Health and Wellness Literacy Initiatives for Immigrant Populations Delivered Through Faith-Based Entities
Bibliographic record
Abstract
Background: Health literacy has been shown to be low among immigrant populations globally, leading to limited ability to locate, access and use health information. Religious entities are often the initial contact for many immigrants regarding health and social supports, there are a lack of knowledge about how initiatives to improve health literacy of the immigrant population may be offered through faith-based entities. The objective of this proposed scoping review is to identify available evidence on health literacy initiatives delivered through faith-based entities for immigrant populations. Methods/Design: Using a scoping review framework we will complete a comprehensive search of relevant keywords in major academic and grey literature databases. Eligible articles will be identified through screening by two independent reviewers according to predefined inclusion and exclusion criteria to include articles relevant to our research question. Selected articles will be charted into data extraction tables for analysis, synthesis and presentation of narrative description and visual graphics. Discussion: This scoping review will identify and assess existing health literacy initiatives delivered through faith-based entities to improve health literacy of immigrant communities. This review will inform which initiatives are commonly practiced, and which immigrant groups are most benefitted from and can potentially be benefitted. It will also describe how to conduct those initiatives and what resources are needed and identify the stakeholders of such initiatives those needed to be engaged with to conduct a successful and acceptable program. The challenges and facilitators of those initiatives will also be identified.
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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 | 0.018 | 0.058 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".