Assessing Awareness, Want, and Adoption of Internet Medical Services Among Chronic Disease Patients in China:A Structural Equation Model and Matrix Analysis

Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown

Published: March 25, 2025

Background Internet Medical Services (IMS) hold substantial potential to address healthcare challenges arising from demographic shifts, such as aging populations, and the evolving disease spectrum, marked by rising prevalence of chronic conditions. However, their practical impact has yet fully meet these expectations. This study seeks investigate factors influencing adoption utilization IMS among patients, focusing on effects across specific domains acceptance processes, provide a fresh perspective enhancing management. Methods We extended Technology Acceptance Model (TAM) with Information-Motivation-Behavioral Skills (IMB) framework, incorporating eHealth literacy, patient activation, demographics (age, education duration, income level). A cross-sectional survey 520 patients in Jinan, China, was analyzed using Structural Equation Modeling (SEM) matrix analysis evaluate patterns factors. Results Information showed high minimal disparities, while Diagnose exhibited low uptake significant gaps, particularly older, less-educated, rural, multimorbid patients. Notably, higher-income displayed lower all categories, expected enhance adoption, unexpectedly hindered use. SEM confirmed Perceived Usefulness duration positive drivers stages, literacy boosting Adoption, age exerting negative effect. Conclusions trailblazing model elucidates complexities, revealing counterintuitive barriers like activation. It underscores need for targeted interventions service quality, providing robust framework optimizing deployment advancing digital health strategies care.

Language: Английский

Public Discourse and Sentiment Toward Older Drivers on Social Media in Japan (Preprint)

Published: Nov. 26, 2024

As the global population ages, concerns about older drivers are intensifying. Although not inherently more dangerous than other age groups, traditional surveys in Japan reveal persistent negative sentiments toward them. This discrepancy suggests importance of analyzing discourse on social media, where public perceptions and societal attitudes actively shaped. study aims to quantify long-term through Twitter, a leading media platform. The specific objectives to: (1) examine tweets, (2) identify textual contents topics discussed (3) analyze how associated with these contents. We collected Japanese tweet related from 2010 2022. Each quarter, we applied J-LIWC J-MFD dictionaries for sentiment analysis, employed two-layer Non-negative Matrix Factorization dynamic topic modeling, logistic regression analyses explore relationships between topics. obtained 2,625,807 tweets 1,052,976 unique users discussing drivers. number has steadily increased, significant peak 2016, 2019, 2021, coinciding high-profile traffic crashes. Sentiment analysis revealed predominance emotion (62.4%), anger (17.4%), anxiety (18.6%), risk (58.2%). Topic modeling identified 29 topics, including those driving licenses, crashes, personal perspectives, issues. Crash events topic, which increased by 0.08% per showed strong correlation (B = 23.39, P < .001) 24.1, .001). 13-year quantified using Twitter data, revealing paradoxical increase perceived risk, despite decline actual crash rate among These findings underscore accurate communication crashed caused mitigate undue prejudice avoid unnecessary disadvantages

Language: Английский

Public Discourse Toward Older Drivers in Japan: Longitudinal Analysis of Social Media Data from 2010 to 2022 (Preprint)

JMIR Infodemiology, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 26, 2024

Language: Английский