Perceptions of Patients and Physicians on Teleconsultation at Home for Diabetes Mellitus: Survey Study
Bibliographic record
Abstract
BACKGROUND: reduction than other telemedicine options, before the 2019 coronavirus disease crisis, their use had been lagging behind. Studies on physicians' or patients' perceptions about telemedicine have been performed independently of each other, and very few have focused on teleconsultations. In a time of great pressure for health systems and when an important portion of health care has to be assured at a distance, obtaining insights about teleconsultations at home from the stakeholders directly involved in the health care interaction is particularly important. OBJECTIVE: The perceptions of patients and physicians about their intentions to use home synchronous teleconsultations for DM care are examined to identify drivers and barriers inherent to programs that involve home teleconsultations. METHODS: Two identical questionnaires integrating the technology acceptance model and the unified theory of acceptance and use of technology and assessing the confidence in information and communication technology use of patients and physicians were developed. Responses by patients (n=75) and physicians (n=68) were analyzed using canonical correlation analysis. RESULTS: of 0.95 (for physicians) and 0.98 (patients). The main identified barriers to patient intention to use were the expected effort to explain the medical problem, and privacy and confidentiality issues. The major drivers were the facilitation of contact with the physician, which is beneficial to patient disease management and treatment, time savings, and reciprocity concerning physicians' willingness to perform teleconsultations. Responses from physicians revealed an association between intention to use and the expected performance of home teleconsultations. The major barrier to intention to use expressed in physicians' answers was doubts concerning the quality of patient examination. The major drivers were time savings, productivity increases, improvements in patient's health and patient management, National Health System costs reduction, and reciprocity relative to patients' willingness to engage in teleconsultations. CONCLUSIONS: To promote the use of home teleconsultations for DM, decision makers should improve patients' health literacy so the physician-patient communication is more effective; explore information and communication technology developments to reduce current limitations of non-face-to-face examinations; ensure patient privacy and data confidentiality; and demonstrate the capabilities of home teleconsultations to physicians.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".