Assessment of Occupational Competence in Dementia: Identifying Key Components of Cognitive Competence and Examining Validity of the Cognitive Competency Test
Bibliographic record
Abstract
Considering the links between dementia and everyday living, occupational therapists are called upon to make recommendations regarding appropriate living arrangements for persons with dementia. Re-framed as occupational competence, this is often accomplished by an evaluation of cognitive competence. Within the context of an aging population, a key question is how to best inform decisions regarding occupational competence, using cognitive competence as an indicator. The Cognitive Competency Test (CCT) is a tool used to evaluate cognitive competence and inform judgments about occupational competence in individuals with dementia. This thesis incorporates two studies that identified cognitive components that predict occupational competence in individuals with dementia, and examined the construct validity of the CCT, using a framework developed by Samuel Messick. A Delphi study, conducted amongst Canadian occupational therapists with experience in dementia care, generated a consensus regarding the components of cognitive competence essential to predict occupational competence in persons with dementia. A second study employed a retrospective chart review and examined the dimensional structure of the CCT and its relationship with other clinical measures typically used in dementia care. Occupational therapists identified ten cognitive components essential to predict occupational competence in individuals with dementia. The structure of the CCT is a unitary factor that demonstrates correlations to some clinical measures commonly used in dementia care. These findings give some support to the validity of the CCT and have implications for development of new measures and education regarding cognitive competence, pointing to the need to address other factors identified in the Delphi.
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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 | 0.013 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".