The Use of Electronic Cigarettes Among College Students

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The Use of Electronic Cigarettes Among College Students

The purpose of the study was to discover what substances students consume apart from nicotine and determine the potential danger of this activity by identifying the use of electronic cigarettes to smoke non-nicotine-based substances by college students.

The research question in the study was: what is the prevalence of e-cigarette use, perceived harm, and reasons for e-cigarette use, prevalence and types of other substances used in e-cigarettes in the population of college students (Kenne et al., 2017, p. 2)?

The hypothesis of the study was that college students are more prone to unhealthy habits and misuse of e-cigarettes or drugs because of such factors as decreased parental supervision.

The research design was observational. Since no variable was manipulated, this study can be considered observational.

The method used to collect the data is a survey. The survey was sent to students through e-mail randomly, decreasing the likelihood of biases. The appropriateness of such a data collection method is justified by the elements of the research question, which entails detecting data on the prevalence and harm of substance use. For example, the scholars stated that the survey allowed for constructing many different questions depending on the complexity of the studied variables, which helped in obtaining participants responses contributing to smoking patterns, substances, and habits (Kenne et al., 2017).

Data collected was categorical and quantitative; quantitative data is age, whereas categorical data is respondents race, affiliation, neighborhood, and smoking status. For example, the survey included demographics and patterns for tobacco use as variables (Kenne et al., 2017).

Potential weaknesses of the data collection methods were related to the sample. In particular, Kenne et al. (2017) have only collected data from undergraduate students studying on the main campus. Thus, the authors have narrowed the pool of respondents, which could have also included graduate students, which might have revealed another interesting pattern. For instance, undergraduate students are more prone to use substances other than nicotine than postgraduate students.

Data analysis methods consisted of binomial logistic regression with the calculations of p-values and percentages commonly used in research with descriptive statistics. It is appropriate due to the focus of the research question on the detection of prevalence rates.

Potential weaknesses of the data analysis methods are one of the elements missing from the analysis is other variables that might contribute to more substance abuse through e-cigarettes, such as stress at the university, which were not considered. Moreover, the limitations of self-reported data might have helped avoid such instances as participants who refused to report or did not know what the other substance was (Kenne et al., 2017, p. 5). Expanding questions could have assisted in the identification of new patterns.

Key demographics of the population sampled were undergraduate students from large Midwestern universities. Students had to reside on the main campus and study at the undergraduate level to be included in the study.

Results of the research are that the Chi-square test confirmed the descriptive study results and statistical significance. The statistical significance of the results was determined by establishing the value of covariates which was P < .05 (Kenne et al., 2017). For example, respondents reported that the most commonly used substitute for nicotine is cannabis, with 77.9 percent (Kenne et al., 2017).

Differences between the groups were that women are less likely to use substances other than nicotine in their e-cigarettes than men. Only 46 out of 850 female e-cigarettes stated that they smoked non-nicotine substances, in contrast to 61 male respondents (Kenne et al., 2017). Moreover, former smokers are more likely to indulge in the risky operation of vaporizing non-nicotine products than those who reported never smoking.

Limitations in the study population and sample size are in the sample selection process. For example, the data was collected only from the undergraduate students living on the main campus, whereas other students were not included (Kenne et al., 2017). It is unclear why only students living on the main campus were selected if surveys were distributed through e-mails and there would be no logistical issues with collecting answers.

Advantages and disadvantages of the type of statistical analysis used include the following. One of the advantages of Chi-square analysis in descriptive statistics is the ability to identify patterns easily. However, if there were more questions regarding the broader background of students, the binomial logistic regression may not have encompassed these. For example, Kenne et al. (2017) state that the study could not identify whether using substances other than nicotine is a habit or a single episode for respondents. Although the survey included the possibility of winning a gift card, there were also instances of respondents skipping the question about other substance use (N = 199). However, these missing responses are inevitable in any survey. However, that is still an important number to consider in examining the responses.

Compare results in your article to results from an article listed in the reference list: The source reveals vitally important patterns among non-nicotine substance use in e-cigarettes among college students. The results of this study slightly differed from the survey conducted by Jones et al. (2016). For example, Jones et al.s (2016) research was conducted in a state where cannabis is legal for medical reasons. Kenne et al. (2017) denoted other substances without specifically determining cannabis due to legal considerations. Thus, the differences in law can account for 199 respondents who did not answer the question on using non-nicotine substances with e-cigarettes (Kenne et al., 2017).

Limitations of the study design are limited generalizability and focus on quantitative data specifically.

This study contributes to scientific literature in that it investigates not only e-cigarette and vape use but also the use of non-nicotine substances. Using self-teaching videos to vaporize substances can be risky for health, and it is important to identify patterns of indulgence in different demographic. The research on e-cigarettes is still quite scarce, and the long-term effects are still unidentified. Nevertheless, healthcare professionals need to understand the scale of the problem and be aware of it.

Further investigation on this topic could consist of identifying habits of smoking non-nicotine products using e-cigarettes among young adults in different universities. Moreover, instead of looking at single instances, further research can focus on identifying underlying patterns, such as the frequency of vaporizing non-nicotine substances. This approach might be a way of assessing risks for young adults and raising awareness for healthcare professionals.

Reference List

Jones, C., Hill, M., Pardini, D., & Meier M. (2016). Prevalence and correlates of vaping cannabis in a sample of young adults. Psychology of Addictive Behaviors, 30(8), 915-921.

Kenne, D., Fischbein, R., Tan, A., & Banks, M. (2017). The use of substances other than nicotine in electronic cigarettes among college students. Substance Abuse: Research and Treatment, 11, 18.

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