A Comprehensive Profiling System Integrating MBTI and DISC for Personalized Health Training: A Correlational Analysis and Usability Evaluation (Preprint)

This study proposes an integrated approach to developing personalized health behavior change programs by combining personality traits and behavior types. Existing tools, such as Myers-Briggs Type Indicator (MBTI) and Dominance, Influence, Steadiness, and Conscientiousness (DISC), have limitations: MBTI reflects internal tendencies but lacks behavioral insights, while DISC highlights behavior but overlooks deeper personality aspects. To address these gaps, the study integrates MBTI and DISC to create a comprehensive profiling system. The goal of this research is to design a novel profiling system that merges MBTI and DISC for personalized health management. This system aims to link personality traits with behavior patterns to enhance the effectiveness of tailored health behavior change programs. The study involved 3 phases: administering MBTI and DISC tests to 130 participants to analyze correlations, developing an integrated survey for health behavior analysis, and testing its usability with 20 experts for validation. Significant correlations were observed between MBTI and DISC indicators, including a notable negative correlation between Thinking-Feeling (T/F) and Dominance (D), suggesting an inverse relationship between decision-making preferences and assertiveness. Usability testing results indicated high participant satisfaction, with an average SUS (System Usability Scale) score of 86.0. The SUS is a widely used questionnaire for measuring subjective assessments of usability. This score exceeded industry benchmarks for system usability. Expert evaluations further reinforced the system's practical applicability, highlighting its potential to enhance user engagement through personalized behavioral insights. This study presents a combined MBTI and DISC profiling system, offering both theoretical insights and practical tools for health behavior change programs. Future research should validate its effectiveness with larger samples and explore broader applications in various health domains.