Videoconferencing psychotherapy from a psychodynamic point of view. A qualitative analysis
Bibliographic record
Abstract
There is a growing interest in delivering videoconferencing psychotherapy (VCP) due to the enormous impact of the COVID-19 pandemic on our lives since the beginning of severe restrictions worldwide in March 2020. Scientific literature has provided interesting results about the transition to remote sessions and its implications, considering different psychotherapy orientations. Less is known about whether and how VCP affects psychodynamic psychotherapeutic approaches and reports on remote work with severe and complex mental health problems such as severe personality disorders are still scarce. The aim of the study was to examine the experiences of psychodynamic psychotherapists, mainly delivering Transference-Focused Psychotherapy (TFP), with the transition and delivery of VCP during the first wave of the COVID-19 pandemic. Four hundred seventy-nine licensed psychotherapists completed an online survey during the peak of the pandemic. Survey data were analyzed using qualitative analysis. Results are presented and discussed concerning advantages and disadvantages regarding the access to psychotherapy, the specificity of the online video setting, bodily aspects, the quality of the therapeutic relationship, the therapeutic process including technical aspects and therapist's experience. Furthermore, we analyzed and discussed the statements concerning transference and countertransference reactions differentiating between high-level borderline and neurotic patients and low-level borderline patients. Our results support the importance to identify patients who potentially benefit from VCP. Further research including more prospective randomized controlled trials are needed to investigate the therapeutic implications of the findings.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".