Web-based board games are real-time board games that are played using a web browser [1]. Well-known board games including chess, backgammon, monopoly, and dice or poker card games are played online. For example, in Korea, a poker card game called “flower cards” is played using a web browser. However, the characteristics of money differ between web-based board games and internet-based gambling (virtual vs. real). Web-based board gamers use virtual money (i.e., not real money), which can be purchased on the game websites. In Korea, the government has strictly limited the amount of virtual money (up to $500 a month) that users can purchase for playing online board games across the country [2]. However, in some instances, a small number of online board gamers have illegally converted virtual money into real money through illegal websites [3]. Internet-based gamblers use real money, typically through credit card transactions. In Korea, internet-based gambling is illegal. Korean internet-based gamblers access illegal gambling sites to bet real money using their personal computers at home.

In our previous study [4] we compared the characteristics of online board gamers with those of online and offline gamblers; we found that online board gamers have more positive reasons for gaming than internet-based gamblers and offline gamblers. In addition, the behavior of online board gamers was less risky, in terms of gambling patterns, compared to that of offline gamblers, and less introverted, compared to that of internet-based gamblers [5,6]. Based on these results, we suggested that monitoring online board gamers may be an efficient approach to curb illegal gambling.

The first step in the monitoring of online board gamers is screening for risky behaviors. The characteristics of online board gamers, which we referred to as gambling behaviors and psychological status, include impulsivity, mood, and attention [7,8]. Online gamblers are thought to have an introverted personality and depressed mood [8]. Based on an online survey, which included 10,838 internet-based poker players, Gainsbury et al. [9] reported that internet-based poker players showed a greater tendency to “chase their losses” (i.e., seek to recoup lost bets by increasing their subsequent bets) than were offline gamblers. In a review of internet-based poker, factors predictive of excessive internet-based poker playing are suggested to be negative emotions, irrational beliefs, and impulsivity [10]. In addition, internet-based gambling is associated with less verbal communication and fewer consequences regarding a lack of emotional control [11].

Therefore, in this study, three measures including the Center for Epidemiological Studies-Depression Scale [12], Gambling Abstinence Self-efficacy Scale [13], and Korean Gambling Behavior Scale [14] were used to evaluate the emotional state of the participants, the result of the games, and the defense effect of the online gambler, respectively. Based on previous studies, we aimed to develop and verify a web-based board game behavioral scale using a sample of 300 Korean online board gamers to assess the risk of problematic web-based board gaming.

Using a sample of 300 web-based board game users, a behavioral assessment (WBGS) with reasonable reliability and validity was created. Our results revealed that the 10-item WBGS had better internal consistency and validity, compared to those of the 17-item WBGS.

In the current study, the participants showed significant differences in frequency, duration, gaming time, money spent, and social problems between the excessive-user group and general-user group. Notably, the SD of the money spent was larger and the number of users with social problems due to web-based board gaming was higher in the excessive-user group than in the general-user group. These results may be associated with impulsivity [21,22]. The Norwegian government helped gamblers control their impulsivity using limit-setting tools, voluntary self-exclusion, and personalized feedback [22].

The internal consistency (Cronbach’s α=0.89) and test-retest reliability of the WBGS (r=0.77, p<0.001) were relatively good and were accepted as reasonable. The criterion-related validity comparing the high-risk group and low-risk group was also statistically significant. However, the WBGS did not have a good fit in the CFA analysis. With that result, we suggest that the 17-items of WBGS cannot be categorized as one factor.

Based on the EFA, the 17-item WBGS had 3 factors; factor 1 (items 1-9 and items 16-17), factor 2 (items 11-12), and factor 3 (items 13-15). Among them, all the items of the 17-item WBGS achieved acceptable factor loading scores except for items 9 and 10. However, the 10-item WBGS lacked the 5 items extracted from CES-D (items 9-13) and the items of factor 3 (items 13-15) present in the 17-item WBGS; consequently, the internal consistency was higher in the former than in the latter. The five items from CES-D were ruled out due to low factor loading or due to other dimensions associated with the factors in the current study. Many studies on gambling or internetbased games have suggested that mood status is associated with the aggravation of gambling or gaming behaviors [23]. In the WBGS results, mood status assessed according to CES-D was not closely correlated with web-based board gaming. Items 14 and 15 were extracted from the low-risk factors of KGBS. The low-risk factors of KGBS were associated with the positive functions associated with gambling and disinterest in gambling [15,16]. According to these results, individuals playing webbased board games may have different psychological characteristics, compared to those involved in gambling or internet gaming. The words “web-based board” were absent in the sentence extracted from CES-D. This may affect the categorization of the 17 items as three factors. Several studies have suggested that item-wording and the dimensionality in scale could affect the consequences of the survey and response of participants [24-26]. Moreover, Greenberg et al. [25] reported that itemwording in the 10-item Rosenberg Self-Esteem Scale could affect the responses of the survey.

The cut-off point (>22) of the risk-user group for problematic web-based board gamers was obtained using an ROC curve of the 10-item WBGS. In the k-means cluster analysis, the centroid (17.28) and SD (4.27) of the risk-user group for problematic web-based board gamers was almost 22. The cutoff point (>31) of the high-risk group for problematic webbased board gamers was obtained using an ROC curve of the 10-item WBGS. In the k-means cluster analysis, the centroid (33.67) and SD (2.04) of high-risk group for problematic webbased board gamers was almost 31. In both the analyses, the cut-off points elucidated by ROC curves and k-means analyses coincided.

The current study had several limitations. First, because the results of the online surveys are based on a relatively small sample size and low response rate, readers should be cautious when interpreting the results. That is, there might be a small sample bias and nonresponse bias. Second, the participants in the current study were not screened by a structured clinical interview. Psychological status and comorbidities of the participants may have affected the analysis and corresponding results. Future studies should focus on the development of scales that include psychological status and comorbidities.

The current results indicate that the 10-item WBGS appeared to have greater validity than the 17-item WBGS. In addition, we suggest that the 10-item WBGS can be a useful tool for screening individuals with risk or high risk of problematic web-based board gaming behavior. Monitoring web-based board gamers may be important step for preventing illegal internet-based gambling or offline gambling. A web-based board game behavioral scale may be an effective simple screening method for assessing the behavior of excessive online game players.