Year: 2026
Type: preprint
Abstract: Objective Temperature readings are routinely stratified by race and ethnicity, though significant group differences may reflect physiology, instrument noise, or categorization rather than biology. This study tests whether these categories partition facial infrared thermography measurements beyond individual variation and baseline device noise. Approach A secondary analysis of thermography data ( n = 951 adults) compares inner-canthus maximum ( T CEmax ) and full-face maximum ( T max ) temperatures across five administrative categories via one-way analysis of variance (ANOVA), mixed-effects modeling, Bland–Altman analysis against oral reference, and Monte Carlo sensitivity analysis. Main results ANOVA returns significant group differences ( p < 0.001; η 2 = 0.04 for T CEmax , 0.03 for T max ), but the total spread (0.2 °C to 0.3 °C) is comparable to device accuracy and within-subject variability. Individual variation accounts for 95% of T CEmax variance, and adding simulated Gaussian noise to participant-level temperatures ( σ = 0.10– 0.30 °C) preserves the complete group-mean rank order in as few as 37.5% of iterations. Significance Testing whether a group difference survives perturbation at the scale of instrument accuracy offers a check against treating significance alone as evidence of physiology. Here, observed group differences are small relative to measurement variability, and their physiological interpretation remains uncertain, with implications for clinical tools that treat administrative categories as biologically meaningful.
Source: medRxiv
Institutions: Yale University, Indiana University Bloomington
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W7223087934