Core Schemas in Youth at Clinical High Risk for Psychosis
Bibliographic record
Abstract
BACKGROUND: Schema Theory proposes that the development of maladaptive schemas are based on a combination of memories, emotions and cognitions regarding oneself and one's relationship to others. A cognitive model of psychosis suggests that schemas are crucial to the development and persistence of psychosis. Little is known about the impact that schemas may have on those considered to be at clinical high risk (CHR) of developing psychosis. AIMS: To investigate schemas over time in a large sample of CHR individuals and healthy controls. METHOD: Sample included 765 CHR participants and 280 healthy controls. Schemas were assessed at baseline, 6 and 12 months using the Brief Core Schema Scale (BCSS). Baseline schemas were compared to 2-year clinical outcome. RESULTS: CHR participants evidenced stable and more maladaptive schemas over time compared to controls. Schemas at initial contact did not vary amongst the different clinical outcome groups at 2 years although all CHR outcome groups evidenced significantly worse schemas than healthy controls. Although there were no differences on baseline schemas between those who later transitioned to psychosis compared to those who did not, those who transitioned to psychosis had more maladaptive negative self-schemas at the time of transition. Associations between negative schemas were positively correlated with earlier abuse and bullying. CONCLUSIONS: These findings demonstrate a need for interventions that aim to improve maladaptive schemas among the CHR population. Therapies targeting self-esteem, as well as schema therapy may be important work for future studies.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".