The Effect Of Adults Smoking Or Vaping On School Children And Toddlers
Smoking is a leading contributor to disease and death worldwide (WHO, 2017). 13.5% of adults smoke worldwide which is 1 billion smokers. If this continues, 1 billion people worldwide will die this century due to cigarette smoking.
The rationale of conducting this research is to aware smokers the health risk they are putting on other people’s health who are surrounded them. The findings of this methodology consist of mundane realism. This means that it can be implied in real-life situations. The hypothesis is, adults’ action to vaping and smoking changes around primary and secondary school children to toddlers. This is a natural experiment, in which no participants were recruited and were only observed outside a shopping centre.
The variable that is measured is the dependent variable which is, do/ don’t adults smoke/vape near children. The independent variable is the adult. There is no control variable. The main findings are that more adults smoked and vaped near children. The conclusions are that adults are more likely to smoke then vape near children.
NHS UK states that people who breath in second-hand smoke are more likely to get lung cancer or heart disease then compared to smokers. Children are at a higher risk and are more likely to be in the risk of asthma. There are 2.6 million e-cigarette users in the UK and are using vaping to slowly quit smoking.
Heather Wipfli Erika Avila-Tang, Ana Navas-Acien (2006) conducted a survey to measure air nicotine concentration in non-smoker and smoker household. The sample was collected from 40 households in 32 countries. The findings shows that the Median air nicotine concentration was 17 times higher in households with smokers (0.18 μg/m3) compared with households without smokers (0.01 μg/m3). Air nicotine increases as the number of smokers increased. To conclude from this, children are at an increased risk of diseases then compared to the control group. This is supported by (Medical news today). They suggest that smoke produces fine particulate matter which is an element considered to be hazardous for air pollution and health.
The study that is conducted by the group shows that there is research to support that second-hand smoking is more dangerous. If people are more alert of this matter, they would naturally stop smoking/vaping in front of others and especially children. This is the main reason as to why this study is important.
(Garfinkel 1981; Hirayama 1981; Trichopoulos et al. 1981) conducted a study on second-hand smoking. There was 2 condition. Condition A had non-smoking women married to smokers and Condition B had non-smoking women married to non-smokers. The women in condition A had a higher risk of developing lung cancer than compared to the control group.
From this study, it shows that the study conducted by our group is considered to be important as it shows the importance of avoiding and alerting people that they are in a risk of lung cancer if they come close in touch with smokers.
The type of research conducted is a field experiment. There are no control variables in a natural setting as the experimenter observes the natural behaviour of the people in the setting. The individual is unaware that they are being observed, from this the extraneous variable can’t be controlled.
The independent variable is the adults, children and toddlers. The dependent variable is the number of adults smoking/vaping near children/toddlers. The extraneous variable is the weather, the condition of the weather consisted of rain and cold wind. This can affect the dependent variable as fewer adults would be smoking/vaping outside due to the rain. Condition A consisted of adults smoking near children. Condition B consisted of adults smoking near toddlers. Condition C consisted of adults vaping near children and condition D consisted of adults vaping near toddlers. The nominal data is adult, children and toddler. The ordinal data is smoking or not smoking. Vaping or not vaping. The interval data is the findings. The number of adults smoking/vaping or not smoking/vaping near children/toddlers. The ratio data is the time sampling, i.e. the experiment was observed in 60 mins.
552 participants took part in this research. They were naïve, unaware of this research and its aims. They did not consent to take part in this research as it’s a field experiment. The age of the participants which was observed was over 18.
Case Processing Summary
Valid Missing Total
N Percent N Percent N Percent
Smoking type * Age group 552 100.0% 0 0.0% 552 100.0%
Smoking type * Age group Crosstabulation
Age group Total
Toddlers School children
Smoking type Smoking Count 56 72 128
Expected Count 70.5 57.5 128.0
% within Smoking type 43.8% 56.3% 100.0%
% within Age group 18.4% 29.0% 23.2%
% of Total 10.1% 13.0% 23.2%
Vaping Count 12 48 60
Expected Count 33.0 27.0 60.0
% within Smoking type 20.0% 80.0% 100.0%
% within Age group 3.9% 19.4% 10.9%
% of Total 2.2% 8.7% 10.9%
No smoking and vaping Count 236 128 364
Expected Count 200.5 163.5 364.0
% within Smoking type 64.8% 35.2% 100.0%
% within Age group 77.6% 51.6% 65.9%
% of Total 42.8% 23.2% 65.9%
Total Count 304 248 552
Expected Count 304.0 248.0 552.0
% within Smoking type 55.1% 44.9% 100.0%
% within Age group 100.0% 100.0% 100.0%
% of Total 55.1% 44.9% 100.0%
Value df Asymptotic Significance (2-sided)
Pearson Chi-Square 50.482a 2 .000
Likelihood Ratio 51.975 2 .000
Linear-by-Linear Association 25.818 1 .000
N of Valid Cases 552
a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 26.96.
The procedure of the experiment is that the setting of the experiment was discussed with the group. The group decided to conduct the experiment outside a shopping centre. The experimenters sat on one of the benches to avoid investigator effect. There was a time sampling of 60 mins. The environment where the research was conducted consisted of a high population of adults and children with 5 benches. The research was conducted at 15.00, as it was the busiest hour of the day. The participants were not given the detail of the research as they were unaware that they were taking part in this research.
The reason why the participants were not given a constant form or were told the aim of the research is because if they are being told the true aim of the research. This would not be a field experiment and therefore the behaviour of the participants would not be natural. By having an artificial setting, the study would, therefore, lack real-life application and lack of generalisability.
A person’s Chi-Squared Test of Association revealed significant association between smoking type and age group.
X2 (2, N = 552) = 50.48, p = < 0.000
There is a significant difference as the P value is lower than 0.05.
Before performing the chi-square test, the data was placed in a consistency table, in which the total was calculated. The graph shows that in condition A. More adults smoke then vape near toddlers. More adults don’t smoke/vape near toddlers. In condition B, it shows that more adults smoke then vape near school children. Also, more adults don’t smoke/vape near school children. The frequency of the consistency table is that the highest number was no smoking/vaping for toddlers and school children. The lowest number was vaping for toddlers and school children.
The research aims to see if adults stop smoking/vaping if they are near children in order to see if they care about second-hand smoking effects. The findings of the report suggest that adults smoke/vape near people. They wouldn’t stop smoking if a child is near them. The results show that many adults are not aware of the effects of second-hand smoking has an impact on the individual. (Garfinkel 1981; Hirayama 1981; Trichopoulos et al. 1981) support this research as this study shows that people have a lack of awareness of the effects of second-hand smoking.
The predicted results state that adults will vape more near children then smoking. A report published by the Royal College of Physicians suggests that electronic cigarettes are less harmful to the individual’s health than compared to smoking. Professor Jeremy Pearson, Associate Medical Director at Heart Foundation, states that from a study that vaping is less harmful to an Individual’s blood vessels than smoking cigarettes. The people’s blood vessel health had started to recover soon after switching from smoking to electronic cigarettes. This report would suggest that people are more likely to vape near children then smoke, as they are aware that vaping is less harmful than smoking. This research implies that it can be used to aware smokers the health risk they are given.
The actual results from the study are different from the predicted results. The result shows that 10.1% of adults smoked near toddlers. 13% of adults smoked near children. Compare this result to the vape condition. About 2.2% of adults vaped near toddlers and 8.7% of adults vaped near children. The results show that more adults smoked near children then vape.
The hypothesis is not supported by the data. The hypothesis states that adults are more likely to vape than smoke near children. The data shows that 23.2% of adults smoked near toddlers and children. About 10.9% of adults vaped near toddlers and children. Furthermore, this data shows that more adults smoked near children/toddlers then vaping.
The reason why the results turned out this way is that the data shows 60 people vaped out of the 188 who smoked. The reason why the level of vapers is low is since electronic cigarettes have been introduced in 2007, people are less aware of vaping. On the other hand, cigarettes were introduced in 1600 in the UK. Cigarette has been in the UK for a longer time than electric cigarettes.
The limitation of this research design is that since it’s a field experiment. Many variables can’t be controlled, such as the extraneous variable. This variable can directly affect the dependent variable. This means that the researcher can’t be certain that the changes to the dependent variable are due to the changes in the independent variable. The limitation of observational research is that observer bias may arise. What researchers observe is distorted by their expectations of what they hope to see which would prove their hypotheses correct.
In conclusion, this research is conducted in a natural setting, which therefore means that the findings of the data can be used to apply to real-life application. The use of this research can contribute to the decline of many health factors such as lung cancer. This alternatively has a positive impact on the economy, as fewer people will have lung cancer leading to fewer people in hospital. Furthermore, this would have less pressure on the NHS and private healthcare services. There would be a decrease in medical cost. This means that the economy would be able to invest its income in other factors such as education.
- Bhf.org.uk. (2019). E-cigarettes are much less harmful than smoking according to report. [online] Available at: https://www.bhf.org.uk/what-we-do/news-from-the-bhf/news-archive/2016/april/e-cigarette-report [Accessed 22 Dec. 2019].
- Bhf.org.uk. (2019). Is vaping safe?. [online] Available at: https://www.bhf.org.uk/informationsupport/heart-matters-magazine/news/e-cigarettes [Accessed 22 Dec. 2019].
- Garfinkel, L. (1981). Time Trends in Lung Cancer Mortality Among Nonsmokers and a Note on Passive Smoking. JNCI: Journal of the National Cancer Institute, 66(6), pp.1061-1066.
- Medical News Today. (2019). Cigarette smoke produces 10 times more air pollution than diesel car exhaust. [online] Available at: https://www.medicalnewstoday.com/releases/12481.php#1 [Accessed 30 Dec. 2019].
- NHS 23 July 2018, Citation: Passive smoking: protect your family and friends. Retrieved from https://www.nhs.uk/live-well/quit-smoking/passive-smoking-protect-your-family-and-friends/
- WIPFLI, H., AVILA-TANG, E., NAVAS-ACIEN, A., KIM, S., ONICESCU, G., YUAN, J., BREYSSE, P. AND SAMET, J. M. Secondhand Smoke Exposure Among Women and Children: Evidence From 31 Countries. Smoke Exposure Among Women and Children: Evidence From 31 Countries. American Journal of Public Health, 98(4), pp.672-679.