Becoming a transcultural psychotherapist: Qualitative study of the experience of professionals in training in a transcultural psychotherapy group
Bibliographic record
Abstract
Transcultural psychotherapy is an original therapeutic technique designed to respond to difficulties encountered in psychiatric treatment for migrants. Today, this psychotherapy is formalized and it is in use at numerous sites in France and internationally. An increasing number of professionals are seeking training in this method. We sought to explore the experiences of these trainees, at their entry in the group and during their training. This qualitative study used focus groups to interview trainees participating in a transcultural psychotherapy training group. The thematic analysis generated two domains of experience: the emotional and personal experience within the transcultural group, including the private feelings of the trainee-participants, their initial difficulties, and the changes in these feelings; and their perception of this specific type of care, that is, their perspectives on transcultural psychotherapy and its most original aspects. Based on the narratives of trainees in this program, we conclude that becoming a transcultural psychotherapist involves a process not only of cultural decentering but also of professional decentering. This decentering cannot be learned theoretically: it must be experienced, for a long enough time to become imbued with it and to allow oneself to modify one’s practices. After sufficient time in the group, the trainees succeed in extricating themselves, little by little, from their ethnocentric vision of psychotherapy, and come to tolerate and then integrate new ways of doing and thinking.
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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 | 0.014 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.017 | 0.019 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.003 | 0.006 |
| 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".