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Abstract：
BACKGROUND: 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.
CONCLUSIONS: 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.
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.
CONCLUSIONS: 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.
摘要：
背景：系统性硬化症（SSc）是一种罕见的，复杂的自身免疫性风湿病有多种因素导致疼痛。SSc患者强调疼痛对他们生活质量的影响，但是没有研究系统地检查了不同SSc疼痛源的频率和相对重要性，不同来源的疼痛模式，和疼痛管理经验。我们的目标是(1)开发一种工具，与研究人员一起，卫生保健提供者,和病人，在SSc中绘制疼痛的来源，确定不同来源的疼痛模式，并了解疼痛管理经验；（2）对大型多国硬皮病患者中心干预网络（SPIN）队列的参与者管理最终工具版本。
方法：首先，我们将使用经过验证的疼痛评估工具作为模板来开发我们的疼痛评估工具的初始版本，我们将从患者顾问那里获得输入，以适应SSc。该工具将包括有关疼痛来源的问题，疼痛模式，疼痛强度，疼痛管理技术，以及SSc疼痛管理的障碍。第二,我们将与SSc患者和照顾SSc患者的医疗保健提供者进行名义小组技术会议，以进一步完善该工具。第三，我们将与SPIN队列参与者进行单独的可用性测试会议。一旦工具定稿，我们将对跨国SPIN队列中的个人进行管理，目前包括来自7个国家54个地点的1300多名活跃参与者。我们将使用MIxedLArge数据的KAy-Means（KAMILA）方法进行无监督聚类，以识别具有相似疼痛源（存在或不存在）的参与者亚组，并评估亚组成员的预测因子。我们将使用潜在的配置文件分析来识别参与者的亚组相似的配置文件基于疼痛强度评分为每个疼痛源和评估预测因素。
结论：完成后，我们的疼痛评估工具将允许我们的团队和其他研究人员在SSc中绘制疼痛来源图,并了解SSc患者的疼痛管理经验.这些知识将为SSc疼痛的病理生理学研究和改善疼痛管理的干预研究提供途径。
方法：首先，我们将使用经过验证的疼痛评估工具作为模板来开发我们的疼痛评估工具的初始版本，我们将从患者顾问那里获得输入，以适应SSc。该工具将包括有关疼痛来源的问题，疼痛模式，疼痛强度，疼痛管理技术，以及SSc疼痛管理的障碍。第二,我们将与SSc患者和照顾SSc患者的医疗保健提供者进行名义小组技术会议，以进一步完善该工具。第三，我们将与SPIN队列参与者进行单独的可用性测试会议。一旦工具定稿，我们将对跨国SPIN队列中的个人进行管理，目前包括来自7个国家54个地点的1300多名活跃参与者。我们将使用MIxedLArge数据的KAy-Means（KAMILA）方法进行无监督聚类，以识别具有相似疼痛源（存在或不存在）的参与者亚组，并评估亚组成员的预测因子。我们将使用潜在的配置文件分析来识别参与者的亚组相似的配置文件基于疼痛强度评分为每个疼痛源和评估预测因素。
结论：完成后，我们的疼痛评估工具将允许我们的团队和其他研究人员在SSc中绘制疼痛来源图,并了解SSc患者的疼痛管理经验.这些知识将为SSc疼痛的病理生理学研究和改善疼痛管理的干预研究提供途径。
