Executive Neurocognitive Functioning and Neurobehavioral Systems Indicators in Borderline Personality Disorder: A Preliminary Study
Bibliographic record
Abstract
It is argued that borderline personality disorder (BPD) represents the interaction of underlying neurobehavioral systems that are reflected principally in the phenotypic constructs of positive emotion, negative emotion, and nonaffective constraint (Depue & Lenzenweger, 2001). This preliminary and exploratory study sought to examine predictions made from the Depue-Lenzenweger model with respect to controlled (effortful) information processing in BPD. It was hypothesized that (a) BPD subjects may display deficits on tasks that require controlled information processing (sustained attention, spatial working memory, and executive functioning), (b) they may reveal elevated negative emotion as well as decreased positive emotion and nonaffective constraint, and (c) nonaffective constraint should be substantially inversely associated with accurate performance on controlled information processing tasks. The results of this study, which examined 24 BPD diagnosed individuals and 68 normal adults, found support for each of these predictions in relation to performance on the Wisconsin Card Sorting Test. The implications of these results for further experimental psychopathology investigations of BPD as well as further refinement of theoretical models of the disorder are discussed.
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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".