A Perspective on Client-Psychologist Relationships in Videoconferencing Psychotherapy: Literature Review
Bibliographic record
Abstract
BACKGROUND: During the COVID-19 pandemic, people have been encouraged to maintain social distance. Technology helps people schedule meetings as remote videoconferencing sessions rather than face-to-face interactions. Psychologists are in high demand because of an increase in stress as a result of COVID-19, and videoconferencing provides an opportunity for mental health clinicians to treat current and new referrals. However, shifting treatment from face-to-face to videoconferencing is not simple: both psychologists and clients miss in-person information cues, including body language. OBJECTIVE: This review proposes a new theoretical framework to guide the design of future studies examining the impact of a computer as a mediator of psychologist-client relationships and the influence of videoconferencing on the relationship process. METHODS: We conducted a literature review including studies focused on communication and key concepts of the therapeutic relationship and therapeutic alliance. RESULTS: Studies have reported that clients are generally satisfied with videoconference therapy in terms of the relationship with their therapists and the establishment of the therapeutic alliance. Conversely, studies indicate that psychologists continue to highlight difficulties in establishing the same quality of therapeutic relationship and therapeutic alliance. The contrasting experiences might underlie the differences in the type of emotional and cognitive work required by both actors in any therapy session; furthermore, the computer seems to take part in their interaction not only as a vehicle to transmit messages but also as an active part of the communication. A new model of interaction and relationship is proposed, taking into account the presence of the computer, along with further hypotheses. CONCLUSIONS: It is important to consider the computer as having an active role in the client-psychologist relationship; thus, it is a third party to the communication that either assists or interferes with the interaction between psychologists and clients.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.015 | 0.027 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".