A Model of Decision-Making in Rheumatoid Arthritis

Rheumatoid arthritis (RA), a costly prevalent rheumatologic condition, can result in joint damage due to an erosive synovitis (ACR Subcommittee, 2002; Wolfe et aI., 1994). Despite the number of effective medications available to treat RA, only 30% of patients regularly take their prescribed medications. Conflicting results have been reported concerning factors affecting this phenomenon (Tuncay et aI., 2007; Wong & Mulherin, 2007). To further the understanding of medication adherence in RA patients, the purpose of this study is to empirically evaluate a process of decision-making used by RA patients as they decide to take medications for this disease and to determine if medication adherence impacts disease activity. A longitudinal study with repeated measures (N= 100) will be used to determine: 1) if five factors: 1) pain rating; 2) functional status; 3) number of health care providers consulted and treatments used before taking the newly prescribed disease modifying anti-rheumatic drug (DMARD); 4) knowledge about RA and treatments for RA; and 5) trusting patient-health care provider relationship impacts medication adherence; 2) if the number of adverse effects attributed to the newly prescribed DMARD impacts medication adherence in patients with RA; and 3) if RA disease activity impacts medication adherence. In a university clinic setting, RA patients will complete self-report scales, record adverse effects, and provide demographic information. Self-report scales will measure pain, knowledge about RA and treatments for RA, functional status, a trusting patient­ health care provider relationship, self-efficacy, social support, and medication adherence. Electronic medication moni~oring devices will be used to measure adherence, and the Disease Activity Score 28 (Prevoo et aI., 1995) will be used to measure disease activity. Descriptive statistics, one-way analysis of covariance, intra­ class correlation coefficients, and two sample t-tests will be used to analyze the data.