Bibliographic record
Abstract
Health literacy (HL) is an essential capacity for living a healthy life. Limited levels of HL are a significant public health issue because of its prevalence and its negative implications for health-care costs, health-care quality, and health outcomes. Given that chronic disease is the leading global cause of death and disability, having the necessary skills to make daily health-related decisions and the capacity to navigate the health-care system is paramount. HL refers not only to the abilities of individuals, but also to the health-related systems and providers of information within those systems. While the concept of HL first appeared in the literature almost fifty years ago, the evolving concept has been informed by three main areas: (1) health care; (2) health promotion; and (3) education. It is important to note that the initial interest in HL in the United States was led by physicians with a medical perspective. However, over the past two decades interest in HL has grown in other countries, such as Canada, Australia, the United Kingdom, and the European Union as well as African and Asian countries, led by people with a background in the social sciences and health promotion. HL as an emerging field of research, practice, and policy has the potential to increase our understanding of both noncommunicable diseases (NCDs) and health promotion in the global context. This article provides a context for HL in relation to NCDs. It offers a collection of key resources (such as textbooks, journals, reports, websites, etc.) to provide insights into the concept of HL, the relevance and role of NCDs, and evidence of the effectiveness of HL interventions in relation to chronic disease prevention and management.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".