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Improving the psychometric utility of the hypomania checklist (HCL-32): A Rasch analysis approach

Court, Helen, Forty, Elizabeth, Jones, Lisa, Gordon-Smith, Katherine, Jones, Ian, Craddock, Nicholas John, Smith, Daniel J., Dunajewski, Katherine and Lesley, Aileen 2014. Improving the psychometric utility of the hypomania checklist (HCL-32): A Rasch analysis approach. Journal of affective disorders 152-15 , pp. 448-53. 10.1016/j.jad.2013.10.014

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Abstract

BACKGROUND: The HCL-32 is a widely-used screening questionnaire for hypomania. We aimed to use a Rasch analysis approach to (i) evaluate the measurement properties, principally unidimensionality, of the HCL-32, and (ii) generate a score table to allow researchers to convert raw HCL-32 scores into an interval-level measurement which will be more appropriate for statistical analyses. METHODS: Subjects were part of the Bipolar Disorder Research Network (BDRN) study with DSM-IV bipolar disorder (n=389). Multidimensionality was assessed using the Rasch fit statistics and principle components analysis of the residuals (PCA). Item invariance (differential item functioning, DIF) was tested for gender, bipolar diagnosis and current mental state. Item estimates and reliabilities were calculated. RESULTS: Three items (29, 30, 32) had unacceptable fit to the Rasch unidimensional model. Item 14 displayed significant DIF for gender and items 8 and 17 for current mental state. Item estimates confirmed that not all items measure hypomania equally. LIMITATIONS: This sample was recruited as part of a large ongoing genetic epidemiology study of bipolar disorder and may not be fully representative of the broader clinical population of individuals with bipolar disorder. CONCLUSION: The HCL-32 is unidimensional in practice, but measurements may be further strengthened by the removal of four items. Re-scored linear measurements may be more appropriate for clinical research.

Item Type: Article
Date Type: Publication
Status: Published
Schools: MRC Centre for Neuropsychiatric Genetics and Genomics (CNGG)
Medicine
Subjects: R Medicine > R Medicine (General)
Publisher: Elsevier
ISSN: 0165-0327
Last Modified: 18 Mar 2019 17:46
URI: http://orca.cf.ac.uk/id/eprint/76680

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