Web-Based Computational Estimation of Energy Availability for Preliminary RED-S Screening in Athletes

¹ Department of Sport Science, Universitas Negeri Jakarta, Indonesia.
² Universiti Teknologi MARA, Faculty of Sports Science and Recreation, Negeri Sembilan Branch, Seremban Campus, Negeri Sembilan, Malaysia

^* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.

Published online: 2 July 2026

Abstract

Relative Energy Deficiency in Sport (RED-S) is a syndrome caused by prolonged low energy availability that negatively affects athlete health and performance. Early identification remains challenging, particularly in settings with limited access to laboratory assessments and specialised monitoring tools. This study developed the SHEnergy RED-S Smart Website, a browser-based platform integrating dietary monitoring, physical activity assessment via the Global Physical Activity Questionnaire (GPAQ), anthropometric evaluation, and computational estimation of Energy Availability (EA) to support preliminary RED-S risk classification. The platform was evaluated across 128 athletes from multiple sport disciplines. System-generated risk classifications were validated against RED-S CAT scores and nutritionist assessments, achieving a macro-averaged accuracy of 89.8%, sensitivity of 88.5%, and specificity of 93.7%. A System Usability Scale (SUS) score of 81.4 confirmed acceptable usability, with a session completion rate of 94.5%. Overall, 76.6% of users demonstrated EA below the recommended threshold, with 32.0% classified as High Risk. The SHEnergy platform integrates RED-S education, screening, and risk feedback within a single accessible web-based workflow, and may serve as an entry-level screening tool in resource-limited sport settings. Further validation using clinical assessment and expert evaluation is required before broader implementation.