The relationship between self-disorders (SDS) and depressive/anxious symptoms in a clinical sample of adolescents
Bibliographic record
Abstract
Introduction Self-disorders (SDs) have been described as a core feature of schizophrenia-spectrum disorders. Previous studies conducted on heterogeneous clinical adult and adolescents samples demonstrated that SDs aggregate selectively in the schizophrenia spectrum disorders compared to other disorders. Objectives To examine the specificity of SDs for schizophrenia spectrum disorders in adolescent inpatient sample. Methods Fifty-five adolescent inpatients admitted to the Child Psychiatry Unit at the Sapienza University in Rome were assessed for psychopathology using Kiddie Schedule for Affective Disorders and Schizophrenia (K-SADS-PL), Structured Interview for Prodromal Syndromes (SIPS/SOPS),Examination of Anomalous Self-Experiences (EASE), Multidimensional Anxiety Scale for Children (MASC), Calgary depression scale for schizophrenia (CDSS) Results Patients, aged 14-18 years, were divided in four diagnostic groups: schizophrenia spectrum disorders (5 pts.), mood disorders (19 pts.), anxiety disorders (27 pts.) and other disorders (4 pts.). Frequency of self-disorders was different among the 4 groups. Including patients schizotypal personality disorder in the schizophrenia-spectrum disorder group, the difference is still significant. Mann-Whitney U test shows no differences between EOP and UHR patients in SD. Furthermore, correlations between EASE total score and Calgary and MASC total scores were significant. Conclusions Our results confirm the specificity of SDs for schizophrenia spectrum disorders and also the belonging of schizotypal personality disorder to schizophrenia-spectrum.
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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 | 0.001 | 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) | 0.001 | 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".