Journal article
Pilot study of an internet-based pain coping skills training program for patients with systemic Lupus Erythematosus
Kelli D Allen, Tyler Beauchamp, Christine Rini, Francis J Keefe, Kim L Bennell, Rebecca J Cleveland, Kimberlea Grimm, Katie Huffman, David G Hu, Andres Santana, Shruti Saxena Beem, Julie Walker, Saira Z Sheikh
BMC RHEUMATOLOGY | SPRINGERNATURE | Published : 2021
Abstract
BACKGROUND: Patients with Systemic Lupus Erythematosus (SLE) often experience pain and other symptoms that negatively impact quality of life. Interventions that enhance the use of behavioral and cognitive coping strategies may lead to improved outcomes among patients with SLE. Pain coping skills training (PCST) programs have been shown to improve outcomes among patients with other rheumatic conditions, but there have been no trials of PCST among patients with SLE. This study was a preliminary assessment of the feasibility and efficacy of painTRAINER, an automated, internet-based PCST program, among patients with SLE. METHODS: Participants (n = 60) with SLE from one health care system were ra..
View full abstractGrants
Awarded by National Health and Medical Research Council Investigator Grant
Awarded by National Institute of Arthritis and Musculoskeletal and Skin Diseases Core Center for Clinical Research at the University of North Carolina, Chapel Hill
Awarded by VA Health Services Research and Development Research Career Scientist Award
Awarded by Center of Innovation to Accelerate Discovery and Practice Transformation (ADAPT) at the Durham VA Health Care System
Awarded by NIH National Center for Advancing Translational Sciences (NCATS)
Funding Acknowledgements
This study was supported by pilot funds from the Fund for Excellence in Lupus & Sjogren's at the UNC Thurston Arthritis Research Center. The funders did not have a role in the analysis of data or interpretation of results. Kim Bennell is supported by a National Health and Medical Research Council Investigator Grant (#1174431). Kelli Allen and Rebecca Cleveland receive support from the National Institute of Arthritis and Musculoskeletal and Skin Diseases Core Center for Clinical Research at the University of North Carolina, Chapel Hill (P30AR072580). KDA receives support from a VA Health Services Research and Development Research Career Scientist Award (19-332) and the Center of Innovation to Accelerate Discovery and Practice Transformation (ADAPT) (CIN 13-410) at the Durham VA Health Care System. Data Informatics (CDW-H and REDCap) is supported by he NIH National Center for Advancing Translational Sciences (NCATS) (#UL1TR002489 and #UL1TR001111). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.