Development of the Building Efficacy for Successful Tapering (BEST) Program

摘要 超过1亿美国人患有慢性疼痛。慢性阿片类药物(COT)在治疗疼痛方面的应用 阿片类药物滥用、滥用、与其他药物危险相互作用的报告急剧增加， 服药过量，然后死亡。随着人们对COT令人担忧的影响的加剧，监管部门采取了一些措施 也有所增加，包括在医疗监督下逐渐减少阿片类药物。缩减可能会让许多患者望而却步 缺乏成功驾驭这一过程的自我效能感和疼痛管理技能。根据 自我效能感是指相信一个人能够成功地采取必要的行动 在特定情况下实现预期结果(例如，逐步缩减)。拟议的第一期SBIR项目将 包括初步开发和试点测试成功缩减的在线建筑功效 (最佳)计划。最佳方案是疼痛自我管理原则的具体实际应用 以缩减进程为目标。BEST旨在通过训练患者来提高对逐渐减少的自我效能 系统地抽样和测试各种基于证据的非阿片类疼痛管理策略，以便 制定一系列经过个人审查的技术。患者将学习以证据为基础的策略(疼痛 减压剂“)源自疼痛自我管理的认知-行为、动机和人际关系模型， 包括情绪聚焦、行为技巧、认知技巧和注意力技巧。计划参与者将确定 并系统地测试和跟踪他们从这些类别中定制的“止痛药”清单。A报道 功能将帮助患者可视化进展，洞察他们最有益的策略，并建立 基于表现的自我效能感。此外，随着患者将数据输入最佳程序，随着时间的推移， 系统将能够使用这些数据提供定制建议。如果被发现有效，最好的 该计划将通过帮助患者自信地从 使用阿片类药物，避免误用/滥用的陷阱，并提高替代治疗的可接受性。 第一阶段项目将包括1)内容开发，2)网页设计和软件开发，3) 形成性评估/可用性测试和修订(N=10名接受医疗监督的阿片类药物治疗的患者 缩减)，以及4)先导性随机对照试验(N=60名接受阿片类药物缩减的患者 分配到最佳计划或常规护理)。RCT将提供1)影响大小的初步估计 与程序相关的疼痛自我效能、强度、干扰和阿片类药物滥用自我报告的变化，以及 2)程序可接受性的证据。成功的结果将为第二阶段奠定基础，该阶段将 涉及添加多个计划增强功能，包括移动版本、临床医生门户以进行监控 患者进度，以及其他跟踪功能。在第二阶段将进行一次全面的随机对照试验，以研究 在较长的随访期内，在大样本中对更广泛的结果进行有效性评估。

ABSTRACT Over 100 million Americans suffer from chronic pain. The use of chronic opioid therapy (COT) for pain has increased dramatically, as have reports of opioid misuse, abuse, dangerous interactions with other drugs, overdose, and death. As concerns over the alarming effects of COT have risen, regulatory efforts have increased as well, including medically supervised opioid tapering. Tapering can be daunting to many patients who lack the self-efficacy and pain management skills to successfully navigate the process. According to Bandura, self-efficacy refers to the belief that one can successfully perform the necessary actions to achieve a desired outcome in a given situation (e.g., tapering). The proposed Phase I SBIR project will include the preliminary development and pilot testing of the online Building Efficacy for Successful Tapering (BEST) program. The BEST Program is a practical application of pain self-management principles specifically targeting the tapering process. BEST is designed to enhance self-efficacy for tapering by training the patient to systematically sample and test a variety of evidence-based non-opioid pain management strategies in order to develop a repertoire of personally vetted techniques. Patients will learn evidence-based strategies (“pain reducers”) derived from cognitive-behavioral, motivational, and interpersonal models of pain self-management, including emotion-focused, behavioral, cognitive, and attentional techniques. Program participants will identify and systematically test and track their custom list of “pain reducers” from these categories. A reporting function will help patients to visualize progress, gain insight into their most beneficial strategies, and build performance-based self-efficacy. Moreover, as the patient enters data into the BEST program, over time the system will be capable of using those data to offer custom recommendations. If found effective, the BEST Program will fill a significant gap in chronic pain treatment by helping patients to confidently transition from the use of opioids, avoid the pitfalls of misuse/abuse, and heighten the acceptability of alternative treatments. The Phase I project will include 1) content development, 2) web design and software development, 3) formative evaluation/usability testing and revision (N=10 patients undergoing medically supervised opioid tapering), and 4) a pilot randomized controlled trial (N=60 patients undergoing opioid tapering randomly assigned to the BEST Program or to Usual Care). The RCT will provide 1) preliminary estimates of effect sizes for program-related changes in pain self-efficacy, intensity, interference, and self-report of opioid misuse, and 2) evidence of program acceptability. Successful results would lay the groundwork for Phase II, which would involve the addition of several Program enhancements, including a mobile version, a clinician portal to monitor patient progress, and additional tracking features. A full scale RCT would be conducted in Phase II to examine efficacy for a broader range of outcomes in a large sample over an extended follow-up period.