A systematic review protocol for assessing equity in clinical practice guidelines for traumatic brain injury and homelessness
Bibliographic record
Abstract
Background: When used optimally, clinical practice guidelines (CPGs) can reduce inappropriate variations in practice, improve application of research to practice, and enhance the quality of healthcare. However, a common criticism, despite its potential, is the lack of consideration for equity and disadvantaged populations. Objectives: This protocol is for a systematic review of CPGs for traumatic brain injury (TBI) and homelessness that aims to assess (1) the extent to which evidence regarding TBI and homelessness is integrated in CPGs for homelessness and TBI, respectively, and (2) equity considerations in CPGs for TBI and homelessness. Methods and analysis: The methodology for this review is guided by the PRISMA-P, validated search filters for CPGs, and methodological guides to searching systematic reviews and gray literature. CPGs will be identified from (a) databases for peer-reviewed literature (MEDLINE, Embase, CINAHL, and PsycInfo), (b) targeted websites and Google Search for gray literature, and (c) reference lists of peer-reviewed and gray literature that meet the eligibility criteria. Searching for gray literature, including from guideline-specific resources, is a critical component of this review and is considered an efficient approach to identifying CPGs, given the low precision of searching peer-reviewed databases. Two independent reviewers will screen all articles based on pre-determined eligibility criteria. A narrative synthesis will be conducted to identify the proportion of CPGs that integrate evidence about TBI and homelessness and how TBI and homelessness is or is not integrated in CPGs. Quality appraisal will take the form of an equity assessment of CPGs and will be completed independently by two reviewers. Conclusion: This protocol outlines the methodology for a systematic review of CPGs for TBI and homelessness. The resulting systematic review from this protocol will form an evidence-based foundation to advance CPGs for individuals with lived experience of TBI and homelessness. Systematic review registration: identifier: CRD42021287696.
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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 | 0.238 | 0.298 |
| Meta-epidemiology (narrow) | 0.006 | 0.007 |
| Meta-epidemiology (broad) | 0.018 | 0.020 |
| Bibliometrics | 0.020 | 0.024 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.007 | 0.007 |
| Research integrity | 0.012 | 0.012 |
| Insufficient payload (model declined to judge) | 0.097 | 0.020 |
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".