Comparison of artificial intelligence generated visuals with visual analog scale for pain assessment.
| Title: | Comparison of artificial intelligence generated visuals with visual analog scale for pain assessment. |
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| Authors: | Turan EI; Department of Anesthesiology, Istanbul Health Science University Kanuni Sultan Süleyman Education and Training Hospital, Istanbul, Türkiye - enginihsan@hotmail.com.; Baydemir AE; Department of Anesthesiology, Basaksehir Cam ve Sakura City Hospital, Istanbul, Türkiye.; Turan ZP; Department of Anesthesiology, Sisli Hamidiye Etfal Hospital, Istanbul, Türkiye.; Top G; Nursing Department, Istanbul Health Science University Kanuni Sultan Süleyman Education and Training Hospital, Istanbul, Türkiye.; Şahin AS; Department of Anesthesiology, Istanbul Health Science University Kanuni Sultan Süleyman Education and Training Hospital, Istanbul, Türkiye. |
| Source: | Minerva anestesiologica [Minerva Anestesiol] 2025 Dec; Vol. 91 (12), pp. 1163-1170. Date of Electronic Publication: 2025 Oct 15. |
| Publication Type: | Journal Article; Comparative Study |
| Language: | English |
| Journal Info: | Publisher: [Edizioni Minerva Medica] Country of Publication: Italy NLM ID: 0375272 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1827-1596 (Electronic) Linking ISSN: 03759393 NLM ISO Abbreviation: Minerva Anestesiol Subsets: MEDLINE |
| Imprint Name(s): | Original Publication: Torino, [Edizioni Minerva Medica] |
| MeSH Terms: | Pain Measurement*/methods ; Postoperative Pain*/diagnosis ; Artificial Intelligence* ; Visual Analog Scale*; Humans ; Female ; Male ; Prospective Studies ; Middle Aged ; Adult ; Aged ; Young Adult |
| Abstract: | Background: Traditional pain assessment tools such as the Visual Analog Scale (VAS) rely heavily on patients' cognitive ability to quantify pain, which may not effectively capture the complexity of the pain experience. This study investigates the use of artificial intelligence (AI)-generated visuals as an alternative method for postoperative pain assessment.; Methods: This prospective, single-center study enrolled 400 postoperative patients aged 18 years and older. Patients first evaluated their pain using VAS and then selected from five AI-generated images depicting various pain intensities. After both assessments, participants completed a survey comparing the two methods in terms of clarity, ease of use, and perceived usefulness.; Results: Image-based assessment was preferred by 73.5% of participants, while 25.5% favored VAS (P=0.001). Paired t-tests showed that image-based assessment scored significantly higher for ease of interpretation (66.49±25.17 vs. 36.23±28.21), clarity (67.59±25.36 vs. 38.10±29.40), and usefulness (67.59±25.62 vs. 37.79±29.38), all with P |
| Entry Date(s): | Date Created: 20251015 Date Completed: 20260116 Latest Revision: 20260116 |
| Update Code: | 20260130 |
| DOI: | 10.23736/S0375-9393.25.19249-3 |
| PMID: | 41091584 |
| Database: | MEDLINE |
Journal Article; Comparative Study