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Record W4242295059 · doi:10.1017/9781107298613

Integrated Modular Treatment for Borderline Personality Disorder

2017· book· en· W4242295059 on OpenAlexaff
W. John Livesley

Bibliographic record

VenueCambridge University Press eBooks · 2017
Typebook
Languageen
FieldPsychology
TopicPersonality Disorders and Psychopathology
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsBorderline personality disorderPsychotherapistPsychologyPsychological interventionConstruct (python library)PersonalityInterpersonal communicationFoundation (evidence)Mental healthIdentity (music)Clinical psychologySocial psychologyPsychiatryComputer science

Abstract

fetched live from OpenAlex

This clinical guide describes a different way to treat borderline personality disorder. Rather than using the currently available therapies, the author presents a trans-theoretical approach that combines the essential elements of all effective treatments. The book offers a framework for understanding the nature and origins of borderline personality disorder that is used to define treatment targets and strategies. Building on this foundation, systems for organizing treatment are presented around change mechanisms common to all effective therapies. Interventions are presented in modules, allowing therapists to select treatment according to the needs of patients. Treatment is explained by dividing therapy into phases, each addressing different problems. Methods are described to promote engagement, manage suicidality, treat crises, improve emotional regulation, restructure maladaptive interpersonal behaviours, construct a new sense of self and identity, and build a life worth living. The volume will interest mental health professionals from all disciplines and different levels of expertise.

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)0.000
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.375
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.045
GPT teacher head0.291
Teacher spread0.246 · 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
GenreOther

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

Citations26
Published2017
Admission routes1
Has abstractyes

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