Development of Predictive Regression Model for Perceived Hair Breakage in Indian Consumers

    March 2019 in “ International Journal of Cosmetic Science ”
    Vaibhav Kaushik, Pratiksha Nihul, Sudhakar Mhaskar
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    TLDR The model predicts hair breakage based on key hair properties and helps product developers.
    The study developed a predictive regression model for consumer-perceived hair breakage using data from 50 Indian women aged 20-40. It considered hair strand parameters (curvature, stiffness, tensile strength), hair matrix parameters (smoothness, detangling, frizz, volume), and biological factors (age, hair density). A second-order, non-linear multi-regression equation with five predictors showed a reasonable correlation (R² = 0.76) between predicted and observed hair breakage. Key influencing factors included hair surface lubrication, extensional strength, and hair density. The model aids product developers in understanding and addressing physical parameters affecting hair breakage and can be adapted for broader populations.
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