Live Streaming of the Professor’s Ward Rounds in Undergraduate Neurology Education: Usability Study
Bibliographic record
Abstract
BACKGROUND: Although neurology department ward rounds are among the most important medical education exercises in Japan, they have several issues. Patients may find it unpleasant to undergo repeated neurological tests, especially when in the presence of several students. Only the front row of students can closely observe the examination findings; moreover, students were prohibited from contacting patients altogether during the COVID-19 pandemic. One possible solution is to use commercial videoconferencing systems. However, Japanese patients are reluctant to have their medical information or video footage of them sent outside of the hospital via the internet. OBJECTIVE: The study aimed to confirm the feasibility of conducting remote teaching rounds using an in-house web conferencing system in which the patients' personal data are securely protected. This study also explored whether using remote rounds alongside face-to-face participation would enhance learning. METHODS: We created an on-premises videoconferencing system using an open-source app. To perform video ward rounds, the professor wore a wireless microphone while leading routine in-person rounds and the attending physician carried a tablet device linked to a web conference, allowing students in another room to watch the rounds on a live stream. In total, 112 of 5th-year students who entered their 1-week neurology rotation between 2021 and 2022 were instructed to participate in 1-hour in-person and remote rounds. Students were given questionnaires to evaluate their satisfaction and the educational effects of the remote rounds. RESULTS: The remote ward rounds were conducted easily with no interference with the in-person rounds, nor any complaints from the patients. Each examination technique was explained by another teacher to the students who participated in remote rounds in the conference room. Characteristic neurological findings, such as plantar reflexes (Babinski sign), which are usually seen only by close observers during in-person rounds, could be visualized under magnification by all students. The postexperience survey (82/112, 73% response rate) showed that the mean score of participants' satisfaction was 3.94 (SD 0.83; excellent 5 and poor 1). No participant scoring 1 was noted. The proportion of students who observed 6 representative abnormal neurological findings (Babinski sign, hyperreflexia, cerebellar ataxia, involuntary movement, muscular weakness, and abnormality in sensory examination) increased by 22% (18/82, range 13-24) compared to in-person rounds alone. When self-rating the learning value, 43% (35/82) of the students answered that remote rounds are equally as valuable as in-person rounds, while 32% (26/82) preferred remote rounds. CONCLUSIONS: Live-streaming of neurology ward rounds using a secure in-house web conferencing system provides additional learning experience without concerns regarding leakage of patient information. This initiative could enhance neurology learning before entering a clinical clerkship.
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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 | 0.008 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".