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Record W2786180544 · doi:10.1521/pedi.2018.32.supp.134

Mechanisms of Change in Treatments of Personality Disorders: Commentary on the Special Section

2018· letter· en· W2786180544 on OpenAlexaff
David Kealy, John S. Ogrodniczuk

Bibliographic record

VenueJournal of Personality Disorders · 2018
Typeletter
Languageen
FieldPsychology
TopicPersonality Disorders and Psychopathology
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsOptimismPsychotherapistPsychologySpecial sectionSection (typography)Personality disordersPersonalityPsychoanalysis

Abstract

fetched live from OpenAlex

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.250
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0060.000

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 head0.061
GPT teacher head0.336
Teacher spread0.275 · 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
GenreCommentary

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

Citations6
Published2018
Admission routes1
Has abstractyes

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