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Record W2755543228 · doi:10.1521/pedi_2017_31_309

Outcome Trajectories and Prognostic Factors for Suicide and Self-Harm Behaviors in Patients With Borderline Personality Disorder Following One Year of Outpatient Psychotherapy

2017· article· en· W2755543228 on OpenAlexaff
Shelley McMain, Skye Fitzpatrick, Tali Boritz, Ryan Barnhart, Paul S. Links, David L. Streiner

Bibliographic record

VenueJournal of Personality Disorders · 2017
Typearticle
Languageen
FieldPsychology
TopicPersonality Disorders and Psychopathology
Canadian institutionsMcMaster UniversitySt Joseph's Health CareUniversity of TorontoToronto Metropolitan UniversityYork UniversityWestern UniversityCentre for Addiction and Mental Health
Fundersnot available
KeywordsBorderline personality disorderPsychologyDialectical behavior therapyDepression (economics)PsychiatryMultinomial logistic regressionSuicide attemptLogistic regressionClinical psychologySuicide preventionPoison controlMedicineInternal medicineMedical emergency

Abstract

fetched live from OpenAlex

This study examined suicide and self-harm trajectories in 180 individuals with BPD receiving dialectical behavior therapy or general psychiatric management in a randomized controlled trial. Suicide and self-harm behaviors were assessed at baseline, every four months throughout treatment, and every 6 months over 2 years of follow-up. Latent class growth mixture modeling identified suicide and self-harm trajectories. Multinomial logistic regression analyses examined baseline patient characteristics. Three latent subgroups were identified. The largest responded rapidly to treatment and sustained a favorable response post-discharge. The second progressed slowly during treatment but achieved and maintained a favorable response. A third subgroup showed a rapid favorable response during treatment, however symptoms returned to near baseline levels post-discharge. This third subgroup had higher baseline depression, emergency department visits, and unemployment. BPD patients with high baseline health care utilization, depression, and unemployment may benefit from modifications to treatment specifically targeting these issues.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.031
GPT teacher head0.343
Teacher spread0.312 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations28
Published2017
Admission routes1
Has abstractyes

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