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Baghel Prakash Prognosis Scoring System - Conceptual framework and preliminary psychometric validation
V Ashwathykutty1, V Rakesh Narayanan1
1Central Council for Research in Ayurvedic Sciences, Jawahar Lal Nehru Bhartiya Chikitsa Avum Homeopathy Anusandhan Bhavan, No.61-65, Institutional Area, Opp. 'D' Block, Janakpuri, New Delhi, 110058, India.
Journal of Ayurveda and Integrative Medicine
|November 20, 2022
Summary
Ayurveda texts offer prognosis assessment methods, but modern practices lack consistency. This study introduces the Baghel Prakash prognosis scoring system (BPPSS), a validated framework for consistent patient prognosis evaluation.
Area of Science:
- Ayurvedic medicine
- Clinical prognosis assessment
- Psychometric validation
Background:
- Traditional Ayurvedic texts describe rigorous prognosis assessment methods.
- Current clinical practices utilize varied assessment techniques, leading to low inter-observer agreement.
Purpose of the Study:
- To propose a conceptual framework for a standardized prognosis scoring system: the Baghel Prakash prognosis scoring system (BPPSS).
- To present the preliminary psychometric validation of the BPPSS.
Main Methods:
- Extensive review of Ayurvedic classics for item generation.
- Calculation of Content Validity Index (I-CVI, S-CVI) and Content Validity Ratio (CVR).
- Pilot testing on 30 patients and reliability analysis using Cronbach's alpha for internal consistency and item analysis.
Main Results:
- Developed a 30-item prognosis scoring system with early clinical warning signs and score adjustment options.
- Preliminary psychometric validation showed a Cronbach's alpha of .761 for internal consistency.
- Item analysis indicated acceptable correlation coefficients for most items, supporting the instrument's validity.
Conclusions:
- The BPPSS framework, rooted in Ayurveda, is suitable for diverse clinical settings.
- Preliminary validation results are satisfactory, indicating the BPPSS's potential as a reliable outcome measure.
- The BPPSS can aid clinical research by enabling patient selection for comparable trial groups.
