Elsevier

Comprehensive Psychiatry

Volume 72, January 2017, Pages 74-82
Comprehensive Psychiatry

The temporal stability of the bifactor model of comorbidity: An examination of moderated continuity pathways

https://doi.org/10.1016/j.comppsych.2016.09.010Get rights and content

Abstract

Background

Structural models of psychopathology indicate that common mental disorder comorbidity reflects latent transdiagnostic factors. Multiple studies have replicated transdiagnostic internalizing (mood and anxiety disorders) and externalizing (substance use, antisociality-, and impulsivity-related disorders) factors; other studies support distress and fear sub-factors of internalizing. These factors show a high degree of temporal stability. Recently, a bifactor conceptualization of multivariate comorbidity has emerged, positing the existence of an orthogonal general psychopathology factor that saturates all diagnoses in addition to internalizing/distress/fear and externalizing, although no studies have examined the temporal stability of the factors in this competing model over time among adults.

Method

In a large, two-wave nationally representative sample (N = 43,093), we investigated the structure of the bifactor model and examined all potential within- and between-factor stability pathways in a structural equation modeling framework.

Results

In general, within-domain stability (e.g., Wave 1 general factor predicting Wave 2 general factor) was high, while between-domain pathways (e.g., Wave 1 general factor predicting the Wave 2 externalizing factor) did not differ significantly from zero. We then tested possible age and gender moderation of factor stability, finding that the stability for all factors, except fear, significantly differed across demographic sub-groups. However, these differences were not clinically meaningful.

Conclusions

Results indicated that bifactor model factors show varying degrees of temporal stability, with lowest comorbidity continuity over time reflecting distress stability. Findings are discussed with regard to recent evidence that the general factor may, to some extent, represent the negative emotionality captured by internalizing/distress in correlated two- and three-factor solutions.

Section snippets

Participants

This study used diagnostic data from two waves (W1 and W2) of the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC). The NESARC sample is a civilian, non-institutionalized adult population of the United States, weighted to be representative of the age, gender, and race/ethnic distributions from the 2000 Census [for a full description of the sampling frame, see 30]. Participants were first assessed at W1 [N = 43,093; response rate: 81% of eligible participants; fielded

Bifactor model parameterizations at waves 1 and 2

A bifactor model fit the W1 lifetime data well (CFI = 0.995, TLI = 0.992, RMSEA = 0.010), consistent with previous research [12]. We replicated the same model using W2 12-month diagnoses, which also fit well (CFI = 0.997, TLI = 0.994, RMSEA = 0.006). Factor loadings for both models are given in Table 1.

Stability

For all models below, see Table 2 for model fit and comparison and Table 3 for regression coefficients. A model where all W1 factors predicted all W2 factors (model 1A in tables) provided good fit. However,

Discussion

To our knowledge this is the first investigation of the longitudinal stability of the bifactor model of psychopathology, in a large, nationally representative sample of adults (N = 43,093). Using SEM, we tested hypotheses regarding the temporal stability of the bifactor model's latent factors by examining pathways of longitudinal stability, and moderators of these stability pathways. Investigation of all potential pathways of temporal stability showed that stability was highest within-domains,

References (55)

  • T. Slade et al.

    The structure of common DSM-IV and ICD-10 mental disorders in the Australian general population

    Psychol Med

    (2006)
  • W.A.M. Vollebergh et al.

    The structure and stability of common mental disorders: the NEMESIS study

    Arch Gen Psychiatry

    (2001)
  • N.R. Eaton et al.

    The meaning of comorbidity among common mental disorders

  • K.J. Holzinger et al.

    The bi-factor method

    Psychometrika

    (1937)
  • S.P. Reise

    Invited paper: the rediscovery of bifactor measurement models

    Multivar Behav Res

    (2012)
  • B.B. Lahey et al.

    Is there a general factor of prevalent psychopathology during adulthood?

    J Abnorm Psychol

    (2012)
  • N. Carragher et al.

    The structure of adolescent psychopathology: a symptom-level analysis

    Psychol Med

    (2015)
  • B.B. Lahey et al.

    Higher-order genetic and environmental structure of prevalent forms of child and adolescent psychopathology

    Arch Gen Psychiatry

    (2011)
  • E. Pettersson et al.

    The general factor of personality and evaluation

    Eur J Pers

    (2012)
  • C. Sharp et al.

    The structure of personality pathology: both general ('g') and specific ('s') factors?

    J Abnorm Psychol

    (2015)
  • J.L. Tackett et al.

    Common genetic influences on negative emotionality and a general psychopathology factor in childhood and adolescence

    J Abnorm Psychol

    (2013)
  • A. Caspi et al.

    The p factor one general psychopathology factor in the structure of psychiatric disorders?

    Clin Psychol Sci

    (2014)
  • B.B. Lahey et al.

    Criterion validity of the general factor of psychopathology in a prospective study of girls

    J Child Psychol Psychiatry

    (2015)
  • O.M. Laceulle et al.

    The structure of psychopathology in adolescence: replication of a general psychopathology factor in the TRAILS study

    Clin Psychol Sci

    (2015)
  • N.R. Eaton et al.

    The structure and predictive validity of the internalizing disorders

    J Abnorm Psychol

    (2013)
  • N.R. Eaton et al.

    Aging and the structure and long-term stability of the internalizing spectrum of personality and psychopathology

    Psychol Aging

    (2011)
  • R.C. Kessler et al.

    Development of lifetime comorbidity in the World Health Organization world mental health surveys

    Arch Gen Psychiatry

    (2011)
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