NetLogo User Community Models

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Download If clicking does not initiate a download, try right clicking or control clicking and choosing "Save" or "Download".(The run link is disabled for this model because it was made in a version prior to NetLogo 6.0, which NetLogo Web requires.)

## WHAT IS IT?

Building on the works of Väänänen, A., Kouvonen, A., Kivimäki, M., Pentti, J., & Vahtera, J. (2008) and Westmass, J. L., Jones, J. B., & Bauer, J. E. (2010), the model aims to look at the pattern of how the number of smokers or non-smokers can affect a smoker’s behavior. In addition, the model aims to see how the strength of intimacy between the smoker and his surrounding people can affect his smoking behavior.

## HOW IT WORKS

Click the SETUP button to create random distribution of red (non-smoker) and black (smoker) patches.

Using the respective sliders, set the percentage of smokers and non-smokers, the strength of intimacy between the chosen smoker and other smokers, the strength of initimacy between the chosen smoker and non-smokers.

Click GO to run the simulation.

The smoker’s attempt to quit smoking (Quit attempt) is measured by the following equation:

Quit attempt = ∑number of smokers surrounding the randomly chosen smoker* (strength of intimacy with other surrounding smokers)*(-1) + ∑number of non-smokers surrounding the randomly chosen smoker * (strength of intimacy with other surrounding non-smokers)*(+1)

∑ : total numbers of smokers/non-smokers surrounding the chosen smoker. At any
one point, there can only be 8 other agents surrounding the chosen smoker.
(-1) : indicate negative influence another smoker has on the chosen smoker
(+1): indicate positive influence a non-smoker has on the chosen smoker

If Quit attempt is negative, the randomly chosen smoker remains a smoker and does not change his smoking behavior. However, if Quit attempt is positive, then the randomly chosen smoker changes to non-smoker.

In short, a smoker changes to non-smoker when the overall influence of the non-smokers is stronger than the overall influence of the smokers surrounding the chosen smoker.

## HOW TO USE IT

Percentage-of-smokers slider allows you to adjust the percentage of smokers and non-smokers. For example, if you shift the slider to 0.2, this means 20% of the patches will be smokers (black patches).

The Total, Smokers and Non-smokers monitor reflects the total number of smokers and non-smokers together, the total number of smokers and the total number of non-smokers respectively.

Smoker-smoker-strength slider allows you to adjust the strength of intimacy between the chosen smoker and another surrouding smoker. For example, if you shift the slider to 0.1, this means that the strength between the chosen smoker and another smoker is weak.

Nonsmoker-smoker-strength slider allows you to adjust the strength of intimacy between the chosen smoker and a non-smoker. For example, if you shift the slider to 0.9, this means that the strength between the chosen smoker and the non-smoker is strong.

## THINGS TO NOTICE

Observe what happens when there are high percentages of smokers and high Smoker-smoker-strength. When Nonsmoker-smoker-strength is also high, are smokers still able to resist changes or will they be influence to change their behaviors?

Observe what happens when there are low percentages of smokers, low Nonsmoker-smoker-strength but high Smoker-smoker-strength. Are the small numbers of smokers still able to resist changes or will they be influence to change their behaviors?

## THINGS TO TRY

Try different combination of Percentage-of-smokers with different Smoker-smoker strength and Nonsmoker-smoker-strength. For example, high Percentage-of-smokers with high Smoker-smoker strength and high Nonsmoker-smoker strength.

## EXTENDING THE MODEL

The current model focuses only on how smokers' behaviours are being affected. One suggestion would be to add in codes to monitor the non-smokers' behaviors as well. This can give a better overall picture of the interaction between smokers and non-smokers.

## NETLOGO FEATURES

This model focus only on monitoring smokers' behaviors thus the "if" function is used to rule out observations of non-smokers' behaviors in the event a non-smoker is being randomly-chosen.

## CREDITS AND REFERENCES

Väänänen, A., Kouvonen, A., Kivimäki, M., Pentti, J., & Vahtera, J. (2008). Social Support, Network Heterogeneity, and Smoking Behavior in Women: The 10-Town Study. American Journal Of Health Promotion, 22(4), 246-255.

Westmass, J. L., Jones, J. B., & Bauer, J. E. (2010). Social support in smoking cessation: reconciling theory and evidence. Nicotine & Tobacco Research. 12(7), 695-707