A novel and remote biochemical verification method of smoking abstinence: Predictors of participant compliance
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Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, USA
Department of Psychiatry and Weill Institute for Neurosciences, University of California San Francisco, San Francisco, USA
Johannes Thrul   

Johns Hopkins Bloomberg School of Public Health, 624 N Broadway, 21205 Baltimore, United States.
Publication date: 2018-05-15
Submission date: 2018-02-12
Final revision date: 2018-04-06
Acceptance date: 2018-04-30
Tob. Prev. Cessation 2018;4(May):20
Biochemical verification of smoking abstinence remains an important validity check of cessation trial outcomes. Digital health trials rarely establish inperson contacts between participants and intervention providers, requiring novel strategies to biochemically verify outcomes. We describe remote verification of smoking abstinence via saliva cotinine and individual predictors of compliance in a digital intervention.

Material and Methods:
Data came from a feasibility trial and randomized controlled trial of a Facebook smoking cessation intervention for young adults. In both trials, participants completed baseline and follow-up surveys at 3, 6 and 12 months. Participants indicating past 7-day point prevalence smoking abstinence were mailed a saliva cotinine kit. Participants were instructed to electronically send two photos — one of them giving a saliva sample and the other with the test results. We investigated predictors of compliance with these procedures, independent of verification results, among participants that were mailed a kit at any follow-up point (N=130; mean age = 21.3; 59.2% female) using logistic and multinomial regression.

A total of 189 kits were sent out, of which 97 were completed (51.3% compliance). We did not identify significant predictors of completing any vs no kits using logistic regression. We also found no significant predictors of extent of kit completion (none vs some; none vs all) using multinomial regression and controlling for number of kits sent.

Findings demonstrate the feasibility of this biochemical verification method and suggest low risk for bias of results. Future studies should replicate findings in larger samples and improve compliance with verification procedures.

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