Mise en œuvre d’une Supervision par observation directe avec ENregistrement vidéo en Situation Authentique de Soins (étude SENSAS) : enquête quantitative de faisabilité et d’intérêt
Bibliographic record
Abstract
Video recording in real-time consultation is mainly used in Canada and United Kingdom for improving the communication skills. No French studies have been published concerning the feasibility and the usefulness of this tool in vocational learning and assessment process of skills other than communication. The aim of this study was to evaluate the feasibility and the usefulness of this teaching method as a training and assessment tool of the learning process of general practitioner (GP) trainees. Between november 2017 and october 2018, trainees in ambulatory training courses collected quantitative data about recording consultations with a video camera: numbers of recordings, feedbacks, patients’ participation refusals, and information about the learning process and competencies. The trainees’ level of satisfaction was measured by means of a questionnaire. Sixty-seven trainees were recruited and 43 of them (64.2%) actively participated in the study; 607 video recordings and 243 feedbacks with trainers were performed. Few patients (10,9%) refused the video-recording. “Relation, communication, patient-centred care”, “Patient education” and “Professional attitude” were the most built competencies. Time was the main limiting factor of this teaching method. Most trainees were positive (83,5%) and in favour of the generalization of this tool (72,1%) in their university course. Video recording with immediate feedback in real-time consultation seems to be feasible but needs to be adapted to training areas. This teaching method seems to be useful in the development of different skills other than communication. It could constitute an additional tool for the certification of GP trainees.
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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 | 0.039 | 0.061 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| 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".