Hemodialysis Clinic Social Networks, Sex Differences, and Renal Transplantation. Issue 9 (21st April 2017)

• Record Type: Journal Article
• Authors: Gillespie, A.; Fink, E. L.; Traino, H. M.; Uversky, A.; Bass, S. B.; Greener, J.; Hunt, J.; Browne, T.; Hammer, H.; Reese, P. P.; Obradovic, Z.
• Is Part Of: American journal of transplantation. Volume 17:Issue 9(2017)
• Page Start: 2400
• Page End: 2409
• Publication Date: 2017-04-21
• Subjects: clinical research/practice -- kidney transplantation/nephrology -- social sciences -- disparities -- dialysis -- gender -- mathematical model -- survey; Transplantation of organs, tissues, etc -- Periodicals; 617.95
• DOI: 10.1111/ajt.14273
• Languages: English
• ISSNs: 1600-6135

Abstract

Abstract : This study describes patient social networks within a new hemodialysis clinic and models the association between social network participation and kidney transplantation. Survey and observational data collected between August 2012 and February 2015 were used to observe the formation of a social network of 46 hemodialysis patients in a newly opened clinic. Thirty‐two (70%) patients formed a social network, discussing health (59%) and transplantation (44%) with other patients. While transplant‐eligible women participated in the network less often than men (56% vs. 90%, p = 0.02), women who participated discussed their health more often than men (90% vs. 45.5%, p = 0.02). Patients in the social network completed a median of two steps toward transplantation compared with a median of 0 for socially isolated patients (p = 0.003). Patients also completed more steps if network members were closely connected (β = 2.23, 95% confidence interval [CI] 0.16–4.29, p = 0.03) and if network members themselves completed more steps (β = 2.84, 95% CI 0.11–5.57, p = 0.04). The hemodialysis clinic patient social network had a net positive effect on completion of transplant steps, and patients who interacted with each other completed a similar number of steps. Abstract : Patients form hemodialysis clinic social networks and share health information within their network, and network characteristics are associated with successful completion of the steps toward kidney transplantation.