Blood Pressure Biofeedback Exerts Intermediate-Term Effects on Blood Pressure and Pressure Reactivity in Individuals with Mild Hypertension: A Randomized Controlled Study
Bibliographic record
Abstract
OBJECTIVE: This randomized controlled study examined whether a 4-week blood pressure (BP) biofeedback program can reduce BP and BP reactivity to stress in participants with mild hypertension. METHODS: Participants in the active biofeedback group (n=20) were trained in 4 weekly laboratory sessions to self-regulate their BP with continuous BP feedback signals, whereas participants in the sham biofeedback group (n=18) were told to manipulate their BP without feedback signals. BP, skin temperature, skin conductance, BP reactivity to stress, body weight, and state anxiety were assessed before training and repeated at the eighth week after the training. RESULTS: The decreases in systolic (12.6 +/- 8.8 versus 4.1 +/- 5.7) and mean BP (8.2 +/- 6.9 versus 3.3 +/- 4.9) from baseline at week 12 follow-up were significantly greater in the active biofeedback group compared with the sham biofeedback group (p=0.001 and 0.017, respectively). Results from analysis of covariance with the follow-up systolic blood pressure (SBP) (or mean arterial pressure [MAP]) as the dependent variable, baseline SBP (or MAP) as the covariate, and group as the independent variable showed that biofeedback training effectively lowered SBP and MAP (p=0.013 and 0.026, respectively). The pre-to-post differences in skin conductance and SBP reactivity were statistically significant for the biofeedback group (p=0.005 and 0.01, respectively), but not for the control group. For the sample as a whole and for the biofeedback group, the state anxiety score and body weight remained unchanged. CONCLUSIONS: BP biofeedback exerts a specific treatment effect in reducing BP in individuals with mild hypertension, possibly through reducing pressor reactivity to stress.
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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 | 0.008 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".