A Phase 3 Bridging Study of Viloxazine ER Capsules in Korean Children and Adolescents With ADHD
Interventions: Drug: AK-D101; Drug: Placebo
Sponsors: Alvogen Korea
Not yet recruiting
The burden of care, parenting stress, and navigating welfare services: parents’ everyday experiences of young children with autism spectrum disorder
Stigma and quality of life in hospitalized schizophrenia patient-family caregiver dyads in Northern China: an actor-partner interdependence model analysis
Knowledge Graphs Based on Meta-Analysis Papers Improve the Quality of Case Formulation: Mixed Methods Design
Background: Case formulation (CF) is a core skill for therapists; however, creating high-quality CFs requires considerable time. Objective: This study aims to demonstrate that providing a knowledge graph based on meta-analytic literature can enhance CF quality. Methods: Five groups were established, including 4 large language model groups and 1 human expert group, each generating 25 CFs based on 25 vignettes. The control group with Claude (Sonnet 3.7; Anthropic) produced 25 CFs. The personalization group served as the control group with additional personalization prompts. The knowledge graph group used a large language model that generated 25 CFs, which was provided with a meta-analysis knowledge graph. Further incorporation of additional personalization prompts then comprised the knowledge graph with personalization group. Finally, the expert group consisted of 25 CFs generated by a human expert. These 125 CFs in total were evaluated for general quality (ie, correctness, completeness, feasibility, and consistency) using a 7-point scale and 18 essential elements with binary scores (0 or 1) by another human expert. The CFs were also qualitatively analyzed. Results: The knowledge graph and knowledge graph with personalization groups scored significantly higher than the control group in terms of correctness, completeness, and feasibility. The expert group scored significantly higher on consistency than the machine-generated groups. Additionally, there was no significant difference in the feasibility scores among the knowledge graph, knowledge graph with personalization, and expert groups. The qualitative evaluation suggested that human CFs narrow the text to content that is easy for the client to read, whereas machine CFs are more likely to include expressions that are unnatural to the client. Conclusions: These results indicate that providing knowledge graphs to novice therapists increases the correctness, completeness, and feasibility of CF. Providing experienced therapists with knowledge graphs is suggested to improve the quality of their CF and mental health services.
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Expedited Transition to Digital Delivery of Recovery Support Services Due to the COVID-19 Pandemic: Mixed Methods Needs Assessment
Background: Recovery support services (RSS) are an evidence-based approach to support recovery from substance use disorders, most often composed of peer-to-peer support, referrals to housing, job training, and other forms of prosocial engagement and activities. During the COVID-19 pandemic, RSS providers quickly converted in-person services to digital delivery to avoid disruption. It is unclear if this rapid conversion impacted the delivery of services or if this delivery model could enhance RSS reach and uptake more generally by extending the reach of RSS providers and offering an alternative delivery method and access point. Objective: The goal of this study was to identify how RSS providers in Texas adapted their services for digital delivery and to what extent, if at all, technology limitations (eg, lack of digital infrastructure) were present. Methods: We conducted an electronic survey of 85 RSS providers, assessing their current capacity and methods for the digital recovery support service (D-RSS), followed by semistructured online interviews with a subset of 20 respondents. Results: Most survey respondents (74/85, 87.1%) used D-RSS, though they used many dated technologies, devices, and platforms for service delivery. Many respondents indicated that they use Zoom (Zoom Video Communications) videoconferencing to communicate with participants; however, providers also indicated that they must use several different technology platforms to accomplish their service delivery goals. Four main themes emerged from the interviews: (1) the impact of the COVID-19 pandemic on RSS, (2) barriers and facilitators to technology-delivered D-RSS, (3) awareness and expectations regarding the use of D-RSS, and (4) training needs to deliver D-RSS. Conclusions: RSS organizations have access to technology for D-RSS; however, the technology is often outdated. Because the pandemic required a rapid and unexpected shift to D-RSS to maintain and potentially expand access during a public health emergency, providers desire guidance for training staff and participants on how to best use technology. A subset of providers endorsed the potential of a unified platform for D-RSS delivery, especially for data capture. Most barriers to D-RSS identified by our respondents may be addressable through the streamlined deployment of technology resources, rigorous training and onboarding programs in best practices for providers and participants, and tailored implementation strategies for varying local contexts.
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Governing Ethical Tensions in Youth Digital Mental Health Research
As mental health research increasingly aims to generate societal impact, researchers operate at the intersection of innovation and ethical responsibility. Drawing on experiences from the cocreated NEON Young Norway Study on youth recovery narratives, this viewpoint identifies four ethical tensions that arise from the existing governance frameworks in youth digital mental health research: (1) balancing safeguarding against harm with youth participation, (2) protecting privacy without undermining authentic storytelling, (3) governing unpredictable outcomes of cocreated research, and (4) meeting ethical and legal standards while ensuring youth-friendly communication. These tensions highlight limitations in mental health research that adopts participatory and digital approaches, as this often struggles to accommodate iterative designs, narrative data, and cross-sector collaboration. We argue that responsible youth mental health research requires ethics to be understood as a dynamic, participatory practice that supports safe and equitable inclusion, rather than having a focus on risk prevention. Ethical governance, therefore, needs to evolve toward proportionate, context-sensitive approaches that can enable innovation while protecting young people’s rights, agency, and voices.
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Use of a Conversational Agent for Training Mental Health Professionals in Suicide Safety Planning: Pilot Feasibility and Acceptability Study
Background: Safety planning is recognized as one of the most effective interventions for reducing suicidal behaviors. The quality of safety plans strongly depends on professional training, and traditional methods, such as role-playing, are time-consuming and offer limited opportunities for repetition across diverse patient profiles. Generative artificial intelligence (GenAI) may provide innovative solutions by offering accessible, flexible, and realistic training environments. Objective: This pilot study aimed to evaluate the acceptability and feasibility of a GenAI-based simulator designed to train mental health professionals in safety planning. Methods: Twenty nurses and nursing assistants from psychiatric units in a French university hospital participated in a pre-post, single-session evaluation. After self-rating their ability, competence, and willingness to manage patients experiencing suicidal ideation, participants interacted individually with the text-based simulator for 20 minutes to perform a safety plan with a chatbot, then completed postsimulation acceptability items, and open-ended feedback. Composite scores were computed: acceptability (eg, helpfulness; 0‐40), realism (eg, looking like real interaction with patient; 0‐20), and challenge (eg, emotional challenge; 0‐30). Pre-post changes were tested (Wilcoxon signed-rank test), and age-group comparisons were performed. Results: Acceptability was high (mean 31.9/40, SD 5.3; median 32, IQR 7), realism moderate-to-high (mean 15.1/20, SD 4.1; median 15, IQR 5.25), and challenge manageable (mean 17.0/30, SD 8; median 18, IQR 12.5). Participants rated usefulness (mean 7.65/10, SD 1.57; median 8, IQR 1.57), perceived learning (mean 7.6/10, SD 1.79; median 8, IQR 2), recommendation to use the chatbot for training (mean 8.3/10, SD 1.59; median 9, IQR 2.25), and feedback quality (mean 8.35/10, SD 1.27; median 8.5, IQR 1.25) favorably. Willingness to actively manage patients experiencing suicidal ideation significantly increased postsimulation (.03). Younger participants reported higher acceptability (.04) and realism (.03). Participants reported minimal concerns regarding the simulator’s use. Conclusions: This pilot study demonstrates that a GenAI-based simulator for safety planning is feasible and highly acceptable among experienced mental health professionals. The findings are promising and warrant larger, controlled trials to assess impacts on training effectiveness and patient outcomes.
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Author Correction: Digital AVATAR therapy for distressing voices in psychosis: the phase 2/3 AVATAR2 trial
Nature Medicine, Published online: 30 June 2026; doi:10.1038/s41591-026-04540-1
Author Correction: Digital AVATAR therapy for distressing voices in psychosis: the phase 2/3 AVATAR2 trial

