Bibliographic record
Abstract
OBJECTIVE: To compare brief dementia screening tests as candidates for routine use in primary care practice. METHOD: We selected screening tests that met 2 criteria: 1) administration time of 10 minutes or less in studies including individuals with, and without, dementia; and 2) performance characteristics evaluated in at least 1 community or clinical sample of older adults. We compared tests for face validity, sensitivity, and specificity in a clearly defined subject sample; for vulnerability to sociodemographic biases unrelated to dementia; for direct comparison with an accepted standard; for acceptability to patients and doctors; and for brevity and ease of administration, scoring, and interpretation by nonspecialists. RESULTS: Thirteen instruments met our inclusion criteria. Very short tests (1 minute or less) proved unacceptable by several criteria. Standard instruments requiring more than 5 minutes to complete, including the best-studied Mini-Mental State Examination (MMSE), were found to be too long for routine application. Several failed other performance tests or could not be adequately assessed. Short tests taking between 2 and 5 minutes that can be administered by nonspecialists with little or no training and are relatively unbiased by language and education level appear to be superior to both shorter and longer instruments. CONCLUSIONS: Three tests showed the most promise for broad application in primary care settings: the Mini-Cog, the Memory Impairment Screen, and the General Practitioner Assessment of Cognition (GPCOG). Formal practice intervention trials are now needed to validate the utility of short screens with regard to implementation, effect on rates of diagnosis and treatment of dementia patients, and outcomes for patients, families, and health care systems.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".