An exploration of how guideline developer capacity and guideline implementability influence implementation and adoption: study protocol
Bibliographic record
Abstract
BACKGROUND: Practice guidelines can improve health care delivery and outcomes but several issues challenge guideline adoption, including their intrinsic attributes, and whether and how they are implemented. It appears that guideline format may influence accessibility and ease of use, which may overcome attitudinal barriers of guideline adoption, and appear to be important to all stakeholders. Guideline content may facilitate various forms of decision making about guideline adoption relevant to different stakeholders. Knowledge and attitudes about, and incentives and capacity for implementation on the part of guideline sponsors may influence whether and how they develop guidelines containing these features, and undertake implementation. Examination of these issues may yield opportunities to improve guideline adoption. METHODS: The attributes hypothesized to facilitate adoption will be expanded by thematic analysis, and quantitative and qualitative summary of the content of international guidelines for two primary care (diabetes, hypertension) and institutional care (chronic ulcer, chronic heart failure) topics. Factors that influence whether and how guidelines are implemented will be explored by qualitative analysis of interviews with individuals affiliated with guideline sponsoring agencies. DISCUSSION: Previous research examined guideline implementation by measuring rates of compliance with recommendations or associated outcomes, but this produced little insight on how the products themselves, or their implementation, could be improved. This research will establish a theoretical basis upon which to conduct experimental studies to compare the cost-effectiveness of interventions that enhance guideline development and implementation capacity. Such studies could first examine short-term outcomes predictive of guideline utilization, such as recall, attitude toward, confidence in, and adoption intention. If successful, then long-term objective outcomes reflecting the adoption of processes and associated patient care outcomes could be evaluated.
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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 | 0.119 | 0.125 |
| Meta-epidemiology (narrow) | 0.002 | 0.004 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.051 | 0.013 |
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".