Literacy and health literacy as defined in cancer education research: A systematic review
Bibliographic record
Abstract
Background Limited literacy and health literacy are associated with lack of cancer screening and later stage cancer diagnoses. Objective To systematically review the literature for definitions of literacy and health literacy as related to patient access, use, and comprehension of cancer prevention and treatment education. Methods Original research articles written from 1992 to 2006 inclusive with the terms health literacy and/or literacy in the title, abstract or key words and explicitly linked to cancer information were found by searching MEDLINE, PsycINFO, CSA Sociological Abstracts, Social Sciences Citation Index, and Cumulative Index to Nursing and Allied Health Literature (CINAHL). Results A final sample of 78 studies was included in this review. Fortyfive articles mentioned literacy, seven were on health literacy, and 26 discussed both literacy and health literacy. Only 15 articles (19.2 per cent) defined literacy and/or health literacy. Conclusion This systematic review indicates that definitions of literacy and health literacy are not being used consistently in the cancer education literature. Best practice definitions of literacy and health literacy are important, especially when screening individuals for their understanding of cancer prevention and treatment information.
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 | 0.013 | 0.073 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.013 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".