Gaps in the System: Supporting People Living With Dementia and Their Caregivers
Bibliographic record
Abstract
Abstract As individuals are living longer, the prevalence of older adults living with dementia and other complex health and social care needs is on the rise (Alzheimer’s Association, 2020; CIHI, 2020). Correspondingly, efforts to develop supportive programming and policies for persons living with dementia (PLWDs) are of paramount importance (CIHR, 2019). The challenges faced by PLWDs and other complex health and social needs are widely known (CIHR, 2019), however, a systematic understanding of how and if current and long-standing efforts are adequately meeting the needs of these individuals remains elusive. This research sought to understand how program administrators, decision makers, PLWD, and caregivers across five North American jurisdictions (British Columbia, Ontario, Newfoundland and Labrador, New York State, and Vermont) perceived specific dementia care programs and support services within their respective jurisdictions. We performed an inductive analysis of semi-structured interviews (N=37) and identified on-going care gaps experienced by participants. We present three main gaps: 1) disconnected and uncoordinated system infrastructure, 2) lack of comprehensive services to meet the diverse needs of PLWD and their caregivers, and 3) inconsistency in how dementia is understood; with associated perceived remedies. The results suggest that even when attempts to address the needs of PLWD and their caregivers are put in place there remains significant limitations of systems. The perspectives of decision makers, program administrators and individuals with lived experience offer unique insight into how these experiences may be improved to better support the complex needs of PLWD and their caregivers.
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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 | 0.011 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.020 | 0.013 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".