People's Perceptions and Expectations of Assistive Health-Enabling Technologies: An Empirical Study in Germany
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Demographic shifts and their consequences will lead to changes in the way health care is provided. Although assistive health-enabling technologies are regarded as one means to support these changes, they are minimally used, despite the maturity of the underlying technologies. This may partly be attributable to a disregard of users' needs and preferences. The aim of this article is to assess acceptance of health-enabling technologies with regard to their perceived usefulness, risks, and people's readiness to actually use them. Furthermore, we attempted to find out to whom individuals would entrust their health information, and what their basic fears are. We used a questionnaire presenting four exemplary technologies: emergency call systems, videophones, activity and health status monitoring. We conducted 147 face-to-face interviews and analyzed the results using descriptive statistics. Emergency call systems, health status and activity monitoring were rated as useful or very useful, videophones as hardly useful. Intrusion into one's privacy was the most prominent concern. Regarding fears in old age, people were mostly afraid of diseases and loss of independence. They would entrust their medical data to their physicians rather than relatives or caregivers. This study may contribute to systematic analyses of users' perceptions and preferences concerning assistive health-enabling technologies.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it