A comparison of face-to-face versus remote assessment of neonatal resuscitation skills
Bibliographic record
Abstract
The neonatal resuscitation skills of 30 third-year medical students were assessed in real time by a face-to-face examiner in the same room as the student, and by a remote examiner located in a separate room using the ANAKIN system. The ANAKIN system combines an instrumented manikin simulator, computer-based assessment and high-bandwidth videoconferencing. The students were assessed while performing a neonatal resuscitation megacode using the ANAKIN system. Students were satisfied with the ANAKIN system as an assessment system and were not intimidated by its use. However, the correlation between the face-to-face and remote examiner's mean total performance assessment scores was 0.27, which was not significant (P=0.14). The results indicated variation between the examiners' performance scores in a number of key technical skill areas. The findings from this study have implications for the use of technology-mediated systems in assessing resuscitation skills. Examiner orientation is critical for individuals using such systems. These persons must be comfortable and confident in using the technology. Interface and design features of the system need to be carefully scrutinized and tested.
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 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) | 0.001 | 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".