Variability in depression prevalence in early rheumatoid arthritis: a comparison of the CES-D and HAD-D Scales

<p>Abstract</p> <p>Background</p> <p>Depression is common in rheumatoid arthritis (RA), however reported prevalence varies considerably. Two frequently used instruments to identify depression are the Center for Epidemiological Studies Depression (CES-D) scale, and the Hospital Anxiety and Depression Scale (HADS). The objectives of this study were to test if the CES-D and HADS-D (a) satisfy current modern psychometric standards for unidimensional measurement in an early RA sample; (b) measure the same construct (i.e. depression); and (c) identify similar levels of depression.</p> <p>Methods</p> <p>Data from the two scales completed by patients with early RA were fitted to the Rasch measurement model to show that (a) each scale satisfies the criteria of fit to the model, including strict unidimensionality; (b) that the scales can be co-calibrated onto a single underlying continuum of depression and to (c) examine the location of the cut points on the underlying continuum as indication of the prevalence of depression.</p> <p>Results</p> <p>Ninety-two patients with early RA (62% female; mean age = 56.3, SD = 13.7) gave 141 sets of paired CES-D and HAD-D data. Fit of the data from the CES-D was found to be poor, and the scale had to be reduced to 13 items to satisfy Rasch measurement criteria whereas the HADS-D met model expectations from the outset. The 20 items combined (CES-D13 and HADS-D) satisfied Rasch model expectations. The CES-D gave a much higher prevalence of depression than the HADS-D.</p> <p>Conclusion</p> <p>The CES-D in its present form is unsuitable for use in patients with early RA, and needs to be reduced to a 13-item scale. The HADS-D is valid for early RA and the two scales measure the same underlying construct but their cut points lead to different estimates of the level of depression. Revised cut points on the CES-D13 provide comparative prevalence rates.</p

The new landscape of medication adherence improvement: where population health science meets precision medicine

Leah L Zullig,1,2 Dan V Blalock,1,3 Samantha Dougherty,4 Rochelle Henderson,5 Carolyn C Ha,4 Megan M Oakes,2 Hayden B Bosworth1&ndash;3,6 1Durham Center for Health Services Research in Primary Care, Durham Veterans Affairs Health Care System, Durham, NC, USA; 2Department of Population Health Sciences, Duke University, Durham, NC, USA; 3Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA; 4Pharmaceutical Research and Manufacturers of America, Washington, DC, USA; 5Express Scripts Holding Company, St Louis, MO, USA; 6School of Nursing, Duke University, Durham, NC, USA Abstract: Despite the known health and economic benefits of medications, nonadherence remains a significant, yet entirely preventable public health burden. Over decades, there have been numerous research studies evaluating health interventions and policy efforts aimed at improving adherence, yet no universal or consistently high impact solutions have been identified. At present, new challenges and opportunities in policy and the movement toward value-based care should foster an environment that appreciates adherence as a mechanism to improve health outcomes and control costs (eg, fewer hospitalizations, reduced health care utilization). Our objective was to provide a commentary on recent changes in the landscape of research and health policy directed toward improving adherence and an actionable agenda to achieve system level savings and improved health by harnessing the benefits of medications. Specifically, we address the complementary perspectives of precision medicine and population health management; integrating data sources to develop innovative measurement of adherence and target adherence interventions; and behavioral economics to determine appropriate incentives. Keywords: adherence, policy, precision medicine, population healt