Psychometric Properties of the General Decision-Making Style (GDMS-20) Questionnaire in a Lebanese Arab Adult Sample.

BACKGROUND: Decision-making styles reflect stable individual tendencies in approaching choices and have been found to relate to health behaviors, clinical decisions, and psychosocial outcomes. The General Decision-Making Style (GDMS) questionnaire is a widely used instrument that assesses five distinct decision-making styles. This scale has been translated into many languages but not in Arabic, and has demonstrated robust psychometric properties across multiple cultural contexts. To address the absence of a validated tool for assessing general decision-making styles in Arabic-speaking populations, this study aimed to evaluate the validity, reliability and factor structure of the 20-item version of the GDMS questionnaire. METHODS: This cross-sectional study conducted between the months of November and December 2024 included 536 Lebanese Arabic speaking participants. RESULTS: Confirmatory factor analysis results supported the original five factor structure. Internal reliability was satisfactory as evidenced by both McDonald's omega and Cronbach's alpha: Systematic (ω = 0.76/α = 0.76), Intuitive (ω = 0.58/α = 0.58), Dependent (ω = 0.72/α = 0.72), Avoidant (ω = 0.71/α = 0.70) and Spontaneous (ω = 0.67/α = 0.66). Measurement invariance across sex was confirmed, with significant higher mean dependent decision making found in females compared to males whereas higher mean spontaneous decision-making style was found in males compared to females. No significant difference was found between males and females in terms of systematic, intuitive and avoidant decision-making styles. Higher systematic, dependent and intuitive styles were significantly associated with better work engagement and wellbeing. CONCLUSION: This study provides a reliable and valid Arabic version of the 20-item GDMS for assessing different general decision-making styles in Arabic-speaking populations. The scale has potential applications in several targeted applications in healthcare and research.