Bibliographic record
Abstract
Introduction:We aimed to assess patient satisfaction of conversion to phone consultation in urology clinic during the COVID-10 pandemic, and to investigate potential patient complaints that could be handled as phone consultations in the future. Methods:We conducted a retrospective review for new urological teleconsultations between April 2020 and September 2020 at our institute.A telephone interview was conducted with potential participants who were invited to answer a designed questionnaire.The questionnaire included nine questions covering patient satisfaction, quality of educational information, confidentiality, ability to share sensitive information, efficacy in absence of physical examination, overall acceptance, and preference of future teleconsultation regarding time and cost saving.Patients' responses were scaled using a five-point Likert scale (1=strongly disagree to 5=strongly agree).Results: After screening and assessment, 770 of 864 (89.1%) patients fulfilled the inclusion criteria; 94 (10.9%) were excluded due to hearing impairment or age under 18.Forty-two (5.5%) refused to participate, 310 (40.3%) of the patients could not be reached by phone, and eventually 307 (39.9%) completed the questionnaire.The highest percentage of agreement (94.4%) was among those who felt consultation was private and confidential.The lowest agreement was found in the question relating to the ability of the physician to do the job without physical exam (72.3%).A total of 204 (66.4%) patients agreed to future teleconsultation regarding time and cost savings (Table 1).On multivariate analysis, irritative lower urinary symptoms was the only independent factor associate with high degree of satisfaction (p=0.02) and wish for future teleconsultation (p=0.03).Conclusions: Urological teleconsultation is a feasible option during travel restrictions, as during COVID-19 pandemic.Two-thirds of patients agree to future teleconsultation.For one-third of patients, the inability to perform physical examinations is a concern.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.524 | 0.120 |
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".