Jennifer Kawi1. 1. Department of Physiological Nursing, School of Nursing, University of Nevada, Las Vegas. Electronic address: jennifer.kawi@unlv.edu.
Abstract
AIMS: (a) Identify variables that predict self-management (SM) of chronic low back pain (CLBP), and (b) evaluate differences in these variables between participants in specialty pain centers (SPCs) and primary care clinics (PCCs). BACKGROUND: Chronic low back pain is highly prevalent in various healthcare settings. Self-management strategies are recommended in pain care guidelines to help address CLBP. However, the evidence of SM effectiveness in CLBP remains unclear. Self-management may be effective for only certain patients. Hence, identifying the predictors to SM of CLBP is essential to help recognize the best responders to SM programs. METHOD: Secondary analysis was conducted on data collected from two CLBP primary research studies in SPCs (N=110) and PCCs (N=120). General linear modeling was utilized for the combined sample of 230 participants and for each practice setting. RESULTS: Overall, in SPCs and PCCs combined, five variables were found to be predictors of SM: age, SM support, education, overall health, and helpfulness of pain management. In SPCs, SM support, support received from other than healthcare providers, religion or spirituality, and overall health were identified as significant predictors to SM. In PCCs, both SM support and overall health were also significant predictors. In addition, those with higher income scored better in SM. CONCLUSIONS: Findings provide essential information to healthcare providers in intervening appropriately toward engaging CLBP patients in SM. Other strategies need to be identified for those who do not respond effectively to SM strategies. Published by Elsevier Inc.
AIMS: (a) Identify variables that predict self-management (SM) of chronic low back pain (CLBP), and (b) evaluate differences in these variables between participants in specialty pain centers (SPCs) and primary care clinics (PCCs). BACKGROUND: Chronic low back pain is highly prevalent in various healthcare settings. Self-management strategies are recommended in pain care guidelines to help address CLBP. However, the evidence of SM effectiveness in CLBP remains unclear. Self-management may be effective for only certain patients. Hence, identifying the predictors to SM of CLBP is essential to help recognize the best responders to SM programs. METHOD: Secondary analysis was conducted on data collected from two CLBP primary research studies in SPCs (N=110) and PCCs (N=120). General linear modeling was utilized for the combined sample of 230 participants and for each practice setting. RESULTS: Overall, in SPCs and PCCs combined, five variables were found to be predictors of SM: age, SM support, education, overall health, and helpfulness of pain management. In SPCs, SM support, support received from other than healthcare providers, religion or spirituality, and overall health were identified as significant predictors to SM. In PCCs, both SM support and overall health were also significant predictors. In addition, those with higher income scored better in SM. CONCLUSIONS: Findings provide essential information to healthcare providers in intervening appropriately toward engaging CLBP patients in SM. Other strategies need to be identified for those who do not respond effectively to SM strategies. Published by Elsevier Inc.
Entities:
Keywords:
Chronic low back pain; Predictors; Self-management
Authors: Tessa M Napoles; Nancy J Burke; Janet K Shim; Elizabeth Davis; David Moskowitz; Irene H Yen Journal: J Urban Health Date: 2017-12 Impact factor: 3.671