The use of low-dose neuroleptics in the treatment of patients with severe personality disorder: An adjunct to psychotherapy
Bibliographic record
Abstract
Some patients with per- sonality disorders suffer from dis- turbances in the form or content of their thinking, in their affect regu- lation, or in their capacity to contain impulses. These disturbances can be significant enough to interfere with progress in various forms of psychotherapy. Case data from pa- tients in a psychiatry treatment pro- gram at the University of Alberta Hospital in Edmonton suggest that small doses of atypical neuroleptics can help to relieve the symptoms of these patients and allow them to ben- efit from group psychotherapy. Fur- ther research is needed to determine whether this benefit will succeed in other modalities of psychotherapy and in patients being supported by family practitioners. Research is also needed to determine to what degree improvement is due to medication and to psychotherapy, and whether at some point after completing psy- chotherapy patients might stop tak- ing neuroleptics without experiencing symptomatic relapse. It is important for clinical and medicolegal reasons to review the serious side effects of neuroleptic medications with pa- tients and to monitor patients for side effect symptoms. P atients in a partial hospital- ization program were found to benefit from the addition of small doses of atypical neuroleptic medications during their treatment in an 18-week group psycho- therapy program offered by the Psy- chodynamic Psychiatry Service of the Department of Psychiatry at the Uni- versity of Alberta Hospital in Edmon- ton. 1 The psychiatric day treatment program (DTP) consists of both un- structured psychotherapy groups and semi-structured groups in which an activity is used to introduce a theme about which the patients may do psy- chotherapeutic work. The theoretical emphasis of the program is psycho- dynamic, with a strong emphasis on confrontation, limit setting, and inter- pretation. At any one time the DTP has approximately 35 patients. While none of the patients are floridly psychotic, between one and four individuals have a disturbance in the form or content of their thinking, in their affect regulation, and/or in their capacity to contain their impulses. These disturbances are sig- nificant enough to interfere with the patients' progress in therapy, and are often difficult to categorize using cur- rent diagnostic terminology.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".