Background:Term of doing computer games among teenagers is growing rapidly. This popular phenomenon can cause physical and psychosocial issues in them. Therefore, this study examined the relationship between computer games and quality of life domains in adolescents aging 12-15 years.Materials and Methods:In a cross-sectional study using the 2-stage stratified cluster sampling method, 444 male and female students in Borkhar were selected. The data collection tool consisted of 1) World Health Organization Quality Of Life – BREF questionnaire and 2) personal information questionnaire. The data were analyzed by Pearson correlation, Spearman correlation, chi-square, independent t-tests and analysis of covariance.Findings:The total mean score of quality of life in students was 67.11±13.34. The results showed a significant relationship between the age of starting to play games and the overall quality of life score and its fourdomains (range r=–0.13 to –0.18). The mean of overall quality of life score in computer game users was 68.27±13.03 while it was 64.81±13.69 among those who did not play computer games and the difference was significant (P=0.01). There were significant differences in environmental and mental health domains between the two groups (P<0.05). However, there was no significant relationship between BMI with the time spent and the type of computer games.Conclusion:Playing computer games for a short time under parental supervision can have positive effects on quality of life in adolescents. However, spending long hours for playing computer games may have negative long-term effects.

The design of agile supply chain networks has attracted more attention in recent years according to the competitive business environment. Further, due to high degree of uncertainty in agile supply chains (SCs), developing robust and efficient decision making tools are of interest. In this study, an integrated approach based on principal component analysis (PCA) and multiobjective possibilistic mixed integer programming (MOPMIP) approaches is proposed to optimally design agile supply chain network under uncertainty. The PCA method is used for ranking and filtering the suppliers, constituting the first layer of the supply chain, based on agility criteria. The proposed MOPMIP model is employed to construct the agile supply chain network under uncertainty. In the proposed MOPMIP model, three objective functions including 1) total costs minimization, 2) total delivery time minimization and 3) maximization of flexibility are considered. An interactive fuzzy solution approach is used to solve the proposed MOPMILP model. Two numerical examples, is conducted to evaluate the performance and efficiency of the proposed integrated approach for agile supply chain network design under uncertainty.

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