Search Results (978)

Gambling disorder is a public health concern, but research on the early detection of gambling-related harm is limited by the scarcity of ethically shareable online conversations. This study presents a framework for generating an entirely synthetic dataset for natural language processing research on gambling-related behavioral signals. Behavioral dimensions from the Online Gambling Disorder Questionnaire were used to construct 2100 risk-aligned user profiles and generate X/Twitter-style monologues and multi-user threads across gambling and non-gambling subtopics. The dataset contains 35,346 monologues and 1716 threads. The generated text was evaluated using automatic metrics, manual target-consistency assessment, and downstream classification under user-disjoint and parent-topic-disjoint protocols. Automatic and manual evaluations indicated acceptable linguistic quality and consistency with predefined behavioral targets. In the stricter parent-topic-disjoint setting, logistic regression achieved a macro-$F_1$ of 0.884 for binary gambling-content detection, whereas four-level risk prediction remained more difficult. These results show that the dataset contains learnable signals for computational detection of gambling-related content without exposing real-user data. However, the dataset was not externally validated against authentic social-media conversations and is not intended for clinical diagnosis. The resulting resource is designed to support reproducible research on gambling disorder and mental health while preserving user privacy. Full article

Perinatal mental health remains a critical global challenge, with maternal mortality, preterm birth, and persistent disparities in care contributing to adverse outcomes for mothers. In addition, mental health difficulties in the perinatal period are associated with poorer developmental outcomes for young children and impose an economic burden on societies. Addressing these issues requires innovative approaches that can complement traditional clinical practices. Artificial intelligence (AI) has emerged as a powerful tool with the potential to transform perinatal care by enabling early risk prediction, personalised interventions, and scalable support systems. However, there are no existing reviews on use of AI across different stages of perinatal mental health. We conclude with a call to action for clinicians, researchers, policymakers, and technology developers to collaborate on a consensus framework that ensures ethical, safe, and equitable integration of AI into perinatal care. Full article

The widespread penetration of generative artificial intelligence is reshaping adolescents’ social ecosystems and emotional experiences, while challenging the interpretive boundaries of traditional connectedness theories. Following the logical path of “connotation reconstruction–extension transformation–concept construction”, this study integrates the ethics of care and neo-ecological theory to systematically construct a theoretical framework of artificial intelligence connectedness. First, tracing theories across philosophy, sociology, and psychology, this research reconstructs the core connotation of connectedness rooted in the ethics of care, proposes the continuum hypothesis of caring relationships, and clarifies AI’s unique position on this continuum. Second, from the neo-ecological perspective, this paper sorts out the extended structure of connectedness and demonstrates the ecological shifts brought by the rise of virtual microsystems and the entry of AI actors. On this basis, the study formally defines artificial intelligence connectedness and establishes its three-dimensional structure: demand identification, two-way behavioral engagement, and responsive confirmation. Through systematic comparison with adjacent concepts, this paper identifies its uniqueness and positions it as a specific subtype of connectedness for the digital era. It defines it as a perceived bond that is both psychologically real and ethically asymmetric, carrying asymmetric risks under particular usage conditions and design logics. Finally, this paper builds a dual interpretive framework integrating traditional connectedness and artificial intelligence connectedness, verifies its incremental validity and unique predictive power, and puts forward falsifiable research propositions. This study expands the boundary of connectedness theory and provides an integrated analytical framework for parsing the complex mental health mechanisms of adolescents in the digital age. However, it should be noted that the artificial intelligence connectedness proposed in this study is currently a theoretical construct; its scientific validity and applicability remain to be verified through the development of standardized measurement tools and systematic empirical research. Full article

Background: Obesity is a chronic, multifactorial disease that demands personalized and sustainable management approaches. Digital health technologies, such as artificial intelligence, wearable devices, mobile health apps, and virtual reality (VR), may support obesity care by providing enhanced behavioral monitoring, personalized feedback, and patient engagement. Objective: This critical narrative review discusses the current evidence on artificial intelligence, wearable technologies, and VR in the context of precision nutrition and obesity management and their possible clinical applications and limitations. Method: A critical narrative review was conducted using peer-reviewed literature published between 2019 and 2026 and identified through PubMed and Google Scholar. Search terms included combinations of “precision nutrition,” “personalized nutrition,” “obesity,” “weight management,” “metabolic health,” “digital health,” “artificial intelligence,” “machine learning,” “mobile health,” “wearable devices,” and “omics” using Boolean operators. Evidence from randomized controlled trials, systematic reviews, meta-analyses, and key conceptual studies was critically synthesized due to substantial heterogeneity in interventions and outcomes. Result: Wearables and mobile applications can enable continuous self-monitoring of physical activity, dietary intake, sleep, and physiological measures. Artificial intelligence may improve dietary personalization, risk prediction, glycemic control, and adaptive feedback. VR offers an immersive way to tackle behavioral and cognitive mechanisms related to overeating such as cravings, food cue reactivity, and inhibitory control. However, the evidence is heterogeneous, with many studies limited by short follow-up periods, small samples, variable adherence, and insufficient clinical validation. Conclusions: Artificial intelligence, wearable technologies, and VR are promising tools for precision obesity management, but their long-term clinical effectiveness remains uncertain. Future research should prioritize adequately powered trials, longer follow-up, standardized outcomes, transparent algorithms, ethical data governance, and integration with multidisciplinary nutrition and obesity care. Full article

Language barriers hinder healthcare, particularly during case history-taking, a key part of diagnosis. While multilingual artificial intelligence (AI) chatbots offer solutions, there is fragmented evidence of their effectiveness and impact. This systematic review followed PRISMA 2020 guidelines, examining studies published between 2015 and 2025 on multilingual AI chatbots in healthcare across four databases (Google Scholar, Scopus, Web of Science, and PubMed), using a two-stage screening process. Data extraction focused on applications, supported languages, underlying technologies, target populations, and clinical outcomes. From 503 records, 49 studies, covering primary care, telemedicine, oncology, mental health, and other areas, met the criteria. Supported languages included English, Spanish, Arabic, Chinese, Hindi, and other underrepresented languages. In individual system evaluations using heterogeneous methodologies and evaluation settings, AI chatbots achieved a diagnostic accuracy ranging from 72–92%. Core technologies included large language models (LLMs), bidirectional encoder representations from transformers (BERT), a generative pre-trained transformer (GPT), retrieval-augmented generation (RAG), speech recognition, and distillation. The findings show that these improve clinical workflow (30–70% time savings) and patient engagement, reduce language barriers, and promote health equity. However, the overall evidence certainty was low to moderate, reflecting the predominance of prototype and proof-of-concept studies. Multilingual AI chatbots demonstrate a boost in healthcare efficiency, a reduction in language barriers, and the promotion of health equity, but exhibit challenges regarding validation, workflow integration, and evaluation standards, along with ethical issues such as privacy and bias. Future research should include real-world studies, diverse populations, standardized outcome measures, and long-term equity assessments. Full article

This review examines the environmental transition of contemporary diets, the effects of plant-based diets on human health, and vegetarianism as a phenomenon extending beyond a dietary choice, offering insights into its relationship with quality of life, physiological mechanisms, psychosocial determinants, and structural implications. In the current landscape, growing interest in vegetarianism is driven by three main factors: its contribution to multiple domains of health, its substantial potential to reduce resource use and environmental impacts, and its association with ethical and animal-related considerations. However, further research is needed to consolidate its role as a key component of future development, requiring integrated educational, cultural, technological, and policy approaches that ensure equitable access to plant-based foods, foster critical reflection on animal welfare and moral responsibility, as well as support coordinated transformations of food systems toward healthier and more environmentally sustainable societies. Ultimately, the global implementation of dietary shifts toward plant-based patterns remains anticipated but constrained, as ingrained economic and cultural interests continue to delay this pivotal systemic change. Therefore, until policy authorities enact substantial structural reforms and individuals actively promote this transition within their immediate social environments, the issue is likely to persist as a subject of ongoing debate and resistance against its operationalization. Full article

Interdisciplinary dialogue between religion and psychoanalysis has long been regarded as an important approach to addressing modern psychological suffering. Erich Fromm sought to integrate Zen Buddhist practice with psychoanalytic reflections on integration of the unconscious, self-awareness, and personality, proposing a framework that links spiritual cultivation with psychological growth. However, this framework’s explanatory power and limitations in the contemporary Chinese context remain insufficiently explored through empirical research. Drawing on semi-structured interviews with 14 Chinese Zen practitioners in China, this study employs thematic analysis to examine their practices, psychological changes, and understandings of the relationship between Zen and mental health. Most participants regarded Zen practice as a long-term process involving cognitive reorientation, emotional regulation, and behavioral transformation, broadly resonant with Fromm’s integrative framework. However, the framework should not be treated as a directly applicable model of psychological intervention, as its practical relevance depends on sustained cultivation, community support, situated understanding, and clear professional and ethical boundaries. These qualitative findings underline potential risks when Zen cultural resources are introduced into contemporary mental health services, including decontextualization, instrumentalization, and an orientation toward immediate results. Therefore, within clearly defined ethical boundaries, a limited and responsible form of collaboration between Zen teachers and mental health professionals may be worth further exploration. Full article

The growth of single-person older adult households has heightened concerns about social isolation, chronic disease management, and diminished quality of life (QoL). A systematic review with meta-analysis was conducted to examine the efficacy of human-centered AI healthcare interventions on QoL among older adults living alone. Five electronic databases (PubMed, Web of Science, CINAHL, Embase, and Cochrane CENTRAL) were searched (January 2020–March 2026) following PRISMA 2020 guidelines. Only randomized controlled trials (RCTs) were eligible. Methodological quality was appraised with the Cochrane RoB 2 tool; pooled effect estimates were derived via random-effects modeling. Fourteen RCTs (N = 2840) were included. Intervention types comprised conversational agents, socially assistive robots, remote monitoring systems, integrated platforms, and AI-driven mHealth applications. Meta-analysis demonstrated significant improvements in overall QoL (SMD = 0.40, 95% CI: 0.27–0.52, I² = 59%), depression (SMD = −0.35, 95% CI: −0.43 to −0.26), and social connectedness (SMD = 0.38, 95% CI: 0.26–0.51). Subgroup analyses showed stronger effects for interventions with personalized feedback and human interaction. GRADE certainty was moderate for all three primary outcomes. GRADE certainty for secondary outcomes was moderate for physical health but low for self-management and cognitive function. Human-centered AI healthcare interventions significantly improve QoL and psychosocial outcomes among older adults living alone. Future research should prioritize long-term effectiveness, ethical implementation, digital inclusion, and culturally adaptive models. Full article

Background/Objectives: Double-J stents (DJS) cause clinically significant lower urinary tract symptoms (LUTS) in 58–80% of patients following ureteroscopy (URS). The distal vesical coil is regarded as the primary anatomical source of trigonal irritation and detrusor instability. The single-J stent (SJS) eliminates this element while preserving the proximal renal pigtail for anti-migration anchorage. This study aimed to evaluate the safety and patient-reported symptom outcomes of a modified SJS compared with standard DJS following elective URS for ureteric stone disease. Methods: A prospective, single-arm, within-patient feasibility study was conducted in 28 adults undergoing elective URS at Austin Health, Melbourne, Australia (Human Research Ethics Committee (HREC)/25658/Austin-2025; NCT07535580). A modified SJS was fashioned from a commercially available 7Fr Bander™ ureteral diversion stent (Cook Medical, G14780) by trimming the shaft to 28 cm and affixing a 7 cm Prolene retrieval suture (Ethicon NW807) to the blunt distal end. The primary outcome was a cystoscopically confirmed SJS migration rate at removal (pre-specified feasibility threshold ≤5%). Secondary outcomes included change in Ureteral Stent Discomfort Test (USDT) total and domain scores (paired analysis, n = 24), adverse events, and patient preference. Results: The clinically significant migration rate was 0% (0/28); 27/28 stent tips were freely floating within the bladder, with one asymptomatic tip at the ureteric orifice at the scheduled removal visit. Mean total USDT score decreased from 39.92 ± 2.00 (DJS) to 30.42 ± 1.73 (SJS)—a mean absolute reduction of 9.50 points (23.8%; p < 0.001), a magnitude consistent with clinically relevant change, although a USDT-specific minimum clinically important difference has not been independently validated. All six USDT domains improved significantly (all p ≤ 0.014). No adverse events were recorded. All 28 patients (100%) reported they would choose the SJS again. Conclusions: The modified SJS demonstrated a favourable safety profile and was associated with lower patient-reported symptom scores than the preceding DJS across all USDT domains in this uncontrolled within-patient comparison. Because stent design, stone burden, and dwell time differed between the two assessment phases, these differences should be regarded as hypothesis-generating and provide a feasibility basis for a prospective randomised controlled trial evaluating the SJS following URS. Full article

Positionality refers to a researcher’s stance within the social context of their research study. It can include information such as gender, race and class, and other characteristics like location. In addition, positionality statements can also include researchers’ personal traits, such as their thoughts, feelings and behaviors. They convey a researcher’s position and are incorporated within research articles to make readers aware of the beliefs and assumptions that a scholar may be bringing into the study. Describing one’s positionality can be particularly beneficial within health professions education (HPE) research, where complex power dynamics often exist between the researcher and participants. However, there is currently limited literature on how positionality statements should be written for HPE research. This paper aims to present an introductory guide on how a novice researcher can write a positionality statement within HPE research, including elements such as reflexivity, location and context, power dynamics, and insider–outsider positioning, as well as the potential risks tied to positionality statements. Additionally, this paper provides readers with a practical step-by-step guide and a real-life example to follow when developing their own positionality statement. By practicing reflexivity and considering how their location and presence impact the research process and participants, a scholar can articulate how their identity and context shape their research approach. Consequently, adding a positionality statement can increase trustworthiness and enhance transparency of a study when they are reflexive, context-specific, ethically constructed and integrated into the research process. Full article

Neonatal screening using Dried Blood Spot (DBS) cards is an important and successful public health facility in Europe, enabling early detection of congenital disorders for early treatment and prevention of overt disease. Biobanks of stored DBS cards offer significant potential for biomedical research. Biobanking and secondary use of DBS cards also raise ethical and legal issues, particularly concerning the rights of parents and children. This study provides a comprehensive overview of legislation and legal practices governing DBS biobanking across 29 European countries, based on a survey conducted in collaboration with the International Society for Neonatal Screening. Findings reveal a highly heterogeneous landscape: 15 countries have national legislation, five have regional guidelines, and nine lack formal regulations. Only four countries require explicit parental consent for DBS storage, with considerable variation in approval processes for research use. A harmonization of practices, with the European General Data Protection Regulation (GDPR) as a basis for future regulation, supplemented by clearer guidance on ‘public interest’ and robust safeguards for individual rights may lead to more transparent and consistent governance, which is essential to balance scientific progress with the protection of parental and children’s rights in DBS-based research across Europe. Full article

Since the onset of the COVID-19 pandemic, children and adolescents across Europe have experienced a significant rise in mental health challenges, including anxiety, depression, and behavioural disorders. Schools have observed a marked shift in social behaviour, with increased emotional instability, social withdrawal, and attention-related issues. Simultaneously, educational systems face a growing shortage of skilled professionals, particularly in psychological support roles. While digital technologies offer partial relief, their effectiveness is limited by concerns such as screen fatigue and a lack of embodied interaction. This paper conceptualises the use of social robots as a novel intervention tool in education, grounded in the 4E cognition framework—embodied, embedded, enacted, and extended—and informed by interdisciplinary research. Using design thinking and insights from empirical and practical work, we developed five use cases for integrating robots into the Swiss MindMatters mental health promotion programme. These five use cases demonstrate how robots can facilitate emotional learning, simulate social interactions, support conflict mediation, and reduce teacher workload. By combining physical presence with adaptive behaviour, social robots, which will serve as digital twins of pedagogical partners, offer a promising, ethically sensitive extension of classroom environments, fostering deeper engagement, social competence, and cognitive development in ways traditional technologies cannot fully replicate. Full article

Background: Depression and anxiety disorders remain among the leading contributors to global disability and represent a major public health challenge. Although evidence-based psychotherapies are available, access to treatment remains limited due to structural, economic, geographical, and workforce-related barriers. Digital mental health interventions have emerged as scalable approaches to reducing this treatment gap, with artificial intelligence (AI)-guided cognitive behavioral therapy (CBT) representing a rapidly developing and clinically relevant extension of digital psychotherapy. Objective: This review aims to synthesize current evidence on digital and AI-guided CBT interventions for depression and anxiety, with a focus on clinical utility, scalability, mechanisms of change, safety considerations, and public health relevance. In addition, the review proposes a clinically oriented conceptual framework for understanding the role of AI-guided CBT within contemporary digital psychiatry. Methods: A focused narrative review was conducted using PubMed, Scopus, and Google Scholar databases, covering publications from 2010 to 2025. Relevant peer-reviewed studies, systematic reviews, meta-analyses, and conceptual papers addressing digital CBT, AI-assisted CBT, conversational agents, symptom monitoring, and digital mental health implementation were identified and analyzed qualitatively. Results: Existing evidence suggests that internet-delivered CBT, mobile applications, and AI-based conversational agents may reduce depressive and anxiety symptoms, particularly in individuals with mild to moderate conditions. However, the evidence base remains heterogeneous, with limitations including short follow-up periods, variability in intervention quality, reliance on self-reported outcomes, and insufficient data on long-term effectiveness, safety, and real-world implementation. Emerging concepts such as digital therapeutic alliance, continuous symptom monitoring, adaptive intervention delivery, and AI-driven personalization may represent key factors influencing engagement and clinical outcomes. Conclusions: AI-guided CBT represents a promising but still evolving component of modern mental health care. These technologies have the potential to improve accessibility, optimize resource allocation, and support stepped-care and hybrid models of treatment. Future research should prioritize rigorous clinical validation, long-term outcome evaluation, transparent safety protocols, ethical governance, and integration into real-world health systems. AI-guided CBT should not be understood as a replacement for clinicians, but as a complementary and scalable extension of evidence-based psychotherapy. Full article

Background/Objectives: Empowerment strategies promoting healthy behaviors are important for preventing chronic diseases and cancer, while individual health responsibility (IHR) plays a significant role. Although widely discussed in the literature, the concept of IHR does not have clearly defined domains or a validated instrument for assessment. Its overlap with locus of control theory, self-motivation, and personality type creates further difficulties. Meanwhile, perception of one’s own responsibility for health is an intuitive, simple item to answer, reflecting a person’s belief related to this topic. Moreover, for ethical reasons, this concept cannot be separated from personal beliefs and should not be adjusted according to strict scales and externally imposed definitions. Therefore, this study aimed to: (1) explore whether there is an association between self-perception of IHR and preventive/risk-taking behaviors; and (2) examine socio-demographic factors associated with the IHR score and three self-perceived characteristics, namely self-perceived locus of control, health literacy, and health status. Methods: A cross-sectional study with 968 healthcare workers was conducted in a large, multidisciplinary hospital covering several behaviors (smoking, alcohol consumption, diet, and participation in a screening program for hepatitis C). IHR was evaluated on a scale from 1 to 10, where 1 meant “to very little extent” and 10 meant “to a great extent”. Results: The average IHR score was 8.80 (SD = 1.88). In the univariate analysis, the IHR score was significantly related to gender, age, education, marital status, and all three personal characteristics. In the multivariate analysis, the socio-demographic associations lost statistical significance. IHR maintained its association with the healthy diet score in the multivariable model (B = 0.113, p = 0.036). In the unadjusted analyses, the distribution of IHR differed between participants who declared alcohol consumption and those who declared abstinence (χ² = 17.157, p = 0.002). However, this association was not retained in the multivariable model. Self-perceived internal locus of control was negatively associated with screening acceptance, but not with IHR. The OR of 0.927 refers to a one-point increase on the 1–10 scale. Across the full observed scale range, this corresponds to an OR of 0.51 (95% CI: 0.29–0.89), indicating lower odds of screening acceptance among participants with higher perceived internal control. Because this estimate assumes linearity across the entire scale, it should be interpreted cautiously. Conclusions: The gap between perceived responsibility and actual behavior suggests that IHR messaging alone is unlikely to be sufficient. Future research should consider social desirability and external locus of control when analyzing IHR and health behaviors. Full article

Background/Objectives: Successful implementation of autonomous surgical technologies requires not only engineering innovation but also early evaluation of clinical usability, patient safety, workflow integration, and stakeholder acceptance. Although autonomous robotic systems are expected to transform minimally invasive surgery, evidence regarding their implementation in gynecological practice remains limited. This study explored multidisciplinary expert perspectives on the clinical implementation, safety, usability, workflow integration, and future adoption of an autonomous mini surgical robot concept designed for intrauterine polyp resection and tubal ligation. Methods: A qualitative study was conducted with 10 experts (3 gynecologists, 2 anesthesiologists, 2 women’s health nurses, and 3 engineers). Participants evaluated the proposed concept through open-ended questionnaires and semi-structured interviews. Data were analyzed using Braun and Clarke’s thematic analysis. Results: Six implementation-oriented themes were identified: clinical value, patient safety and human oversight, technology readiness, clinical workflow integration, future adoption and scalability, and ethical governance. Participants considered the proposed concept to have the potential to improve procedural precision and standardization while emphasizing that successful implementation would require physician supervision, rigorous safety validation, integration into existing clinical workflows, multidisciplinary collaboration, professional training, and appropriate ethical and regulatory oversight. Clinicians primarily emphasized patient safety and usability, whereas engineers focused on technological optimization and AI integration. Conclusions: This exploratory qualitative study provides preliminary insights into multidisciplinary expert perspectives on the future implementation of autonomous mini surgical robots in gynecology. The findings may help inform future technology development, implementation planning, and subsequent prototype-based clinical research. Full article