Critical considerations for the practical utility of health equity tools: a concept mapping study
Bibliographic record
Abstract
BACKGROUND: Promoting health equity within health systems is a priority and challenge worldwide. Health equity tools have been identified as one strategy for integrating health equity considerations into health systems. Although there has been a proliferation of health equity tools, there has been limited attention to evaluating these tools for their practicality and thus their likelihood for uptake. METHODS: Within the context of a large program of research, the Equity Lens in Public Health (ELPH), we conducted a concept mapping study to identify key elements and themes related to public health leaders and practitioners' views about what makes a health equity tool practical and useful. Concept mapping is a participatory mixed-method approach to generating ideas and concepts to address a common concern. Participants brainstormed responses to the prompt "To be useful, a health equity tool should…" After participants sorted responses into groups based on similarity and rated them for importance and feasibility, the statements were analyzed using multidimensional scaling, then grouped using cluster analysis. Pattern matching graphs were constructed to illustrate the relationship between the importance and feasibility of statements, and go-zone maps were created to guide subsequent action. RESULTS: The process resulted in 67 unique statements that were grouped into six clusters: 1) Evaluation for Improvement; 2) User Friendliness; 3) Explicit Theoretical Background; 4) Templates and Tools 5) Equity Competencies; and 6) Nothing about Me without Me- Client Engaged. The result was a set of concepts and themes describing participants' views of the practicality and usefulness of health equity tools. CONCLUSIONS: These thematic clusters highlight the importance of user friendliness and having user guides, templates and resources to enhance use of equity tools. Furthermore, participants' indicated that practicality was not enough for a tool to be useful. In addition to practical characteristics of the tool, a useful tool is one that encourages and supports the development of practitioner competencies to engage in equity work including critical reflections on power and institutional culture as well as strategies for the involvement of community members impacted by health inequities in program planning and delivery. The results of this study will be used to inform the development of practical criteria to assess health equity tools for application in public health.
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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 | 0.118 | 0.171 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.005 |
| Science and technology studies | 0.013 | 0.015 |
| Scholarly communication | 0.012 | 0.016 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".