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Published on: April 12, 2021
Self-Management Using eHealth Technologies for Liver Transplant Recipients: Scoping Review
Soo Hyun Kim1, Kyoung-A Kim2, Sang Hui Chu3
1School of Nursing, Johns Hopkins University, Baltimore, MD, United States.
eHealth technologies show promise for liver transplant recipients managing their health, but current tools need improvement in areas like alcohol relapse prevention and personalized support. Further research should focus on digital inclusion and tailored interventions.
Area of Science:
- Transplantation Science
- Digital Health
- Health Services Research
Background:
- Liver transplantation is a common treatment for end-stage liver disease and cancer, with improving outcomes.
- Recipients require lifelong self-management, including medication adherence and lifestyle adjustments.
- eHealth technologies offer potential for optimizing self-management but face slow adoption due to post-transplant complexity.
Purpose of the Study:
- To review the use of eHealth technologies in supporting self-management for liver transplant recipients.
- To identify the benefits and challenges of these technologies.
- To suggest future research directions in this area.
Main Methods:
- A scoping review was conducted using the Arksey and O'Malley methodology.
- Searches were performed across five major electronic databases (PubMed, CINAHL, Embase, PsycINFO, Web of Science).
- Studies involving adult liver transplant recipients and eHealth-based self-management were included, with quality assessed using TIDieR and Lorig & Holman's core skills.
Main Results:
- Fifteen studies were included, focusing on lifestyle management, medication adherence, and remote monitoring.
- A significant gap exists in eHealth interventions for alcohol relapse prevention.
- Technologies like mobile apps and telehealth were used, but with limited integration of decision-making and collaborative features.
Conclusions:
- eHealth interventions show potential for personalized care in liver transplant recipients.
- Future research should prioritize predictive models, patient-generated data, and digital human-to-human interactions.
- Addressing the digital divide and ensuring inclusivity across diverse populations are crucial for future eHealth self-management research.
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