Investigating brain responses to e-cigarette product features

Background

Use of e-cigarettes is increasing globally. These products have been found to contain a number of toxic substances known to be harmful to humans including diethylene glycol, formaldehyde, nicotine, and toxic metals. Significant health risks associated with e-cigarette use have been observed, with a growing body of evidence linking use to various short- and long-term harms including vascular oxidative stress, endothelial dysfunction, arterial stiffness, and decreased lung function capacity. These risks are not limited to e-cigarettes that contain nicotine, with tests of e-liquids demonstrating the cytotoxicity of non-nicotine ingredients, such as additives and flavourings. Of particular concern are the rapid and substantial increases in e-cigarette use among youth. A considerable body of evidence indicates that e-cigarette use acts as a gateway to tobacco smoking, with a recent meta-analysis concluding that people who have never smoked but use e-cigarettes are approximately three times more likely than those who avoid e-cigarettes to initiate tobacco smoking. E-cigarettes have thus emerged as a potential threat to tobacco control efforts, contributing to the development of a new population of young people who smoke and are at risk of experiencing the harms associated with tobacco cigarette use. Preventing increases in e-cigarette use, especially among youth, and minimising the harms associated with vaping have become public health priorities. While the strategies used by the e-cigarette industry to advertise their products are well-documented, a particularly notable gap in the literature is the lack of research assessing the impact of product features.

Youth are targeted via the development of youth-oriented

(i) e-liquid flavours;

(ii) e-liquid and e-cigarette packaging; and

(iii) product innovations.

E-liquids are available in thousands of flavours, many of which are highly appealing to youth, such as bubblegum, popcorn, Red Bull, Skittles, and unicorn cakes. A substantial minority of e-liquid labels and product packaging feature cartoons31, a marketing strategy that increases product recognition and alters attitudes towards products. This strategy has been used by the tobacco industry to effectively increase awareness, appeal, and uptake of combustible tobacco cigarettes among children. Despite the likely impact of product features, past studies have only assessed youth exposure to product advertising. In addition, this prior work relied on self-report: respondents were asked to indicate whether they have noticed e-cigarettes being advertised, with their responses then correlated with self-reported use. Such studies are subject to social desirability bias and fail to account for the cognitions and behaviours of which youth are unaware. Cognitive neuroscience methods can provide unique insights into the impact of e-cigarette product features. This field of research has advanced considerably in recent decades. It is now possible to use physiological signals and patterns of brain activity to predict unconscious attitudes toward various products with high precision. Neural ‘decoding’ techniques, which apply classifiers from machine learning to detect regularities in complex brain activity patterns, have been used to predict a wide range of cognitive processes and behaviours.

Research Questions / Hypotheses

How do various features of e-cigarette products influence the cognitive and neurophysiological bases of attitude towards e-cigarettes and susceptibility to use e-cigarettes among young adults?

Participants

A total of 32 participants were recruited via the REP from 29th Feb to 3rd June.

Methods

A 64-channel EEG system (Biosemi Active 2 EEG system) was used to measure neural activity during simple tests. We also measured galvanic skin response, heart rate, and pupil dilation (via eye tracking). We collected responses to exposure to e-cigarette products. In each test, participants were presented with pictures displaying variants of e-cigarettes. They were then asked to rate these products on the dimensions of valence (i.e. how much the product is “liked”) and arousal (i.e. how strong is the response triggered by the product) while their brain activity and physiological signals were recorded. These tests allowed us to establish basic, emotional reactions to key product features and identify neurophysiological measures that best predict consumer attitudes. Finally, participants were administered a questionnaire that assessing vaping and smoking-related behaviours, basic demographics, attitudes towards e-cigarettes, and susceptibility to e-cigarette use (see attached).

Results

Data currently being analysed.

Implications

There is a lack of research assessing how various features of e-cigarette products influence attitudes towards the devices and susceptibility to use among youth. This makes it difficult for policymakers to make evidence-based decisions about how to effectively regulate e-cigarettes and e-liquids. With restrictions on certain product features recently announced by the Australian Government, it is critical to obtain evidence on the effectiveness of these policies. This research will provide an understanding of young people’s cognitive, neurocognitive, and physiological responses to e-cigarettes. Results will assist our partners in their efforts to improve child health and wellbeing by providing them with evidence on the impact of e-cigarettes that can be used to inform tobacco control policy via policy briefs, joint statements, and submissions to government inquiries and consultations on tobacco/e-cigarette control legislation.