[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"trial:NCT03288207":3,"trial-entities:NCT03288207":171,"trial-summary:NCT03288207":175},{"id":4,"nct_id":4,"org_study_id":5,"brief_title":6,"official_title":7,"overall_status":8,"completion_date":9,"status_verified_date":10,"last_update_date":11,"start_date":12,"sponsor_name":13,"lead_sponsor_class":14,"has_dmc":15,"brief_summary":16,"detailed_description":17,"conditions":18,"keywords":20,"study_type":24,"primary_purpose":25,"phases":26,"enrollment_info":28,"interventions":31,"primary_outcomes":63,"secondary_outcomes":68,"sex":92,"minimum_age":93,"maximum_age":94,"healthy_volunteers":95,"eligibility_criteria":96,"std_ages":117,"locations":120,"central_contacts":137,"overall_officials":146,"references":149,"see_also_links":167},"NCT03288207","170162","Tailoring Mobile Health Technology to Reduce Obesity and Improve Cardiovascular Health in Resource-Limited Neighborhood Environments","Tailoring Mobile Health Technology to Reduce Obesity and Improve Cardiovascular Health in Resource-Limited Neighborhood Environments: A Multi-Level, Community-Based Physical Activity Intervention","RECRUITING","2027-08-04","2026-08-20","2026-08-31","2018-06-21","National Heart, Lung, and Blood Institute (NHLBI)","NIH",null,"Background:\n\nHeart disease is a leading cause of death. People can reduce their heart disease risk by exercising more. Mobile health technology may make people more successful at increasing their exercise. This includes things like physical activity monitors and smartphone apps.\n\nObjective:\n\nTo find out if mobile health technology can increase physical activity.\n\nEligibility:\n\nAfrican American women ages 21-75 who:\n\n* Are overweight or obese\n* Live in certain areas near Washington, DC\n* Have a smartphone that can use the study app\n\nDesign:\n\nAt visit 1, participants will\n\n* Answer survey questions. These may be about medical history, physical activity, and weight. They may also cover body image, health perception, and spirituality.\n* Have body size measured and get blood tests\n* Get a device to wear on the wrist. It will record physical activity and hours of sleep.\n* Learn how to download and use the study mobile app\n\nFor 2 weeks, researchers will collect data about participants physical activity.\n\nThen participants will have a study visit with additional blood tests.\n\nAll participants will get messages from the app that encourage exercise.\n\nSome participants will get data from the app about exercise near their home or work.\n\nSome participants may get face-to-face coaching.\n\nParticipants may get wireless devices. These measure body weight, blood pressure, and blood glucose. Participants can measure these at home and upload the data to the app for the study.\n\nParticipants will have visits after 3 and 6 months. They will repeat the visit 1 tests.","Targeted, effective behavioral interventions are critically needed to ameliorate the disproportionate prevalence of poor cardiometabolic health for African-American women. We propose a sequential, multiple-assignment, randomized trial targeting physical activity (PA) among at-risk African American women in resource-limited, Washington, D.C. communities using mobile health (mHealth) technology. We hypothesize that by beginning a community-based, adaptive PA intervention with remote coaching tailored to neighborhood environment PA resources, we will see greater increases in PA levels as compared to standard remote coaching. In Aim 1, we will determine if beginning an adaptive intervention with remote coaching tailored to neighborhood environment resources and delivered using mHealth technology (wearables and mobile applications) will lead to a greater PA increase (as measured by steps per day) as compared to standard remote coaching. In Aim 2, we will examine which of four embedded adaptive interventions produce the largest PA increase over the six-month study period. In Aim 3, we will evaluate the feasibility of remote capture of cardiometabolic measures, including blood pressure, weight, and glucose, using mHealth technology. We will also examine intervention effects on cardiometabolic health (adiposity, blood pressure, fasting lipids\u002Fglucose, self-reported PA, dietary intake, cigarette smoking). In Aim 4a, we will characterize effects of increasing PA on integrated serologic cytokine\u002Fchemokine and lipid inflammatory intermediates to identify potential novel inflammatory pathways linked to cardiometabolic risk phenotypes most responsive to the multi-level, community-based PA intervention. In Aim 4b, we examine the feasibility of measuring potential psychosocial and behavioral mediators of the relationship between PA change and CV health. In Aim 5, we will conduct iterative testing of the mobile health technology used in the protocol with a user-centered design approach. In Aim 6a and 6b, we will assess for changes in cardiac structure and function as well as body composition using MRI before and after the intervention. In Aim 7a and 7b, the intersection of common biological signatures of menopause, sleep disruption, and blood pressure as a marker of cardiometabolic risk in the setting of adverse social determinants of health will be investigated in the study population. We will also determine the feasibility of measuring behavioral and psychosocial mediating factors of the relationship between PA change and cardiometabolic health in this intervention, including chronic psychological\u002Fenvironmental stress and sedentary behavior\u002Fsleep. Also, since PA has the potential to improve sleep, vascular function, autonomic regulation, and inflammatory status, incorporating the sleep study and ambulatory blood pressure monitoring (ABPM) further provides more insights on how the behavioral changes from the Step-it-Up intervention translate into clinically meaningful physiological improvements in this population.\n\nIn addition, because of the COVID-19 pandemic in 2020, we will measure exposure to COVID-19 and psychosocial stress caused by the pandemic as potential confounders of immunologic outcomes and psychosocial stressors in this study. Finally, we will explore the relationships between PA, social determinants of health, and biological markers in this intervention cohort and compare them to other populations using available cohort data. This project provides fundamental knowledge towards the development of tailored, effective behavioral interventions incorporating mHealth technology to promote health among populations most impacted by health disparities.",[19],"Obesity",[21,19,22,23],"Community-Based Participatory Research","Cardiovascular Disease Risk","Social Determinants of Health","INTERVENTIONAL","BASIC_SCIENCE",[27],"NA",{"count":29,"type":30},325,"ESTIMATED",[32,38,41,44,47,51,55,59],{"type":33,"name":34,"description":34,"armGroupLabels":35},"DEVICE","Step it Up mobile app",[36,37],"Group 1 Label: PA monitor with remote coaching tailored to place","Group 2 Label: PA monitor with standard remote coaching (SRC)",{"type":33,"name":39,"description":39,"armGroupLabels":40},"Global Positioning System (GPS) Device",[36,37],{"type":33,"name":42,"description":42,"armGroupLabels":43},"Bluetooth-enabled scale",[36,37],{"type":33,"name":45,"description":45,"armGroupLabels":46},"Bluetooth-enabled glucometer",[36,37],{"type":33,"name":48,"description":49,"armGroupLabels":50},"MRI: Image Reconstruction and Analysis Software (Device Manufacturer: NIH)","Image Reconstruction and Analysis Software",[36,37],{"type":33,"name":52,"description":53,"armGroupLabels":54},"MRI: Research pulse sequences (Device Manufacturer: NIH)","pulse sequences",[36,37],{"type":33,"name":56,"description":57,"armGroupLabels":58},"MRI: radiofrequency coils (Device Manufacturer: Siemens Medical Solutions USA, Inc.)","radiofrequency coils",[36,37],{"type":33,"name":60,"description":61,"armGroupLabels":62},"AMRA Researcher Image reconstruction software","Image reconstruction software",[36,37],[64],{"measure":65,"description":66,"timeFrame":67},"The difference in physical activity (PA) change between an adaptive intervention with remote coaching tailored to neighborhood resources (referred to as tailored-to-place coaching) versus beginning w\u002F standard remote coaching","The difference in physical activity (PA) change (as measured by steps\u002Fday) by beginning an adaptive intervention with remote coaching tailored to neighborhood resources (referred to as tailored-to-place coaching) versus beginning with standard remote coaching.","baseline, and up to 6 months",[69,73,76,79,82,85,88],{"measure":70,"description":71,"timeFrame":72},"Measure exposure to COVID-19 and psychosocial stress caused by the pandemic","Measure exposure to COVID-19 and psychosocial stress caused by the pandemic as potential confounders of immunologic outcomes and psychosocial stressors","Up to 6 months",{"measure":74,"description":75,"timeFrame":72},"Examine the feasibility of measuring potential psychosocial and behavioral mediators of the relationship between PA change and CV health","Examine the feasibility of measuring potential psychosocial and behavioral mediators of the relationship between PA change and CV health, such as chronic stress and sedentary behavior\u002Fsleep",{"measure":77,"description":78,"timeFrame":72},"Identify potential novel inflammatory pathways linked to cardiometabolic risk phenotypes","Characterize effects of increasing PA on integrated serologic cytokine\u002Fchemokine and lipid inflammatory intermediates to identify potential novel inflammatory pathways linked to cardiometabolic risk phenotypes most responsive to the multi-level, community-based PA intervention",{"measure":80,"description":81,"timeFrame":72},"Examine the effect of an adaptive community-based intervention targeting Physical Activity on Cardiovascular health measures","Examine the effect of an adaptive community-based intervention targeting Physical Activity on Cardiovascular health measures (BMI, blood pressure, fasting lipids, fasting plasma glucose, dietary intake, \\[self-reported minutes of moderate\u002Fvigorous PA, cigarette smoking)",{"measure":83,"description":84,"timeFrame":72},"Examine the feasibility of incorporating methods for remote capture of CV health measures","Examine the feasibility of incorporating methods for remote capture of CV health measures (weight, blood pressure, blood glucose) in a target community-based population",{"measure":86,"description":87,"timeFrame":72},"Determine which embedded adaptive interventions produce the largest PA increase","Determine which of four embedded adaptive interventions produce the largest PA increase over six months",{"measure":89,"description":90,"timeFrame":91},"Exploratory Aim: Examine the relationships between PA, social determinants of health, and biological markers in this intervention population and through comparison to other populations using available cohort data","To measure biological markers that may include vascular markers (i.e. extracellular vesicles, markers of vascular and endothelial function), transcriptomic (i.e, RNA sequencing), epigenomic, proteomic, and metabolomic markers, immune cell measures, and markers of inflammation and chronic stress.","up to 6 months","FEMALE","21 Years","75 Years",true,{"inclusion":97,"exclusion":107,"raw_text":116},[98,99,100,101,102,103,104,105,106],"Must be an African-American female","Must be within the age of 21-75 years old","Must have overweight or obesity (Body Mass Index (BMI) \\>= 25 kg\u002Fm\\^2)","Must live in Washington DC Wards (5, 7, or 8) or live in Prince George s County, Maryland","Must have a smartphone that is compatible with the study software (mobile app)","Must be willing to use the software on personal smartphone for the study","Must be able to provide consent","Must be willing to wear the wrist-worn physical activity device for the study","Must not be pregnant",[108,109,110,111,112,113,114,115],"Medical condition, including heart failure, recent unintentional weight loss or physical limitation, that might prohibit safe participation in physical activity for any reason","Heart disease as indicated by history of myocardial infarction in past 1 year, documented obstructive coronary artery disease on coronary angiography, coronary artery stent placement within the last year significant structural heart disease (e.g. hypertrophic or dilated cardiomyopathy with EF \\\u003C35%, severe valvular heart disease) with evidence of decompensation.","Pregnant women due to large hormonal changes during pregnancy that affect study variables and potential pregnancy-related restrictions on exercise. All participants of childbearing potential will need to self-report a negative pregnancy at the screening visit, baseline visit, and at the three-month and six-month visits, unless the participant self-reports being postmenopausal, having had a tubal ligation, or having undergone a complete hysterectomy.","they are unwilling or unable to be evaluated and followed as clinically indicated (examples might include participants with severe behavioral problems who refuse physical examination).","they do not have a primary healthcare provider or do not accept recommendations provided by study team for provider resources \u002F referral networks.","they have a chronic or acute medical condition severe enough to interfere with overnight sleep study acquisition, such as a tracheotomy, uncontrolled seizure disorder, ventilator dependency, or history of stroke or major neurologic insult.","they work night shift.","they have started any new medications that modify sleep within the last two weeks.","* INCLUSION CRITERIA:\n\nIndividuals eligible for this protocol have overweight or obesity (BMI \\>= 25 kg\u002Fm\\^2) African American women aged 21-75 years who live in Washington, DC Wards 5, 7, or 8 and neighboring areas of Prince George s County, MD. Eligible participants should also have access to a smartphone compatible with the mobile app for the protocol that they can use for the study. Eligible participants must be able to provide informed consent independently and also speak and read English at the 8th grade level.\n\nEXCLUSION CRITERIA:\n\n* Medical condition, including heart failure, recent unintentional weight loss or physical limitation, that might prohibit safe participation in physical activity for any reason\n* Heart disease as indicated by history of myocardial infarction in past 1 year, documented obstructive coronary artery disease on coronary angiography, coronary artery stent placement within the last year significant structural heart disease (e.g. hypertrophic or dilated cardiomyopathy with EF \\\u003C35%, severe valvular heart disease) with evidence of decompensation.\n* Pregnant women due to large hormonal changes during pregnancy that affect study variables and potential pregnancy-related restrictions on exercise. All participants of childbearing potential will need to self-report a negative pregnancy at the screening visit, baseline visit, and at the three-month and six-month visits, unless the participant self-reports being postmenopausal, having had a tubal ligation, or having undergone a complete hysterectomy.\n\nPilot Study INCLUSION CRITERIA:\n\n* Must be an African-American female\n* Must be within the age of 21-75 years old\n* Must have overweight or obesity (Body Mass Index (BMI) \\>= 25 kg\u002Fm\\^2)\n* Must live in Washington DC Wards (5, 7, or 8) or live in Prince George s County, Maryland\n* Must have a smartphone that is compatible with the study software (mobile app)\n* Must be willing to use the software on personal smartphone for the study\n* Must be able to provide consent\n* Must be willing to wear the wrist-worn physical activity device for the study\n* Must not be pregnant\n\nEligibility for Post-Menopausal Status for Sleep Sub-study:\n\nEligibility is limited to post-menopausal women who have either completed or are currently enrolled in the main study. Confirmation of post-menopausal status will be determined by review of medical history prior to final eligibility assessment for the study. In patients with prior hysterectomy and retained ovaries, menopause cannot be diagnosed using menstrual criteria. Diagnosis will be made clinically based on age consistent with natural menopause ( \\>=45) and the presence of menopausal symptoms, such as vasomotor or genitourinary symptoms.\n\nIn addition to the Step it Up Study's exclusion criteria, during the screening visit, which can happen by telephone or telehealth, participants will be asked for certain conditions such as bilateral arm deformity, significant peripheral vascular disease, lymphedema, an arteriovenous (AV) fistula or graft in the monitoring arm, severe skin conditions or wounds at the cuff site, inability to tolerate cuff inflation, severe blood disorder or coagulopathy, and any other condition deemed unsafe at the discretion of the principal investigator.\n\nAdditionally, participants will not be eligible for the optional Sleep Sub-study if:\n\n* they are unwilling or unable to be evaluated and followed as clinically indicated (examples might include participants with severe behavioral problems who refuse physical examination).\n* they do not have a primary healthcare provider or do not accept recommendations provided by study team for provider resources \u002F referral networks.\n* they have a chronic or acute medical condition severe enough to interfere with overnight sleep study acquisition, such as a tracheotomy, uncontrolled seizure disorder, ventilator dependency, or history of stroke or major neurologic insult.\n* they work night shift.\n* they have started any new medications that modify sleep within the last two weeks.\n\nOptional MRI Tests\n\nSubjects will be screened for implanted metal objects or devices that may be incompatible with MRI (i.e. cerebral aneurysm clip, cochlear implant, pacemaker, etc.) These subjects will be eligible to proceed with study enrollment but will not undergo the optional MRI study.",[118,119],"ADULT","OLDER_ADULT",[121],{"facility":122,"status":8,"city":123,"state":124,"zip":125,"country":126,"contacts":127,"geoPoint":134},"National Institutes of Health Clinical Center","Bethesda","Maryland","20892","United States",[128],{"name":129,"role":130,"phone":131,"phoneExt":132,"email":133},"For more information at the NIH Clinical Center contact Office of Patient Recruitment (OPR)","CONTACT","800-411-1222","TTY8664111010","prpl@cc.nih.gov",{"lat":135,"lon":136},38.98067,-77.10026,[138,142],{"name":139,"role":130,"phone":140,"email":141},"Marie Marah, R.N.","(301) 640-1701","marie.marah@nih.gov",{"name":143,"role":130,"phone":144,"email":145},"Tiffany M Powell-Wiley, M.D.","(301) 496-5817","powelltm2@mail.nih.gov",[147],{"name":143,"affiliation":13,"role":148},"PRINCIPAL_INVESTIGATOR",[150,154,157,160,164],{"pmid":151,"type":152,"citation":153},"26811276","BACKGROUND","Writing Group Members; Mozaffarian D, Benjamin EJ, Go AS, Arnett DK, Blaha MJ, Cushman M, Das SR, de Ferranti S, Despres JP, Fullerton HJ, Howard VJ, Huffman MD, Isasi CR, Jimenez MC, Judd SE, Kissela BM, Lichtman JH, Lisabeth LD, Liu S, Mackey RH, Magid DJ, McGuire DK, Mohler ER 3rd, Moy CS, Muntner P, Mussolino ME, Nasir K, Neumar RW, Nichol G, Palaniappan L, Pandey DK, Reeves MJ, Rodriguez CJ, Rosamond W, Sorlie PD, Stein J, Towfighi A, Turan TN, Virani SS, Woo D, Yeh RW, Turner MB; American Heart Association Statistics Committee; Stroke Statistics Subcommittee. Executive Summary: Heart Disease and Stroke Statistics--2016 Update: A Report From the American Heart Association. Circulation. 2016 Jan 26;133(4):447-54. doi: 10.1161\u002FCIR.0000000000000366. No abstract available.",{"pmid":155,"type":152,"citation":156},"21899451","Boggs DA, Rosenberg L, Cozier YC, Wise LA, Coogan PF, Ruiz-Narvaez EA, Palmer JR. General and abdominal obesity and risk of death among black women. N Engl J Med. 2011 Sep 8;365(10):901-8. doi: 10.1056\u002FNEJMoa1104119.",{"pmid":158,"type":152,"citation":159},"19833999","Lightwood J, Bibbins-Domingo K, Coxson P, Wang YC, Williams L, Goldman L. Forecasting the future economic burden of current adolescent overweight: an estimate of the coronary heart disease policy model. Am J Public Health. 2009 Dec;99(12):2230-7. doi: 10.2105\u002FAJPH.2008.152595. Epub 2009 Oct 15.",{"pmid":161,"type":162,"citation":163},"41057147","DERIVED","Troendle JF, Sur A, Leifer ES, Powell-Wiley T. Sensitivity Analyses for Missing in Repeatedly Measured Outcome Data. Stat Med. 2025 Oct;44(23-24):e70282. doi: 10.1002\u002Fsim.70282.",{"pmid":165,"type":162,"citation":166},"33371027","Tamura K, Vijayakumar NP, Troendle JF, Curlin K, Neally SJ, Mitchell VM, Collins BS, Baumer Y, Gutierrez-Huerta CA, Islam R, Turner BS, Andrews MR, Ceasar JN, Claudel SE, Tippey KG, Giuliano S, McCoy R, Zahurak J, Lambert S, Moore PJ, Douglas-Brown M, Wallen GR, Dodge T, Powell-Wiley TM. Multilevel mobile health approach to improve cardiovascular health in resource-limited communities with Step It Up: a randomised controlled trial protocol targeting physical activity. BMJ Open. 2020 Dec 21;10(12):e040702. doi: 10.1136\u002Fbmjopen-2020-040702.",[168],{"label":169,"url":170},"NIH Clinical Center Detailed Web Page","https:\u002F\u002Fclinicalstudies.info.nih.gov\u002Fcgi\u002Fdetail.cgi?A_2017-H-0162.html",{"nct_id":4,"conditions":172,"biomarkers":174},[19,173],"Risk of cardiovascular disease",[],{"nct_id":4,"found":95,"summary":176,"prompt_version":186},{"design":177,"status":178,"heading":179,"summary":180,"follow_up":181,"word_count":182,"commitments":183,"compensation":184,"drugs_mentioned":185},"This is an interventional study with a planned enrollment of 325 participants. It will compare two different coaching approaches for increasing physical activity.","completed","Mobile Health Technology for Obesity and Heart Health in African American Women","This study is looking at how mobile health technology can help African American women who are overweight or obese improve their physical activity and heart health. Researchers want to see if using the \"Step it Up mobile app\" along with devices like a GPS device, Bluetooth-enabled scale, and Bluetooth-enabled glucometer, can lead to more physical activity. The study will compare two approaches: one that offers coaching tailored to your neighborhood resources, and another that starts with standard remote coaching. The main goal is to see the difference in physical activity changes between these two groups over six months. You may be able to join if you are an African American woman, aged 21-75, overweight or obese, live in specific areas near Washington, DC, and have a compatible smartphone.","Physical activity changes will be measured at baseline and up to 6 months.",128,"You will answer survey questions about your health, physical activity, and other topics at the first visit. The study will last for six months.","Not stated in the trial record.",[34,42,45],"v2"]