Abstract:

            Cigarette smoking behaviours are continuously changing due to the introduction of electronic cigarettes. An apparent gender influence can be seen between these genders, and the background literature of the research showed that males do more smoking than females. Still, not a significant pattern was seen in the behaviour of smoking. The research question is to examine if any gender influence is present in the type of nicotine used. The research aims to see the gender influence along with the smoking behaviour. It hypothesised that a significant relationship is currently in the genders for determining the smoking behaviour. The research involves 84 participants (50 males and 34 females) in the rush time at Paddington train station. Gender and type of nicotine were the two variables analysed using SPSS, and it is a real experiment. The research s main findings showed a significant relation between both gender referring to smoke, but no smoking pattern was seen between male and female.

Introduction:

            Different individuals have different cigarette smoking behaviours. Smoking behaviours involve additional influencing factor like gender influence the type of nicotine being smoked. The smoking behaviour is shifting from nicotine to electronic cigarettes (Cho et al., 2011). Tobacco smoking status is decreasing, and both the genders are moving towards the electronic cigarettes (Smith et al., 2016). The researches predicted that the reason behind this behaviour is that it has fewer chemicals and does not cause a significant range of health issues. However, these cigarettes have heavy metal in them, which can cause lung cancer issues. Different researches predict that gender differences has an influence on the type of cigarettes smoked. One of a previous research study indicated that apparent gender differences could be seen in cigarette smoking. Psychosocial and the psychobiological factors are one of the leading factors which present the evident gender differences (Smith et al., 2015). This research study predicted that men used to use tobacco as compared to females. But different cultural variations are also present here, which leads to cause these differences (Grunberg et al., 2010). Another research study was conducted to see the percentage of tobacco product use among adults. Adults are more likely to adopt the smoking behaviour. This research includes a National Health Interview Survey, 2017, which predicts that males do more smoking than females in both nicotine and electronic cigarette smoke types. People in the age 25 44 have more smoking behaviour as compared to all other age groups. The individuals change in behaviours is due to the variations in smoking type (Wang et al., 2017). A consumption of tobacco s behavioural patterns was also analysed in the university students to assess the consumption patterns of smoking. A significant difference can be seen in between the percentage of the male and female smokers. Male smokers were 32.7% while the female smokers were 5.9%. This percentage of smoking is now shifting from the nicotine to the electronic cigarette smoke. But this study also predicts several factors which influence the smoking patterns in between both genders. The risk factors analysed in this case were age, father s smoking habits, and the friend s smoking habits. In comparison, females risk factors include sister s and friend s smoking habits (Mandil et al., 2010).

            The rationale of this study is to examine the patterns of nicotine type smoke in both genders. This study will be a contribution to the previous research as it is more up to date. It will also help examine different behavioural patterns.

            This study aims to examine the gender influence on the type of nicotine used. This research could help clinics improve public health and give insight into what products are being smoked. Gender influence is the independent variable here while the smoking is the dependent variable in the research. Gender is the independent variable as it predicts the smoking behaviours of nicotine and electronic cigarette smoking. The hypothesis statement is that males some more than females and there are also differences in the type of nicotine smoked.

Methodology:

            This section will reflect on the entire methodology that has been followed in the whole research. It will include the study s design, participants involved, material, and the procedure that is followed for conducting the entire investigation.

Design:

            This research is based on the primary data collection, which is defined as gathering information on the interviews and surveys of ideas. In this case, the type of experimental design that has been used is the naturalistic experiment. It involves the subjects as the random assignment of the issues while observing them. This study is used to answer a particular question in this research; the main focus is to see the impact of the gender influence on the type of nicotine smoked. The categorical variable that cannot be changed in this case is gender while type of nicotine (tobacco and electronic cigarette) are the dependent variables. This is a quantitative study, so the level of measurement is the ordinal in this research. The rationale of choosing this design is to enhance the research s validity and make it more appropriate and reliable.

Participants:

            A total number of 84 participants were present in the study out of which 50 were the male smokers while the rest of the 34 were female smokers. Behaviour of smoking and gender influence will also be analysed in the selected participants. Paddington train station was used as a location within the rush time, i.e., 4:30 pm and 7:00 pm.

Material:

            None of the stimulus is involved in the research as it is based on the naturalistic observation. Also, the random sampling was used in the selection of the participants.

Procedure:

            This experiment is a naturalistic one which means that there was no appropriate design and place. The smoking behaviour was observed at Paddington train station randomly in the rush hours. Only gender and the nicotine product were the variables which were involved during the experiment. The patterns of smoking were analysed along with the type of nicotine these genders prefer. Rationale for choosing this procedure is to reduce the component of the discriminatory behaviour. Using this type of naturalistic observation will also provide about the daily smoking patterns in both the genders. Both the tobacco smoking and electronic smoking patterns were encountered in both the genders. The time was specified within rusk hour to analyse the behaviour of the maximum number of people.

Results:

Analysis of the research data includes two different quantitative interpretations: smoking cigarette cross tabulation and Chi square tests. The relationship cannot be interpreted by merely looking upon the data collected (see supplementary data). So, this cross tabulations primary purpose is to examine the connection between two variables which are gender and nicotine type in this case. The findings propagate differently in both genders except for a single subject. The only scenario in which both the gender show similar behaviour is that tobacco cigarettes are more common than electronic cigarettes. Thirty one of the male participants used tobacco cigarettes, and 22 of the female participants also used it. At the same time, the rest of the individuals were for electronic cigarettes. Tobacco cigarette smoking is more common in females which is 64.7% compared to males which is 62.0%. Simultaneously, the electronic cigarette tobacco percentage is more in males (38.0%) than females (35.3%). Another relationship gathered by the cross tabulation is that tobacco cigarette smoking (portion) is more common in males (58.5%) as compared to females (41.5%) and same is the case with electronic cigarettes (61.3% for males and 38.7% for females). The overall percentage of both genders for tobacco cigarettes is 63.1% and 36.9% for electronic cigarettes. Using the cross tabulation methodology e helps reduce the complexity of data collected and provides more profound insight into the categorical variables involved in the quantitative research.

            All the findings of the chi square test were more significant than alpha value. Pearson Chi square value is greater than 0.05, which is the Alpha value. This means that the Pearson Chi square showed a non significant relationship in both genders. On the other hand, the continuity correction showed a significant value. All the remaining findings reported no gender influence on the type of nicotine (Wang et al., 2020). Both the genders show an equal behaviour towards the kind of smoking.

On the other hand, other variables which are cigarettes were also not associated with each other as per the chi square test. This means that the null hypothesis is accepted and there is no significant relationship between both genders. The only case in which statistical is significant is continuity correction value as presented in the table. All the findings of the statistical research non significant. This means that no gender influence is associated with the type of nicotine smoking. The non significant results can be given to the limited data collected.

Discussion:

            The general trend of smoking dictated in most countries is that men used to smoke more than women. But this research contradicts the literature s previous findings, as negligible gender differences were seen in between nicotine type smoke (Mucha et al., 2006). This degree of agents can be due to the differences between psychological, cultural and behavioural factors. Environmental factors can also be involved because much cannot be generalised due to certain limitations (Perkins, 2001). The susceptibility is different in case of nicotine addiction in both genders. Higher exposure rate is seen in men as compared to two women (Samet et al., 2010). The clustered bar of mean frequencies was also a part of the findings, reflecting that male smokers are more frequent than female smokers. This finding was in relevance to the previous literature review. At the same time, tobacco cigarettes were standard in both genders rather than electronic cigarettes (Verplaetse et al., 2019).

Another finding of the literature is that it males do smoke more electronic cigarettes than females. The positive expectancies regarding e cigarettes are taste social facilitation and the energy (Kong et al., 2017). While the positive expectancy is associated with female is that electronic cigarettes are highly beneficial for weight loss. The reduction factor is more likely to occur in males than females. These gender differences give a detailed discussion about the gender rules and the smoking behaviour. It can be due to different environmental all the influence factors in the society (McMillan et al., 2018). The rapid generation changes and the social determinants are also one of the reasons involved here. Quantitative analysis of the research allows us to see the influence of gender with different perspectives as, in some cases, non significant relationships can also be seen.

Limitations of the research:          

            The research cannot be generalised and implemented overall cultures due to the limitation of the data collected. Also, the research participants were limited to a single place, which means that the findings cannot be same for every region due to the cross cultural differences. Also, as the null hypothesis is accepted in different cases, the research can be questioned and is challenging for the previous literature. The variables cannot be observed from a holistic perspective (Karado?an & Onal, 2018). Validity of analysis which determine its effectiveness are confirmation and completeness.

Future research:

            The future research will be involved more detailed quantitative analysis to see the behavioural differences in the genders. The stud will also be cross cultural to see the different patterns of smoking in these cultures.

Implications of the research:

It is a positive contribution to the previous findings. The research results will also be highly beneficial in analysing the behavioural patterns of smoking and different factors susceptibility. Moreover, the research findings provide a detailed insight into the general influence and patterns of smoking in both genders. It will be highly beneficial in improving public health and understanding the smoked products more likely (Hemsing & Greaves, 2020).

Conclusion:

            In a concluding note, the hypothesis was accepted, which refers to the fact that males do more smoking than females. However, no significant differences were seen between the patterns and behaviour of smoke. To sum up, the research s critical point is that it validates some of the findings but does not provide a broader picture due to the data s limitation (Hemsing & Greaves, 2020).

References:

Assari, S., Smith, J. L., Zimmerman, M. A., & Bazargan, M. (2019). Cigarette smoking among economically disadvantaged African American older adults in South Los Angeles: Gender differences. International journal of environmental research and public health16(7), 1208.

Cho, J. H., Shin, E., & Moon, S. S. (2011). Electronic cigarette smoking experience among adolescents. Journal of Adolescent Health, 49(5), 542 546.

Greaves, L., & Hemsing, N. (2020). Sex and gender interactions on the use and impact of recreational cannabis. International journal of environmental research and public health17(2), 509.

Grunberg, N. E., Winders, S. E., & Wewers, M. E. (2010). Gender differences in tobacco use. Health psychology10(2), 143.

Karado?an, D., & Önal, Ö. (2018). Influencing factors of university students smoking status according to gender. Tobacco Induced Diseases16(3).

Kong, G., Kuguru, K. E., & Krishnan Sarin, S. (2017). Gender differences in US adolescent e cigarette use. Current addiction reports4(4), 422 430.

Mandil, A., BinSaeed, A., Ahmad, S., Al Dabbagh, R., Alsaadi, M., & Khan, M. (2010). Smoking among university students: a gender analysis. Journal of infection and public health3(4), 179 187.

McMillan, C., Felmlee, D., & Osgood, D. W. (2018). Peer influence, friend selection, and gender: How network processes shape adolescent smoking, drinking, and delinquency. Social networks55, 86 96.

Mucha, L., Stephenson, J., Morandi, N., & Dirani, R. (2006). Meta analysis of disease risk associated with smoking, by gender and intensity of smoking. Gender medicine, 3(4), 279 291.

Perkins, K. A. (2001). Smoking cessation in women. CNS drugs, 15(5), 391 411.

Smith, P. H., Bessette, A. J., Weinberger, A. H., Sheffer, C. E., & McKee, S. A. (2016). Sex/gender differences in smoking cessation: a review. Preventive medicine, 92, 135 140.

Smith, P. H., Kasza, K. A., Hyland, A., Fong, G. T., Borland, R., Brady, K., ... & McKee, S. A. (2015). Gender differences in medication use and cigarette smoking cessation: results from the International Tobacco Control Four Country Survey. Nicotine & Tobacco Research, 17(4), 463 472.

Samet, J. M., Yoon, S. Y., & World Health Organization. (2010). Gender, women, and the tobacco epidemic. World Health Organization.

Verplaetse, T.L., Moore, K.E., Pittman, B.P., Roberts, W., Oberleitner, L.M., Peltier, M.K.R., Hacker, R., Cosgrove, K.P. and McKee, S.A., 2019. Intersection of e cigarette use and gender on transitions in cigarette smoking status: findings across waves 1 and 2 of the population assessment of tobacco and health study. Nicotine and Tobacco Research21(10), pp.1423 1428.

Wang, T. W., Asman, K., Gentzke, A. S., Cullen, K. A., Holder Hayes, E., Reyes Guzman, C., ... & King, B. A. (2018). Tobacco product use among adults—United States, 2017. Morbidity and Mortality Weekly Report67(44), 1225.

Supplementary Materials:

Smoking * Cigarettes Cross tabulation

 

Cigarettes

Total

Tobacco cigarettes

Electronic cigarettes

Smoking

Male smokers

Count

31

19

50

Expected Count

31.5

18.5

50.0

% within Smoking

62.0%

38.0%

100.0%

% within Cigarettes

58.5%

61.3%

59.5%

% of Total

36.9%

22.6%

59.5%

Female smokers

Count

22

12

34

Expected Count

21.5

12.5

34.0

% within Smoking

64.7%

35.3%

100.0%

% within Cigarettes

41.5%

38.7%

40.5%

% of Total

26.2%

14.3%

40.5%

Total

Count

53

31

84

Expected Count

53.0

31.0

84.0

% within Smoking

63.1%

36.9%

100.0%

% within Cigarettes

100.0%

100.0%

100.0%

% of Total

63.1%

36.9%

100.0%

               

 

 

 

 

Chi Square Tests

 

Value

df

Asymptotic significance (2 sided)

Exact Sig. (2 sided)

Exact Sig. (1 sided)

Pearson Chi Square

.064a

1

.801

 

 

Continuity Correctionb

.000

1

.982

 

 

Likelihood Ratio

.064

1

.801

 

 

Fisher s Exact Test

 

 

 

.822

.493

Linear by Linear Association

.063

1

.802

 

 

N of Valid Cases

84

 

 

 

 

a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 12.55.

b. Computed only for a 2x2 table

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