Search

Cognitive-behavioral models conceptualize health anxiety as a construct that varies in degree along a continuum rather than existing as nonpathological versus pathological classes or taxons. Only two studies have empirically evaluated the latent structure of health anxiety, both using taxometric statistical methods and both supporting its conceptualization as continuous (Ferguson, 2009; Longley et al., 2010). We sought to further evaluate the latent structure of health anxiety using factor mixture modeling (FMM), which involved a combination of exploratory factor analysis (EFA) and mixture modeling that allowed comparison of models comprising one or more latent classes. Health anxiety symptom data were obtained from the Illness Attitude Scales (IAS) administered to 1768 university undergraduate students. Indicators of health anxiety, derived from EFA of IAS item data, included disease worry, disease conviction, health-related safety behaviors, fear of death, somatic focus, interference due to symptoms, and treatment seeking. FMM of these indicators suggested that health anxiety consists of two classes: (a) an "anxious" class comprising 81.4% of the sample and characterized primarily by somatic focus and interference due to symptoms, and (b) a "nonanxious" class comprising 18.6% of the sample with low scores on all indicators. Contrary to current conceptualizations and taxometric findings, the FMM results indicate the latent structure of health anxiety to be taxonic rather than continuous. Implications for the measurement and conceptualization of health anxiety are discussed and future research directions are highlighted., (Copyright © 2011 Elsevier Ltd. All rights reserved.)

Anxiety sensitivity (AS) was initially conceptualized as existing along a continuum; however, emerging evidence from taxometric analyses is mixed as to whether the latent structure of AS is dimensional or taxonic. The purpose of the present study was to further evaluate the latent structure of AS in an effort to clarify the contrasting findings reported in the literature. To do so, we examined the latent structure of AS in two large independent samples unselected with regard to AS level (comprising undergraduate respondents and/or community residents). MAXEIG and MAMBAC analyses were performed with indicator sets drawn from distinct self-report measures of AS within either sample. MAXEIG and MAMBAC, as well as comparison analyses utilizing simulated taxonic and dimensional datasets, yielded converging evidence that AS has a dimensional latent structure. Implications of these finding for the conceptualization and measurement of AS are discussed and future research directions are highlighted., (Copyright © 2010 Elsevier Ltd. All rights reserved.)