Factors Affecting Fine Dexterity: A Structural Equation Modeling Approach

Abstract

Fine dexterity is one of the most fundamental parts of human factors and ergonomics. The aim of this study was to investigate factors affecting fine dexterity. Gender, age, hand length, grip strength, hand skin temperature, room temperature, and room humidity were analyzed simultaneously to predict fine dexterity by utilizing Structural Equation Modeling (SEM). The results showed that hand skin temperature was the most predicting factor for fine dexterity followed by gender, age, and hand length. Female was found to have better fine dexterity and participants with smaller hand size were also found to have better fine dexterity. In addition, grip strength, room temperature, and room humidity were found not significant predictors for fine dexterity. Interestingly, participants with older age were found had better fine dexterity. The causal relationship derived from SEM could be very significant theoretical foundations which would be beneficial for human factors engineer, hand therapist, and even medical doctors.