Self-reported smoking effects and comparative value between cigarettes and high dose e-cigarettes in nicotine-dependent cigarette smokers

McPherson, Sterling; Howell, Donelle; Lewis, Jennifer; Barbosa‐Leiker, Celestina; Metoyer, Patrick B.

doi:10.1097/fbp.0000000000000226

Cited by 10 publications

(17 citation statements)

References 35 publications

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“…The current studies replicate previous findings that e-cigarettes have lower abuse liability compared to conventional tobacco cigarettes, 8,9,21 and provide evidence that e-cigarette flavors and modified risk messages may affect behavioral economic measures of abuse liability among current cigarette smokers. In the MCP, crossover points were significantly lower for most e-cigarette conditions compared to own-brand cigarettes, regardless of flavor or message.…”

Section: Discussionsupporting

confidence: 85%

“…Two, using the MCP, found significantly higher abuse liability for cigarettes than for e-cigarettes. 8,9 Our work corroborates this, adding that the lower abuse liability of e-cigarettes may be sensitive to flavors and modified risk messages. While we have not identified any studies that directly measure e-cigarette demand elasticity using the CPT, we note that our elasticity estimates for own-brand cigarettes are similar to those found in CPT studies of cigarettes.…”

Section: Discussionsupporting

confidence: 75%

“…8 More recently, this design was partially replicated among cigarette smokers; results were consistent with participants valuing own-brand cigarettes higher than e-cigarettes. 9 In the CPT, smokers were asked how many cigarettes they would smoke at a variety of incrementally increasing prices. 5,7,10,11 The CPT produces demand elasticity and other indices measuring the relative value of the product, where higher relative value indicates greater abuse liability.…”

Section: Introductionmentioning

confidence: 99%

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Effect of Flavors and Modified Risk Messages on E-cigarette Abuse Liability

et al. 2017

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Objectives To measure e-cigarettes’ abuse liability compared to conventional tobacco cigarettes under flavor and message conditions amenable to regulation. Methods Two studies used 2×2 within-subjects designs with factors of e-cigarette flavor (Study 1: tobacco vs. menthol; Study 2: cherry vs. unflavored) and message (Study 1: reduced harm vs. no message; Study 2: reduced exposure to carcinogens vs. no message) with cigarette smokers (N(total) = 36). Linear mixed effects models assessed abuse liability for tobacco products. Outcomes included the price after which consumption is zero (the maximum amount participants would pay for a tobacco product) from the multiple choice procedure (MCP) and cigarette purchase task (CPT) and demand elasticity (price sensitivity) from the CPT. Results In the MCP, the price where consumption reached zero was significantly lower in all e-cigarette conditions except tobacco flavor (message or no message) compared to cigarettes (p < .05 each). Demand elasticity was significantly higher for menthol/no message and unflavored/reduced exposure message conditions relative to cigarettes (p < .05 each). Conclusions Flavors and modified risk messages included with e-cigarettes may affect e-cigarette abuse liability among smokers, suggesting regulatory pathways to influence demand for conventional and alternative tobacco products.

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Section: Discussionsupporting

confidence: 85%

Section: Discussionsupporting

confidence: 75%

Section: Introductionmentioning

confidence: 99%

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Effect of Flavors and Modified Risk Messages on E-cigarette Abuse Liability

et al. 2017

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“…This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. McPherson et al, 2016;Vansickel et al, 2012). Two studies suggest that other factors, such as flavor, may influence e-cig abuse liability as well (Barnes et al, 2017;Krishnan-Sarin et al, 2017).…”

mentioning

confidence: 99%

Abuse liability assessment of an electronic cigarette in combustible cigarette smokers.

Maloney¹,

Breland²,

Soule³

et al. 2019

Experimental and Clinical Psychopharmacology

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Under certain conditions, electronic cigarettes (e-cigs) can deliver nicotine to and suppress tobacco abstinence symptoms in cigarette smokers. Growing popularity of e-cigs raises abuse liability concerns. This study's purpose was to compare the abuse liability of an e-cig (1.5 Ohm, 3.3 V) filled with 36 mg/mL or 0 mg/mL nicotine to an Food and Drug Administration (FDA)-approved nicotine inhaler (IN) and participants' own brand (OB) of cigarettes. Smokers (N ϭ 24) completed four sessions in which they completed the multiple-choice procedure, and plasma nicotine concentration and subjective effects were measured. Mean (SD) multiple-choice procedure crossover point was $0.87 (1.0) for the 36-mg/mL nicotine e-cig and $0.96 (1.2) for the 0-mg/mL e-cig, significantly higher than the IN mean of $0.32 (0.6) but significantly lower than the OB cigarette mean of $1.42 (1.4). Ten puffs from an own-brand cigarette increased mean plasma nicotine concentration from 3.55 (2.8) to 13.64 (9.8) ng/mL, as compared to an increase from 3.16 (1.8) to 8.51 (5.4) ng/mL for the 36-mg/mL e-cig. The 36-mg/mL e-cig reduced nicotine abstinence symptoms more than the 0-mg/mL e-cig, and both e-cigs were rated as more reinforcing than the inhaler but less reinforcing than participants' OB cigarettes (ps Ͻ .05). Results suggest that the e-cig examined had higher abuse liability than the IN but lower than combustible cigarettes. These data and methods may be useful for policymakers by revealing how e-cig abuse liability compares to tobacco/nicotine products with abuse liability profiles that are well established.

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“…The average FTND score was 5.4 (SD = 2.4) and the mean age of smoking initiation was 15.1 years (SD = 4.4). The average FTND score translates to a population of moderately dependent smokers, not unlike averages among smoking cessation populations our team and others have reported [ [30] , [31] , [32] ]. The randomized sample did not significantly differ across group assignment on any of the baseline characteristics (all p s > 0.05).…”

Section: Resultsmentioning

confidence: 92%

Culturally-tailored text-messaging intervention for smoking cessation in rural American Indian communities: Rationale, design, and methods

Orr

Burduli

Hirchak

et al. 2019

Contemporary Clinical Trials Communications

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Background American Indian (AI) and Alaska Native (AN) communities experience disproportionately high rates of tobacco use when compared to the overall U.S. population, especially among rural populations. Methods We implemented a single-blind, randomized clinical trial of a text messaging-based smoking cessation intervention through the tobacco quitlines of five states (Alaska, Minnesota, New Mexico, Oklahoma, and Wisconsin) with high percentages of AI residents. We partnered with state quitlines and Optum, a multi-state entity that manages quitlines. Participants who called the quitlines and identified as AI/AN were given the option to enroll in this trial. Upon consent, they were randomly assigned to either the standard quitline program (control) or a program culturally tailored for AI/ANs (intervention), which used a text messaging intervention to encourage smoking cessation. We adapted the text messages based on key informant and focus group input. Baseline data was analyzed for differences across age, sex, and the Fagerström Test for Nicotine Dependence. Results We recruited n = 487 AIs into the trial. Participants had an average age of 41.9 years (SD = 11.7) and 66% were female. The average Fagerström Test for Nicotine Dependence score was 5.38 (SD = 2.37). The intervention and control arms did not significantly differ across any of the baseline characteristics. Conclusion Implementation of this trial illustrated important lessons in adapting, implementing, and evaluating trials in collaboration with AI communities and local and national organizations. This work will inform future efforts to implement culturally-tailored interventions with AI/ANs and advance our knowledge about adapting and implementing smoking cessation interventions.

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Self-reported smoking effects and comparative value between cigarettes and high dose e-cigarettes in nicotine-dependent cigarette smokers

Cited by 10 publications

References 35 publications

Effect of Flavors and Modified Risk Messages on E-cigarette Abuse Liability

Effect of Flavors and Modified Risk Messages on E-cigarette Abuse Liability

Abuse liability assessment of an electronic cigarette in combustible cigarette smokers.

Culturally-tailored text-messaging intervention for smoking cessation in rural American Indian communities: Rationale, design, and methods

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