MétaCan
Menu
Back to cohort
Record W4245749004 · doi:10.24124/2009/bpgub1408

Using dialectical behaviour therapy to treat clients with left temporal lobe epilepsy

2009· dissertation· en· W4245749004 on OpenAlexaff
Cheryl Andersen

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldPsychology
TopicPersonality Disorders and Psychopathology
Canadian institutionsUniversity of Northern British Columbia
Fundersnot available
KeywordsBorderline personality disorderPsychologyEpilepsyPsychotherapistPersonalityDialectical behavior therapySuicidal ideationTemporal lobePsychiatryClinical psychologyMedicineMedical emergencyPsychoanalysis

Abstract

fetched live from OpenAlex

The purpose of this project is to address the gap that exists in the literature in regards to providing counselling to clients with left temporal lobe epilepsy (LTLE). In many ways, the psychological symptoms of LTLE and those of borderline personality disorder are similar. Both client populations can have difficulty regulating emotions and with maintaining healthy relationships. Both populations have high rates of suicidal ideation and depression. Dialectical Behaviour Therapy (DBT) was developed to treat clients with borderline personality disorder. Due to the similarities between many of the symptoms of borderline personality disorder and those of LTLE, counsellors should be successful when teaching the skills of DBT to LTLE clientele. This project provides a description of LTLE and of DBT, and it demonstrates how DBT can be applied to counsel clients with LTLE.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.052
GPT teacher head0.388
Teacher spread0.337 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
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

Citations0
Published2009
Admission routes1
Has abstractyes

Explore more

Same topicPersonality Disorders and PsychopathologyFrench-language works237,207