Prevalence of E-Cigarette Use, Perceptions, and Attitudes Among Adolescents in Rural Communities of Samut Songkhram Province, Thailand: A Cross-Sectional Study

Highlights

Public health relevance—How does this work relate to a public health issue?

• Current and lifetime e-cigarette use among adolescents in rural Thailand were 5.86% and 18.36%, respectively, indicating ongoing experimentation despite national restrictions.
• Friends and online purchases were the most commonly reported sources of e-cigarettes, demonstrating the importance of social and digital access pathways.

Public health significance—Why is this work of significance to public health?

• This study provides context-specific evidence on e-cigarette use, perceptions, and attitudes among adolescents in rural Thai communities.
• Although overall perceptions and attitudes were generally protective, the affective attitude component remained moderate, while sex and perception scores were significantly associated with overall attitude scores.

Public health implications—What are the key implications or messages for practitioners, policy makers and/or researchers in public health?

• School and community-based prevention should strengthen refusal skills, address peer influence, and correct misconceptions about nicotine addiction, secondhand aerosol exposure, and long-term health risks.
• Regulatory enforcement should be combined with adolescent-friendly risk communication and measures to restrict access through online platforms and informal social networks.

Abstract

Electronic cigarette use among adolescents is an emerging public health concern, yet evidence from specific rural communities in Thailand remains limited. This cross-sectional study estimated the prevalence of e-cigarette use, described perceptions of e-cigarettes and attitudes toward e-cigarette use, and examined factors associated with overall attitude scores among 512 participants recruited from selected rural communities in Samut Songkhram Province, Thailand. The mean age was 18.46 years (SD = 1.37). Data were collected from December 2024 to August 2025 using a structured questionnaire and analyzed using descriptive statistics and multiple linear regression. Current e-cigarette use, defined as use within the previous 30 days, was reported by 5.86% of participants, while 18.36% reported lifetime use. Overall perceptions of e-cigarettes were classified as high (M = 2.52, SD = 0.34), whereas overall attitudes toward e-cigarette use were classified as good (M = 2.73, SD = 0.40). Sex was positively associated with overall attitude scores (B = 0.109, β = 0.097, p = 0.023), whereas perceptions of e-cigarettes were negatively associated with attitude scores (B = −0.473, β = −0.343, p < 0.001). The model explained 12.3% of the variance in overall attitudes. Among adolescents participating in this study from selected rural communities in Samut Songkhram Province, the findings indicate ongoing e-cigarette experimentation and highlight the potential importance of coordinated prevention strategies addressing peer influence, misconceptions, affective attitudes, and access through informal and online channels. These findings should be interpreted within the specific study setting and sampling design and should not be generalized to adolescents in rural Thailand as a whole.

1. Introduction

Electronic cigarettes (e-cigarettes), also known as electronic nicotine delivery systems, are battery-operated devices that heat a liquid to produce an aerosol that is inhaled by the user. E-cigarette liquids may contain nicotine, flavoring agents, solvents, additives, and other chemicals. Although e-cigarettes do not involve the combustion of tobacco, their aerosols are not harmless and may contain nicotine, volatile organic compounds, carcinogenic substances, ultrafine particles, and heavy metals. Most e-cigarettes contain nicotine, which is highly addictive and may adversely affect the developing adolescent brain, particularly the areas responsible for attention, learning, mood, memory, and impulse control [1,2].

E-cigarette use among adolescents has emerged as an important global public health concern. In the United States, the prevalence of current e-cigarette use among high school students increased substantially from 1.5% in 2011 to 20.8% in 2018 [3]. Although the prevalence subsequently declined, e-cigarettes remained the most commonly used tobacco product among American adolescents in 2024, with 7.8% of high school students and 3.5% of middle school students reporting use during the previous 30 days [4]. These changing prevalence patterns demonstrate the rapid evolution of e-cigarette products and the continuing need for surveillance among adolescent populations. The problem is also evident in Southeast Asia. A systematic review of studies published between 2012 and 2021 reported that the prevalence of current e-cigarette use among adolescents in Southeast Asian countries ranged from 3.3% to 11.8% [5]. Importantly, these figures represent the range of prevalence reported across different studies and countries rather than an increase over time. The review identified several groups of factors associated with adolescent e-cigarette use, including sociodemographic characteristics, adverse childhood experiences, peer and parental influence, knowledge and perceptions of e-cigarettes, the use of conventional cigarettes and other substances, and the accessibility of e-cigarette products [5].

Thailand has a longstanding commitment to tobacco control and became a Party to the World Health Organization Framework Convention on Tobacco Control (WHO FCTC) after ratifying the Convention in 2004, with entry into force in 2005 [6]. The WHO FCTC provides the international framework for comprehensive tobacco-control policies, while the WHO MPOWER package supports its implementation through measures to monitor tobacco use, protect people from tobacco smoke, offer help to quit tobacco use, warn about the dangers of tobacco, enforce bans on tobacco advertising, promotion, and sponsorship, and raise taxes on tobacco [7]. Thailand has implemented comprehensive tobacco-control measures through legislation, multisectoral collaboration, public health surveillance, health warnings, smoke-free policies, restrictions on advertising and promotion, and other population-based approaches. Nevertheless, the rapid emergence of e-cigarettes and their promotion through digital and social-media environments presents new challenges for protecting adolescents and sustaining progress in tobacco control [6,7].

Thailand has experienced a particularly substantial increase in e-cigarette use among adolescents. According to the 2015 Thailand Global Youth Tobacco Survey, 3.3% of students aged 13–15 years reported current e-cigarette use, defined as using an e-cigarette on at least one day during the previous 30 days [8]. In the 2022 survey, the prevalence increased to 17.6%, including 20.2% among boys and 15.0% among girls [9]. Therefore, the national prevalence increased approximately 5.3-fold between 2015 and 2022. In addition, 37.3% of Thai students aged 13–15 years reported having ever used an e-cigarette in 2022, indicating that experimentation with these products was widespread among school-aged adolescents [9,10]. The increasing use of e-cigarettes among adolescents may be influenced by several interacting factors. At the individual level, sex, age, knowledge, attitudes, perceived harmfulness, curiosity, conventional cigarette use, alcohol consumption, and other health-risk behaviors have been associated with e-cigarette use. Interpersonal factors include e-cigarette or cigarette use among friends and family members, peer encouragement, perceived social acceptance, and parental attitudes. Environmental factors include exposure to e-cigarette advertising and social media content, online and retail accessibility, appealing flavors and product designs, and the implementation of tobacco-control policies [5,11]. Adolescents who perceive e-cigarettes as less harmful, non-addictive, or helpful for quitting conventional cigarettes may be more likely to experiment with or continue using these products. E-cigarette use is therefore not determined solely by individual knowledge or decisions but is shaped by interactions among individual, interpersonal, community, media, and policy environments [12]. Rural adolescents may experience different patterns of family supervision, peer relationships, access to products, exposure to online media, and enforcement of tobacco-control regulations compared with adolescents in urban areas. Consequently, national prevalence estimates may not fully reflect the circumstances influencing e-cigarette use in particular rural communities. Context-specific evidence is needed to support the development of locally appropriate school-, family-, and community-based preventive interventions [13].

Samut Songkhram Province, Thailand is located in central Thailand and comprises predominantly rural and semi-rural communities. However, rural residence in this setting should not be interpreted as implying limited digital connectivity. National Statistical Office data indicate that, in 2024, approximately 52.0 thousand of the province’s 60.3 thousand households were connected to the Internet, while approximately 58.8 thousand households had a mobile phone [14]. These figures correspond to approximately 86% of households having an Internet connection and approximately 98% having a mobile phone, indicating substantial household-level digital connectivity. In addition, the average monthly household income in Samut Songkhram was 27,869 Thai baht in 2023 [15]. Although these household-level indicators do not directly measure adolescents’ individual disposable income or personal access to digital devices, they demonstrate that rurality in Samut Songkhram coexists with substantial access to digital communication infrastructure and household economic resources. This context is relevant because online platforms and digital social networks may provide adolescents with exposure to e-cigarette-related content and potential channels of access to e-cigarette products.

Despite the increasing availability and visibility of e-cigarettes among young people, evidence regarding adolescents’ perceptions of e-cigarettes and the factors associated with these perceptions remains limited, particularly in rural settings. Adolescents’ perceptions of the harmfulness, addictiveness, social acceptability, and potential benefits of e-cigarettes may influence their willingness to experiment with or use these products. These perceptions may be shaped by sociodemographic characteristics, knowledge of e-cigarettes, attitudes toward e-cigarette use, product accessibility, family and peer influences, exposure to e-cigarette-related information, and awareness of relevant laws and regulations. Understanding these factors is essential for identifying misconceptions and developing context-appropriate prevention and health education strategies [16]. Accordingly, examining e-cigarette use in a rural but digitally connected setting such as Samut Songkhram may provide important evidence for understanding how individual perceptions, peer influences, product accessibility, and online environments interact within the broader context of Thailand’s tobacco-control policies. Therefore, this study aimed to estimate the prevalence of current and lifetime e-cigarette use, describe perceptions of e-cigarettes and attitudes toward e-cigarette use, and examine factors associated with overall attitude scores among adolescents living in rural communities in Samut Songkhram Province, Thailand. The association between sex and lifetime e-cigarette use was also examined. The findings may provide evidence to guide the development of targeted school-, family-, and community-based interventions aimed at correcting misconceptions, strengthening risk awareness, and preventing e-cigarette initiation among adolescents in rural Thailand.

2. Materials and Methods

2.1. Study Design and Setting

This study employed a cross-sectional design to investigate the prevalence of e-cigarette use, perceptions of e-cigarettes, and associated factors among adolescents in rural Thailand. Data were collected using a structured questionnaire between December 2024 to August 2025.

2.2. Participants and Sampling

The study population consisted of adolescents residing in rural areas of Samut Songkhram Province, Thailand. Administratively, the province is divided into three districts: Mueang Samut Songkhram, Amphawa, and Bang Khonthi. According to official population records, the total adolescent population across these districts was 19,424 individuals.

The minimum required sample size was calculated using the n4Studies Plus program based on the formula for estimating a population proportion [17,18]. Given a total adolescent population of 19,424 individuals, an expected population proportion of 0.50, a margin of error of 0.05, and a 95% confidence level, the minimum required sample size was 383 participants. To account for anticipated non-response, incomplete questionnaires, and potential data loss, the target sample size was increased to 512 participants. Complete data from all 512 participants were included in the final analysis.

A multistage area-selection procedure followed by non-probability participant recruitment was used. First, Samut Songkhram Province was stratified into its three administrative districts. Second, two subdistricts were selected from each district using simple random sampling. Third, two villages were randomly selected from each selected subdistrict. At the final stage, eligible participants within the selected villages were recruited using convenience sampling until the predetermined quota for each area was reached. Because individuals were not randomly selected within villages, the probability of selection at the individual level was unknown. Therefore, although probability-based procedures were used to select subdistricts and villages, the final participant sample should be considered a non-probability sample. Consequently, valid probability-based sample design weights could not be calculated because individual-level selection probabilities were unavailable. Accordingly, sample design weights were not applied, and all analyses were conducted using unweighted data. The resulting estimates should therefore be interpreted as describing the study sample rather than as population-weighted estimates representative of all adolescents in Samut Songkhram Province. This sampling approach may have introduced selection bias and limits the representativeness and generalizability of the findings.

The inclusion criteria were as follows: (1) adolescents aged 15–19 years, consistent with the World Health Organization definition of adolescence as the period from 10 to 19 years of age, who resided in rural areas of Samut Songkhram Province; and (2) adolescents who were willing to participate in the study and cooperate with the researchers. The exclusion criteria were as follows: (1) adolescents who reported having a chronic disease requiring prescription medication and (2) adolescents with a history of psychiatric disorders. These exclusion criteria were prespecified to reduce clinical heterogeneity and the potential influence of ongoing health conditions or treatment on participants’ perceptions, attitudes, and responses to the questionnaire. The study was therefore intended to characterize e-cigarette-related perceptions, attitudes, and behaviors primarily among adolescents without these pre-existing health conditions.

2.3. Instruments

The questionnaire was developed based on a review of the literature on the prevalence of e-cigarette use, perceptions of e-cigarettes, and related factors among adolescents. It consisted of four parts.

Part 1: General information. This section included three items assessing sex, age, and religion.

Part 2: E-cigarette use and related factors. This section assessed e-cigarette use and related environmental factors among the participants and consisted of seven multiple-choice items. The items covered the following issues: (1) having close friends who regularly smoked conventional cigarettes, (2) having parents or caregivers who used e-cigarettes, (3) having ever been persuaded or encouraged by friends to use any type of tobacco product, (4) the perceived ease or difficulty of accessing e-cigarettes, (5) e-cigarette use within the past 30 days, (6) lifetime e-cigarette use, and (7) sources of e-cigarettes. Response options were categorical and varied according to the nature of each item. Items concerning close friends’ smoking, parental or caregiver e-cigarette use, peer persuasion, past-30-day e-cigarette use, and lifetime e-cigarette use were primarily answered using dichotomous response options (e.g., yes/no). Perceived accessibility of e-cigarettes was assessed using ordered categorical response options ranging from difficult to easy, whereas the item concerning sources of e-cigarettes provided categorical response options representing different potential sources of access. The items in this section were treated as categorical variables and were not summed to generate a total score. Instead, they were analyzed individually to describe patterns of e-cigarette use and related factors among the study participants. The prevalence of e-cigarette use was assessed using two key items: (1) e-cigarette use within the past 30 days, which represented current e-cigarette use, and (2) lifetime e-cigarette use, which represented ever e-cigarette use.

Part 3: Perceptions of e-cigarettes. Perceptions of e-cigarettes were assessed using a previously developed questionnaire [19], which was adopted for the present study. The instrument comprised 10 items assessing participants’ perceptions and beliefs regarding the harmfulness of e-cigarettes, toxic substances, nicotine, health effects, effects on people nearby, and e-cigarette use among adolescents. The individual statements, including statements comparing the perceived harmfulness or nicotine exposure of e-cigarettes with other substances or conventional cigarettes, were retained from the previously developed instrument [19] and were used to assess participants’ agreement with the perceptions represented by the questionnaire. These items should therefore be interpreted as perception statements rather than as independently verified biomedical claims or objective tests of factual health knowledge. In the present study, content validity was evaluated by three experts using the Index of Item–Objective Congruence (IOC), and reliability was assessed through pretesting and Cronbach’s alpha. The questionnaire was pretested among 30 individuals with characteristics similar to those of the study participants, and the perception and attitude sections achieved IOC values of 0.82 and 0.91 and Cronbach’s alpha coefficients of 0.89 and 0.94, respectively. Responses were rated on a three-point Likert scale: agree, unsure, and disagree, scored as 3, 2, and 1, respectively. Negatively worded items were reverse-coded before analysis. After recoding, higher scores represented greater endorsement of the risk-oriented perception pattern measured by the instrument and should not be interpreted as indicating objectively more accurate health knowledge. Mean scores were interpreted into three levels: low = 1.00–1.66, moderate = 1.67–2.33, and high = 2.34–3.00.

Part 4: Attitudes toward e-cigarette use. Attitudes toward e-cigarette use were assessed using a 10-item questionnaire covering three domains: cognitive, affective, and behavioral components. Responses were rated on a four-point Likert scale: strongly agree, agree, disagree, and strongly disagree. The questionnaire included both positively and negatively worded statements. Positively worded items were scored from 4 to 1, whereas negatively worded items were reverse-scored from 1 to 4. After reverse scoring, all items were oriented in the same direction, such that higher scores indicated a more protective attitude toward e-cigarette use, reflecting stronger opposition to and lower acceptance of e-cigarette use. Conversely, lower scores indicated a less protective and more accepting attitude toward e-cigarette use. The total score ranged from 10 to 40. Mean scores were used to interpret the level of attitude according to the criteria proposed by Kiess (1989), as follows: 3.26–4.00 = very good, 2.51–3.25 = good, 1.76–2.50 = moderate, and 1.00–1.75 = low. In this study, the terms “very good” and “good” refer to stronger protective attitudes against e-cigarette use rather than more favorable attitudes toward e-cigarettes.

The questionnaire was evaluated for content validity by three experts. Their assessments were used to examine the congruence between the questionnaire items and the research objectives using the Index of Item–Objective Congruence (IOC). Two sections of the questionnaire achieved IOC values of 0.82 and 0.91, respectively. The questionnaire was subsequently pretested with 30 individuals who had characteristics similar to those of the study sample. Internal consistency reliability was assessed using Cronbach’s alpha, yielding coefficients of 0.89 and 0.94, respectively.

2.4. Data Analysis

Data were analyzed using SPSS software version 23.0 (IBM Corp., Armonk, NY, USA). Descriptive statistics, including frequency, percentage, median, arithmetic mean (M), and standard deviation (SD), were used to describe the general characteristics of the participants, e-cigarette use, perceptions of e-cigarettes, and attitudes toward e-cigarette use. Multiple linear regression analysis was performed to examine factors associated with overall attitude scores. The dependent variable was the overall attitude score toward e-cigarette use, while the independent variables were sex, age, religion, and the overall perception score regarding e-cigarettes. Sex was coded as female = 0 and male = 1, with female participants serving as the reference category. Because participants were recruited using convenience sampling at the final stage and individual-level probabilities of selection were therefore unavailable, probability-based sample design weights could not be calculated. Consequently, all descriptive and regression analyses were conducted using unweighted data, and the resulting estimates should be interpreted as pertaining to the study sample rather than as population-weighted estimates for all adolescents in Samut Songkhram Province. The level of statistical significance was set at a two-tailed p-value of less than 0.05.

2.5. Ethical Considerations

The study protocol was approved by the Human Research Ethics Committee of Suan Sunandha Rajabhat University (COA. 2-052-2024). All participants were informed about the study objectives, procedures, potential risks and benefits, confidentiality of data, and their right to withdraw from the study at any time. Written informed consent was obtained from participants aged 18 years or older. For participants younger than 18 years, written parental or guardian consent and adolescent assent were obtained prior to participation.

3. Results

Of the 512 adolescent participants residing in rural areas of Samut Songkhram Province, Thailand, the majority were female (77.5%). The mean age of the participants was 18.46 years (SD = 1.37). Most participants were Buddhist (86.9%). Most participants reported no e-cigarette use within the previous 30 days (94.14%) and no e-cigarette use by their parents or caregivers (90.82%).

Most participants did not have close friends who regularly smoked conventional cigarettes (71.68%) and did not have parents or caregivers who used e-cigarettes (90.82%). Most participants had never been persuaded or encouraged by friends to use any type of tobacco product (77.15%). Regarding accessibility, 34.77% of participants perceived obtaining e-cigarettes as difficult, whereas 26.95% perceived it as easy. The prevalence of current e-cigarette use, defined as use within the past 30 days, was 5.86%, while the prevalence of lifetime e-cigarette use was 18.36%. Among the 94 participants who reported lifetime e-cigarette use, asking for or borrowing e-cigarettes from friends was the most commonly reported source (44.68%; 42/94), followed by online purchases (34.04%; 32/94) (

Table 1. Prevalence of e-cigarette use and related factors among participants (n = 512).

Variables	n	%
1. Do you have close friends who regularly smoke conventional cigarettes?
Yes	145	28.32
No	367	71.68
2. Do your parents or caregivers use e-cigarettes?
Yes	47	9.18
No	465	90.82
3. Have you ever been persuaded or encouraged by friends to use any type of tobacco product?
Yes	117	22.85
No	395	77.15
4. How easy or difficult is it for you to obtain e-cigarettes for use?
Difficult	178	34.77
Somewhat difficult	95	18.55
Somewhat easy	101	19.73
Easy	138	26.95
5. Have you used e-cigarettes in the past 30 days?
Yes	30	5.86
No	482	94.14
6. Have you ever used e-cigarettes in your lifetime?
Yes	94	18.36
No	418	81.64
7. Sources of e-cigarettes among participants who had ever used e-cigarettes (n = 94) a
Convenience stores/shopping malls	12	12.77
Online purchases	32	34.04
Asked someone else to buy them	11	11.70
Asked for or borrowed them from friends	42	44.68
Family members	1	1.06

^a Percentages for sources of e-cigarettes were calculated using the 94 participants who reported lifetime e-cigarette use as the denominator. Multiple responses were allowed; therefore, the sum of frequencies and percentages may exceed 94 and 100%, respectively.

).

The overall perception score among participants was high according to the predefined scoring criteria (M = 2.52, SD = 0.34). This classification reflects participants’ responses to the perception instrument and should not be interpreted as indicating objectively accurate health knowledge. The highest mean score was observed for the statement that e-cigarettes are as harmful as heroin and cocaine (M = 2.96, SD = 0.55), followed by the statements that e-cigarettes are considered a new type of addictive substance and contain toxic substances that are more harmful than those in conventional cigarettes (M = 2.88, SD = 0.39) and that e-cigarettes contribute to the problem of new smokers among youth (M = 2.88, SD = 0.38). These values indicate the degree of participants’ agreement with the respective questionnaire statements rather than confirmation of the biomedical accuracy of the statements themselves. Participants also reported relatively high agreement scores for statements concerning the potential of e-cigarettes to cause serious diseases, such as cancer, emphysema, and heart disease (M = 2.87, SD = 0.40), as well as the presence of harmful substances, such as heavy metals and arsenic (M = 2.76, SD = 0.47). The lowest mean scores were observed for the statements that e-cigarette aerosol is not harmful to people nearby and does not cause heart disease or hypertension (M = 1.78, SD = 0.92) and that e-cigarette use does not lead to cancer (M = 1.78, SD = 0.91). Both items were classified as moderate according to the predefined cut-off criteria (

Table 2. Perceptions of e-cigarettes among participants (n = 512).

Perceptions of E-Cigarettes	M	SD	Level
1. E-cigarettes are considered a new type of addictive substance and contain toxic substances that are more harmful than those in conventional cigarettes.	2.88	0.39	High
2. E-cigarettes are as harmful as heroin and cocaine.	2.96	0.55	High
3. E-cigarette aerosol is not harmful to people nearby and does not cause heart disease or hypertension.	1.78	0.92	Moderate
4. E-cigarettes can cause serious diseases, such as cancer, emphysema, and heart disease.	2.87	0.40	High
5. Using e-cigarettes once is equivalent to smoking 15 conventional cigarettes and contains a higher amount of nicotine than conventional cigarettes.	2.71	0.52	High
6. E-cigarettes contribute to the problem of new smokers among youth.	2.88	0.38	High
7. E-cigarettes contain substances that are harmful to the body, such as heavy metals and arsenic.	2.76	0.47	High
8. In the long term, conventional cigarettes are more harmful than e-cigarettes.	2.48	0.67	High
9. Nicotine is a substance that helps people relax.	2.37	0.78	High
10. E-cigarette use does not lead to cancer.	1.78	0.91	Moderate
Overall	2.52	0.34	High

Note: The items represent participants’ perceptions and beliefs as assessed by the adopted questionnaire [19]. Item-level and overall scores indicate the degree of endorsement of the perception pattern represented by the instrument and should not be interpreted as measures of factual or biomedical accuracy. Negatively worded items were reverse-coded before calculation of the overall score. M = mean; SD = standard deviation.

).

The overall attitude toward e-cigarette use among participants was at a good level (M = 2.73, SD = 0.40), indicating an overall protective attitude against e-cigarette use. When classified by domain, the behavioral component had the highest mean score and was at a good level (M = 3.05, SD = 1.00), followed by the cognitive component, which was also at a good level (M = 2.97, SD = 0.91). In contrast, the affective component was at a moderate level (M = 2.33, SD = 0.56), indicating comparatively weaker protective attitudes in the affective domain (

Table 3. Attitudes toward e-cigarette use by domain among participants (n = 512).

Attitudes Toward E-Cigarette Use	M	SD	Level
Cognitive component	2.97	0.91	Good
Affective component	2.33	0.56	Moderate
Behavioral component	3.05	1.00	Good
Overall	2.73	0.40	Good

).

Additional sex-stratified analyses showed that female participants had significantly higher overall perception scores than male participants (M = 2.55, SD = 0.31 vs. M = 2.38, SD = 0.35; t = −5.026, p < 0.001). However, overall attitude scores did not differ significantly between female and male participants (M = 2.76, SD = 0.39 vs. M = 2.70, SD = 0.38; t = −1.461, p = 0.145). Current e-cigarette use was significantly more prevalent among male participants than female participants (14.78% vs. 3.27%; χ² = 21.409, p < 0.001). Similarly, lifetime e-cigarette use was significantly higher among male participants than female participants (33.04% vs. 14.11%; χ² = 21.336, p < 0.001) (

Table 4. Sex-stratified comparison of e-cigarette use, perceptions, and attitudes among participants (n = 512).

Variable	Male (n = 115)	Female (n = 397)	Test Statistic	p-Value
Overall perception score, M ± SD	2.38 ± 0.35	2.55 ± 0.31	t = −5.026	<0.001
Overall attitude score, M ± SD	2.70 ± 0.38	2.76 ± 0.39	t = −1.461	0.145
Current e-cigarette use, n (%)	17 (14.78)	13 (3.27)	χ2 = 21.409	<0.001
Lifetime e-cigarette use, n (%)	38 (33.04)	56 (14.11)	χ2 = 21.336	<0.001

Note: M = mean; SD = standard deviation. Independent-samples t-tests were used to compare overall perception and attitude scores between male and female participants, whereas Pearson’s chi-square tests were used to compare current and lifetime e-cigarette use. A two-tailed p-value < 0.05 was considered statistically significant.

).

Multiple linear regression analysis indicated that sex and perceptions of e-cigarettes were significantly associated with overall attitudes toward e-cigarette use. After adjustment for age, religion, and perceptions of e-cigarettes, male participants had overall attitude scores that were 0.102 points higher than those of female participants (B = 0.102, β = 0.091, 95% CI: 0.010 to 0.194, p = 0.031). This adjusted association differed in direction from the unadjusted sex-stratified comparison in Table 4, in which male participants had slightly lower mean attitude scores than female participants (M = 2.70 vs. 2.76), although this unadjusted difference was not statistically significant (p = 0.145). The directional change after adjustment may reflect the influence of covariates included in the regression model, particularly perception score, which differed significantly between male and female participants and was independently associated with overall attitude scores. Thus, the positive coefficient for male sex should be interpreted as an adjusted association conditional on the other variables in the model rather than as a direct contradiction of the unadjusted comparison. Perceptions of e-cigarettes showed the strongest association with overall attitude scores (B = 0.421, β = 0.327, 95% CI: 0.309 to 0.533, p < 0.001). Specifically, a one-unit increase in the overall perception score was associated with a 0.421-point increase in the overall attitude score after adjustment for the other variables in the model. Because higher scores on both measures represented more protective orientations toward e-cigarette use, this positive association indicates that participants with more protective perceptions tended to have more protective attitudes toward e-cigarette use. Age (B = 0.012, β = 0.049, p = 0.276) and religion (B = −0.009, β = −0.013, p = 0.764) were not significantly associated with overall attitude scores. The overall regression model was statistically significant, F(4, 507) = 19.46, p < 0.001, and explained 13.3% of the variance in overall attitude scores (R² = 0.133; adjusted R² = 0.126) (

Table 5. Multiple linear regression analysis of factors associated with overall attitudes toward e-cigarette use among participants.

Variables	B	SE	β	t	p-Value	95% CI for B	Tolerance	VIF
Constant	1.421	0.261	—	5.44	<0.001	0.908 to 1.934	—	—
Sex	0.102	0.047	0.091	2.17	0.031	0.010 to 0.194	0.958	1.044
Age	0.012	0.011	0.049	1.09	0.276	−0.010 to 0.034	0.937	1.067
Religion	−0.009	0.030	−0.013	−0.30	0.764	−0.068 to 0.050	0.964	1.037
Perception score	0.421	0.057	0.327	7.39	<0.001	0.309 to 0.533	0.989	1.011

Note: Reference category for sex: female (0); male was coded as 1. Model statistics: R = 0.365, R² = 0.133, adjusted R² = 0.126, F(4, 507) = 19.46, p < 0.001., and Durbin–Watson = 1.866.

).

4. Discussion

4.1. Prevalence of E-Cigarette Use

This study investigated the prevalence of e-cigarette use, perceptions of e-cigarettes, attitudes toward e-cigarette use, and associated factors among adolescents in rural communities in Samut Songkhram Province, Thailand. The prevalence of current e-cigarette use, defined as use within the past 30 days, was 5.86%, while lifetime e-cigarette use was 18.36%. The prevalence of current use in this study was lower than the 17.6% reported among Thai students aged 13–15 years in the Thailand Global Youth Tobacco Survey 2022 [9,20], but higher than the 3.7% current use reported among Thai seventh-grade students in a previous national study [21]. Similarly, the lifetime prevalence in the present study was higher than the 7.2% ever-use prevalence reported by Patanavanich et al. [21]. These differences may be explained by variation in age group, study setting, sampling procedures, survey period, and adolescents’ exposure to e-cigarette products through peer and online networks. Although most participants did not currently use e-cigarettes, the proportion reporting lifetime use suggests that experimentation with e-cigarettes exists among adolescents in rural communities. This finding is important because adolescence is a critical developmental period, and nicotine exposure during this stage may affect brain development, attention, learning, mood, and impulse control [22,23]. The World Health Organization also recognizes past-30-day e-cigarette use among adolescents as an important public health indicator, as adolescent use of nicotine-containing e-cigarettes is associated with nicotine dependence, respiratory conditions, poor oral health, negative mental health outcomes, and possible later tobacco use [18]. Therefore, even a relatively low level of current use should be considered a public health concern, particularly when lifetime experimentation is evident.

Social and environmental influences appeared to play an important role in adolescents’ e-cigarette-related behaviors. In this study, 28.32% of participants had close friends who regularly smoked conventional cigarettes, and 22.85% had been persuaded or encouraged by friends to use tobacco products. In addition, among reported sources of e-cigarettes, asking for or borrowing them from friends was the most common source. These findings are consistent with previous evidence from Thailand showing that peer e-cigarette use, parental e-cigarette use, peer approval of smoking, and lack of awareness of e-cigarette risks were significantly associated with current e-cigarette use among youth [21]. A recent study among adolescents in a rural Thai community also found that peer influence, prior encouragement, perceived social acceptance, and misconceptions about e-cigarettes were associated with e-cigarette use tendency [11,24]. These findings suggest that prevention programs should address peer influence, refusal skills, and social norms related to e-cigarette use. At the school level, school administrators and relevant education authorities should integrate e-cigarette prevention into existing tobacco-free school policies, provide age-appropriate refusal-skills training, establish mechanisms for students to confidentially report e-cigarette sales or promotion around schools, and engage parents in recognizing and responding to peer-related risks.

Accessibility to e-cigarettes remains another important issue. Although Thailand has regulatory restrictions on e-cigarettes, 26.95% of participants perceived that obtaining e-cigarettes was easy, and online purchases were reported as the second most common source among users. This indicates that adolescents may still access e-cigarette products through informal peer networks and digital channels. The Thailand Global Youth Tobacco Survey 2022 also showed high exposure to tobacco and e-cigarette-related environments among students, including current e-cigarette use and exposure to tobacco-related advertising and promotion [11]. Thailand currently bans the manufacture, import, and sale of e-cigarettes and e-cigarette liquids [25]. However, the findings of the present study suggest that legal restrictions alone may not be sufficient to prevent adolescent access. Enforcement responsibilities should therefore be clearly coordinated across agencies. The Office of the Consumer Protection Board and law-enforcement authorities should strengthen surveillance and investigation of illegal retail and online sales, while the Customs Department should continue efforts to intercept prohibited imports. The Department of Disease Control, provincial tobacco-control mechanisms, and local public health authorities can support surveillance, risk communication, and coordination with schools and communities. Online platform operators should also cooperate with competent authorities in identifying and removing illegal e-cigarette listings and advertisements. Such coordinated action is particularly important in rural settings, where informal distribution networks and online transactions may be less visible.

4.2. Perceptions of E-Cigarettes

The overall perception score among participants was high according to the predefined scoring criteria. However, this score represents participants’ degree of endorsement of the perception statements included in the adopted instrument and should not be interpreted as a direct measure of the factual accuracy of their health knowledge. In particular, some questionnaire items included strong comparative statements regarding the harmfulness or nicotine exposure associated with e-cigarettes; these statements were retained from the previously developed instrument [19] and were analyzed as indicators of participants’ perceptions rather than as independently verified biomedical claims. Participants reported relatively high agreement with several risk-oriented statements concerning the harmful effects of e-cigarettes, including their potential to cause serious diseases and their role in creating new smokers among youth. However, lower scores were found for negatively worded items, such as the statements that e-cigarette aerosol is not harmful to people nearby and that e-cigarette use does not lead to cancer. The variation across individual items suggests that participants’ perceptions of e-cigarette-related risks were not uniform and that particular beliefs may warrant further investigation. This is important because e-cigarette aerosol may contain nicotine, cancer-causing chemicals, heavy metals, volatile organic compounds, and fine particles that can be inhaled deeply into the lungs [23]. Therefore, health education should provide accurate and evidence-based information about e-cigarette harms, including secondhand aerosol exposure, nicotine addiction, respiratory and cardiovascular effects, and potential long-term health risks [16]. Rather than relying solely on general awareness campaigns, schools and local health services should provide targeted risk-communication activities addressing the specific perceptions identified in this study. Teachers, school health personnel, public health professionals, and parents should reinforce consistent, evidence-based messages regarding nicotine addiction, secondhand aerosol exposure, and potential long-term health consequences.

4.3. Attitudes Toward E-Cigarette Use

The overall attitude toward e-cigarette use among participants was at a good level. When classified by domain, the behavioral and cognitive components were at good levels, whereas the affective component was at a moderate level. This suggests that although participants may have appropriate knowledge and behavioral tendencies related to e-cigarette use, emotional responses, curiosity, perceived attractiveness, and social acceptance may remain important concerns. Previous studies have shown that attitudes, perceived risks, and social influences are associated with e-cigarette use or the decision to use e-cigarettes among young people [24,26]. Therefore, interventions should not focus only on knowledge improvement but should also address affective and social components, including curiosity, peer acceptance, perceived modernity, and the belief that e-cigarettes are less harmful or socially acceptable [27]. School- and community-based interventions should therefore incorporate peer-led activities, refusal-skills training, media-literacy education, and discussion of marketing strategies that portray e-cigarettes as modern, attractive, or socially acceptable. Youth leaders and peer networks may be particularly useful in changing perceived social norms and reducing the attractiveness of e-cigarette use.

4.4. Factors Associated with Attitudes Toward E-Cigarette Use

The multiple linear regression analysis showed that sex and perceptions of e-cigarettes were significantly associated with overall attitude scores. Because higher attitude scores represented more protective attitudes toward e-cigarette use, the regression coefficients were interpreted accordingly. Male participants had, on average, overall attitude scores that were 0.102 points higher than those of female participants after adjustment for age, religion, and perceptions of e-cigarettes (B = 0.102, β = 0.091, 95% CI: 0.010 to 0.194, p = 0.031), indicating slightly more protective attitudes toward e-cigarette use among male participants. Notably, this adjusted association differed in direction from the unadjusted comparison, in which male participants had slightly lower mean attitude scores than female participants (M = 2.70 vs. 2.76), although the unadjusted difference was not statistically significant (p = 0.145). This directional change may reflect the influence of covariate adjustment in the multivariable model, particularly the perception score. Female participants had significantly higher perception scores than male participants, while perception score was independently and positively associated with overall attitude scores. Therefore, the positive coefficient for male sex in the regression model should be interpreted as an adjusted association after accounting for perception score, age, and religion, rather than as directly equivalent to the unadjusted difference between male and female participants. Perceptions of e-cigarettes were positively associated with overall attitude scores (B = 0.421, β = 0.327, 95% CI: 0.309 to 0.533, p < 0.001). Because higher scores on both the perception and attitude measures represented more protective orientations toward e-cigarette use, this positive association indicates that adolescents with more protective perceptions of e-cigarettes tended to have more protective attitudes toward their use. This finding suggests that greater recognition of e-cigarette-related risks and harms may be associated with stronger opposition to e-cigarette use. Perceptions of e-cigarettes showed the strongest association with overall attitude scores among the variables included in the model. These findings suggest that adolescents’ perceptions and attitudes toward e-cigarettes are significantly associated; however, the regression model explained 13.3% of the variance in overall attitude scores (R² = 0.133; adjusted R² = 0.126), indicating that other social, behavioral, and environmental factors may also contribute to adolescents’ attitudes toward e-cigarette use. Furthermore, the observed associations should be interpreted cautiously because the cross-sectional design does not permit causal inference [28].

The findings of this study have several public health implications. First, at the school level, school administrators and relevant education authorities should strengthen tobacco- and e-cigarette-free school policies through age-appropriate health education, peer-led prevention activities, refusal-skills training, media literacy, parental engagement, and confidential mechanisms for reporting e-cigarette sales or promotion in and around schools. School-based activities should address not only knowledge but also the affective and social influences identified in this study, including curiosity, peer acceptance, perceived attractiveness, and misconceptions regarding harm. Given the positive association between protective perceptions and protective attitudes observed in the revised analysis, prevention activities should also strengthen adolescents’ accurate perceptions of e-cigarette-related harms while reinforcing attitudes that discourage initiation and continued use. Second, at the community level, local public health authorities, provincial tobacco-control mechanisms, community leaders, parents, and youth networks should establish coordinated surveillance and prevention activities. These activities may include identifying locations or channels through which adolescents obtain e-cigarettes, reporting suspected illegal sales, conducting community risk-communication campaigns, and providing appropriate referral or cessation support for adolescents who have already initiated nicotine use. Third, enforcement responsibilities should be clearly differentiated among competent government agencies. The Office of the Consumer Protection Board and law-enforcement authorities should strengthen detection and investigation of illegal retail and online sales, the Customs Department should continue to prevent prohibited e-cigarette imports, and the Department of Disease Control together with provincial and local public health authorities should support tobacco-control surveillance, risk communication, and multisectoral coordination. Cooperation with online platform operators is also needed to identify and remove illegal advertisements and product listings that facilitate youth access.

These recommendations can be considered within the broader implementation framework of the WHO Framework Convention on Tobacco Control and the WHO MPOWER measures [29,30]. In particular, surveillance of adolescent use and digital promotion is consistent with monitoring tobacco and nicotine use; school and community risk communication supports warning about health risks; maintaining tobacco- and e-cigarette-free environments supports protection from exposure; access to appropriate cessation support is relevant for adolescents already using nicotine; and coordinated action against prohibited promotion and sales supports effective enforcement. Civil society should complement, rather than replace, statutory enforcement by government authorities. Civil society organizations, tobacco-control networks, parent groups, community organizations, and youth groups can monitor emerging patterns of use and promotion, document suspected violations, report illegal retail or online sales to the competent authorities, conduct independent advocacy, support school- and community-based education, and promote public accountability for implementation of existing policies. This collaborative approach is consistent with the multisectoral and whole-of-society principles underlying WHO FCTC implementation. Finally, enforcement of existing regulations should be combined with adolescent-friendly risk communication because global public health agencies have emphasized the need for urgent action to protect children and adolescents from e-cigarette uptake [30]. An additional limitation concerns the exclusion of adolescents with chronic diseases requiring prescription medication and those with a history of psychiatric disorders. Although these criteria were prespecified to reduce clinical heterogeneity and the potential influence of ongoing health conditions or treatment on questionnaire responses, they may have introduced selection bias. Adolescents with chronic or psychiatric conditions may differ from those included in the study in terms of health perceptions, psychosocial characteristics, nicotine-related behaviors, or susceptibility to e-cigarette use. Consequently, the prevalence estimates and observed associations in this study may not be generalizable to adolescents with these conditions. Future studies should consider including these populations and examining health-condition status as a potential covariate or effect modifier.

5. Conclusions

This study provides context-specific evidence on e-cigarette use, perceptions, and attitudes among adolescents recruited from selected rural communities in Samut Songkhram Province, Thailand. Current e-cigarette use was reported by 5.86% of participants, while 18.36% had used e-cigarettes at least once, indicating that experimentation remains an important public health concern within the study population despite national restrictions. Although participants generally demonstrated protective perceptions and attitudes toward e-cigarette use, the affective component of attitude remained at a moderate level, suggesting that curiosity, perceived attractiveness, and social acceptance may still influence e-cigarette-related decisions. Sex and perceptions of e-cigarettes were significantly associated with overall attitude scores; however, the relatively modest variance explained by the regression model indicates that additional social, behavioral, and environmental factors should be investigated. These findings may inform context-specific school, family, community, and health-system interventions that address peer influence, strengthen refusal skills, correct misconceptions about nicotine addiction and health risks, and reduce access through online platforms and informal social networks. Nevertheless, causal inference and broad generalization are limited by the cross-sectional design and convenience sampling at the final recruitment stage. The exclusion of adolescents with chronic diseases requiring prescription medication and those with a history of psychiatric disorders may also have introduced selection bias and may further limit the generalizability of the findings to adolescents with these health conditions. Future longitudinal studies using probability-based sampling and validated measures are needed to examine changes in e-cigarette use and evaluate preventive interventions in rural settings. In addition, because individual-level selection probabilities were unavailable, sample design weights could not be applied; therefore, the reported prevalence estimates are unweighted and should not be interpreted as population-representative estimates for all adolescents in Samut Songkhram Province.