Mechanisms of Change in Treatments of Personality Disorders: Commentary on the Special Section
Bibliographic record
Abstract
Considerable progress has been made in the psychotherapeutic treatment of patients with personality disorders (PDs). Once engendering a pervasive therapeutic nihilism, PDs are starting to be viewed as treatable with a much better prognosis than previously thought. Evidence from several randomized controlled trials demonstrating the effectiveness of various forms of psychotherapy, coupled with findings from several longitudinal studies, suggests that such increased clinical optimism is warranted. However, the persistent focus on treatment brands obscures our understanding of the mechanisms through which benefits are actually realized. This article considers emerging trends in PD treatment research, exemplified by the series of articles contained within this special section, that attempt to identify more precisely the mechanisms of therapeutic change. It is only through such work that we will be able to accomplish further refinement of effective strategies, create possibilities for true integration of therapies, and achieve real progress in the field for the betterment of our patients.
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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 | 0.005 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.047 | 0.041 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".