Abstract
The State-Trait Anxiety Inventory (STAI), composed of two 20-item subscales (STAI-state and STAI-trait), has been increasingly used to assess anxiety symptoms in patients with Parkinson's disease (PD). However, the clinimetric attributes of the STAI under the statistical framework of the item-response theory (IRT) have not been fully elucidated within this population to date. We performed an IRT-based Rasch analysis of the STAI outcomes of patients with de novo PD from the Parkinson's Progression Markers Initiative database. The unidimensionality, Rasch model fit, scale targeting, separation reliability, differential item functioning, and response category utility of the STAI were statistically evaluated. A total of 326 (209 males, 117 females) patients without cognitive dysfunction were enrolled in our study. The original versions of the STAI-state and STAI-trait had acceptable separation reliability but lacked appropriate response category functioning, exhibited scale off-targeting, and several items demonstrated poor fit to the Rasch model. The response categories were reduced from four to three, and the rescored three-point TASI-trait demonstrated a marked improvement in clinimetric properties without a significant impact on unidimensionality and separation reliability. The rescored three-point version of the STAI-state required the additional removal of four misfitting items in order to improve the Rasch model fit. To our knowledge, this is the first study to assess the measurement properties based on the IRT of the STAI in patients with PD. Our Rasch analysis identified the components requiring possible amendments in order to improve the clinimetric attributes of the STAI.
Highlights
Anxiety is a prevalent non-motor symptom that affects 12–57% of patients with Parkinson’s disease (PD) [1,2,3]
The current findings are in line with previous classical test theory (CTT) studies in the PD population reporting that the State-Trait Anxiety Inventory (STAI) is significantly correlated with the Hospital Anxiety and Depression Scale-Anxiety subscale (HADS-A), Hamilton anxiety rating scale (HARS), and Geriatric Anxiety Inventory (GAI) [17, 18]
The person-item distribution maps indicated that item difficulties of both STAI subscales were more highly distributed than the level of anxiety in the study patients, which indicated the inability of the questions to capture low level of anxiety and that the questions were off-targeted in PD [6, 9]
Summary
Anxiety is a prevalent non-motor symptom that affects 12–57% of patients with Parkinson’s disease (PD) [1,2,3]. The structural evaluation of anxiety is crucial for the effective management of PD; the importance of the reliability and validity of the clinical rating scale used to assess the anxiety symptoms in patients with PD has been highlighted [3,4,5]. The classical test theory (CTT) is a popular statistical framework for evaluation of the reliability and validity of questionnaires, patient-reported outcomes, and rating scales in health-care studies [6,7,8]. Shortcomings of the CTT include dependency between the clinimetric properties of the rating scale and the patients’ responses, an ordinal level of measurement rather than interval, and a lack of statistical assessment for polytomous response category function [8,9,10]. The Rasch analysis, which is a widely used one-parameter IRT model approach, has previously been successfully utilized to validate several anxiety rating scales among patients with PD, including the Hospital Anxiety and Depression Scale-Anxiety subscale (HADS-A), Hamilton anxiety rating scale (HARS), and Beck Anxiety Inventory (BAI) [5, 14]
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