Developing a Framework to Measure Health Literacy Demands of Consumer-Facing Healthcare Organization Websites
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Many consumer-facing healthcare organization websites are challenging for people with low e-health literacy skills to navigate and use the information to make informed decisions. Though searchers may be familiar with how to use the Internet, navigating website designs, often referred to as eHealth literacy, can make finding health information confusing. Health literacy demands, related to eHealth literacy skills concerning the content and design, can make the difference between consumers’ frustration and success. In this study, we aimed to create a framework to measure the accessibility and usability of healthcare organization consumer-facing websites using this question, “How can the information offered, and navigation of consumer-facing healthcare organization websites be improved to increase accessibility and usability?” We scored select healthcare organizations’ consumer-facing websites including their home page and two patient education pages, using Social Cognitive Theory and Health Literacy constructs both of which promote better accessibility and usability of health information. In addition, we analyzed how the health literacy demands of these pages support or obstruct the eHealth literacy skills of consumers. Results indicated that only 50% of Social Cognitive Theory constructs and 47% of Health Literacy constructs were observed. However, by examining the missing constructs healthcare organizations can assess where to focus consumer-facing website improvement efforts. Therefore, we concluded that Social Cognitive Theory combined with Health Literacy constructs offer a viable framework for measuring and potentially improving consumer-facing healthcare websites.
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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 | 0.010 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it