%0 Journal Article
%T Using Topic Modeling to Understand Patients' and Caregivers' Perspectives About Left Ventricular Assist Device: Thematic Analysis.
%A Melnikov S
%A Klein S
%A Shahar M
%A Guy D
%J J Med Internet Res
%V 26
%N 0
%D 2024 Aug 13
%M 39137408
%F 7.076
%R 10.2196/50009
%X BACKGROUND: Heart failure (HF) is a significant global clinical and public health challenge, impacting 64.3 million individuals worldwide. To address the scarcity of donor organs, left ventricular assist device (LVAD) implantation has become a crucial intervention for managing end-stage HF, serving as a bridge to heart transplantation or as a destination therapy. Web-based health forums, such as MyLVAD.com, play a vital role as trusted sources of information for individuals with HF symptoms and their caregivers.
OBJECTIVE: We aim to uncover the latent topics within the posts shared by users on the MyLVAD.com website.
METHODS: Using the latent Dirichlet allocation algorithm and a visualization tool, our objective was to uncover latent topics within the posts shared on the MyLVAD.com website. Through the application of topic modeling techniques, we analyzed 459 posts authored by recipients of LVAD and their family members from 2015 to 2023.
RESULTS: This study unveiled 5 prominent themes of concern among patients with LVAD and their family members. These themes included family support (39.5% weight value), encompassing subthemes such as family caregiving roles and emotional or practical support; clothing (23.9% weight value), with subthemes related to comfort, normalcy, and functionality; infection (18.2% weight value), covering driveline infections, prevention, and care; power (12% weight value), involving challenges associated with power dependency; and self-care maintenance, monitoring, and management (6.3% weight value), which included subthemes such as blood tests, monitoring, alarms, and device management.
CONCLUSIONS: These findings contribute to a better understanding of the experiences and needs of patients implanted with LVAD, providing valuable insights for health care professionals to offer tailored support and care. By using latent Dirichlet allocation to analyze posts from the MyLVAD.com forum, this study sheds light on key topics discussed by users, facilitating improved patient care and enhanced patient-provider communication.