Behavioral Counseling to Promote a Healthful Diet and Physical Activity for Cardiovascular Disease Prevention in Adults Without Known Cardiovascular Disease Risk Factors: Updated Systematic Review for the U.S. Preventive Services Task Force [Internet]
Bibliographic record
Abstract
Background: A healthy diet is characterized by a balanced and varied selection of meals and drinks that aids a person in attaining and sustaining a healthy weight. Aim: To carefully assess the proof regarding the harm and benefits of behavior therapy for the 1ry avoidance of cardiovascular illness in adults lacking recognized cardiovascular risk factors to educate the United States Preventive Services Task Force. Materials and methods: This systematic review and meta-analysis encompassed nine research studies, submitting to the Cochrane Collaboration principles and conforming to the PRISMA declaration (Preferred Reporting Items for Systematic Reviews and Meta-analyses). Main findings: Behavioral interventions enhanced levels of nutritional consumption and physical activity, with consistent benefits for healthful diets versus controls at 6+ months. Small, although significant variations have been detected in systolic blood pressure (−1.26 millimeters mercury [ninety-five percent confidence interval, −1.77 to −0.75]), total cholesterol (−2.85 milligrams per deciliter [ninety-five percent confidence interval, −4.95 to −0.75]), in addition to body mass index (−0.41 [ninety-five percent confidence interval, −0.62 to −0.19]) at the six- to twelve-month interval. Modest correlations with activity and dietary behaviors were observed, with no increased adverse events in intervention participants. Conclusion: Behavioral interventions significantly improve levels of dietary intake and physical activity, with healthy diets and programs showing significant benefits over 6+ months. Small improvements in blood pressure, cholesterol, and BMI were noted, with tailored approaches being particularly effective without increased adverse events
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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 | 0.006 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.010 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".