Structure of self-schemas in patients with paranoia
Bibliographic record
Abstract
Negative self-schemas have been implicated in both paranoia and depression. There is a lack of research on the structural characteristics of self-schemas, even though these characteristics might be stable risk factors. The present study explored organization of positive and negative self-schemas in currently non-depressed individuals with persistent delusional disorder (PD), currently depressed individuals with persistent delusional disorder (PDD), and nonpsychiatric controls (NC). Self-schema consolidation was measured via the Psychological Distance Scaling Task. Within the interpersonal domain, negative selfschemas were more densely organized in PDD compared to both PD and NC. Both patient groups had less interconnected positive interpersonal schemas than controls. Within the achievement domain, PDD demonstrated less consolidated positive achievement schemas than NC and greater interconnectedness among negative adjectives than PD. Central limitation includes a small sample size. The findings point to an existence of at least two self-schema organizations in paranoid individuals.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 teacher head, 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".