Sigerson, Li, Cheung, Luk, & Cheng, 2017; Wenzel,Bakken, Johansson, Götestam, & Øren, 2009). The firstaim of this study is to investigate the prevalence of probableIGD among community-dwelling adults in Macao, Chinaaccording to the DSM-5 criteria (APA, 2013).Psychological distress such as depression and anxiety hasbeen proposed to be a predispositional factor of Internet-related addictions, including IGD (Davis, 2001). People withhigher psychopathology are more vulnerable to these addic-tions due to multiple plausible mechanisms such as fewerpsychosocial resources and the desire to escape from emo-tional difficulties (Ko, Yen, Chen, Yeh, & Yen, 2009;Wu, Li,Lau, Mo, & Lau, 2016). Previous research showed thatdepression, anxiety, social phobia, cognitive functioning, andoverall psychological or internalizing problems were posi-tively associated with gaming addictions among students,online gamers, and pathological gamblers (Jiménez-Murciaet al., 2014; Müller et al., 2015; Stockdale & Coyne, 2018;Wei, Chen, Huang, & Bai, 2012). The second aim of thisstudy is to test if the positive association between psycho-logical distress (depression and anxiety symptoms) and IGDtendency can be replicated in a representative sample ofcommunity-dwelling adults to inform interventions.In addition to the risk factors for IGD, such as psychologi-cal distress, an examination of protective factors is alsowarranted, because many individuals who are at risk for IGDdue to the presence of particular risk factors do not developIGD. According to positive psychology, character strengthsuch as psychological resilience and purpose in life would notonly help one to flourish, but also protect one againstdeveloping addictions (Krentzman, 2013). Psychologicalresilience is defined as an ego strength, which helps one tonot only rebound from but also thrive in adverse situations(Lee et al., 2013); purpose in life is regarded as living withreasons and objectives (Ryff, 1995). These two characterstrength variables have been demonstrated to be negativelyassociated with both psychosocial problems (e.g., loneliness,stress, and anxiety) and addictive behaviors (Fumaz et al.,2015; Harlow, Newcomb, & Bentler, 1986; Hou et al., 2017;Wu, Lei, & Ku, 2013). Their protective effects against IGDhave not yet been tested and reported in the existing literature.The third aim of this study is to fill in this research gap, andwe tested the hypothesis that the psychological resilience andthe purpose in life would be negatively correlated with IGDtendency. Previous studies also reported that psycho-logical resilience buffered the effect of an individual riskfactor (e.g., childhood abuse) on an addictive behavior(e.g., drug use and problematic social networking use; Houet al., 2017; Wingo, Ressler, & Bradley, 2014). This study,therefore, also tested whether the potential buffering effect ofthe two variables of character strength would also attenuatethe relationship between psychological distress and IGD.To our best knowledge, this study is the first empiricalattempt to estimate the prevalence of IGD among Chineseadults. Given that previous research attention was mainly onadolescents and studies of IGD in general adult populationswere scarce in both the West and the East, we also aimed totest psychological risk (i.e., depression and anxiety) andprotective (i.e., psychological resilience and purpose in life)factors of IGD among community-dwelling adults. In thisstudy, the following hypotheses were tested:Hypothesis 1: A positive association exists between psy-chological distress (i.e., depression and anxiety) and IGD.Hypothesis 2: A negative association exists between char-acter strength (i.e., psychological resilience and purpose inlife) and IGD.Hypothesis 3: Psychological resilience and purpose in lifeattenuate the positive association between psychologicaldistress and IGD.METHODSProcedures and respondentsAfter obtaining ethical approval from the affiliated univer-sity of the corresponding author, the telephone survey wasconducted in 2016 (October–November) in Macao, China.We randomly sampled telephone numbers from the 2015Macao residential phonebook. At the household level, weselected Chinese residents, who were 18 years old or abovefollowing the “last birthday” rule. Each interview lastedapproximately 12 min. The participation of the respondentswas voluntary and no monetary reward was involved. Noexclusion criteria were set and there were 1,000 respondentsparticipated in and completed the survey on the phone. Withreference to the formula of the American Association forPublic Opinion Research (2011), the cooperation rate of thisstudy was 61.8%.The sample consisted of 440 males (44%, 95% CI [40.9,47.1]) and 560 females (56%, 95% CI [52.9, 59.1]) with amean age of 40.0 years (SD= 15.3; range = 18–97). Themajority of the respondents had senior secondary (27%)and tertiary education (41%). About 67% of the respon-dents were full-time or part-time workers. Sex and agedistribution of the present sample was similar to the popu-lation parameters reported in the 2016 Population By-census of Macao (Macao Statistics and Census Services,2017), while taking into account that our sample includedonly those aged ≥18 years. In this sample, 47.3% hadengaged in online gaming in the past 12 months and wereclassified as “recent gamers.”MeasuresIGD. The nine diagnostic criteria for IGD listed in theDSM-5 (APA, 2013) were used to assess IGD tendency andidentify probable IGD in this study. These criteria havebeen used in previous research for the same purpose (Wu,Lai, Yu, & Tong, 2017; Yu & Cho, 2016). Only respon-dents who were recent gamers were asked to indicatewhether each of these symptoms (e.g., preoccupation withInternet games) described their own condition in the past12 months (0= no, 1= yes). Internal consistency (KR-20)of these items was 0.69 for the current sample. A greaterlevel of IGD symptoms indicated a greater tendency to haveIGD. Moreover, a cut-off of 4/5 was suggested in Ko et al.’sstudy (2014), which examined the diagnostic validity of theDSM-5 IGD items with a sample of Taiwanese youngadults.Journal of Behavioral Addictions 7(1), pp. 62–69 (2018) | 63Adult Internet gaming disorder
Psychological distress. Depression and anxiety symp-toms were measured with the two 7-item subscales from theChinese version of the 21-item Depression Anxiety StressScales (DASS-21; Moussa, Lovibond, & Laube, 2001);items were scored on a 4-point Likert scale, in which0= did not apply to me at all and 3 = applied to me verymuch or most of the time. Higher scores represented higherseverity with respect to the corresponding psychologicalproblem. The Cronbach’s α were .82 and .79 for thedepression and anxiety subscales, respectively, in thisstudy.Psychological resilience. The Connor–Davidson Resil-ience Scale (Connor & Davidson, 2003) has been validatedin various Chinese populations. In this study, the10-item Chinese version (Wang, Shi, Zhang, & Zhang,2010) was used. A sample item was “You are not easilydiscouraged by failure,” with a 5-point scale from 0= nottrue at all to 4= true nearly all the time. A higher scale scoreindicates higher resilience. The Cronbach’s α was .90in this study.Purpose in life. The 6-item Purpose in Life Scale(PIL; Crumbaugh & Maholick as cited in McKenna &West, 2007) was used to assess perceived life purpose andmeaning. It has been used with Chinese adults (Wu et al.,2013). The respondents were asked to rate if they had foundsatisfying goals and purpose in life, on a 5-point Likertresponse scale (1 = strongly disagree to 4= stronglyagree). A higher score indicated a more positive perceptionof one’s life purpose. The Cronbach’s α was .82 in thisstudy.Background variables. We asked the respondents toreport their age, sex, educational level, and employmentstatus [i.e., full-time, part-time, student, and other types(e.g., homemaker and retired)]. Regarding online gamingbehaviors, only recent gamers were asked to reportweekly gaming frequency [1 = seldom, 2= occasionally,3= several times a week, 4= almost everyday (less than1 hr per day), and 5= everyday (2 hr or above per day)],any online gaming expense in the past 12 months (yes/no),and favorite game type (multiplayer/single player).Statistical analysisWe first examined all the respondents’ gaming and demo-graphic profiles in the overall sample and categorized theoverall sample into different subsamples (i.e., recent gamervs. non-gamer and probable IGD gamer vs. non-IGDgamer). Because some of the variables were ordinallyscaled (e.g., education attainment) or skewed (e.g., age),they were analyzed by non-parametric statistical proce-dures, including the χ2 tests, Mann–Whitney U tests, andKruskal–Wallis tests.We subsequently estimated the prevalence of IGDamong gamers using DSM-5 criteria and further exploredpotential risk factors contributing to IGD with univariate χ2tests and Mann–Whitney U tests for demographic factorsand t-tests and logistical regressions for psychologicalfactors. Finally, we examined the potential moderatingeffects of psychological resilience and purpose in life onthe relationship between psychological distress and IGDusing PROCESS macro (Hayes, 2012) in SPSS 22.0.EthicsTelephone interviewers received data-collection trainingand performance assessment, which were conducted bythe investigators of this study, before the telephone surveywas implemented. The respondents were interviewed bythese trained telephone interviewers on the phone after theywere briefed on the study’s purpose and their rights ofparticipation. They also gave their informed consent toparticipate. The study was proposed and conducted by theresearch team involving clinical, social, and health psy-chologists as well as an epidemiologist, who are experi-enced in behavioral addiction research. The procedures,including data collection and analyses, were carried out inaccordance with the Declaration of Helsinki. Ethicalapproval (ref. no.: MYRG2015-00213-FSS) was obtainedfrom the affiliated university of the corresponding author.RESULTSOnline gaming profiles of this sampleOverall sample (N= 1,000). Table 1 shows that recentgamers (who engaged in online games in the past 12 months)were more likely to be male, younger, and with highereducational attainment (p< .05) than non-gamers. Studentswere also more likely to be recent gamers than full-timeemployees (OR= 3.31), part-time employees (OR= 2.14),or other types (OR= 10.43). Part-time employees weremore likely to be recent gamers than full-time employees(OR= 1.55) or other types (OR= 4.87).Regarding psychological distress, 10.7% (95% CI [8.7,12.7]) of the respondents reported moderate or abovelevels of depression (DASS-Depression ≥14), whereas19.9% (95% CI [17.3, 22.5]) reported moderate or aboveanxiety levels (DASS-Anxiety ≥10). Depression and anxietysymptoms were negatively correlated with psychologicalresilience (Pearson’s r=−.31 and −.22, respectively,p< .001) and purpose in life (Pearson’s r=−.32 and −.23,respectively, p< .001). Recent gamers did not significantlydiffer from their counterparts on psychological distress orresilience (p> .05), but they reported significantly lowerscores regarding purpose in life (p= .004).Gamer sample (n= 473). Some statistically significantdemographic differences were observed on gaming-relatedvariables. Gamers who were male (Mann–WhitneyU= 22,919.0, z=−2.85, p= .004), younger (Spearman’srank correlation ρ=−.16, p= .001), and more educated[Kruskal–Wallis H(5)= 12.70, p= .03] were more likelyto report higher weekly gaming frequency. Gamers whowere male and younger were also more likely to spendmoney on gaming [χ2(1)= 28.27, p< .001, OR= 3.56, andMann–Whitney U= 13,658.0, z=−3.46, p= .001, respec-tively]. Employment status was significantly associatedwith gaming expense [χ2(3)= 13.02, p= .005], and part-time employees were more likely to spend money ongaming than full-time employees, students, and other types(OR= 2.33, 2.39, and 7.20, respectively).Multiplayer games were more preferred by males[χ2(1)= 32.87, p< .001, OR= 3.38] and younger gamers64 | Journal of Behavioral Addictions 7(1), pp. 62–69 (2018)Wu et al.
(Mann–Whitney U= 10,782.5, z=−6.59, p< .001). Part-time employees also tended to prefer multiplayer gamesthan students [χ2(3)= 16.34, p= .001, OR= 1.80], whoshowed stronger preference to multiplayers gamesthan full-time employees (OR= 1.91) and other types(OR= 2.12).Estimating prevalence of Internet gaming disorder amongrecent gamers (n= 473)The frequency of endorsement on each DSM-5 criterionfor IGD is listed in Table 2. The most commonly endorseditems were mood modification (i.e., use Internet games toescape or relieve a negative mood; 26.2%) and continuedexcessive use (i.e., continue to play Internet games exces-sively despite knowledge of psychosocial problems;24.1%).Forty-six respondents, who were recent gamers,answered “uncertain” or refused to answer at least one itemof the DSM-5 criteria, and the rate of these missingresponses ranged from 0.4% to 4.2%. After removing fiveunidentified cases with missing IGD items, the subsequentanalyses retained three IGD cases that scored 5 or above ononly the answered items and 39 non-IGD cases that scored 4or below even when all the missing items were endorsed. Asa result, 20 respondents were classified as probable IGDgamers among 468 recent gamers, which accounted for anIGD prevalence as 4.3% (95% CI [2.4, 6.1]). Consideringthe overall sample (N= 1,000), the IGD prevalence was2.0% (95% CI [1.1, 2.9]).Examining the potential risk factors of Internet gamingdisorderBackground factors. As shown in Table 1, no statisticallysignificant differences with respect to sex, age, educationalattainment, employment status, and gaming frequencywere found between probable IGD gamers and non-IGDgamers (p = .07–.53). Probable IGD gamers were foundto be more likely to spend money on online gamesTable 1. Comparing stratified background profiles of overall sample and subsamplesOverall(N= 1,000)Overall sample subgroups Gamer subgroupsNon-gamer(n= 525)Recent gamer(n= 473)Probable IGD(n= 20)Non-IGD(n= 448)Age U= 151,242.0, z= 13.17, p< .001 U= 3,063.5, z=−1.63, p= .10M (SD) 40.0 (15.3) 46.5 (15.1) 33.0 (12.2) 27.3 (8.9) 33.2 (12.2)Sex χ2(1)= 44.87, p< .001 χ2(1)= 3.27, p= .07Male 44% 34.1% 55.2% 75.0% 54.5%Educational attainment U= 89,470.0, z=−6.52, p< .001 U= 3,844.5, z=−0.63, p= .53Primary or below 13.9% 19.6% 7.6% 5.0% 7.8%Junior secondary 14.9% 18.1% 11.4% 10.0% 11.6%Senior secondary 26.7% 24.6% 29.2% 35.0% 28.6%Tertiary 41.3% 33.6% 49.9% 45.0% 50.2%Working status χ2(3)= 83.65, p< .001 χ2(3)= 4.06, p= .26Full-time 61.0% 57.5% 64.7% 55.0% 65.2%Part-time 5.9% 4.4% 7.6% 10.0% 7.6%Student 8.7% 3.8% 14.2% 10.0% 14.3%Others 21.8% 31.4% 11.5% 25.0% 10.7%Weekly gaming frequency – U= 5,067.5, z= 1.54, p= .12Mdn (SD) – – 3.00 (1.43) 4.00 (1.20) 3.00 (1.43)Gaming expense – χ2(1) = 14.74, p< .001Yes % – – 23.9% 60.0% 22.3%Game-type preference – χ2(1) = 12.07, p= .001Multiplayers % – – 33.0% 70.0% 31.3%Depression t(996)=−0.25, p= .80 t(19.6)=−2.88, p= .01M (SD) 4.81 (6.51) 4.95 (6.83) 4.67 (6.15) 10.80 (9.89) 4.39 (5.81)Mild 9.0% 8.8% 9.3% 15.0% 8.7%Moderate 7.6% 8.0% 7.2% 10.0% 7.1%Severe 3.1% 3.6% 2.5% 15.0% 2.0%Anxiety – t(995)=−1.16, p= .25 t(466)=−4.26, p< .001M (SD) 5.31 (6.52) 5.56 (6.97) 5.06 (6.01) 10.50 (7.04) 4.79 (5.82)Mild 6.8% 5.0% 8.9% 25.0% 8.3%Moderate 11.2% 12.0% 10.4% 30.0% 9.4%Severe 8.7% 9.7% 7.6% 15.0% 7.4%Resilience – t(994)=−1.76, p= .80 t(465)= 2.95, p= .003M (SD) 2.59 (0.67) 2.62 (0.69) 2.55 (0.64) 2.16 (0.71) 2.58 (0.63)Purpose in life – t(996)=−2.87, p= .004 t(466)= 0.60, p= .55M (SD) 3.35 (0.64) 3.41 (0.64) 3.29 (0.64) 3.21 (0.85) 3.30 (0.63)Journal of Behavioral Addictions 7(1), pp. 62–69 (2018) | 65Adult Internet gaming disorder
(OR = 5.18) and prefer multiplayer games (OR = 5.32)than non-IGD gamers.Psychological factors. A total of 25.0% and 45.0% ofthe probable IGD respondents had moderate or abovelevels of anxiety and depression, respectively. Pearson’scorrelation results showed that IGD tendency increasedwith depression and anxiety symptoms (r = .34 and .32,respectively, p < .001) and decreased with psychologicalresilience (r =−.20, p < .001) and purpose in life(r =−.11, p = .02). Similarly, probable IGD gamers weremore likely to report higher levels of psychological distressand lower level of psychological resilience than theirnon-IGD counterparts (p < .001). However, no significantIGD-group difference was shown on purpose in life(p = .55; Table 1).After adjusted for the demographic variables (i.e., sex,age, education, and employment status), the logistic regres-sion models showed that depression (p= .02, adjustedOR = 1.1, 95% CI [1.0, 1.2]), anxiety (p= .01, adjustedOR = 1.1, 95% CI [1.0, 1.2]), and psychological resilience(p= .02, adjusted OR= .40, 95% CI [0.18, 0.88]), but notfor purpose in life (p= .96), were significantly associatedwith probable IGD classification.Moderating effects of psychological resilience and purposein lifeThe potential moderating effects of psychological resilienceand purpose in life on the associations between two psy-chological distress variables and probable IGD classificationwere probed by four independent logistic regression models.The interaction terms of Depression ×Resilience, Depres-sion × Purpose in life, Anxiety ×Resilience, and Anxiety ×Purpose in life were not statistically significant (OR rangedfrom 0.98 to 1.08, ps> .05).DISCUSSION AND CONCLUSIONSWith the cut-off of 4/5 for the nine-item DSM-5 criteria, theestimated prevalence of probable IGDwas 2.0% in our overallcommunity-dwelling adult sample, and 4.3% among recentgamers in Macao, China. It was lower than the prevalencefound among adult gamer samples, which were recruitedonline (e.g., 13.8%–16.7%; Kim et al., 2016; Wu et al.,2017), but comparable with those reported by some studiesof adolescents (e.g., 1.2% and 5.9% among German andKorean adolescents, respectively; Rehbein, Kliem, Baier,Mößle, & Petry, 2015; Yu & Cho, 2016). This study providesevidence that, similar to adolescents, adult gamers are alsosusceptible to problematic gaming. Therefore, IGD preventionshould be addressed by not only school-based programs butalso interventions that take place in general community.Our findings that a high proportion of probable IGDgamers suffered from moderate/severe levels of depressionand anxiety (25.0% and 45.0%, respectively) providedfurther support for this recommendation. Our first hypothe-sis regarding the positive association between psychologicaldistress and IGD was supported. In addition to the increasedsusceptibility to IGD due to psychological distress (Davis,2001; Jo et al., 2017), it is also plausible that the develop-ment of IGD results in psychological distress amonggamers, because excessive gaming is associated withadverse consequences, such as sleep problems, stress,and relationship deterioration (Kuss & Griffiths, 2012;Lemmens, Valkenburg, & Peter, 2011). The bidirectionalrelationship of depression and Internet addiction was shownin a longitudinal study among adolescents (Lau et al., underreview), but empirical test on the reciprocal link betweenpsychological distress and IGD in adults is warranted. Tobreak the vicious cycle, IGD prevention programs aresuggested to consider the risk effects of psychologicalTable 2. Endorsement rate of each item of the DSM-5 criteriaRecent gamers (n= 473)Probable IGD gamers(n= 20)Item description Yes No Uncertain/unanswered Yes1. Feel preoccupied with Internet games 51 (10.8%) 415 (87.7%) 7 (1.5%) 15 (75%)2. Feel irritable, anxious, or sad when Internetgaming is taken away25 (5.3%) 446 (94.3%) 2 (0.4%) 12 (60%)3. Spend increasing amounts of time on gaming toachieve satisfaction51 (10.8%) 416 (87.9%) 6 (1.3%) 16 (80%)4. Have made unsuccessful attempts to control yourparticipation in Internet games46 (9.7%) 420 (88.8%) 7 (1.5%) 13 (65%)5. Have lost interests in previous hobbies andentertainment as a result of, and with theexceptions of, Internet games43 (9.1%) 426 (90.1%) 4 (0.8%) 15 (75%)6. Continue to play Internet games excessivelydespite knowledge of psychosocial problems114 (24.1) 339 (71.7%) 20 (4.2%) 13 (65%)7. Have deceived others regarding the amount ofInternet gaming33 (7.0%) 431 (91.1%) 9 (1.9%) 12 (60%)8. Use Internet games to escape or relieve a negativemood124 (26.2%) 344 (72.7%) 5 (1.1%) 17 (85%)9. Have jeopardized or lost a significant relationship,job, or educational or career opportunity becauseof participation in Internet games16 (3.4%) 454 (96.0%) 3 (0.6%) 10 (50%)66 | Journal of Behavioral Addictions 7(1), pp. 62–69 (2018)Wu et al.
distress, while interventions for depression and anxietyshould pay special attention to people with IGD.The commonest symptoms endorsed by our Chinese gamerrespondents were “gaming for an escape or a relief fromnegative moods” and “continued engagement despite psycho-social problems.” Indeed, escape from reality and moodmodification is a major drive for those who engage in onlinegaming and represents the strongest motivational factor asso-ciated with IGD in previous studies (Király et al., 2015; Wuet al., 2017). In a multisample study, escape was also found tobe the commonest IGD symptom reported by adult gamers(Kim et al., 2016). Despite their awareness of negativeconsequences, adult gamers tend to continue their problematicgaming pattern. Therefore, public education on the adverseconsequences of excessive online gaming may not be the mosteffective prevention strategy. It is recommended that inter-vention may stress on positive trait enhancement. For exam-ple, phone applications promoting mood management andcoping flexibility (Ameringen, Turna, Khalesi, Pullia, &Patterson, 2017; Christmann, Hoffmann, & Bleser, 2017) canbe developed to lower the general public’s risk of IGD.The hypothesized negative correlation between characterstrength (i.e., psychological resilience and purpose in life)and IGD tendency was found, but the magnitude was weak(r=−.20 and −.11, respectively) and no significantIGD-group difference was found on purpose in life. More-over, the hypothesized buffering effect of character strengthon the relationship between psychological distress andprobable IGD was not supported in this study. Althoughthe protective function of psychological resilience andpurpose in life against social networking and gaming addic-tions in young adults have been reported (Hou et al., 2017;Wu et al., 2013), our findings provided only mildly sup-portive evidence that the positive psychology interventionsare applicable to preventive measures for IGD amongChinese adults. It is plausible that the effects of resilienceand purpose in life are more salient in young adults, whoface new developmental tasks including searching for andaccomplishing work and romance goals (Roisman, Masten,Coatsworth, & Tellegen, 2004) than other older adults. Thisspeculation needs further examination with a larger age-stratified gamer sample in future studies.No statistically significant demographic difference betweenprobable IGD and non-IGD gamers was found in this study.Another recent study among adult gamers who spoke eitherKorean or European language also showed no demographicdifference in terms of sex, age, education, marital status, andwork status between probable IGD and non-IGD gamers whowere recruited online (Kim et al., 2016). These findingssuggest that some demographic risk factors reported in ado-lescent studies may not be very strong predictors of IGD inadults. Even male sex showed only a marginal significanteffect (p< .10) in this study. This non-significant finding wasplausibly related to the small group of probable IGD gamers(n= 20) in our sample and the power of the statistics wasaffected. On the other hand, such non-significant differencesheds lights on the potentially increasing vulnerability offemale and older gamers to IGD in this Internet era. Althoughit was commonly observed that male and younger adults weremore likely to play games and to have higher time andfinancial involvement, many female and older gamers werealso vulnerable to IGD. A recent study reported that the femalevideo game addicts had more somatic problems and sleepdisturbance (Stockdale & Coyne, 2018), and hence furtherstudies are warranted to not only compare demographic riskfactors of IGD between adolescents and adults but alsoidentify sex-specific predictors and consequences of IGD indifferent age groups. Moreover, different consequences ofIGD should also be considered in future intervention programs(e.g., personal health management).Our telephone survey design with random samplingoffered us the likelihood of collecting a representativeheterogeneous community sample, including both onlinegamers and non-gamers, in Macao. Despite the practicalinsights brought by this study, some of its limitations shouldbe noted. First, this approach allowed for only a shortquestionnaire to be administered, and only a limited numberof variables were assessed. A number of potential protectorfactors were not included (e.g., social support) and theywould be useful for designing effective intervention pro-grams. Similar to those of other telephone surveys, thepresent findings are susceptible to self-report bias. Wetherefore began all interviews by assuring the respondentsof anonymity and encouraging them to be frank in makingtheir response to each item. They were also allowed to refuseto answer any question if they chose to. Due to its correla-tional study design, this study neither provided causalinference nor details on factors affecting the course of IGDdevelopment over time for adult sample.To conclude, this study showed that some Chinese adultgamers were at high risk of IGD, and that IGD waspositively associated with psychological distress. Interven-tions for both psychological distress and IGD should con-sider the potentially high comorbidity of these disorders.Moreover, demographic variables were not strong predictorsof IGD and thus interventions should target to both sexesand different age groups in the Chinese communities. IGDtendency was negatively, but only slightly, associated withpsychological resilience and purpose in life. Future studiesmay investigate whether demographic and psychologicalfactors are specific to a particular age group or life stage dueto different developmental needs.Funding sources: The project was supported by a researchgrant from the University of Macau (ref. no.: MYRG2015-00213-FSS).Authors’ contribution: Dr. AMSW was the principal inves-tigator of the project. She was responsible for the researchconception and design, supervision, data interpretation, andmanuscript writing. Ms. JHC and Dr. K-KT conducted thedata analysis, interpreted the findings, and were involved inmanuscript writing. Ms. SY was involved in project imple-mentation and manuscript preparation. Prof. JTFL participat-ed in research conception and manuscript preparation. Allauthors contributed to and approved the final manuscript.Conflict of interest: All authors declare no conflict ofinterest.Journal of Behavioral Addictions 7(1), pp. 62–69 (2018) | 67Adult Internet gaming disorder
REFERENCESAmerican Association for Public Opinion Research. (2011).Standard definitions: Final dispositions of case codes andoutcome rates for surveys (7th ed.). Retrieved from http://aapor.org/Content/NavigationMenu/AboutAAPOR/StandardsampEthics/StandardDefinitions/StandardDefinitions2011.pdfAmerican Psychiatric Association [APA]. (2013). Diagnostic andstatistical manual of mental disorders (5th ed.). Washington,DC: American Psychiatric Association.Ameringen, M., Turna, J., Khalesi, Z., Pullia, K., & Patterson, B.(2017). There is an app for that! The current state ofmobile applications (apps) for DSM-5 obsessive-compulsive dis-order, posttraumatic stress disorder, anxiety and mood disorders.Depression and Anxiety, 34(6), 526–539. doi:10.1002/da.22657China Internet Network Information Center. (2017). The 39th surveyreport: Statistical report on Internet development in China.Retrieved from https://cnnic.com.cn/IDR/ReportDownloads/201706/P020170608523740585924.pdfConnor, K. M., & Davidson, J. R. T. (2003). Development of anew resilience scale: The Connor-Davidson ResilienceScale (CDRISC). Depression and Anxiety, 18(2), 76–82.doi:10.1002/da.10113Christmann, C. A., Hoffmann, A., & Bleser, G. (2017). Stressmanagement apps with regard to emotion-focused coping andbehavior change techniques: A content analysis. JMIRmHealth and uHealth, 5(2), e22. doi:10.2196/mhealth.6471Davis, R. A. (2001). A cognitive-behavioral model of pathologicalInternet use. Computers in Human Behavior, 17(2), 187–195.doi:10.1016/S0747-5632(00)00041-8Feng, W., Ramo, D., Chan, S., & Bourgeois, J. (2017). Internetgaming disorder: Trends in prevalence 1998–2016. AddictiveBehaviors, 75, 17–24. doi:10.1016/j.addbeh.2017.06.010Fumaz, C. R., Ayestaran, A., Perez-Alvarez, N., Muñoz-Moreno,J. A., Moltó, J., Ferrer, M. J., & Clotet, B. (2015). Resilience,ageing, and quality of life in long-term diagnosed HIV-infectedpatients. AIDS Care, 27(11), 1396–1403. doi:10.1080/09540121.2015.1114989Harlow, L., Newcomb, M., & Bentler, P. (1986). Depression, self-derogation, substance abuse, and suicide ideation: Lack ofpurpose in life as a mediational factor. Journal of ClinicalPsychology, 42(1), 5–21. doi:10.1002/1097-4679(198601)42:1<5::AID-JCLP2270420102>3.0.CO;2-9Hayes, A. F. (2012). PROCESS: A versatile computational tool forobserved variable mediation, moderation, and conditional pro-cess modeling [PDF file]. Retrieved from http://www.afhayes.com/public/process2012.pdfHou, X. L., Wang, H. Z., Guo, C., Gaskin, J., Rost, D. H., &Wang,J. L. (2017). Psychological resilience can help combat theeffect of stress on problematic social networking site usage.Personality and Individual Differences, 109, 61–66.doi:10.1016/j.paid.2016.12.048Jiménez-Murcia, S., Fernández-Aranda, F., Granero, R., Chóliz, M.,La Verde, M., Aguglia, E., Signorelli, M. S., Sá, G. M.,Aymamí, N., Gómez-Peña, M., del Pino-Gutiérrez, A.,Moragas, L., Fagundo, A. B., Sauchelli, S., Fernández-Formoso, J. A., & Menchón, J. M. (2014). Video gameaddiction in gambling disorder: Clinical, psychopathological,and personality correlates. BioMed Research International,2014, 1–11. doi:10.1155/2014/315062Jo, S. J., Yim, H. W., Hyunsuk, J., Eunjin, K., Hye-Jung, S., &Koo, L. H. (2017). Does adolescents’ depressive symptomsincrease the possibility of addictive Internet gaming?: 1-yearfollow up study in Korea. European Psychiatry, 41, S204.doi:10.1016/j.eurpsy.2017.01.2159Kim, N. R., Hwang, S. S. H., Choi, J. S., Kim, D. J., Demetrovics, Z.,Király, O., Nagygyörgy, K., Griffiths, M. D., Hyun, S. Y., Youn,H. C., & Choi, S. W. (2016). Characteristics and psychiatricsymptoms of Internet gaming disorder among adults usingself-reported DSM-5 criteria. Psychiatry Investigation, 13(1),58–66. doi:10.4306/pi.2016.13.1.58Király, O., Urbán, R., Griffiths, M. D., Ágoston, C.,Nagygyörgy, K., Kökönyei, G., & Demetrovics, Z. (2015).The mediating effect of gaming motivation between psychi-atric symptoms and problematic online gaming: An onlinesurvey. Journal of Medical Internet Research, 17(4), e88.doi:10.2196/jmir.3515Ko, C. H., Yen, J. Y., Chen, C. S., Yeh, Y. C., & Yen, C. F. (2009).Predictive values of psychiatric symptoms for Internet addic-tion in adolescents: A 2-year prospective study. Archives ofPediatrics & Adolescent Medicine, 163(10), 937–943.doi:10.1001/archpediatrics.2009.159Ko, C. H., Yen, J. Y., Chen, S. H., Wang, P. W., Chen, C. S., &Yen, C. F. (2014). Evaluation of the diagnostic criteria ofInternet gaming disorder in the DSM-5 among young adults inTaiwan. Journal of Psychiatric Research, 53(1), 103–110.doi:10.1016/j.jpsychires.2014.02.008Ko, C.-H., Yen, J.-Y., Yen, C.-F., Lin, H.-C., & Yang, M.-J.(2007). Factors predictive for incidence and remission ofInternet addiction in young adolescents: A prospective study.CyberPsychology & Behavior, 10(4), 545–551. doi:10.1089/cpb.2007.9992Krentzman, A. R. (2013). Review of the application of positivepsychology to substance use, addiction, and recovery research.Psychology of Addictive Behaviors, 27(1), 151–165.doi:10.1037/a0029897Kuss, D. J., & Griffiths, M. D. (2012). Internet gaming addiction: Asystematic review of empirical research. International Journalof Mental Health and Addiction, 10(2), 278–296. doi:10.1007/s11469-011-9318-5Lau, J. T. F., Gross, D. L., Wu, A. M. S., Cheng, K. M., Lau,M. M. C., & Mo, P. K. H. (under review). Bidirectionalitybetween Internet addiction and probable depression amongChinese adolescents. Journal of Behavioral Addictions.Lee, J. H., Nam, S. K., Kim, A. R., Kim, B., Lee, M. Y., & Lee,S. M. (2013). Resilience: A meta-analytic approach. Journal ofCounseling and Development, 91(3), 269–279. doi:10.1002/j.1556-6676.2013.00095.xLemmens, J. S., Valkenburg, P. M., & Peter, J. (2011). Psychoso-cial causes and consequences of pathological gaming. Com-puters in Human Behavior, 27(1), 144–152. doi:10.1016/j.chb.2010.07.015Li, Y., Zhang, X., Lu, F., Zhang, Q., & Wang, Y. (2014). Internetaddiction among elementary and middle school students inChina: A nationally representative sample study. Cyberpsy-chology, Behavior, and Social Networking, 17(2), 111–116.doi:10.1089/cyber.2012.0482Macao Statistics and Census Services. (2017). Detailed results of2016 Population By-census. Macao: Macao Statistics andCensus Services. Retrieved from http://www.dsec.gov.mo/68 | Journal of Behavioral Addictions 7(1), pp. 62–69 (2018)Wu et al.
getAttachment/bfa0112a-eaf3-49a9-9168-b5add46e9d65/C_ICEN_PUB_2016_Y.aspxMcKenna, K. Y. A., & West, K. J. (2007). Give me that online-time religion: The role of the Internet in spiritual life.Computers in Human Behavior, 23(2), 942–954. doi:10.1016/j.chb.2005.08.007Moussa, M. T., Lovibond, P. F., & Laube, R. (2001). Psychometricproperties of a Chinese version of the short Depression AnxietyStress Scales (DASS21). Report for New South Wales Trans-cultural Mental Health Centre, Cumberland Hospital, Sydney,Australia.Müller, K. W., Janikian, M., Dreier, M., Wölfling, K., Beutel,M. E., Tzavara, C., Richardson, C., & Tsitsika, A. (2015).Regular gaming behavior and Internet gaming disorder inEuropean adolescents: Results from a cross-national represen-tative survey of prevalence, predictors, and psychopathologicalcorrelates. European Child & Adolescent Psychiatry, 24(5),565–574. doi:10.1007/s00787-014-0611-2Rehbein, F., Kliem, S., Baier, D., Mößle, T., & Petry, N. M.(2015). Prevalence of Internet gaming disorder in Germanadolescents: Diagnostic contribution of the nine DSM-5 criteriain a state-wide representative sample. Addiction, 110(5), 842–851. doi:10.1111/add.12849Roisman, G. I., Masten, A. S., Coatsworth, J. D., & Tellegen, A.(2004). Salient and emerging developmental tasks in thetransition to adulthood. Child Development, 75(1), 123–133.doi:10.1111/j.1467-8624.2004.00658.xRyff, C. D. (1995). Psychological well-being in adult life. CurrentDirection in Psychological Science, 4(4), 99–104. doi:10.1111/1467-8721.ep10772395Sigerson, L., Li, A. Y. L., Cheung,M.W. L., Luk, J.W., &Cheng, C.(2017). Psychometric properties of the Chinese Internet GamingDisorder Scale. Addictive Behaviors, 74, 20–26. doi:10.1016/j.addbeh.2017.05.031Stockdale, L., & Coyne, S. M. (2018). Video game addiction inemerging adulthood: Cross-sectional evidence of pathology invideo game addicts as compared to matched healthy controls.Journal of Affective Disorder, 225, 265–272. doi:10.1016/j.jad.2017.08.045Wei, H. T., Chen, M. H., Huang, P. C., & Bai, Y. M. (2012).The association between online gaming, social phobia, anddepression: An Internet survey. BMC Psychiatry, 12(1), 92.doi:10.1186/1471-244X-12-92Wenzel, H. G., Bakken, I. J., Johansson, A., Götestam, K. G., &Øren, A. (2009). Excessive computer game playing amongNorwegian adults: Self-reported consequences of playing andassociation with mental health problems. PsychologicalReports, 105(3 Suppl), 1237–1247. doi:10.2466/PR0.105.F.1237-1247Wang, C.-W., Chan, C. L. W., Mak, K.-K., Ho, S.-Y., Wong,P. W. C., & Ho, R. T. H. (2014). Prevalence and correlates ofvideo and Internet gaming addiction among Hong Kongadolescents: A pilot study. Scientific World Journal, 2014,874648. doi:10.1155/2014/874648Wang, L., Shi, Z., Zhang, Y., & Zhang, Z. (2010). Psychometricproperties of the 10-item Connor–Davidson Resilience Scalein Chinese earthquake victims. Psychiatry and ClinicalNeurosciences, 64(5), 499–504. doi:10.1111/j.1440-1819.2010.02130.xWingo, A. P., Ressler, K. J., & Bradley, B. (2014). Resiliencecharacteristics mitigate tendency for harmful alcohol and illicitdrug use in adults with a history of childhood abuse: A cross-sectional study of 2024 inner-city men and women. Journal ofPsychiatric Research, 51, 93–99. doi:10.1016/j.jpsychires.2014.01.007Wu, A. M. S., Lai, M. H., Yu, S., & Tong, K. K. (2017). Motivesfor online gaming questionnaire: Its psychometric propertiesand correlation with Internet gaming disorder symptomsamong Chinese people. Journal of Behavioral Addictions,6(1), 11–20. doi:10.1556/2006.6.2017.007Wu, A. M. S., Lei, L. L., & Ku, L. (2013). Psychologicalneeds, purpose in life, and problem video game playingamong Chinese young adults. International Journalof Psychology, 48(4), 583–590. doi:10.1080/00207594.2012.658057Wu, A. M., Li, J., Lau, J. T., Mo, P. K., & Lau, M. M. (2016).Potential impact of Internet addiction and protective psycho-social factors onto depression among Hong Kong Chineseadolescents – Direct, mediation and moderation effects.Comprehensive Psychiatry, 70, 41–52. doi:10.1016/j.comppsych.2016.06.011Xu, J., Shen, L.-X., Yan, C.-H., Hu, H., Yang, F., Wang, L., Kotha,S. R., Zhang, L.-N., Liao, X.-P., Zhang, J., Ouyang, F.-X.,Zhang, J.-S., & Shen, X.-M. (2012). Personal characteristicsrelated to the risk of adolescent Internet addiction: A surveyin Shanghai, China. BMC Public Health, 12(1), 1106.doi:10.1186/1471-2458-12-1106Yu, H., & Cho, J. (2016). Prevalence of Internet gaming disorderamong Korean adolescents and associations with non-psychoticpsychological symptoms, and physical aggression. AmericanJournal of Health Behavior, 40(6), 705–716. doi:10.5993/AJHB.40.6.3Journal of Behavioral Addictions 7(1), pp. 62–69 (2018) | 69Adult Internet gaming disorder
