Mobile apps and artificial intelligence (AI) based tools for analysis, prediction and prevention of tobacco and alcohol relapse: A review of past and current market
 
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1
Maria Skłodowska-Curie National Research Institute of Oncology, Warsaw, Poland
 
2
Collegium Civitas, Warsaw, Poland
 
3
Foundation "Smart Health - Health in 3D" (SHF), Warsaw, Poland
 
4
Affinity Research, Gdańsk, Poland
 
5
University of Łódź, Łódź, Poland
 
 
Publication date: 2021-12-10
 
 
Tob. Prev. Cessation 2021;7(Supplement):57
 
ABSTRACT
Background:
Substance addictions, for example from tobacco and alcohol, are very common at population level, generate the risk of massive mental and somatic problems and are difficult to be effectively treated. Addicts are not commonly and often asked, assessed, advised, assisted and followed up in addiction's diagnostics and treatment. A big problem in effective prevention and treatment of tobacco and alcohol addictions is very high risk of relapse and lack of effective tools that can continuously and objectively analyze, predict and prevent it. The progress of new technologies, including mobile apps and AI-based tools seem to close this gap on therapeutic tools market and may help therapists and patients in effective struggle with addiction relapse.

Objective:
To review the most common and comprehensive mobile applications, including tools based on AI algorithms, aimed to strengthen treatment of tobacco and alcohol dependence through analyzing, predicting and preventing addiction relapse.

Material and Methods:
Brief narrative review of scientific papers and research, development and commercial reports on the role of mobile applications in treatment of tobacco and alcohol dependence that have been published since 2000, with special focus on those using AI-algorithms for predicting addiction relapse. The search was made on Google Scholar, WorldWideScience, Medline, PubMed and on the Directory of the Open Access Journals as well as on websites of major international health organizations, mobile apps producers and pro-health start-ups.

Results:
New technologies meet and create new market, social, mental and health needs. Tobacco and alcohol industry accommodates its marketing strategy to new challenges. Past, current and potential tobacco and alcohol consumers are massively exposed to Internet and social media marketing and to the offer of alternative products (for example, vaping tobacco or alcohol), and new generations do not know how to effectively function without smartphone or access to social media. On the other side, mobile applications give a response to these needs and create an opportunity to combine all anti-tobacco or anti-alcohol interventions in one tool: 1/ permanently collect, store and analyze broad spectrum of various data on tobacco and alcohol use and cessation habits, 2/ screen tobacco and alcohol users due to the strength of addiction, cessation's intention and stage, the potential risk of tobacco or alcohol related disease, characteristics and progress in addiction treatment, etc., 3/ prevent tobacco and alcohol use, dependence and relapse through rising awareness on their harm, cost and access to educational and treatment tools and services as well as through short and long-time prediction of addiction relapse, 4/ make tobacco and alcohol treatment faster, more comprehensive, ergonomic and effective. Unfortunately, there is not still too many mobile apps that are dedicated for tobacco or alcohol consumers and only very few that use AI-algorithms for analysis, prediction and prevention of addiction relapse. Nevertheless, those based on digital therapeutic system equipped with machine learning or automated natural dialogue language seem to offer very high (over 70-80%) efficacy of relapse prediction and be characterized by high values in sensitivity and specificity tests.

Conclusions:
1/ Mobile applications seem to be promising tools for strengthening prevention and treatment of tobacco and alcohol dependence; 2/ They offer various functions that may substantially improve traditional treatment and make it much more effective and ergonomic; 3/ Mobile apps may increase a proportion of tobacco and alcohol dependent patients who decide to be treated from substance abuse in cessation clinics; 4/ With these tools, we may have a permanent access to bigger number of patients and broader spectrum of predictors what may have an impact on progress in research on prevention and treatment of tobacco and alcohol dependence; 5/ AI-algorithms and new analytical methods may help in sufficient prediction of tobacco and alcohol relapse and creation of chatbots (as virtual assistants) that could support therapists in their diagnostic and treatment activities; 6/ There is a urgent need for conducting further research and development projects and clinical trials that precisely report on safety and effectiveness of mobile apps based on AI-algorithms and chatbots in tobacco and alcohol treatment.

CONFLICTS OF INTEREST
No Conflicts of Interest were reported.
eISSN:2459-3087