007). It is therefore reasonable to expect that stronger parental monitoring(through asking probing questions, placing the computer in an observable spot, tracking a whereabouts, showing interest in school performance etc. )will reduce ones playing time, and prevent higher levels of online gaming addiction. Hen H7a: Parental monitoring reduces online game playing H7b: Parental monitoring reduces the level of addiction to online games Individual's perceptions regarding the availability of resources(e. g, technical support)influence their usage of information systems(Taylor Todd, 1995). The applies to online games(Blakely et al., 2010). In this context resources, such as play time, funding, and equipment, can be constrained by parents/ guardians and teacl ase of adolescents, or by employers, life circumstances, and family members in the case of more mature individuals. Such constraints can reduce one's access to onli for example, by restricting playing time. Free time is associated with more frequent playing of online games(Wan& Chiou, 2006), and hence, by restricting it one co person's use time and levels of addiction. In many cases, other resources are also needed (e.g, money, network access, fast computers)(Jeong& Kim, 2007); and by ogic, if these are constrained, one s play time and level of addiction should be diminished. Hence: H8a: Resource restriction reduces online game playing. H8b: Resource restriction reduces the level of addiction to online games Prevention and harm reduction strategies focusing on increasing substance prices can diminish substance problems(Mosher, 1999; Ponicki et al, 2007). The san nould apply to potentially problematic use of information systems, and specifically online games. The perceived cost of using an IT artifact or service is an importan determinant of IS use because it influences its perceived value(Turel et al., 2007). If this cost is increased, the perceived benefits seem lower compared to the costs, a subsequently use is reduced (Turel et al., 2010). Thus, we expect that the perceived cost of online games should reduce one's willingness to play games, and his or a Note that in the Chinese online gaming market, gamers can incur any combination of four types of costs. One type of games is free of charge at lower levels, but dvance in the game they need point-cards which they can buy at stores. Another family of games is also free of charge, but gamers may need to purchase virtual prop o do better in these games. Regardless, a third type of cost is very common among adolescents in China. Many of them do not have computers at home, and even if ti lay want to socialize and/or avoid parental monitoring. Thus, the use of Intemet cafes for gaming purposes is very popular. The fees for Internet cafes are therefore a they may face. Lastly, even if a person has a computer, he or she may need to purchase special gamming gears and pay for high speed Internet connection. Thus, the ases there is some cost involved in online gaming, which is the basis for perceived cost assessments. H9a: Perceived cost reduces online game playing. H9b: Perceived cost reduces the level of addiction to online games The hypotheses translate into the nomological network presented in Figure I Figure 1 Research Model Methods A paper-based survey was used for data collection. The survey (see Appendix A[lD was developed through a simplified process of survey translation and adapta et al., 2000, Geisinger, 1994)which involved item generation, synthesis, forward and backward translation, and review. Whenever possible, valid existing scales were adjusting them to the context of online game playing, le scales were developed based on concepts described in the literature Content validity was established
2007). It is therefore reasonable to expect that stronger parental monitoring (through asking probing questions, placing the computer in an observable spot, tracking a whereabouts, showing interest in school performance etc.) will reduce one’s playing time, and prevent higher levels of online gaming addiction. Hence: H7a: Parental monitoring reduces online game playing. H7b: Parental monitoring reduces the level of addiction to online games. Individual's perceptions regarding the availability of resources (e.g., technical support) influence their usage of information systems (Taylor & Todd, 1995). The applies to online games (Blakely et al., 2010). In this context resources, such as play time, funding, and equipment, can be constrained by parents/ guardians and teach case of adolescents, or by employers, life circumstances, and family members in the case of more mature individuals. Such constraints can reduce one’s access to onli for example, by restricting playing time. Free time is associated with more frequent playing of online games (Wan & Chiou, 2006), and hence, by restricting it one co person’s use time and levels of addiction. In many cases, other resources are also needed (e.g., money, network access, fast computers) (Jeong & Kim, 2007); and by t logic, if these are constrained, one’s play time and level of addiction should be diminished. Hence: H8a: Resource restriction reduces online game playing. H8b: Resource restriction reduces the level of addiction to online games. Prevention and harm reduction strategies focusing on increasing substance prices can diminish substance problems (Mosher, 1999; Ponicki et al., 2007). The sam should apply to potentially problematic use of information systems, and specifically online games. The perceived cost of using an IT artifact or service is an importan determinant of IS use because it influences its perceived value (Turel et al., 2007). If this cost is increased, the perceived benefits seem lower compared to the costs, a subsequently use is reduced (Turel et al., 2010). Thus, we expect that the perceived cost of online games should reduce one’s willingness to play games, and his or ad levels. Note that in the Chinese online gaming market, gamers can incur any combination of four types of costs. One type of games is free of charge at lower levels, but advance in the game they need point-cards which they can buy at stores. Another family of games is also free of charge, but gamers may need to purchase virtual prop to do better in these games. Regardless, a third type of cost is very common among adolescents in China. Many of them do not have computers at home, and even if th may want to socialize and/or avoid parental monitoring. Thus, the use of Internet cafes for gaming purposes is very popular. The fees for Internet cafes are therefore a they may face. Lastly, even if a person has a computer, he or she may need to purchase special gamming gears and pay for high speed Internet connection. Thus, the cases there is some cost involved in online gaming, which is the basis for perceived cost assessments. H9a: Perceived cost reduces online game playing. H9b: Perceived cost reduces the level of addiction to online games. The hypotheses translate into the nomological network presented in Figure 1. Figure 1 Research Model Methods A paper-based survey was used for data collection. The survey (see Appendix A[1]) was developed through a simplified process of survey translation and adapta et al., 2000; Geisinger, 1994) which involved item generation, synthesis, forward and backward translation, and review. Whenever possible, valid existing scales were adjusting them to the context of online game playing, and some scales were developed based on concepts described in the literature. Content validity was established
literature review, interviews and panel discussions(described below). Published papers on game addiction, and intervention and prevention of various addictions w to prepare a broad understanding of the concepts, and a list of candidate items for new scale Several steps were then taken in order to make the survey suitable to adolescent game players. First, a semi-structured open-ended face to face interview was cor Two authors interviewed a convenience sample of three university students and two high school students who were highly engaged in online game playing. Each inte minutes. The interviews elicited gamers game playing history, patterns, motivations, and inhibitors, and opinions on and suggestions regarding our measure vo authors interviewed in a similar process a convenience sample of three high-school teachers and three parents, to better understand the prevention and harm reduc they have employed. Third, a focus group of six students( three university students and three high school students )was formed to validate the insights steps, and the measures that were formulated and refined throughout this process. This discussion was moderated by one of the authors and lasted about an hour. Last professors who are familiar with this line of research were invited to evaluate the questionnaire. Minor modifications were applied based on their feedback. The instrument based on all of these inputs was first drafted in English, and then translated into Chinese independently and cross checked by two of the authors v proficient in both languages. After receiving comments from game players for modification and clarification, the finally agreed Chinese version was then translated b English independently by these two authors to check for inaccuracies. Several adjustments were applied to the original version until the authors all agreed that the iter accurately reflect the intention of the measurement. All of the motivation constructs as well as Rationalization/ Education, Dissuasion and Cost prevention were opera reflective latent variables. The Attention Switching, Parental Monitoring and Resource Restriction constructs were operationalized as formative composite variable questionnaire also captured respondents gender and age. Below we provide details on the different measurement scales Online Game addiction: We follow Charlton and Danforth(2005)'s criteria, according to which technology addiction is captured by the magnitude of key symp havioral salience, conflict, withdrawal, and relapse/reinstatement. The measure has been reliable( Charlton, 2002: Charlton Danforth, 2007, Charlton danfort hence we use it. Four motivation factors based on the functional needs online game playing addresses were measured by a total 17 items with reference to prior research. These f Need for- Advancement, Mechanics, Relationship, and Escapism. Reflective scales that capture these concepts were adapted from Yee(2006) There were no well established measures for some of the prevention and harm reduction factors. We hence developed these scales utilizing extant frameworks fo development(Sweeney Soutar, 2001)as described above. Synthesizing inputs from academics, university and high school students with insight from the literature following measurement instruments were developed. All used a seven point Likert-type scale ranging from"completely disagree" to"completely agree Dissuasion: It was conceptualized as a reflective scale and measured with four items from Babor(1994), as reinforced by expert-matter interviewees and focus g Rationalization/ Education: We developed a four-item reflective scale based on the definition from Eisen et al. (2002; Eisen et al., 2003)which were then adju feedback from the expert-matter interviewees and focus groups Perceived Cost: We adopt the five- item scale from Wu and Wang(2005) Attention switching: This construct was conceptualized as a second-order factor consisting of two first order constructs: Inner Attention switching and External switching, each component factor is important, but not individually sufficient, for reflecting the latent construct. If addicted players participate in meaningful activitie higher priority over game-playing, their addiction-driven behavior will be restrained (Wan Chiou, 2006). These activities can come from internal sources (e.g,inte babies)or extemal forces(e.g, attending family events). Thus, the attention is shifted away from the addiction-driven behavior using two mechanisms: intemal and Expert-matter interviewees and focus groups assisted in adjusting this concept and items Parental monitoring: Based on the definition and our interviews with expert online gamers, parental monitoring can be active or passive. Passive monitoring ir getting some information, but not necessarily"spying" on one s children. In contrast, active monitoring includes more hands-on approaches to monitoring and ensurin boundaries set-up are not infringed. Following this conceptualization we operationalized parental monitoring as a second-order composite which includes two first or onstructs, PM Passive and PM Active. We adopt 6 scale items from Dishion and McMahon(1998)as modified based on comments from our expert game players. Resource Restriction: We developed four items that captured strictions users observe, based on key resource concems discussed in the literature: guidance quipment, and network connection availability(e.g, Jeong& Kim, 2007, Wan Chiou, 2006). The items were refined using inputs from the panels of experts. Thes focused on tangible resources, and not on time resources because it was assumed that time constraints are captured by internal and external attention switching activit time ts of this behavior, including the longest online playing time and the percentage online game playing occupies one Based on inputs from the panel these items best reflect the extent to which they are engaged in online game playing Pilot Test a pilot test was conducted to assess the scales. a total of 163 records were collected from adolescent online game players. They were recruited from a middle sc large city in China. Their ages ranged from 13 to 15. The data were used to run an array of reliability and factor analysis tests. A number of modifications were made nstrument based on feed back from respondents and reliability tests. The four subcomponents of motivation factors, advancement, mechanics, relationship, and escap obtained Cronbach's alphas of0.95, 0.71, 0.87 and 0.70 respectively. The addiction factor yielded a Cronbach's alpha of 0.83
literature review, interviews and panel discussions (described below). Published papers on game addiction, and intervention and prevention of various addictions were to prepare a broad understanding of the concepts, and a list of candidate items for new scales. Several steps were then taken in order to make the survey suitable to adolescent game players. First, a semi-structured open-ended face to face interview was con Two authors interviewed a convenience sample of three university students and two high school students who were highly engaged in online game playing. Each inte about 30 minutes. The interviews elicited gamers’ game playing history, patterns, motivations, and inhibitors, and opinions on and suggestions regarding our measure two authors interviewed in a similar process a convenience sample of three high-school teachers and three parents, to better understand the prevention and harm reduc they have employed. Third, a focus group of six students (three university students and three high school students) was formed to validate the insights gathered in the steps, and the measures that were formulated and refined throughout this process. This discussion was moderated by one of the authors and lasted about an hour. Last professors who are familiar with this line of research were invited to evaluate the questionnaire. Minor modifications were applied based on their feedback. The instrument based on all of these inputs was first drafted in English, and then translated into Chinese independently and cross checked by two of the authors w proficient in both languages. After receiving comments from game players for modification and clarification, the finally agreed Chinese version was then translated b English independently by these two authors to check for inaccuracies. Several adjustments were applied to the original version until the authors all agreed that the item accurately reflect the intention of the measurement. All of the motivation constructs as well as Rationalization/ Education, Dissuasion and Cost prevention were opera as reflective latent variables. The Attention Switching, Parental Monitoring and Resource Restriction constructs were operationalized as formative composite variable questionnaire also captured respondents’ gender and age. Below we provide details on the different measurement scales. Online Game addiction: We follow Charlton and Danforth (2005)’s criteria, according to which technology addiction is captured by the magnitude of key symp behavioral salience, conflict, withdrawal, and relapse/reinstatement. The measure has been reliable (Charlton, 2002 ; Charlton & Danforth, 2007; Charlton & Danfort hence we use it. Four motivation factors based on the functional needs online game playing addresses were measured by a total 17 items with reference to prior research. These f Need for - Advancement, Mechanics, Relationship, and Escapism. Reflective scales that capture these concepts were adapted from Yee (2006). There were no well established measures for some of the prevention and harm reduction factors. We hence developed these scales utilizing extant frameworks fo development (Sweeney & Soutar, 2001) as described above. Synthesizing inputs from academics, university and high school students with insight from the literature, following measurement instruments were developed. All used a seven point Likert-type scale ranging from “completely disagree” to “completely agree”. Dissuasion: It was conceptualized as a reflective scale and measured with four items from Babor (1994), as reinforced by expert-matter interviewees and focus g Rationalization/ Education: We developed a four-item reflective scale based on the definition from Eisen et al. (2002; Eisen et al., 2003) which were then adjus feedback from the expert-matter interviewees and focus groups. Perceived Cost: We adopt the five- item scale from Wu and Wang (2005). Attention switching: This construct was conceptualized as a second-order factor consisting of two first order constructs: Inner Attention switching and External switching; each component factor is important, but not individually sufficient, for reflecting the latent construct. If addicted players participate in meaningful activitie higher priority over game-playing, their addiction-driven behavior will be restrained (Wan & Chiou, 2006). These activities can come from internal sources (e.g., inte hobbies) or external forces (e.g., attending family events). Thus, the attention is shifted away from the addiction-driven behavior using two mechanisms: internal and Expert-matter interviewees and focus groups assisted in adjusting this concept and items. Parental monitoring: Based on the definition and our interviews with expert online gamers, parental monitoring can be active or passive. Passive monitoring in getting some information, but not necessarily “spying” on one’s children. In contrast, active monitoring includes more hands-on approaches to monitoring and ensurin boundaries set-up are not infringed. Following this conceptualization we operationalized parental monitoring as a second-order composite which includes two first or constructs, PM_Passive and PM_Active. We adopt 6 scale items from Dishion and McMahon (1998) as modified based on comments from our expert game players. Resource Restriction: We developed four items that captured the restrictions users observe, based on key resource concerns discussed in the literature: guidance equipment, and network connection availability (e.g., Jeong & Kim, 2007; Wan & Chiou, 2006). The items were refined using inputs from the panels of experts. Thes focused on tangible resources, and not on time resources because it was assumed that time constraints are captured by internal and external attention switching activit consume users’ time. Game playing: We focused on relevant aspects of this behavior, including the longest online playing time and the percentage online game playing occupies one’ Based on inputs from the panel these items best reflect the extent to which they are engaged in online game playing. Pilot Test A pilot test was conducted to assess the scales. A total of 163 records were collected from adolescent online game players. They were recruited from a middle sc large city in China. Their ages ranged from 13 to 15. The data were used to run an array of reliability and factor analysis tests. A number of modifications were made instrument based on feedback from respondents and reliability tests. The four subcomponents of motivation factors, advancement, mechanics, relationship, and escap obtained Cronbach’s alphas of 0.95, 0.71, 0.87 and 0.70 respectively. The addiction factor yielded a Cronbach’s alpha of 0.83