Deaf Adults’ Health Literacy and Access to Health Information: Protocol for a Multicenter Mixed Methods Study
Bibliographic record
Abstract
BACKGROUND: Deaf American Sign Language (ASL) users often struggle with limited health literacy compared with their hearing peers. However, the mechanisms driving limited health literacy and how this may impact access to and understanding of health information for Deaf individuals have not been determined. Deaf individuals are more likely than hearing individuals to use the internet, yet they continue to report significant barriers to health information. This study presents an opportunity to identify key targets that impact information access for a largely marginalized population. OBJECTIVE: This study aims to elucidate the role of information marginalization on health literacy in Deaf ASL users and to better understand the mechanisms of health literacy in this population for the purpose of identifying viable targets for future health literacy interventions. METHODS: This is an exploratory mixed methods study to identify predictors and moderators of health literacy in the Deaf population. These predictors of health literacy will be used to inform the second step that qualitatively explains the findings, including how Deaf individuals access and understand Web-based health information. Multiple interviewer- and computer-based instruments underwent translation and adaptation, from English to ASL, to make them accessible for the Deaf participants in our study. A planned sample of 450 Deaf ASL users and 450 hearing native English speakers, aged 18 to 70 years, will be recruited from 3 partnering sites: Rochester, NY; Flint, MI; and Chicago, IL. These individuals will participate in a single data collection visit. A subset of participants (approximately 30) with key characteristics of interest will be invited for a second data collection visit to observe and inquire more about their ability to directly access, navigate, and comprehend Web-based health information. The study will help assess how the ways health literacy and information are visualized may differ between Deaf individuals and hearing individuals. The study will also survey participants' ownership and use of computer and mobile devices and their level of Web-based information use, including health information. RESULTS: Adaptation and translation of protocols and instruments have been completed and are now in use for the study. Recruitment is underway and will continue until late 2020. Results from this study will be used to provide a guide on how to structure Web-based health information in a way that maximizes accessibility and improves health literacy for Deaf individuals. CONCLUSIONS: The results from this mixed methods proposal will advance what is known about health literacy and health information accessibility for Deaf individuals. This innovative study will generate rich data on how to formulate health information and health literacy interventions more accurately to take advantage of visual learning skills. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/14889.
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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 | 0.008 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".