Clients in Simulated Teletherapy via Videoconference Compensate for Altered Eye Contact When Evaluating Therapist Empathy
Bibliographic record
Abstract
Eye contact is frequently associated with an increased perception of empathy and telepresence, but the currently used videoconferencing (VC) technologies diminish the possibility of naturally conveying eye contact. This study compared the empathy, telepresence, and eye gaze patterns of clients in simulated VC teletherapy sessions where eye contact was altered or facilitated. Forty-two would-be clients met with one of four therapists in training for one 20-min simulated teletherapy session taking place via VC. The session either altered or facilitated eye contact perception by manipulating the positioning of the webcams and of the clients in their chair. Eye-tracking data focusing on the eyes, face, and general body regions of interest were obtained for 25 clients. The results show that facilitating eye contact in VC did not increase the clients' perceptions of empathy or telepresence. However, empathy was associated with greater time spent looking at the eyes and faces of the therapists, but only in the sessions facilitating eye contact. We suggest that clients successfully rely on other verbal and nonverbal cues to detect therapist empathy when eye contact is altered in teletherapy sessions.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".