Line bisection performance in patients with personality disorders
Bibliographic record
Abstract
INTRODUCTION: Normal line bisection deviation to the left of the true centre has been interpreted as resulting from relative right hemisphere activation. Right hemisphere involvement has also been associated with the problems in dependency and attachment from infancy to adulthood. This hemispheric association predicts that patients diagnosed with dependent personality disorder will deviate significantly to the left on the line bisection task. METHODS: This hypothesis was tested by comparing the results of the line bisection task obtained respectively from 30 right-handed healthy volunteers and 14, 16, 18, and 26 outpatients with schizotypal, antisocial, borderline, and dependent personality disorders. Subjects completed eight horizontal line bisection tasks and the Dimensional Assessment of Personality Pathology-Basic Questionnaire (DAPP-BQ), a self-report measure of 18 traits delineating personality disorder. RESULTS: Patients with dependent personality disorder bisected significantly leftward compared to healthy controls. Dependent personality disorder patients scored significantly higher on DAPP-BQ Insecure Attachment, and lower on DAPP Stimulus Seeking, Callousness, Intimacy Problems, and Conduct Problems compared to the healthy controls and all other patient groups. CONCLUSIONS: Line bisection differentiates dependent personality disorder from other personality disorder diagnoses and healthy controls. This study thus suggests that line bisection can be used to enhance diagnostic specificity of dependent personality disorder and localises the brain areas implicated in the disorder.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".