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Abstract

Introduction:

E-cigarette use has become increasingly prevalent among adolescents and young adults.

Objective:

This study aimed to identify determinants associated with successful e-cigarette cessation among secondary school students.

Setting:

Study was conducted at the secondary schools in northern Thailand.

Methods:

A cross-sectional study was conducted among 277 secondary school students in Thailand, aged 12 to 25 years. Participants completed a self-administered electronic questionnaire assessing sociodemographic characteristics, academic performance, age of initiation, exposure to e-cigarette use in the environment (defined as having 1 or more e-cigarette users among family, relatives, or friends), perceived risks, and attitudes toward e-cigarettes (the higher score indicates risky attitudes toward e-cigarettes). The outcome was successful cessation, defined as being a former e-cigarette user (no use in the past 12 months among ever-users). Multiple logistic regression analyses were used to explore the factors associated with successful e-cigarette quitting. The gender subgroup analysis was performed.

Results:

Of 277 participants, 114 (41.2%) were former users and 163 (58.8%) were current users. The absence of e-cigarette users in the environment (aOR 0.38, 95% CI 0.22-0.67, P = .001) and risky attitudes toward e-cigarettes (aOR 0.79, 95% CI 0.72-0.88, P < .001) were independently associated with cessation. Subgroup analysis confirmed the importance of attitudes for both males and females, while environmental exposure was significant among females.

Conclusion:

Successful cessation among secondary school students was strongly associated with less risky attitudes toward e-cigarettes and the absence of e-cigarette users in the peer and family environment. Interventions should target both individual attitude and environmental factors to improve quit rates. Therefore, interventions should focus on correcting attitudes regarding the social image, stress relief, and socialization aspects of e-cigarettes, while simultaneously engaging families and peers to create a vape-free environment.

Keywords

e-cigarette cessation adolescents school-based intervention environmental exposure attitudes

Introduction

The World Health Organization (WHO) reports that e-cigarette use among youth aged 13 to 15 is higher than among adults in every region worldwide.¹ This trend is particularly concerning in countries such as the United States, where in 2023, 10% of high school students reported using e-cigarettes, 5 times the prevalence of cigarette smoking.² Thailand enforces 1 of the world’s strictest e-cigarette regulations, imposing a complete ban on the import, sale, and possession of e-cigarettes since 2014. However, e-cigarette use among Thai adolescents has risen sharply. Between 2015 and 2022, prevalence increased more than fivefold, from 3.3% to 17.6% among youth aged 13 to 15 years.³ This surge reflects both the growing popularity of e-cigarettes and their accessibility, driven largely by aggressive marketing strategies targeting young people, especially through black market and aggressive online marketing.⁴ There is the unique challenge that absolute prohibition has paradoxically contributed to a sharp increase in prevalence and accessibility. A 2021 survey by Thailand’s Department of Disease Control revealed the highest rates of use among individuals aged 15 to 24 years.⁵ This pattern mirrors data from the U.S. Centers for Disease Control and Prevention (CDC), which found prevalence peaking among those aged 18 to 24 years.⁶

Scientific evidence shows that nicotine disrupts the developing young adult brain, particularly the dopaminergic system, increasing vulnerability to addiction. Consequently, e-cigarette use has been linked not only to nicotine dependence but also to concurrent use of other substances, including alcohol and cannabis.⁷ Health risks extend beyond addiction. E-cigarette use has been strongly associated with severe lung inflammation, for which no specific treatment exists.⁸ Furthermore, e-cigarettes negatively affect multiple organ systems: they increase the risk of cardiovascular disease,⁹ harm oral health by contributing to dental disease,¹⁰ and impair brain function through nicotine’s addictive effects. These consequences result in lasting harm to both individuals and society by undermining physical health and increasing long-term healthcare costs.¹¹

Adolescents are particularly vulnerable to e-cigarette use, not only due to age-related curiosity but also because a lack of proper understanding often leads them to continue using substances without recognizing the long-term harms.¹² Perceived risks and attitudes also play a crucial role, as misconceptions are commonly linked with continued e-cigarette use. For example, despite limited evidence that e-cigarettes facilitate smoking cessation, this belief remains common, and product design and marketing often appeal to children and adolescents.¹³ A study among Thai students aged 13 to 19 years found that only about 60% demonstrated accurate perception about e-cigarettes, and most schools lacked clear regulations to control their use.¹⁴

WHO emphasizes that cessation should be the primary goal of care for e-cigarette users.¹⁵ Various interventions have been explored, encompassing both pharmacological and behavioral approaches. Among these, Cognitive Behavioral Therapy (CBT) is the most widely applied non-pharmacological method and has demonstrated notable effectiveness for both smoking and vaping cessation in adults and adolescents.¹⁶ CBT functions as an active learning process that enhances perceived risks, corrects misconceptions, and reshapes permissive attitudes toward e-cigarette use. It also restructures distorted beliefs that trigger cravings and equips individuals with practical coping strategies and adaptive behaviors for real-life situations.¹⁷ The Theory of Planned Behavior (TPB) provides a theoretical explanation for these CBT mechanisms, positing that behavior is directly determined by intention, which is shaped by perceived risks and attitude.^18,19 Both perceived risks and attitude play crucial roles in forming these intentions and guiding behavioral change. Therefore, successful cessation requires a comprehensive, multifaceted strategy that addresses cognitive, emotional, and social determinants of behavior. This is particularly important among adolescents, for whom limited perceived risks, misinformed attitudes, and the influence of family and school environments critically shape their susceptibility and success in cessation efforts. Peer support has been shown to facilitate quitting, while guidance from teachers and parents can further strengthen cessation success.²⁰ In Thailand, research on e-cigarette cessation remains limited and has primarily focused on adolescents aged 15 years and older.²¹ Existing studies have often examined the prevalence of use and associated risk factors,^22-24 but there is still little evidence on what contributes to successful cessation. To address this gap, the present study aimed to identify factors associated with successful e-cigarette cessation among secondary school students. The findings are intended to inform healthcare providers and stakeholders in developing effective prevention and cessation strategies within schools.

Methods

Study Design

This is an observational cross-sectional study, a subset of a larger school-based cross-sectional survey, focusing specifically on students with a history of e-cigarette use. The analysis was not pre registered and the results should be considered exploratory. The study was reported in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement (Supplemental Material).²⁵

Study Population and Setting

In Thailand, there are 2 educational pathways. Formal education typically places students in secondary school from ages 12-13 to 17-18.²⁶ Informal education serves those who paused or left school, allowing them to return and complete their secondary level. Therefore, student ages in this system often vary widely, usually starting from 12 and above.²⁷ The study was conducted in the secondary school in 1 district of the northern region of Thailand. The eligible participants were secondary school students, both formally and informally educated, aged 12 to 25 years at the time of data collection, who could answer questions independently and had reported using e-cigarettes at least once in their lifetime. Participants were recruited via convenience sampling through school announcement invitations disseminated by the research assistant. To minimize potential self-selection bias, we provided essential information about the study’s purpose and confidentiality to all potential participants, ensuring that the decision to participate was based on an informed choice.

Sample Size

The sample size calculation was performed using the prevalence from a previous study about successful e-cigarette cessation at 27.5%.²⁸ We used the infinite population proportion with the beta error 0.1 and the alpha error 0.01. At least 133 sample sizes were required. The post-hoc analysis was performed to assess the statistical power of the final model. The sample size of 277 can detect odd ratios below 0.4 and greater than 2.5 with a power of 91.97%.

Measurements and Variables

Participant Characteristics

Determinants were defined based on previous literature about factors associated with e-cigarette use among Thai secondary school students.^23,29 Younger age of initiation was defined as those who initiated e-cigarette use at an age of onset less than 15 years old. Good academic performance was defined as having a grade point average greater than 2.0, according to Thai Ministry of Education Regulations.³⁰ Low socioeconomic status was defined as household incomes less than 3000 baht (approximately 94.24 USD) per month, as defined by the Office of the National Economic and Social Development Council (NESDC).³¹ Exposure to e-cigarette use in the environment was defined as having 1 or more people who use e-cigarettes in their environment, including family, relatives, and friends.

Perceived Risks of E-Cigarettes

Perceived risks of e-cigarettes were measured from the questionnaire from a previous study.³² The questions included (1) e-cigarettes cannot help people quit smoking conventional cigarettes, (2) e-cigarettes contain nicotine, which is addictive and can damage the brain if used long-term, (3) e-cigarettes can cause severe lung inflammation, (4) e-cigarettes increase the risk of coronary artery disease, and (5) e-cigarettes can cause oral diseases such as tooth decay and black teeth. The answering is a 5-point likert scale, from 1 (totally disagree) to 5 (totally agree). The higher score in perceived risks of e-cigarettes indicates higher perceived risks associated with e-cigarettes. Cronbach’s alpha indicates good internal consistency for this data at 0.8602.

E-Cigarette Attitude

E-cigarette attitude was measured from the questionnaire from a previous study.³² The questions included (1) e-cigarettes make you look good and stylish, (2) e-cigarettes helps relieve stress, and (3) e-cigarettes make it easier to socialize with friends. The answering is a 5-point likert scale, from 1 (totally disagree) to 5 (totally agree). The lower score in attitude indicates an appropriate attitude for e-cigarettes. Therefore, the higher score indicates risky attitudes toward e-cigarettes. Cronbach’s alpha indicates good internal consistency for this data at 0.8024.

The Success of Stopping E-Cigarette Use

The study outcome was successful cessation, defined as being a former e-cigarette user (reporting no e-cigarette use in the past 12 months among all ever-users).

Data Collection

The data collection was conducted in August 2025 using a self-administered electronic questionnaire. Both parents and students were informed about the study process. Parental consent was obtained before participant consent. The electronic questionnaire was distributed directly in class by displaying a quick response (QR) code linked to a Google Form.

Data Analysis

All statistical analysis and modeling were performed using Stata version 17 (StataCorp, College Station, TX, USA). Categorical variables were presented with frequency and percentage. The chi-square test was used for comparing categorical variables. Multiple logistic regression analyses were used to examine independent variables associated with the successful quitting of e-cigarettes (former user). Younger age of initiation, good academic performance, low socioeconomic status, and exposure to e-cigarette use in the environment were included in the model as categorical variables (yes/no). Perceived risks of e-cigarettes (scores 5-25) and risky attitudes toward e-cigarettes (scores 3-15) were included in the model as continuous variables. The linearity in the logit for all continuous predictors was confirmed, and it was checked for multicollinearity using Variance Inflation Factor (VIF) scores, finding no evidence of significant multicollinearity. Since male and female were found to have difference behavior about e-cigarette use.^33,34 Subgroup analysis by gender (male and female) was performed to determine different between variables.

Results

From 900 participants who completely responded to the questionnaire, there were 277 participants who reported a history of using e-cigarettes at least once in their lifetime. There was no missing data. Figure 1 shows the study flow diagram. Of the 277 participants, 114 were former e-cigarette users (41.2%) and 163 were current users (58.8%). The former user group had a younger age (P = .008). In addition, the former user group showed a higher proportion of academic performance (93.0% vs 85.3%, P = .048), lower exposure to e-cigarette use in the environment (52.6% vs 76.7%, P < .001), and lower risky attitudes toward e-cigarettes (3.60 ± 2.88 vs 5.34 ± 2.43, P < .001). The younger age of initiation, low socioeconomic status, and perceived risks of e-cigarettes were not different between the groups. Table 1 presents the characteristics of the participants.

Figure 1.

Study flow diagram.

Table 1.

Participant Characteristics.

Characteristics	Former user	Current user	P-value
N = 277	n = 114 (41.2%)	n = 163 (58.8%)	P-value
Gender
Male	54 (47.4)	88 (55.7)	.231
Female	56 (49.1)	68 (43.0)
Other	4 (3.5)	2 (1.3)
Age (mean ± SD)	16.55 ± 2.77	17.53 ± 3.13	.008
Younger age of initiation (less than 15)	58 (50.9)	71 (43.6)	.229
Academic performance (GPA 2.00 and better)	106 (93.0)	139 (85.3)	.048
Low socioeconomic status (household incomes < 3000 baht per month)	8 (7.0)	9 (5.5)	.610
Exposure to e-cigarette use in the environment	60 (52.6)	125 (76.7)	<.001
Perceived risks of e-cigarettes (mean ± SD)	14.36 ± 4.49	13.73 ± 4.23	.236
Risky attitudes toward e-cigarettes (mean ± SD)	3.60 ± 2.88	5.34 ± 2.43	<.001

Abbreviation: SD, Standard deviation.

Figure 2 presents factors associated with e-cigarette cessation among secondary school students. Exposure to e-cigarette users in the environment and attitudes toward e-cigarettes were associated with successful cessation. Participants who had no e-cigarette users in their environment (adjusted odds ratio [aOR] 0.38, 95% confidence interval [CI] 0.22-0.67, P = .001) and had more appropriate attitudes toward e-cigarettes (aOR 0.79, 95% CI 0.72-0.88, P < .001) were more likely to successfully stop using e-cigarettes. Academic performance was not shown to have a significant association with successful cessation in multivariable analysis. For subgroup analysis by gender, more appropriate attitudes toward e-cigarettes showed a significant association with successful cessation in both males and females (aOR 0.74, 95% CI 0.64-0.86, P < .001 and aOR 0.83, 95% CI 0.71-0.96, P = .013, respectively). Participants who had no e-cigarette users in their environment also showed a significant association with successful cessation in both males and females (aOR 0.40, 95% CI 0.18-0.88, P = .022 and aOR 0.27, 95% CI 0.11-0.67, P = .004, respectively).

Figure 2.

Factors associated with former user among secondary school students.

Discussion

Overall, 41.2% of students successfully discontinued e-cigarette use. Participants without e-cigarette users in their immediate environment and those with more favorable attitudes toward cessation demonstrated a higher likelihood of successful quitting. Subgroup analyses stratified by gender indicated that, among both males and females, positive attitudes toward cessation were significantly associated with successful discontinuation. Moreover, the absence of e-cigarette users in the participants’ environment remained positively associated with cessation.

The proportion of students who successfully quit e-cigarettes in this study is consistent with previous findings. A study among high school students, age 15.9 (SD 1.2), in Connecticut, United States, reported that 40.3% of those who attempted to quit were successful.³⁵ The factors found to be associated with successful quitting included older age, fewer friends who vaped, and perceiving that quitting would be easy. Furthermore, more than half of younger users had made at least 1 quit attempt.³⁶ Similarly, data from the National Youth Tobacco Survey (NYTS) indicated that 70.2% of adolescent current e-cigarette users reported intentions to quit vaping, while 66.3% reported a quit attempt within the past year.³⁷

In univariable analysis, the former user group showed a higher proportion of academic performance. Poor academic performance was associated with susceptibility to e-cigarette use among high school students in China,³⁸ and vice versa, a study among secondary school students in the United States found that initiating e-cigarette use was associated with subsequent poorer academic performance.³⁹ E-cigarette users may use the products during school hours, which can disrupt learning.⁴⁰ Moreover, they may be affected by substances, particularly nicotine, which can impair attention and learning.⁴¹

In multivariable analysis, exposure to e-cigarette users in the environment and attitudes toward e-cigarettes were associated with successful cessation. Environmental influences played a critical role. Students who reported no e-cigarette users in their immediate environment were significantly more likely to quit, emphasizing the influence of peers and social contexts. This finding is consistent with prior studies showing that exposure to peers or family members who use e-cigarettes normalizes the behavior and reinforces continued use.⁴² Reducing environmental exposure through stricter school regulations and community-based prevention initiatives could therefore be instrumental in promoting cessation.⁴³ Attitudes toward e-cigarettes also emerged as a key determinant of successful cessation among students. Participants with more positive attitudes toward quitting, likely to reflect greater awareness of harm, were significantly more likely to stop using e-cigarettes. This finding highlights that, in health promotion, factual risk from e-cigarettes alone is often insufficient to drive behavior change. Current users tend to hold stronger beliefs that vaping helps them manage stress, fit in socially, or concentrate, whereas former users may have shifted their beliefs to emphasize negative outcomes such as health risks, financial costs, or feelings of addiction.⁴⁴ Prior research on adolescent substance use has shown that although young people often recognize the associated risks or cognitive awareness alone is insufficient to prevent use.⁴⁵ The TPB helps explain this pattern by suggesting that behavior is directly predicted by intention, which is shaped by attitudes toward the behavior, subjective norms (perceived social pressure), and perceived behavioral control (self-efficacy).^18,19 Therefore, perceived risk provides the foundation for informed decision-making, it must be coupled with positive attitude change and strengthened perceived behavioral control to translate awareness into behavioral action. These findings highlight the need for interventions that move beyond simple information about the risk of e-cigarette dissemination to actively reshape attitudes and beliefs about e-cigarettes. School-based programs that integrate perceived risks enhancement with attitude modification and behavioral skill-building may be particularly effective in supporting cessation efforts among adolescents and young adults.³² A study of school-based e-cigarette cessation programs among youth in the United States revealed that adolescents require a vaping cessation program to incorporate education regarding the health impacts of vaping, personal experiences from others, and rewards for cessation.⁴⁶ Additionally, the possession and use of e-cigarettes carry legal risks (eg, fines or confiscation),⁴⁷ which may serve as strong external motivators for quitting, especially among adolescents who fear disciplinary consequences from schools or law enforcement.

Interestingly, the results of this study diverged from prior evidence regarding age of initiation. We did not find the association between age of initiation and quitting successfully. It is possible that younger initiators were more likely to engage in experimental rather than habitual use, making cessation easier before long-term dependence developed.⁴⁸ Previous studies have consistently demonstrated that earlier age of initiation is a strong predictor of substance dependence.^49,50 The discrepancy in this study may be attributable to differences in inclusion criteria, as ever-users, both transient and established users, were included. This group of transient users would increase the overall successful quit rate among the younger initiation group. Consequently, the expected association between age of initiation and cessation was not observed. Future study may focus on early initiation, especially on the transition to dependence. Another factor that may explain is the variability in product characteristics, specifically nicotine concentration and formulation, used by our participants. Earlier nicotine exposure is strongly linked to higher dependence and typically makes cessation much harder.⁵¹

Subgroup analysis revealed strong association between the absence of e-cigarette users in their environment and appropriate attitude and success quitting in both male and female students. The absence of e-cigarette users in their environment and appropriate attitude was associated with success quitting. These results are in line with broader evidence on adolescent social dynamics.³⁴ The heightened importance of the social environment may reflect stronger conformity pressures within peer groups.⁵² These insights suggest that gender sensitive component interventions may be warranted. The interventions could explore the connection between their personal attitudes toward e-cigarettes and their vaping behaviors. This could involve challenging positive expectancies and linking vaping to negative personal outcomes.^53,54 The intervention programs may add focusing on building resilience against peer influence.³⁴ This might involve teaching refusal skills and emphasizing the negative social consequences of vaping.⁵⁵ Furthermore, because social dynamics and conformity pressures can vary across genders. For male students, whose vaping behavior may be more closely linked to social image, status, and perceived masculinity.⁵⁶ The interventions should challenge and dismantle the belief that e-cigarettes enhance social standing by reframing the social narrative surrounding vaping. In addition, among male students, perceived risks appear to be a potential factor associated with successful quitting. Therefore, while health education is likely necessary, components of an intervention for this group remain a crucial foundation for ensuring that students have accurate beliefs about health risks.⁵⁷ For female students, who may be more likely to use e-cigarettes for stress relief or emotional regulation,⁵⁸ interventions should prioritize non-substance-based coping strategies, such as cognitive restructuring and mindfulness techniques, to replace the perceived stress-relief function of vaping.

This is the first study on the supportive factors associated with successfully quitting e-cigarette use among secondary school students in Thailand. The results could be beneficial for schools, government agencies, and healthcare sectors involved in prevention programs targeting adolescent e-cigarette use. Nevertheless, some limitations should be acknowledged. First, due to the cross-sectional design of the study, causal relationships between determinants and outcomes cannot be established. However, we used clear definitions for each variable, including the age of initiation of e-cigarette use, which may enhance the reliability of the results. Second, the data was based on participants’ self-reports, meaning that accuracy could not be independently verified. To address this, we provided detailed explanations of each specific question during the informed consent process. We also checked for distribution errors and outliers, which were subsequently excluded, ensuring that the data was as accurate and reliable as possible. Third, we could not identify the actual substances in e-cigarettes those participants used, such as nicotine. Nicotine dependence is a likely mediator between the studied factors and the actual outcome of cessation. High exposure to e-cigarette use in the environment may not only normalize the behavior but also facilitate more frequent use, leading to higher nicotine dependence, which in turn makes quitting harder. Greater e-cigarette dependence among adolescents was associated with a lower likelihood of intending to quit and a higher number of past-year quit attempts, suggesting that dependent users struggle more and are less successful.³⁶ Future research should include a measurement for substance dependence, such as the Fagerström Test for Nicotine Dependence or a validated equivalent for e-cigarettes, to better account for this critical factor. Fourth, a predefined sample size was not performed due to the nature of secondary data analysis. However, we performed post-hoc analysis and proved that this sample size could detect more than 90% power to detect odd ratios lower than 0.4 and greater than 2.5. Fifth, there are limitations regarding the measurement tools. The questions may not cover all aspects of negative expectations, particularly financial cost. However, the perceived risk of e-cigarettes may capture the health risk perception. Sixth, the findings may not be generalizable to the broader adolescent population because the study employed convenience sampling of only the students in 1 province of Thailand. Finally, we did not collect students’ grades and classes because the study population comprised both formal and non-formal education students. Consequently, specific grade levels or class identifiers were not collected to avoid misclassification arising from these differing educational structures. Therefore, the variance of the estimates from the regression analysis was not corrected for clustering effects from grade or class, which may lead to an underestimation of the standard errors.

Conclusion

The successful cessation among secondary school students is influenced by a combination of individual and environmental, attitudes toward e-cigarettes and close people who use e-cigarettes. Interventions should correct misperceptions about vaping’s social image and perceived benefits (eg, stress relief and socialization) while actively engaging families and peers to support a vape-free environment. Overall, these findings support a comprehensive approach. Strengthening school-based prevention policies, increasing family involvement, and reducing peer-related pressures may be especially important in helping students quit successfully.

Supplemental Material

sj-docx-1-jpc-10.1177_21501319261415797 – Supplemental material for Attitude and Environmental Factors Associated With Successful E-Cigarette Quitting Among Secondary School Students: A Cross-Sectional Observational Study

Supplemental material, sj-docx-1-jpc-10.1177_21501319261415797 for Attitude and Environmental Factors Associated With Successful E-Cigarette Quitting Among Secondary School Students: A Cross-Sectional Observational Study by Wichuda Jiraporncharoen, Nida Buawangpong, Pasiri Singhasiri, Awirut Oon-arom, Wachiranun Sirikul, Pimploy Choradon, Thanachat Yotruangsri, Apinun Aramrattana, Kanittha Thaikla, Kanrawee Tongton and Atchararapee Champa in Journal of Primary Care & Community Health

Footnotes

ORCID iDs

Wichuda Jiraporncharoen

Nida Buawangpong

Wachiranun Sirikul

Thanachat Yotruangsri

Ethical Considerations

This study has been approved by the medical council from the faculty of Medicine Chiangmai University. Study code: FAM-2568-0091.

Consent to Participate

All the participants gave their consents and signed their signature before the data collection process. The collected data does not include personal identity information.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by a Grant from Faculty of Medicine, Chiang Mai University (grant number 107-2568).

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

The datasets in the current study are available from the corresponding author upon reasonable requests.*

Supplemental Material

Supplemental material for this article is available online.

References

World Health Organization. Tobacco and nicotine industry tactics addict youth for life. 2024. Accessed 1 October 2025, https://www.who.int/news/item/23-05-2024-tobacco-and-nicotine-industry-tactics-addict-youth-for-life

Tattan-Birch

Jackson

Kock

Dockrell

Brown

. Rapid growth in disposable e-cigarette vaping among young adults in Great Britain from 2021 to 2022: a repeat cross-sectional survey. Addiction. 2023;118(2):382-386. doi:10.1111/add.16044

Embassy

. Prohibition of e-cigarettes. 2019. Accessed 25 September 2025, https://london.thaiembassy.org/en/publicservice/86207-prohibition-of-e-cigarettes?page=5d6636ce15e39c3bd000734d&menu=5d6636cd15e39c3bd00072e2

Sittibusaya

Benjakul

Noonak

, et al. Global youth tobacco survey 2022 for developing tobacco control policies in Thailand. Dis Control J. 2025;51(2):339-353. doi:10.14456/dcj.2025.27

Adebisi

Phungdee

Saokaew

Lucero-Prisno

. Prevalence and determinants of current cigarette smoking among adolescents in Thailand: evidence from 2021 global school-based health survey. J Res Health Sci. 2024;24(2):e00610. doi:10.34172/jrhs.2024.145

Kramarow

Elgaddal

. Current electronic cigarette use among adults aged 18 and over: United States, 2021. NCHS Data Brief. 2023;475:1-8.

Chen

Rahman

Lutfy

. E-cigarettes may serve as a gateway to conventional cigarettes and other addictive drugs. Adv Drug Alcohol Res. 2023;3:11345. doi:10.3389/adar.2023.11345

Winnicka

Shenoy

. EVALI and the pulmonary toxicity of electronic cigarettes: a review. J Gen Intern Med. 2020;35(7):2130-2135. doi:10.1007/s11606-020-05813-2

Bianco

Skipalskyi

Goma

, et al. E-cigarettes: a new threat to cardiovascular health—a world heart federation policy brief. Glob Heart. 2021;16(1):72. doi:10.5334/gh.1076

10.

Herman

Tarran

. E-cigarettes, nicotine, the lung and the brain: multi-level cascading pathophysiology. J Physiol. 2020;598(22):5063-5071. doi:10.1113/jp278388

11.

Wang

Sung

H-Y

Lightwood

Yao

Max

. Healthcare utilisation and expenditures attributable to current e-cigarette use among US adults. Tobacco Control. 2023;32(6):723. doi:10.1136/tobaccocontrol-2021-057058

12.

Deep

Ghosh

Gaither

Rahaman

. The factors affecting substance use and the most effective mental health interventions in adolescents and young adults. Psychoactives. 2024;3(4):461-475.

13.

Songsin

Wannapaschaiyong

Loylib

, et al. Perception and attitude towards electronic cigarettes among rural Thai young adults. Siriraj Med J. 2024;76(9):604-610. doi:10.33192/smj.v76i9.269105

14.

Phetphum

Keeratisiroj

Prajongjeep

. Perception of e-cigarette control policies and education in schools on increased legal knowledge, harm perception, susceptibility and e-cigarette use among students in Thailand: a cross-sectional classroom-based survey. Tob Induc Dis. 2024;22. doi:10.18332/tid/187840

15.

Hajek

Peerbux

Phillips-Waller

Smith

Pittaccio

Przulj

. Are ‘dual users’ who smoke and use e-cigarettes interested in using varenicline to stop smoking altogether, and can they benefit from it? A cohort study of UK vapers. BMJ Open. 2019;9(3):e026642. doi:10.1136/bmjopen-2018-026642

16.

Hampsher-Monk

Prieger

Patwardhan

. E-cigarettes and smoking cessation. In: Hampsher-Monk

Prieger

Patwardhan

, eds. Tobacco Regulation, Economics, and Public Health, Volume II: Clearing the Air on E-Cigarettes and Harm Reduction. Springer Nature Switzerland; 2024:105-184.

17.

McHugh

Hearon

Otto

. Cognitive behavioral therapy for substance use disorders. Psychiatr Clin North Am. 2010;33(3):511-525. doi:10.1016/j.psc.2010.04.012

18.

Hershberger

Connors

Cyders

. The theory of planned behavior and E-cig use: impulsive personality, E-cig attitudes, and E-cig use. Int J Ment Health Addict. 2018;16(2):366-376. doi:10.1007/s11469-017-9783-6

19.

Topa

Moriano

. Theory of planned behavior and smoking: meta-analysis and SEM model. Subst Abuse Rehabil. 2010;1:23-33. doi:10.2147/sar.S15168

20.

Palmer

Price

Foster

Sanford

Fucito

Toll

. Urgent need for novel investigations of treatments to quit E-cigarettes: findings from a systematic review. Cancer Prev Res. 2022;15(9):569-580. doi:10.1158/1940-6207.Capr-22-0172

21.

Academic information about e-cigarettes. Department of Disease Control, Thai Ministry of Public Health. 2024; 1-20.

22.

Benjakul

Nakju

Termsirikulchai

. Factors associated with e-cigarette use among vocational students: a cross-sectional multistage cluster survey, Thailand. journal article. Tob Induc Dis. 2023;21:1-11. doi:10.18332/tid/170421

23.

Phetphum

Keeratisiroj

Prajongjeep

. Socio-ecological factors associated with e-cigarette susceptibility and current use among Thai adolescents. Addict Res Theory. 2025;33(3):213-222. doi:10.1080/16066359.2024.2415571

24.

Phetphum

Prajongjeep

Thawatchaijareonying

, et al. Personal and perceptual factors associated with the use of electronic cigarettes among university students in northern Thailand. Tob Induc Dis. 2021;19:31. doi:10.18332/tid/133640

25.

von Elm

Altman

Egger

Pocock

Gøtzsche

Vandenbroucke

. The strengthening the reporting of observational studies in epidemiology (STROBE) statement: guidelines for reporting observational studies. Ann Intern Med. 2007;147(8):573-577. doi:10.7326/0003-4819-147-8-200710160-00010

26.

Policies and Practices for Student Admissions under the Office of the Basic Education Commission . Accessed October 1, 2025. https://cmu.to/QcCbP

27.

Office of Non-Formal and Informal Education, Office of the Permanent Secretary, Ministry of Education. Non-formal education. 2020. Accessed October 1, 2025. https://cmu.to/0gcKi

28.

Bejarano

Bluestein

Tackett

, et al. Factors associated with successful E-cigarette cessation among a convenience sample of adult users. Subst Use Misuse. 2024;59(7):1126-1132. doi:10.1080/10826084.2024.2320395

29.

Phetphum

Prajongjeep

Youngiam

Thawatchaijareonying

. Susceptibility to smoking and determinants among never-smoking high school students in Thailand. Tob Induc Dis. 2023;21:2. doi:10.18332/tid/156456

30.

Ratanasuwan

. The Management of Education and the Evaluation of Learning Outcomes According to the Vocational Certificate Curriculum. Ministry of Education Regulations. Royal Thai Government Gazette. 2013. Accessed October 1, 2025. https://www.ratchakitcha.soc.go.th/DATA/PDF/2559/E/200/1.PDF

31.

Office of the National Economic and Social Development Council. Poverty & Inequality Report. NESDC; 2024.

32.

Vichayanrat

Chidchuangchai

Karawekpanyawong

Phienudomkitlert

Chongcharoenjai

Fungkiat

. E-cigarette use, perceived risks, attitudes, opinions of e-cigarette policies, and associated factors among Thai university students. Tob Induc Dis. 2024;22:1-10. doi:10.18332/tid/186536

33.

Klemperer

Kock

Feinstein

MJP

Coleman

SRM

Gaalema

Higgins

. Reprint of: sex differences in tobacco use, attempts to quit smoking, and cessation among dual users of cigarettes and e-cigarettes: longitudinal findings from the US Population Assessment of Tobacco and Health Study. Prev Med. 2024;188:108112. doi:10.1016/j.ypmed.2024.108112

34.

Piñeiro

Correa

Simmons

, et al. Gender differences in use and expectancies of e-cigarettes: online survey results. Addict Behav. 2016;52:91-97. doi:10.1016/j.addbeh.2015.09.006

35.

Bold

Kong

Morean

, et al. Understanding reasons to quit or reduce vaping and associations with quitting outcomes among high school adolescents in Connecticut. J Adolesc Health. 2025;77(4):766-770. doi:10.1016/j.jadohealth.2025.01.004

36.

Merreighn

Veilleux

Schisler

Tabassum

Dobbs

. The experiences of young adults attempting to quit e-cigarettes: a mixed-methods analysis. Tob Prev Cessat. 2025;11:1-13. doi:10.18332/tpc/202831

37.

Daisy Dai

. Factors associated with intentions to quit vaping and quit attempts among adolescents: a structural equation modeling approach. Addict Behav. 2024;157:108074. doi:10.1016/j.addbeh.2024.108074

38.

Deng

Fang

Zhang

, et al. Susceptibility to e-cigarette among high school students: a study based on the ecological model of health behavior. Front Public Health. 2024;12:1395717. doi:10.3389/fpubh.2024.1395717

39.

Dearfield

Chen-Sankey

McNeel

Bernat

Choi

. E-cigarette initiation predicts subsequent academic performance among youth: results from the PATH Study. Prev Med. 2021;153:106781. doi:10.1016/j.ypmed.2021.106781

40.

Dai

. Youth observation of e-cigarette use in or around school, 2019. Am J Prev Med. 2021;60(2):241-249. doi:10.1016/j.amepre.2020.07.022

41.

Mooney-Leber

Gould

. The long-term cognitive consequences of adolescent exposure to recreational drugs of abuse. Learn Mem. 2018;25(9):481-491. doi:10.1101/lm.046672.117

42.

Durkin

Williford

Turiano

, et al. Associations between peer use, costs and benefits, self-efficacy, and adolescent e-cigarette use. J Pediatr Psychol. 2021;46(1):112-122. doi:10.1093/jpepsy/jsaa097

43.

National Center for Chronic Disease Prevention and Health Promotion (US) Office on Smoking and Health. E-Cigarette Use Among Youth and Young Adults: A Report of the Surgeon General The Call to Action. Centers for Disease Control and Prevention (US); 2016.

44.

Harrell

Brandon

England

, et al. Vaping expectancies: a qualitative study among young adult nonusers, smokers, vapers, and dual users. Subst Abuse. 2019;13:1178221819866210. doi:10.1177/1178221819866210

45.

Cengiz

Turan

Çelik

. Attitudes of adolescents toward addictive substances: hope and self-control as protective factors. Children. 2025;12(1):106. doi:10.3390/children12010106

46.

Bold

Kong

Cavallo

Davis

Jackson

Krishnan-Sarin

. School-based e-cigarette cessation programs: what do youth want? Addict Behav. 2022;125:107167. doi:10.1016/j.addbeh.2021.107167

47.

Royal Thai Embassy Stockholm. ban-on-electronic-cigarettes-in-Thailand. 2016. Accessed 1 October 2025, https://thaiembassy.se/en/ban-on-electronic-cigarettes-in-thailand/

48.

Castellanos-Ryan

O’Leary-Barrett

Conrod

. Substance-use in childhood and adolescence: a brief overview of developmental processes and their clinical implications. J Can Acad Child Adolesc Psychiatry. 2013;22(1):41-46.

49.

Jordan

Andersen

. Sensitive periods of substance abuse: early risk for the transition to dependence. Dev Cogn Neurosci. 2017;25:29-44. doi:10.1016/j.dcn.2016.10.004

50.

Poudel

Gautam

. Age of onset of substance use and psychosocial problems among individuals with substance use disorders. BMC Psychiatry. 2017;17(1):10. doi:10.1186/s12888-016-1191-0

51.

Kendler

Myers

Damaj

Chen

. Early smoking onset and risk for subsequent nicotine dependence: a monozygotic co-twin control study. Am J Psychiatry. 2013;170(4):408-413. doi:10.1176/appi.ajp.2012.12030321

52.

Klemperer

Kock

Feinstein

MJP

Coleman

SRM

Gaalema

Higgins

. Sex differences in tobacco use, attempts to quit smoking, and cessation among dual users of cigarettes and e-cigarettes: longitudinal findings from the US Population Assessment of Tobacco and Health Study. Prev Med. 2024;185:108024. doi:10.1016/j.ypmed.2024.108024

53.

Liu

Ramamurthi

Halpern-Felsher

. Inside the adolescent voice: a qualitative analysis of the appeal of different tobacco products. Tob Induc Dis. 2021;19:15. doi:10.18332/tid/132856

54.

Liu

Gaiha

Halpern-Felsher

. School-based programs to prevent adolescent e-cigarette use: a report card. Curr Probl Pediatr Adolesc Health Care. 2022;52(6):101204. doi:10.1016/j.cppeds.2022.101204

55.

McCauley

Baiocchi

Cruse

Halpern-Felsher

. Effects of a short school-based vaping prevention program for high school students. Prev Med Rep. 2023;33:102184. doi:10.1016/j.pmedr.2023.102184

56.

Groom

Landry

, et al. The influence of friends on teen vaping: a mixed-methods approach. Int J Environ Res Public Health. 2021;18(13):6784. doi:10.3390/ijerph18136784

57.

Weng

Yang

Song

Liu

Wang

. Engaging and supporting young adults in smoking cessation: insights from a mobile-based cessation program in China. Digit Health. 2025;11:20552076241311055. doi:10.1177/20552076241311055

58.

VanFrank

Williams

Alcantara

, et al. E-cigarette use and symptoms of depression and anxiety among US middle and high school students. Prev Chronic Dis. 2025;22:E51. doi:10.5888/pcd22.250186

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