Cognitive impairment and dependency in activities of daily living: a cross-lagged analysis
Bibliographic record
Abstract
Background: This study investigates the bidirectional relationship between cognitive function and Activities of Daily Living (ADL) at varying levels of cognitive impairment. Specifically, it explores how cognitive function affects Basic Activities of Daily Living (BADL) and Instrumental Activities of Daily Living (IADL) over time, and how changes in ADL impact cognitive function. Method: A retrospective analysis of clinical data was conducted using cross-lagged panel models to examine the relationships between cognitive function and ADL. Cognitive function was measured using the Montreal Cognitive Assessment, while ADL were assessed via standardized measures of both BADL and IADL at two time points. Participants were grouped according to the severity of their initial cognitive impairment, allowing for comparative analysis across different levels of impairment. Results: < 0.001). Subgroup analyses indicated that these associations were most pronounced in individuals with moderate cognitive impairment. Conclusion: This study highlights the significant association between cognitive function and ADL, with lower baseline cognitive function predicting increased dependency, particularly in IADL. The findings emphasize the importance of early cognitive health interventions to prevent further decline in daily functioning, especially in individuals with moderate cognitive impairment.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".