Trends and Techniques: A Statistical Review of Hair Care Product Evaluation Research

    Maheshvari Patel, Nayan Patel, Rutuja Patil, S. S. Shrivastava
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    Studysummary This review systematically analyzed 22 clinical trials on hair care, finding that while most studies employed appropriate statistical methods, significant inconsistencies in reporting test assumptions and effect sizes may hinder reproducibility, highlighting a need for better standardization and transparency in these research practices. Our plain-language summary of this paper — not a Tressless recommendation.
    This review analyzes the statistical methods used in 22 clinical trials on hair care products from 2020 to 2025, highlighting the importance of appropriate and transparent statistical analysis for validating study outcomes. Common techniques included t-tests, Wilcoxon signed-rank, Mann-Whitney U tests, and more complex models like ANOVA and ANCOVA. Despite generally appropriate methods, inconsistencies in reporting assumptions, effect sizes, and statistical justifications were noted, potentially affecting reproducibility and interpretability. The review calls for better standardization and transparency in statistical reporting to enhance the quality and reliability of hair care research.
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