Abstract TH229: Assessing medical resident knowledge of isometric handgrip training for hypertension control before and after review of a brief medical education packet
Bibliographic record
Abstract
Introduction: Isometric handgrip training (IHT) is a simple and time efficient blood pressure (BP)-lowering intervention endorsed in AHA/ACC clinical practice guidelines for HTN management, yet is not routinely prescribed. Understanding knowledge of IHT and the potential concerns for its implementation as a HTN management strategy will inform future strategies for physician uptake. Hypothesis: We hypothesized that a brief medical education packet administered to internal medicine residents would improve knowledge and likelihood of recommending IHT as a BP-lowering tool. Methods: An electronic Google Forms survey was distributed to internal medicine residents (PGY-1 to PGY-4, N=182) at a single academic institution. The anonymous survey consisted of 10 questions designed to assess residents’ knowledge of and willingness to implement IHT in clinical practice before and after the brief educational intervention. Implementation concerns were also recorded. The study was deemed exempt by the Institutional Review Board. Results: Twenty-four residents (41.7% PGY-3) completed the survey. Of respondents, the top planned specialties were cardiology (25%) and primary care (16.7%). Before the educational intervention, respondents had never heard of IHT (83.3%) or did not understand the technique well (16.7 %). After a brief educational intervention, 75% of residents understood the technique moderately well and 70.8% were moderately likely to recommend this practice to patients [Figures 1, 2]. The majority of participants (66.8%) cited issues obtaining the equipment as a concern for suggesting the technique to patients. Conclusions: As a first step in understanding the potential role of IHT as a BP-lowering tool in standard care HTN management, it is imperative to first understand the current state of provider knowledge. Enhancing this knowledge may lead to wider implementation of IHT in clinical practice and potentially improve patient outcomes in the future.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".