Social Determinants of Health and Disparities in Pediatric Trauma Care: Protocol for a Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Abstract Background Social determinants of health (SDH), including "the conditions in which individuals are born, grow, work, live and age" affect child health and well-being. Several studies have synthesized evidence about the influence of SDH on childhood injury risks and outcomes. However, there is no systematic evidence about the impact of SDH on accessing care and quality of care once a child has suffered an injury. We aim to evaluate the extent to which access to care and quality of care after injury are affected by children and adolescents’ SDH. Methods Using Cochrane methodology, we will conduct a systematic review including observational and experimental studies evaluating the association between social/material elements contributing to health disparities, using the PROGRESS-Plus framework: Place of residence, Race/ethnicity/culture/language, Occupation, Gender/sex, Religion, Education, Socioeconomic status, and Social capital and care received by children and adolescents (≤ 19 years of age) after injury. We will consult published literature using PubMed, EMBASE, CINAHL, PsycINFO, Web of Science, and Academic Search Premier and grey literature using Google Scholar from their inception to a maximum of six months prior to submission for publication. Two reviewers will independently perform study selection, data extraction, and risk of bias assessment for included studies. Risk of bias will be assessed using the ROBINS-E and ROB-2 tools respectively for observational and experimental study designs. We will analyze data to perform narrative syntheses and if enough studies are identified, we will conduct a meta-analysis using random effects models. Discussion This systematic review will provide a synthesis of evidence on the association between SDH and pediatric trauma care (access to care and quality of care) that clinicians and policymakers can use to better tailor care systems and promote equitable access and quality of care for all children. We will share our findings through clinical rounds, conferences, and publication in a peer-reviewed journal. Systematic review registration : This review has been registered in the PROSPERO database (ID: CRD42023408467)
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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 | 0.091 | 0.131 |
| Meta-epidemiology (narrow) | 0.008 | 0.006 |
| Meta-epidemiology (broad) | 0.028 | 0.041 |
| Bibliometrics | 0.014 | 0.014 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.007 | 0.006 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.093 | 0.009 |
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".