Vadathya, Anil KumarGarza, TatyanaAlam, UzairHo, AlexMusaad, Salma M. A.Beltran, AliciaMoreno, Jennette P.Baranowski, TomHaidar, NimahHughes, Sheryl O.Mendoza, Jason A.Veeraraghavan, AshokYoung, JosephSano, AkaneO’Connor, Teresia M.2025-01-092025-01-092024Vadathya, A. K., Garza, T., Alam, U., Ho, A., Musaad, S. M. A., Beltran, A., Moreno, J. P., Baranowski, T., Haidar, N., Hughes, S. O., Mendoza, J. A., Veeraraghavan, A., Young, J., Sano, A., & O’Connor, T. M. (2024). Validation studies of the FLASH-TV system to passively measure children’s TV viewing. Scientific Reports, 14(1), 29805. https://doi.org/10.1038/s41598-024-81136-0https://hdl.handle.net/1911/118149TV viewing is associated with health risks, but existing measures of TV viewing are imprecise due to relying on self-report. We developed the Family Level Assessment of Screen use in the Home (FLASH)-TV, a machine learning pipeline with state-of-the-art computer vision methods to measure children’s TV viewing. In three studies, lab pilot (n = 10), lab validation (n = 30), and home validation (n = 20), we tested the validity of FLASH-TV 3.0 in task-based protocols which included video observations of children for 60 min. To establish a gold-standard to compare FLASH-TV output, the videos were labeled by trained staff at 5-second epochs for whenever the child watched TV. For the combined sample with valid data (n = 59), FLASH-TV 3.0 provided a mean 85% (SD 8%) accuracy, 80% (SD 17%) sensitivity, 86% (SD 8%) specificity, and 0.71 (SD 0.15) kappa, compared to gold-standard. The mean intra-class correlation (ICC) of child’s TV viewing durations of FLASH-TV 3.0 to gold-standard was 0.86. Overall, FLASH-TV 3.0 correlated well with the gold standard across a diverse sample of children, but with higher variability among Black children than others. FLASH-TV provides a tool to estimate children’s TV viewing and increase the precision of research on TV viewing’s impact on children’s health.engExcept where otherwise noted, this work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives (CC BY-NC-ND) license. Permission to reuse, publish, or reproduce the work beyond the terms of the license or beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.Journal articleTelevisionGaze estimationScreen mediaMachine learningFace detections41598-024-81136-0https://doi.org/10.1038/s41598-024-81136-0