Development of Telepresence Among Patients and Psychotherapists in the Actor-Partner Interdependence Model: Longitudinal Observational Study of 20 Dyads From a Randomized Trial on Video Consultations in Primary Care
Bibliographic record
Abstract
Background: The COVID-19 pandemic has accelerated the adoption of video consultations in mental health care, highlighting the importance of therapeutic alliances for successful treatment outcomes in both face-to-face and web-based settings. Telepresence, the sense of being present with the mental health specialist (MHS) rather than feeling remote, is a critical component of building a strong therapeutic alliance in video consultations. While patients often report high telepresence levels, MHSs express concerns about whether video consultations can replicate the quality of face-to-face interactions. Despite its importance, research on telepresence development in MHSs over time and the dyadic interplay between patients and MHSs remains limited. Objective: This study aimed to evaluate the mutual influence within patient-MHS dyads on telepresence development during video consultations, using data from a randomized controlled trial assessing the feasibility of video consultations for depression and anxiety disorders in primary care. Methods: The study included 22 patient-MHS dyads (22 patients, 4 MHSs). Telepresence was measured using the Telepresence in Videoconference Scale. Dyadic data were analyzed using the actor-partner interdependence model with a distinguishable dyad structural equation model. Actor effects refer to the impact of an individual's telepresence at time point 1 (T1) on their telepresence at time point 2 (T2), while partner effects represent the influence of one party's telepresence at T1 on the other's telepresence at T2. Sensitivity analyses excluded data from individual MHSs to account for their unique effects. Results: A significant actor effect for MHSs (P<.001) indicated a high temporal stability of telepresence between T1 and T2. In contrast, the actor effect for patients was not statistically significant, suggesting a greater variability between T1 and T2. No significant partner effects for both patients and MHSs were observed, suggesting no mutual influence between dyad members. Age was a significant covariate for telepresence in both groups. Conclusions: Consistent with prior findings, MHSs experienced increased telepresence over time, whereas patients reported high telepresence levels from the start of therapy. The lack of dyadic influence highlights the need for further exploration into factors affecting telepresence development, such as age, technical proficiency, and prior treatment experience. Future studies with larger samples and more sessions are necessary to enhance the generalizability of these findings and to optimize the use of video consultations in mental health care.
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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 | 0.020 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".