The rapid digital transformation in healthcare has reshaped the landscape of mental health practice and education. Universities face the challenge of balancing technological innovation with the preservation of humanistic values and relational care, particularly within the formation of health professionals. This article aims to discuss the implications of digitalization for mental health education in university contexts and to propose an integrative model that reconciles technological advancement with empathy, ethical reflection, and clinical humanism. A conceptual review was conducted, combining literature on health professions education, digital health technologies, and transdisciplinary pedagogical practices. Theoretical perspectives from psychology, medicine, and education were integrated to identify critical tensions and opportunities within the digital transformation of higher education. Universities that embed humanistic dialogue, reflective practice, and interprofessional collaboration within curricula demonstrate greater resilience and adaptability in training in mental health. Higher education institutions must act as laboratories for balancing technology and humanism. Future professionals require both digital competence and emotional intelligence to ensure that mental health care remains centered on the individual. Ethical education, empathy, and common sense should guide the digital evolution of mental health teaching and practice.

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Digital narratives no longer emerge solely from human intention; they are increasingly co-constructed within ecosystems shaped by intelligent systems. This paper interrogates how algorithmic processes, particularly those driven by artificial intelligence, reconfigure narrative authority, temporality, and meaning-making. Rather than treating technology as a neutral conduit, the study positions intelligent systems as active narrative agents that influence both the production and circulation of stories. The inquiry begins by re-examining foundational assumptions in narrative theory, where authorship was historically singular and linear, and contrasts this with contemporary, data-driven storytelling environments. Through a conceptual-analytical approach, the paper traces the shift from static digital storytelling to adaptive, generative, and interactive narrative forms. It argues that narratives produced within intelligent systems operate through probabilistic logic, introducing fluidity and indeterminacy that challenge traditional notions of coherence and authenticity. A proposed conceptual diagram illustrates the triadic relationship between human creators, algorithmic systems, and audiences, emphasizing feedback loops that continuously reshape narrative outputs. This transformation carries significant implications for cultural production, epistemology, and ethical accountability. The paper concludes by calling for a re-theorization of narrative frameworks within digital humanities to accommodate the agency of intelligent systems.

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Online communities are valuable tools for information exchange, professional networking, and peer support for health professionals. However, evidence of how and why health professionals are engaging with their peers online is lacking. This study aimed to identify the types and frequency of peer online interactions conducted by health professionals across a broad range of online platforms and identify factors influencing their use. We used online questionnaires to capture health professionals’ online behaviours, digital competency, feelings of online social connectedness, and well-being. Participants (n = 119) used an average of 3.4 platforms. Facebook (66.39%), LinkedIn (64.71%), and WhatsApp (46.22%) were the platforms with the highest account ownership relative to Instagram (45.38%), X (39.50%), YouTube (27.73%), TikTok (14.29%), and Reddit (11.76%). The types of interaction (active vs. passive) health professionals used to engage with their peers varied by platform. A key factor motivating participants to engage in online communities was that our participants possessed the knowledge and skills to leverage the online resources provided by their collective peers for professional benefits. The study revealed a positive association between broader online platform use and greater feelings of social connectedness, while the relationship between social connectedness and well-being was more complex after adjustment for demographic factors. The results of this study highlight the benefits of online peer engagement but also identify strategies that can be implemented to support and enhance the use of online communities for health professionals. Continuing work in this field will enhance understanding of the professional and social benefits provided by online communities for health professionals.

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Trans-synthetic kinship and meta-synthetic ecology reconceive cognition as a co-emergent, relational process distributed across human, synthetic, ecological, and technological assemblages. Intelligence arises through intra-active embodiment, sympoietic entanglement, and multispecies interaction rather than as a property of discrete agents. Trans-synthetic kinship situates synthetic agents as relational companions within morphogenetic and cybernetic fields, while meta-synthetic ecology articulates multi-scale relationality from microtemporal embodied resonance to planetary feedback. The model was developed through a comparative analysis of structuralist, post-structuralist, and humanistic-critical perspectives on human experience and expression, tabulating nine thematic domains revealing the ontological, ethical, and cultural stakes of AI and robotics. Design principles and practical interventions were derived from these analyses, which lists 90 interventions for operationalizing co-emergent cognition in synthetic systems. Analyses of embodied and co-emergent forms of agency, alongside processes of autonomy, reveal how synthetic bodies function as operative sites for distributed intelligence, and show that autonomy emerges through relationally negotiated processes that adapt over time and respond dynamically to context. Applying the model fosters collaborative stewardship among technologists, activist-practitioners, policymakers, and community stakeholders; it cultivates socio-technical ecologies characterized by justice, relational attunement, context adaptability, and resilience to complex social and environmental pressures.

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This study examines how artificial intelligence (AI) interacts with structural transformation to shape labour market outcomes in India, with particular focus on whether labour-intensive growth remains a viable strategy for inclusive development. India's demographic advantage demands large-scale productive employment, yet traditional pathways through manufacturing-led industrialisation are being disrupted by AI and automation technologies that affect both routine and cognitive tasks across sectors. Using a descriptive-analytical method, this paper draws on secondary data from the Periodic Labour Force Survey (PLFS), the India Employment Report (2024), World Bank indicators, OECD (Organization for Economic Co-operation and Development) publications, and IMF (International Monetary Fund) research to examine sectoral employment trends, AI adoption patterns, and workforce exposure across skill levels and regions. The findings reveal that India's structural transformation remains incomplete: employment growth is concentrated in low-productivity construction and informal services rather than in manufacturing. AI adoption follows a highly uneven trajectory, confined largely to formal, urban, high-skill environments, while the majority of workers remain in low-exposure, low-complementarity occupations that are bypassed by technological productivity gains. This creates a form of technological dualism that reinforces existing labour market segmentation. The study concludes that while labour-intensive growth retains developmental relevance, its viability depends on the simultaneous pursuit of technological upgrading, broad-based skill development, and supportive institutional frameworks. India's challenge lies not in choosing between employment and technology, but in redesigning its growth strategy so that both reinforce each other.

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The contemporary expansion of platform economies has produced labor landscapes in the Global South that are at once hyper-visible and profoundly obscured. Workers such as drivers, content moderators, and microtaskers perform essential functions that sustain digital infrastructures, yet their contributions remain largely invisible, rendered abstract within algorithmic systems. This paper interrogates the mechanisms through which invisibility is produced, tracing the interlocking layers of digital labor, platform governance, and socio-economic precarity. Employing a conceptual-analytical methodology, it examines case studies from ride-hailing, crowdwork, and content moderation platforms, highlighting the asymmetrical distribution of agency between platforms and laborers. Analytical attention focuses on three layers: input labor, algorithmic mediation, and economic output, revealing how platforms simultaneously operationalize, quantify, and obscure human work. Methodologically, the paper adopts a conceptual-analytical approach grounded in secondary empirical literature and comparative case illustrations from the Global South. Diagrams illustrate labor flows and visibility gradients, situating worker contributions within broader computational and economic structures. Findings indicate that invisibility is not incidental but structurally embedded: it serves both profit maximization and epistemic obfuscation, reshaping perceptions of labor value and authorship. Beyond empirical description, the paper engages critically with ethical, cultural, and epistemological implications, emphasizing how platform-mediated work reproduces pre-existing social hierarchies while generating novel forms of digital inequality. In conclusion, the study advances a framework for understanding platform labor as emergent, distributed, and algorithmically conditioned, urging further research on governance, regulation, and labor rights in digitally mediated economies. The study contributes a fourfold typology of invisible labor and develops a comparative framework linking algorithmic governance, labor invisibility, and socio-economic inequality.

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