A Psychopathological Comparison between Delusional Disorder and Schizophrenia
Bibliographic record
Abstract
Objective: To contribute to a better differential clinical categorisation of delusional disorder (DD) versus schizophrenia (SZ) and to add and complete evidence from previous clinical studies of DD compared to schizophrenia. Methods: A cross-sectional study using a clinical sample of 275 patients (132 patients with DD) was studied. Patients were consecutively attending public clinics located in urban and rural areas in both Andalusia and Catalonia (Spain). All participants met DSM-IV diagnostic criteria for either DD or SZ. Data were gathered on sociodemographics, illness duration, Barona-Index estimation of intelligence quotient (IQ), and global functioning, along with a thorough psychopathological assessment using the Positive and Negative Syndrome Scale (PANSS). Comparisons between both groups were calculated using χ 2 , Student t, and multivariate analysis of covariance tests. Results: Patients with DD were older (mean [SD], 50.3 [14.6] years vs. 36.6 [11.1] years; t = 8.597; P ≤ 0.0001), were more frequently married (45.4% vs. 10.8%; χ 2 = 38.569; P ≤ 0.0001), and had a higher mean estimated premorbid IQ (111.4 vs. 105.4; t = 2.609; P ≤ 0.01). On the other hand, SZ patients were predominantly male (71.4% vs. 48.9%; χ 2 = 14.433; P ≤ 0.0001) and had greater work-related disability than DD patients (20.5% vs. 50.3%; χ 2 = 19.564; P ≤ 0.001). Overall, the DD group showed a less severe PANSS psychopathology than SZ group. Thus, total mean (SD) PANSS scores for schizophrenia and delusional disorder, respectively, were 76.2 (22.4) versus 54.1 (18.4) ( t = –8.762; P ≤ 0.0001). Moreover, patients with DD showed a better global functioning than those with SZ (62.7 [13.2] vs. 51.9 [16.9]; F = 44.114; P ≤ 0.0001). Conclusions: DD is a milder and distinct disorder compared to SZ in terms of psychopathology and global functionality.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".