Functional profiles of older adults from the dementia continuum: Analyzing critical errors that occurred during an IADL ecological evaluation
Bibliographic record
Abstract
Abstract Background Older adults with Alzheimer disease (AD) or mild cognitive impairment (MCI) experience challenges that affect their independence. Instrumental activities of daily living (IADLs) are critical in assessing the independence. Single errors can have considerable impact, as they can lead to institutionalization. Thus, optimal recommendations regarding independence depends on an accurate analysis of IADL, including a fine grain analysis of the type of critical errors. Our study aim to describe the errors produced by older adults from the dementia continuum (AD, MCI and older adults living in the community with no dementia) when performing IADL. More specifically, our objectives are to understand: (1) What are the main types of errors occurring during IADL and (2) When are these errors more likely to occur. Method We conducted a performance based IADL assessment with older adults (n = 24), including 7 with AD, 8 with MCI, and 9 without dementia. We used the IADL Profile[1], which is a standardized assessment based on ecological observation of 8 IADL tasks. For each task, observations of performance are grouped into 4 operations: (1) formulate a goal, (2) plan, (3) execute, and (4) achieve the goal. Based on video recordings of the sessions, participants performances were transcribed into verbatim reports of all the errors that occurred. Deductive qualitative analysis and descriptive statistical analysis (standard deviation and correlation) were used to categorize/count the main type of errors for each task. Result Our results highlighted that (1) older adults make several errors while performing IADLs, with a higher occurrence according to the advancement along the dementia continuum and some of which may be crucial to the person’s independence; (2) the most frequent errors for all participants were in formulating a goal and in planning a task and (3) these errors are likely to occur during grocery shopping and meal preparation. Conclusion The fine grain analysis of errors during the performance of IADL allows us to better identify the needs of older adults from the dementia continuum that can service to guide the selection of effective strategies that can optimize their safety and functional independence. [1] Bottari et al. (2009)
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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 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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 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".