Using Smartwatches to Monitor Smoking in Real-life Situations
NCT ID: NCT07067151
Last Updated: 2025-11-12
Study Results
Results pending
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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Recruitment Status
ENROLLING_BY_INVITATION
Total Enrollment
30 participants
Study Classification
OBSERVATIONAL
Study Start Date
2025-11-17
Study Completion Date
2028-03-20
Brief Summary
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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.
Objective: 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.
Eligibility: 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.
Design: 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.
Participants 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.
Participants 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.
Participation will last for 3 days of home monitoring and 2 visits to the research clinic that last about 2 hours.
Objective: 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.
Eligibility: 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.
Design: 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.
Participants 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.
Participants 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.
Participation will last for 3 days of home monitoring and 2 visits to the research clinic that last about 2 hours.
Detailed Description
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Background:
The 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.
Objectives:
* 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.
* 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.
Endpoints:
* 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.
* Secondary endpoint: Not applicable.
The 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.
Objectives:
* 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.
* 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.
Endpoints:
* 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.
* Secondary endpoint: Not applicable.
Conditions
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Smoking
Keywords
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Nicotine
Smoking
Smart watches
Pre-smoking
Cessation support
Thermal-sensor wearables
Home-based assessment
Cigarettes
Observational
Study Design
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Observational Model Type
CASE_ONLY
Study Time Perspective
PROSPECTIVE
Study Groups
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Smokers
Individuals aged 21 and older who smoke, have not gone beyond a high school education, and earn low incomes.
No interventions assigned to this group
Eligibility Criteria
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Inclusion Criteria
We 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.
To be included in the study, participants must:
* be 21 years or older in compliance with Tobacco 21 laws
* 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)
* have smoked 100 cigarettes in their lifetime and 5+ cigarettes per day in the past year to establish daily smoking status
* 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
* willing to abstain from using any nicotine products or devices for (Bullet)12 hours prior to the lab visit
* willing to abstain from alcohol use for \>=12 hours prior to the lab session verifiable by breath alcohol concentration (BrAC = 0.000)
* willing to adhere to all study procedures including agreeing to a blood draw and bringing \>=1cigarette for use during the study visit
* 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
* speak English
* and willing and able to provide informed consent.
Participants will be excluded if they:
* are not abstinent before the lab session through biochemical verification after two attempts
* 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
* 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,
* are pregnant or breastfeeding
* and are unable or unwilling to provide informed consent.
To be included in the study, participants must:
* be 21 years or older in compliance with Tobacco 21 laws
* 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)
* have smoked 100 cigarettes in their lifetime and 5+ cigarettes per day in the past year to establish daily smoking status
* 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
* willing to abstain from using any nicotine products or devices for (Bullet)12 hours prior to the lab visit
* willing to abstain from alcohol use for \>=12 hours prior to the lab session verifiable by breath alcohol concentration (BrAC = 0.000)
* willing to adhere to all study procedures including agreeing to a blood draw and bringing \>=1cigarette for use during the study visit
* 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
* speak English
* and willing and able to provide informed consent.
Participants will be excluded if they:
* are not abstinent before the lab session through biochemical verification after two attempts
* 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
* 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,
* are pregnant or breastfeeding
* and are unable or unwilling to provide informed consent.
Exclusion Criteria
Vulnerable populations will not be enrolled in the study (i.e., adults unable to consent, individuals who are not yet adults, pregnant women, prisoners).
Minimum Eligible Age
21 Years
Maximum Eligible Age
120 Years
Eligible Sex
ALL
Accepts Healthy Volunteers
Yes
Sponsors
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National Institute on Minority Health and Health Disparities (NIMHD)
NIH
Sponsor Role
lead
Responsible Party
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Responsibility Role
SPONSOR
Principal Investigators
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Sherine M El-Toukhy, Ph.D.
Role: PRINCIPAL_INVESTIGATOR
National Institute on Minority Health and Health Disparities (NIMHD)
Locations
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University of Kansas Medical Center
Kansas City, Kansas, United States
Site Status
Countries
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United States
References
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Hoeppner BB, Hoeppner SS, Schick MR, Milligan CM, Helmuth E, Bergman BG, Abroms LC, Kelly JF. Using the text-messaging program SmokefreeTXT to support smoking cessation for nondaily smokers. Subst Use Misuse. 2019;54(8):1260-1271. doi: 10.1080/10826084.2018.1552300. Epub 2019 Apr 19.
Reference Type
BACKGROUND
Ho BK, Robinson JK. Color bar tool for skin type self-identification: A cross-sectional study. J Am Acad Dermatol. 2015 Aug;73(2):312-3.e1. doi: 10.1016/j.jaad.2015.05.024. No abstract available.
Reference Type
BACKGROUND
Henrich J, Heine SJ, Norenzayan A. Most people are not WEIRD. Nature. 2010 Jul 1;466(7302):29. doi: 10.1038/466029a. No abstract available.
Reference Type
BACKGROUND
Benowitz NL, Bernert JT, Foulds J, Hecht SS, Jacob P, Jarvis MJ, Joseph A, Oncken C, Piper ME. Biochemical Verification of Tobacco Use and Abstinence: 2019 Update. Nicotine Tob Res. 2020 Jun 12;22(7):1086-1097. doi: 10.1093/ntr/ntz132.
Reference Type
BACKGROUND
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.
Reference Type
BACKGROUND
Hoeppner BB, Hoeppner SS, Seaboyer L, Schick MR, Wu GW, Bergman BG, Kelly JF. How Smart are Smartphone Apps for Smoking Cessation? A Content Analysis. Nicotine Tob Res. 2016 May;18(5):1025-31. doi: 10.1093/ntr/ntv117. Epub 2015 Jun 4.
Reference Type
BACKGROUND
Hebert ET, Stevens EM, Frank SG, Kendzor DE, Wetter DW, Zvolensky MJ, Buckner JD, Businelle MS. An ecological momentary intervention for smoking cessation: The associations of just-in-time, tailored messages with lapse risk factors. Addict Behav. 2018 Mar;78:30-35. doi: 10.1016/j.addbeh.2017.10.026. Epub 2017 Oct 28.
Reference Type
BACKGROUND
Hebert ET, Ra CK, Alexander AC, Helt A, Moisiuc R, Kendzor DE, Vidrine DJ, Funk-Lawler RK, Businelle MS. A Mobile Just-in-Time Adaptive Intervention for Smoking Cessation: Pilot Randomized Controlled Trial. J Med Internet Res. 2020 Mar 9;22(3):e16907. doi: 10.2196/16907.
Reference Type
BACKGROUND
Heatherton TF, Kozlowski LT, Frecker RC, Fagerstrom KO. The Fagerstrom Test for Nicotine Dependence: a revision of the Fagerstrom Tolerance Questionnaire. Br J Addict. 1991 Sep;86(9):1119-27. doi: 10.1111/j.1360-0443.1991.tb01879.x.
Reference Type
BACKGROUND
Hayano J, Yamada M, Sakakibara Y, Fujinami T, Yokoyama K, Watanabe Y, Takata K. Short- and long-term effects of cigarette smoking on heart rate variability. Am J Cardiol. 1990 Jan 1;65(1):84-8. doi: 10.1016/0002-9149(90)90030-5.
Reference Type
BACKGROUND
Grimes LM, Garg R, Weng O, Wolff JM, McQueen A, Carpenter KM, Kreuter MW. Appeal of Tobacco Quitline Services Among Low-Income Smokers. Prev Chronic Dis. 2023 Mar 2;20:E11. doi: 10.5888/pcd20.220214.
Reference Type
BACKGROUND
Galobardes B, Shaw M, Lawlor DA, Lynch JW, Davey Smith G. Indicators of socioeconomic position (part 1). J Epidemiol Community Health. 2006 Jan;60(1):7-12. doi: 10.1136/jech.2004.023531.
Reference Type
BACKGROUND
El-Toukhy S, Pike JR, Zuckerman G, Hegeman P. Decision Trade-Offs in Ecological Momentary Assessments and Digital Wearables Uptake: Protocol for a Discrete Choice Experiment. JMIR Res Protoc. 2023 Sep 25;12:e47567. doi: 10.2196/47567.
Reference Type
BACKGROUND
Dinas PC, Koutedakis Y, Flouris AD. Effects of active and passive tobacco cigarette smoking on heart rate variability. Int J Cardiol. 2013 Feb 20;163(2):109-15. doi: 10.1016/j.ijcard.2011.10.140. Epub 2011 Nov 17.
Reference Type
BACKGROUND
Cornelius ME, Loretan CG, Jamal A, Davis Lynn BC, Mayer M, Alcantara IC, Neff L. Tobacco Product Use Among Adults - United States, 2021. MMWR Morb Mortal Wkly Rep. 2023 May 5;72(18):475-483. doi: 10.15585/mmwr.mm7218a1.
Reference Type
BACKGROUND
Collins LM, Baker TB, Mermelstein RJ, Piper ME, Jorenby DE, Smith SS, Christiansen BA, Schlam TR, Cook JW, Fiore MC. The multiphase optimization strategy for engineering effective tobacco use interventions. Ann Behav Med. 2011 Apr;41(2):208-26. doi: 10.1007/s12160-010-9253-x.
Reference Type
BACKGROUND
Cole CA, Powers S, Tomko RL, Froeliger B, Valafar H. Quantification of Smoking Characteristics Using Smartwatch Technology: Pilot Feasibility Study of New Technology. JMIR Form Res. 2021 Feb 5;5(2):e20464. doi: 10.2196/20464.
Reference Type
BACKGROUND
Cole CA, Anshari D, Lambert V, Thrasher JF, Valafar H. Detecting Smoking Events Using Accelerometer Data Collected Via Smartwatch Technology: Validation Study. JMIR Mhealth Uhealth. 2017 Dec 13;5(12):e189. doi: 10.2196/mhealth.9035.
Reference Type
BACKGROUND
Cerrada CJ, Dzubur E, Blackman KCA, Mays V, Shoptaw S, Huh J. Development of a Just-in-Time Adaptive Intervention for Smoking Cessation Among Korean American Emerging Adults. Int J Behav Med. 2017 Oct;24(5):665-672. doi: 10.1007/s12529-016-9628-x.
Reference Type
BACKGROUND
Carter BL, Lam CY, Robinson JD, Paris MM, Waters AJ, Wetter DW, Cinciripini PM. Real-time craving and mood assessments before and after smoking. Nicotine Tob Res. 2008 Jul;10(7):1165-9. doi: 10.1080/14622200802163084.
Reference Type
BACKGROUND
Carreiro S, Fang H, Zhang J, Wittbold K, Weng S, Mullins R, Smelson D, Boyer EW. iMStrong: Deployment of a Biosensor System to Detect Cocaine Use. J Med Syst. 2015 Dec;39(12):186. doi: 10.1007/s10916-015-0337-9. Epub 2015 Oct 21.
Reference Type
BACKGROUND
Businelle MS, Perski O, Hebert ET, Kendzor DE. Mobile Health Interventions for Substance Use Disorders. Annu Rev Clin Psychol. 2024 Jul;20(1):49-76. doi: 10.1146/annurev-clinpsy-080822-042337. Epub 2024 Jul 2.
Reference Type
BACKGROUND
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.
Reference Type
BACKGROUND
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.
Reference Type
BACKGROUND
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. Health Psychol. 2010 May;29(3):262-73. doi: 10.1037/a0019285.
Reference Type
BACKGROUND
Bryant J, Bonevski B, Paul C, McElduff P, Attia J. A systematic review and meta-analysis of the effectiveness of behavioural smoking cessation interventions in selected disadvantaged groups. Addiction. 2011 Sep;106(9):1568-85. doi: 10.1111/j.1360-0443.2011.03467.x. Epub 2011 Jul 22.
Reference Type
BACKGROUND
Brandon TH, Vidrine JI, Litvin EB. Relapse and relapse prevention. Annu Rev Clin Psychol. 2007;3:257-84. doi: 10.1146/annurev.clinpsy.3.022806.091455.
Reference Type
BACKGROUND
Boland VC, Stockings EA, Mattick RP, McRobbie H, Brown J, Courtney RJ. The Methodological Quality and Effectiveness of Technology-Based Smoking Cessation Interventions for Disadvantaged Groups: A Systematic Review and Meta-analysis. Nicotine Tob Res. 2018 Feb 7;20(3):276-285. doi: 10.1093/ntr/ntw391.
Reference Type
BACKGROUND
Boland VC, Mattick RP, McRobbie H, Siahpush M, Courtney RJ. "I'm not strong enough; I'm not good enough. I can't do this, I'm failing"- A qualitative study of low-socioeconomic status smokers' experiences with accesssing cessation support and the role for alternative technology-based support. Int J Equity Health. 2017 Nov 13;16(1):196. doi: 10.1186/s12939-017-0689-5.
Reference Type
BACKGROUND
Bodin F, McIntyre KM, Schwartz JE, McKinley PS, Cardetti C, Shapiro PA, Gorenstein E, Sloan RP. The Association of Cigarette Smoking With High-Frequency Heart Rate Variability: An Ecological Momentary Assessment Study. Psychosom Med. 2017 Nov/Dec;79(9):1045-1050. doi: 10.1097/PSY.0000000000000507.
Reference Type
BACKGROUND
Bertz JW, Epstein DH, Preston KL. Combining ecological momentary assessment with objective, ambulatory measures of behavior and physiology in substance-use research. Addict Behav. 2018 Aug;83:5-17. doi: 10.1016/j.addbeh.2017.11.027. Epub 2017 Nov 16.
Reference Type
BACKGROUND
Bell BM, Alam R, Alshurafa N, Thomaz E, Mondol AS, de la Haye K, Stankovic JA, Lach J, Spruijt-Metz D. Automatic, wearable-based, in-field eating detection approaches for public health research: a scoping review. NPJ Digit Med. 2020 Mar 13;3:38. doi: 10.1038/s41746-020-0246-2. eCollection 2020.
Reference Type
BACKGROUND
Battalio SL, Conroy DE, Dempsey W, Liao P, Menictas M, Murphy S, Nahum-Shani I, Qian T, Kumar S, Spring B. Sense2Stop: A micro-randomized trial using wearable sensors to optimize a just-in-time-adaptive stress management intervention for smoking relapse prevention. Contemp Clin Trials. 2021 Oct;109:106534. doi: 10.1016/j.cct.2021.106534. Epub 2021 Aug 8.
Reference Type
BACKGROUND
Alharbi R, Shahi S, Cruz S, Li L, Sen S, Pedram M, Romano C, Hester J, Katsaggelos AK, Alshurafa N. SmokeMon: Unobtrusive Extraction of Smoking Topography Using Wearable Energy-Efficient Thermal. Proc ACM Interact Mob Wearable Ubiquitous Technol. 2022 Dec;6(4):155. doi: 10.1145/3569460. Epub 2023 Jan 11.
Reference Type
BACKGROUND
Al-Khalidi FQ, Saatchi R, Burke D, Elphick H, Tan S. Respiration rate monitoring methods: a review. Pediatr Pulmonol. 2011 Jun;46(6):523-9. doi: 10.1002/ppul.21416. Epub 2011 Jan 31.
Reference Type
BACKGROUND
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.
Reference Type
BACKGROUND
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.
Reference Type
DERIVED
Other Identifiers
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002323-MD
Identifier Type: -
Identifier Source: secondary_id
10002323
Identifier Type: -
Identifier Source: org_study_id