A modified Delphi and cross-sectional survey to facilitate selection of optimal outcomes and measures for a systematic review on geriatrician-led care models
Bibliographic record
Abstract
OBJECTIVE: The objective of this study was to identify relevant outcomes and measures to inform a systematic review (SR) on the comparative effectiveness of geriatrician-led care models. STUDY DESIGN AND SETTING: In the modified Delphi to select outcomes for inclusion in the SR, knowledge users (KUs) from Ontario, Alberta, and Saskatchewan rated outcome importance using a Likert scale. A survey was then completed by geriatricians to determine optimal measures for selected outcomes. Findings were analyzed using frequencies, means, and standard deviations (SDs). RESULTS: Thirty-three KUs (patients, caregivers, policymakers and geriatricians) rated 27 outcomes in round 1 of the modified Delphi. Top-rated outcomes included function (mean 6.85 ± SD 0.36), cognition (6.47 ± SD 0.72), and quality of life (6.38 ± SD 0.91). Twenty-three KUs participated in round 2 and rated 24 outcomes. Top-rated outcomes in round 2 were function (6.87 ± SD 0.34), quality of life (6.45 ± SD 1.10), and cognition (6.43 ± SD 0.73). The survey was completed by 22 geriatricians and the highest ranked measures were Activities of Daily Living (function), Mini-Mental State Examination (cognition), and the Medical Outcomes Study SF-36 (quality of life). CONCLUSION: We identified the most relevant outcomes and measures for patients, caregivers, policymakers, and geriatricians, allowing us to tailor the SR to KU needs.
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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 | 0.121 | 0.292 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.011 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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; both teacher heads agree on what is shown here.
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".