Social Determinants of Health Screening Tools for Adults in Primary Care: Protocol for a Scoping Review
Bibliographic record
Abstract
BACKGROUND: Social determinants of health (SDH) have been shown to be predictors of health outcomes. Integrating SDH screening tools into primary care may help identify individuals or groups with a greater burden of social vulnerability and promote health equity. OBJECTIVE: This study aimed (1) to identify the existing screening tools to assess social deprivation in adults in primary care settings; (2) to describe the characteristics of these tools and, where appropriate, their psychometric properties; (3) to describe their validity and reliability in those scales in which validation processes have been conducted; and (4) to identify evidence gaps and provide recommendations for future research. METHODS: This study protocol was structured according to the Joanna Briggs Institute methodology for scoping reviews and reported according to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines. Furthermore, since not all SDH assessment tools are published as scientific papers, we will use a slightly modified form of the scoping review framework to retrieve specific information about specific tools for screening SDH in primary care contexts. The following electronic databases will be searched by 2 reviewers: MEDLINE (via PubMed), CINAHL Plus, Web of Science, and Scopus. In addition, the following sources will also be searched for gray literature: DART-Europe E-thesis Portal, OpenGrey, and Google Scholar. After the revision of inclusion and exclusion criteria, the titles, abstracts, and full text of the included studies will be separately screened by 2 reviewers. A PRISMA-ScR flowchart will be used to depict the sources of evidence screened, and data charting will be used to gain in-depth knowledge. The findings of the scoping review will be presented in both narrative and tabular formats, summarizing the existing literature on tools used for SDH in primary care settings. A critical analysis will be undertaken to address the variability in tool validation, cultural adaptability, and integration into different health care systems. Finally, key gaps in the existing evidence will be explored, and research priorities will be proposed, emphasizing the need for screening tools that are culturally sensitive, scalable, and easily integrated into primary care workflows. This critically appraised information may be useful for implementing SDH screening tools in primary care settings and may contribute to future research addressing feasibility and validation studies in different primary health care systems. RESULTS: The study began in July 2024. Data collection is expected to be completed in April 2025, with publication expected in October 2025. CONCLUSIONS: This scoping review will provide a comprehensive and critical description of the available tools aimed at screening SDH in primary care settings. Incorporating these tools into routine care has been recognized as a key strategy for addressing health inequalities, given the growing evidence base on the influence of SDH on health outcomes. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/68668.
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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 | 0.103 | 0.098 |
| Meta-epidemiology (narrow) | 0.005 | 0.006 |
| Meta-epidemiology (broad) | 0.011 | 0.015 |
| Bibliometrics | 0.016 | 0.015 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.086 | 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, 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".