OBJECTIVES:Our objective was to describe the social networks of Black individuals with rheumatic and musculoskeletal conditions and understand the clustering of health-related behaviors to inform future community-based, peer-led interventions. METHODS:We used an adapted Personal Network Survey for Clinical Research (PERSNET) to map the personal social networks of Black individuals with rheumatic conditions in Boston and Chicago. We used egocentric network analyses to quantify network composition, and descriptive statistics and Welch's two-sample t-tests to assess network characteristics and behavioral concordance between participants and their network members. RESULTS:We mapped the social networks of 40 individuals with rheumatic conditions in Boston and Chicago. All participants self-identified as Black, with 6 indicating Hispanic or Latino ethnicity. One participant self-identified as male. Networks had a median size of 10, with 54% of all possible ties present and an average of 5 structurally distinct connections within each network. Boston networks had a larger proportion of kin (71%) compared to those in Chicago (40%). There was greater diversity in sex and education within Boston networks. Chicago networks displayed morelanced strong and weak ties and higher prevalence of health problems within networks. Smoking and drinking behaviors clustered within networks across both sites, which may reflect patterns of behavioral homophily or social influence. CONCLUSIONS:Differences in network density, constraint, and diversity highlight structural and relational patterns that may influence how health behaviors develop. They also reveal network configurations that position individuals to act as bridges, introducing new information and behaviors into communities where medical mistrust and systemic inequities undermine health messaging.
Interstitial lung disease (ILD) is a significant cause of morbidity and mortality in patients with inflammatory rheumatic disorders (IRDs). High-resolution computed tomography (HRCT) is widely considered the gold standard for the noninvasive assessment of ILD; however, its interpretation is constrained by substantial interobserver variability and the need for time-consuming expert evaluation. Computer-based image analysis, including artificial intelligence, has emerged as a promising approach for the automated, objective, and quantitative analysis of HRCT images. This method enables precise volumetric assessment of parenchymal alterations and facilitates pattern classification with unprecedented accuracy and efficiency. This review synthesizes current evidence on computational driven HRCT quantification in IRD-ILD, highlighting available technical approaches, validation strategies, and clinical applications.
OBJECTIVE:Osteoarthritis (OA) is a leading cause of joint pain and people often self-manage their symptoms before seeking support. Community pharmacies are accessible and well-placed to support people with OA using pharmacological and non-pharmacological approaches. Current policy recommends that pharmacies should be integrated into long-term condition management pathways. This study aimed to explore the experiences of people with OA engaging with community pharmacy staff for their joint problems, and their views about an extended community pharmacy role for OA. DESIGN:A multi-method study with surveys of people with OA who were recruited through general practices in two geographical areas of the United Kingdom (UK), followed by qualitative interviews with respondents who consented to further contact. Survey data underwent descriptive statistical analysis, whilst qualitative data were analysed using reflexive thematic analysis, mapped to the Theoretical Domains Framework. RESULTS:In 450 survey responses and 18 interviews, people with OA reported that current community pharmacy OA care focused on advice about medicines and sometimes included self-care advice. There was support for an extended role for OA management in community pharmacy that focused on explaining the joint problem and its treatment, medicines optimisation and support for self-care (including exercise and weight management). However, there was uncertainty about whether community pharmacists should diagnose OA. A reported key facilitator to this extended role was pharmacy staff training, and barriers included high workloads and limited access to medical records. CONCLUSION:Current community pharmacy care for people with OA could be extended and include a greater focus on supported self-care.
