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Dr Olga Perski

Dr Olga Perski is a Research Associate in UCL’s Tobacco and Alcohol Research Group. She completed her PhD at UCL in 2018 under the supervision of Prof. Susan Michie, Prof. Ann Blandford and Prof. Robert West. Her doctoral research focused on the definition, measurement and promotion of engagement with digital interventions. Her current research is interdisciplinary in scope, drawing on theories and methods from behavioural science, computer science and human-computer interaction to develop, evaluate and implement digital interventions for smoking cessation and alcohol reduction. Her work is also focused on the understanding of population-wide influences on smoking, smoking cessation, alcohol consumption and alcohol reduction, using data from household surveys such as the Smoking and Alcohol Toolkit Studies.


Does the addition of a supportive chatbot promote user engagement with a smoking cessation app? An experimental study


Presentation link: Does the addition of a supportive chatbot promote user engagement with a smoking cessation app? An experimental study

Presentation audio: Does the addition of a supportive chatbot promote user engagement with a smoking cessation app?

Aims: To assess whether a version of the Smoke Free app with a supportive chatbot powered by artificial intelligence (vs. a version without the chatbot) led to increased engagement and short-term quit success.

Methods: Daily or non-daily smokers aged >18 years who purchased the ‘pro’ version of the app and set a quit date were randomly assigned (unequal allocation) to receive the app with or without the chatbot. The outcomes were engagement (i.e. total number of logins over the study period) and self-reported abstinence at a 1-month follow-up. Unadjusted and adjusted negative binomial and logistic regression models were fitted to estimate incidence rate ratios (IRRs) and odds ratios (ORs) for the associations of interest.

Results: 57,214 smokers were included (intervention: 9.3% (5,339); control: 90.7% (51,875). The app with the chatbot compared with the standard version led to a 101% increase in engagement (IRR adj = 2.01, 95% CI = 1.92-2.11, ‘p’ < .001). The 1-month follow-up rate was 10.6% (intervention: 19.9% (1,061/5,339); control: 9.7% (5,050/51,875). Smokers allocated to the intervention had greater odds of quit success (missing equals smoking: 844/5,339 vs. 3,704/51,875, OR adj = 2.38, 95% CI = 2.19-2.58, ‘p’ < .001; follow-up only: 844/1,061 vs. 3,704/5,050, OR adj = 1.36, 95% CI = 1.16-1.61, ‘p ‘< .001).

Conclusion: The addition of a supportive chatbot to a popular smoking cessation app more than doubled user engagement. In view of very low follow-up rates, there is low quality evidence that the addition also increased self-reported smoking cessation.