The Use of Spatial Analysis in Syphilis-Related Research: Protocol for a Scoping Review
Bibliographic record
Abstract
BACKGROUND: Latin America, Africa, and Asia have high incidences of syphilis. New approaches are needed to understand and reduce disease transmissibility. In health care, spatial analysis is important to map diseases and understand their epidemiologic aspects. OBJECTIVE: The proposed scoping review will identify and map the use of spatial analysis as a tool for syphilis-related research in health care. METHODS: This protocol was based on the Joanna Briggs Institute manual, guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR). We will conduct searches in Embase; Lilacs, via the Virtual Health Library (Biblioteca Virtual en Salud; BVS), in Portuguese and English; Medline/PubMed; Web of Science; Cumulative Index to Nursing and Allied Health Literature (CINAHL); and Scopus. Gray literature will be searched for in Google Scholar, the Digital Library of Theses and Dissertations, the Catalog of Theses and Dissertations of the Coordination of Improvement of Higher Education Personnel (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; CAPES), Open Access Theses and Dissertations, ProQuest Dissertations and Theses Global, and the Networked Digital Library of Theses and Dissertations. The main research question is "How has spatial analysis been used in syphilis-related research in health care?" Studies are included if they have the full text available, address syphilis, and use geographic information systems software and spatial analysis techniques, regardless of sample characteristics or size. Studies published as research articles, theses, dissertations, and government documents will also be considered, with no location, time, or language restrictions. Data will be extracted using a spreadsheet adapted from the Joanna Briggs Institute. Quantitative and qualitative data will be analyzed using descriptive statistics and a thematic analysis, respectively. RESULTS: The results will be presented according to the PRISMA-ScR guidelines and will summarize the use of spatial analysis in syphilis-related research in health care in countries with different contexts, factors associated with spatial cluster formation, population health impacts, contributions to health systems, challenges, limitations, and possible research gaps. The results will guide future research and may be useful for health and safety professionals, managers, public policy makers, the general population, the academic community, and health professionals who work directly with people with syphilis. Data collection is projected to start in June 2023 and end in July 2023. Data analysis is scheduled to take place in August and September 2023. We expect to publish results in the final months of 2023. CONCLUSIONS: The review may reveal where syphilis incidence has the highest incidence, which countries most use spatial analysis to study syphilis, and whether spatial analysis is applicable to syphilis in each continent, thereby contributing to discussion and knowledge dissemination on the use of spatial analysis as a tool for syphilis-related research in health care. TRIAL REGISTRATION: Open Science Framework CNVXE; https://osf.io/cnvxe. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/43243.
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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 | 0.160 | 0.206 |
| Meta-epidemiology (narrow) | 0.006 | 0.007 |
| Meta-epidemiology (broad) | 0.014 | 0.017 |
| Bibliometrics | 0.021 | 0.019 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.006 | 0.010 |
| Research integrity | 0.013 | 0.009 |
| Insufficient payload (model declined to judge) | 0.082 | 0.017 |
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".