The impact of communication training on the clinical care of hypertension in general practice: a cluster randomized controlled trial in China
Bibliographic record
Abstract
BACKGROUND: Hypertension is one of the most common chronic diseases with a low control rate globally. The effect of communication skills training contributing to hypertension control remains uncertain. The aim of the present study was to assess the effectiveness of an educational intervention based on the Calgary-Cambridge guide in improving hypertensive management. METHODS: A cluster randomized controlled trial enrolled 27 general practitioners (GPs) and 540 uncontrolled hypertensive patients attending 6 community health centers in Chengdu, China. GPs allocated to the intervention group were trained by an online communication course and two face-to-face workshops based on Calgary-Cambridge guides. The primary outcome was blood pressure (BP) control rates and reductions in systolic and diastolic BP from baseline to 3 months. The secondary outcome was changes in GPs' communication skills after one month, patients' knowledge and satisfaction after 3 months. Bivariate analysis and the regression model assessed whether the health provider training improved outcomes. RESULTS: After the communication training, the BP control rate was significantly higher (57.2% vs. 37.4%, p < 0.001) in the intervention groups. Compared to the control group, there was a significant improvement in GP's communication skills (13.0 vs 17.5, p < 0.001), hypertensive patients' knowledge (18.0 vs 20.0, p < 0.001), and systolic blood pressure (139.1 vs 134.7, p < 0.001) after 3 months of follow-up. Random effects least squares regression models showed significant interactions between the intervention group and time period in the change of GP's communication skills (Parameter Estimated (PE): 0.612, CI:0.310,0.907, p = 0.006), hypertensive patient's knowledge (PE:0.233, CI: 0.098, 0.514, p < 0.001), satisfaction (PE:0.495, CI: 0.116, 0.706, p = 0.004), SBP (PE:-0.803, CI: -1.327, -0.389, p < 0.001) and DBP (PE:-0.918, CI: -1.694, -0.634, p < 0.001), from baseline to follow-up. CONCLUSION: Communication training based on the Calgary-Cambridge guide for GPs has shown to be an efficient way in the short term to improve patient-provider communication skills and hypertension outcomes among patients with uncontrolled BPs. TRIAL REGISTRATION: The trial was registered on Chinese Clinical Trials Registry on 2019-04-03. (ChiCTR1900022278).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".