Digital Health for Breast Care: Patient Satisfaction and Reducing Disparities through Telemedicine
Bibliographic record
Abstract
Background Virtual teleconsultation plays a pivotal role in managing diseases requiring long‐term communication between patients and treatment teams, such as breast diseases. The Ruban Virtual Breast Clinic in Iran offers teleconsultation services focusing on nonurgent chronic complaints through offline messaging. This study aimed to evaluate patient satisfaction with these teleconsultation services. Methods A comprehensive questionnaire was designed with three sections: identifying the individual interacting with the clinic and prior teleconsultation use; collecting demographic data and reasons for consultation; and assessing satisfaction using 16 items rated on a Likert scale from 1 ( poor ) to 10 ( excellent ). The study included patients who received at least one consultation by a breast surgeon through the Ruban platform. Results Of 583 eligible cases, 367 (62.9%) consented to participate. The average satisfaction score was 91.6 out of 100, indicating a high level of patient satisfaction. Conclusions The high satisfaction rates suggest that telehealth services, particularly virtual consultations, are feasible and highly acceptable in meeting patients′ healthcare needs. These findings underscore telehealth′s potential to improve access to care, though further research is required to establish its clinical effectiveness.
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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 | 0.000 | 0.000 |
| 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".