Literature DB >> 33866675

Perspectives of solid organ transplant recipients on medicine-taking: Systematic review of qualitative studies.

James Tang1,2, Jasmijn Kerklaan2,3, Germaine Wong1,2,4, Martin Howell1,2, Nicole Scholes-Robertson1,2, Chandana Guha1,2, Ayano Kelly2, Allison Tong1,2.   

Abstract

Medicine-taking among transplant recipients is a complex and ubiquitous task with significant impacts on outcomes. This study aimed to describe the perspectives and experiences of medicine-taking in adult solid organ transplant recipients. Electronic databases were searched to July 2020, and thematic synthesis was used to analyze the data. From 119 studies (n = 2901), we identified six themes: threats to identity and ambitions (impaired self-image, restricting goals and roles, loss of financial independence); navigating through uncertainty and distrust (lacking tangible/perceptible benefits, unprepared for side effects, isolation in decision-making); alleviating treatment burdens (establishing and mastering routines, counteracting side effects, preparing for the unexpected); gaining and seeking confidence (clarity with knowledge, reassurance through collective experiences, focusing on the future outlook); recalibrating to a new normal posttransplant (adjusting to ongoing dependence on medications, in both states of illness and health, unfulfilled expectations); and preserving graft survival (maintaining the ability to participate in life, avoiding rejection, enacting a social responsibility of giving back). Transplant recipients take medications to preserve graft function, but dependence on medications jeopardizes their sense of normality. Interventions supporting the adaptation to medicine-taking and addressing treatment burdens may improve patient satisfaction and capacities to take medications for improved outcomes.
© 2021 The American Society of Transplantation and the American Society of Transplant Surgeons.

Entities:  

Keywords:  clinical research/practice; immunosuppressant; organ transplantation in general; qualitative research

Mesh:

Year:  2021        PMID: 33866675     DOI: 10.1111/ajt.16613

Source DB:  PubMed          Journal:  Am J Transplant        ISSN: 1600-6135            Impact factor:   8.086


  1 in total

1.  Prediction Model of Immunosuppressive Medication Non-adherence for Renal Transplant Patients Based on Machine Learning Technology.

Authors:  Xiao Zhu; Bo Peng; QiFeng Yi; Jia Liu; Jin Yan
Journal:  Front Med (Lausanne)       Date:  2022-02-18
  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.