Calculating Continuous Percentile Scores to Improve Interpretation of Pediatric Eating Assessment Tools

Many pediatric assessment tools rely on limited percentile cut points, such as the 90th and 95th, forcing clinicians into broad risk categories and losing essential precision for tracking change. We propose a simple, robust method to impute continuous percentile scores using a piecewise-linear function. Validation against true percentiles in a longitudinal study of children at risk for pediatric feeding disorder (N = 234) yielded exceptionally strong correlations (r = 0.97-0.99). Although slight overestimation occurred in low-score ranges due to sparse cut points, the rank-ordering of scores was reliably preserved. Continuous percentile scores provide the fine-grained differentiation needed to observe subtle changes in developmental trajectory. As illustrated by a clinical case, this enhances data interpretation and allows for more precise tracking to alert the care team of worsening symptoms and facilitate timely, objective evidence for targeted referral. This reliable method is broadly applicable to many clinical tools, and improves the reporting of longitudinal research.