Validating cognitive screening in young people with <scp>first‐episode</scp> psychosis: The <i>CogScreen</i> protocol
Bibliographic record
Abstract
AIM: Cognitive impairments are a core feature of first-episode psychosis (FEP) and one of the strongest predictors of long-term psychosocial functioning. Cognition should be assessed and treated as part of routine clinical care for FEP. Cognitive screening offers the opportunity to rapidly identify and triage those in most need of cognitive support. However, there are currently no validated screening measures for young people with FEP. CogScreen is a hybrid effectiveness-implementation study which aims to evaluate the classification accuracy (relative to a neuropsychological assessment as a reference standard), test-retest reliability and acceptability of two cognitive screening tools in young people with FEP. METHODS: Participants will be 350 young people (aged 12-25) attending primary and specialist FEP treatment centres in three large metropolitan cities (Adelaide, Sydney, and Melbourne) in Australia. All participants will complete a cross-sectional assessment over two sessions including two cognitive screening tools (Screen for Cognitive Impairment in Psychiatry and Montreal Cognitive Assessment), a comprehensive neuropsychological assessment battery, psychiatric and neurodevelopmental assessments, and other supplementary clinical measures. To determine the test-retest reliability of the cognitive screening tools, a subset of 120 participants will repeat the screening measures two weeks later. RESULTS: The protocol, rationale, and hypotheses for CogScreen are presented. CONCLUSIONS: CogScreen will provide empirical evidence for the validity and reliability of two cognitive screening tools when compared to a comprehensive neuropsychological assessment. The screening measures may later be incorporated into clinical practice to assist with rapid identification and treatment of cognitive deficits commonly experienced by young people with FEP.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".