Identifying what matters most for the health of older adults in Alberta: results from a James Lind Alliance Research Priority Setting Partnership
Bibliographic record
Abstract
BACKGROUND: As the number of older adults continues to increase, addressing their health becomes increasingly important for both the population and the health care system. The aim of this priority setting partnership was to use direct engagement with older adults, caregivers and health care providers to identify and prioritize the most important topics on the health of older adults that should be addressed by future research. METHODS: We followed the James Lind Alliance method. We conducted an initial online and paper survey from Jan. 22 to May 2, 2018, with older adults in Alberta aged 65 years and older to identify what respondents saw as being most important for the health of older adults. We formed responses into summary questions and checked them against existing evidence. We administered a second survey (July 3 to Aug. 2, 2018) to shortlist summary questions and held an in-person workshop (Aug. 30, 2018) to rank the list through discussion and shared decision-making. RESULTS: We recruited 670 participants (32.7% older adults, 19.7% caregivers, 46.9% health and social care workers) in the initial survey to tell us what topics on the health of older adults mattered most to them. Over 3000 responses generated 101 summary questions, of which only 4 were completely answered by existing evidence. The second prioritization survey was completed by 232 participants (28.4% older adults, 24.6% care partners, 47.0% health and social care workers) to produce a shortlist of 22 high priority questions. Twenty-two attendees participated in the summary workshop to create a prioritized list of 10 questions for future research that address aspects of the health system, provision of care and living well in older adulthood. INTERPRETATION: Older adults, caregivers and clinicians collectively produced a prioritized list of questions that matter most to older adults' health in Alberta. Provincial researchers and research funders should consider these unmet knowledge needs of end-users in future endeavours.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".