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By using a standard questionnaire, the level of dental brushing frequency was assessed among 201 adolescent female middle school students in Tehran. The initial assessment was repeated after 5 months, in order to observe the dynamics in dental health behavior level. Logistic Regression model was used to evaluate the correlation among individuals’ dental health behavior in their social network. A significant correlation on dental brushing habits was detected among groups of friends. This correlation was further spread over the network within the 5 months period. Moreover, it was identified that the average brushing level was improved within the 5 months period. Given that there was a significant correlation between social network’s nodes’ in-degree value, and brushing level, it was suggested that the observed improvement was partially due to more popularity of individuals with better tooth brushing habit. Agent Based Modeling (ABM) was used to demonstrate the dynamics of dental brushing frequency within a sample of friendship network. Two models with static and dynamic assumptions for the network structure were proposed. The model with dynamic network structure successfully described the dynamics of dental health behavior. Based on this model, on average, every 43 weeks a student changes her brushing habit due to learning from her friends. Finally, three training scenarios were tested by these models in order to evaluate their effectiveness. When training more popular students, considerable improvement in total students’ brushing frequency was demonstrated by simulation results.

Although many researchers, in different social sciences fields, are being attracted to the new potential promotional phenomenon, the influence of peer connections, the literature in dental public health is very poor. Objective: This article investigates the role of peer influence on individuals’ oral health knowledge and behavior among adolescents. Methods: The purpose of the study was to explore the correlation between secondary school students’ oral health u and knowledge within friendship groups. A valid and reliable questionnaire was developed. A total of 421 students (228 boys and 193 girls) aged between 12-13 years old participated in the study. Ordinal regression analysis was used to identify the correlation between an individual’s oral health knowledge and his/her friends. Results: The results demonstrated a strong relationship between students’ oral health behaviors and their peer connections within their friendship groups at school. Specifically, the tooth brushing frequency of a student had a strong correlation with the similar behavior of his/her friends. Also, investigation of the role of the second level connections (friends of one’s friend with no direct connection) showed a significant correlation in brushing behavior. However, the results revealed no strong correlation of oral health knowledge among friends within their social network. Conclusion: This paper highlighted the importance of the role of peer influence on oral health behavior. Understanding the relationship between oral health behavior and social network would help policymakers for more cost-effective oral health promotion programs among adolescents.

There are some empirical evidences indicating that there is a collective complex oscillatory pattern in the amount of demand for dental visit at society level. In order to find the source of the complex cyclic behavior, we develop an agent-based model of collective behavior of routine dental check-ups in a social network. Simulation results show that demand for routine dental check-ups can follow an oscillatory pattern and the pattern's characteristics are highly dependent upon the structure of the social network of potential patients, the population, and the number of e ective contacts between individuals. Such a cyclic pattern has public health consequences for patients and economic consequences for providers. The amplitude of oscillations was analyzed under di erent scenarios and for di erent network topologies. This allows us to postulate a simulation-based theory for the likelihood observing and the magnitude of a cyclic demand. Results show in case of random networks, as the number of contacts increases, the oscillatory pattern reaches its maximum intensity, for any population size. In case of ringing lattice networks, the amplitude of oscillations reduces considerably, when compared to random networks, and the oscillation intensity is strongly dependent on population. The results for small world networks is a combination of random and ring lattice networks. In addition, the simulation results are compared to empirical data from Google Trends for oral health related search queries in di erent United States cities. The empirical data indicates an oscillatory behavior for the level of attention to dental and oral health care issues. Furthermore, the oscillation amplitude is correlated with town's population. The data fits the case of random networks when the number of e ective contacts is about -for each person. These results suggest that our model can be used for a fraction of people deeply involved in Internet activities like Web-based social networks and Google search.