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The proposed diagnosis of Internet gaming disorder (IGD) in DSM-5 has been criticized for “borrowing” criteria related to substance addiction, as this might result in misclassifying highly involved gamers as having a disorder. In this paper, we took a person-centered statistical approach to group adolescent gamers by levels of addiction-related symptoms and gaming-related problems, compared these groups to traditional scale scores for IGD, and checked how groups were related to psychosocial well-being using a preregistered analysis plan. We performed latent class analysis and regression with items from IGD and psychosocial well-being scales in a representative sample of 7865 adolescent European gamers. Symptoms and problems matched in only two groups: an IGD class (2.2%) having a high level of symptoms and problems and a Normative class (63.5%) having low levels of symptoms and problems. We also identified two classes comprising 30.9% of our sample that would be misclassified based on their report of gaming-related problems: an Engaged class (7.3%) that seemed to correspond to the engaged gamers described in previous literature, and a Concerned class (23.6%) reporting few symptoms but moderate to high levels of problems. Our findings suggest that a reformulation of IGD is needed. Treating Engaged gamers as having IGD when their poor well-being might not be gaming related may delay appropriate treatment, while Concerned gamers may need help to reduce gaming but would not be identified as such. Additional work to describe the phenomenology of these two groups would help refine diagnosis, prevention and treatment for IGD.

Gaming disorder has been described as an urgent public health problem and has garnered many systematic reviews of its associations with other health conditions. However, review methodology can contribute to bias in the conclusions, leading to research, policy, and patient care that are not truly evidence-based. This study followed a pre-registered protocol (PROSPERO 2018 CRD42018090651) with the objective of identifying reliable and methodologically-rigorous systematic reviews that examine the associations between gaming disorder and depression or anxiety in any population. We searched PubMed and PsycInfo for published systematic reviews and the gray literature for unpublished systematic reviews as of June 24, 2020. Reviews were classified as reliable according to several quality criteria, such as whether they conducted a risk of bias assessment of studies and whether they clearly described how outcomes from each study were selected. We assessed possible selective outcome reporting among the reviews. Seven reviews that included a total of 196 studies met inclusion criteria. The overall number of participants was not calculable because not all reviews reported these data. All reviews specified eligibility criteria for studies, but not for outcomes within studies. Only one review assessed risk of bias. Evidence of selective outcome reporting was found in all reviews-only one review incorporated any of the null findings from studies it included. Thus, none were classified as reliable according to prespecified quality criteria. Systematic reviews related to gaming disorder do not meet methodological standards. As clinical and policy decisions are heavily reliant on reliable, accurate, and unbiased evidence synthesis; researchers, clinicians, and policymakers should consider the implications of selective outcome reporting. Limitations of the current summary include using counts of associations and restricting to systematic reviews published in English. Systematic reviewers should follow established guidelines for review conduct and transparent reporting to ensure evidence about technology use disorders is reliable.

Annotated bibliographies summarize literature, but training, experience, and time are needed to create concise yet accurate annotations. Summaries generated by artificial intelligence (AI) can save human resources, but AI-generated content can also contain serious errors. To determine the feasibility of using AI as an alternative to human annotators, we explored whether ChatGPT can generate annotations with characteristics that are comparable to those written by humans. We had 2 humans and 3 versions of ChatGPT (3.5, 4, and 5) independently write annotations on the same set of 15 publications. We collected data on word count and Flesch Reading Ease (FRE). In this study, 2 assessors who were masked to the source of the annotations independently evaluated (1) capture of main points, (2) presence of errors, and (3) whether the annotation included a discussion of both the quality and context of the article within the broader literature. We evaluated agreement and disagreement between the assessors and used descriptive statistics and assessor-stratified binary and cumulative mixed-effects logit models to compare annotations written by ChatGPT and humans. On average, humans wrote shorter annotations (mean 90.20, SD 36.8 words) than ChatGPT (mean 113, SD 16 words) which were easier to interpret (human FRE score, mean 15.3, SD 12.4; ChatGPT FRE score, mean 5.76, SD 7.32). Our assessments of agreement and disagreement revealed that one assessor was consistently stricter than the other. However, assessor-stratified models of main points, errors, and quality/context showed similar qualitative conclusions. There was no statistically significant difference in the odds of presenting a better summary of main points between ChatGPT- and human-generated annotations for either assessor (Assessor 1: OR 0.96, 95% CI 0.12-7.71; Assessor 2: OR 1.64, 95% CI 0.67-4.06). However, both assessors observed that human annotations had lower odds of having one or more types of errors compared to ChatGPT (Assessor 1: OR 0.31, 95% CI 0.09-1.02; Assessor 2: OR 0.10, 95% CI 0.03-0.33). On the other hand, human annotations also had lower odds of summarizing the paper's quality and context when compared to ChatGPT (Assessor 1: OR 0.11, 95% CI 0.03-0.33; Assessor 2: OR 0.03, 95% CI 0.01-0.10). That said, ChatGPT's summaries of quality and context were sometimes inaccurate. Rapidly learning a body of scientific literature is a vital yet daunting task that may be made more efficient by AI tools. In our study, ChatGPT quickly generated concise summaries of academic literature and also provided quality and context more consistently than humans. However, ChatGPT's discussion of the quality and context was not always accurate, and ChatGPT annotations included more errors. Annotated bibliographies that are AI-generated and carefully verified by humans may thus be an efficient way to provide a rapid overview of literature. More research is needed to determine the extent that prompt engineering can reduce errors and improve chatbot performance.

The coronavirus disease (COVID-19) pandemic has revealed many areas of public health preparedness that are lacking, especially in lower- and middle-income countries. Digital interventions provide many opportunities for strengthening health systems and could be vital resources in the current public health emergency. We provide several use cases for infection control, home-based diagnosis and screening, empowerment through information, public health surveillance and epidemiology, and leveraging crowd-sourced data. A thoughtful, concerted effort—leveraging existing experience and robust enterprise-grade technologies—can have a substantive impact on the immediate and distal consequences of COVID-19.

Background: Little is known about strategies or mechanics to improve self-regulation of video game play that could be developed into novel interventions. This study used a participatory approach with the gaming community to uncover insider knowledge about techniques to promote healthy play and prevent gaming disorder. Methods: We used a pragmatic approach to conduct a convergent-design mixed-methods study with participants attending a science fiction and education convention. Six participants answered questions about gaming engagement and self- or game-based regulation of gaming which were then categorized into pre-determined (a priori) themes by the presenters during the presentation. The categorized themes and examples from participant responses were presented back to participants for review and discussion. Seven participants ranked their top choices of themes for each question. The rankings were analyzed using a nonparametric approach to show consensus around specific themes. Results: Participants suggested several novel potential targets for preventive interventions including specific types of social (e.g., play with others in a group) or self-regulation processes (e.g., set timers or alarms). Suggestions for game mechanics that could help included clear break points and short missions, but loot boxes were not mentioned. Conclusions: Our consensus development approach produced many specific suggestions that could be implemented by game developers or tested as public health interventions, such as encouraging breaks through game mechanics, alarms or other limit setting; encouraging group gaming; and discussing and supporting setting appropriate time or activity goals around gaming (e.g., three quests, one hour). As some suggestions here have not been addressed previously as potential interventions, this suggests the importance of including gamers as stakeholders in research on the prevention of gaming disorder and the promotion of healthy gaming. A large-scale, online approach using these methods with multiple stakeholder groups could make effective use of players’ in-depth knowledge and help speed discovery and translation of possible preventive interventions into practice and policy.

Depressive symptoms have been associated with how an individual is involved with their online activity, particularly their experience of the balance between their skills and the online challenges they may encounter. Interestingly, the occurrence of different depressive typologies has been supported, whilst the concept of online flow has been introduced to describe immersive engagement with online tasks/actions due to experiencing challenges. To assess such hypotheses, this study aims to determine the potentially distinct depressive profiles best describing a normative sample of gamers whilst also assessing how these may vary in their reported online flow levels both concurrently and longitudinally. The sample included 565 gamers ranging from 12 to 68 years old, who were longitudinally assessed in the community, 6 months apart, at two different timepoints. Their depressive and online flow behaviours were examined via the Depression, Anxiety, and Stress Scale and the Online Flow Questionnaire, respectively. Advanced latent class analyses indicated five distinct depressive profiles: Mild Depression With Low Self-Deprecation (16.6%), More Severe Depression With High Devaluation of Life (11.9%), No Depression With Low Motivation/Self-Esteem (10.1%), High Self-Image/Life Satisfaction (54.2%), and Moderate Depression With High Self-Deprecation (7.26%). Furthermore, a significant difference in concurrent and prospective online flow scores between different depressive profiles was revealed. Results support that individuals experiencing higher online flow may differ regarding their depressive symptoms, with significant implications for assessment and intervention practice. Les symptômes dépressifs ont été associés à la façon dont une personne est impliquée dans son activité en ligne, en particulier son expérience de l'équilibre entre ses compétences et les défis en ligne qu'elle peut rencontrer. Fait intéressant, la présence de différentes typologies dépressives a été corroborée, tandis que le concept de flux en ligne a été introduit pour décrire l'engagement immersif avec des tâches/actions en ligne en raison de difficultés rencontrées. Pour évaluer ces hypothèses, cette étude vise à déterminer les profils dépressifs potentiellement distincts qui décrivent le mieux un échantillon normatif de joueurs, tout en évaluant la façon dont ces profils peuvent varier dans leurs niveaux de flux en ligne rapportés, à la fois simultanément et longitudinalement. L'échantillon comprenait 565 joueurs âgés de 12 à 68 ans, qui ont été évalués longitudinalement dans la communauté, à 6 mois d'intervalle, à deux moments différents. Leurs comportements dépressifs et de flux en ligne ont été examinés à l'aide de l'échelle de dépression, d'anxiété et de stress et du questionnaire de flux en ligne, respectivement. Des analyses avancées de classes latentes ont révélé cinq profils dépressifs distincts : Dépression légère avec faible dépréciation de soi (16,6%), dépression plus grave avec forte dévalorisation de la vie (11,9%), pas de dépression avec faible motivation/estime de soi (10,1%), image de soi/satisfaction de la vie élevée (54,2%) et dépression modérée avec forte dépréciation de soi (7,26%). De plus, une différence significative dans les scores de flux en ligne simultanés et prospectifs entre les différents profils dépressifs a été révélée. Les résultats confirment que les personnes ayant un flux en ligne plus élevé peuvent présenter des symptômes dépressifs différents, ce qui a des implications significatives pour l'évaluation et la pratique d'intervention. Public Significance Statement The present study finds that the concept of \"online flow\"-the deeply engaging experience of online gaming-varies significantly among gamers with different depressive profiles. Understanding these differences is crucial not just for recognising the potential risks of gaming disorder but also for developing targeted digital interventions and treatments that could improve psychological well-being. This knowledge is particularly relevant as digital interactions continue to shape significant aspects of our daily lives, influencing our mental health and leisure activities.

Background In Saudi Arabia, the rapid growth of digital media and smartphone use has raised concerns about problematic usage and its impacts on well-being, especially among young people. Research on stakeholder perspectives regarding intervention strategies remains limited. Objective This study aimed to gather insights from societal stakeholders, including youth, parents, policymakers, industry leaders, clinicians, educators, and digital media users, to inform culturally tailored interventions for digital well-being in Saudi Arabia. Methods A purposeful non-random sample of 92 participants representing different stakeholder groups was recruited to complete an online survey, answering questions about their experiences and perspectives on digital media use. Primary stakeholder group was assigned based on participant self-selection. We analyzed distributions of categorical variables related to media use time, reasons for use, impacts, self-regulation strategies, and perceived effectiveness of interventions (e.g., education programs, media campaigns, Internet use restrictions). Results Of the participants, 63.0% were male, and 46.7% were under 25 years old. Regular digital media users, individuals with problematic Internet use, and clinicians/health professionals comprised 26.1%, 18.5%, and 18.5% of respondents, respectively. Extensive screen time was common, with 47.8% reporting four or more hours of recreational digital use on weekdays and 56.6% on weekends. Participants reported both positive impacts (e.g., social connections, school/work performance) and negative impacts (e.g., sleep disruption, reduced physical activity) of digital media use. Efforts to regulate media use were reported by 72.8%, with strategies like deleting apps or digital detoxes. At least 50.0% of participants endorsed all proposed intervention approaches as likely effective for improving digital well-being, with educational programs for parents, school programs, and regulatory apps receiving over 75.0% support. Children and adolescents were seen as key target groups for these interventions. Conclusions Findings from this diverse stakeholder sample suggest that digital well-being interventions in Saudi Arabia should prioritize youth, focusing on education-based approaches and apps for media regulation. Incorporating these perspectives can lead to culturally relevant interventions addressing the unique challenges of digital media use in Saudi Arabia. The generalizability of the findings may be limited due to sample size and potential overrepresentation of certain stakeholder groups.

How can we stay healthy in an increasingly digital society? The current study evaluates the literature at the intersection of health and digital media use. It identifies which universally relevant topics are studied using a quantitative, reproducible topic modelling approach to inform a scoping review. Relevant scientific literature was identified in July 2023 using three databases (Web of Science, PubMed and PsycInfo). Topics of interest were determined in the integrated corpus (N = 136 394) by evaluation of keywords for health relevance, resulting in 554 relevant keywords. Keywords were then sorted into topic groups and the content of each topic group was summarized, primarily using reviews and meta-analyses in each group. We retained 16 topic groups of interest: physical health covers sleep, exercise/sports, sedentarism/bodyweight, physical symptoms, eye health and eating. Mental health covers negative and positive mood states, fatigue/burnout, self-image, cognition and brain, focus/concentration and academic performance. Social health covers both social support and negative social states. Emerging topics echo earlier work by the World Health Organization, but also identified new elements. Only a small number of studies covered multiple health domains. We suggest that evidence based advice about healthy engagement in digital media use and screen time could benefit from a broader focus.

Background Despite the increasing use of digital health interventions (DHIs) in low- and middle-income countries (LMICs), gender disparities persist in access, utilization, and outcomes. Barriers to women’s phone ownership and use include affordability, digital literacy, and social norms; these are not only technological, but institutional as reflected in the limited integration of gender equity in national digital health strategies. While the body of evidence on DHI effectiveness is growing how to implement gender equitable digital programs is less clear. Methods We conducted an umbrella review of systematic reviews to synthesize gender-related outcomes on DHIs in LMICs. Eligible DHIs included those used by community health workers and client-facing interventions for health communication, self-management, and symptom monitoring. We included only reviews that reported quantitative outcomes with confidence intervals and reported the study design for included studies. We classified interventions along the Gender Equality Continuum. Findings were reported using PRISMA guidelines. Results Of the reviews analyzed, only eight (5.5%) explicitly applied a gender lens. Barriers to women’s participation in DHIs included limited phone ownership, financial dependence, and socio-cultural norms restricting access to health information. Gender-responsive interventions that accounted for these challenges were rare. Gender-transformative approaches (which seek to shift harmful gender norms), such as engaging men in health-seeking behaviors, showed promise but remain underutilized and under evaluated. Measurement of gender-related barriers and their influence on outcomes was limited. No studies used validated gender scales. Conclusions Based on these findings, we propose the Gender Framework for Responsive and Adaptive Design in Digital Health (FORWARD) to guide implementers in designing DHIs that address gender disparities. Gender FORWARD emphasizes gender-responsive design at individual (i.e. literacy and access), workforce (i.e. usability, interoperability, and supportive supervision), and ecosystem (i.e. capture and use of gender data in decision-making) levels. This framework offers a critical resource for researchers, implementors, and policy makers to improve digital health equity by ensuring interventions are inclusive, accessible, and sustainable across genders.

Background Digital technologies proliferate in many people's lives around the world with over 65% of these technology users being online. Children and youth are among the most prominent adopters of digital technologies in forms such as video gaming, social media, and online shopping. Problematic use of digital technologies can lead to poorer school/work performance, neglect of self-care skills, and comorbidities with other mental health issues. However, when used non-problematically, digital technology can also contribute to improving health and well-being. With the abundance of literature published, many reviews have sought to collate literature on treatment and interventions for children and youth with varying results. Thus, our proposed systematic review aims to synthesize current systematic reviews and meta-analyses on interventions and treatment of problematic digital technology use in children and youth (up to 25 years old). Methods As part of a three-paper series, a systematic search was completed in PsycINFO, Web of Science, and PubMed databases. Grey literature databases of the World Health Organization (IRIS database) and ClinicalTrials.gov were also searched. Furthermore, hand-searching of reference lists was also conducted. Title and abstract screening, followed by full-text screening, were completed by at least two independent reviewers. For this review, the extractions and the quality of selected reviews will be assessed using AMSTAR 2.0 by two authors independently and reviewed by two additional authors. Results Results will be presented in narrative and tabular form. The results of this study are expected to offer insights into the populations of children and youth studied, treatments/interventions provided, outcomes, results, limitations, and conclusions of literature from the past five years. Feasibility and generalizability of the reviews will also be discussed. Conclusions Methodological strengths and weaknesses of reviewed studies will point to gaps in knowledge and can be used to inform future areas of policy and research.