Improving the usefulness of evidence concerning the effectiveness of implementation strategies for knowledge products in primary healthcare: Protocol for a series of systematic reviews
Bibliographic record
Abstract
Abstract Background : The literature on the implementation of knowledge products is extensive. However, this literature is still difficult to interpret for policymakers and other stakeholders when faced with choosing implementation strategies likely to bring about successful change in their health systems. This work has the particularity to examine the scope of this literature, and to clarify the effectiveness of implementation strategies for different knowledge products. Consequently, we aim to: 1) determine the strengths and weaknesses of existing literature overviews; 2) produce a detailed portrait of the literature on implementation strategies for various knowledge products; and 3) assess the effectiveness of implementation strategies for each knowledge product identified and classify them. Methods : We will use a three-phase approach consisting of a critical analysis of existing literature overviews, a systematic review of systematic reviews, and a series of systematic reviews and meta-analyses. We will follow the Cochrane Methodology for each of three phases. Our eligibility criteria are defined following a PICOS approach: Population , individuals or stakeholders participating in healthcare delivery, specifically, healthcare providers, caregivers, and end users; I ntervention, any type of strategy aiming to implement a knowledge product including, but not limited to, a decision support tool, a clinical practice guideline, a policy brief, or a decision-making tool, a one-pager, or a health intervention; Comparison, any comparator will be considered; Outcomes, Phases 1 and 2 – any outcome related to implementation strategies including, but not limited to, the measures of adherence/fidelity to the use of knowledge products, their acceptability, adoption, appropriateness, feasibility, adaptability, implementation costs, penetration/reach and sustainability; Phase 3 – any additional outcome related to patients (psychosocial, health behavioral, and clinical outcomes) or healthcare professionals (behavioral and performance outcomes); Setting , primary healthcare has to be covered. For each phase, two reviewers will independently perform the selection of studies, data extraction, and assess their methodological quality. We will analyze extracted data, and perform narrative syntheses and meta-analyses when possible. Discussion : Our results could inform not only the overviews’ methodology, but also the development of an online platform for the implementation strategies of knowledge products. This platform could be useful for stakeholders in implementation science.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Systematic review | low |
| gpt | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
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 | 0.191 | 0.285 |
| Meta-epidemiology (narrow) | 0.009 | 0.009 |
| Meta-epidemiology (broad) | 0.022 | 0.034 |
| Bibliometrics | 0.020 | 0.021 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.010 | 0.014 |
| Open science | 0.007 | 0.009 |
| Research integrity | 0.013 | 0.011 |
| Insufficient payload (model declined to judge) | 0.058 | 0.012 |
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, unvalidatedLabeled directly by 2 models reading the full record.
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".