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Assessing the Impact of a Health Education Anti-smoking Program for Students: A Follow-Up Investigation

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Abstract
In this follow-up study, we aimed to assess the effectiveness of the “I do not smoke, I exercise”, anti-smoking preventive health education program. The program was based on the Theory of Planned Behavior supplemented with life-skills teaching and targeted at high school students. The intervention comprised ten one-hour online sessions, administered by physical education instructors. The study cohort comprised 222 students (109 boys, 113 girls) from 11 secondary schools, with an average age of 16.42 ± 1.36 years. Data collection involved pre- and post-intervention self-assessment questionnaires. The examined variables included attitudes towards smoking, intention to smoke, subjective norm, perceived behavioral control (PBC), knowledge about smoking, smoking behavior, exercise behavior, attitudes toward the program's implementation, and satisfaction with the program. Separate paired samples t-test revealed a significant improvement in students' knowledge about smoking, perceived behavioral control, and overall program satisfaction following the intervention. However, no significant changes were observed in the remaining variables. These findings suggest that the health education smoking prevention intervention incorporates techniques and strategies that influence the Perceived Behavioral Control variable, emphasizing students' strong interest in educationally theorized programs integrating technology into their design. Future studies should consider further examination of tobacco control strategies within the high school context.
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Subject: Public Health and Healthcare  -   Health Policy and Services

1. Introduction

Tobacco constituted a substantial portion of the worldwide disease burden in 2019, accounting for 15.4% of all deaths (approximately 8.71 million) [1], primarily attributed to non-communicable diseases associated with smoking [2]. The existing literature provides substantial evidence that cigarette smoking is associated with a broad spectrum of diseases [3], notably lung cancer and other types of cancer [4], chronic obstructive pulmonary disease [4,5], and types of cardiovascular diseases [6]. Given that smoking leads to the death of approximately half of its consumers [7], preventing the initiation of smoking and implementing targeted interventions implies substantial long-term health benefits [8].
Healthy behaviors established in early life tend to persist into adulthood [9]. Smoking behavior typically takes root during adolescence, with the majority of adolescents trying their first cigarette or becoming addicted before reaching the age of 18. [10,11]. For example, over 80 percent, of adult heavy smokers were heavy smokers during adolescence [12]. Thus, interventions aimed at preventing unhealthy behaviors among youth, particularly smoking, have strategically focused on the school environment [13]. There is empirical evidence confirming the efficacy of integrated school health approaches in reducing rates of various adolescents’ health behaviors, including smoking [14,15,16]. As illustrated by a comprehensive examination of systematic reviews conducted by Das et al. [17], it was indicated that school-based preventive initiatives and intensive family-centered interventions, have shown effectiveness in reducing smoking behaviors.
In recent years, there has been a substantial surge in internet accessibility and computer utilization, notably among the younger demographic, wherein a significant portion of their time is allocated toward computer-based activities [18]. Web-based health education programs have been shown a positive impact on children’s and adolescents’ health behaviors [19,20]. When considering smoking prevention initiatives, the results are promising [21,22]
Ajzen's [23], Theory of Planned Behavior (TPB), attempts to elucidate the rationale behind human behavior by describing individuals' actions in a systematic framework. The TPB postulates that the intention to perform a behavior, that is, an individual's motivation to act, serves as the actual precedence for behavior. The intention to perform a behavior is influenced by three elements, attitudes, perceived behavioral control, and subjective norms. An individual’s attitude towards the behavior, that is, the evaluation of the behavior (positive or negative), the perceived impact of influential individuals on behavior and their adoption of it, subjective norm, and the perceived capability to engage in the behavior, which stands for PBC, which also impacts directly the behavior [23,24].
Ajzen [24] emphasizes the importance of incorporating a theory in interventions targeting smoking behavior, as the belief in one's capacity to influence behavior significantly impacts both intentions and actual actions. Steinmetz et al. [25], found that interventions based on the TPB had a notable positive impact on changing various health behaviors and related factors, according to their meta-analysis. Recent studies have effectively used the TPB to predict the link between smoking behavior and TPB’s variables [26,27]. Moreover, it has been effectively used to design, implement, and evaluate theory-based, behavior-change antismoking interventions [28,29].
Lareyre et al. [30], after conducting a systematic review of TPB-based interventions for smoking behavior, found that the percentage of studies reporting a significant impact on smoking behavior, intention, attitude, subjective norm, or perceived behavioral control ranged from 42% to 50%. For example, results of studies applying health education behavior change interventions utilizing the TPB, intending to prevent smoking among adolescents, indicate significant effects on the TPB constructs post-intervention [29,31,32,33]
Health promotion interventions have the potential to impact various dimensions of the self, including cognitive, behavioral, and motivational aspects, on an individual level [34]. Health education was initially defined as the capacity to comprehend, assess, and utilize health information to make informed decisions about one's health [35]. Systematic reviews highlight the effectiveness of school-based smoking prevention programs for children and adolescents, emphasizing a combination of social competence and social influences curricula in preventing smoking initiation [13,36].
Long-term research has demonstrated the positive effects of life skills teaching on various substance use behaviors, including smoking [37]. In what manner do life skills contribute to the well-being of adolescents? They do so by furnishing them with the requisite knowledge, positive attitudes, and values necessary for a healthy future [38]. Skills-based health education involves specifying knowledge, attitudes, and life skills to guide young individuals in adopting targeted behaviors and meeting outlined objectives, encompassing psychosocial competencies and interpersonal abilities crucial for effective decision-making, problem-solving, critical thinking, communication, relationship-building, empathy, and productive life management [39]. The incorporation of life skills into smoking reduction programs, whether delivered through cognitive behavior, or life skills modalities and implemented within a school-community framework, has demonstrated the potential to enhance adolescent smoking reduction rates [40,41]. As an illustration, Velasco et al. [42], conducted a drug abuse prevention program for Italian adolescents, employing a life skills-based approach. Encouragingly, this intervention demonstrated positive effects, not only in terms of reducing substance use behavior, and associated variables, but also in bolstering overarching protective factors such as normative beliefs, life skills, and various psychosocial outcomes. Zhao et al. [33], implemented and evaluated a brief antismoking intervention, based on extended TPB and assisted by life-skills, that targeted high school students. Improved attitudes towards smoking and PBC were observed, but no significant improvements in intentions, subjective norms, and smoking behavior. The authors suggested a focus on sessions that target attitudes.
Substantial evidence supports the benefits of exercise as an effective option for alleviating tobacco symptoms of withdrawal and urges [43,44]. Experimental research has examined the acute and long-term effects of exercise on smoking behavior, offering valuable information for developing antismoking interventions [45,46,47]. Literature findings demonstrate that adolescents can effectively improve multiple health behaviors, with positive changes in both activity levels and smoking cessation [48,49]. On top of these, interventions grounded in the TPB have demonstrated effectiveness in promoting physical activity behavior when compared to interventions based on other theories [50,51].
In sum, the above evidence encourages the development and implementation of a theory-based, school, health education program, targeting smoking prevention among adolescents. This article represents a follow-up study building upon prior research conducted by Kolovelonis et al. [29]. This follow-up study examines the effectiveness of the “I do not smoke, I exercise” web-based program, targeting a healthier lifestyle and smoking prevention among secondary students. In this extended version tailored for secondary high school students, we utilized a new web platform, updated educational materials, and added two new sessions, building upon the study conducted by Kolovelonis et al. [29]. The program now features ten sessions specifically designed for adolescents, with the hypothesis of positive effects on the examined variables.

2. Materials and Methods

2.1. Participants

Eleven physical education instructors voluntarily implemented the program, with both teachers and students participating in the study of their own accord. Eleven secondary schools, and 222 students (109 boys and 113 girls; Mage: 16.42 ± 1.36 years), voluntarily participated in the school-based intervention program “I do not smoke, I exercise”. The data collection period was between 21/02/2018- 4/1/2021.

2.2. Instruments

The assessment scales utilized in this study were grounded in the TPB model, encompassing measures of attitudes towards smoking, intention to smoke, subjective norm, and perceived behavioral control over smoking behavior, as outlined by Ajzen [24,52]. Exercise behavior, attitudes toward the program, and satisfaction with the program's content were also assessed. Furthermore, similar assessment tools have been employed to gauge the effectiveness and suitability of health education programs targeting behaviors like nutrition [45].
Attitudes towards smoking. Attitudes towards smoking behavior were evaluated using a set of five questions “For me smoking is…” and the answer ranged in a 7-point bipolar adjective scale good-bad, silly-clever, healthy-unhealthy, pleasant-unpleasant, useful-unuseful. The responses were recorded on a 7-point bipolar adjective scale, encompassing dimensions such as good-bad, silly-clever, healthy-unhealthy, pleasant-unpleasant, and useful-unuseful.
Intention to smoke. The assessment of intention to smoke involved the inclusion of two specific items (e.g., “I plan to smoke in the coming months” and “I will try to smoke in the coming months”). Participants rated their responses on a 7-point Likert scale, ranging from 1 (signifying strong disagreement) to 7 (signifying strong agreement).
Subjective norm. Subjective norm assessment involved the use of two items: “People important in my life believe that I will smoke in the next months” and “Great people in my life will like me to smoke in the next months”. Participants indicated their responses on a 7-point Likert scale, ranging from 1 (indicating strong disagreement) to 7 (indicating strong agreement).
Perceived behavioral control (PBC). Participants' perceived competence in exerting control over their smoking behavior was evaluated using two items: “It's entirely up to me whether I will smoke in the coming months” and “It is my responsibility if I smoke in the coming months”. Responses were recorded on a 7-point Likert scale, ranging from 1 (strongly agree) to 7 (strongly disagree).
Attitudes towards the program implementation. Participants were asked to provide their responses within the context of the prompt “For me, the program is...” using a 7-point Likert scale, which included bipolar word pairs such as good-bad, pleasant-unpleasant, attractive-unattractive, and useful-useless.
Satisfaction with the program. Participants' satisfaction with the program was assessed post-intervention, using six items (“Using this program via computer and the internet was easy”, “Using the computer and the internet through this program was easy”, “I prefer to learn about such issues via the computer and the internet, rather than from a book”, “I am satisfied with the texts in this program”, “I am satisfied with the design of this program”, “I am satisfied with the images I saw in the program”). Responses were recorded on a 7-point Likert scale, ranging from 1 (indicating complete disagreement) to 7 (indicating complete agreement).
Knowledge about smoking. A 14-item questionnaire was developed to assess participants' knowledge regarding smoking, specifically focusing on the health consequences associated with smoking behavior. Example items included statements like “Smoking brings difficulty breathing when exercising”, “Smoking hardens and destroys arteries”, and “Smoking causes cancer”. The questionnaire has been modified to the program's sessions. It covered the dangers of smoke inhalation, nicotine addiction, statistics regarding the prevalence of smoking in Greece compared to Europe, and causes that lead youth to start smoking. Participants responded to the questions using a 3-point scale (0 = no, 1 = I am not sure, 2 = yes), with scores from 0 to 28.
Exercise behavior was assessed with the question: “In your free time, how often do you engage in physical activity that induces sweating or heavy breathing?” on a 7-point scale (0 = never, 6 = every day) [53].
Smoking behavior was evaluated using an assortment of five yes-or-no questions based on a questionnaire used in previous research [54]. These questions gradually examined a participant's smoking history, starting with “Have you ever tried smoking, even just 1 or 2 puffs?”, “Have you ever smoked 1 or more cigarettes every day for a whole month (30 days)?”, “Have you smoked even one day in the past month (30 days)?”, “Have you smoked on 20 or more days in the last month?” and concluding with “Do you smoke more than 10 cigarettes per day?”.

2.3. Procedures

All participating students and their parents/guardians provided their consent to partake in the study. The program's materials and assessments were administered through the website http://research.pe.uth.gr/health/. Teachers who expressed interest in implementing the program completed a participation form and were subsequently provided access to the program's materials. Students utilized the usernames provided for pre-intervention questionnaires and reused them for post-intervention assessments. Teachers who successfully completed all sessions and encouraged student participation were awarded a certificate of attendance, in addition to receiving the evaluation results. The program offered downloadable materials featuring instructions, relevant sources, presentations, activities, games, teaching strategies, project work topics, pertinent websites, and more. It comprised ten one-hour sessions, as outlined in Table 1.

2.4. Data Analysis

Descriptive statistics (means, standards deviations) and reliability index (Cronbach’s α) were calculated for both measurements. Then, separate paired samples t-tests with Cohen’s d effect sizes were calculated in order to examine possible differences on the dependent variables (attitudes toward smoking, intention to smoke, subjective norms, PBC, attitudes toward the program’s implementation, smoking knowledge, smoking behavior and exercise behavior) between pre and post intervention. All statistical analyses were conducted with IBM SPSS v 26.0. The p value was set at .05.

3. Results

Results from the paired samples t-tests showed significant differences on students’ PBC (t220 = -2.166, p < .05, d = .15), and knowledge about smoking (t217 = -5.605, p < .001, d = .38) between pre and post-intervention measures. Students reported higher scores on PBC and knowledge about smoking after the implementation of the “I do not smoke, I exercise” health education program compared to their pre-intervention measure (Table 2). Students also reported that they were very satisfied with the implementation of the “I do not smoke, I exercise” health education program. In contrast, there were no significant differences on students’ attitudes towards smoking (t221 = 1.418, p = .158), intention to smoke (t221 = .534, p = .594), subjective norm (t221 = .193, p = .847), attitudes toward the program’s implementation (t221 = -.975, p = .331), smoking behavior (t220 = -.907, p = .365), and exercise behavior (t221 = -1.232, p = .219).

4. Discussion

The current study aimed to assess the effectiveness of a school-based health education program focused on preventing smoking among adolescents. Overall, the implementation of the program was deemed satisfactory. The findings highlighted that the most substantial impact of the program, as indicated by effect sizes, was the enhancement of students’ knowledge of smoking behavior and the PBC variable. In accordance with previous research findings, these results demonstrate that health education programs exert a notable influence on improving students’ knowledge [28,29,45]. Certainly, targeted education has been shown to enhance individual awareness and proficiency [55]. There is some evidence, that improving health literacy, through health education, can be advantageous in preventing smoking, aiding in smoking cessation, and preventing smoking relapse, along with addressing associated behaviors and issues [56]. However, a mere increase in knowledge does not necessarily translate to behavior change [57], although Sorensen et al. [58], have found that an increase in knowledge aids in fostering positive attitudes towards abstaining from smoking.
The program also demonstrated a notable impact on the PBC variable, a finding consistent with previous studies [29,33,59]. This suggests that the incorporation of life skills and the use of behavior change techniques, such as behavioral practice and rehearsal, enhanced students' PBC and self-efficacy [60]. Relevant research demonstrated the significance of the PBC variable on students smoking behavior [61,62].
Consistent with the findings of Kolovelonis et al. [29] regarding secondary students, no improvements were observed in students' attitudes toward smoking, intention to smoke, and subjective norms post-intervention. However, significant changes were noted in perceived behavioral control and knowledge, similar to the outcomes of the present study. This might be attributed to the existing weak pre-intervention attitudes toward smoking. Applying the intervention to a targeted group, consisting rigorously of smokers or non-smokers, could lead to more explicit inferences. Concerning the subjective norms variable, Zhao et al. [63], found that the subjective norm emerged as the most resistant construct to antismoking intervention efforts. Also, a previous study (Zhao et al., [33], suggested that displayed a limited association with the intention variable. Home environment, modeling, and mass media have a substantial effect on forming youth’s smoking behavior [64,65]. Thus, future studies should consider influencing this context, targeting students' peers and families.
Smoking behavior and exercise behavior remained unaffected post-intervention. Results are in line with previous studies [29,33] which indicated that their intervention failed to change smoking behavior. Davey et al. [66], noted that subjective norm exerts a potent influence on intention, and the challenge of altering this norm may be a factor contributing to the modest changes observed in smoking behavior. An alternative interpretation could be that students initially reported low levels of smoking, which may have posed a challenge in detecting significant changes in the post-test results. Nevertheless, it is noteworthy that a recent systematic review by Lareyre et al. [30] revealed that none of the studies focusing on smoking prevention provided results on smoking behavior. Furthermore, exercise behavior showed no significant changes in the post-test, aligning with the earlier study by Kolovelonis et al. [29]. This limited impact could be attributed to the high levels of exercise behavior reported at the baseline.
In summary, students overwhelmingly welcomed the program, signifying a substantial influence on their satisfaction levels. This aligns with findings from comparable studies, highlighting students' keen interest in educationally theorized programs. Moreover, research outcomes [28,29,45] indicate that integrating technology into health education program delivery serves as an effective method for augmenting the quality and effectiveness of these endeavors.
Regarding limitations of the study, the absence of control group should be noted. Furthermore, these differences among aspects of TPB may attribute to sample differences (different age groups and school contexts). It appears that interventions aimed at the adolescent population should be addressed distinctly, as these findings pertain specifically to this demographic. Future studies should contemplate the development of age-specific interventions. The implementation of the program in different ages and groups may give more efficient results. The employment of self-assessment questionnaires and the implementation fidelity which is always an issue in this kind of online material training and intervention programs [67], represent two potential constraints that could exert an influence on the outcomes. Future school education programs should consider the participation of peers and family and assess the impact of life skills on students, employed in the intervention.

5. Conclusions

In general, this intervention demonstrated limited effectiveness in positively influencing participants' smoking behavior and its immediate cognitive precursors, such as attitudes and intentions. Favorable outcomes were observed only in participants' knowledge, perceived behavioral control (PBC), and overall program satisfaction. These results carry significant implications for smoking prevention initiatives within the context of Greece. This study underscores the imperative for additional scrutiny of tobacco control strategies within the high school settings of Greece.

Author Contributions

Conceptualization, M.H. and Y.T.; methodology, Y.T. and M.H; validation, Y.T., and M.H.; formal analysis, C.K. and I.M.; investigation, M.A.; resources, M.H and Y.T.; data curation, M.A.; C.K.; writing—original draft preparation, M.A.; writing—review and editing, M.A.; M.H. and Y.T.; supervision, Y.T.; project administration, Y.T. All authors have read and agreed to the published version of the manuscript.

Funding

Please add: The present study is a part of a doctoral thesis, which was co-financed by Greece and the European Union (European Social Fund-ESF) through the Operational Programme «Human Resources Development, Education and Lifelong Learning» in the context of the Act “Enhancing Human Resources Research Potential by undertaking a Doctoral Research” Sub-action 2: IKY Scholarship Programme for PhD candidates in the Greek Universities» (MIS 5113934).

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Ethics Committee of the Department of Physical Education and Sport Science, University of Thessaly (protocol code 653, 12 December 2012).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data underlying the results presented in the study are part of a research program and are available on request to the corresponding author (Y.T.; theodorakis@uth.gr).

Acknowledgements

We would like to thank all volunteered teachers and their students participating in this program.

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

References

  1. GBD 2019 Risk Factors Collaborators. Global burden of 87 risk factors in 204 countries and territories, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet 2020, 396(10258), 1223–1249. [CrossRef] [PubMed]
  2. World Health Organization. Available online: https://www.who.int/news-room/fact-sheets/detail/noncommunicable-diseases (accessed on 16 September 2023).
  3. Larsson, S.C.; Burgess, S. Appraising the Causal Role of Smoking in Multiple Diseases: A Systematic Review and Meta-Analysis of Mendelian Randomization Studies. eBioMedicine 2022, 82, 104154. [Google Scholar] [CrossRef] [PubMed]
  4. Dai, X.; Gil, G.F.; Reitsma, M.B.; Ahmad, N.S.; Anderson, J.A.; Bisignano, C.; Carr, S.; Feldman, R.; Hay, S.I.; He, J.; et al. Health Effects Associated with Smoking: A Burden of Proof Study. Nature Medicine 2022, 28, 2045–2055. [Google Scholar] [CrossRef] [PubMed]
  5. Christenson, S.A.; Smith, B.M.; Bafadhel, M.; Putcha, N. Chronic Obstructive Pulmonary Disease. The Lancet 2022, 399. [Google Scholar] [CrossRef]
  6. Nowbar, A.N.; Gitto, M.; Howard, J.P.; Francis, D.P.; Al-Lamee, R. Mortality from Ischemic Heart Disease. Circulation: Cardiovascular Quality and Outcomes 2019, 12. [Google Scholar] [CrossRef]
  7. WHO Global Tobacco Report 2021 Available online: https://www.who.int/teams/health-promotion/tobacco-control/global-tobacco-report-2021.
  8. Roth, G.A.; Mensah, G.A.; Johnson, C.O.; Addolorato, G.; Ammirati, E.; Baddour, L.M.; Barengo, N.C.; Beaton, A.Z.; Benjamin, E.J.; Benziger, C.P.; et al. Global Burden of Cardiovascular Diseases and Risk Factors, 1990-2019: Update from the GBD 2019 Study. Journal of the American College of Cardiology 2020, 76, 2982–3021. [Google Scholar] [CrossRef]
  9. Sawyer, S.M.; Afifi, R.A.; Bearinger, L.H.; Blakemore, S.-J.; Dick, B.; Ezeh, A.C.; Patton, G.C. Adolescence: A Foundation for Future Health. The Lancet 2012, 379, 1630–1640. [Google Scholar] [CrossRef]
  10. Hu, L.; Li, L.; Ji, J. Machine Learning to Identify and Understand Key Factors for Provider-Patient Discussions about Smoking. Preventive Medicine Reports 2020, 20, 101238. [Google Scholar] [CrossRef]
  11. Miech, R.; Patrick, M.E.; O’Malley, P.M.; Johnston, L.D. E-Cigarette Use as a Predictor of Cigarette Smoking: Results from a 1-Year Follow-up of a National Sample of 12th Grade Students. Tobacco Control 2017, 26, e106–e111. [Google Scholar] [CrossRef]
  12. Wiener, J.; Biondic, D.; Grimbos, T.; Herbert, M. Parenting Stress of Parents of Adolescents with Attention-Deficit Hyperactivity Disorder. Journal of Abnormal Child Psychology 2015, 44, 561–574. [Google Scholar] [CrossRef]
  13. Thomas, R.E.; McLellan, J.; Perera, R. School-Based Programmes for Preventing Smoking. Evidence-Based Child Health: A Cochrane Review Journal 2013, 8, 1616–2040. [Google Scholar] [CrossRef]
  14. Sevil, J.; Sánchez-Miguel, P.A.; Pulido, J.J.; Práxedes, A.; Sánchez-Oliva, D. Motivation and Physical Activity: Differences between High School and University Students in Spain. Perceptual and Motor Skills 2018, 125, 894–907. [Google Scholar] [CrossRef] [PubMed]
  15. Shackleton, N.; Jamal, F.; Viner, R.M.; Dickson, K.; Patton, G.; Bonell, C. School-Based Interventions Going beyond Health Education to Promote Adolescent Health: Systematic Review of Reviews. Journal of Adolescent Health 2016, 58, 382–396. [Google Scholar] [CrossRef] [PubMed]
  16. Mélard, N.; Grard, A.; Robert, P.-O.; Kuipers, M.A.G.; Schreuders, M.; Rimpelä, A.H.; Leão, T.; Hoffmann, L.; Richter, M.; Kunst, A.E.; et al. School Tobacco Policies and Adolescent Smoking in Six European Cities in 2013 and 2016: A School-Level Longitudinal Study. Preventive Medicine 2020, 138, 106142. [Google Scholar] [CrossRef] [PubMed]
  17. Das, J.K.; Salam, R.A.; Arshad, A.; Finkelstein, Y.; Bhutta, Z.A. Interventions for Adolescent Substance Abuse: An Overview of Systematic Reviews. Journal of Adolescent Health 2016, 59, S61–S75. [Google Scholar] [CrossRef] [PubMed]
  18. Trong, A.; Nam Gia Dao; Duy Cao Nguyen; Thi, M.; Boyer, L.; Pascal Auquier; Fond, G.; Roger; Cyrus; Zhang, B. Quality of Life and Mental Health of Adolescents: Relationships with Social Media Addiction, Fear of Missing Out, and Stress Associated with Neglect and Negative Reactions by Online Peers. PLOS ONE 2023, 18, e0286766–e0286766. [CrossRef]
  19. Coşkun, S.; Güvenç, G.; Bebiş, H. Effectiveness of web-based health education and consultation on health promotion behaviors of adolescents. Gulhane Medical Journal 2019, 61, 139–146. [Google Scholar] [CrossRef]
  20. Cremers, H.-P.; Mercken, L.; Oenema, A.; de Vries, H. A Web-Based Computer-Tailored Smoking Prevention Programme for Primary School Children: Intervention Design and Study Protocol. BMC Public Health 2012, 12. [Google Scholar] [CrossRef]
  21. de Josselin de Jong, S.; Candel, M.; Segaar, D.; Cremers, H.-P.; de Vries, H. Efficacy of a Web-Based Computer-Tailored Smoking Prevention Intervention for Dutch Adolescents: Randomized Controlled Trial. Journal of Medical Internet Research 2014, 16, e82. [Google Scholar] [CrossRef]
  22. Park, E.; Drake, E. Systematic Review: Internet-Based Program for Youth Smoking Prevention and Cessation. Journal of Nursing Scholarship 2014, 47, 43–50. [Google Scholar] [CrossRef]
  23. Ajzen, I. The Theory of Planned Behavior. Organizational Behavior and Human Decision Processes 1991, 50, 179–211. [Google Scholar] [CrossRef]
  24. Ajzen, I. Perceived behavioral control, self-efficacy, locus of control, and the theory of planned behavior. Journal of Applied Social Psychology 2002, 32, 665–683. [Google Scholar] [CrossRef]
  25. Steinmetz, H.; Knappstein, M.; Ajzen, I.; Schmidt, P.; Kabst, R. How Effective Are Behavior Change Interventions Based on the Theory of Planned Behavior? Zeitschrift für Psychologie 2016, 224, 216–233. [Google Scholar] [CrossRef]
  26. Sakineh Dadipoor; Heydari, G. ; Niveen M E Abu-Rmeileh; Mohseni, S.; Hadi; Teamur Aghamolaei; Shahabi, N. A Predictive Model of Waterpipe Smoking Cessation among Women in Southern Iran: Application of the Theory of Planned Behavior. BMC Public Health 2023, 23. [Google Scholar] [CrossRef]
  27. Sutha, D.W.; Prabandari, Y.S.; Padmawati, R.S. Smoking Behavior among Junior High School Students Based on the Theory of Planned Behavior in Madura, Indonesia. International Journal of Adolescent Medicine and Health 2022, 0. [Google Scholar] [CrossRef] [PubMed]
  28. Hassandra, M.; Theodorakis, Y.; Kosmidou, E.; Grammatikopoulos, V.; Hatzigeorgiadis, A. I Do Not Smoke — I Exercise: A Pilot Study of a New Educational Resource for Secondary Education Students. Scandinavian Journal of Public Health 2009, 37, 372–379. [Google Scholar] [CrossRef] [PubMed]
  29. Kolovelonis, A.; Goudas, M.; Theodorakis, Y. Examining the Effectiveness of the Smoking Prevention Program “I Do Not Smoke, I Exercise” in Elementary and Secondary School Settings. Health Promotion Practice 2016, 17, 827–835. [Google Scholar] [CrossRef]
  30. Lareyre, O.; Gourlan, M.; Stoebner-Delbarre, A.; Cousson-Gélie, F. Characteristics and Impact of Theory of Planned Behavior Interventions on Smoking Behavior: A Systematic Review of the Literature. Preventive Medicine 2020, 143, 106327. [Google Scholar] [CrossRef]
  31. Saeed Bashirian; Barati, M. ; Karami, M.; Hamzeh, B.; Elahe Ezati The Effect of a Web-Based Educational Program on Perevention of Hookah Smoking among Adolescent Girls: Application of Theory of Planned Behavior. PubMed 2021, 13, 259–267. [Google Scholar] [CrossRef]
  32. Fathi, Y.; Moeini, B.; Bazvand, A.; Barati, M.; Roshanaei, G. The Effectiveness of Educational Program Based on Theory of Planned Behavior on Preventing and Decreasing Tobacco Smoking among Post-Secondary Students. Journal of Education and Community Health 2017, 3, 54–61. [Google Scholar] [CrossRef]
  33. Zhao, X.; White, K.M.; McD Young, R. A TPB-Based Smoking Intervention among Chinese High School Students. Substance Use & Misuse 2018, 54, 459–472. [Google Scholar] [CrossRef]
  34. Arnold, J.; Dannemann, S.; Gropengießer, I.; Heuckmann, B.; Kahl, L.; Schaal, S.; Schaal, St.; Schlüter, K.; Schwanewedel, J.; Simon, U.; Spörhase, U. Modell zur reflexiven gesundheitsbezogenen Handlungsfähigkeit aus biologiedidaktischer Perspektive. Biologie in Unzerer Zeit 2019, 49, 243–244. [Google Scholar] [CrossRef]
  35. Simonds, S.K. Health Education as Social Policy. Health Education Monographs 1974, 2, 1–10. [Google Scholar] [CrossRef]
  36. Stockings, E.; Hall, W.D.; Lynskey, M.; Morley, K.I.; Reavley, N.; Strang, J.; Patton, G.; Degenhardt, L. Prevention, Early Intervention, Harm Reduction, and Treatment of Substance Use in Young People. The Lancet Psychiatry 2016, 3, 280–296. [Google Scholar] [CrossRef] [PubMed]
  37. Botvin, G.J.; Griffin, K.W. Life Skills Training: Empirical Findings and Future Directions. The Journal of Primary Prevention 2004, 25, 211–232. [Google Scholar] [CrossRef]
  38. Naik, P.; Tiwari, P.; Nirgude, A.; Datta, A. Effectiveness of Life Skills Health Education Program: A Quasi-Experimental Study among School Students of South India. Journal of Education and Health Promotion 2020, 9, 336. [Google Scholar] [CrossRef]
  39. Sherif, Y.; Zaid, A. ; Hamidin Awang; Siti Aisha Mokhtar; Marjan Mohammadzadeh; Aisha Siddiqah Alimuddin Effectiveness of Life Skills Intervention on Depression, Anxiety and Stress among Children and Adolescents: A Systematic Review. The Malaysian Journal of Medical Science 2023, 30, 42–59. [Google Scholar] [CrossRef]
  40. La Torre, G.; Chiaradia, G.; Ricciardi, G. School-Based Smoking Prevention in Children and Adolescents: Review of the Scientific Literature. Journal of Public Health 2005, 13, 285–290. [Google Scholar] [CrossRef]
  41. Lee, J.S.; Kim, H. Meta-Analysis of Effectiveness of Smoking Prevention Program for Elementary School Students. Korean Journal of Health Education and Promotion 2017, 34, 99–110. [Google Scholar] [CrossRef]
  42. Velasco, V.; Griffin, K.W.; Botvin, G.J. Preventing Adolescent Substance Use through an Evidence-Based Program: Effects of the Italian Adaptation of Life Skills Training. Prevention Science 2017, 18, 394–405. [Google Scholar] [CrossRef] [PubMed]
  43. Roberts, V.; Maddison, R.; Simpson, C.; Bullen, C.; Prapavessis, H. The Acute Effects of Exercise on Cigarette Cravings, Withdrawal Symptoms, Affect, and Smoking Behaviour: Systematic Review Update and Meta-Analysis. Psychopharmacology 2012, 222, 1–15. [Google Scholar] [CrossRef] [PubMed]
  44. Ussher, M.H.; Taylor, A.H.; Faulkner, G.E.J. Exercise Interventions for Smoking Cessation. Cochrane Database of Systematic Reviews 2014. [Google Scholar] [CrossRef] [PubMed]
  45. Angeli, M.; Hatzigeorgiadis, A.; Comoutos, N.; Krommidas, C.; Morres, I.D.; Theodorakis, Y. The effects of self-regulation strategies following moderate intensity exercise on ad libitum smoking. Addictive Behaviors 2018, 87, 109–114. [Google Scholar] [CrossRef]
  46. Hatzigeorgiadis, A.; Pappa, V.; Tsiami, A.; Tzatzaki, T.; Georgakouli, K.; Zourbanos, N.; Goudas, M.; Chatzisarantis, N.; Theodorakis, Y. Self-Regulation Strategies May Enhance the Acute Effect of Exercise on Smoking Delay. Addictive Behaviors 2016, 57, 35–37. [Google Scholar] [CrossRef] [PubMed]
  47. Smits, J. A.; Zvolensky, M. J.; Davis, M. L.; Rosenfield, D.; Marcus, B. H.; Church, T. S.; Powers, M. B.; Frierson, G. M.; Otto, M. W.; Hopkins, L. B.; Brown, R. A.; Baird, S. O. The efficacy of vigorous-intensity exercise as an aid to smoking cessation in adults with high anxiety sensitivity: A randomized controlled trial. Psychosomatic Medicine 2016, 78(3), 354–364. [Google Scholar] [CrossRef] [PubMed]
  48. Horn, K.; Branstetter, S.; Zhang, J.; Jarrett, T.; O’Hara Tompkins, N.; Anesetti-Rothermel, A.; Olfert, M.; Richards, T.; Dino, G. Understanding Physical Activity Outcomes as a Function of Teen Smoking Cessation. Journal of Adolescent Health 2013, 53, 125–131. [Google Scholar] [CrossRef] [PubMed]
  49. Theodorakis, Y.; Natsis, P.; Papaioannou, A.; Goudas, M. Greek Students’ Attitudes toward Physical Activity and Health-Related Behavior. Psychological Reports 2003, 92, 275–283. [Google Scholar] [CrossRef] [PubMed]
  50. Abdi, J.; Eftekhar, H.; Estebsari, F.; Sadeghi, R. Theory-Based Interventions in Physical Activity: A Systematic Review of Literature in Iran. Global Journal of Health Science 2014, 7. [Google Scholar] [CrossRef]
  51. Rhodes, R.E.; Boudreau, P.; Josefsson, K.W.; Ivarsson, A. Mediators of Physical Activity Behaviour Change Interventions among Adults: A Systematic Review and Meta-Analysis. Health Psychology Review 2020, 1–15. [Google Scholar] [CrossRef]
  52. Ajzen, I. TPB Questionnaire Construction 1 CONSTRUCTING a THEORY of PLANNED BEHAVIOR QUESTIONNAIRE, 2006.
  53. Booth, M.L. The Reliability and Validity of the Physical Activity Questions in the WHO Health Behaviour in Schoolchildren (HBSC) Survey: A Population Study. British Journal of Sports Medicine 2001, 35, 263–267. [Google Scholar] [CrossRef]
  54. Kann, L.; Kinchen, S.A.; Williams, B.I.; Ross, J.G.; Lowry, R.; Grunbaum, J.A.; Kolbe, L.J. Youth Risk Behavior Surveillance - United States, 1999. Journal of School Health 2000, 70, 271–285. [Google Scholar] [CrossRef] [PubMed]
  55. Arlinghaus, K.R.; Johnston, C.A. Advocating for Behavior Change with Education. American Journal of Lifestyle Medicine 2017, 12, 113–116. [Google Scholar] [CrossRef] [PubMed]
  56. Li, M.; Sonoda, N.; Koh, C.; Yasumoto, R.; Morimoto, A. Meta-Analysis of the Association between Health Literacy and Smoking. Population Medicine 2022, 4, 1–11. [Google Scholar] [CrossRef]
  57. Hewitt, A.M.; Stephens, C. Healthy Eating among 10 – 13-Year-Old New Zealand Children: Understanding Choice Using the Theory of Planned Behaviour and the Role of Parental Influence. Psychology, Health & Medicine 2007, 12, 526–535. [Google Scholar] [CrossRef]
  58. Sorensen, G.; Gupta, P.C.; Nagler, E.; Viswanath, K. Promoting Life Skills and Preventing Tobacco Use among Low-Income Mumbai Youth: Effects of Salaam Bombay Foundation Intervention. PLoS ONE 2012, 7, e34982. [Google Scholar] [CrossRef]
  59. Barati, M.; Hidarnia, A.; Niknami, S.; Allahverdipour, H. The effect of web-based intervention on preventing tobacco smoking among male adolescents: An application of the theory of planned behavior. Indian Journal of Fundamental and Applied Life Sciences 2015, 5(2), 125–134. [Google Scholar]
  60. Senkowski, V.; Gannon, C.; Branscum, P. Behavior Change Techniques Used in Theory of Planned Behavior Physical Activity Interventions among Older Adults: A Systematic Review. Journal of Aging and Physical Activity 2019, 27, 1–9. [Google Scholar] [CrossRef] [PubMed]
  61. Tapera, R.; Mbongwe, B.; Mhaka-Mutepfa, M.; Lord, A.; Phaladze, N.A.; Zetola, N.M. The Theory of Planned Behavior as a Behavior Change Model for Tobacco Control Strategies among Adolescents in Botswana. PLOS ONE 2020, 15, e0233462. [Google Scholar] [CrossRef]
  62. Karimy, M.; Zareban, I.; Araban, M.; Montazeri, A. An Extended Theory of Planned Behavior (TPB) Used to Predict Smoking Behavior among a Sample of Iranian Medical Students. International Journal of High Risk Behaviors and Addiction 2015, 4. [Google Scholar] [CrossRef]
  63. Zhao, X.; Dichtl, F.F.; Foran, H.M. Predicting Smoking Behavior: Intention and Future Self-Continuity among Austrians. Psychology, Health & Medicine 2020, 1–10. [Google Scholar] [CrossRef]
  64. Mbongwe, B.; Tapera, R.; Phaladze, N.; Lord, A.; Zetola, N.M. Predictors of Smoking among Primary and Secondary School Students in Botswana. PLOS ONE 2017, 12, e0175640. [Google Scholar] [CrossRef] [PubMed]
  65. Simons-Morton, B.; Haynie, D.L.; Crump, A.D.; Eitel, P.; Saylor, K.E. Peer and Parent Influences on Smoking and Drinking among Early Adolescents. Health Education & Behavior 2001, 28, 95–107. [Google Scholar] [CrossRef]
  66. Davey, G.; McClenahan, C.; Zhao, X. Subjective Smoking Norms Measure. PsycTESTS Dataset 2014. [Google Scholar] [CrossRef]
  67. Bosak, K.A.; Pozehl, B.; Yates, B. Challenges of Applying a Comprehensive Model of Intervention Fidelity. Western Journal of Nursing Research 2011, 34, 504–519. [Google Scholar] [CrossRef] [PubMed]
Table 1. Description of the “I do not smoke, I exercise” web-based program.
Table 1. Description of the “I do not smoke, I exercise” web-based program.
Sessions Theoretical Construct BCT Contents Activities
1st Attitudes
Education
 Shaping knowledge
Natural consequences
 Initial Evaluation – General knowledge about smoking Create an antismoking message – Knowledge quiz: “What do we know about smoking?”
2nd Education
Attitudes
Knowledge		 Shaping knowledge
Salience of consequences		 Presentation: Research data about smoking – harmful effects of smoking on our body Discuss; “what are the ingredients of a cigarette” – “Smoking causes…” - Passive smoking: "Is it dangerous?" – True or False? – Create your antismoking message – Homework in groups:
I reread the information in the material and create a knowledge quiz”
3rd Education
Perceived behavioral control.
Intention
Life skills		 Goal setting
Monitoring of behavior
Behavior substitution		 Physical activity as an alternative to smoking behavior - Why exercise is important - what is aerobic exercise Learn the benefits of exercise – presentation of research data- Discussion: “Does smoking affect my ability to exercise?” – Create your own positive and encouraging message about PA and smoking.
4th Subjective norm
Attitude
Life skills		 Behavioral experiments
Health consequences
Motivational interviewing		 Effects of tobacco consumption – Smoking behavior and your body - What you need to know Experimental activity: “Smoking bottle” – Presentation: “Smoking: effects on the body” – Discussion: “Why nicotine is addictive?”- Work team: “Interview family members, smokers & non-smokers”
5th Education
Perceived behavioral control.
Attitudes
Life skills		 Information about social and environmental consequences
Salience of consequences
 Social effects of smoking – The negative effects of smoking compared to its enticing image Facts: “Why do young people smoke?”– Worksheet: “Why do I have to imitate???”– Tobacco industry’s campaign to hide the hazards of smoking: Demystification of smoking advertisements
6th Knowledge
Life skills
Attitude 		Behavioral rehearsal
Shaping knowledge
Comparative imagining of future outcomes
 Practicing refusal skills - find ways to intelligently say NO to someone who offers you a cigarette - How an addiction can become more important to a person than family, friends, clubs, job, reputation Brainstorming: “The BIG NO” – Teamwork: “Practice your big NO’s in possible scenarios” – Activity: “The red balloon” - create a poster with antismoking messages
7th Perceived behavioral control
Life skills		 Action planning
Problem solving
Commitment		 Introduce a goal-setting technique – Introduction to problem-solving technique “Setting my goals on smoking” – Brainstorming: “Barrier or Justification?”- Long-term Vs Short term consequences of smoking
8th Knowledge
Life skills
Perceived behavioral control		 Action planning
Commitment 		Practice goal-setting and problem-solving techniques – Use these techniques to set your activity goals Self-assessment quiz:
“How active are you?”- Set your goals to exercise daily – Physical activity pyramid
9th Subjective norm
Attitudes
Life skills		 Information about antecedents
Provide healthy alternatives
Comparative imagining of future outcomes		 Transmit knowledge to others Teamwork: “Develop a campaign about smoking and exercise” – Work in groups and create anti-smoking posters – “Share what you have learned with family and friends”
10th Attitudes
Subjective norm 		Social comparison Raising awareness for the harm smoking causes Work in groups: “Writing Down Goals & Rewarding Yourself”- Organize an information day and inform your classmates about the consequences of smoking and the health benefits of exercise
Table 2. Descriptive statistics, reliability index and significant differences between pre and post intervention measures on the “I do not smoke, I exercise” health education program.
Table 2. Descriptive statistics, reliability index and significant differences between pre and post intervention measures on the “I do not smoke, I exercise” health education program.
Pre-intervention Post-intervention
Variables α M SD α M SD
Attitudes towards smoking .78 1.40 .58 .73 1.34 .62
Intention to smoke .60 1.18 .50 .85 1.15 .59
Subjective norm .59 1.33 .77 .84 1.32 .88
PBC .48 4.51* 2.07 .86 4.92* 2.40
Attitudes toward the program’s implementation .90 5.31 1.61 .90 5.43 1.68
Knowledge about smoking .68 21.67*** 3.74 .80 23.45*** 4.03
Smoking behavior .73 .31 1.14 .79 .38 1.23
Exercise behavior - 4.50 1.46 - 4.64 1.51
Satisfaction of the program - - - .90 5.72 1.39
M: Mean; SD: Standard Deviation; PBC: Perceived Behavioral Control; α: Cronbach’s α reliability index; *p < .05; ***p < .001
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