An examination of instrumental activities of daily living assessment in older adults and mild cognitive impairment
Bibliographic record
Abstract
Basic activities of daily living (ADL) are self-maintenance abilities such as dressing or bathing. Instrumental ADL (IADL) are more complex everyday tasks, such as preparing a meal or managing finances (Lawton & Brody, 1969). IADL questionnaires play an important role in assessing the functional abilities of older adults and evaluating the impact of cognitive impairment on routine activities. This paper examined the cognitive processes that underlie IADL performance and concluded that the accurate and reliable execution of IADL likely draws upon the integrity of a wide range of cognitive processes. This review examined IADL in mild cognitive impairment (MCI) because of the controversial nature of distinguishing a significant decline in functional abilities in those with MCI versus dementia or MCI versus cognitively normal aging. The challenges of investigating IADL empirically were explored, as well as some of the reasons for the inconsistent findings in the literature. A review of questionnaire-based assessments of IADL indicated that: MCI can be distinguished statistically from healthy older adults and dementia, individuals with multiple domain MCI are more impaired on IADL than those with single domain MCI, mild IADL changes can be predictive of future cognitive decline, and the ability to manage finances may be among the earliest IADL changes in MCI and a strong predictor of conversion to dementia. This paper concluded with recommendations for more sensitive and reliable IADL questionnaires.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".