| Background and Objectives:Games based on mobile devices have become a common entertainment choice,with the adolescents being the major group of game users.Excessive gaming behavior and unhealthy gaming habits could be harmful to the health of the adolescents.Game addiction is a typical representative of this issue.In the International Classification of Diseases11 th reversion(ICD-11)revised in 2019,gaming disorder(GD)is officially identified as a diagnosis entity under the “disorders caused by addictive behaviors”.Previous studies have adopted various inconsistencies diagnostic criteria and tools,which makes it hard to assess the actual conditions and influencing factors of this issue.This study aimed to develop a screening tool for GD suitable for our national conditions and culture based on ICD-11 and other related tools for GD,and to determine its psychometric characteristics in adolescents,as well as applied the new tool in these adolescents to investigate the status quo of GD and to explore influencing factors of GD.Methods:This study is composed of three sub-studies,the methods of which are described as follows:Study 1.The development of a GD screening tool and verification of its psychometric properties.(1)According to the diagnostic guideline of GD in ICD-11 and other existing questionnaires,a self-rating screening questionnaire named the Gaming Disorder Symptom Questionnaire(GDSQ)adapted on the cultural background of China was developed.Pretest data was collected among 650 junior and senior middle school students to analyze the items and factors of GDSQ.Then it was further optimized as a 21-item questionnaire named the Gaming Disorder Symptom Questionnaire-21(GDSQ-21).(2)The optimized questionnaire was tested among 544 middle school students twice with an 8-week interval,thereby verifying the re-test reliability.(3)The factor analysis was used to compare four measurement models of GDSQ-21,thereby verifying the structural validity.Study 2.The status quo of GD identified by GDSQ-21 in adolescents.(1)This newly developed screening tool GDSQ-21 in Study 1 was tested in 7,790 middle school students to determine the cut-off of GDSQ-21 for identifying GD through taking the synchronous test results of the mature screening tool named Video Game Dependency Scale(VGDS)as the criterion and ROC curve analysis.(2)The prevalence rate of GD in the adolescents was determined based on the above study procedures.(3)To detect the heterogeneity of adolescent game users in terms of symptoms of gaming disorders,the different potential categories of the study object was identified by latent profile analysis and was named according to the characteristics of their symptoms.Study 3.The influencing factors of GD in adolescents.By simultaneous collection of socio-demographic data,behavioral characteristics of game use and questionnaires related to psychological factors(such as Behavioral Inhibition System and Behavioral Activation System Scale,Emotion Regulation Questionnaire,Short-form Egna Minnenav Barndoms Uppfostran for Chinese,and Adolescent Self-Rating Life Events Check List),(1)The relationships of demographics,psychological characteristics(reward processing,moods),and social environment factors(parenting approach and life events)with GD in adolescents was examined by univariate analyses.(2)The independent influencing factors of GD in adolescents was explored by regression model analysis.Results:Study 1.(1)The newly developed screening tool for GD named Gaming Disorder Symptom Questionnaire(GDSQ-21)included 21 items and was divided into three dimensions: impaired control over gaming behavior(“impaired control”,6 items),increasing priority of gaming over other life interests and daily activities(“priority”,7 items),and continued playing games regardless of negative consequences and significant functional impairment(“continuation”,8 items).(2)The GDSQ-21 has a good reliability with Cronbach’s α coefficient being 0.964,which met the psychometric requirement.(3)The one-order three factor model,secondorder factor model and bi-factor model all demonstrated acceptable fitting results,with the fitting results of the bi-factor model being optimal(TLI,0.961;CFI,0.969;SRMR,0.027).The questionnaire displayed satisfactory structural validity that conformed the ICD-11 diagnostic guidelines.Study 2.(1)According to the ROC curve with the VGDS as the criterion and the diagnostic guideline of ICD-11,those adolescents who met the following criteria in GDSQ-21 at the same time could be diagnosed as GD: “impaired control score” ≥14,“increasing priority score” ≥11,“continuation score” ≥4,and total score≥62.(2)Based on the above mentioned criteria in GDSQ-21 for GD,the prevalence rate of GD among the adolescents was 2.27%.(3)Based on the symptoms of GD,those junior and senior middle school students could be grouped into four groups,namely “healthy gamers”(56.8%),“impaired control gamers”(26.1%),“impaired control-increasing priority gamers”(9.7%),and “gamers with disorder”(7.4%)Study 3.(1)The results of univariate analyses showed that the adolescents with GD were mostly male,single child and upperclassmen;weaker behavioral inhibition,reward reactivity,and drive caused by negative emotional events,and less use of expressive inhibition strategies in emotion regulation;higher occurrence of negative life events;and higher rejection,lower emotional warmth,and higher overprotection in parenting styles;(2)The results of logistic regression model showed that males were0.211 times more likely to have a game disorder than females;each 1-year increase in age and each 1-point increase in rejections from mother score increased the likelihood of a game disorder by 26.1% and 6.1%,respectively;each 1-point increase in interpersonal relationship and punishment factor scores increased the likelihood of a game disorder by7.0% and 7.3%,respectively.The likelihood of play disorder decreased by14% for each 1-point increase in the ASLEC loss factor score in the model.Conclusions:1.In study 1,we developed the Gaming Disorder Symptom Questionnaire-21(GDSQ-21)with a good validity based on ICD-11,which could provide a reliable screening tool for relevant researches in the future.By comparing four measurement models of the factor analysis of GDSQ-21,it was concluded that the fitting result of the bi-factor model was optimal.2.Study 2 found that the prevalence rate of GD among the adolescents was 2.27%,and these adolescents could be divided into four heterogeneous categories according to their gaming symptoms.These findings are very important for us to understand the essence of GD and carry out clinical practices under the guidance of “precision medicine” in the future.3.Study 3 found that gender,parenting style and self-control were independent influencing factors of GD.Future researches on public health,education,and other fields could focus on these factors and targeted prevention and intervention could be carried out.There are 8 figures,39 tables and 178 references... |
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