Impasses et opportunités dans le traitement des personnes souffrant d’un trouble sévère de la personnalité limite
Bibliographic record
Abstract
Borderline personality disorder is a serious mental health problem for which one of its main characteristics is significant difficulties in relationships with others. These relational problems have the unfortunate consequence of fostering negative attitudes among mental health professionals and contributing to the stigmatization of people suffering from this disorder. In this article, the author emphasizes the importance of taking into account the parameter of the therapeutic frame within which the feeling of facing a stalemate in the treatment of borderline personality disorder patients occurs. Six general strategies are presented that enable the therapist to limit or hinder the risk of stalemate in treatment. This article then presents the commonalities between treatments teams that tend to feel comfortable and efficacious in their management of borderline personality disorder patients. Finally, a case history is used to illustrate how some stalemates can in fact be seen as opportunities for growth for both the patient and the therapist. In order to avoid the vicious circle of negative interactions with patients already hypersensitive to inconsistencies and rejection, the author concludes by insisting on the necessity that more mental health professional have access to training programs and workshops specifically addressing how to better manage and treat people with BPD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".