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Refined Analysis of Older eHealth Users From an Agency Perspective: Quantitative Telephone Interview Study.
1Ruppin Academic Center, Department of Behavioral Sciences, Faculty of Community and Social Sciences, Emek Hefer District, Israel.
Older adults increasingly use eHealth, driven by a desire to help family and friends and manage health crises. Factors like internet experience and perceived literacy, not just age or education, predict eHealth adoption.
Area of Science:
- Gerontology
- Digital Health
- Health Informatics
Background:
- Traditional studies on the eHealth divide in older adults often focus on user vs. non-user comparisons, identifying age, gender, and education as barriers.
- These studies frequently offer a narrow view of eHealth practices and present conflicting findings regarding health conditions and eHealth use.
Purpose of the Study:
- To comprehensively describe eHealth usage patterns among older adults.
- To investigate if demographic factors (age, gender, education) still correlate with eHealth clusters.
- To determine the association between contextual factors, such as health changes in users or their relatives, and older adult eHealth engagement.
Main Methods:
- A representative sample of 442 Israeli adults aged 50 and above participated in a 30-minute telephone interview.
- Factor analysis of 21 eHealth use questions identified four clusters: instrumental/administrative information seeking, information sharing, peer information seeking, and web-based self-tracking.
- Data collected included demographics, internet experience, eHealth literacy, self-rated health, and use of offline services due to health crises.
Main Results:
- The most common eHealth uses were seeking instrumental/administrative information (95%) and information from peers (78.7%).
- Web-based self-tracking was utilized by 69%, while uploading/sharing health information was less common (11.3%).
- Age, gender, and education were not significant predictors of eHealth use when controlling for other factors; internet experience, usage frequency, and perceived literacy were key predictors for most clusters. Seeking health information for family/friends predicted all clusters.
Conclusions:
- Older adults can overcome structural barriers (age, gender, education) to eHealth adoption.
- Motivations for eHealth use include seeking information for family/friends and managing unexpected health crises.
- Health professionals should encourage older adults to use eHealth, avoiding stereotypes and recognizing their agency in adopting digital health practices.
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