Medication Literacy in a Cohort of Chinese Patients Discharged With Essential Hypertension
Bibliographic record
Abstract
Background: In recent years, research on medication literacy has been increasing in many countries. Medication literacy of patients with hypertension affects the management and prognosis of hypertension. Therefore, the purpose of this study was to assess the present situation of medication literacy and meaningful determinants affecting medication literacy in discharged patients with essential hypertension. Methodology: This is a cross-sectional study among 147 discharged patients with essential hypertension in a tertiary hospital in Changsha, Hunan province, China between March and June 2016. The Chinese version of Medication Literacy Questionnaire was applied to measure medication literacy by means of structured interview for 7 and 30 days after discharge. Furthermore, discharged patient’s demographic were acquired from the hospital records. Data were analyzed using SPSS version 19.0. Multiple linear regression was used to analyze the meaningful determinants of medication literacy. And p-value <0.05 was considered statistically significant. Results: The present situation of medication literacy was poor. More than 70% participants didn't have substantial knowledge of the effects and side effects of the medicine they were taking, more than 30% participants didn't know the name or dose of the medicine, more than 20 % participants didn't even know how often to take medicine. In addition, medication literacy scores increased with educational level and length of hospital stay (P < 0.05), but decreased with age (P < 0.05). Conclusion: It is necessary to conduct targeted health education for discharged patients with essential hypertension through the determinants of low medication literacy obtained in this study, so as to reduce the risk of low level of medication literacy.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 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".