The Effect of an Anti-Smoking Mobile Application on Self-Efficacy, Decision Making and Breath Carbon Monoxide Levels

Purpose:This research aims to examine the effect of a mobile application developed against smoking behavior on teachers' self-efficacy, decision-making and carbon monoxide levels in breath.The research was planned as a randomized controlled experimental type.Working in public schools in Izmir/Narlıdere District teachers constitute the universe of the research. According to the calculations made, it was decided to include 35 people in the experimental group and 35 people in the control group. After obtaining institutional permissions, teachers who meet the inclusion criteria will be determined.To ensure homogeneity, control and intervention groups will be stratified according to age, gender, and addiction levels.Assignment to intervention and control groups will be made by simple randomization method.The average scores of teachers' self-efficacy, breath carbon monoxide and decision-making levels are the dependent variables of the study.The status of using the mobile application is the independent variable. "Personal Information Form", "Fagerstrom Nicotine Dependency Test (FNBT)", "Self-Efficacy Scale", "Classification of Stages of Change Scale", "Decision Making Scale" and "Carbon Monoxide Measurement Values Tracking Form" will be used in this research. SPSS 26.0 Package program will be used to analyze the data in the study. It will be evaluated statistically at a 95% confidence interval and a significance level of p\<0.05. Number and percentage distributions for sociodemographic characteristics will be used in the analysis of the data.In comparisons between groups, parametric or nonparametric tests will be used after evaluating the normal distribution feature of the scale scores.

Hypotheses 1 H1:There is a difference between the breath CO level scores of intervention and control group teachers according to time (pre-test - 1st month, 3rd month and 6th month).

Hypotheses 2 H1:There is a difference between the self-efficacy scale scores of intervention and control group teachers according to time (pre-test, 1st month, 3rd month, 6th month).

Hypotheses 3 H1: There is a difference between the decision-making level scores of teachers in the intervention and control groups according to time (pretest-1st month, 3rd month and 6th month).

Smoking is one of the leading preventable causes of disease. According to global adult tobacco survey data, 19.2 million people (31.6%) in Turkey use tobacco products (KYTA, 2016). The rate of individuals over the age of 15 who use tobacco products every day is announced as 28.3% in TUIK 2022 data. Smoking rates of teachers were found to be between 29.1 and 52.4% in studies conducted in Turkey (Perincek, 2021). Teachers are the most important exemplary community in the school, with their identity as educators and their function as role models in society. Teachers with nicotine addiction must smoke during school hours.However, there is a negative relationship between teachers' desire to smoke and their personal success (Becet A.,2019). In a study, it was stated that transtheoretic model-based education increased teachers' anti-smoking attitudes and reduced nicotine addiction (Mermer et al. 2016). Studies indicate that the presence of teachers who smoke at school is associated with students' smoking behavior (Radha et al.,2019; Kjeld et al.,2023; Piontek et al. 2008; Savadi et al.,2013). In addition, the success rate of smoking cessation initiatives carried out by teachers themselves is low (Tunç, 2007). It is important for teachers to quit smoking not only for their own health but also for setting an example for students, who are the adults of the future.

It has been stated that the reason for the diversity in the effectiveness of investments made to quit smoking all over the world is the differences in the behavioral support provided to individuals (Hartmann et al., 2021). Most non-pharmacological interventions for smoking cessation use the transtheoretic change model defined by Prochaska and DiClemente (Prochaska \& DiClemente, 1992; Ripoll et al, 2012). The transeoretic model is one of the guiding models used to help individuals achieve positive behavioral change. According to this model, a smoker goes through a series of stages in the process of quitting smoking: non-reflection (the individual does not think about quitting smoking), contemplation (the individual begins to feel unhappy with his addiction and begins to think about quitting smoking in the next 6 months), preparation (the individual is ready to quit smoking), action (the individual has not completed six months of quitting smoking), continuation (the individual has not smoked for more than six months (Prochaska et al., 1992). The model is based on the principle that behavioral change is a process and that the interventions are developed according to the stage of change the individual is in ( Taş et al., 2016). When individuals are not ready for behavioral change, the risk of relapse increases (Koyun, 2015). The best form of behavioral change is the one that occurs in stages (Maddux, 1995). Motivational interviewing techniques and counseling training are included in smoking cessation attempts. , web-based interventions, and mobile phone-based interventions have been found effective as smoking cessation methods and are accepted as recommended approaches (Önür et al.2016; Taş et al.,2016; Fang et al,2023; Akdeniz et al.2020; Mermer et al,2016).

Today, mobile technologies are among the effective methods in health promotion and development. On the other hand, the rate of individuals using mobile and smartphones in Turkey in 2023 is 95.4% (Mobisad, 2023). 87.1% of these individuals can access the internet from their mobile devices (TUIK, 2023). Mobile internet interventions allow users to carry the intervention with them during their daily routine (Danaher et al., 2019). Barriers to quitting smoking include limited access and adherence to effective cessation interventions. It is thought that technology can help overcome these obstacles (Iacoviello et al.,2017). Mobile applications can reduce negative health outcomes by providing real-time, permanent and cost-effective support to support tobacco cessation (Chu et al.,2021). In their meta-analysis study investigating e-health-based smoking cessation interventions, Fang et al. (2023) defined the mobile health application as the dominant approach compared to others and stated that it could be an encouraging method for quitting smoking. Iacoviello et al (2017) found that the use of the Clickotine smartphone application to quit smoking may be associated with smoking cessation results. Many other studies have mentioned the effectiveness of mobile technologies in quitting smoking (Baskerville et al., 2018; Crane et al., 2018; Marler et al., 2019; Zhou et al., 2023; Brin et al., 2023; Pandya et al., 2023).

Biochemical confirmations are considered the gold standard in detecting smoking (Fanshawe et al.,2017). While smoking causes the body to absorb various toxins, one of these toxins that can be easily monitored is carbon monoxide (CO). CO assessment is an easy, non-invasive and fast-yielding method (Babaoğlu et al., 2016; Shie et al., 2017). Public health nurses have important roles in protecting and improving health and reducing health risks. In the theme of the International Council of Nurses (ICN (2005), it is stated that nurses have an important opportunity in their daily work routines to protect individuals from smoking and to help users quit smoking (Bilir \& Telatar, 2005). While nurses can provide objective data with CO measurement in the monitoring of the smoking cessation initiative process, Thanks to mobile technology, they can communicate with individuals more easily, increase their motivation, and follow up. Nurses can support individuals to take action in the fight against smoking. In a study, the emergency room nurse used the "Ask, Advise, Refer" method to increase the number of patients with 6.3 cigarettes after a 12-week intervention. It has been reported that many people accept smoking cessation interventions (Simerson \& Hackbarth, 2018). Similarly, in a systematic review, it was stated that smoking cessation interventions made by nurses were effective in helping individuals give up their smoking habits (Petersen et al., 2017).

Eligibility Criteria:
Inclusion Criteria:

* Having a smartphone and daily internet access
* Volunteering to participate in the study
* Getting a score of 5 medium level or above according to the Fagerström Nicotine Dependency Test rules test
* Not always having any smoking cessation support or a smoking cessation intervention

Exclusion Criteria:

* Those who did not agree to participate in the research
* Those who do not smoke or have quit smoking
* Those who use any tobacco product other than cigarettes (e-cigarette, hookah, cigar, etc.)
* Those who have severe chronic health problems (vision-hearing problems, dementia and Alzheimer's, chronic lung diseases)
* Those who do not use smartphones