An Examination of Factor Structure of the Hamilton Anxiety Rating Scale in a Non-Clinical Persian Sample
- 1 Ulster University, Ireland
- 2 American University of Madaba, Jordan
- 3 Hashemite University, Jordan
- 4 Belfast Health and Social Care Trust, Ireland
Abstract
The Hamilton Anxiety Rating Scale is an internationally used assessment tool for anxiety level however its acceptable factor structure remains fluid. The aim of this paper is to examine the psychometric properties and establish normative anxiety prevalence rates with a Persian randomized sample. A cross sectional survey was distributed to a randomised sample of adults (n = 1260) in the Middle East. A two-factor model was deemed the most statistically and theoretically appropriate measurement model. This represented a split between cognitive and physiological symptoms. Overall, 15.2% of respondents reported at least mild anxiety, with 2.3% experiencing severe anxiety. Lower anxiety scores on the scale were reported among males, the married, younger and higher educated people. The Hamilton Anxiety Scale continues to be a useful tool in the measurement of anxiety. The two factor model separates anxiety into two dimensions, cognitive and physiological aspects and both are highly correlated with each other suggesting a single overarching construct of anxiety. The two-factor model may help provide a better understanding of the effectiveness of different therapeutic techniques. The pooled prevalence of ADs in a non-clinical Persian sample was relatively lower than those of some other countries.
DOI: https://doi.org/10.3844/ijrnsp.2019.1.9
Copyright: © 2019 Paul Slater, Brendan Bunting, Felicity Hasson, Ahmed Mohammad Al-Smadi, Omar Salem Gammouh, Ala Ashour and Damian Jordan. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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Keywords
- Anxiety
- Hamilton Anxiety Rating Scale
- Normative Data
- Psychometrics