{"title":"ChatGPT as a collaborative research assistant in the ICF linking process of the brief version of the Burn Specific Health Scale","authors":"Hatice Gül , Murat Ali Çınar , Kezban Bayramlar","doi":"10.1016/j.burns.2025.107609","DOIUrl":null,"url":null,"abstract":"<div><h3>Introduction</h3><div>Burn injuries profoundly affect multiple aspects of health-related quality of life (HRQoL). The Brief Version of the Burn Specific Health Scale (BSHS-B) is commonly used to assess HRQoL in burn survivors. Linking such tools to the International Classification of Functioning, Disability and Health (ICF) enhances data comparability and standardisation for patients with burn injuries. However, linking process is often complex and time-consuming. Large language models may support linking process and help streamline future linking studies in burn rehabilitation.</div></div><div><h3>Objectives</h3><div>This study evaluated the feasibility of using ChatGPT-4o as a collaborative assistant in the ICF linking process of BSHS-B items.</div></div><div><h3>Methods</h3><div>The study followed the refined ICF linking rules. In the first stage, two physiotherapists independently linked the contents of BSHS-B items to ICF categories. When the two linkers disagreed, a third assigned the item to a category. In the second stage, ChatGPT-4o guided by specialised prompting performed the same task according to linking rules. In the content analysis, Cohen’s Kappa coefficient was computed to evaluate the consistency between expert consensus and ChatGPT-4o-based linking. An agreement on item perspective analyses was also conducted. Frequencies of identified ICF categories across major domains were reported descriptively.</div></div><div><h3>Results</h3><div>The agreement between linkers on ICF category assignment was fair (κ = 0.41, p < .001), while ChatGPT and expert consensus agreement was moderate (κ = 0.55, p < .001). In the perspective analysis, agreement between experts was fair (κ = 0.21, p < .01), whereas ChatGPT demonstrated almost perfect agreement with experts (κ = 0.86, p < .001). A total of 25 ICF codes were identified, mainly in Activity Participation (52.11 %) and Body Functions (40.85 %).</div></div><div><h3>Conclusion</h3><div>ChatGPT demonstrated substantial potential in the ICF linking process as a supportive tool. While not replacing human expertise, ChatGPT may be able to reduce workload and facilitate ICF linking process.</div></div>","PeriodicalId":50717,"journal":{"name":"Burns","volume":"51 7","pages":"Article 107609"},"PeriodicalIF":2.9000,"publicationDate":"2025-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Burns","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0305417925002384","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CRITICAL CARE MEDICINE","Score":null,"Total":0}
引用次数: 0
Abstract
Introduction
Burn injuries profoundly affect multiple aspects of health-related quality of life (HRQoL). The Brief Version of the Burn Specific Health Scale (BSHS-B) is commonly used to assess HRQoL in burn survivors. Linking such tools to the International Classification of Functioning, Disability and Health (ICF) enhances data comparability and standardisation for patients with burn injuries. However, linking process is often complex and time-consuming. Large language models may support linking process and help streamline future linking studies in burn rehabilitation.
Objectives
This study evaluated the feasibility of using ChatGPT-4o as a collaborative assistant in the ICF linking process of BSHS-B items.
Methods
The study followed the refined ICF linking rules. In the first stage, two physiotherapists independently linked the contents of BSHS-B items to ICF categories. When the two linkers disagreed, a third assigned the item to a category. In the second stage, ChatGPT-4o guided by specialised prompting performed the same task according to linking rules. In the content analysis, Cohen’s Kappa coefficient was computed to evaluate the consistency between expert consensus and ChatGPT-4o-based linking. An agreement on item perspective analyses was also conducted. Frequencies of identified ICF categories across major domains were reported descriptively.
Results
The agreement between linkers on ICF category assignment was fair (κ = 0.41, p < .001), while ChatGPT and expert consensus agreement was moderate (κ = 0.55, p < .001). In the perspective analysis, agreement between experts was fair (κ = 0.21, p < .01), whereas ChatGPT demonstrated almost perfect agreement with experts (κ = 0.86, p < .001). A total of 25 ICF codes were identified, mainly in Activity Participation (52.11 %) and Body Functions (40.85 %).
Conclusion
ChatGPT demonstrated substantial potential in the ICF linking process as a supportive tool. While not replacing human expertise, ChatGPT may be able to reduce workload and facilitate ICF linking process.
期刊介绍:
Burns aims to foster the exchange of information among all engaged in preventing and treating the effects of burns. The journal focuses on clinical, scientific and social aspects of these injuries and covers the prevention of the injury, the epidemiology of such injuries and all aspects of treatment including development of new techniques and technologies and verification of existing ones. Regular features include clinical and scientific papers, state of the art reviews and descriptions of burn-care in practice.
Topics covered by Burns include: the effects of smoke on man and animals, their tissues and cells; the responses to and treatment of patients and animals with chemical injuries to the skin; the biological and clinical effects of cold injuries; surgical techniques which are, or may be relevant to the treatment of burned patients during the acute or reconstructive phase following injury; well controlled laboratory studies of the effectiveness of anti-microbial agents on infection and new materials on scarring and healing; inflammatory responses to injury, effectiveness of related agents and other compounds used to modify the physiological and cellular responses to the injury; experimental studies of burns and the outcome of burn wound healing; regenerative medicine concerning the skin.