เปรียบเทียบวิธี
ดูวิธีที่เลือกเทียบกันแบบเคียงข้าง แถวที่ต่างกันจะถูกเน้นไว้
| System Usability Scale สำหรับแอปพลิเคชันสุขภาพ× | มาตรวัดการยอมรับเทคโนโลยีดิจิทัลสุขภาพ× | |
|---|---|---|
| สาขาวิชา | สารสนเทศสุขภาพ | สารสนเทศสุขภาพ |
| ตระกูล | Process / pipeline | Process / pipeline |
| ปีกำเนิด≠ | 1996 | 1989 |
| ผู้ริเริ่ม≠ | John Brooke | Fred D. Davis (Technology Acceptance Model); extended by Venkatesh et al. (Unified Theory of Acceptance and Use of Technology) |
| ประเภท | Self-report questionnaire | Self-report questionnaire |
| แหล่งต้นตำรับ≠ | Brooke, J. (1996). SUS—A quick and dirty usability scale. In P. W. Jordan, B. Weerdmeester, A. Thomas, & I. L. McClelland (Eds.), Usability evaluation in industry (pp. 189–194). Taylor & Francis. ISBN: 978-0-7484-0635-1 | Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. DOI ↗ |
| ชื่อเรียกอื่น≠ | SUS-Health, System Usability Scale, SUS | DHAS, Digital Health Acceptance |
| ที่เกี่ยวข้อง | 3 | 3 |
| สรุป≠ | The System Usability Scale (SUS) is a rapid, validated tool for measuring perceived usability of digital products, widely adapted for health applications. Developed by John Brooke in 1996 and extensively validated by Bangor and colleagues, the 10-item SUS generates a single composite score reflecting users' subjective perception of ease of use, learnability, and overall system quality. Its simplicity and robustness have made it the de facto standard for usability assessment in health technology research. | The Digital Health Acceptance Scale measures the extent to which patients and providers perceive digital health technologies as useful, easy to use, and worth adopting. Grounded in Davis's Technology Acceptance Model (TAM) and extended by Venkatesh and colleagues through the Unified Theory of Acceptance and Use of Technology (UTAUT), the scale captures both intrinsic factors (usefulness, ease of use, subjective norms) and contextual factors (facilitating conditions, effort expectancy) that predict technology adoption and sustained use in healthcare settings. |
| ScholarGateชุดข้อมูล ↗ |
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