manipulative intent. In such cases they may ignore persuasive attempts and experience instead a boomerang effect, where they do the opposite of the intended behavi by the persuasive messages or acts(Reinhart et al., 2007). Again, future research should examine this possible explanation Finally, our findings add to the mounting evidence regarding the potential existence of online game addiction(Bruner& Bruner, 2006, Chou Ting, 2003: Kim Klimmt et al., 2009, Park et al., 2007; Qian et al., 2008; Wolfling et al., 2008). The average level of addiction in our study was 2.68. It indicates that most of the samp oblematic levels of this state, but some did (e.g, individuals with average scores of over 6 out of 7). While individuals as addicted or not due to lack of acceptable criteria(Block, 2008), we do see quite a few records with high scores on the addiction scale. This therefore ca further research on this phenomenon, its antecedents, and consequences Practical Implications Our findings can provide guidelines for society to develop more effective ways to reduce the levels of addiction to some applications among adolescents. First, b for reducing these needs should be devised. For example, cities can invest in offline opportunities(e.g, more parks, sports clubs, and community centers) for adolesce interact in real world and reduce the need to escape reality. Focusing on prevention and harm reduction factors, our study indicates that attention switching, rationalization/education, costs, and parental monitoring can all level of addiction(directly, or indirectly through game playing). Thus, parents and teachers(and possibly employers in the case of adults)should(1)encourage and su alternative activities(e.g, sports), (2)educate people about the potential problems of excessive online game playing(e. g, by having classes on the topic), (3)increase erceived cost of playing online games, by for example controlling and monitoring ones allowance, or from a govemment perspective, taxing these games(Ponickie d (4)actively and passively monitor online gamer activities(e. g, by checking game logs). Online service providers and system developers may have a different perspective that could also be informed by our findings. They may be interested play time, because their revenues are often associated with user activity. However, as our findings show, playtime is instrumental to the formation of high levels of ad which can lead to liability issues(Turel Serenko, 2010). Thus, such service providers and developers need to strike a balance: promote playing, but avoid yielding addiction levels. Our model suggests that focusing on parental monitoring can help in this regard. This is the only prevention factor that reduces addiction, without si educing ones play time. Companies can help parents monitor the game playing activities of their kids by implementing features that allow online tracking. For exam Leapfrog allows parents to follow their kids activities and record their progress in different games, via their website. Additionally, companies may develop and provi with parental monitoring guidelines and best practices when they purchase or subscribe to a game. This strategy may have limited success, though, because parents m always be involved in game purchasing/ subscription decisions of adolescents While three functional needs were identified as the basis for game playing and ultimately for the formation of high levels of addiction, only need increase play time, but not addiction. Thus, online game developers may focus on this need, and help users create and optimize their characters in online games, and t performance. For example, they can make it easier to create and update one's character from any device, improve the ease of use of the interface, and provide text me garding the performance and relative standing of characters. Game developers may also cater to other user needs, for example by promoting interactive features bety gamers, because these can address the need for relationship and possibly escapism. Nevertheless, as our study shows, they should be aware because these may come leading to addiction, for which they may be held liable. Limitations and future research Several limitations should be acknowledged, together with the research directions they point to. First, we considered only a limited set of functional needs and revention/harm reduction factors in this study. Additional motivating factors can be included such that more variation is explained; for example, personality( Charlt Danforth, 2010), individual differences(Kim et al., 2008), demographic and socioeconomic factors(Hur, 2006)and elements in one's environment(e.g, family or scl elationships)(Tyas& Pederson, 1998). Similarly, additional prevention and harm reduction factors should be considered. These may include government policies regulation, and parent-child relationship management(Benowitz, 2008; Hatsukami et al., 2004; Marlatt, 1996; Weeks et al., 1998). Furthermore, additional factors with addiction, such as IS habit(Limayem et al, 2007)may be included in future research to further develop the nomological network of online game addiction. Second, based on our findings, dissuasion and resource restriction are not good strategies for addiction reduction among adolescents. But, caution should be exer As mentioned in the theoretical implications section, our design fails to distinguish between pre-addiction prevention and potential harm reduction factors, and post-a interventions. Different research designs that focus on this distinction can be employed to better understand the efficacy of the abovementioned techniques. Third, our findings are based on a sample of adolescents collected in one country. To increase the generalizability of the findings, future research should replicat lel with different samples- varying by at least age and geography (Lee Baskerville, 2003). Also, our sample had access to a limited and varying set of onlin pes of games(e.g, Finally, our findings provide imperfect support for the proposed causality, and limited explanation for the observed phenomena. For example, game playing coul antecedent and a consequence(symptom) of online game addiction. Future research should employ other designs (longitudinal, qualitative, etc. )to provide evidencemanipulative intent. In such cases they may ignore persuasive attempts and experience instead a boomerang effect, where they do the opposite of the intended behavio by the persuasive messages or acts (Reinhart et al., 2007). Again, future research should examine this possible explenation. Finally, our findings add to the mounting evidence regarding the potential existence of online game addiction (Bruner & Bruner, 2006; Chou & Ting, 2003; Kim Klimmt et al., 2009; Park et al., 2007; Qian et al., 2008; Wolfling et al., 2008). The average level of addiction in our study was 2.68. It indicates that most of the samp plausibly the adolescent population) had no problematic levels of this state, but some did (e.g., individuals with average scores of over 6 out of 7). While we cannot c individuals as addicted or not due to lack of acceptable criteria (Block, 2008), we do see quite a few records with high scores on the addiction scale. This therefore ca further research on this phenomenon, its antecedents, and consequences. Practical Implications Our findings can provide guidelines for society to develop more effective ways to reduce the levels of addiction to some applications among adolescents. First, b social deficiencies expressed as need for relationship and escapism are important drivers of excessive online game playing and addiction, from a society’s perspective for reducing these needs should be devised. For example, cities can invest in offline opportunities (e.g., more parks, sports clubs, and community centers) for adolesce interact in real world and reduce the need to escape reality. Focusing on prevention and harm reduction factors, our study indicates that attention switching, rationalization/education, costs, and parental monitoring can all level of addiction (directly, or indirectly through game playing). Thus, parents and teachers (and possibly employers in the case of adults) should (1) encourage and su alternative activities (e.g., sports), (2) educate people about the potential problems of excessive online game playing (e.g., by having classes on the topic), (3) increase perceived cost of playing online games, by for example controlling and monitoring one’s allowance, or from a government perspective, taxing these games (Ponicki e and (4) actively and passively monitor online gamer activities (e.g., by checking game logs). Online service providers and system developers may have a different perspective that could also be informed by our findings. They may be interested in increasi play time, because their revenues are often associated with user activity. However, as our findings show, playtime is instrumental to the formation of high levels of ad which can lead to liability issues (Turel & Serenko, 2010). Thus, such service providers and developers need to strike a balance: promote playing, but avoid yielding h addiction levels. Our model suggests that focusing on parental monitoring can help in this regard. This is the only prevention factor that reduces addiction, without sig reducing one’s play time. Companies can help parents monitor the game playing activities of their kids by implementing features that allow online tracking. For exam Leapfrog allows parents to follow their kids’ activities and record their progress in different games, via their website. Additionally, companies may develop and provi with parental monitoring guidelines and best practices when they purchase or subscribe to a game. This strategy may have limited success, though, because parents m always be involved in game purchasing/ subscription decisions of adolescents. While three functional needs were identified as the basis for game playing and ultimately for the formation of high levels of addiction, only need for mechanics s increase play time, but not addiction. Thus, online game developers may focus on this need, and help users create and optimize their characters in online games, and t performance. For example, they can make it easier to create and update one’s character from any device, improve the ease of use of the interface, and provide text me regarding the performance and relative standing of characters. Game developers may also cater to other user needs, for example by promoting interactive features betw gamers, because these can address the need for relationship and possibly escapism. Nevertheless, as our study shows, they should be aware because these may come a leading to addiction, for which they may be held liable. Limitations and future research Several limitations should be acknowledged, together with the research directions they point to. First, we considered only a limited set of functional needs and prevention/harm reduction factors in this study. Additional motivating factors can be included such that more variation is explained; for example, personality (Charlto Danforth, 2010), individual differences (Kim et al., 2008), demographic and socioeconomic factors (Hur, 2006) and elements in one’s environment (e.g., family or sch relationships) (Tyas & Pederson, 1998). Similarly, additional prevention and harm reduction factors should be considered. These may include government policies, in regulation, and parent-child relationship management (Benowitz, 2008; Hatsukami et al., 2004; Marlatt, 1996; Weeks et al., 1998). Furthermore, additional factors ass with addiction, such as IS habit (Limayem et al., 2007) may be included in future research to further develop the nomological network of online game addiction. Second, based on our findings, dissuasion and resource restriction are not good strategies for addiction reduction among adolescents. But, caution should be exer As mentioned in the theoretical implications section, our design fails to distinguish between pre-addiction prevention and potential harm reduction factors, and post-a interventions. Different research designs that focus on this distinction can be employed to better understand the efficacy of the abovementioned techniques. Third, our findings are based on a sample of adolescents collected in one country. To increase the generalizability of the findings , future research should replicat the model with different samples – varying by at least age and geography (Lee & Baskerville, 2003). Also, our sample had access to a limited and varying set of onlin may be desirable to see how our model is attuned when focusing on different types of games (e.g., violent vs. non-violent games). Finally, our findings provide imperfect support for the proposed causality, and limited explanation for the observed phenomena. For example, game playing coul antecedent and a consequence (symptom) of online game addiction. Future research should employ other designs (longitudinal, qualitative, etc.) to provide evidence i