Feasibility of biochemical verification in a web-based smoking cessation study

- 93/600 participants abstinent at 3-mo mailed saliva kits and 71% returned samples.
- 36.4% had cotinine levels above 15 ng/mL and had discordant results.
- Biochemical verification yielded low number of usable sample and was cost-intensive.
- Findings reiterate questionable utility of biochemical verification in this setting.

Background and aimsCogent arguments have been made against the need for biochemical verification in population-based studies with low-demand characteristics. Despite this fact, studies involving digital interventions (low-demand) are often required in peer review to report biochemically verified abstinence. To address this discrepancy, we examined the feasibility and costs of biochemical verification in a web-based study conducted with a national sample.MethodsParticipants were 600 U.S. adult current smokers who registered on a web-based smoking cessation program and completed surveys at baseline and 3 months. Saliva sampling kits were sent to participants who reported 7-day abstinence at 3 months, and analyzed for cotinine.ResultsThe response rate at 3-months was 41.2% (n = 247): 93 participants reported 7-day abstinence (38%) and were mailed a saliva kit (71% returned). The discordance rate was 36.4%. Participants with discordant responses were more likely to report 3-month use of nicotine replacement therapy or e-cigarettes than those with concordant responses (79.2% vs. 45.2%, p = 0.007). The total cost of saliva sampling was $8280 ($125/sample).ConclusionsBiochemical verification was both time- and cost-intensive, and yielded a relatively small number of samples due to low response rates and use of other nicotine products during the follow-up period. There was a high rate of discordance of self-reported abstinence and saliva testing. Costs for data collection may be prohibitive for studies with large sample sizes or limited budgets. Our findings echo previous statements that biochemical verification is not necessary in population-based studies, and add evidence specific to technology-based studies.