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Test of a Factor Mixture-Based Taxonic-Dimensional Model of Anxiety Sensitivity and Panic Attack Vulnerability among University and Clinical Samples in Mexico City

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Abstract

The aim of the present study was to evaluate a factor mixture-based taxonic-dimensional model of anxiety sensitivity (AS) (Bernstein et al. Behavior Therapy 41:515-521, 2010), as measured by the ASI-3 (Taylor et al. Psychological Assessment 19:176-188, 2007), in regard to panic attacks, anxiety symptoms, and behavioral impairment among a university sample (N = 150, n females  = 107, M age = 21.3 years, SD = 4.3) and a clinical sample (N = 150, n females  = 102, M age = 39.0 years, SD = 12.0) from Mexico City, Mexico. Findings demonstrated cross-national support for the conceptual and operational utility of the AS taxonic-dimensional hypothesis (Bernstein et al. Journal of Anxiety Disorders 20:1-22, 2007b). Specifically, (1) the FMM-based AS taxon class base rate was significantly greater among the clinical relative to the university sample; (2) risk for panic attacks was significantly greater among the AS taxon class relative to the AS normative class; and (3) continuous individual differences in AS physical and psychological concerns, within the AS taxon class, were associated with level of risk for panic attacks, as well as panic attack severity and anxiety symptom levels. Similar AS taxonic-dimensional effects were observed in relation to degree of behavioral impairment across domains of functioning. The study results are discussed with respect to their implications for better understanding the nature of AS-related cognitive vulnerability for panic and related anxiety psychopathology.

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Notes

  1. FMM has a number of advantages relative to CCK taxometric methods and other latent mixture modeling techniques (Bauer and Curran 2004; Muthén 2008). Unlike other more commonly employed data analytic strategies such as CCK taxometrics, K-means clustering, latent class and latent profile analyses, and factor analysis, FMM facilitates the concurrent modeling of various models that incorporate latent class (categorical) structure and within-class continuity. Thus, FMM is not limited to testing: (1) whether a latent variable is either a dichotomous categorical (taxonic) or continuous (i.e., CCK taxometrics) variable, (2) the relative fit of various continuous models (i.e., factor analysis) assuming a single latent homogeneous population, or (3) relative fit of various categorical models that lack within-class continuity due to assumption of local independence (i.e., K-means clustering, latent class/profile analysis). Rather, FMM permits arguably more construct valid and flexible latent structural modeling of various possible categorical and continuous structures simultaneously. Furthermore, and unlike CCK taxometrics, FMM offers a model-based approach in which latent structural models are compared and contrasted in terms of multiple, well-established, objective fit indices. In addition, unlike CCK taxometrics, and similar to other model-based mixture techniques, FMM imposes no limit on the number of possible latent classes that may underlie a construct’s putative population heterogeneity or latent class structure. Finally, because FMM incorporates mixture modeling and factor analytic techniques, it is rooted in extensive and well-established quantitative theory and methods. Relatedly, unlike CCK taxometrics in which procedures may be applied and their results interpreted in a variety of (unstandardized) ways (e.g., Ruscio et al. 2006), FMM is applied and interpreted in a highly standardized manner (e.g., Lubke and Muthén 2005). Consequently, unlike CCK taxometric research, application and interpretation of FMM is more likely to yield reliable and valid latent structural findings that consequently may be more replicable across studies and between independent research groups.

  2. We initially planned an additional test in which AS taxonic membership was associated with significant differences in anxiety symptoms in addition to panic. These effects are indeed significant and large in effect size. However, in light of the very low rates of panic and anxiety psychopathology among the normative class and the very high rates of these problems in the AS taxon – additional tests along these similar variables (i.e., panic symptom severity, anxiety symptoms, and phobic anxiety symptoms) between AS taxa are de facto significantly different and inflate family-wise alpha further, yet do not add substantively to the study findings. Notably, these between-taxonic group effects were also observed when conducted among the student and clinical samples separately.

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Authors and Affiliations

  1. Department of Psychology, University of Haifa, Mount Carmel, Haifa, 31905, Israel

    Amit Bernstein

  2. Universidad Nacional Autónoma de México, Mexico City, Mexico

    Samuel Jurado Cárdenas

  3. Psiquiatria Ramón de la Fuente Muñiz, Mexico City, Mexico

    Patricia Edith Campos Coy

  4. The University of Vermont, Burlington, VT, USA

    Michael J. Zvolensky

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  1. Amit Bernstein
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  2. Samuel Jurado Cárdenas
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  3. Patricia Edith Campos Coy
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  4. Michael J. Zvolensky
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Correspondence to Amit Bernstein.

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Dr. Bernstein recognizes the funding support from the Israeli Council for Higher Education Yigal Alon Fellowship, the European Union FP-7 Marie Curie Fellowship International Reintegration Grant, the National Institutes of Health Clinical LRP, and the Rothschild-Caesarea Foundation’s Returning Scientists Project at the University of Haifa.

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Bernstein, A., Cárdenas, S.J., Coy, P.E.C. et al. Test of a Factor Mixture-Based Taxonic-Dimensional Model of Anxiety Sensitivity and Panic Attack Vulnerability among University and Clinical Samples in Mexico City. J Psychopathol Behav Assess 33, 491–500 (2011). https://doi.org/10.1007/s10862-011-9235-8

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