Protocol of a feasibility study for cognitive assessment of an ageing cohort within the Southeast Asia Community Observatory (SEACO), Malaysia
Bibliographic record
Abstract
INTRODUCTION: There is a growing proportion of population aged 65 years and older in low-income and middle-income countries. In Malaysia, this proportion is predicted to increase from 5.1% in 2010 to more than 15.4% by 2050. Cognitive ageing and dementia are global health priorities. However, risk factors and disease associations in a multiethnic, middle-income country like Malaysia may not be consistent with those reported in other world regions. Knowing the burden of cognitive impairment and its risk factors in Malaysia is necessary for the development of management strategies and would provide valuable information for other transitional economies. METHODS AND ANALYSIS: This is a community-based feasibility study focused on the assessment of cognition, embedded in the longitudinal study of health and demographic surveillance site of the South East Asia Community Observatory (SEACO), in Malaysia. In total, 200 adults aged ≥50 years are selected for an in-depth health and cognitive assessment including the Mini Mental State Examination, the Montreal Cognitive Assessment, blood pressure, anthropometry, gait speed, hand grip strength, Depression Anxiety Stress Score and dried blood spots. DISCUSSION AND CONCLUSIONS: The results will inform the feasibility, response rates and operational challenges for establishing an ageing study focused on cognitive function in similar middle-income country settings. Knowing the burden of cognitive impairment and dementia and risk factors for disease will inform local health priorities and management, and place these within the context of increasing life expectancy. ETHICS AND DISSEMINATION: The study protocol is approved by the Monash University Human Research Ethics Committee. Informed consent is obtained from all the participants. The project's analysed data and findings will be made available through publications and conference presentations and a data sharing archive. Reports on key findings will be made available as community briefs on the SEACO website.
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 | 0.078 | 0.055 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.054 | 0.016 |
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".