Influence of Digital Health Literacy on Blood Pressure and Hemoglobin A1c in Patients With Comorbid Type 2 Diabetes and Hypertension
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
Digital health literacy is emerging as an important element in chronic illness management, yet its relationship with clinical outcomes remains unclear. Utilizing data from the ongoing EXpanding Technology-Enabled, Nurse-Delivered Chronic Disease Care trial, this cross-sectional, correlational study explored the association between digital health literacy, health literacy, and patient outcomes, specifically blood pressure and hemoglobin A 1c levels in 76 patients managing comorbid type 2 diabetes and hypertension. Results indicate patients had moderate digital health literacy, which was not significantly correlated with health literacy ( r = 0.16, P = .169). Both bivariate and covariate-adjusted regression models indicated that digital health literacy was not significantly associated with patient outcomes (all P > .05, small effects). These findings suggest that although patients from diverse sociodemographic backgrounds may possess the digital health literacy to engage with digital health tools, this alone may not improve clinical outcomes. Although digital health literacy may not be directly related to improved clinical outcomes, future research should explore how digital health tools can be optimized to enhance patient engagement and address complex challenges in diverse populations managing chronic conditions.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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