Perspective: leveraging review protocols to advance implementation science in support of older adults’ health equity
Bibliographic record
Abstract
Globally, there has been an increasing call for dissemination and implementation science to improve the health equity of older adults. However, improving the health equity of older adults requires methods that allow for an in-depth understanding of the existing research. While the value of review articles is widely recognized, the value of publishing review protocols is an emerging paradigm with great potential to advance implementation science and aging research. In this article, we propose that prior to review articles, review protocols are necessary as they provide a clear and comprehensive search strategy, which greatly enhances the quality and rigor of reviews. More specifically, we argue that review protocols are indispensable because they support: (1) a clearly defined and comprehensive search methodology; (2) reviewer feedback to mitigate potential issues; and (3) registration to reduce risk of research replication. Additionally, we propose three strategies to accelerate review protocols in implementation science to support older adults' health equity.
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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 | 0.849 | 0.926 |
| Meta-epidemiology (narrow) | 0.003 | 0.005 |
| Meta-epidemiology (broad) | 0.006 | 0.010 |
| Bibliometrics | 0.012 | 0.011 |
| Science and technology studies | 0.005 | 0.024 |
| Scholarly communication | 0.032 | 0.051 |
| Open science | 0.014 | 0.019 |
| Research integrity | 0.053 | 0.054 |
| Insufficient payload (model declined to judge) | 0.011 | 0.008 |
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; the direct Gemma label and the distilled Codex classifier 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".