Baghel Prakash Prognosis Scoring System - Conceptual framework and preliminary psychometric validation

Abstract

BackgroundThe assessment of prognosis in a patient using a rigorous methodology is documented in old Ayurveda texts. But in present times, practitioners employ varied clinical assessment methods, which results in low inter-observer agreement. ObjectivesThis study proposes a conceptual framework for developing a prognosis scoring system, which we refer to as the “Baghel Prakash prognosis scoring system” (BPPSS), and presents its preliminary psychometric validation. Materials and methodsClassics of Ayurveda were extensively reviewed for item generation. Thirty-nine items were pooled initially. The Content Validity Index for Items (I-CVI), Scale-level Content Validity Index (S-CVI), and Content Validity Ratio (CVR) were calculated. The final framework contained 30 items. The scoring system was pilot-tested in a sample of 30 patients with various disease conditions. The reliability checks were done to evaluate internal consistency. Inter-item correlations, item-total correlations, and Cronbach's alpha (if an item is deleted) were used to conduct item analysis for the instrument. ResultsThe framework developed includes a set of early clinical warning signs and a prognosis scoring system of 30 items with a provision for clinical adjustment of scores for selected items. Internal consistency of the scoring system during the initial psychometric validation revealed a value of .761 for Cronbach's alpha (based on standardized items), and item analysis revealed that most of the items had acceptable correlation coefficients between .3 and .7. ConclusionBased on this preliminary validation study, we found that this prognosis framework, based on the principles of Ayurveda, may be used in varied clinical situations. The preliminary psychometric validation experiments yielded satisfactory results. The framework also has potential in clinical research, such as selecting patients with similar prognostic scores for comparability in case and control groups of clinical trials. This tool can be utilized as a reliable outcome measure after conducting enough validation studies.