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Data Sheet 1_Research on the influencing factors of using health science popularization short videos on the self-management behavior of older adult patients with chronic diseases.docx

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NIAID Data Ecosystem2026-05-10 收录
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https://figshare.com/articles/dataset/Data_Sheet_1_Research_on_the_influencing_factors_of_using_health_science_popularization_short_videos_on_the_self-management_behavior_of_older_adult_patients_with_chronic_diseases_docx/31115851
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BackgroundThe global prevalence of chronic diseases among the older adults population continues to rise, emerging as a core issue affecting the health and quality of life of older adults. This trend is particularly pronounced in China, which has entered a phase of deep aging society. With the rapid development of the internet, digital media technologies—represented by health science popularization short videos, offer new possibilities for self-health management in older adults. MethodsUtilizing data collected via face-to-face electronic questionnaires from 2024 to 2025 (N = 833), this study employed multivariable logistic regression model to analyze the role of various sociodemographic factors influencing self-management behavior following the use of health science popularization short videos among older adult patients with chronic diseases. Structural equation model (SEM) was used to analyze the mechanisms underlying these self-management behavior, incorporating descriptive statistics, regression analysis, and mediation testing. ResultsThe results indicate that watching health science popularization short videos had a significant positive effect on the self-management behavior of older adults patients with chronic conditions. Self-perceived level, medical compliance, and family caregiving level were identified as significant factors influencing both trust in the video content and self-management behavior. Content trustworthiness mediated this relationship and also directly influenced self-management behavior. Significant differences were observed based on “urban–rural location” and “extent of media exposure”; however, no significant behavioral differences were found by “gender,” and “education level” and “income” did not significantly affect content trustworthiness. ConclusionThis study treats digital media use as a key research variable. The findings suggest that in promoting the adaptation of digital health services for older adults, it is essential to strengthen the credibility of health science content and address the diverse needs of older adult populations across different regions and with varying media usage habits. Furthermore, by enhancing self-efficacy and strengthening family support, among other dimensions, more targeted health behavior intervention strategies should be developed. This approach will help to fully leverage the positive role of digital media in improving health management among older adults.
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2026-01-21
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