A literature review of health literacy competency for health professionals
Bibliographic record
Abstract
Purpose: This study aimed to provide a descriptive review of health literacy competency questionnaires and to identify their attributes for developing a health literacy competency measurement tool to be used by Korean health professionals.Methods: A literature review was conducted through a search in international and Korean databases (PubMed, CINAHL, RISS, and KISS) for articles published between 2010 and 2024. A total of 2,200 articles were explored, out of which 6 studies met the inclusion criteria.Results: In Canada, an initial set of health literacy competency questionnaires was developed; subsequently, two questionnaires were developed in China and Brazil. Another study was translated using the initial Canadian study questionnaires, and two studies were modified. All six studies meeting the inclusion criteria employed a Delphi process involving 20~41 expert panels. Among the six studies, only one reported the psychometric properties of the questionnaires used. The reviewed questionnaires comprised knowledge, attitude, skills, and practice domains based on Bloom’s taxonomy. Knowledge and skills were commonly included factors in the questionnaires.Conclusion: There were 17 knowledge, 10 attitude, 13 skills, and 13 practice attributes for each area of the reviewed questionnaires. “Easy-to-read materials,” “plain language,” and “teach-back” were identified as appropriate attributes for measuring health literacy competencies. Among the questionnaires, there were many items and many overlapping items between the domains. Further studies are required to refine their essential attributes and to verify the instruments’ psychometric properties in order to increase their feasibility.
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 | 0.007 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.020 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| 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".