Development and assessment of a brief screening tool for psychosis in dementia
Bibliographic record
Abstract
INTRODUCTION: Hallucinations and delusions (H+D) are common in dementia, but screening for these symptoms-especially in busy clinical practices-is challenging. METHODS: Six subject matter experts developed the DRP3™ screen, a novel valid tool to detect H+D in dementia, assessed its content validity through alignment with DRP reference assessments (Scale for the Assessment of Positive Symptoms-Hallucinations + Delusions, Neuropsychiatric Inventory-Questionnaire, International Psychogeriatric Association Criteria), and retrospectively investigated its ability to detect H+D in HARMONY trial (NCT03325556) enrollees. RESULTS: < .0001). Retrospectively applying the DRP3 screen to HARMONY identified all (N = 392) trial enrollees. DISCUSSION: The DRP3 screen, comprising three yes/no questions, is a content-valid tool for detecting H+D in dementia that aligned with current reference assessments and successfully identified trial participants when retrospectively applied to a completed trial. Within busy practice constraints, the DRP3 screen provides a brief tool for sensitive detection of H+D in patients with dementia.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".