Background and aims: Following the recognition of ‘internet gaming disorder’ (IGD) as a condition requiring further study by the DSM‐5, ‘gaming disorder’ (GD) was officially included as a diagnostic entity by the World Health Organization (WHO) in the 11th revision of the International Classification of Diseases (ICD‐11). However, the proposed diagnostic criteria for gaming disorder remain the subject of debate, and there has been no systematic attempt to integrate the views of different groups of experts. To achieve a more systematic agreement on this new disorder, this study employed the Delphi expert consensus method to obtain expert agreement on the diagnostic validity, clinical utility and prognostic value of the DSM‐5 criteria and ICD‐11 clinical guidelines for GD.Methods: A total of 29 international experts with clinical and/or research experience in GD completed three iterative rounds of a Delphi survey. Experts rated proposed criteria in progressive rounds until a pre‐determined level of agreement was achieved.Results: For DSM‐5 IGD criteria, there was an agreement both that a subset had high diagnostic validity, clinical utility and prognostic value and that some (e.g. tolerance, deception) had low diagnostic validity, clinical utility and prognostic value. Crucially, some DSM‐5 criteria (e.g. escapism/mood regulation, tolerance) were regarded as incapable of distinguishing between problematic and non‐problematic gaming. In contrast, ICD‐11 diagnostic guidelines for GD (except for the criterion relating to diminished non‐gaming interests) were judged as presenting high diagnostic validity, clinical utility and prognostic value.Conclusions: This Delphi survey provides a foundation for identifying the most diagnostically valid and clinically useful criteria for GD. There was expert agreement that some DSM‐5 criteria were not clinically relevant and may pathologize non‐problematic patterns of gaming, whereas ICD‐11 diagnostic guidelines are likely to diagnose GD adequately and avoid pathologizing.

The American Psychiatric Association (APA) included internet game disorder (IGD) in section III of the Diagnostic and Statistical Manual of Mental Disorders-Fifth Edition (DSM-5) on the condition that it guaranteed more clinical research and experience. The World Health Organization (WHO) also included Game Disorder (GD) in the 11th final revision of the International Classification of Diseases (ICD-11) and recently recognized it as a diagnosis code. This study aims to compare clinical characteristics and gaming behavior patterns between the IGD diagnosis criteria proposed by the DSM-5 and the GD diagnosis criteria proposed by the ICD-11 based on clinical cohort data (c-CURE: clinic-Cohort for Understanding of internet addiction Rescue factors in Early life) obtained in the Republic of Korea. Psychologists and psychiatrists conducted semi-structured interviews with children/adolescents and their caregivers to identify IGD (Diagnostic Interview for Internet, Game, SNS, etc. Addiction, DIA), and comorbid psychiatric disorders (Kiddie-Schedule for Affective Disorders and Schizophrenia-Present and Lifetime Version-Korean version, K-SADS-PL). The cohort was divided into three IGD diagnosis groups (Normal, DSM5, DSM5 + ICD11) based on DSM-5 and ICD-11 diagnosis criteria. Internet usage pattern and addiction characteristics and psychiatric comorbidities were compared among the three IGD diagnosis groups. The Normal group consisted of 115 subjects, the DSM5 group contained 61 subjects, and the DSM5 + ICD11 group amounted to 12 subjects. The DSM5 + ICD11 group had a lower age of starting use of Internet/games/smartphones than other groups and the average time of Internet/game/smartphone use during weekdays/weekends was the highest. Also, in the eight items scored, excluding ‘deceiving’ and ‘craving’, the rate of threshold was highest in the DSM5 + ICD11 group, followed by the DSM5 group and the Normal group. On the other hand, ‘deceiving’ and ‘craving’ were the highest in DSM5, followed by DSM5 + ICD11 and Normal. The DSM5 + ICD11 group had significantly higher rates of depressive disorder, oppositional defiant disorder (ODD) and conduct disorder (CD) compared to other groups. This study provides implications for the clinical characteristics of IGD diagnosis in the field by comparing the DSM-5 IGD diagnosis criteria with the ICD-11 GD diagnosis criteria. Furthermore, this study provides empirical evidence that ICD-11 GD emphasizes serious symptoms such as functional impairment caused by excessive Internet/game/smartphone use over a long time, and it supports the validity of the ICD-11 GD diagnosis.

Kim MS, et al. Ann Occup Environ Med. 2018 Dec;30(1):31. https://doi.org/10.1186/s40557-018-0244-x

Adverse childhood experiences (ACEs) are known to be closely related to depression, anxiety and sleep problems. However, it remains unclear whether adolescents with ACEs have sleep problems regardless of depression or anxiety or under a mediating effect from depression or anxiety. Therefore, our aim was to examine whether depression or anxiety mediates the relationship between ACEs and sleep problems in adolescents by using a community sample. The Early Trauma Inventory Self Report–Short Form (ETISR-SF) and List of Threatening Experiences Questionnaire (LTE-Q) were used to assess traumatic ACEs. Ultimately, data from 737 students (M = 448, F = 289, 15.1 ± 1.4 years old) were included in the statistical analysis. A total of 576 (78.1%) participants reported that they had experienced one or more ACEs. Adolescents with ACEs had higher levels of depression, anxiety and sleep problems than did adolescents without ACEs, and boys tended to experience more trauma than girls. Depression and anxiety partially mediated the relationship between ACEs and sleep problems. The results of this study suggest the need for depression and anxiety interventions for adolescents with ACEs to reduce the long-term consequences, including sleep problems and physical health problems.

The clinical course of problematic smartphone use (PSU) remains largely unknown due to a lack of longitudinal studies. We recruited 193 subjects with smartphone addiction problems for the present study. After providing informed consent, the subjects completed surveys and underwent comprehensive interviews regarding smartphone usage. A total of 56 subjects among the 193 initially recruited subjects were followed up for six months. We compared baseline characteristics between persistent addicted users and recovered users at the end of the 6-month follow-up. Persistent problematic smartphone users displayed higher baseline smartphone addiction severity and were more prone to develop mental health problems at the follow-up. However, baseline depressive or anxiety status did not significantly influence the course of PSU. PSU behaved more like an addictive disorder rather than a secondary psychiatric disorder. Harm avoidance, impulsivity, higher Internet use, and less conversation time with mothers were identified as poor prognostic factors in PSU. Lower quality of life, low perceived happiness, and goal instability also contributed to persistent PSU, while recovery increased these scores as well as measures of self-esteem. These findings suggest that the Matthew effect is found in the recovery of PSU with better premorbid psychosocial adjustment leading to a more successful recovery. Greater clinical resources are required for interventions in vulnerable populations to modify the course of this increasingly prevalent problematic behavior worldwide.