Health Literacy in Health Professionals Two Years into the COVID-19 Pandemic: Results From a Scoping Review
Bibliographic record
Abstract
BACKGROUND: Health literacy (HL) is an important public health goal but also crucial in individuals providing medical care. During the pandemic, COVID-19-related HL of health professionals (HPs) has gained momentum; it helps to minimize the risk of self-infection, on the one hand, and to protect patients and relatives from infection, on the other. However, comprehensive information about the levels of individual pandemic-related HL in HPs is scarce. OBJECTIVE: In this paper, we aimed at describing the extent of existing research on HL (concept) conducted in HPs (population) in the COVID-19 pandemic (context). The review intends to map the literature on HL in HPs, thereby highlighting research gaps. METHODS: This scoping review was conducted using the methodology of Khalil et al (2016). This involved an electronic search of PubMed (MEDLINE) and PsycInfo and a hand search. The included studies were iteratively examined to find items representing the four HL dimensions of access, understand, critically appraise, and apply COVID-19-related health information. RESULTS: The search yielded a total of 3875 references. Only 7 (1.4%) of the 489 included studies explicitly stated to have addressed HL; 2 (0.4%) studies attempted to develop an instrument measuring COVID-19-related HL in HPs; 6 (1.2%) studies included an HL measure in an observational survey design. Of the remainder, the vast majority used a cross-sectional design. The dimensions access and understand were frequently examined, but few studies looked at the dimensions critical appraisal or apply. Very few studies reported an intervention aiming to improve a COVID-19-related HL outcome. CONCLUSIONS: High levels of COVID-19-related HL among HPs are necessary to ensure not only safe practice with necessary protection of HPs, their patients, and relatives, but also successful care delivery and subsequently improved health outcomes in the long term. To advance our understanding of how high COVID-19-related HL manifests itself in HPs, how it relates to health outcomes, and how it can be improved, more research is necessary. TRIAL REGISTRATION: Open Science Framework dbfa5; https://osf.io/dbfa5/.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.034 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.006 |
| Insufficient payload (model declined to judge) | 0.009 | 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; both teacher heads agree on what is shown here.
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".