Digital Health Literacy in Adults With Low Reading and Writing Skills Living in Germany: Mixed Methods Study
Bibliographic record
Abstract
Background: Digital health literacy is a key factor in enabling users to navigate in an increasingly digitalized health care system. Low levels of digital health literacy are associated with higher age, low education, and income, as well as low functional health literacy. Around 6.2 million adults living in Germany have low reading and writing skills. Due to their low literacy, this group is often underrepresented in research studies and therefore little is known about their digital health literacy and use of digital health tools. Objective: The objectives of this study were to assess digital health literacy in adults with low reading and writing skills and to explore which digital health tools they use in daily life. Methods: An interviewer-administered survey and focus groups were conducted with adult residents of Bremen, Germany, who were aged 18-64 years and had low reading and writing skills. In addition, a stakeholder workshop was held to derive recommendations on how digital health literacy could be improved. The survey questionnaire included 21 items addressing the use of digital health technologies and digital health literacy (eHealth Literacy Scale). Focus group participants completed several tasks on web-based health information and then discussed their experiences. Survey data were analyzed using descriptive statistics and linear regression. Qualitative content analysis was applied to analyze the focus group data and the written documentation of the stakeholder workshop. Results: Survey participants (n=96) were on average 43 (SD 10.7) years old, 72% (69/96) were female, and 92% (88/96) were not born in Germany. Participants reported mainly using information-related digital health technologies such as health apps (40/96, 42%), health websites (30/96, 31%), or activity trackers (27/96, 28%). The mean digital health literacy score was 22 (SD 8) points, with 35% (34/96) of participants classified as having a low digital health literacy (score between 8-19/40 points). Digital health technology use was associated with higher digital health literacy. For participants in the 5 focus groups (total n=39; mean age 43, SD 12.6 years; n=34, 87% female), limited technical skills and language problems were the most important challenges. Furthermore, focus group participants reported that they favor videos when searching for web-based health information and prefer to seek support from family members or local organizations for health issues. Stakeholders (n=15) recommended that health websites should be available in multiple languages, contain simple and easy-to-read language, and use images, symbols, and videos. Conclusions: While adults with low reading and writing skills use digital health technologies, many find it challenging to search for health information on the internet due to lacking technical skills and language problems. To ensure that adults with low reading and writing skills are not further left behind, future research should focus on developing tailored interventions to promote digital health literacy.
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 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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| 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".