Validation of the ACSID-11 for consistent screening of specific Internet-use disorders based on ICD-11 criteria for gaming disorder: A multitrait-multimethod approach.

INTRODUCTION: With the inclusion of gaming disorder in the ICD-11, diagnostic criteria were introduced for this relatively new disorder. These criteria may be applied to other potential specific Internet-use disorders. The 11-item Assessment of Criteria for Specific Internet-use Disorders (ACSID-11) was developed for consistent screening of gaming disorder, online buying-shopping disorder, online pornography-use disorder, social networks-use disorder, and online gambling disorder. This study tested the construct validity of the ACSID-11, including convergent and divergent measures. METHODS: The ACSID-11 measures five behavioral addictions with the same set of items by following the principles of the Alcohol, Smoking and Substance Involvement Screening Test (ASSIST). The ACSID-11 was administered to a convenience sample of active Internet users (N = 1597) together with validated and established measures of each specific Internet-use disorder along with screeners for mental health. Included are the Ten-Item Internet Gaming Disorder Test (IGDT-10), the Bergen Shopping Addiction Scale (BSAS), the Problematic Pornography Consumption Scale (PPCS), the Bergen Social Media Addiction Scale (BSMAS) and the Berlin Inventory of Gambling behavior - Screening (BIG-S). The ACSID-11 was compared convergently and divergently through a multitrait-multimethod approach along with contingency tables with the other Internet-use disorder screeners. RESULTS: The multitrait-multimethod results shows that each behavior assessed with the ACSID-11 has moderate to strong correlations (r's from 0.462 to 0.609) with the scores of the corresponding established measures and, furthermore, positive correlations (r's from 0.122 to 0.434) with measures of psychological distress and further shows that the ACSID-11 can be used for a comprehensive assessment of different behaviors. The contingency tables reveal large divergences between the ACSID-11 and other screening instruments concerning the classification of problematic specific Internet use based on the given cut-off values. CONCLUSION: The current work provides additional validation for the ACSID-11. Accordingly, this tool can be considered as reliable and valid for the simultaneous assessment of different Internet-use disorders: gaming disorder, online buying-shopping disorder, online pornography use disorder, social networks use disorder, and online gambling disorder. With a subsequent clinical validation of the scale and the proposed cut-off score, the ACSID-11 will be a thoroughly validated useful screening tool for clinical practice.

A comprehensive measure assessing different types of problematic use of the internet among Chinese adolescents: The Assessment of Criteria for Specific Internet-use Disorders (ACSID-11).

BACKGROUND: Problematic use of the internet (PUI) is prevalent, particularly among adolescents and young adults. Given the limited measures to assess specific types of PUI, which encompasses a broad spectrum of activities such as online gaming, social media use, pornography use, shopping, gambling, and web-streaming, Muller et al. (2022) developed the Assessment of Criteria for Specific Internet-use Disorders (ACSID-11) to comprehensively assess different types of PUI (i.e., gaming, shopping, social media use, gambling, and pornography use). The present study aimed to validate the Chinese ACSID-11 among adolescents incorporating cross-cultural adaptations. METHODS: Using forward-backward translation method, a culturally adapted version of the ACSID-11 was prepared. Then, a cross-sectional online survey was administered between September 8 and September 26, 2023. Adolescents, using a convenience sample (N = 11,492; mean age = 16.42 years [SD ± 0.91]; 59.1% male), were recruited from six schools to complete the translated ACSID-11, Internet Gaming Disorder Scale-Short Form (IGDS9-SF), Bergen Social Media Addiction Scale (BSMAS), and Smartphone Application Based Addiction Scale (SABAS) via an online platform. Pearson correlation coefficients assessed convergent/discriminant validity. Factor structure and measurement invariance were examined through confirmatory factor analysis (CFA) and multi-group CFA. Cronbach's alpha and McDonald's omega tested internal consistency. RESULTS: Associations between the ACSID-11 components and other scales supported convergent validity (i.e., ACSID-11 gaming scale with IGDS9-SF [0.37 ≤ r ≤ 0.41]; social networks use scale with BSMAS [0.24 ≤ r ≤ 0.31]) and discriminant validity (i.e., online gambling scale with BSMAS [0.16 ≤ r ≤ 0.19] and with SABAS [0.11 ≤ r ≤ 0.13]). A four-factor solution indicated good fit with comparative fit index (CFI) ranging from 0.982 to 0.958. The ACSID-11 was measurement invariant across sexes (∆CFI = -0.001 to 0.000) and different levels of related addictive behaviors (∆CFI = -0.001 to 0.000). Both Cronbach's alpha and McDonald's omega (0.63 to 0.97) were acceptable for both frequency and intensity of responses. CONCLUSIONS: The ACSID-11 is an appropriate scale to assess different kinds of PUI among Chinese adolescents and students. Psychometric assessment of the measure in other cultures and among clinical samples is recommended.

Psychometric properties of the Turkish version of the gaming disorder scale for adolescents (GADIS-A).

PURPOSE: This methodological study established the Turkish validity and reliability of the Gaming Disorder Scale for Adolescents (GADIS-A). METHODS: The study was conducted with 378 adolescents studying in primary and secondary education institutions in the central districts of a province in Turkey affiliated with the Provincial Directorate of National Education. Data were collected using an adolescent information form and GADIS-A. An ethics committee approved the study, and permission was obtained from the institution. RESULTS: Confirmatory Factor Analysis (CFA) showed that the scale had factor loadings of 0.511 to 0.768, the Goodness of Fit indices of >0.87, and the RMSEA index of <0.10. The total scale had a Cronbach's alpha of 0.860. CONCLUSION: The results show that GADIS-A is a valid and reliable measure for the Turkish sample. IMPLICATIONS TO PRACTICE: GADIS-A, a highly valid and reliable scale, can be used as a measurement tool in national and international screening programs.

Comparing psychopathological symptoms, life satisfaction, and personality traits between the WHO and APA frameworks of gaming disorder symptoms: A psychometric investigation.

INTRODUCTION: The inclusion of Internet Gaming Disorder (IGD) in the fifth revision of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) by the American Psychiatric Association and Gaming Disorder in the 11th revision of the International Classification of Diseases (ICD-11) by the World Health Organization requires consistent psychological measures for reliable estimates. The current study aimed to investigate the psychometric properties of the Gaming Disorder Test (GDT), the Ten-Item Internet Gaming Disorder Test (IGDT-10), and the Five-Item Gaming Disorder Test (GDT-5) and to compare the WHO and the APA frameworks of gaming disorder symptoms in terms of psychopathological symptoms, life satisfaction, and personality traits. METHODS: A sample of 723 Swedish gamers was recruited (29.8% women, 68.3% men, 1.9% other, Mage = 29.50 years, SD = 8.91). RESULTS: The results indicated notable differences regarding the estimated possible risk groups between the two frameworks. However, the association between gaming disorder symptoms and personality traits, life satisfaction, and psychopathological symptoms appeared consistent across the two frameworks. The results showed excellent psychometric properties in support of the one-factor model of the GDT, IGDT-10, and GDT-5, including good reliability estimates (McDonald's omega) and evidence of construct validity. Additionally, the results demonstrated full gender and age measurement invariance of the GDT, IGDT-10, and GDT-5, indicating that gaming disorder symptoms are measured equally across the subgroups. CONCLUSION: These findings demonstrate that the IGDT-10, GDT-5, and GDT are appropriate measures for assessing gaming disorder symptoms and facilitating future research in Sweden.

Measurement Invariance of the Lemmens Internet Gaming Disorder Scale-9 Across Age, Gender, and Respondents.

Although Internet gaming disorder (IGD) has gained increased attention in scientific, clinical, and community contexts, there is still a lack of consensus regarding the best assessment tools (i.e., self-report or other reports) for assessing its symptoms. The present study aimed to investigate the reliability, validity, and measurement invariance of both versions (youth and parent) of The Lemmens Internet Gaming Disorder Scale-9. To achieve this goal, we recruited between June and October 2019 from five Romanian highschools a total of 697 adolescents (11-19 years old) and one of their parents (N = 391). The internal consistency was good in both versions of the instrument (α = 0.772 for the youth version and α = 0.781 for the parent version). Construct validity assessed through confirmatory factor analysis showed support for the one factor structure of the scales, while multigroup confirmatory factor analysis endorsed the invariance across age, gender, and respondents (i.e., parent vs. youth report). The current research identifies both IGD scales to be reliable and valid, arguing for their utility for assessing IGD symptomatology among adolescents. Implications for theory, assessment, and future directions are discussed.

Determination of the cutoff point for Smartphone Application-Based Addiction Scale for adolescents: a latent profile analysis.

BACKGROUNDS: The Smartphone Application-Based Addiction Scale (SABAS) is a validated 6-item measurement tool for assessing problematic smartphone use (PSU). However, the absence of established cutoff points for SABAS hinders its utilities. This study aimed to determine the optimal cutoff point for SABAS through latent profile analysis (LPA) and receiver operating characteristic curve (ROC) analyses among 63, 205. Chinese adolescents. Additionally, the study explored whether PSU screening with SABAS could effectively capture problematic social media use (PSMU) and internet gaming disorder (IGD). METHOD: We recruited 63,205. adolescents using cluster sampling. Validated questionnaires were used to assess PSMU, IGD, and mental health (depression, anxiety, sleep disturbances, well-being, resilience, and externalizing and internalizing problems). RESULTS: LPA identified a 3-class model for PSU, including low-risk users (38.6%, n = 24,388.), middle-risk users (42.5%, n = 26,885.), and high-risk users (18.9%, n = 11,932.). High-risk users were regarded as "PSU cases" in ROC analysis, which demonstrated an optimal cut-off point of 23 (sensitivity: 98.1%, specificity: 96.8%). According to the cutoff point, 21.1% (n = 13,317.) were identified as PSU. PSU adolescents displayed higher PSMU, IGD, and worse mental health. PSU screening effectively captured IGD (sensitivity: 86.8%, specificity: 84.5%) and PSMU (sensitivity: 84.5%, specificity: 80.2%). CONCLUSION: A potential ideal threshold for utilizing SABAS to identify PSU could be 23 (out of 36). Employing SABAS as a screening tool for PSU holds the potential to reliably pinpoint both IGD and PSMU.

Validation of the Thai Assessment of Criteria for Specific Internet-use Disorders (ACSID-11) among young adults.

BACKGROUND: The Assessment of Criteria for Specific Internet-use Disorders (ACSID-11) is a consistent and comprehensive instrument to assess symptoms of specific internet-use disorders including those related to gaming, shopping, pornography use disorder, social networks use and gambling considering criteria in the eleventh revision of the International Classification of Diseases (ICD-11). However, to date, there is little evidence supporting instruments assessing major types of specific internet use disorders in Thailand. The aim of this present study was to assess the psychometric properties of the ACSID-11 among Thai young adults. METHODS: A total of 612 participants were recruited. A confirmatory factor analysis (CFA) examined construct validity of the ACSID-11. Cronbach's α and McDonald's ω were used to assess reliability of the ACSID-11. Pearson correlations examined relationships between ACSID-11 domains and Internet Gaming Disorder Scale-Short Form (IGDS9-SF) scores. RESULTS: The CFA supported validity of the Thai version of the ACSID-11 and a four-factor structure. Specific domains of the Thai ACSID-11, particularly gaming, were positively and significantly correlated with IGDS9-SF scores. CONCLUSIONS: Data indicate that the Thai version of the ACSID-11 is a valid and reliable instrument to assess major types of specific internet use disorders. Additional studies are needed to further examine the validity and reliability of the Thai ACSID-11.

Problematic internet gaming and non-suicidal self-injury in Chinese adolescents: Moderating and mediating roles of anxiety.

INTRODUCTION: Despite consistent reports of the association between problematic internet gaming (PIG) and non-suicidal self-injury (NSSI), an increase in PIG does not necessarily lead to increased NSSI. This apparent paradox indicates the presence of other mediators and moderators in the PIG-NSSI association. This study aimed to investigate the role of anxiety as a potential moderating and mediating factor of the PIG-NSSI association in Chinese adolescents. METHODS: A cross-sectional study was conducted among 10,479 Chinese adolescents (50.5% male; age range, 9-18 years). Standardized self-report questionnaires were used to assess the severity of PIG, anxiety, and NSSI. Spearman correlation and multiple linear regression were applied to examine the relationships among PIG, anxiety, and NSSI. Both moderating and mediating effects of anxiety were assessed using Hayes' methods. RESULTS: PIG, anxiety symptoms, and NSSI significantly correlated with one another. Anxiety significantly moderated the relationship between PIG and NSSI [B = 0.002, standard error (SE) = 0.000, p < 0.001], and it partially mediated the PIG-NSSI association [B = 0.017, SE = 0.001, 95% confidence interval (CI) 0.014-0.021]. Social concern and concentration were the two dimensions of anxiety that exerted the strongest mediation effect (B = 0.017, SE = 0.002, 95% CI 0.014-0.020). CONCLUSIONS: Adolescents with PIG and high anxiety are likely to suffer more severe NSSI and may benefit from interventions to reduce anxiety symptoms.

Network analyses of internet gaming disorder symptoms and their links with different types of motivation.

The study used regularized partial correlation network analysis (EBICglasso) to examine the structure of DSM-5 internet gaming disorder (IGD) symptoms (network 1); and the associations of the IGD symptoms in the network with different types of motivation as defined in the self-determination theory i.e., intrinsic motivation (engaging in an activity for something unrelated to the activity), identified regulation (engaging in the activity because it aligns with one's values and/or goals), external regulation (engagement in activity being driven by external rewards and/or approval), and amotivation (engaging in an activity without often understanding why) (network 2). Participants were 968 adults from the general community. They completed self-rating questionnaires covering IGD symptoms and different types of motivation. The findings for network 1 showed mostly positive connections between the symptoms within the IGD network. The most central symptom was loss of control, followed by continuation, withdrawal symptoms, and tolerance. In general, these symptoms were more strongly connected with each other than with the rest of the IGD symptoms. The findings for network 2 showed that the different types of motivation were connected differently with the different IGD symptoms. For instance, the likeliest motivation for the preoccupation and escape symptoms is intrinsic motivation, and for negative consequences, it is low identified regulation. Overall, the findings showed a novel understanding of the structure of the IGD symptoms, and the motivations underlying them. The clinical implications of the findings for assessment and treatment of IGD are discussed.

Addiction Symptom Network of Young Internet Users: Network Analysis.

BACKGROUND: An increasing number of people are becoming addicted to the internet as a result of overuse. The Internet Addiction Test (IAT) is a popular tool for evaluating internet use behaviors. The interaction between different symptoms and the relationship between IAT and clinical diagnostic criteria are not well understood. OBJECTIVE: This study aimed to explore the core symptoms of internet addiction (IA) and the correlation between different symptoms of the IA symptom network. Network analysis was also conducted to explore the association between the IAT scale and the Diagnostic and Statistical Manual of Mental Disorders-5th edition (DSM-5) criteria for IA. METHODS: We recruited 4480 internet users (aged 14-24 years), and they completed the IAT. The final analysis included 63.50% (2845/4480) of the participants after screening the submitted questionnaires. Participants were classified into IA group and non-IA (NIA) group. By using partial correlation with Lasso regularization networks, we identified the core symptoms of IA in each group and compared the group differences in network properties (strength, closeness, and betweenness). Then, we analyzed the symptom networks of the DSM-5 diagnostic criteria and IAT scale for IA. RESULTS: A total of 12.47% (355/2845) of the patients were in the IA group and 87.52% (2490/2845) of the patients were in the NIA group, and both groups were evaluated for the following nodes: IAT_06 (school work suffers; strength=0.511), IAT_08 (job performance suffers; strength=0.531), IAT_15 (fantasize about being on the web; strength=0.474), IAT_17 (fail to stop being on the web; strength=0.526), and IAT_12 (fear about boredom if offline; strength=0.502). The IA groups had a stronger edge between IAT_09 (defensive or secretive about being on the web) and IAT_18 (hidden web time) than the NIA groups. The items in DSM-5 had a strong association with IAT_12 (weight=-0.066), IAT_15 (weight=-0.081), IAT_17 (weight=-0.106), IAT_09 (weight=-0.198), and IAT_18 (weight=-0.052). CONCLUSIONS: The internet use symptom network of the IA group is significantly different from that of the NIA group. Nodes IAT_06 (school work affected) and IAT_08 (work performance affected) are the resulting symptoms affected by other symptoms, whereas nodes IAT_12 (fear about boredom if offline), IAT_17 (inability to stop being on the web), and IAT_15 (fantasize about being on the web) are key symptoms that activate other symptoms of IA and are strongly linked to the inability to control the intention to play games in the DSM-5.

A serotonin voltammetric biosensor composed of carbon nanocomposites and DNA aptamer.

A sensitive and selective voltammetric biosensor composed of layer-by-layer (LbL) self-assembly of positively charged poly(diallyldimethylammonium)-wrapped oxidized single-walled carbon nanotubes (PDDA-oSWCNTs), negatively charged serotonin (5-hydroxytryptamine, 5-HT)-specific aptamer, and tyrosinase on Au nanoparticles deposited screen printed carbon electrode was developed for measurement of 5-HT. Surface characteristics of 5-HT biosensor were explored using scanning electron microscopy, X-ray photoelectron spectroscopy, and electrochemical impedance spectroscopy. The respective effects of 5-HT-specific aptamer and oSWCNTs on the detection of 5-HT were investigated by differential pulse voltammetry (DPV). The peak current at the potential of 0.29 V (vs. Ag/AgCl) increased with respect to 5-HT concentration resulting in two dynamic ranges from 0.05 to 0.5 and 1 to 20 µM with a limit of detection of 2 nM from the LbL biosensor in buffer solution, which were better than those without the LbL of aptamer and oSWCNTs. The developed biosensor was applied to the direct determination of 5-HT concentrations in undiluted healthy control and Internet gaming disorder serum samples. The results were verified by comparison with those from liquid chromatography-mass spectrometric analyses.

Treatment Efficacy of Internet Gaming Disorder With Attention Deficit Hyperactivity Disorder and Emotional Dysregulaton.

BACKGROUND: Recent youth with Attention Deficit Hyperactivity Disorder (ADHD) noticed emotional dysregulation if they had Internet Gaming Disorder (IGD). This study aims to understand the treatment efficacy of IGD with ADHD and emotional dysregulaton. METHOD: A total of 101 ADHD youths were recruited. We used the Chen Internet Addiction Scale and IGD criteria of the diagnotsic statistical manual (DSM)-5 to confirm IGD. The Swanson, Nolan, and Pelham questionnaire Version IV was used for symptoms of ADHD and oppositional defiant disorder. Disruptive mood dysregulation disorder was assessed by psychiatrist. RESULTS: There is a new phenomenon that emotional dysregulation has been frequently noticed in severely gaming-addicted ADHD youth. Treatment efficacy of IGD is good when the underlying symptom of ADHD is controlled. Symptom scores of disruptive mood dysregulation (DMDD) were significantly reduced by 71.9%, 74.8%, and 84.4% at week 2, 3, and 4, respectively (P ≤ .001) after adjusting baseline symptom severity. CONCLUSION: IGD may strongly arouse emotional dysregulation. Future DSM criteria could consider these gaming-addicted youth as a specific subclass of ADHD.

Validity, functional impairment and complications related to Internet gaming disorder in the DSM-5 and gaming disorder in the ICD-11.

BACKGROUND: Many concerns have been raised regarding the Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM-5) criteria for Internet gaming disorder and International Classification of Diseases, 11th Revision (ICD-11) criteria for gaming disorder. AIMS: In this study, we demonstrated the diagnostic validity of each criterion for Internet gaming disorder in the DSM-5 in terms of their intensity and frequency thresholds and evaluated functional impairments, unhealthy behaviors and complications among adults with Internet gaming disorder and gaming disorder. METHODS: We recruited 69 subjects with Internet gaming disorder, 69 regular gamers and 69 controls without regular gaming based on diagnostic interviewing conducted by a psychiatrist according to the DSM-5 Internet gaming disorder criteria. RESULTS: Except for the 'deceiving' and 'escapism' criteria, all criteria for Internet gaming disorder had a diagnostic accuracy ranging from 84.7% to 93.5% in differentiating between adults with Internet gaming disorder and regular gamers. A total of 44 participants with Internet gaming disorder (63.8%) fulfilled the gaming disorder criteria. In addition, 89% and 100% of the Internet gaming disorder and gaming disorder groups, respectively, had academic, occupational or social functional impairment. Both the Internet gaming disorder and gaming disorder groups had higher rates of delayed sleep phase syndrome and insomnia. The gaming disorder group also had a higher obesity proportion. CONCLUSION: The 'deceiving' and 'escapism' criteria had relatively lower diagnostic accuracy. Both the Internet gaming disorder and gaming disorder groups demonstrated functional impairments and unhealthy behaviors. They also exhibited complications, such as obesity and sleep disorders. These results support the utility of the DSM-5 Internet gaming disorder and ICD-11 gaming disorder criteria in identifying individuals who need treatment for both gaming addiction symptoms and complications resulting from the addiction.

Development and Validation of a Short-Form Internet Overuse Screening Questionnaire for Adults.

AIMS: The aim of the current study was to develop and validate a short-form of the internet overuse screening questionnaire (IOS-Qs). METHODS: A total of 571 adults were recruited from a representative, stratified, and multistage cluster sample. Among participants, 188 and 383 were used in the development and validation of the IOS-Qs, respectively. RESULTS: Experts' ratings and Rasch model analyses led to the selection of 8 items from the IOS-Qs; latent-class analysis using these 8 items revealed an estimated prevalence of 8.6% (33 out of 383) of problematic internet over-users. Problematic internet over-users were positively associated with a 1-year prevalence rate of any mental disorder (OR 3.08, p = 0.008), mood disorder (OR 7.11, p = 0.003), and depressive disorder (OR 5.22, p = 0.016). The receiver operating characteristic curves identified an optimal cutoff score of 9.5 for differentiating problematic internet over-users from unproblematic internet users with 94% sensitivity and 94% specificity. CONCLUSION: The results suggest that the IOS-Qs was valid, and items including social isolation were crucial to the brief distinction of at-risk internet users. Because of its brevity, the questionnaire can be effectively administered as a large-scale survey.

Findings on the relationship between Internet addiction and psychological symptoms in Brazilian adults.

This study evaluated the prevalence of Internet addiction (IA) and its association with negative psychological symptoms in Brazilian adults. A network analysis was conducted to estimate specific variables and their expected influence on IA. In this cross-sectional study, 15,476 adults (Mage  = 37.5, SD = 9.59) completed an open web-based survey. Three questionnaires were used: the Internet Addiction Test (IAT), Depression Anxiety and Stress Scale (DASS-21) and Satisfaction With Life Scale (SWLS). Based on IAT scores, participants were classified as No-Risk user (NRU), Low-Risk user (LRU) or High-Risk user (HRU). We observed that 4.8% of the participants were classified in the HRU group. In addition, their risk for severe symptoms of depression was 10 times higher and, for anxiety, seven times higher than that in the NRU group (p < .001). Time spent using smartphones was also significantly higher in the HRU group (Mhours  = 5.1, p < .001). The main factors associated with IA were depression, gender and anxiety, but the variable "having children" was the most influential in the IA network. These findings suggest that psychiatric symptoms are the main factors associated with IA among the adult population.

Network analysis of additional clinical features of (Internet) gaming disorder.

OBJECTIVES: There are dozens of screening instruments purporting to measure the (Internet) gaming disorder (IGD/GD). The two prominent diagnostic manuals, DSM-5 and ICD-11, list several additional diagnostic or clinical features and problems (e.g., neglect of sleep, neglect of daily duties, health deterioration) that should co-occur or be caused by the IGD/GD. It remains unclear how specific IGD/GD operationalizations (different screening scales) are related to these functional impairments. METHODS: To explore this, data on six measures of IGD/GD (IGDS9-SF, GDSS, GDT, GAMES test, two self-assessments) and 18 additional diagnostic features were collected from a sample of 1009 players who play digital games at least 13 h per week. A network approach was utilized to determine which operationalization is most strongly associated with functional impairment. RESULTS: In most of the networks, IGD/GD consistently emerged as the most central node. CONCLUSION: The similar centrality of IGD/GD, irrespective of its definition (DSM-5 or ICD-11) or operationalization, provides support for the valid comparison or synthesis of results from studies that used instruments coming from both DSM-5 and ICD-11 ontologies, but only if the goal is to evaluate IGD/GD relationships to other phenomena, not the relationships between the symptoms themselves.

The nature and characteristics of problem gaming, with a focus on ICD-11 diagnoses.

PURPOSE OF REVIEW: This review describes the diagnoses related to problem gaming that are included in ICD-11, published by the WHO in 2022. It summarizes the recent literature on the prevalence of Gaming Disorder, its structure, antecedents and comorbidities, and explores whether the range of diagnoses currently available adequately covers the range of experiences seen with problem gaming. RECENT FINDINGS: Overall, between 3 and 6% of the population worldwide are reported to have a gaming disorder as defined by ICD-11 or DSM-5. However, most studies are constrained by methodological issues such as nonrepresentative samples and the use of brief questionnaires to determine prevalence. ICD-11 Gaming Disorder is a psychometrically sound diagnosis. There is no diagnosis that currently captures the experience of harm from gaming, where the requirements for the diagnosis of Gaming Disorder are not reached. SUMMARY: There is evidence in support of the proposed new entity of 'Harmful Gaming', which encompasses mental and physical harm/impairment due to a repeated pattern of gaming, but where requirements for the diagnosis of Gaming Disorder are not met. Such a diagnosis would complete the spectrum of diagnoses available for problem or unhealthy gaming, similar to those for unhealthy substance use, and would provide a framework for a public health approach to reducing the overall harm from unhealthy gaming.

Digital Phenotypes for Early Detection of Internet Gaming Disorder in Adolescent Students: Explorative Data-Driven Study.

BACKGROUND: Limited awareness, social stigma, and access to mental health professionals hinder early detection and intervention of internet gaming disorder (IGD), which has emerged as a significant concern among young individuals. Prevalence estimates vary between 0.7% and 15.6%, and its recognition in the International Classification of Diseases, 11th Revision and Diagnostic and Statistical Manual of Mental Disorders, 5th Edition underscores its impact on academic functioning, social isolation, and mental health challenges. OBJECTIVE: This study aimed to uncover digital phenotypes for the early detection of IGD among adolescents in learning settings. By leveraging sensor data collected from student tablets, the overarching objective is to incorporate these digital indicators into daily school activities to establish these markers as a mental health screening tool, facilitating the early identification and intervention for IGD cases. METHODS: A total of 168 voluntary participants were engaged, consisting of 85 students with IGD and 83 students without IGD. There were 53% (89/168) female and 47% (79/168) male individuals, all within the age range of 13-14 years. The individual students learned their Korean literature and mathematics lessons on their personal tablets, with sensor data being automatically collected. Multiple regression with bootstrapping and multivariate ANOVA were used, prioritizing interpretability over predictability, for cross-validation purposes. RESULTS: A negative correlation between IGD Scale (IGDS) scores and learning outcomes emerged (r166=-0.15; P=.047), suggesting that higher IGDS scores were associated with lower learning outcomes. Multiple regression identified 5 key indicators linked to IGD, explaining 23% of the IGDS score variance: stroke acceleration (ß=.33; P<.001), time interval between keys (ß=-0.26; P=.01), word spacing (ß=-0.25; P<.001), deletion (ß=-0.24; P<.001), and horizontal length of strokes (ß=0.21; P=.02). Multivariate ANOVA cross-validated these findings, revealing significant differences in digital phenotypes between potential IGD and non-IGD groups. The average effect size, measured by Cohen d, across the indicators was 0.40, indicating a moderate effect. Notable distinctions included faster stroke acceleration (Cohen d=0.68; P=<.001), reduced word spacing (Cohen d=.57; P=<.001), decreased deletion behavior (Cohen d=0.33; P=.04), and longer horizontal strokes (Cohen d=0.34; P=.03) in students with potential IGD compared to their counterparts without IGD. CONCLUSIONS: The aggregated findings show a negative correlation between IGD and learning performance, highlighting the effectiveness of digital markers in detecting IGD. This underscores the importance of digital phenotyping in advancing mental health care within educational settings. As schools adopt a 1-device-per-student framework, digital phenotyping emerges as a promising early detection method for IGD. This shift could transform clinical approaches from reactive to proactive measures.