Employing a three-stage procedure to develop a sizing system for medical gloves.

There is a need for gloves that are designed based on the dimensions of the hand of each society because the proper size is a key factor that affects performance. This study aimed to design and develop a glove-sizing system for Iranian healthcare workers using anthropometric data. This study was conducted on a sample including 540 healthcare workers across Iran classified by ethnicity and gender. Thirty-three dimensions were measured as the anthropometric data. Principal Component Analysis (PCA) and clustering analysis were used to create classifications for glove sizes. The most effective dimensions in defining the hand sizes of Iranian healthcare workers were middle finger length and the handbreadth. The designed six-size system covered 94% of the sample. This system can be used to design suitable gloves for Iranians. The sizes presented can be used to compare size differences in different communities. Practitioner summary: In this study, an attempt was made to design a sizing system with maximum coverage for medical gloves using statistical analysis methods and hand anthropometric dimensions of Iranian healthcare workers. The method of this study can be used in other communities as well for improving sizing systems. Abbreviations : PCA: Principal Component Analysis; GSS: Glove Sizing Systems; TEM: Technical error of measurement; R: Reliability coefficient; KMO: The Kaiser-Meyer-Olkin; PC1: The first principal component; PC2: The second principal component; FCMC: Fuzzy c-means clustering; XS: Very small; S: Small; SM: Medium small; LM: Medium large; L: Large; Xl: Very large.