Opinions and Beliefs About Telemedicine for Emergency Treatment During Ambulance Transportation and for Chronic Care at Home
Bibliographic record
Abstract
BACKGROUND: Telemedicine is a valid alternative to face-to-face patient care in many areas. However, the opinion of all stakeholders is decisive for successful adoption of this technique, especially as telemedicine expands into novel domains such as emergency teleconsultations during ambulance transportation and chronic care at home. OBJECTIVE: We evaluate the viewpoints of the broad public, patients, and professional caregivers in these situations. METHODS: A 10-question survey was developed and obtained via face-to-face interviews of visitors at the Universitair Ziekenhuis Brussel (UZB). The online questionnaire was also distributed among professional caregivers via the intranet of the UZB and among the broad public using social media. RESULTS: In total, 607 individuals responded to the questionnaire, expressing a positive opinion regarding telemedicine for in-ambulance emergency treatment and for chronic care at home. Privacy issues were not perceived as relevant, and most respondents were ready to participate in future teleconsultations. Lack of telecommunication knowledge (213/566, 37.6%) was the only independent factor associated with rejection of telemedicine at home and respondents via social media (250/607, 41.2%) were less concerned about privacy issues than respondents via face-to-face interviews (visitors, 234/607, 38.6%). The visitors were more positive towards in-ambulance telemedicine and more likely to agree with future participation in teleconsultations than respondents via social media. CONCLUSIONS: The broad public, professional caregivers, and patients reported a positive attitude towards telemedicine for emergency treatment during ambulance transportation and for chronic care at home. These results support further improvement of telemedicine solutions in these domains.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".