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Record W2156374833 · doi:10.3109/09540261.2011.586992

Psychotherapy for personality disorders

2011· review· en· W2156374833 on OpenAlexaff
Katherine L. Dixon–Gordon, Brianna J. Turner, Alexander L. Chapman

Bibliographic record

VenueInternational Review of Psychiatry · 2011
Typereview
Languageen
FieldPsychology
TopicPersonality Disorders and Psychopathology
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsPersonality disordersPsychosocialPsychological interventionPersonalityClinical psychologyPsychologyDistressPsychiatryMental healthIntervention (counseling)Randomized controlled trialCluster (spacecraft)PsychotherapistMedicineSocial psychology

Abstract

fetched live from OpenAlex

Personality disorders are widely prevalent among those seeking mental health services, resulting in substantial distress and a heavy burden on public assistance and health resources. We conducted a qualitative review of randomized controlled trials (RCTs) of psychosocial interventions for personality disorders. Articles were identified through searches of electronic databases and classified based on the focus of the psychological intervention. Data regarding treatment, participants and outcomes were identified. We identified 33 RCTs that evaluated the efficacy of various psychosocial treatments. Of these studies, 19 focused on treatment of borderline personality disorder, and suggested that there are several efficacious treatments and one well-established treatment for this disorder. In contrast, only five RCTs examined the efficacy of treatments for Cluster C personality disorders, and no RCTs tested the efficacy of treatments for Cluster A personality disorders. Although other personality disorders, especially Cluster A, place heavy demands on public assistance, and in spite of recommendations that psychosocial interventions should be the first line of treatment for these disorders, our review underscored the dearth of treatment research for many of these personality disorders. We highlight some obstacles to such research and suggest directions for future research.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.828
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0110.000

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.

Opus teacher head0.059
GPT teacher head0.430
Teacher spread0.372 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations58
Published2011
Admission routes1
Has abstractyes

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