Rethinking Pain Assessment: Subjective Scales, Biomarkers, and Multimodal Integration

Pain assessment is fundamental in pain medicine, anesthesiology, perioperative care, and clinical trials, yet it remains difficult to standardize across diseases, populations, and care settings. This review organizes pain assessment into four interrelated layers: subjective experience, behavioral and functional proxies, mechanistic biosignals, and multimodal integration. Pain characteristics guide many clinical decisions, but they must be interpreted alongside diagnosis, imaging, laboratory findings, treatment context, and regulatory expectations for reliable and interpretable trial endpoints. Patient-reported scales remain central when feasible because they directly capture the experienced dimension of pain; however, in neonates, critically ill patients, and individuals with severe cognitive or communication impairment, behavioral and functional proxies may become the practical baseline rather than merely supplementary measures. Recent advances in observational scales, facial-expression analysis, sleep and activity monitoring, wearable sensing, electroencephalography, neuroimaging, biofluids, autonomic physiology, and artificial intelligence provide complementary information for phenotyping, monitoring, prediction, and treatment evaluation. These tools should not be treated as interchangeable measures of the same construct or as simple replacements for self-report. A task-oriented layered framework may help clarify what each indicator can and cannot answer, while emphasizing feasibility, reproducibility, effect size, external validation, interpretability, and clinical context.