Is It Possible to Standardize Diagnostic Decision-Making in Yoga Therapy for LBP? A Study Using AHP, BWM, RANCOM, and BCM

The primary objective of this study is to examine whether expert-based Multi-Criteria Decision Analysis (MCDA) methods might be used to support physiotherapists in yoga-based treatment of non-specific Lower Back Pain (LBP). LBP is one of the most common pain syndromes globally, particularly in industrialized and aging populations, and its prevalence continues to increase. This growing challenge highlights the need to develop AI-based systems that can support not only conventional medicine but also physiotherapeutic approaches to treatment. To our knowledge, this is the first study to explore the application of MCDA methods in yoga-based therapy. To fill this gap, we tested four expert-based MCDA methods — Analytic Hierarchy Process (AHP), Best - Worst Method (BWM), Ranking Comparison Method (RANCOM), and Base Criterion Method (BCM) with the support of two highly experienced physiotherapy experts. Despite minor differences, all methods delivered consistent and highly promising results, demonstrating the potential and usefulness of MCDA approaches in yoga-based treatment of LBP. The results lay the groundwork for future development of AI-supported decision-making tools tailored to physiotherapeutic and integrative treatment strategies. This research contributes to the growing body of evidence on the applicability of MCDA in healthcare and highlights its relevance in non-conventional therapeutic contexts.