Daily Living Activities as Indicators of Mild Cognitive Impairment and Subjective Cognitive Decline
Bibliographic record
Abstract
Abstract Objectives: With aging, we gradually lose our functional ability which is assessed through understanding the difficulty of doing activities of daily living (ADL). Advanced ADL (AADL) performance steadily worsens with declining cognitive function, followed by instrumental ADL (IADL) performance, and finally, the incapacity to do basic ADLs. In this study, we intended to early identify mild cognitive impairment (MCI) and to focus on understanding the ADLs as an indicator to differentiate between the elderly with MCI and subjective memory complaint (SMC). Methods: The study sample consisted of 30 patients with SMC and MCI, respectively, within the age of 60–80 years with at least eight years of education and being noninstitutionalized. Those patients were divided into the two groups based on the diagnostic criteria. Furthermore, Montreal Cognitive Assessment and Clinical Dementia Rating (CDR) Scale were used for screening. AADL scale was used for assessing the performance on AADL. Results: The study findings showed that a significant difference existed between the MCI and SMC groups in ADLs ( p < 0.05). We also found that significantly higher difficulties in the item in shopping alone for clothes, household necessities, or groceries ( p < 0.001), remembering appointments, family occasions, holidays, medications ( p < 0.001), preparing a balanced meal ( p < 0.01), and assembling tax records, business affairs, and papers ( p < 0.05). Conclusion: The study findings indicate that IADLs and AADLs can be considered as indicators of MCI and SCD.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".