The Florida Shock Anxiety Scale (FSAS) for patients with implantable cardioverter defibrillators: testing factor structure, reliability, and validity of a previously established measure.

BACKGROUND: The implantable cardioverter defibrillator (ICD) reduces mortality in patients at risk for life-threatening arrhythmias via high energy shock. The Florida Shock Anxiety Scale (FSAS) was developed to measure ICD patient shock-related anxiety. Initial psychometric evaluation revealed good reliability and validity. The purpose of this study was to examine the psychometrics of the FSAS in a large US sample of ICD patients. METHODS: Participants were recruited via e-mail and the survey was completed online. Ultimately, 443 ICD patients (359 male and 421 White) completed the 10-item FSAS. RESULTS: Means for FSAS were comparable to previously published data (M = 15.18, SD = 6.5). Interitem reliability was good (Cronbach's α= 0.89). The FSAS was negatively correlated with single-item measures of emotional well-being (r =-0.378, P < 0.01), sense of security (r =-0.365, P < 0.01), perceived general health (r =-0.185, P < 0.01), and quality of life (r =-0.216, P < .01), demonstrating discriminant validity. Convergent validity was supported through significant correlations with number of shocks (r = 0.464, P < 0.01) and reported disruptiveness of shock (r = 0.484, P < 0.01). Confirmatory factor analysis revealed that a single (second-order) factor model (χ(2) [34] = 75.34, P < 0.05, comparative fit index = 0.98, root mean-square error of approximation = 0.05) had the best fit. CONCLUSIONS: Shock anxiety as a construct can be measured in a reliable and valid method by the FSAS. These nationally representative data suggest that a single score for shock anxiety is an easy to use and appropriate method of assessment.

The longitudinal relationship of personality traits and disorders.

Personality disorders are presumed to be stable because of underlying stable and maladaptive personality traits, but while previous research has demonstrated a link between personality traits and personality disorders cross-sectionally, personality disorders and personality traits have not been linked longitudinally. This study explores the extent to which relevant personality traits are stable in individuals diagnosed with 4 personality disorders (schizotypal, borderline, avoidant, and obsessive-compulsive personality disorders) and examines the assumption that these personality disorders are stable by virtue of stable personality traits. This assumption was tested via the estimation of a series of latent longitudinal models that evaluated whether changes in relevant personality traits lead to subsequent changes in personality disorders. In addition to offering large consistency estimates for personality traits and personality disorders, the results demonstrate significant cross-lagged relationships between trait change and later disorder change for 3 of the 4 personality disorders studied.

Testing latent longitudinal models of social ties and depression among the elderly: a comparison of distribution-free and maximum likelihood estimates with nonnormal data.

Using a latent-variable modeling approach, relationships between social ties and depression were studied in a sample of 201 older adults. Both positive and negative ties were related to concurrent depression, whereas only negative ties predicted future depression. Nonnormally distributed scores were observed for several variables, and results based on maximum likelihood (ML), which assumes multivariate normality, were compared with those obtained using Browne's (1982, 1984) arbitrary distribution function (ADF) estimator for nonnormal variables. Inappropriate use of ML with nonnormal data yielded model chi-square values that were too large and standard errors that were too small. ML also failed to detect the over-time effect of negative ties on depression. The results suggest that the negative functions of social networks may causally influence depression and illustrate the need to test distributional assumptions when estimating latent-variable models.

Longitudinal effects of hope on depression and anxiety: a latent variable analysis.

This study tested the prospective effects of hope on depression and anxiety using a longitudinal design. A sample of 522 college students completed self-report measures of hope, depression, and anxiety at three time points, with 1-month delays between administrations. Structural equation modeling was employed to test two cross-lagged panel models of the reciprocal effects of the Agency and Pathways components of hope on depression and anxiety. Results indicated statistically significant negative effects for the Agency component of hope on later depression but no unique effect of the Pathways component of hope on depression. Likewise, Agency showed a statistically significant negative effect on later anxiety, but again Pathways had no significant influence on anxiety. In both cases, neither depression nor anxiety demonstrated any longitudinal effects on either the Agency or Pathways components of hope. Implications of these findings are discussed, along with potential directions for future research.