Validation of Web-Based Star Cancellation and Line Bisection Tests in Hemiplegic Stroke

Overview

The goal of this observational study is to evaluate the clinical usability and diagnostic performance of newly developed web-based Star Cancellation and Line Bisection tests in assessing visuospatial neglect in hemiplegic stroke patients. It will also compare these digital tests with conventional paper-and-pencil assessments. The main questions it aims to answer are: Can the web-based Star Cancellation and Line Bisection tests accurately distinguish between stroke patients with and without visuospatial neglect? Do digital test parameters (such as completion time, search speed, and search patterns) provide additional clinical information beyond conventional test scores? Researchers will compare the results of the web-based tests with standard paper-and-pencil tests to evaluate their diagnostic accuracy and clinical validity. Participants will: Complete conventional paper-and-pencil Star Cancellation and Line Bisection tests Perform web-based (digital) versions of the same tests using a tablet and stylus Undergo routine clinical and cognitive assessments as part of standard care Provide demographic and clinical information

This study is designed as a cross-sectional, comparative, diagnostic accuracy and methodological validation study to evaluate newly developed web-based (browser-based) Star Cancellation Test (SCT) and Line Bisection Test (LBT) for the assessment of visuospatial neglect in hemiplegic stroke patients. Visuospatial neglect is a common neuropsychological condition following stroke, particularly after right hemisphere lesions, and is associated with significant functional impairment. In clinical practice, neglect is typically assessed using paper-and-pencil tests such as cancellation tasks and line bisection tests. While these methods are widely used, they rely on manual scoring and provide limited information about the underlying search process and performance dynamics. The digital tests developed in this study are designed to preserve the core structure and spatial characteristics of conventional assessments while enabling automated scoring and recording of additional performance metrics. These include process-based parameters such as completion time, search speed, search path characteristics, and ineffective or off-target responses. The system operates on a web-based platform without requiring software installation and is accessible through standard consumer devices, aiming to improve standardization, accessibility, and scalability in clinical settings. Participants will be recruited from patients admitted to a physical medicine and rehabilitation clinic and will be classified into three groups based on independent clinical assessment: (1) stroke patients with visuospatial neglect, (2) stroke patients without visuospatial neglect, and (3) age- and sex-matched healthy controls without neurological disease. The presence of visuospatial neglect will be determined using routine clinical reference standards, including established paper-and-pencil neuropsychological tests and behavioral assessment scales. Digital test results will not be used in diagnostic classification to avoid incorporation bias. All participants will complete both conventional paper-and-pencil and web-based versions of the Star Cancellation Test and Line Bisection Test under standardized conditions in a quiet clinical environment. To minimize potential order effects such as fatigue or learning, the sequence of test administration will be counterbalanced across participants. Digital assessments will be performed using a tablet device and stylus pen to ensure consistency in motor and spatial interaction. The primary objective of the study is to evaluate the diagnostic performance of the digital tests in distinguishing between patients with and without visuospatial neglect. Secondary objectives include examining the additional clinical value of process-based digital metrics and assessing the agreement between conventional and digital test outcomes. Statistical analyses will be conducted to assess diagnostic accuracy using receiver operating characteristic (ROC) curve analysis, including estimation of area under the curve (AUC), sensitivity, and specificity. Multivariate modeling approaches may be applied to explore the contribution of multiple digital parameters to diagnostic classification. Descriptive and correlational analyses will be used to evaluate relationships between digital performance measures and clinical variables. Data will be collected and stored in a secure and anonymized format. Automated data capture within the digital platform will reduce manual entry errors and improve data completeness. All analyses will be performed using standard statistical software. This study aims to provide a clinically applicable, accessible, and standardized digital alternative to conventional visuospatial neglect assessment methods, while also contributing novel process-based performance measures to the field.