Protocol for the development of a tool to map systemic sclerosis pain sources, patterns, and management experiences: a Scleroderma Patient-centered Intervention Network patient-researcher partnership

Author:

Dal Santo Tiffany,Golberg Meira,Nassar Elsa-Lynn,Carrier Marie-Eve,Hu Sophie,Kwakkenbos Linda,Bartlett Susan J.,Fox Rina S.,Lee Yvonne C.,Varga John,Benedetti Andrea,Thombs Brett D.ORCID, ,Lapointe McKenzie Jo-Ann,Lawrie-Jones Amanda,Mieszczak Tracy,Petrozza Silvia,Sauve Maureen,Wixson Gayle

Abstract

Abstract Introduction Systemic sclerosis (SSc) is a rare, complex autoimmune rheumatic disease with multiple factors that contribute to pain. People with SSc emphasize the effect pain has on their quality of life, but no studies have systematically examined the frequency and relative importance of different SSc pain sources, patterns of pain from different sources, and pain management experiences. Our objectives are to (1) develop a tool, jointly with researchers, health care providers, and patients, to map sources of pain in SSc, determine patterns of pain from different sources, and understand pain management experiences; and (2) administer the final tool version to participants in the large multinational Scleroderma Patient-centered Intervention Network (SPIN) Cohort. Methods First, we will use validated pain assessment tools as templates to develop an initial version of our pain assessment tool, and we will obtain input from patient advisors to adapt it for SSc. The tool will include questions on pain sources, pain patterns, pain intensity, pain management techniques, and barriers to pain management in SSc. Second, we will conduct nominal group technique sessions with people living with SSc and health care providers who care for people with SSc to further refine the tool. Third, we will conduct individual usability testing sessions with SPIN Cohort participants. Once the tool has been finalized, we will administer it to individuals in the multinational SPIN Cohort, which currently includes over 1,300 active participants from 54 sites in 7 countries. We will perform unsupervised clustering using the KAy-Means for MIxed LArge data (KAMILA) method to identify participant subgroups with similar profiles of pain sources (present or absent) and to evaluate predictors of subgroup membership. We will use latent profile analysis to identify subgroups of participants with similar profiles based on pain intensity scores for each pain source and evaluate predictors. Discussion Once completed, our pain assessment tool will allow our team and other researchers to map sources of pain in SSc and to understand pain management experiences of people living with SSc. This knowledge will provide avenues for studies on the pathophysiology of pain in SSc and studies of interventions to improve pain management.

Funder

Fonds de Recherche du Québec - Santé

National Institutes of Health

Arthritis Society

Canada Research Chairs

Publisher

Springer Science and Business Media LLC

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3