Introduction Use of flavoured pod-mod-like disposable electronic cigarettes (e-cigarettes) has grown rapidly, particularly among cost-sensitive youth and young adults. To date, little is known about their design characteristics and toxicant emissions. In this study, we analysed the electrical and chemical characteristics and nicotine and pulmonary toxicant emission profiles of five commonly available flavoured disposable e-cigarettes and compared these data with those of a JUUL, a cartridge-based e-cigarette device that pod-mod-like disposables emulate in size and shape. Methods Device construction, electrical power and liquid composition were determined. Machine-generated aerosol emissions including particulate matter, nicotine, carbonyl compounds and heavy metals were also measured. Liquid and aerosol composition were measured by high-performance liquid chromatography, gas chromatography-mass spectrometry/flame ionisation detection, and inductively coupled plasma mass spectrometry. Results We found that unlike JUUL, disposable devices did not incorporate a microcontroller to regulate electrical power to the heating coil. Quality of construction varied widely. Disposable e-cigarette power ranged between 5 and 9 W and liquid nicotine concentration ranged between 53 and 85 mg/mL (~95% in the protonated form). In 15 puffs, total nicotine yield for the disposables ranged between 1.6 and 6.7 mg, total carbonyls ranged between 28 and 138 µg, and total metals ranged between 1084 and 5804 ng. JUUL emissions were near the floors of all of these ranges. Conclusions Disposable e-cigarettes are designed with high nicotine concentration liquids and are capable of emitting much higher nicotine and carbonyl species relative to rechargeable look-alike e-cigarettes. These differences are likely due to the lower quality in construction, unreliable labelling and lack of temperature control regulation that limits the power during operation. From a public health perspective, regulating these devices is important to limit user exposure to carbonyls and nicotine, particularly because these devices are popular with youth and young adults.

Assessing tobacco use intensity allows researchers to examine tobacco use in greater detail than assessing ever or current use only. Tobacco use intensity measures have been developed that are specific to tobacco products, such as asking smokers to report number of cigarettes smoked per day. However, consensus on electronic cigarette use intensity measures that can be used for survey research has yet to be established due to electronic cigarette product and user behavior heterogeneity. While some survey measures that attempt to assess electronic cigarette use intensity exist, such as examining number of ‘times’ using an electronic cigarette per day, number of puffs taken from an electronic cigarette per day, volume of electronic cigarette liquid consumed per day, or nicotine concentration of electronic cigarette liquid, most measures have limitations. Challenges in electronic cigarette measurement often stem from variations across electronic cigarette device and liquid characteristics as well as the difficulty that many electronic cigarette users have regarding answering questions about their electronic cigarette device, liquid, or behavior. The inability for researchers to measure electronic cigarette use intensity accurately has important implications such as failing to detect unintended consequences of regulatory policies. Development of electronic cigarette use intensity measures, though not without its challenges, can improve understanding of electronic cigarette use behaviors and associated health outcomes and inform development of regulatory policies.

Background JUUL is an electronic cigarette that aerosolises a nicotine-containing liquid, while IQOS heats tobacco to produce an aerosol. Both are marketed to smokers, but their effects have seldom been examined in this population. Methods Eighteen cigarette smokers (13 men) with no JUUL or IQOS experience completed a within-subject, laboratory study assessing nicotine delivery and subjective effects after controlled (10 puffs, ~30 s interpuff interval) and ad libitum (90 min) use of JUUL, IQOS or own-brand (OB) cigarettes. Results JUUL increased mean plasma nicotine concentration significantly from 2.2 (SD=0.7) ng/mL to 9.8 (4.9) ng/mL after 10 puffs and to 11.5 (9.3) ng/mL after ad libitum use. IQOS increased mean plasma nicotine significantly from 2.1 (0.2) ng/mL to 12.7 (6.2) ng/mL after 10 puffs and to 11.3 (8.0) ng/mL after ad libitum use. OB increased mean plasma nicotine significantly from 2.1 (0.2) ng/mL to 20.4 (11.4) ng/mL after 10 puffs and to 21.0 (10.2) ng/mL after ad libitum use. Mean OB plasma nicotine concentration was significantly higher than JUUL and IQOS. OB increased expired carbon monoxide concentration, but IQOS and JUUL did not. ‘Craving a cigarette/nicotine’ and ‘Urges to smoke’ were reduced significantly for all products following the directed bout. Conclusions Among smokers, JUUL and IQOS delivered less nicotine than cigarettes. Also, in this sample, IQOS and OB reduced abstinence symptoms more effectively than JUUL. Additional work with experienced JUUL and IQOS users is needed, as their nicotine delivery profiles and subjective experiences may differ.

Background: COVID-19 has caused health impacts and disruptions globally. Electronic cigarette (ECIG) users may face additional impacts. This study examined impacts of COVID-19 on ECIG users. Methods: Concept mapping, a mixed-methods approach, was used to identify COVID-19 impacts on adult ECIG users. ECIG users (n = 93) provided statements completing a prompt: “A specific way Coronavirus/COVID-19 has affected my vaping/e-cigarette use, my vaping/e-cigarette related purchasing, or other vaping/e-cigarette related behaviors or issues is…”. Participants generated 85 unique statements, sorted statements into groups of similar content and rated each statement on how true they were. Multidimensional scaling and hierarchical cluster analysis identified thematic clusters. Mean cluster ratings were compared between sample subgroups. Results: Ten clusters were identified: Stocking up and Bulk Purchasing, Challenges in Obtaining ECIG Supplies, Alternative Purchasing Procedures, Increased ECIG use, Disruption of Routine and ECIG Use, Efforts to Decrease ECIG Use, Improving ECIG Skills, COVID-19 Health Concerns, Perceptions of ECIG Use and COVID-19, and COVID-19 Protection. More dependent ECIG users and dual users of ECIGs and cigarettes rated clusters higher than less dependent ECIG users and non-dual users. Conclusions: ECIG users may experience or perceive they face additional COVID-19 impacts, such as increased exposure, financial burdens, stress, and health risks.