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| Telemedicine Satisfaction Scale× | Skala zur Akzeptanz digitaler Gesundheitsanwendungen× | |
|---|---|---|
| Fachgebiet | Gesundheitsinformatik | Gesundheitsinformatik |
| Familie | Process / pipeline | Process / pipeline |
| Entstehungsjahr≠ | 2009 | 1989 |
| Urheber≠ | Multiple researchers; consensus measure | Fred D. Davis (Technology Acceptance Model); extended by Venkatesh et al. (Unified Theory of Acceptance and Use of Technology) |
| Typ | Self-report questionnaire | Self-report questionnaire |
| Wegweisende Quelle≠ | Or, Z., & Kartak, F. (2009). Review of the empirical literature on telemedicine in the OECD countries: Does telemedicine improve outcomes? In M. Rechel, B. Goddard (Eds.), Improving healthcare quality in Europe. WHO Regional Office for Europe. link ↗ | Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. DOI ↗ |
| Aliasnamen | TSS, Telemedicine Satisfaction | DHAS, Digital Health Acceptance |
| Verwandt | 3 | 3 |
| Zusammenfassung≠ | The Telemedicine Satisfaction Scale measures patient satisfaction with remote clinical encounters, assessing perceptions of communication quality, technical usability, provider competence, and perceived benefit. While no single universal scale dominates the literature, core satisfaction domains—connection quality, provider accessibility, clinical effectiveness, and likelihood to recommend—are consistently measured across telemedicine studies to evaluate user acceptance and identify barriers to adoption. | 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. |
| ScholarGateDatensatz ↗ |
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