels of psychological symptoms in smokers. In this study, we used confirmatory factor analysis to compare three models (1-factor, 2-factor [internalizing-externalizing], and 3-factor [low positive affect-negative affect-disinhibition]) of relations among nine measures of affective and behavioral symptoms implicated in smoking spanning depression, anxiety, happiness, anhedonia, ADHD, aggression, and alcohol use disorder symptoms. We then examined associations of scores from each of the manifest scales and the latent factors from the best-fitting model to several smoking characteristics (i.e., experimentation, lifetime established smoking [≥100 cigarettes lifetime], age of smoking onset, cigarettes/day, nicotine dependence, and past nicotine withdrawal). We used two samples: (1) College Students (N =288; mean age =20; 75 % female) and (2) Adult Daily Smokers (N=338; mean age=44; 32 % female). In both samples, the 3-factor model separating latent dimensions of deficient positive affect, negative affect, and disinhibition fit best. In the college students, the disinhibition factor and its respective indicators significantly associated with lifetime smoking. In the daily smokers, low positive and high negative affect factors and their respective indicators positively associated with cigarettes/day and nicotine withdrawal symptom severity. These findings suggest that shared features of psychological symptoms may be parsimonious explanations of how multiple manifestations of psychological dysfunction play a role in smoking. Implications for research and treatment of co-occurring psychological symptoms and smoking are discussed.
    Journal of Psychopathology and Behavioral Assessment 09/2015; 37(3):454-468. DOI:10.1007/s10862-014-9467-5 · 1.55 Impact Factor
    • "GAD and panic disorder have distinct biology (Wilkinson et al. 1998), medical co-morbidities (Davies et al. 2012; Davies & Allgulander, 2013) and differ in the frequency of reports of genetic association with depression (Roy et al. 1995; Kendler, 1996, Kendler et al. 2003, 2007). Factor analyses of cross-sectional data in large populations had suggested that GAD may be more closely associated with depression than is panic disorder (Krueger, 1999; Vollebergh et al. 2001; Slade & Watson, 2006). Although this finding was confirmed in a population of adolescents and young adults (Beesdo-Baum et al. 2009), there remains a controversy over whether this factor structure is robust to addition of other diagnoses and in other age groups (Wittchen et al. 2009). "
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    ABSTRACT: Generalized anxiety disorder (GAD) and panic disorder (PD) differ in their biology and co-morbidities. We hypothesized that GAD but not PD symptoms at the age of 15 years are associated with depression diagnosis at 18 years. Using longitudinal data from the Avon Longitudinal Study of Parents and Children (ALSPAC) birth cohort we examined relationships of GAD and PD symptoms (measured by the Development and Well-Being Assessment) at 15 years with depression at 18 years (by the Clinical Interview Schedule - Revised) using logistic regression. We excluded adolescents already depressed at 15 years and adjusted for social class, maternal education, birth order, gender, alcohol intake and smoking. We repeated these analyses following multiple imputation for missing data. In the sample with complete data (n = 2835), high and moderate GAD symptoms in adolescents not depressed at 15 years were associated with increased risk of depression at 18 years both in unadjusted analyses and adjusting for PD symptoms at 15 years and the above potential confounders. The adjusted odds ratio (OR) for depression at 18 years in adolescents with high relative to low GAD scores was 5.2 [95% confidence interval (CI) 3.0-9.1, overall p < 0.0001]. There were no associations between PD symptoms and depression at 18 years in any model (high relative to low PD scores, adjusted OR = 1.3, 95% CI 0.3-4.8, overall p = 0.737). Missing data imputation strengthened the relationship of GAD symptoms with depression (high relative to low GAD scores, OR = 6.2, 95% CI 3.9-9.9) but those for PD became weaker. Symptoms of GAD but not PD at 15 years are associated with depression at 18 years. Clinicians should be aware that adolescents with GAD symptoms may develop depression.
    Psychological Medicine 08/2015; -1:1-13. DOI:10.1017/S003329171500149X · 5.94 Impact Factor
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