Screening for cognitive impairment among individuals aged 60 years or over: scoping review
Bibliographic record
Abstract
BACKGROUND: Growth in aging of the population has led to increasing numbers of elderly people presenting cognitive impairment and evolution to dementia. There is still no consensus within primary care on the best strategy for screening for cognitive impairment among elderly people. Standardization of a simple but reasonably accurate instrument for a brief cognitive test, in primary care environments, would enable healthcare professionals to identify individuals who require a more in-depth assessment of cognition. OBJECTIVES: To investigate the instruments used by healthcare professionals in studies conducted worldwide and ascertain the most suitable instruments for screening for cognitive impairment among individuals aged 60 years or over, in the Brazilian population. DESIGN AND SETTING: Scoping review developed at Pontifícia Universidade Católica de São Paulo, Brazil. METHOD: A systematic search of the literature was conducted for primary studies using instruments to screen for cognitive impairment among individuals aged 60 years or over, in the MEDLINE, EMBASE, Cochrane Central and LILACS databases. RESULTS: A total of 983 articles were identified by two independent reviewers, from which 49 were selected for full-text reading, based on the criteria defined for this review. From this, 16 articles adhering to the theme of screening for cognitive impairment among the elderly were selected for in-depth analysis. CONCLUSION: The Mini-Mental State Examination was the instrument most cited in these studies. The Pfeffer Functional Activities Questionnaire and the Verbal Fluency Test (semantic category) present characteristics favoring further studies, for testing as screening instruments for cognitive impairment among elderly people in Brazil.
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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 | 0.009 | 0.058 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.021 | 0.018 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".