Abstract
The NIH Pain Common Data Elements (CDEs) provide a standardized framework for pain research, but their implementation and interpretation present challenges. To review the NIH CDE Program's selected pain domains, provide best practices for implementing required questions, and offer a checklist for appropriate CDE use in clinical trials and secondary data analysis. This work analyzed the ten core pain research domains selected by the NIH CDE Program and discuss their limitations and considerations for use. The manuscript provides an overview of the ten core pain research domains, including pain intensity, interference, physical function, sleep, catastrophizing, depression, anxiety, global impression of change, substance use screening, and quality of life. It offers sample scenarios for implementing required questions and presents a checklist to guide researchers in using pain CDEs effectively for clinical trials and secondary data analysis. Key challenges identified include contextual variability, lack of validation across all pain conditions and populations, and potential misuse or misinterpretation of measures. This work proposes solutions such as supplementary measures, context-specific guidance, comprehensive training programs, and ongoing refinement of the CDE framework. While NIH Pain CDEs are valuable tools for standardizing pain assessment in research, addressing challenges in their implementation and interpretation is crucial for improving the consistency, validity, and interpretability of pain research data, ultimately advancing the field and enhancing patient care.
Published Version (Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.