Evaluation of effectiveness of peer education on smoking behavior among high school students

Bilgiç, Nurcan; Günay, Türkan

doi:10.15537/smj.2018.1.21774

Cited by 23 publications

(18 citation statements)

References 10 publications

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“…Peer education is an effective method that promotes positive decision making and changes in risk-taking behaviors in all age groups. [27][28][29] Risk Similarly, in our study, peer educated students compared to non-peer educated students, FNAT, SPF, and S-DBS benefit subscale scores decreased significantly and SES, BCPS, and S-DBS-loss subscale scores increased significantly. One of the strengths of our study is that it is unique to university students between the ages Figure 7 The students' in the experimental and control groups according to eight follow-up results Decision Balance Scale losses and benefit scores and smoking quit of rate.…”

Section: What Are the Factors Affecting The Decision Of Students To Qsupporting

confidence: 71%

“…They form positive role models and encourage social learning with their friends. [27][28][29]35 Similarly, in our study, the students in the peer education group according to students without peer education, in eight follow-up sessions, it has a significant effect on quitting smoking, increasing their self-efficacy and reducing smoking-promoting factors (Table 2; Figures 5 and 6). In one study, short-term and non-continuous peer education programs did not affect the smoking behavior of young people.…”

Section: Self-efficacy and Smoking-promoting Factorssupporting

confidence: 53%

“…Each individual is expected to communicate with the individuals around him, especially his peers, about the harms of smoking and the quit. 3 , 26 , 28 In our study, all students who received peer education quit smoking. In line with this result, it is recommended to focus on peer education in smoking quit programs for young people.…”

Section: Discussionmentioning

confidence: 91%

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The Effect of Peer Education on Decision-Making, Smoking-Promoting Factors, Self-Efficacy, Addiction, and Behavior Change in the Process of Quitting Smoking of Young People

Örsal

Ergün

2021

RMHP

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Purpose The study aims to examine the effect of peer education on the decision to quit smoking, factors that encourage smoking, self-efficacy, addiction, and behavior change in students who apply to the Youth Friendly Center to quit smoking. Participants and Methods This research is a Randomized Controlled Trials study. The experimental group consisted of students who were enrolled in the peer education course (n=759). The control group has consisted of students (n=1095) who did not enroll in this course. Results Participants in the experimental group to quit smoking, more than the control group (p>0,01). The addiction level of the participants in the experimental group, less than the participants in the control group (p>0,01). According to the scores of the participants in the control group of the participants in the experimental group, the factors that trigger smoking, and the benefit sub-dimension scores in the Decision Balance Scale were low. Loss sub-dimension scores, which show the losses from the harms of smoking, increased significantly in the Self-Efficacy Scale, Behavior Change Process Scale, and Decision Balance Scale (p>0,01). Conclusion Peer educators trained by the researcher and her team in the Youth Friendly Center Smoking Quit Program have an important effect in supporting/improving the cognitive and behavioral change processes of university students in smoking quit compared to those who do not receive an education. 94% success of the smoking quit program; Students’ voluntary application to receive professional support, students’ voluntary attendance of the treatment program for 6 months, strong communication and feedback, effective and functional professional counseling, and social support depend on strengthening the program with peer education. Especially with peer education, the development of leadership and role model characteristics made the smoking quit program preferred by students.

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Section: What Are the Factors Affecting The Decision Of Students To Qsupporting

confidence: 71%

Section: Self-efficacy and Smoking-promoting Factorssupporting

confidence: 53%

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The Effect of Peer Education on Decision-Making, Smoking-Promoting Factors, Self-Efficacy, Addiction, and Behavior Change in the Process of Quitting Smoking of Young People

Örsal

Ergün

2021

RMHP

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“…The predictor variables identified by both machine learning algorithms confirmed many socio-environmental determinants, such as peer pressure and brand name of tobacco products [ 48 , 49 , 50 , 51 ], as important predictor variables. Studies indicate there are several factors closely associated with youth nicotine addiction, including age of starting tobacco use, gender, grade level, ethnicity/race, living with current tobacco users, English not being the first language at home, and having a disability/mental health condition [ 42 , 52 , 53 , 54 , 55 , 56 , 57 , 58 ].…”

Section: Discussionmentioning

confidence: 88%

Machine Learning-Based Nicotine Addiction Prediction Models for Youth E-Cigarette and Waterpipe (Hookah) Users

Choi

Jung

Ferrell

et al. 2021

JCM

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Despite the harmful effect on health, e-cigarette and hookah smoking in youth in the U.S. has increased. Developing tailored e-cigarette and hookah cessation programs for youth is imperative. The aim of this study was to identify predictor variables such as social, mental, and environmental determinants that cause nicotine addiction in youth e-cigarette or hookah users and build nicotine addiction prediction models using machine learning algorithms. A total of 6511 participants were identified as ever having used e-cigarettes or hookah from the National Youth Tobacco Survey (2019) datasets. Prediction models were built by Random Forest with ReliefF and Least Absolute Shrinkage and Selection Operator (LASSO). ReliefF identified important predictor variables, and the Davies–Bouldin clustering evaluation index selected the optimal number of predictors for Random Forest. A total of 193 predictor variables were included in the final analysis. Performance of prediction models was measured by Root Mean Square Error (RMSE) and Confusion Matrix. The results suggested high performance of prediction. Identified predictor variables were aligned with previous research. The noble predictors found, such as ‘witnessed e-cigarette use in their household’ and ‘perception of their tobacco use’, could be used in public awareness or targeted e-cigarette and hookah youth education and for policymakers.

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“…A recent study by Bilgic and Gunay 3 reported that the smoking behaviors of high school students positively changed as a result of using the peer education method in the transtheoretical model. This study is very impressive because it provides an inspiration of establishing a new strategy for youth smoking cessation education programs in Korea.…”

mentioning

confidence: 99%