Comparison of patient preference for and interpretability of video-based pain-expression scenarios and the numerical rating scale for postoperative pain assessment: a prospective observational study

Authors:
Open Access
Publisher website
Google Scholar
Abstract
Background: Postoperative pain assessment relies primarily on numeric self-report tools, such as the numerical rating scale (NRS); these tools require abstract numerical cognition and may be challenging for some patients in the immediate postoperative period. Thus, in this prospective observational study, we aimed to evaluate a novel video-based pain-expression method in postoperative adults, with the primary objective of assessing patient preference for the video-based pain-expression method compared with that for the NRS.Methods: This prospective single-center observational study was conducted in a post-anesthesia care unit. Adult patients reporting postoperative pain (NRS ≥ 1) were shown five standardized artificial intelligence-generated video scenarios representing increasing pain ranges and asked to select the video best reflecting their pain. Patients also reported their NRS scores. The primary outcome was method preference. Secondary outcomes included exact and ± 1-category agreement, Spearman correlation, and decision-making time.Results: Of 240 enrolled patients, 239 were included in the final analysis. Overall, 133 patients (55.6%; 95% confidence interval [CI] 49.3–61.8) preferred the NRS, whereas 106 patients (44.4%; 95% CI 38.2–50.7) preferred the video-based method. Exact agreement between the video category and NRS was 40.6%, while ± 1-category agreement reached 80.8%. Quadratic weighted kappa demonstrated substantial agreement between the two methods (κ = 0.65). Mean decision time was longer for the video-based method than for NRS (32.87 ± 15.83 vs. 21.04 ± 8.21 s; mean difference 11.83 s, 95% CI 9.92–13.74).Conclusions: Agreement between the NRS and video-based method was strongest at pain extremes. Although NRS is more time-efficient, video-based assessment appears to be a feasible complementary tool that may enhance patient-centered postoperative pain communication.