Allison H Oakes1, Vincent S Garmo2, Lee R Bone3,4, Daniel R Longo5, Jodi B Segal2,3, John F P Bridges2,4. 1. Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, 624 North Broadway, Hampton House 663, Baltimore, MD, 21205, USA. aoakes2@jhu.edu. 2. Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, 624 North Broadway, Hampton House 663, Baltimore, MD, 21205, USA. 3. Department of Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA. 4. Department of Health Behavior and Society, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA. 5. Department of Family Medicine and Population Health, Virginia Commonwealth University, Richmond, VA, USA.
Abstract
OBJECTIVE: Self-management of type 2 diabetes mellitus is crucial to controlling the disease and preventing harm. Multiple factors have been identified in the literature as potential barriers and facilitators to self-management, but the magnitude and directionality of these factors are seldom studied. We sought to develop and test an instrument to identify and quantify the barriers and facilitators to self-management of type 2 diabetes. METHODS: A community-centered approach was used to design, implement, and interpret the results of a stated-preference study. All activities were guided by a diverse stakeholder board. Based on previously reported development work, a novel survey instrument consisting of 13 potential barriers and facilitators was pretested and piloted in our local community. Participants were asked to discuss, rate, and rank each factor. A simple self-explicated method was used to quantify the data and Z scores were used for hypothesis testing. RESULTS: In total, 25 patients with self-reported type 2 diabetes (64% female; 92% minorities) participated in the pretest and pilot. Time commitments (Z = -3.72), lack of active support groups (Z = -3.39) and other resources in the local community (Z = -2.96), and language/culture (Z = -2.69) were identified as barriers to self-management. Access to healthy food (Z = +5.68), personal understanding (Z = +4.81), and communication with healthcare providers (Z = +4.62) were identified as facilitators. CONCLUSION: We demonstrate that factors impacting self-management can be quantified and categorized as barriers and facilitators. While further refinement to some factors and investigation into alternative prioritization methods is necessary, our stakeholder board endorsed moving this to a large nationally representative study to see how these factors vary across different people.
OBJECTIVE: Self-management of type 2 diabetes mellitus is crucial to controlling the disease and preventing harm. Multiple factors have been identified in the literature as potential barriers and facilitators to self-management, but the magnitude and directionality of these factors are seldom studied. We sought to develop and test an instrument to identify and quantify the barriers and facilitators to self-management of type 2 diabetes. METHODS: A community-centered approach was used to design, implement, and interpret the results of a stated-preference study. All activities were guided by a diverse stakeholder board. Based on previously reported development work, a novel survey instrument consisting of 13 potential barriers and facilitators was pretested and piloted in our local community. Participants were asked to discuss, rate, and rank each factor. A simple self-explicated method was used to quantify the data and Z scores were used for hypothesis testing. RESULTS: In total, 25 patients with self-reported type 2 diabetes (64% female; 92% minorities) participated in the pretest and pilot. Time commitments (Z = -3.72), lack of active support groups (Z = -3.39) and other resources in the local community (Z = -2.96), and language/culture (Z = -2.69) were identified as barriers to self-management. Access to healthy food (Z = +5.68), personal understanding (Z = +4.81), and communication with healthcare providers (Z = +4.62) were identified as facilitators. CONCLUSION: We demonstrate that factors impacting self-management can be quantified and categorized as barriers and facilitators. While further refinement to some factors and investigation into alternative prioritization methods is necessary, our stakeholder board endorsed moving this to a large nationally representative study to see how these factors vary across different people.
Authors: Nneka C Onwudiwe; C Daniel Mullins; Reed A Winston; Faida T Shaya; Francoise G Pradel; Aurelia Laird; Elijah Saunders Journal: Ethn Dis Date: 2011 Impact factor: 1.847
Authors: Tanjala S Purnell; Thomas J Lynch; Lee Bone; Jodi B Segal; Crystal Evans; Daniel R Longo; John F P Bridges Journal: Patient Date: 2016-08 Impact factor: 3.883
Authors: Amber E Johnson; L Ebony Boulware; Cheryl A M Anderson; Tatpong Chit-ua-aree; Kimberly Kahan; LaPricia Lewis Boyér; Yang Liu; Deidra C Crews Journal: BMC Nephrol Date: 2014-12-06 Impact factor: 2.388
Authors: Melissa B Gilkey; Mo Zhou; Annie-Laurie McRee; Melanie L Kornides; John F P Bridges Journal: Cancer Epidemiol Biomarkers Prev Date: 2018-06-14 Impact factor: 4.254
Authors: Ilene L Hollin; Jonathan Paskett; Anne L R Schuster; Norah L Crossnohere; John F P Bridges Journal: Pharmacoeconomics Date: 2022-07-15 Impact factor: 4.558
Authors: Kristin L Rising; Mackenzie Kemp; Patricia Davidson; Judd E Hollander; Serge Jabbour; Eric Jutkowitz; Benjamin E Leiby; Cheryl Marco; Ian McElwee; Geoffrey Mills; Laura Pizzi; Rhea E Powell; Anna Marie Chang Journal: Contemp Clin Trials Date: 2021-07-24 Impact factor: 2.261