The association between late-life cognitive test scores and retrospective informant interview data
Bibliographic record
Abstract
BACKGROUND: Cognitive assessment of older persons, particularly those with impairment, is hampered by measurement error and the ethical issues of testing people with dementia. A potential source of valuable information about end-of-life cognitive status can be gained from those who knew the respondent well - mostly relatives or friends. This study tested the association between last cognitive assessment before death and a retrospective informant assessment of cognition. METHODS: Data were analyzed from 248 participants from the Medical Research Council Cognitive Function and Ageing Study who were aged 71 to 102 years at death. Late-life cognition was assessed 0 to 8 years before death using the Mini-mental State Examination (MMSE) and the informant measure was taken 0 to 7 years after death using a Retrospective Informant Interview (RInI). RESULTS: Zero-inflated Poisson regression showed a strong association between MMSE scores and RInI scores - those scoring 29-30 on the MMSE had a RInI score four times lower than those who scored <18 (p < 0.001). The time between MMSE and death was also a significant predictor with each additional year increasing RInI scores by 12.4% (p < 0.001). The time between death and RInI was only a significant predictor when including measures that were taken four years or more after death. CONCLUSIONS: Cognitive scores from retrospective informant interviews are strongly associated with late-life MMSE scores taken close to death. This suggests that the RInI can be used as a proxy measure of cognition in the period leading up to death.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".