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NIH HEAL Pain Management Effectiveness Research Network (ERN) Funding Opportunity Announcement (FOA) Applicant Webinar

Date: December 17, 2018 - 12:00 p.m. ET to 2:00 p.m. ET

Location: Webinar

Event Description

Join an applicant webinar about the “HEAL Initiative: Pain Management Effectiveness Research Network: Clinical Trial Planning and Implementation Cooperative Agreement (UG3/UH3 Clinical Trial Required)” – RFA-NS-19-021.

The purpose of the funding opportunity announcement (FOA) is to support research that will test the comparative effectiveness of existing therapies or effectiveness of existing or novel approaches for prevention and management of pain while reducing risk of addiction. Effectiveness research is defined as the conduct and synthesis of research comparing the benefits and harms of different interventions and strategies to prevent, treat and monitor pain conditions in “real world” settings. The overall goal is to inform clinicians about the effectiveness of interventions or management strategies to reduce opioid use that will improve functional outcomes and reduce pain across the continuum of acute to chronic pain associated with many types of diseases or conditions or pain presenting as a disease itself.

The NCCIH is interested in supporting comparative effectiveness trials of mind and body approaches that have already demonstrated efficacy for specific pain conditions, such as low back pain, fibromyalgia, osteoarthritis and headache. Types of mind and body approaches to study include, but are not limited to, passive body-based approaches (e.g., spinal manipulation, mobilization, massage, acupuncture), mind-based approaches (e.g., meditation, mindfulness techniques), active movement-based approaches (e.g., yoga, tai chi), or an integrative approach that involves more than one intervention (e.g., Mindfulness Based Stress Reduction). NCCIH is particularly interested in applications utilizing innovative clinical trial designs such as sequential, multiple assignment, randomized trials (SMARTs) designed to determine predictors of treatment response, treatment options at decision points, possible tailoring variables, or a sequence of treatment decision rules.