Markov model- Quantifying outlook towards success of tobacco cessation counseling

Abstract

Smoking is still a major public health issue that causes morbidity and mortality all over the world. The percentage of deaths caused by tobacco smoking has escalated from 1.4% in 1990 to 13.3% by 2020. There are numerous evidence-based tobacco control strategies available, and newer ones are always being developed. However, on ceasing the habit, cigarettes users go through a period of withdrawal with an increased percentage of relapse before entering to a more stable condition of sobriety in the long run. In this review, Endnote software was used as resource material to collect literature, which was then carefully arranged in a synchronised way. The Markov model captures the dynamic character of the quitting/relapse process, allowing for more accurate figures of abstinence rate, treatment outcomes and evaluating the performance of newer cessation initiatives during tobacco cessation counselling, as well as suggesting pathways for survivability.

Keywords: Addiction; Markov model; cessation; cigarette; smoking; tobacco.

Figure 1

A schematic illustrating the smoking cessation steps and simplifying a complex and idiosyncratic process with the stages of habitual usage (U), active struggle during withdrawal symptoms (W) and prolonged abstinence (A). The chance of transformation on any particular day is represented by Greek symbols. Cessation moves the person from left to right, with slips from A, which happen with a high probability λ, returning the person to W, which has a higher probability r of relapse to habitual usage