Approximately 970 million people worldwide suffer from mental disorders, yet over 60% do not seek professional help. Key barriers include low mental health literacy (MHL), insufficient awareness of psychological issues, and the overwhelming and non-transparent nature of information retrieval tools. Explainable artificial intelligence (XAI) can provide transparent and personalized feedback; however, its unique contribution to facilitating professional psychological help-seeking behavior remains unclear. Two randomized scenario-based experiments were conducted. Experiment 1 (n = 168) examined the effect of XAI on professional psychological help-seeking behavior. Experiment 2 (n = 178), utilizing a virtual simulation program based on AI search, tested the interaction between XAI and MHL and the mediating effect of psychological problem recognition. Both XAI and MHL significantly enhanced participants’ psychological problem recognition and professional psychological help-seeking behavior. A significant interaction was observed; XAI had a stronger facilitative effect on psychological problem recognition and professional psychological help-seeking behavior, particularly among participants with lower MHL. Furthermore, psychological problem recognition mediated the effects of both XAI and MHL on professional psychological help-seeking behavior. XAI can compensate for low MHL by reshaping individuals’ psychological problem recognition, thereby promoting the utilization of professional mental health services.

Adolescents’ internet adaptability (IA) is crucial for their online behavior and mental health. Serious games (SGs), as an emerging educational tool, hold promise for enhancing this adaptability through engaging, goal-oriented learning. Yet, direct evidence in this area remains limited. This viewpoint aims to clarify the mechanisms through which SGs enhance adolescents’ IA and to derive corresponding design principles that can inform educational practice and game development. Drawing on insights from both Chinese and international studies, this study adopts a cross-contextual perspective to explore how SGs can foster IA in varied educational environments. Beyond synthesizing existing findings, this viewpoint provides an integrated account of why IA is essential in contemporary digital life and how SGs can support its development. It proposes a 3-stage framework, illustrating how contextualized design, real-time feedback, and dynamic tasks promote experiential learning, self-regulation, and the transfer of online skills. Based on this framework, the study further articulates 6 core design principles: clear goal definition, interaction diversity, contextual authenticity, immediate, scaffolding and explanatory feedback, a dynamically adaptive learning environment, and safety-by-design for digital well-being. These principles translate the core characteristics and mechanisms of SGs into actionable guidance for developing effective IA interventions. By synthesizing theoretical insights with practical considerations, this viewpoint highlights how SGs can serve as accessible and scalable tools to support adolescents in navigating increasingly complex digital environments. Together, these insights provide practical implications for educators, curriculum designers, and digital game developers seeking to foster adolescents’ safe, responsible, and adaptive engagement in online environments.

Insomnia and depression frequently co-occur during adolescence, posing significant challenges to adolescent mental health. However, the direction of their

The development of digital technology has facilitated the 'democratisation' of the internet, but it has also provided opportunities for online hate speech, which can have negative effects on individuals, groups, and society. Therefore, addressing online hate speech is crucial. However, owing to the paradox between free speech and the regulation of hate speech, soft hate speech, which is morally unacceptable but not directly constrained by law, as hard hate speech is, can result in harmful consequences in more subtle forms. In response, this study proposes shifting the focus of online hate speech research to individuals, with the objective of influencing the comment modification intention of soft hate speech commenters through AI-based persuasion and its associated strategies. Specifically, Study 1 establishes baseline effects by comparing AI-based persuasion against no-persuasion and irrelevant-persuasion controls. A pilot study examines how participant perspective moderates strategy effectiveness, providing the empirical basis for Study 2’s design. Study 2 further examines the comparative effects of emotional labelling and reason-explanation strategies and the mediating role of perceived persuasiveness under higher ecological validity conditions. In summary, this study explores a human-centric approach to responding to online soft hate speech and, through controlled scenario-based experiments, provides preliminary evidence that AI-based persuasion has a positive effect on scenario-based comment modification intention, with perceived persuasiveness identified as a psychological mechanism underlying this effect.