Ignite Creation Date:
2025-12-24 @ 11:45 PM
Ignite Modification Date:
2025-12-25 @ 9:38 PM
Study NCT ID:
NCT07067151
Status:
ENROLLING_BY_INVITATION
Last Update Posted:
2025-12-24
First Post:
2025-07-12
Is NOT Gene Therapy:
False
Has Adverse Events:
False
Brief Title:
Using Smartwatches to Monitor Smoking in Real-life Situations
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D012907', 'term': 'Smoking'}], 'ancestors': [{'id': 'D001519', 'term': 'Behavior'}]}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'PROSPECTIVE', 'observationalModel': 'CASE_ONLY'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 30}}, 'statusModule': {'overallStatus': 'ENROLLING_BY_INVITATION', 'startDateStruct': {'date': '2025-12-29', 'type': 'ESTIMATED'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2025-12-11', 'completionDateStruct': {'date': '2028-03-20', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2025-12-23', 'studyFirstSubmitDate': '2025-07-12', 'studyFirstSubmitQcDate': '2025-07-12', 'lastUpdatePostDateStruct': {'date': '2025-12-24', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2025-07-16', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2026-04-30', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'The primary endpoint is to evaluate changes in biomarker measurements obtained from wearables, which include heart rate, heart rate variability, respiratory rate, blood oxygen levels & hand/arm movement, across three smoking stages.', 'timeFrame': '7 days', 'description': 'As the research progresses, the team will work diligently to gather a robust dataset from various sources, including wearable devices, lab sessions, medical-grade information, and detailed questionnaires. This comprehensive approach will enable the identification of specific biomarkers and hand-mouth gestures related to the different stages of tobacco use: pre-smoking, active smoking, and post-smoking. By analyzing these diverse data sources, the team aims to gain valuable insights into the physiological and behavioral patterns associated with each stage. This knowledge will not only enrich our understanding of tobacco use but also pave the way for developing targeted interventions and tailored support systems for individuals seeking to quit smoking. Through collaboration and innovative analysis, this research endeavors to create more effective strategies for smoking cessation, ultimately fostering healthier lifestyles.'}]}, 'oversightModule': {'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['Nicotine', 'Smoking', 'Smart watches', 'Pre-smoking', 'Cessation support', 'Thermal-sensor wearables', 'Home-based assessment', 'Cigarettes', 'Observational'], 'conditions': ['Smoking']}, 'referencesModule': {'references': [{'pmid': '34815538', 'type': 'BACKGROUND', 'citation': 'Hojjatinia S, Daly ER, Hnat T, Hossain SM, Kumar S, Lagoa CM, Nahum-Shani I, Samiei SA, Spring B, Conroy DE. Dynamic models of stress-smoking responses based on high-frequency sensor data. NPJ Digit Med. 2021 Nov 23;4(1):162. doi: 10.1038/s41746-021-00532-2.'}, {'pmid': '26045249', 'type': 'BACKGROUND', 'citation': 'Hoeppner BB, Hoeppner SS, Seaboyer L, Schick MR, Wu GW, Bergman BG, Kelly JF. 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Epub 2024 Jul 2.'}, {'pmid': '27956375', 'type': 'BACKGROUND', 'citation': 'Businelle MS, Ma P, Kendzor DE, Frank SG, Vidrine DJ, Wetter DW. An Ecological Momentary Intervention for Smoking Cessation: Evaluation of Feasibility and Effectiveness. J Med Internet Res. 2016 Dec 12;18(12):e321. doi: 10.2196/jmir.6058.'}, {'pmid': '23379613', 'type': 'BACKGROUND', 'citation': 'Businelle MS, Lam CY, Kendzor DE, Cofta-Woerpel L, McClure JB, Cinciripini PM, Wetter DW. Alcohol consumption and urges to smoke among women during a smoking cessation attempt. Exp Clin Psychopharmacol. 2013 Feb;21(1):29-37. doi: 10.1037/a0031009.'}, {'pmid': '20496980', 'type': 'BACKGROUND', 'citation': 'Businelle MS, Kendzor DE, Reitzel LR, Costello TJ, Cofta-Woerpel L, Li Y, Mazas CA, Vidrine JI, Cinciripini PM, Greisinger AJ, Wetter DW. Mechanisms linking socioeconomic status to smoking cessation: a structural equation modeling approach. 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Respiration rate monitoring methods: a review. Pediatr Pulmonol. 2011 Jun;46(6):523-9. doi: 10.1002/ppul.21416. Epub 2011 Jan 31.'}, {'pmid': '11900187', 'type': 'BACKGROUND', 'citation': 'Adler NE, Newman K. Socioeconomic disparities in health: pathways and policies. Health Aff (Millwood). 2002 Mar-Apr;21(2):60-76. doi: 10.1377/hlthaff.21.2.60.'}, {'pmid': '40819863', 'type': 'DERIVED', 'citation': 'El-Toukhy S, Haghayegh S, Leavens E, Sassano F, Tarran R. Use of non-invasive wearables biomonitoring to detect presmoking, smoking and postsmoking stages: protocol for an observational laboratory study. BMJ Open. 2025 Aug 16;15(8):e103292. doi: 10.1136/bmjopen-2025-103292.'}]}, 'descriptionModule': {'briefSummary': 'Background: It is important to quickly identify when people are at risk of smoking. Most current methods rely on people reporting when they smoke or what makes them want to smoke. But this can be hard for people to do and may not always be accurate. Other methods use special gadgets to identify smoking movements, but these may not always work well in real life. We want to see if we can use devices available on the market such as smartwatches to identify signs in the body and hand movements that might indicate when someone is about to smoke, is currently smoking, or has just smoked.\n\nObjective: To record body signs and hand movements before, during, and after smoking in real-life and in a lab to see how they change when someone is craving cigarettes, while a person is smoking, and after a person has smoked.\n\nEligibility: People who are 21 years or older and smoke, do not have more than a high school education, and are low-income earners. To participate in the study, participants have to pass a breath test that shows they smoke cigarettes and, for women, a urine test to show that they are not currently pregnant.\n\nDesign: Participants will complete an eligibility survey to see if they qualify to be in the study. If they qualify, they will answer a brief baseline survey that includes questions about themselves, their health, and their smoking behavior.\n\nParticipants will get a smartwatch to wear for 3 days at home, log each time they are about to smoke and have finished smoking, and answer a 5-question health survey via the app. They will get instructions on how to set up and wear the smartwatch. They will download a mobile application on their phone. The app will collect data from the smartwatch.\n\nParticipants will then come to the lab but will be asked not to smoke or drink alcohol for at least 12 hours. They will have to take a breath test to show they have not smoked or had alcohol. They will also give a blood sample. In the lab, they will sit in a room where they will be hooked to devices that monitor their vitals such as heart rate and blood pressure for one hour. They will also wear a smartwatch on each hand. While they are in the smoking room, they will go through 3 different phases: (a) pre-smoking where they will be asked to stay seated for about 25 minutes, (b) smoking where they will be asked to smoke as many cigarettes of their choice as they want for about 10 to 15 minutes, (c) post-smoking where they will be asked to stay seated, not smoking, for about 25 minutes. They will answer a brief 10-minute health survey before and after the session.\n\nParticipation will last for 3 days of home monitoring and 2 visits to the research clinic that last about 2 hours.', 'detailedDescription': 'Background:\n\nThe study is part of a systematic effort to develop and evaluate a smoking cessation intervention, Quit Journey, a smoking cessation intervention targeting individuals with low socioeconomic status. Specifically, the study will inform the development of just-in-time momentary support to preempt a lapse or prevent it from progressing to a relapse to users of Quit Journey. Additionally, the study fills a gap in wearable-based studies for smoking detection that have thus far relied exclusively on socially and economically advantaged populations by increasing the representation of underserved populations and more accurately developing algorithms for smoking detection that include input from minority populations and pave the way for its replication with a larger sample in real-world settings. Finally, the data collected from this laboratory-based study will serve as baseline parameters for detecting smoking events in free-living conditions. In a planned real-world study, we aim to finetune our smoking-detection algorithms with data collected in natural environments, potentially improving their robustness and generalizability. Insights from this study have real-world applications of smoking-detection algorithms in wearables and mobile applications, ultimately advancing technology-assisted smoking cessation and contributing to reduced smoking rates.\n\nObjectives:\n\n* The objective of this study is to identify wearables-based digital biomarkers that are associated with nicotine deprivation (i.e., pre-smoking) and satiation (i.e., post-smoking) and with smoking episodes (i.e., during smoking). Identifying signature digital biomarkers of smoking can help us to unobtrusively detect with great probability the proclivity to smoke or smoking behavior, which can inform the delivery of momentary support to preempt lapsing or progressing toward a relapse among people attempting to quit smoking.\n* We hypothesize that, relative to pre-smoking, (a) blood oxygen saturation will be lower, (b) heart rate will be higher, (c) heart rate variability will be higher, and (d) respiratory rate will be lower during a smoking episode and post-smoking.\n\nEndpoints:\n\n* Primary endpoint: Changes in wearables-measured biomarker measures including heart rate, heart rate variability, respiratory rate, and blood oxygenation, in addition to hand/arm movement, across three smoking stages.\n* Secondary endpoint: Not applicable.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'maximumAge': '120 Years', 'minimumAge': '21 Years', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': "The study population will comprise individuals aged 21 years or older who currently smoke cigarettes. Participants must have completed a high school education or possess a lower level of academic achievement, and they should be classified as low-income earners. To be eligible for participation in the study, individuals will need to successfully pass a breath test that confirms their smoking status. Furthermore, female participants will be required to undergo a urine test to verify that they are not currently pregnant, ensuring the study's safety and ethical standards. This rigorous participant selection process is designed to ensure a focused and relevant study group that aligns with the research objectives.", 'healthyVolunteers': True, 'eligibilityCriteria': '* INCLUSION CRITERIA:\n\nWe will recruit up to 30 non-treatment seeking participants with low socioeconomic status who smoke. We will strive to have representation across racial and ethnic groups and biological sex.\n\nTo be included in the study, participants must:\n\n* be 21 years or older in compliance with Tobacco 21 laws\n* be maximally high school educated (or equivalent) and earn at or below 200% of the federal poverty line for 2024 corresponding to number of people in their household (US Department of Health and Human Services)\n* have smoked 100 cigarettes in their lifetime and 5+ cigarettes per day in the past year to establish daily smoking status\n* willing to abstain from smoking for \\>=12 hours prior to the lab visit verifiable by a CO reading that is below 10 ppm and retrospectively by minimal nicotine in blood sample\n* willing to abstain from using any nicotine products or devices for (Bullet)12 hours prior to the lab visit\n* willing to abstain from alcohol use for \\>=12 hours prior to the lab session verifiable by breath alcohol concentration (BrAC = 0.000)\n* willing to adhere to all study procedures including agreeing to a blood draw and bringing \\>=1cigarette for use during the study visit\n* have a smartphone compatible with wearable device requirements for Bluetooth and operating system (iphone iOS 14 and higher, Android 9.0 and higher) and willing to download the study apps onto their phone\n* speak English\n* and willing and able to provide informed consent.\n\nParticipants will be excluded if they:\n\n* are not abstinent before the lab session through biochemical verification after two attempts\n* have sought treatment for tobacco/nicotine use in the past 2 months (e.g., on pharmacotherapy for smoking cessation, enrolled in smoking cessation support programs or interventions, currently attempting to change their nicotine/tobacco use) or intend to quit within the next month\n* have past 3-month pulmonary or cardiovascular event, or those who have been hospitalized or visited the emergency room for seizure, stroke, or new heart problems,\n* are pregnant or breastfeeding\n* and are unable or unwilling to provide informed consent.\n\nEXCLUSION CRITERIA:\n\nVulnerable populations will not be enrolled in the study (i.e., adults unable to consent, individuals who are not yet adults, pregnant women, prisoners).'}, 'identificationModule': {'nctId': 'NCT07067151', 'briefTitle': 'Using Smartwatches to Monitor Smoking in Real-life Situations', 'organization': {'class': 'NIH', 'fullName': 'National Institutes of Health Clinical Center (CC)'}, 'officialTitle': 'Use of Noninvasive Wearables Biomonitoring to Detect Pre-Smoking, Smoking, And Post-Smoking Stages: An Observational Laboratory Study', 'orgStudyIdInfo': {'id': '10002323'}, 'secondaryIdInfos': [{'id': '002323-MD'}]}, 'armsInterventionsModule': {'armGroups': [{'label': 'Smokers', 'description': 'Individuals aged 21 and older who smoke, have not gone beyond a high school education, and earn low incomes.'}]}, 'contactsLocationsModule': {'locations': [{'zip': '66103', 'city': 'Kansas City', 'state': 'Kansas', 'country': 'United States', 'facility': 'University of Kansas Medical Center', 'geoPoint': {'lat': 39.11417, 'lon': -94.62746}}], 'overallOfficials': [{'name': 'Sherine M El-Toukhy, Ph.D.', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'National Institute on Minority Health and Health Disparities (NIMHD)'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'National Institute on Minority Health and Health Disparities (NIMHD)', 'class': 'NIH'}, 'responsibleParty': {'type': 'SPONSOR'}}}}