Development of a community toolkit for identifying and managing mild cognitive impairment among older adults
Bibliographic record
Abstract
Objective To develop a toolkit suitable for assisting community health institutions in the early identification and intervention of mild cognitive impairment (MCI) among older adults. Methods A literature review was conducted to construct a draft of the identification and intervention toolkit. Tools with an expert approval rate above 70% were included after expert consultation. The final version of the toolkit was developed by integrating these tools with officially recommended tools in China. Results The expert consultation yielded an authority coefficient of 0.84. The finalized toolkit included the assessment tools of Mini-Mental State Examination, Montreal Cognitive Assessment, General Practitioner Assessment of Cognition, Cognitive Abilities Screening Instrument and Clock Drawing Test, and 18 intervention measures including pharmacological treatment, cognitive training and psychological interventions, etc. Conclusion The MCI Identification-Intervention Toolkit may serve as a reference for guiding the identification and intervention of MCI among older adults for community health institutions.
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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 | 0.034 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".