Determinants of Disability and Disablement in Ontario Long-term Care Residents
Bibliographic record
Abstract
Purpose: Disability is difficulty with or dependence on others to conduct activities of daily living, such as bathing, eating and dressing; disablement is worsening disability measured over time. Among long-term care residents, disability and disablement lower quality of life and increase health care costs. Understanding the determinants of disability and disablement in this population is critical to guide clinical practice and accountability policies in long-term care homes. Methods: This thesis is theoretically grounded in the Disablement Process Model. It consists of a literature review and two retrospective studies done using Ontario health administrative data. Study 1 features a critical literature review and analytic framework of the determinants of disability and disablement in older adults. Study 2 examines the relative effect of long-term care home versus resident characteristics in explaining residentsâ disability. Study 3 focuses on the association between disability and geriatric syndromes present at admission and disablement experienced by long-term care residents over time. Hierarchical linear regression models were used in both Studies 2 and 3. Implications: The conceptually-grounded, evidence-based analytic framework from Study 1 can be used to advance future research on disability and disablement in older adults, whether or not they live in the community or long-term care. Study 2 demonstrates that the majority of variation in disability among Ontario long-term care home residents is explained by residentsâ geriatric syndromes, not characteristics of the homes in which they live. Study 3 shows that residents with lower disability at admission become disabled more rapidly over the course of their stay; our exploration of possible mechanisms for this finding is relevant to frontline providers and researchers alike.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".