Ignite Creation Date:
2025-12-24 @ 11:30 PM
Ignite Modification Date:
2025-12-25 @ 9:18 PM
Study NCT ID:
NCT07238556
Status:
NOT_YET_RECRUITING
Last Update Posted:
2025-12-22
First Post:
2025-11-07
Is NOT Gene Therapy:
False
Has Adverse Events:
False
Brief Title:
A Novel Digital Tool Physicians Can Use to Prescribe Exercise to Patients With Cardiovascular Disease Risk Factors
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D006973', 'term': 'Hypertension'}, {'id': 'D050171', 'term': 'Dyslipidemias'}, {'id': 'D003920', 'term': 'Diabetes Mellitus'}, {'id': 'D009765', 'term': 'Obesity'}, {'id': 'D002318', 'term': 'Cardiovascular Diseases'}, {'id': 'D009043', 'term': 'Motor Activity'}, {'id': 'D015438', 'term': 'Health Behavior'}], 'ancestors': [{'id': 'D014652', 'term': 'Vascular Diseases'}, {'id': 'D052439', 'term': 'Lipid Metabolism Disorders'}, {'id': 'D008659', 'term': 'Metabolic Diseases'}, {'id': 'D009750', 'term': 'Nutritional and Metabolic Diseases'}, {'id': 'D044882', 'term': 'Glucose Metabolism Disorders'}, {'id': 'D004700', 'term': 'Endocrine System Diseases'}, {'id': 'D050177', 'term': 'Overweight'}, {'id': 'D044343', 'term': 'Overnutrition'}, {'id': 'D009748', 'term': 'Nutrition Disorders'}, {'id': 'D001835', 'term': 'Body Weight'}, {'id': 'D012816', 'term': 'Signs and Symptoms'}, {'id': 'D013568', 'term': 'Pathological Conditions, Signs and Symptoms'}, {'id': 'D001519', 'term': 'Behavior'}]}}, 'protocolSection': {'designModule': {'phases': ['NA'], 'studyType': 'INTERVENTIONAL', 'designInfo': {'allocation': 'RANDOMIZED', 'maskingInfo': {'masking': 'NONE', 'maskingDescription': 'Outcome assessors (Graduate Research Assistants) of vitals, body composition, and physical activity levels will be blinded to intervention assignments at baseline. Outcome assessors (laboratory technicians) of blood lipid-lipoprotein and blood glucose profiles will be blinded to intervention assignments. The healthcare providers (physicians) who will deliver the intervention, the participants (patients) who receive the intervention; and the investigators (Graduate Research Assistants) who will provide exercise intervention oversight will have knowledge of will intervention assignment due to feasibility and the behavioral nature of the trial.'}, 'primaryPurpose': 'HEALTH_SERVICES_RESEARCH', 'interventionModel': 'CROSSOVER', 'interventionModelDescription': 'Physicians (N=24) will deliver a Prioritized Personalized EXercise Prescription (P3-EX) to one of their patients with cardiovascular disease risk factors (n=24) and the American College of Sports Medicine Physical Activity Vital Sign exercise program to the other with cardiovascular disease risk factors (n=24) in random sequence.'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 72}}, 'statusModule': {'overallStatus': 'NOT_YET_RECRUITING', 'startDateStruct': {'date': '2026-01-01', 'type': 'ESTIMATED'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2025-12', 'completionDateStruct': {'date': '2026-05-31', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2025-12-15', 'studyFirstSubmitDate': '2025-11-07', 'studyFirstSubmitQcDate': '2025-11-15', 'lastUpdatePostDateStruct': {'date': '2025-12-22', 'type': 'ESTIMATED'}, 'studyFirstPostDateStruct': {'date': '2025-11-20', 'type': 'ESTIMATED'}, 'primaryCompletionDateStruct': {'date': '2026-05-31', 'type': 'ESTIMATED'}}, 'outcomesModule': {'otherOutcomes': [{'measure': 'Fidelity of Prioritize Personalize Prescribe Exercise (P3-EX)', 'timeFrame': "Throughout the 5-month study, at each physicians' use of P3-EX to deliver an exercise prescription to a patient in the study (assessed once per physician; anticipated 19-24 physicians)", 'description': 'The investigators will assess the degree to which Prioritize Personalize Prescribe EXercise (P3-EX) is implemented as intended by obtaining the selected American College of Sports Medicine strategy used to prioritize the cardiovascular disease risk factor chosen by the physicians when there is multiple risk factors tied for the greatest risk.'}, {'measure': 'Usage Time of Prioritize Personalize Prescribe Exercise (P3-EX)', 'timeFrame': "Throughout the 5-month study, at each physicians' use of P3-EX to deliver an exercise prescription to a patient in the study (assessed once per physician; anticipated 19-24 physicians)", 'description': 'The investigators will obtain the time it takes in minutes for physicians to prescribe the exercise prescription to each patient using P3-EX.'}, {'measure': 'Trial Satisfaction', 'timeFrame': 'Within 48 hours after completing the delivery of both P3-EX and ACSM PAVS', 'description': 'Physicians and patients will complete open-ended written questions to assess their satisfaction with key study components, to inform the design of a larger trial. Within 48 hours after completing the delivery of both Prioritize Personalize Prescribe Exercise (P3-EX) and American College of Sports Medicine Physical Activity Vital Sign (ACSM-PAVS), physicians will provide their thoughts on the recruitment procedures and the exercise prescription training they received. Patients will provide their thoughts on use of the Timeline Followback for Exercise and the exercise guidance Graduate Assistants gave them during virtual study visits after they complete the intervention. Responses will be coded and categorized to identify common themes.'}], 'primaryOutcomes': [{'measure': 'Feasibility and Acceptability of Prioritize Personalize Prescribe EXercise (P3-EX)', 'timeFrame': 'Within 48 hours following the delivery of P3-EX and ACSM-PAVS', 'description': 'The mHealth Application Usability Questionnaire is validated to measure the usability of mobile health apps for healthcare providers and/or patients through 21 items spilt into three subscales; Ease of Use and Satisfaction, System Information Arrangement, and Usefulness. The rating of each item is scaled from 1 to 7, and responses are averaged to provide a single score. Physicians will rate both P3-EX and American College of Sports Medicine Physical Activity Vital Sign (ACSM-PAVS), and patients will rate the one they receive. Overall scores (mean ± SD) will be compared to the middle score of 4.0.'}, {'measure': 'Feasibility and Acceptability of Prioritize Personalize Prescribe EXercise (P3-EX)', 'timeFrame': 'Within 48 hours following the delivery of P3-EX and ACSM-PAVS', 'description': 'The System Usability Scale is the most common questionnaire to assess the usability of mHealth apps. Ratings for each of the 10 items are scaled from 1 to 5. Physicians will rate both P3-EX and American College of Sports Medicine Physical Activity Vital Sign (ACSM-PAVS), and patients will rate the one they receive. Overall scores (mean ± SD) will be scaled from 0 to 100 and compared to normative reference ratings and scores in the literature.'}], 'secondaryOutcomes': [{'measure': 'Physician Barriers to and Confidence with Exercise Prescription (ExRx)', 'timeFrame': 'Before completing brief ExRx training and within 48 hours following the delivery of either P3-EX or ACSM-PAVS', 'description': 'Physicians will complete an adapted ExRx self-reflection questionnaire before completing brief ExRx training and within 48 hours following the delivery of either Prioritize Personalize Prescribe EXercise (P3-EX) or the American College of Sports Medicine Physical Activity Vital Sign (ACSM-PAVS), to assess the impact of the trial on their perceived barriers to and confidence with ExRx. Responses will be rated a Likert scale from 1 to 4, with 4 being the highest impact from a barrier or the highest confidence with a skill (mean ± SD).'}, {'measure': "American Heart Association Life's Essential 8 Score Change from Baseline", 'timeFrame': '12 weeks', 'description': 'Patient Cardiovascular Health Scores from 0 to 100 points will be determined at pre- and 12-weeks post-intervention (mean ± SD) based on patient survey responses to metrics of diet, PA, nicotine exposure, sleep health, and assessed values of body mass index, blood pressure, blood lipids, and blood glucose.'}, {'measure': 'Resting Blood Pressure Changes', 'timeFrame': '12 weeks', 'description': 'Patient resting systolic and diastolic blood pressure (mm Hg) will be assessed at pre- and 12-weeks post-intervention (mean ± SD) via automatic monitors (OMRON HEM-705CP, Kyoto, Japan), to indicate health improvement for hypertension.'}, {'measure': 'Resting Heart Rate Changes', 'timeFrame': '12 weeks', 'description': 'Resting heart rate (bpm) will be assessed at pre- and 12-weeks post-intervention (mean ± SD) via automatic monitors (Polar Electro Oy F7, Kempele, Finland, respectively), to indicate health improvement for cardiovascular fitness.'}, {'measure': 'Body Mass Index Changes', 'timeFrame': '12 weeks', 'description': 'Height (m) and weight (kg) will be assessed at pre- and 12-weeks post-intervention (mean ± SD) via a mechanical beam balance scale with stadiometer (Health o meter, Pelion, IL, USA) to calculate body mass index (kg/m2) and indicate health improvement for obesity.'}, {'measure': 'Waist Circumference Changes', 'timeFrame': '12 weeks', 'description': 'Patient waist circumference (cm) will be assessed at pre- and 12-weeks post-intervention (mean ± SD) via a Gullick tape measure (Sammons Preston) to indicate health improvement for obesity.'}, {'measure': 'Blood Lipid-Lipoproteins Profile Changes', 'timeFrame': '12 weeks', 'description': 'Patient total cholesterol, triglycerides, high-density lipoproteins, and low-density lipoproteins (mg/dL) will be assessed at pre- and 12 weeks post-intervention (mean ± SD), processed by phlebotomy technicians at Quest Patient Service Centers, to indicate health improvement for dyslipidemia.'}, {'measure': 'Blood Glucose Profile Changes', 'timeFrame': '12 weeks', 'description': 'Glycated hemoglobin (%) will be assessed at pre- and 12 weeks post-intervention (mean ± SD), processed by phlebotomy technicians at Quest Patient Service Centers, to indicate health improvement for diabetes.'}, {'measure': 'Blood Glucose Profile Changes', 'timeFrame': '12 weeks', 'description': 'Fasting plasma glucose (mg/dL) will be assessed at pre- and 12 weeks post-intervention (mean ± SD), processed by phlebotomy technicians at Quest Patient Service Centers, to indicate health improvement for diabetes.'}, {'measure': 'Subjective Physical Activity Levels Changes', 'timeFrame': 'Weekly for 12 weeks', 'description': 'Patient self-reported physical activity levels will be assessed at pre-intervention and 12 weeks post-intervention via the Timeline Followback for Exercise for the various Frequency, Intensity, Time, and Type (FITT) metrics (mean ± SD). The Timeline Followback for Exercise is a validated calendar diary method for recording the FITT of exercise, whereby, frequency is the number of days per week that physical activity is performed; type is the modality of physical activity performed (e.g., running, weightlifting); time is the duration performed in minutes for each modality; and intensity using the Borg 6-20 rating of perceived exertion scale. Graduate Research Assistants will assign a metabolic equivalent (MET) value for each recorded exercise to calculate exercise volume in MET\\*min/wk.'}, {'measure': 'Exercise Adherence', 'timeFrame': 'Weekly for 12 weeks', 'description': 'Patient self-reported physical activity levels will be assessed weekly for the 12-week exercise intervention via the Timeline Followback for Exercise for the various Frequency, Intensity, Time, and Type (FITT) metrics (mean ± SD). The Timeline Followback for Exercise is a validated calendar diary method for recording the FITT of exercise, whereby, frequency is the number of days per week that physical activity is performed; type is the modality of physical activity performed (e.g., running, weightlifting); time is the duration performed in minutes for each modality; and intensity using the Borg 6-20 rating of perceived exertion scale. Graduate Research Assistants will assign a metabolic equivalent (MET) value for each recorded exercise to calculate exercise volume in MET\\*min/wk.'}, {'measure': 'Objective Physical Activity Level Changes', 'timeFrame': '12 weeks', 'description': 'Minutes of physical activity per day within different intensities (i.e., light, moderate, and vigorous) will be measured at pre- and 12-weeks post-intervention (mean ± SD) via accelerometers (Actigraph wGT3X-BT, Pensacola, FL).'}, {'measure': 'Energy Expenditure Changes', 'timeFrame': '12 weeks', 'description': 'Patient energy expenditure (kcal) will be measured at pre- and 12-weeks post-intervention (mean ± SD) via accelerometers (Actigraph wGT3X-BT, Pensacola, FL).'}, {'measure': 'Step Count Changes', 'timeFrame': '12 weeks', 'description': 'Steps per day will be measured at pre- and 12-weeks post-intervention (mean ± SD) via accelerometers (Actigraph wGT3X-BT, Pensacola, FL).'}, {'measure': 'Sedentary Behavior Changes', 'timeFrame': '12 weeks', 'description': 'Sedentary time (minutes/wk) will be measured at pre- and 12-weeks post-intervention (mean ± SD) via accelerometers (Actigraph wGT3X-BT, Pensacola, FL).'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['Exercise prescription', 'Exercise Therapy', 'Physical Activity', 'Preventive Health Services', 'Health Behavior', 'Medical Informatics Applications', 'Health technology', 'Precision Medicine', 'Primary Health Care'], 'conditions': ['Hypertension', 'Dyslipidemia', 'Diabetes Mellitus', 'Obesity', 'Cardiovascular Disease']}, 'referencesModule': {'references': [{'pmid': '38206661', 'type': 'BACKGROUND', 'citation': 'Zaleski AL, Berkowsky R, Craig KJT, Pescatello LS. Comprehensiveness, Accuracy, and Readability of Exercise Recommendations Provided by an AI-Based Chatbot: Mixed Methods Study. JMIR Med Educ. 2024 Jan 11;10:e51308. doi: 10.2196/51308.'}, {'pmid': '40677518', 'type': 'BACKGROUND', 'citation': 'Chen S, Wu Y, Kennedy J, Panza G, Guidry MZ, Pescatello LS; FACSM. An exercise prescription algorithm for clinicians to use with their patients with cardiovascular disease risk factors. Digit Health. 2025 Jul 16;11:20552076251360884. doi: 10.1177/20552076251360884. eCollection 2025 Jan-Dec.'}, {'pmid': '38132645', 'type': 'BACKGROUND', 'citation': 'Chen S, Wu Y, Bushey EL, Pescatello LS. Evaluation of Exercise Mobile Applications for Adults with Cardiovascular Disease Risk Factors. J Cardiovasc Dev Dis. 2023 Nov 28;10(12):477. doi: 10.3390/jcdd10120477.'}, {'pmid': '33718793', 'type': 'BACKGROUND', 'citation': 'Pescatello LS, Wu Y, Panza GA, Zaleski A, Guidry M. Development of a Novel Clinical Decision Support System for Exercise Prescription Among Patients With Multiple Cardiovascular Disease Risk Factors. Mayo Clin Proc Innov Qual Outcomes. 2020 Oct 22;5(1):193-203. doi: 10.1016/j.mayocpiqo.2020.08.005. eCollection 2021 Feb.'}]}, 'descriptionModule': {'briefSummary': 'The investigators will conduct a feasibility and pilot efficacy randomized controlled trial to test the usability and user satisfaction of an evidence-based digital health tool the investigators developed for physicians to use to Prioritize Personalize Prescribe EXercise (P3-EX) to patients with cardiovascular disease (CVD) risk factors. The investigators will recruit 24 physicians from two local hospitals in CT, USA. Physicians will recruit two patients each (N=48) having CVD risk factors. Physicians will deliver a P3-EX exercise prescription (ExRx) to one of their patients (n=24) and the American College of Sports Medicine Physical Activity Vital Sign (ACSM-PAVS) ExRx to the other (n=24) in a random sequence crossover design. Physicians and patients will rate the feasibility and acceptability of each method using validated questionnaires. Patients will perform their prescribed ExRx for 12 weeks and complete a self-report exercise diary to monitor exercise adherence with virtual oversight from University of Connecticut (UConn) Graduate Research Assistants. Before and after the exercise intervention, the investigators will measure patient CVD risk factors and physical activity (PA) levels via accelerometry. The primary aim is to evaluate the feasibility and acceptability of P3-EX for physicians to use to prescribe exercise to patients with CVD risk factors, and the secondary aim is to explore the preliminary efficacy of P3-EX to improve patient CVD risk factors, PA levels, and exercise adherence. The investigators hypothesize P3-EX will be feasible for physicians to use to prescribe customized exercise routines for patients with CVD risk factors, and physicians and patients will be satisfied with P3-EX.', 'detailedDescription': "Background\n\nApproximately half of U.S. adults have 1 or more of the major CVD risk factors of obesity, hypertension, dyslipidemia, and diabetes, and 1 in 4 have 3 or more. Professional organizations such as the American College of Sports Medicine (ACSM) and the American Heart Association (AHA) recommend exercise as a first-line lifestyle therapy to prevent and treat CVD and its risk factors. The ACSM advocates clinicians to assess PA as a vital sign and prescribe exercise for every patient. However, only about 20% of U.S. adults and 44-56% of patients with CVD risk factors report being advised by their health care providers to exercise. Although physicians are receptive to prescribing exercise to their patients, they encounter barriers to doing so such as a lack of time, training, and the tools. Digital health tools show promise as clinical decision support systems to guide physicians in prescribing exercise to their patients. The investigators developed a clinical decision support tool named P3-EX. P3-EX includes: 1) the ACSM exercise preparticipation health screening recommendations to determine if there is a need for medical clearance; 2) an adapted AHA Life's Essential 8 cardiovascular health scoring system to determine the CVD risk factor posing the greatest risk; 3) the ACSM strategies for designing an ExRx for adults with multiple CVD risk factors; and 4) the ACSM Frequency, Intensity, Time, Type (FITT) ExRx for the prioritized CVD risk factor posing the greatest risk.\n\nObjectives\n\nThe primary aim of this trial is to evaluate the feasibility and acceptability of P3-EX for physicians to use to prescribe exercise to patients with CVD risk factors.\n\nThe secondary aim is to explore the preliminary efficacy of P3-EX to improve patient CVD risk factors, PA levels, and exercise adherence.\n\nStudy Procedures\n\nThe investigators will recruit 24 physicians from Hartford HealthCare or UConn Health clinics using email listservs, newsletters, university communication channels, flyers, and word of mouth. Physicians will attend a virtual study orientation led by a UConn Graduate Research Assistant to provide informed consent, confirm eligibility, complete demographics, assess barriers to and confidence with ExRx, and receive brief ExRx delivery training to their patients. Physicians will then recruit two of their patients (N=48) who have obesity, hypertension, dyslipidemia, and/or diabetes. Patients will attend two in-person study visits led by a UConn Graduate Research Assistant at a clinic in Hartford or Farmington, CT, to provide informed consent, confirm eligibility, complete demographics, and assess the AHA Life's Essential 8, anthropometrics, vitals, subjective PA levels via the Timeline Followback for Exercise, and objective PA levels via accelerometry. Patients will attend their local Quest Diagnostics Service Center to assess blood lipid-lipoproteins and blood glucose. Physicians will be individually randomized with a 1:1 allocation ratio to deliver an P3-EX ExRx to one of their patients and the ACSM-PAVS ExRx to the other patient in a random sequence crossover design. Patients will attend their healthcare appointment with their physician and receive either a P3-EX ExRx (n=24) or the ACSM-PAVS ExRx (n=24). Within 48 hours following each healthcare appointment, physicians and patients will complete the validated mHealth Application Usability Questionnaire and the System Usability Scale to rate the feasibility and acceptability of P3-EX or ACSM-PAVS. Patients will be asked to perform their ExRx and monitor their exercise adherence for 12 weeks using the Timeline Followback for Exercise with virtual oversight from UConn Graduate Research Assistants. Patients will receive a 12-week exercise program information packet, two exercise guidance virtual student visits led by UConn Graduate Research Assistants, and weekly progressive FITT exercise goals via email from UConn Graduate Research Assistants. UConn Graduate Research will also provide Timeline Followback for Exercise summary reports to patients weekly via email. At post-intervention, patients will attend two more in-person study visits led by a UConn Graduate Research Assistant at a clinic in Hartford or Farmington, CT to assess trial satisfaction, AHA Life's Essential 8, CVD risk factors and PA levels.\n\nStatistical Analysis Plan\n\nThe investigators will conduct statistical analyses using Statistical Package for the Social Sciences Version 30. The investigators will first use descriptive statistics and graphical techniques to ensure all test assumptions are met, including the inspection for outliers, normal distributions, and homogeneity of variances. Missing values will be addressed using multiple imputations when appropriate to include the whole randomized sample. If normality assumptions are not met for secondary outcomes, considerations will be made to transform the data to achieve a normal distribution. An alpha level of 0.05 will be used to determine statistical significance.\n\nThe investigators will use the following statistical approaches to evaluate the feasibility and acceptability of P3-EX for physicians to use to prescribe exercise to patients with CVD risk factors. The investigators will use a one-sided Wilcoxon signed-rank test (one sample case) to assess whether the physician mHealth Application Usability Questionnaire ratings of P3-EX and the ACSM-PAVS are above the null hypothesis middle score of 4.0 on the Likert scale, and whether System Usability Scale ratings are above the average score of 68/100. A two-sided Wilcoxon signed-rank (paired two-sample case) test will assess differences in physician usability questionnaire scores between P3-EX and the ACSM-PAVS. The investigators will use normal linear regression to test relationships between the three domains on the mHealth Application Usability Questionnaire and the usage time of P3-EX.\n\nThe investigators will use the following statistical approaches to explore the preliminary efficacy of P3-EX to improve patient PA levels, CVD risk factors, and exercise adherence. A one-way Analysis of Variance will test if pre-intervention values are equal between groups, indicating if there is a need to adjust for potential covariates related to demographics, medication use, and/or pre-intervention PA level and CVD risk factor values. The investigators will use a repeated measures two-way Analysis of Covariance using a linear mixed effects model to test patient differences in PA level and CVD risk factor changes over 12 weeks between the P3-EX and the ACSM-PAVS groups, adjusting for potential covariates related to demographics, medication use, and/or pre-intervention values.\n\nScientific Rationale\n\nThe novelty of P3-EX is supported by the investigators' systematic review which evaluated whether there are decision support tools on the market that utilize evidence-based ExRx standards of the ACSM and AHA to target CVD risk factors. The investigators evaluated 219 exercise apps that were rated ≥4 out of 5 overall with ≥1000 reviews, free to download, and not gender specific. Of the 219 apps, very few (0 to 4.3%) were evidence based, had a preparticipation screening protocol, framed exercise plans by the FITT of ExRx, specified special considerations, or focused on chronic diseases or health conditions, and only 28% built CVD risk factor profiles. The investigators concluded there are no evidence-based ExRx apps on the market like P3-EX.\n\nThe potential usability and user satisfaction of P3-EX in the healthcare setting is further supported by the investigators' feasibility survey study. A total of 309 healthcare providers and allied health professionals, including 101 physicians, completed a timed case study using the P3-EX web-based algorithm, and then rated its satisfaction and usability using the Mobile Application Rating Scale. Most of the respondents (93%) agreed they would recommend P3-EX to their colleagues, the primary goal of any feasibility study, and 80% agreed P3-EX produced safe ExRx and were satisfied with P3-EX. Also, over 70% agreed P3-EX would make their patients healthier and could save them time, prescribing exercise in an average time of 4.6 minutes.\n\nConclusions\n\nThis protocol provides the scientific rationale and methodology to test P3-EX within a real-world clinical setting, to inform the feasibility of using P3-EX as a digital health support tool to be used by physicians to prescribe personalized FITT ExRx to their patients with CVD risk factors, and the preliminary efficacy of P3-EX to improve patient cardiovascular health and PA levels. If successful, this trial could demonstrate that P3-EX is a solution for physicians to overcome their barriers to ExRx, which includes lacking the tools, training, time, and confidence. The investigators intend to use the pilot data for secondary outcomes to power a larger clinical trial to evaluate the efficacy of P3-EX for improving PA levels and CVD risk factors."}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT'], 'maximumAge': '64 Years', 'minimumAge': '18 Years', 'healthyVolunteers': False, 'eligibilityCriteria': 'Physician Inclusion Criteria\n\n1. Practicing medical doctors employed at the study recruitment sites\n2. Do not recommend written exercise programs or plans to their patients, nor refer them to exercise clinics or exercise professionals\n3. Are willing to recruit two of their patients to deliver Prioritize Personalize Prescribe EXercise (P3-EX) and American College of Sports Medicine Physical Activity Vital Sign (ACSM PAVS)\n\nPatient Inclusion Criteria\n\n1. Sedentary: have not performed planned, structured physical activity at moderate intensity for ≥30 minutes on ≥3 days per week in the last 3 months\n2. Adults: ≥18 and ≤64 yrs\n3. ≥1 cardiovascular disease risk factors: Having obesity, hypertension, dyslipidemia, and/or diabetes (or prediabetes)\n\n * Obesity: BMI ≥30 kg/m2 or WC \\>102 cm (40 in) for men and \\>88 cm (35 in) for women\n * Hypertension: Systolic BP ≥130 mm Hg and/or diastolic BP ≥80 mm Hg, or on antihypertensive medication\n * Dyslipidemia: LDL-C ≥130 mg/dL (3.37 mmol/L), or HDL-C \\<40 mg/dL (1.04 mmol/L) in men and \\<50 mg/dL (1.3 mmol/L) in women, or non-HDL-C ≥160 mg/dL (4.14 mmol/L), or on lipid-lowering medication, or TC ≥200 mg/dL (5.18 mmol/L)\n * Diabetes (or prediabetes): FBG ≥100 mg/dL or HbA1c ≥5.7%, or on medication for diabetes\n4. Healthy: Having no signs or symptoms of or have cardiovascular or renal disease, or other diseases or health conditions that significantly limit physical activity engagement\n5. Not pregnant or lactating\n6. Not a cigarette smoker or quit smoking ≥6 months ago\n7. Consume \\<2 alcoholic drinks daily\n8. Able to use a computer or phone with internet access\n9. Fluent in English\n10. Willing to maintain their medication routine and habitual diet and not follow other exercise or nutrition programs.\n\nPatient Exclusion Criteria 4a. Have pain or discomfort in the chest, neck, jaw, or arms; dizziness or syncope; shortness of breath at rest or with mild exertion; unusual fatigue or shortness of breath with usual activities; orthopnea; ankle edema; intermittent claudication; palpitations; or known heart murmur 4b. Stroke or cancer survivors or currently have cancer, chronic obstructive pulmonary disease, musculoskeletal injury, chronic back pain, depression, dementia, or other diseases or health conditions that are deemed to significantly limit physical activity engagement.'}, 'identificationModule': {'nctId': 'NCT07238556', 'acronym': 'P3-EX', 'briefTitle': 'A Novel Digital Tool Physicians Can Use to Prescribe Exercise to Patients With Cardiovascular Disease Risk Factors', 'organization': {'class': 'OTHER', 'fullName': 'University of Connecticut'}, 'officialTitle': 'Feasibility and Acceptability of a Novel Algorithm for Physicians to Prescribe Personalized Exercise Prescriptions to Patients With Cardiovascular Disease Risk Factors: Study Protocol for an Exploratory Randomized Controlled Crossover Trial', 'orgStudyIdInfo': {'id': 'E25-0518'}, 'secondaryIdInfos': [{'id': 'N/A (Internal Funding)', 'type': 'OTHER_GRANT', 'domain': 'University of Connecticut Department of Kinesiology'}, {'id': 'N/A (Internal Funding)', 'type': 'OTHER_GRANT', 'domain': 'University of Connecticut Scholarship Facilitation Fund'}, {'id': 'E-HHC-2025-0198', 'type': 'OTHER', 'domain': 'Hartford HealthCare Institutional Review Board'}]}, 'armsInterventionsModule': {'armGroups': [{'type': 'EXPERIMENTAL', 'label': 'Prioritizes Personalizes Prescribes EXercise (P3-EX)', 'description': "Physicians will use Prioritizes Personalizes Prescribes Exercise (P3-EX), hosted by a web-based platform, to deliver P3-EX, an evidence-based personalized exercise prescription to improve cardiovascular disease (CVD) risk factors.\n\nP3-EX will determine whether the patient needs medical clearance. P3-EX will score the patient's CVD risk factors using an adapted American Heart Association Life's Essential 8 cardiovascular health scoring system to determine the CVD risk factor posing the greatest risk. If ≥2 CVD risk factors are tied for the greatest risk, P3-EX will prompt the physician to choose an American College of Sports Medicine strategy to prioritize one CVD risk factor to personalize the Frequency, Intensity, Time, and Type (FITT) exercise prescription. P3-EX will also produce special exercise considerations for the prioritized CVD risk factor. The physician will print the exercise prescription and give it to the patient to perform for 12 weeks.", 'interventionNames': ['Behavioral: Experimental - 12 Week P3-EX Unsupervised Exercise Program with Virtual Weekly Oversight from Graduate Research Assistants']}, {'type': 'ACTIVE_COMPARATOR', 'label': 'American College of Sports Medicine Physical Activity Vital Sign (ACSM-PAVS)', 'description': "Physicians will use a hard copy instruction manual adapted from the Exercise is Medicine HealthCare Providers' Action Guide to deliver the American College of Sports Medicine Physical Activity Vital Sign (ACSM-PAVS), a generic exercise program to improve general health.\n\nThe physician will ask the patient exercise preparticipation health screening questions to determine whether medical clearance is needed. The physician will assess their patient's physical activity levels as a vital sign (i.e., minutes per week of moderate to vigorous intensity exercise and days per week of resistance exercise). The physician will give the patient the ACSM-PAVS exercise program as a handout, which recommends the Physical Activity Guidelines for Americans of 150 minutes per week of moderate and/or 75 minutes per week of vigorous intensity aerobic exercise (or a combination) and 2 days per week of muscular strengthening exercise.", 'interventionNames': ['Behavioral: Active Control - 12 Week ACSM-PAVS Unsupervised Exercise Program with Virtual Weekly Oversight from Graduate Research Assistants']}], 'interventions': [{'name': 'Experimental - 12 Week P3-EX Unsupervised Exercise Program with Virtual Weekly Oversight from Graduate Research Assistants', 'type': 'BEHAVIORAL', 'description': 'UConn Graduate Research Assistants will provide patients with virtual weekly oversight to follow their P3-EX unsupervised exercise program for 12 weeks. Patients will choose the location and the FITT of exercise they prefer. UConn Graduate Research Assistants will provide all patients with a 12-week exercise program information packet containing progressive FITT exercise recommendations for their exercise program. Patients will use an exercise diary called the Timeline Followback for Exercise to record the FITT of exercise daily. Patients will attend two virtual study visits led by UConn Graduate Research Assistants during the first week and midway through the intervention to receive standardized guidance on how they are doing following their exercise program. UConn Graduate Research Assistants will email all patients weekly to provide their progressive FITT exercise recommendations and summary reports of their Timeline Followback for Exercise recordings.', 'armGroupLabels': ['Prioritizes Personalizes Prescribes EXercise (P3-EX)']}, {'name': 'Active Control - 12 Week ACSM-PAVS Unsupervised Exercise Program with Virtual Weekly Oversight from Graduate Research Assistants', 'type': 'BEHAVIORAL', 'description': 'University of Connecticut (UConn) Graduate Research Assistants will provide patients with virtual weekly oversight to follow their ACSM-PAVS unsupervised exercise program for 12 weeks. Patients will choose the location and the FITT of exercise they prefer. UConn Graduate Research Assistants will provide all patients with a 12-week exercise program information packet containing progressive FITT exercise recommendations for their exercise program. Patients will use an exercise diary called the Timeline Followback for Exercise to record the FITT of exercise daily. Patients will attend two virtual study visits led by UConn Graduate Research Assistants during the first week and midway through the intervention to receive standardized guidance. UConn Graduate Research Assistants will email all patients weekly to provide their progressive FITT exercise recommendations and summary reports of their Timeline Followback for Exercise recordings.', 'armGroupLabels': ['American College of Sports Medicine Physical Activity Vital Sign (ACSM-PAVS)']}]}, 'contactsLocationsModule': {'locations': [{'zip': '06030', 'city': 'Farmington', 'state': 'Connecticut', 'country': 'United States', 'contacts': [{'name': 'Peter F Robinson, MD', 'role': 'CONTACT', 'email': 'perobinson@uchc.edu', 'phone': '(860) 679-3343'}], 'facility': 'UConn Health', 'geoPoint': {'lat': 41.71982, 'lon': -72.83204}}, {'zip': '06102', 'city': 'Hartford', 'state': 'Connecticut', 'country': 'United States', 'contacts': [{'name': 'Antonio B Fernandez, MD', 'role': 'CONTACT', 'email': 'Antonio.Fernandez@hhchealth.org', 'phone': '(860) 972-1695'}], 'facility': 'Hartford HealthCare', 'geoPoint': {'lat': 41.76371, 'lon': -72.68509}}, {'zip': '06269', 'city': 'Storrs', 'state': 'Connecticut', 'country': 'United States', 'contacts': [{'name': 'Linda S Pescatello, PhD', 'role': 'CONTACT', 'email': 'linda.pescatello@uconn.edu', 'phone': '(860) 486-0008'}], 'facility': 'University of Connecticut', 'geoPoint': {'lat': 41.80843, 'lon': -72.24952}}], 'centralContacts': [{'name': 'Alexander J Wright, MS', 'role': 'CONTACT', 'email': 'Alexander.Wright@hhchealth.org', 'phone': '(860) 486-6814'}, {'name': 'Linda S Pescatello, PhD', 'role': 'CONTACT', 'email': 'linda.pescatello@uconn.edu', 'phone': '(860) 486-0008'}], 'overallOfficials': [{'name': 'Linda S Pescatello, PhD', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'Department of Kinesiology, University of Connecticut'}, {'name': 'Antonio B Fernandez, MD', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'Hartford HealthCare Heart & Vascular Institute, Hartford Hospital'}, {'name': 'Gregory Panza, PhD', 'role': 'STUDY_DIRECTOR', 'affiliation': 'Department of Research Administration, Hartford HealthCare'}]}, 'ipdSharingStatementModule': {'infoTypes': ['STUDY_PROTOCOL', 'SAP', 'ICF'], 'timeFrame': 'All de-identified IPD will be available upon reasonable request with no time limit.', 'ipdSharing': 'YES', 'description': 'The analyzable dataset for de-identified individual participant data (IPD) will be made available upon request and provided as supplementary material with any published manuscripts.', 'accessCriteria': 'All de-identified IPD will be shared via email to researchers who reasonably request the dataset.'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'University of Connecticut', 'class': 'OTHER'}, 'collaborators': [{'name': 'Hartford HealthCare', 'class': 'OTHER'}, {'name': 'UConn Health', 'class': 'OTHER'}], 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'Board of Trustees Distinguished Professor', 'investigatorFullName': 'Linda Pescatello', 'investigatorAffiliation': 'University of Connecticut'}}}}