Evaluation of the MoMba Live Long Remote Smoking Detection System During and After Pregnancy: Development and Usability Study

Stephanie Valencia, Laura Callinan, Frederick Shic, Megan Smith, Stephanie Valencia, Laura Callinan, Frederick Shic, Megan Smith

Abstract

Background: The smoking relapse rate during the first 12 months after pregnancy is around 80% in the United States. Delivering remote smoking cessation interventions to women in the postpartum period can reduce the burden associated with frequent office visits and can enable remote communication and support. Developing reliable, remote, smoking measuring instruments is a crucial step in achieving this vision.

Objective: The study presents the evaluation of the MoMba Live Long system, a smartphone-based breath carbon monoxide (CO) meter and a custom iOS smartphone app. We report on how our smoking detection system worked in a controlled office environment and in an out-of-office environment to examine its potential to deliver a remote contingency management intervention.

Methods: In-office breath tests were completed using both the MoMba Live Long system and a commercial monitor, the piCO+ Smokerlyzer. In addition, each participant provided a urine test for smoking status validation through cotinine. We used in-office test data to verify the validity of the MoMba Live Long smoking detection system. We also collected out-of-office tests to assess how the system worked remotely and enabled user verification. Pregnant adult women in their second or third trimester participated in the study for a period of 12 weeks. This study was carried out in the United States.

Results: Analyses of in-office tests included 143 breath tests contributed from 10 participants. CO readings between the MoMba Live Long system and the piCO+ were highly correlated (r=.94). In addition, the MoMba Live Long system accurately distinguished smokers from nonsmokers with a sensitivity of 0.91 and a specificity of 0.94 when the piCO+ was used as a gold standard, and a sensitivity of 0.81 and specificity of 1.0 when cotinine in urine was used to confirm smoking status. All participants indicated that the system was easy to use.

Conclusions: Relatively inexpensive portable and internet-connected CO monitors can enable remote smoking status detection in a wide variety of nonclinical settings with reliable and valid measures comparable to a commercially available CO monitor.

Trial registration: ClinicalTrials.gov NCT02237898; https://ichgcp.net/clinical-trials-registry/NCT02237898.

Keywords: breath carbon monoxide; contingency management; mobile phone; mobile-based sensor; pregnancy; smoking cessation.

Conflict of interest statement

Conflicts of Interest: None declared.

©Stephanie Valencia, Laura Callinan, Frederick Shic, Megan Smith. Originally published in JMIR mHealth and uHealth (http://mhealth.jmir.org), 24.11.2020.

Figures

Figure 1
Figure 1
The custom and portable breath carbon monoxide (CO) meter is comprised of an environmental CO gas sensor and a custom 3D-printed chassis. A smartphone was loaded with a custom app (MoMba Live Long) that enables participants to complete scheduled breath tests and collect rewards. The Sensordrone and chassis sizes are shown at scale with respect to the phone in the image.
Figure 2
Figure 2
Receiver operating characteristic curves for the MoMba Live Long system carbon monoxide (CO) measure with the piCO+ measure as gold standard.
Figure 3
Figure 3
Receiver operating characteristic curves for the MoMba Live Long system carbon monoxide (CO) and piCO+ measures with cotinine in urine as gold standard.
Figure 4
Figure 4
Breath carbon monoxide (CO) values according to time since last cigarette smoked. ppm: parts per million.
Figure 5
Figure 5
Breath carbon monoxide (CO) and cotinine in urine values according to pregnancy status (n=4). ppm: parts per million.

References

    1. Higgins ST, Chilcoat HD. Women and smoking: An interdisciplinary examination of socioeconomic influences. Drug Alcohol Depend. 2009 Oct 01;104 Suppl 1:S1–S5. doi: 10.1016/j.drugalcdep.2009.06.006.
    1. DiClemente C, Dolan-Mullen P, Windsor R. The process of pregnancy smoking cessation: Implications for interventions. Tob Control. 2000;9 Suppl 3:III16–III21. doi: 10.1136/tc.9.suppl_3.iii16.
    1. Fingerhut LA, Kleinman JC, Kendrick JS. Smoking before, during, and after pregnancy. Am J Public Health. 1990 May;80(5):541–544. doi: 10.2105/ajph.80.5.541.
    1. Clinical Practice Guideline Panel‚ Liaisons‚ and Staff . Treating Tobacco Use and Dependence: 2008 Update. Clinical Practice Guideline. Rockville, MD: US Department of Health and Human Services. Public Health Service; 2008. May, [2020-10-24]. .
    1. Lumley J, Chamberlain C, Dowswell T, Oliver S, Oakley L, Watson L. Interventions for promoting smoking cessation during pregnancy. Cochrane Database Syst Rev. 2009 Jul 08;(3):CD001055. doi: 10.1002/14651858.CD001055.pub3.
    1. Pew Research Center. Washington, DC: Pew Research Center; 2019. Jun 12, [2020-10-20]. Mobile fact sheet.
    1. Chen Y, Madan J, Welton N, Yahaya I, Aveyard P, Bauld L, Wang D, Fry-Smith A, Munafò MR. Effectiveness and cost-effectiveness of computer and other electronic aids for smoking cessation: A systematic review and network meta-analysis. Health Technol Assess. 2012;16(38):1–205, iii. doi: 10.3310/hta16380. doi: 10.3310/hta16380.
    1. Carrasco-Hernandez L, Jódar-Sánchez F, Núñez-Benjumea F, Moreno Conde J, Mesa González M, Civit-Balcells A, Hors-Fraile S, Parra-Calderón CL, Bamidis PD, Ortega-Ruiz F. A mobile health solution complementing psychopharmacology-supported smoking cessation: Randomized controlled trial. JMIR Mhealth Uhealth. 2020 Apr 27;8(4):e17530. doi: 10.2196/17530.
    1. Baskerville N, Struik L, Hammond D, Guindon G, Norman C, Whittaker R, Burns CM, Grindrod KA, Brown KS. Effect of a mobile phone intervention on quitting smoking in a young adult population of smokers: Randomized controlled trial study protocol. JMIR Res Protoc. 2015 Jan 19;4(1):e10. doi: 10.2196/resprot.3823.
    1. Meredith SE, Robinson A, Erb P, Spieler CA, Klugman N, Dutta P, Dallery J. A mobile-phone-based breath carbon monoxide meter to detect cigarette smoking. Nicotine Tob Res. 2014 Jun;16(6):766–773. doi: 10.1093/ntr/ntt275.
    1. Moscato U, Poscia A, Gargaruti R, Capelli G, Cavaliere F. Normal values of exhaled carbon monoxide in healthy subjects: Comparison between two methods of assessment. BMC Pulm Med. 2014 Dec 16;14:204. doi: 10.1186/1471-2466-14-204.
    1. Javors MA, Hatch JP, Lamb RJ. Cut-off levels for breath carbon monoxide as a marker for cigarette smoking. Addiction. 2005 Feb;100(2):159–167. doi: 10.1111/j.1360-0443.2004.00957.x.
    1. Stoops WW, Dallery J, Fields NM, Nuzzo PA, Schoenberg NE, Martin CA, Casey B, Wong CJ. An internet-based abstinence reinforcement smoking cessation intervention in rural smokers. Drug Alcohol Depend. 2009 Nov 01;105(1-2):56–62. doi: 10.1016/j.drugalcdep.2009.06.010.
    1. Adkins J, Dutta P. Monoxalyze: Verifying smoking cessation with a keychain-sized carbon monoxide breathalyzer. Proceedings of the 14th ACM Conference on Embedded Network Sensor Systems (SenSys '16); 14th ACM Conference on Embedded Network Sensor Systems (SenSys '16); November 14-16, 2016; Stanford, CA. 2016. pp. 190–201.
    1. You C, Lin Y, Chuang Y, Lee Y, Hsu P, Lin S, Chang C, Chung Y, Chen Y, Huang M, Shen P, Tseng H, Wang H. SoberMotion: Leveraging the force of probation officers to reduce the risk of DUI recidivism. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (to be presented at UbiComp 2018); ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (to be presented at UbiComp 2018); October 8-12, 2018; Singapore. 2018. Sep, pp. 1–34.
    1. Hsu P, Lin Y, Huang J, Chang C, Lin S, Lee Y, You C, Chuang Y, Huang M, Tseng H, Wang H. A mobile support system to assist DUI offenders on probation in reducing DUI relapse. Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and the 2017 ACM International Symposium on Wearable Computers (UbiComp '17); 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and the 2017 ACM International Symposium on Wearable Computers (UbiComp '17); September 11-15, 2017; Maui, HI. 2017. Sep, pp. 77–80.
    1. Dáu ALBT, Callinan LS, Mayes LC, Smith MV. Postpartum depressive symptoms and maternal sensitivity: An exploration of possible social media-based measures. Arch Womens Ment Health. 2017 Feb;20(1):221–224. doi: 10.1007/s00737-016-0650-4.
    1. Wagner M. Sensordrone: A practical, tricorder like platform for consumers and mobile device developers. Tech Briefs. 2012. Jun 25, [2020-10-25]. .
    1. Valencia S, Smith MV, Atyabi A, Shic F. Mobile ascertainment of smoking status through breath: A machine learning approach. 7th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON); October 20-22, 2016; New York, NY. 2016. pp. 1–7.
    1. Higgins ST, Washio Y, Heil SH, Solomon LJ, Gaalema DE, Higgins TM, Bernstein IM. Financial incentives for smoking cessation among pregnant and newly postpartum women. Prev Med. 2012 Nov;55 Suppl:S33–S40. doi: 10.1016/j.ypmed.2011.12.016.
    1. Low ECT, Ong MCC, Tan M. Breath carbon monoxide as an indication of smoking habit in the military setting. Singapore Med J. 2004 Dec;45(12):578–582.
    1. Fagerström K. Determinants of tobacco use and renaming the FTND to the Fagerstrom Test for Cigarette Dependence. Nicotine Tob Res. 2012 Jan;14(1):75–78. doi: 10.1093/ntr/ntr137.
    1. Middleton ET, Morice AH. Breath carbon monoxide as an indication of smoking habit. Chest. 2000 Mar;117(3):758–763. doi: 10.1378/chest.117.3.758.
    1. Bailey BA. Using expired air carbon monoxide to determine smoking status during pregnancy: Preliminary identification of an appropriately sensitive and specific cut-point. Addict Behav. 2013 Oct;38(10):2547–2550. doi: 10.1016/j.addbeh.2013.05.011.
    1. Robin X, Turck N, Hainard A, Tiberti N, Lisacek F, Sanchez J, Müller M. pROC: An open-source package for R and S+ to analyze and compare ROC curves. BMC Bioinformatics. 2011 Mar 17;12:77. doi: 10.1186/1471-2105-12-77.
    1. McCarthy WF, Guo N. The estimation of sensitivity and specificity of clustered binary data. Proceedings of SAS Users Group International 31 (SUGI 31); SAS Users Group International 31 (SUGI 31); March 26-29, 2006; San Francisco, CA. 2006. pp. 1–10.
    1. Irimata K, Wakim P, Li X. Estimation of correlation coefficient in data with repeated measures. Proceedings of the SAS Global Forum 2018; SAS Global Forum 2018; April 8-11, 2018; Denver, CO. 2018.
    1. Dempsey D, Jacob P, Benowitz NL. Accelerated metabolism of nicotine and cotinine in pregnant smokers. J Pharmacol Exp Ther. 2002 May;301(2):594–598. doi: 10.1124/jpet.301.2.594.
    1. Secker-Walker RH, Vacek PM, Flynn BS, Mead PB. Exhaled carbon monoxide and urinary cotinine as measures of smoking in pregnancy. Addict Behav. 1997;22(5):671–684. doi: 10.1016/s0306-4603(97)00013-0.
    1. Usmani ZC, Craig P, Shipton D, Tappin D. Comparison of CO breath testing and women's self-reporting of smoking behaviour for identifying smoking during pregnancy. Subst Abuse Treat Prev Policy. 2008 Feb 17;3(1):4. doi: 10.1186/1747-597X-3-4.
    1. Hertzberg JS, Carpenter VL, Kirby AC, Calhoun PS, Moore SD, Dennis MF, Dennis PA, Dedert EA, Beckham JC. Mobile contingency management as an adjunctive smoking cessation treatment for smokers with posttraumatic stress disorder. Nicotine Tob Res. 2013 Nov;15(11):1934–1938. doi: 10.1093/ntr/ntt060.
    1. 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.
    1. Shipton D, Tappin DM, Vadiveloo T, Crossley JA, Aitken DA, Chalmers J. Reliability of self reported smoking status by pregnant women for estimating smoking prevalence: A retrospective, cross sectional study. BMJ. 2009 Oct 29;339:b4347. doi: 10.1136/bmj.b4347.
    1. Ford RP, Tappin DM, Schluter PJ, Wild CJ. Smoking during pregnancy: How reliable are maternal self reports in New Zealand? J Epidemiol Community Health. 1997 Jun;51(3):246–251. doi: 10.1136/jech.51.3.246.
    1. Campbell E, Sanson-Fisher R, Walsh R. Smoking status in pregnant women assessment of self-report against carbon monoxide (CO) Addict Behav. 2001;26(1):1–9. doi: 10.1016/s0306-4603(00)00070-8.
    1. Crowley TJ, Andrews A, Cheney J, Zerbe G, Petty TL. Carbon monoxide assessment of smoking in chronic obstructive pulmonary disease. Addict Behav. 1989 Jan;14(5):493–502. doi: 10.1016/0306-4603(89)90069-5.
    1. Raiff BR, Faix C, Turturici M, Dallery J. Breath carbon monoxide output is affected by speed of emptying the lungs: Implications for laboratory and smoking cessation research. Nicotine Tob Res. 2010 Aug;12(8):834–838. doi: 10.1093/ntr/ntq090.
    1. Robinson E, Higgs S, Daley AJ, Jolly K, Lycett D, Lewis A, Aveyard P. Development and feasibility testing of a smart phone based attentive eating intervention. BMC Public Health. 2013 Jul 09;13:639. doi: 10.1186/1471-2458-13-639.
    1. Hecht E, Vogt TM. Marijuana smoking: Effect on expired air carbon monoxide levels. Int J Addict. 1985 Feb;20(2):353–361. doi: 10.3109/10826088509044917.

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