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Record W4308142337 · doi:10.1210/jendso/bvac150.1067

ODP358 The effect of multi-cultural inter-facility endocrine video case conferencing – A novel model of education during the COVID pandemic

2022· article· en· W4308142337 on OpenAlexaboutno aff
Takako Araki, Hiraku Kameda, Masaaki Yamamoto, Toru Tateno, Yasumasa Iwasaki, Run Yu, Angela Radulescu, Lynn A. Burmeister, Hidenori Fukuoka

Bibliographic record

VenueJournal of the Endocrine Society · 2022
Typearticle
Languageen
FieldMedicine
TopicAdvances in Oncology and Radiotherapy
Canadian institutionsnot available
Fundersnot available
KeywordsAttendancePandemicCoronavirus disease 2019 (COVID-19)Medical educationVideoconferencingMedicineFamily medicinePsychologyDiseasePolitical sciencePathologyInfectious disease (medical specialty)Computer scienceMultimedia

Abstract

fetched live from OpenAlex

Abstract Introduction Coronavirus disease 2019 (COVID-19) pandemic brought not only physical and mental health problems but also negative impacts on social, economic and educational activities. Trainees, including medical students, residents, and clinical fellows had fewer opportunities to see and discuss patients with supervisors in person. In contrast, recent advances in technology have made it possible to review cases with overseas experts through online conferences. We launched a biannual inter-facility endocrine case review meeting in a video conference format during the pandemic of COVID-19. Here we present the format of our inter-facility online case conference and its impact on trainees. Methods The conference was organized by clinical faculty members from Japan, USA and Canada. For each conference, each facility prepared one to two cases in English. Four to five cases were presented and discussed with participants and guest commentators. After completion of the 4th conference, an anonymous multiple-choice online survey was administered to all attendees, and data was collected and analyzed by the committee members. Differences in responses before and after attendance were analyzed by paired t-test. Results Four conferences were held between July/31/2020, and Dec/10/2021 (CST). The facilities participating was as follows: University of Minnesota, Hokkaido Univ., University of Alberta, and Kobe Univ. Participants included medical students, residents, endocrine fellows, and faculty. Presenters were medical students (n=1), endocrine fellows (n=15), and neurosurgery faculty (n=1). Presented topics included the following: 11 cases with pituitary disorders, 3 cases with neuroendocrine tumors, 2 cases with adrenal disorders and 1 case of thyroid disorder. Sixty-two percent of the attendees stated that 3-4 facilities are an ideal size of the collaborations in inter-facility case conference, and 82% of the attendees felt twice a year is an appropriate frequency of the conference. Ninety-seven percent of the participants indicated their willingness to continue to attend. The survey results also revealed that the conference has a positive impact on trainees’ clinical practice and career development. Furthermore, the confidence in presenting skills in English significantly increased after the conference (p<0. 01). Conclusion Under the COVID-19 pandemic, we launched a new format of inter-institutional case review meeting using a video conferencing system that transcends national boundaries. This represents a new educational method for trainees. A small-scale (3-4 facilities) international collaboration in a video format may provide opportunities for learning rare endocrine cases, cultural diversity of endocrine care, enhanced active learning for trainees, and the opportunity for international presentation. This may lead to the development of a novel educational system in the future. Presentation: No date and time listed

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.369
Threshold uncertainty score0.466

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.030
GPT teacher head0.373
Teacher spread0.343 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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