SAT0558 IDENTIFYING HEATH LITERACY PROFILES OF RA AND SPA PATIENTS USING THE HEALTH LITERACY QUESTIONNAIRE
Authors: Mark Bakker, Polina Putrik, Jany Rademakers, Mart van de Laar, Harald Vonkeman, Marc Kok, Hanneke Voorneveld, Sofia Ramiro, Maarten de Wit, Richard Osborne, Roy Batterham, Rachelle Buchbinder, Annelies Boonen
Journal: Annals of the Rheumatic Diseases (2019)

<h3>Background</h3> Delivery of rheumatological care is suggested to be compromised by patient health literacy. Prevalence of problematic health literacy in the Netherlands is estimated to be as high as 36%. <i>"Health literacy represents the cognitive and social skills which determine the motivation and ability of individuals to gain access to, understand and use information in ways which promote and maintain good health"</i> (Nutbeam, 1998). A deeper understanding of diverse health literacy profiles of patients attending rheumatology clinics could facilitate development of interventions tailored to patients' needs, in order to improve health outcomes and reduce inequities. <h3>Objectives</h3> To identify health literacy strengths and weaknesses among patients with Spondyloarthritis (SpA) and Rheumatoid Arthritis (RA) attending a rheumatology clinic, and identify typical 'health literacy profiles' based on these strengths and weaknesses. <h3>Methods</h3> Consecutive RA and SpA patients attending the outpatient clinic at Maastricht UMC+, the Netherlands, were invited to participate. Health literacy was assessed using the Health Literacy Questionnaire (HLQ), which includes nine dimensions (Figure 1). Socio-demographics and health-related characteristics were also collected. Hierarchical cluster analysis following Ward's method identified clusters based on HLQ scale scores. This method groups subjects into a predefined number of clusters, based on smallest differences to the mean of all scales, creating minimal variance within each cluster, and maximum variance between clusters. Three researchers jointly examined twenty cluster solutions for meaningfulness by interpreting HLQ scales and patient characteristics. Meaningful clusters are translated into health literacy profiles using HLQ patterns and demographic data. A patient representative confirmed the identified profiles. <h3>Results</h3> In total, 133 patients with RA and 106 with SpA completed the questionnaire. Of these, 61% (n=146) were female, mean age was 61.6 (±13.3), 27% (n=65) lived alone, 11% (n=26) did not speak Dutch at home, 28% (n=68) were employed, and 22% and 50% had received low and medium education, respectively. Figure 1 displays identified health literacy profiles and scale scores, with greener values representing strengths and red scores representing weaknesses. Overall, the pattern indicates RA and SpA patients have similar profiles, but some represent a clear majority of SpA or RA patients and could be considered disease-specific. For example, cluster 10 includes patients who typically feel comfortable in their relationship with their doctor (scales 1 and 6), and are rather confident in managing their health and getting the information they need (scale 3 and 7). However, they struggle in understanding health information (scale 9), and lack the social support needed to make health decisions and maintain good health (scale 4). This profile appeared restricted to RA patients. <h3>Conclusion</h3> This study identified potential typical health literacy profiles in patients with inflammatory arthritis in our clinic. Profiles reflected distinctive strengths and weaknesses on the nine health literacy dimensions. Some profiles appeared to be condition-specific, which warrants further investigation. Identified profiles will feed into co-design workshops with patients, professionals and other stakeholders, in order to develop interventions to tailor the care to patients' needs. <h3>References</h3> [1] Nutbeam D. (1998). Health promotion glossary. Health Promotion International, 13, 349–364. <h3>Disclosure of Interests</h3> Mark Bakker: None declared, Polina Putrik: None declared, Jany Rademakers: None declared, Mart van de Laar Grant/research support from: AbbVie, Eli Lilly, Janssen-Cilag, Merck Inc, Pfizer Inc, Sanofi Genzyme, Speakers bureau: Eli Lilly, Pfizer Inc, Harald Vonkeman: None declared, Marc Kok: None declared, Hanneke Voorneveld: None declared, Sofia Ramiro Grant/research support from: MSD, Consultant for: AbbVie, Lilly, MSD, Novartis, Pfizer, Sanofi, Speakers bureau: AbbVie, Lilly, MSD, Novartis, Pfizer, Sanofi, Maarten de Wit: None declared, Richard Osborne: None declared, Roy Batterham: None declared, Rachelle Buchbinder: None declared, Annelies Boonen: None declared