Optimal Cut-Off Points on the Health Anxiety Inventory, Illness Attitude Scales and Whiteley Index to Identify Severe Health Anxiety
2015 (English)In: PLoS ONE, ISSN 1932-6203, Vol. 10, no 4, e0123412- p.Article in journal (Refereed) Published
Background Health anxiety can be viewed as a dimensional phenomenon where severe health anxiety in form of DSM-IV hypochondriasis represents a cut-off where the health anxiety becomes clinically significant. Three of the most reliable and used self-report measures of health anxiety are the Health Anxiety Inventory (HAI), the Illness Attitude Scales (IAS) and the Whiteley Index (WI). Identifying the optimal cut-offs for classification of presence of a diagnosis of severe health anxiety on these measures has several advantages in clinical and research settings. The aim of this study was therefore to investigate the HAI, IAS and WI as proximal diagnostic instruments for severe health anxiety defined as DSM-IV hypochondriasis. Methods We investigated sensitivity, specificity and predictive value on the HAI, IAS and WI using a total of 347 adult participants of whom 158 had a diagnosis of severe health anxiety, 97 had obsessive-compulsive disorder and 92 were healthy non-clinical controls. Diagnostic assessments were conducted using the Anxiety Disorder Interview Schedule. Results Optimal cut-offs for identifying a diagnosis of severe health anxiety was 67 on the HAI, 47 on the IAS, and 5 on the WI. Sensitivity and specificity were high, ranging from 92.6 to 99.4%. Positive and negative predictive values ranged from 91.6 to 99.4% using unadjusted prevalence rates. Conclusions The HAI, IAS and WI have very good properties as diagnostic indicators of severe health anxiety and can be used as cost-efficient proximal estimates of the diagnosis.
Place, publisher, year, edition, pages
Public Library of Science , 2015. Vol. 10, no 4, e0123412- p.
IdentifiersURN: urn:nbn:se:liu:diva-117793DOI: 10.1371/journal.pone.0123412ISI: 000352477800232PubMedID: 25849477OAI: oai:DiVA.org:liu-117793DiVA: diva2:811270
Funding Agencies|Karolinska Insititutet; Stockholm County Council2015-05-112015-05-082015-05-12