Smoking is one of the leading causes of preventable diseases and death in the United States, accounting for over 480,000 deaths annually between 2005 and 2009 [1]. In 2019, there were 1.14 billion smokers worldwide [2], and tobacco-related deaths exceeded 8 million globally [3]. Efforts to reduce tobacco use have been successful on a global scale; the prevalence of current tobacco use dropped from 32.7% in 2000 to 22.3% in 2020 [4]. In the United States, 68% of smokers have expressed a desire to quit completely, and 55.1% of adult smokers reported attempting to quit in the previous year [5]. However, nicotine, a component of tobacco, has addictive properties that are a major reason for the failure of smoking cessation efforts [6].

Nicotine acts on nicotinic cholinergic receptors in the brain, releasing neurotransmitters that play a crucial role in nicotine dependence and withdrawal symptoms. Addiction to nicotine develops when smokers depend on smoking to regulate their mood or alleviate withdrawal symptoms [7]. Varenicline, a partial agonist of the nicotine cholinergic receptor, prevents full receptor activation and has proven effective in aiding smoking cessation [8]. However, approximately 25% of patients attempting to quit smoking do not adhere to their medication regimen as prescribed [9,10]. Yu et al. [11] suggested that higher medication compliance was linked to a lower risk of failing to quit smoking, yet more than half of all individuals registered at smoking cessation clinics drop out after one or two visits [12]. Digital health solutions, including smartphone applications, have been proposed to address these adherence issues [10,13]. In the United States, 75.9% of smokers own smartphones, and those motivated to quit are more likely to download such applications [14]. Individual, group, and telephone counseling have been effective, and their effectiveness increases with the intensity of the treatments [15]. If smokers were to use smoking cessation applications in conjunction with these counseling programs, the treatment outcomes could be significantly enhanced.

Smokers who fully adhered to using a smartphone application were four times more likely to quit smoking, although only 24% of users achieved full adherence [16]. Among users of a smartphone application designed to support drug adherence, 29% used the application at least once a week for a minimum of 4 weeks [17]. To address these high attrition rates, a new smartphone application for smoking cessation was developed, adhering strictly to the US Clinical Practice Guideline (USCPG). On average, participants engaged with the application 100.6 times over the 8-week study, and 26.2% reported 30 days of smoking cessation after 8 weeks [10]. Therefore, exploring methods to increase compliance with smoking cessation applications is crucial. The Fagerstrom Test for Nicotine Dependence (FTND) is widely used to assess the intensity of a smoker’s nicotine dependence [18]. The success of a smoker’s cessation efforts has been linked to the severity of their nicotine dependence [19]. Thus, it is essential to consider the severity of nicotine dependence when counseling smokers. Before developing a smartphone application for smoking cessation, we conducted a survey to gather data on smokers’ mobile usage patterns, smoking habits, and nicotine dependence.

Thus, this study aimed to investigate the association between smartphone application usage patterns, smoking habits, nicotine dependence, and expected compliance with a smoking cessation application among smokers. The goal is to inform the development of a future smartphone application for smoking cessation.

Among the 53 participants with nicotine use disorder who visited Kangwon National University Hospital’s pulmonology outpatient department, the average FTND score was 3.79 ± 2.51 points, with 24 smokers (45.28%) exhibiting medium or high nicotine dependence. Given that smokers with high nicotine dependence are less likely to attempt quitting [25], it is essential to assess their level of dependence and provide appropriate treatment. In our study, the majority (90.57%) of participants were aware of the harmful effects of tobacco, and 43 participants (81.13%) had previously attempted to quit smoking. Kim et al. [26] have demonstrated that smokers who failed to quit had higher stress levels. Since 18 participants (33.96%) reported that mental stress had caused their previous cessation attempts to fail, clinicians at the smoking cessation clinic should assess the smoker’s stress level and determine if there are any underlying mental health issues.

Withdrawal symptoms, cravings, and exposure to smoking triggers such as alcohol consumption and peer pressure were the primary reasons for relapse [24]. In our study, the triggers identified for smoking included meals, waking up, drinking alcohol, and peer pressure, aligning with findings from previous research. When these situations occur repeatedly, they become cues that trigger the urge to smoke. The pleasurable effects of smoking or the unpleasant moods associated with not smoking serve as further incentives to smoke [7]. However, as indicated in Table 3, 36 participants (67.92%) lacked a structured approach to manage these cravings. Twenty participants (37.74%) reported using self-suggestion as a strategy to cope with tobacco cravings. Therefore, it is essential to establish effective methods for managing cravings and withdrawal symptoms to prevent relapse.

Shankar et al. [23] demonstrated that a text message program was effective in motivating smokers with opioid use disorder to quit smoking. Participants reported that text messages highlighting the health benefits of quitting and providing positive encouragement were helpful. The preferences for text content among participants were similar to those in our study. Specifically, 20 participants (37.74%) indicated that messages emphasizing the harmful effects of smoking were useful, while 12 participants (22.64%) found texts promoting a positive mindset helpful. However, participants also noted that receiving too many texts could be annoying [27]. In our study, 22 participants (41.51%) preferred to receive one text message per day, and 16 participants (30.19%) wanted to receive between two to five messages daily. Although text messages can be effective, it is important to limit their number to avoid causing annoyance. Regarding smartphone applications, 25 participants (47.17%) reported that they would use an app for less than 1 week. To address this low engagement, a previous study suggested incorporating game elements [13]. When developing digital health solutions, it is crucial to consider methods that enhance compliance with the applications. Social connections can have powerful influences on health behavior [28] and social support. As shown in Table 4, 35 participants (66.04%) preferred not to inform their families and friends about their plans to quit smoking, and 28 participants (52.83%) believed that sharing their intentions would not enhance their chances of quitting. Additionally, 31 participants (58.49%) indicated they would not seek help from others when facing difficulties in quitting smoking. These attitudes may be influenced by cultural factors. Previous research has suggested that South Koreans often prioritize maintaining face and are highly sensitive to others’ evaluations [29]. This cultural context can make it challenging for smokers to seek support, as they may fear negative judgments. Therefore, when considering social connections, including SNS, as a potential aid for smoking cessation, it is important to take cultural considerations into account.

The partial correlation matrix between FTND and the main variables, adjusted for age, is presented in Table 6. P_ freq and M_text were negatively correlated, indicating that the more time smokers spent on their mobile devices, the fewer text messages they preferred to receive. Similarly, P_ freq and A_comp showed a negative correlation, suggesting that the more time smokers spent on their mobile devices, the shorter the duration they desired to use smartphone applications for smoking cessation. This suggests that heavy smartphone users may have lower compliance with smoking cessation apps. Excessive use of mobile phones can lead to smartphone addiction [30]. Individuals addicted to mobile phones are likely to spend more time on the applications they use. Therefore, it is important to inquire about the amount of time smokers spend on their smartphones and develop strategies to encourage the use of smoking cessation applications. Previous studies have demonstrated that a combination of methods, including personalized messaging, social engagement, and completing missions, can enhance compliance with applications [10]. Behavioral counseling or cognitive behavioral therapy (CBT) can be employed to address tobacco cravings and manage situations that trigger smoking. M_text and A_comp were positively correlated, indicating that the fewer text messages smokers wished to receive, the shorter the duration they wanted to use the smartphone application. This suggests that smokers who are disinterested in using smartphone applications as a quitting tool will likely exhibit poor compliance. It is crucial to carefully select smokers who could benefit from using smartphone applications. The correlations between FTND and other main variables were not statistically significant.

Our study has identified a relationship between smartphone usage patterns and anticipated compliance with a smoking cessation application. The findings can inform the design of the application to improve user compliance based on these patterns. However, this study has several limitations. First, it depended on patients’ responses to questionnaires, which necessitates caution. Second, it utilized cross-sectional data, precluding any determination of causality. Third, the number of patients enrolled in this study was relatively small. Future longitudinal studies with larger sample sizes are needed.

In conclusion, smokers who spent more time on their mobile devices expressed a preference for receiving fewer text messages about smoking cessation, and they anticipated lower compliance with the smoking cessation application. Conversely, smokers who were open to receiving more text messages about smoking cessation were also inclined to use the smoking cessation application for a longer period. When developing smoking cessation applications, it may be beneficial to inquire about the user’s preferred frequency of text messages and their smartphone usage patterns to increase compliance with the application. Further research is needed to confirm this relationship in practical settings.