South Korean survey data from 349 adults aged 65 and older recruited from senior welfare centers and community facilities in the Seoul metropolitan area. The cross-sectional study, authored by Taeyeon Koo, measured ten constructs within an Augmented Technology Acceptance Model framework. Supplementary files were last updated on May 28, 2026.
Use Cases
- Segmenting user groups based on technology acceptance patterns using K-means clustering.
- Analyzing the relationship between perceived usefulness, ease of use, and intention to use digital health devices.
- Identifying barriers to adoption, such as low self-efficacy or price consciousness, among specific demographic segments.
- Validating clustering robustness through stability analysis and sensitivity tests as described in the methodology.
Strengths
- Dataset is based on a survey of 349 participants, providing a substantive sample size.
- Clustering reliability was confirmed with high agreement rates between 94% and 99%.
- The study design explicitly measures ten constructs within an established theoretical framework.
Limitations
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count is unknown, which may limit suitability assessment.
- Data may reflect geographic bias inherent to the Seoul metropolitan area sample.
Provenance
- Source
- Taeyeon Koo via figshare.
- Collection Method
- Cross-sectional survey conducted at senior welfare centers and community facilities.
- Freshness
- Last updated 2026-05-28 10:25:30; freshness should be verified.
- Geography
- Seoul metropolitan area, South Korea.