Psychosis detection in dementia: a systematic review of diagnostic test accuracy studies
Bibliographic record
Abstract
Introduction: Symptoms of psychosis, characterized by delusions and hallucinations, are commonly experienced by persons living with dementia. A systematic review was completed to identify tools to evaluate symptoms of psychosis compared to a reference standard in persons with dementia. Articles reporting correlation values between psychosis tools were also identified. Methods: The search concepts psychosis, dementia, and diagnostic accuracy were used to search MEDLINE, PsycINFO, and Embase. Included articles meeting the primary objective described a tool to assess symptoms of psychosis, delusions, or hallucinations in persons with dementia, a reference standard form of diagnostic assessment for psychosis, and diagnostic accuracy outcomes for the psychosis tool. Secondary objective articles reported correlation values between two or more psychosis tools in persons with dementia. Results: One study met the primary objective and described the sensitivity and specificity of the Neuropsychiatric Inventory (NPI) and Columbia University Scale for Psychopathology in Alzheimer's Disease (CUSPAD) in identifying symptoms of psychosis, hallucinations, and delusions. The sensitivity of the NPI and CUSPAD in identifying symptoms of psychosis was 83 and 90%, respectively. Nine studies meeting the secondary objective described eleven unique tools and examined the degree to which tools used to assess psychotic symptoms in persons with dementia were related. Discussion: The NPI and CUSPAD were identified in a single study as psychosis tools that have been evaluated against a reference standard of psychosis assessment in persons with dementia. Various tools to assess the burden of psychotic symptoms in persons with dementia exist, but the diagnostic accuracy of existing tools remains understudied. Further research on the comparative utility and diagnostic accuracy is required for all psychosis tools used with persons 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 | 0.053 | 0.265 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.011 | 0.012 |
| Bibliometrics | 0.019 | 0.016 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".