Cognitive Abilities in Schizoid Personality Disorder with and without Borderline Intellectual Functioning: The Burden in Psychopathology
Bibliographic record
Abstract
Background: Borderline intellectual functioning (BIF) and schizoid personality disorder (Schizoid PD) are clinical conditions under-researched and poorly understood. The principal aim of this retrospective study was to investigate cognitive abilities in people with BIF and Schizoid PD. Clinical, demographic, and neuropsychological data of forty-seven Schizoid PD participants, with an average age of 35, were analyzed. The sample split into two groups: Schizoid PD with BIF (BIF+: n = 24; intelligence quotient – IQ range: 71-84) and Schizoid PD without BIF (BIF-: n = 23; IQ range: 89-121). A descriptive analysis of the clinical and demographic characteristics of the two groups was performed. Methods: Neuropsychological measures (Wechsler Adult Intelligence Scale-Revised – WAIS-R IQ, factor index, subtest scores) and cognitive performance deficits in the two groups were compared using parametric and non-parametric tests, as necessary. Correlation coefficients were calculated for relationships between variables. Regression analyses were conducted to identify predictors associated with negative outcomes, such as substance use behavior. Results: The results revealed that the cognitive profile of BIF+ deviated significantly from that observed in BIF-. Peculiar BIF+ dysfunctions were found in the domains of verbal and perceptual reasoning, attention, memory, processing speed, planning, and problem-solving. The verbal IQ had the highest discriminative value for the presence of BIF in patients with Schizoid PD. Conclusions: The BIF condition and the verbal comprehension index were the predictors most associated with substance use behavior. Early identification of BIF should be relevant to planning targeted intervention strategies to improve daily life skills and outcomes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".