Health Literacy Among Adults With Multiple Chronic Health Conditions
Bibliographic record
Abstract
Low health literacy (HL) is associated with poorer health outcomes. We examined HL among adults with multiple chronic conditions (CCs), using 2016 Behavioral Risk Factor Surveillance System data. Health literacy was measured by 3 subjective questions about difficulty with the following tasks: (1) obtaining health information or advice; (2) understanding spoken health information; and (3) understanding written health information. We estimated the prevalence of low HL (difficulty with ≥1 HL tasks) and used multiple logistic regression analysis to examine associations between HL and number of CCs. The prevalence of low HL was 13.8% overall and increased with the number of CCs from 10.6% among those with no CC to 24.7% among those with 3 or more CCs, with the latter having more than twice the adjusted odds of low HL compared with the former (adjusted odds ratio = 2.65; 95% confidence interval, 2.36-2.97). Efforts to improve HL in this population are needed.
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 | 0.021 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.007 |
| Open science | 0.000 | 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 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".