Identifying HAM‐A cutoffs for mild, moderate, and severe generalized anxiety disorder
Citations Over TimeTop 10% of 2010 papers
Abstract
The aim of the current study was to identify and evaluate cutoffs for mild, moderate, and severe ranges of Hamilton Anxiety Rating Scale (HAM-A) scores. Data were from a four-week randomized trial of treatment for generalized anxiety disorder. Measures included the HAM-A, SF-36, Hospital Anxiety and Depression Scale (HADS), and Clinical Global Impressions of Severity (CGI-S) scale. HAM-A cutoffs were identified based on literature review, expert panel input, and MANOVA models. The optimal cutoff set was evaluated based on association with clinician CGI-S ratings. The sample included 144 patients (56.3% female; 73.6% white; mean age = 35.7 years; mean baseline HAM-A score = 23.7). The optimal HAM-A score ranges were: mild anxiety = 8-14; moderate = 15-23; severe ≥ 24 (scores ≤ 7 were considered to represent no/minimal anxiety). Analysis of variance (ANOVA) models found statistically significant differences among these groups in the SF-36 and HADS. The HAM-A severity ranges closely corresponded to clinicians' CGI-S ratings. The study represents the first step towards developing severity ranges for the HAM-A. These cutoffs should be used with caution and validated in larger samples. If the proposed cutoffs are accepted for general use, they could make results more meaningful and interpretable for researchers, clinicians, and patients.
Related Papers
- → Recommendations for analysis of repeated‐measures designs: testing and correcting for sphericity and use of manova and mixed model analysis(2017)87 cited
- → The Analysis of Repeated Measures Designs Involving Multiple Dependent Variables(1987)188 cited
- → Relative Merits of MANOVA, Repeated Measures ANOVA, and Univariate ANOVAs for Research Utilizing Multiple Criterion Measures(1974)13 cited
- → Analysis of repeated measures experiments on individuals subjected to different treatments(1988)2 cited
- Repeated Measures Anova: the Wide, the Long and the Long(2007)