Perception of eye contact in video teleconsultation
Bibliographic record
Abstract
During patient consultations by videoconferencing, clinicians often sit as close as 1 m from the videoconferencing units, creating a significant eye gaze angle (i.e. the angle between the eye and the camera, and the eye and the centre of the display). Eye gaze angle may adversely affect the satisfaction with videoconferencing. Four videoconferencing environments were examined: desktop PC, portable telehealth unit, videoconferencing room, and a boardroom equipped with a ceiling-mounted camera and a projection screen. Two still images of each of the three subjects were captured: one at a 7 degrees eye gaze angle and the other at 15 degrees. Each of 53 observers ranked four pairs of images for each of the three subjects. In 87% of cases, the observers perceived better eye contact at an eye gaze angle of 7 degrees than 15 degrees. Also, 92% of observers responded that the difference in the perceived eye contact was important to them as patients. Improved eye contact can be realized by increasing the horizontal distance of participants from the videoconferencing unit.
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 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 | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".