Strengthening the Status of Psychotherapy for Personality Disorders: An Integrated Perspective on Effects and Costs
Bibliographic record
Abstract
OBJECTIVE: Despite scientific evidence of effectiveness, psychotherapy for personality disorders is not yet fully deployed, nor is its reimbursement self-evident. Both clinicians and health care policy-makers increasingly rely on evidence-based medicine and health economics when determining a treatment of choice and reimbursement. This article aims to contribute to that understanding by applying these criteria on psychotherapy as a treatment for patients with personality disorder. METHOD: We have evaluated the available empirical evidence on effectiveness and cost-effectiveness, and integrated this with necessity of treatment as a moderating factor. RESULTS: The effectiveness of psychotherapy for personality disorders is well documented with favourable randomized trial results, 2 metaanalyses, and a Cochrane review. However, the evidence does not yet fully live up to modern standards of evidence-based medicine and is mostly limited to borderline and avoidant personality disorders. Data on cost-effectiveness suggest that psychotherapy for personality disorders may lead to cost-savings. However, state-of-the-art cost-effectiveness data are still scarce. An encouraging factor is that the available studies indicate that patients with personality disorder experience a high burden of disease, stressing the necessity of treatment. CONCLUSIONS: When applying an integrated vision on outcome, psychotherapy can be considered not only an effective treatment for patients with personality disorder but also most likely a cost-effective and necessary intervention. However, more state-of-the-art research is required before clinicians and health care policy-makers can fully appreciate the benefits of psychotherapy for personality disorders. Considerable progress is possible if researchers focus their efforts on evidence-based medicine and cost-effectiveness research.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".