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Background: Half of US adults have ≥1 cardiovascular disease (CVD) risk factors. Exercise is the first-line lifestyle therapy to prevent and treat CVD. We developed the Prioritize Personalize Prescribe Exercise algorithm (P3-EX), an evidence-based tool that clinicians can use to prescribe exercise for patients with CVD risk factors. Purpose: To conduct a feasibility survey study of user satisfaction and usability of P3-EX as an exercise prescription (ExRx) tool among healthcare providers. Methods: = 231) who recommend exercise to patients through professional society meetings, presentations, newsletters, and investigators' networks. Participants completed a timed case study of a patient with CVD risk factors using P3-EX on a templated website. They then completed an adapted version of the Mobile Application Rating Scale, with responses ranging from 5 (completely agree) to 1 (completely disagree) to evaluate the ease of use, system information arrangement, and usefulness of P3-EX. Descriptive statistics determined the % response, time spent using P3-EX, and ExRx produced. Results: Of the 844 recruited participants, 309 completed the feasibility survey study (healthcare provider N = 143, people with other professional affiliates N = 166). Of these, 86.9% agreed using P3-EX will make their patients healthier; 86.6% agreed feedback is immediate and understandable; 81.4% agreed P3-EX is intuitive, producing high-quality, evidenced-based, individualized ExRx; 83.5% are generally satisfied with P3-EX; 81.3% would recommend P3-EX to colleagues; and 79.2% agreed ExRx produced by P3-EX is safe. However, 34.4% agreed fault tolerance could be improved. Most participants (88.8%) produced an ExRx for the same prioritized CVD risk factor. The average time spent using P3-EX was 4.6 min. Conclusion: We found healthcare providers are satisfied with P3-EX and agreed that it is a usable ExRx tool for patients with CVD risk factors. Our results are promising because healthcare providers lack the time, knowledge, confidence, and guidance to recommend exercise to patients. Prioritize Personalize Prescribe Exercise algorithm appears to be a potential solution to this problem.
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Wu et al. (2025) studied this question.
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