The role of a family history of psychosis for youth at clinical high risk of psychosis
Bibliographic record
Abstract
AIM: On average, there is a 10% to 12% likelihood of developing a psychotic disorder solely based on being at familial high risk. However, the introduction of the criteria for clinical high risk (CHR) of psychosis suggested for CHR individuals, 20% to 30% will go on to develop a full-blown psychotic illness within 3 years. Several studies suggest a role for family history in conversion to psychosis among those at CHR. However, we know very little about those who meet the CHR criteria and have a positive family history for psychosis compared to those at CHR with no known family history. The aim of this study was to compare these 2 groups on demographics, clinical symptoms, social and role functioning, IQ, environmental factors and conversion to psychosis. METHOD: A total of 762 participants met criteria for being at CHR, 119 of whom had a family history (CHR + FH) and 643 without (CHR-FH). Groups were compared on attenuated symptoms, role and social functioning, IQ, past trauma, perceived discrimination and cannabis use. Survival analysis was used to compare groups on conversion rates. RESULTS: There were no major differences between the groups in symptoms, functioning, IQ, cannabis use or in the rate of conversion between the groups. The CHR + FH group reported increased amounts of early trauma. CONCLUSION: There is a possibility that CHR + FH individuals believe that it is more difficult for them to cope with circumstances such as abuse or potential abuse. Future research on this subject should investigate family environment and its role in conversion to psychosis among CHR + FH individuals.
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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 | 0.010 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".