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Implementing a novel digital health platform for self-management of postmenopausal osteoporosis: A qualitative study of user experiences, perspectives and implementation outcomes.

BACKGROUND: Osteoporosis self-management requires scalable support, and digital health platforms may meet this need. This study aimed to characterise the experiences and perspectives of postmenopausal women who participated in a 12-month randomised controlled trial (RCT) of a digital voice assistant (DVA) delivered osteoporosis self-management intervention, and to assess key implementation outcomes. METHODS: This was a qualitative analysis of interviews with postmenopausal women from the intervention arm (DVA group) of the RCT. The DVA program broadcast education videos, medication reminders, home-based exercise, nutrition advice and monthly quizzes through a DVA device. Semi-structured interviews were recorded, transcribed and managed in NVivo through reflexive thematic analysis, guided by the Practical Planning for Implementation and Scale-Up and Proctor's implementation outcome taxonomy frameworks. Evidence weighting summarised participant coverage and code density. RESULTS: Twenty-two of 25 (88%) DVA group participants completed semi-structured interviews. Thematic analysis identified seven themes mapped to Proctor's implementation outcomes. Evidence weighting indicated strong support for the intervention's appropriateness and acceptability, moderate support for its adoption, fidelity, feasibility and sustainability, and limited support for costs. Participants valued clear audiovisual guidance, conversation-based interactions with natural language, and flexible home-based access to self-management. CONCLUSION: Digital health platforms for osteoporosis self-management appear feasible, acceptable and sustainable among postmenopausal women. Findings indicate that these platforms are approaching readiness for evaluation in implementation-focused settings, contingent on streamlined content, reliable delivery modalities, accessible user support, clear privacy regulations and pragmatic pricing models.

Humans

Experimental validation of an AI-driven digital healthcare platform for oral health behavior and plaque assessment among vietnamese children.

BACKGROUND: Oral health among children in developing countries, including Vietnam, remains a significant public health concern. Innovative approaches leveraging artificial intelligence AI-based digital health platforms may offer effective strategies for managing dental plaque and promoting better oral hygiene behaviors among school-aged children. This study aimed to evaluate the effectiveness of an AI-driven oral healthcare platform (Denti-i Vietnam) in improving oral hygiene and behavioral outcomes among Vietnamese primary school students. METHODS: A total of 204 primary school students aged 8-10&#xa0;years in Hanoi, Vietnam, participated in this experimental study. Participants were randomly assigned to an intervention group (n&#xa0;=&#xa0;107), which used the AI-driven oral healthcare platform, and a comparison group (n&#xa0;=&#xa0;97), which received traditional oral health education via pamphlets. Oral health behaviors, dental plaque levels (Simplified Oral Hygiene Index; OHI-S), and caries indices (dft/DMFT) were assessed at baseline and after the intervention period. RESULTS: The intervention group demonstrated a significant reduction in the OHI-S score compared to baseline (2.49&#xa0;&#xb1;&#xa0;0.60 to 1.70&#xa0;&#xb1;&#xa0;0.76, p&#xa0;<&#xa0;0.001), particularly in the debris component, indicating enhanced plaque control. Notable improvements were also observed in oral hygiene behaviors, including increased frequency of toothbrushing before and after breakfast (p&#xa0;<&#xa0;0.01) and more frequent parental assistance during brushing (p&#xa0;=&#xa0;0.03). Furthermore, parental awareness of dental caries significantly increased in the intervention group (p&#xa0;=&#xa0;0.001). CONCLUSIONS: The AI-driven oral healthcare platform significantly improved both oral hygiene behaviors and plaque control among Vietnamese primary school children. These findings suggest that AI-driven digital health tools can serve as practical and scalable solutions for promoting oral health in developing countries.

Humans

Building a Digital Health Research Platform to Enable Recruitment, Enrollment, Data Collection, and Follow-Up for a Highly Diverse Longitudinal US Cohort of 1 Million People in the All of Us Research Program: Design and Implementation Study.

BACKGROUND: Longitudinal cohort studies have traditionally relied on clinic-based recruitment models, which limit cohort diversity and the generalizability of research outcomes. Digital research platforms can be used to increase participant access, improve study engagement, streamline data collection, and increase data quality; however, the efficacy and sustainability of digitally enabled studies rely heavily on the design, implementation, and management of the digital platform being used. OBJECTIVE: We sought to design and build a secure, privacy-preserving, validated, participant-centric digital health research platform (DHRP) to recruit and enroll participants, collect multimodal data, and engage participants from diverse backgrounds in the National Institutes of Health's (NIH) All of Us Research Program (AOU). AOU is an ongoing national, multiyear study aimed to build a research cohort of 1 million participants that reflects the diversity of the United States, including minority, health-disparate, and other populations underrepresented in biomedical research (UBR). METHODS: We collaborated with community members, health care provider organizations (HPOs), and NIH leadership to design, build, and validate a secure, feature-rich digital platform to facilitate multisite, hybrid, and remote study participation and multimodal data collection in AOU. Participants were recruited by in-person, print, and online digital campaigns. Participants securely accessed the DHRP via web and mobile apps, either independently or with research staff support. The participant-facing tool facilitated electronic informed consent (eConsent), multisource data collection (eg, surveys, genomic results, wearables, and electronic health records [EHRs]), and ongoing participant engagement. We also built tools for research staff to conduct remote participant support, study workflow management, participant tracking, data analytics, data harmonization, and data management. RESULTS: We built a secure, participant-centric DHRP with engaging functionality used to recruit, engage, and collect data from 705,719 diverse participants throughout the United States. As of April 2024, 87% (n=613,976) of the participants enrolled via the platform were from UBR groups, including racial and ethnic minorities (n=282,429, 46%), rural dwelling individuals (n=49,118, 8%), those over the age of 65 years (n=190,333, 31%), and individuals with low socioeconomic status (n=122,795, 20%). CONCLUSIONS: We built a participant-centric digital platform with tools to enable engagement with individuals from different racial, ethnic, and socioeconomic backgrounds and other UBR groups. This DHRP demonstrated successful use among diverse participants. These findings could be used as best practices for the effective use of digital platforms to build and sustain cohorts of various study designs and increase engagement with diverse populations in health research.

Humans

Pilot Evaluation of a Digital Pretest Education Platform for Genomic Counseling: Perspectives of Health Care Providers and Patients.

Traditional in-person consultations for genetic services create access barriers. We hypothesized that the Genetics Adviser platform-a web-based digital platform delivering clinical genomic services-could reduce these barriers. Focusing on pretest education and counseling, we tested a pilot version of the platform in medical genetics and pediatric endocrinology group practices. The multimethod design consisted of quantitative patient and caregiver surveys, Google Analytics data, and qualitative healthcare provider interviews. Surveys included validated measures of acceptability and empowerment. Transcribed interviews were thematically coded and analyzed using NVivo. Of the 102 patients and caregivers targeted for this study, 85/102 (83%) accessed the platform, 71/102 (70%) proceeded beyond the landing page, and 60/102 (59%) completed the post-module survey. Users expressed high confidence in genetic understanding and empowerment (Genomics Outcome Scale [GOS]: 77/100), and providers noted potential benefits and highlighted technological and content-related limitations. Further research is needed to validate effectiveness across diverse populations and to evaluate long-term impacts on patient outcomes and healthcare efficiency.

Humans

Navigating Social Media: Balancing Connectivity With Media Literacy to Combat Misinformation and Protect Mental Well-Being.

BACKGROUND: The pervasive use of social media has created a complex digital ecosystem where high connectivity coexists with significant challenges, including the rapid spread of misinformation, particularly regarding mental health, and documented negative impacts on psychological well-being. Platform architectures designed for engagement maximization have been identified as central factors in both issues. OBJECTIVE: This paper critically analyzes the interconnected relationships between social media use, misinformation dissemination, and mental health impacts, with particular attention to psychiatric misinformation across diagnostic categories (e.g., depression, anxiety, ADHD). A primary objective is to evaluate the potential of advanced critical digital literacy frameworks to serve as protective mechanisms against these dual threats. METHODS: A systematic search was conducted following PRISMA 2020 guidelines across APA PsycInfo, PubMed, JSTOR, and Google Scholar for literature published between January 2018 and March 2026 (updated from the original 2023 search). The search yielded 2672 records. After removing 624 duplicates, 2048 records underwent title and abstract screening, with 1802 excluded. The remaining 246 full-text articles were assessed for eligibility, resulting in 86 studies included in the final qualitative synthesis. Inter-rater reliability was established (Cohen's &#x3ba;&#x2009;=&#x2009;0.82). Quality assessment was conducted using the Joanna Briggs Institute Checklist, AXIS, and CASP tools, with findings weighted by methodological quality. A thematic analysis was undertaken to synthesize findings. RESULTS: The analysis reveals that core architectural features of social media platforms, algorithmic curation and engagement-based metrics, simultaneously foster environments ripe for misinformation spread and contribute to psychological distress, including anxiety, depression, and harmful social comparison. Psychiatric misinformation specifically (e.g., inaccurate claims about treatment effectiveness, diagnostic criteria, and medication side effects) represents a growing concern, particularly on image- and video-based platforms. The findings indicate that conventional media literacy approaches focused solely on fact-checking are insufficient. Instead, a critical digital literacy framework encompassing algorithmic awareness, data literacy, and emotional awareness is essential for building user resilience, with evidence from high-quality systematic reviews supporting this approach. CONCLUSIONS: Navigating the complexities of modern social media requires an integrated approach combining "pedagogies of play" for experiential skill development with advocacy for structural change (e.g., algorithmic transparency, well being by design principles). This dual strategy empowers individual users to critically engage with digital content while advocating for ethical platform design, thereby safeguarding both mental well-being and democratic discourse. Implications for educators, mental health professionals (including competencies for addressing patient encounters with psychiatric misinformation), policymakers, and platform designers are discussed.

Humans

A Preventive Social Media Intervention for Perinatal Depression and Anxiety in Regional, Rural, and Remote Communities: Participatory Co-Design Study.

BACKGROUND: Perinatal depression and anxiety are significant public health concerns, affecting up to 1 in 5 women globally, with disproportionate burden carried by women in regional, rural, and remote communities where structural and social inequities amplify vulnerability. Access to perinatal mental health support in these settings is severely constrained by geographical isolation, workforce shortages, financial barriers, and a lack of culturally safe services. Prevention is recognized as critical to reducing this burden, with evidence suggesting that effective preventive approaches can reduce population-level illness by up to 40% and alleviate downstream demand on overstretched services. Digital mental health interventions hold promise for improving access to support, yet few are co-designed with underserved perinatal populations. OBJECTIVE: This study aimed to identify the mental health needs of perinatal women in regional, rural, and remote communities and to co-design a framework for a preventive social media-based intervention informed by platform-specific affordances and constraints, using Northern Queensland, Australia, as an exemplar. METHODS: Using a participatory co-design approach, 26 perinatal women (21 postnatal and 5 antenatal) and 8 mental health care professionals from regional, rural, and remote Northern Queensland participated in focus groups or interviews, supplemented by ongoing consultation with a community advisory group comprising lived experience representatives, clinicians, and local community leaders. Qualitative data were analyzed using reflexive thematic analysis to identify core community mental health needs. Identified needs were then examined through a needs-affordances framework to determine how specific platform features could address, enable, or constrain those needs in the context of a preventive intervention. RESULTS: Five core mental health needs were identified: (1) social connection and support; (2) personalized and respectful health care; (3) information that empowers; (4) place-based and culturally safe support; and (5) accessible, low-burden digital formats. Participants viewed social media as a potentially useful platform for fostering peer connection, normalizing perinatal experiences, and providing timely psychoeducation. However, both mothers and professionals expressed concerns about misinformation, harmful social comparison, and privacy risks that must be proactively addressed in program design. These insights were synthesized into a set of prototype design guidelines specifying recommended content, features, tone, and delivery formats to inform subsequent intervention development. CONCLUSIONS: This study provides a place-based, co-designed needs-affordances framework to guide the development of a preventive social media-based intervention for perinatal mental health support in regional, rural, and remote communities. The findings demonstrate that social media is an acceptable and promising platform for preventive perinatal mental health support in these settings, provided that design is driven by community need, platform affordances are systematically analyzed, and known risks are explicitly mitigated. These findings address a significant gap in the literature and offer a replicable methodological approach for co-designing contextually relevant digital mental health interventions with underserved populations.

Humans

Effectiveness of Mobile-Delivered Exercise and Yoga Programs on Depressive Symptom Reduction in Employees: Randomized Controlled Trial.

BACKGROUND: Mental health challenges such as stress and depression are prevalent among employees. Mobile health platforms that deliver exercise or yoga interventions offer a promising approach to improve mental health outcomes in this population. OBJECTIVE: This study aimed to assess the effectiveness of 12-session adaptive moderate-intensity exercise and yoga programs delivered via a motion-detecting digital platform in reducing stress and depressive symptoms among employees. METHODS: This was an unblinded, 3-arm, parallel-group, randomized controlled trial conducted at Seoul National University Bundang Hospital and Boramae Medical Center between November 2023 and January 2024. Eligible participants were full-time employees. Seventy-five participants were randomly assigned to an exercise, a yoga, or a cognitive behavioral therapy-based self-care control group using computer-generated randomization. The exercise and yoga groups engaged in motion-detecting, adaptive physical activity training, whereas the control group accessed mobile-based, self-directed stress management educational materials. The intervention was largely automated, with no individualized therapeutic guidance provided. Allocation was concealed until trial entry. All recruitment and outcome assessments were conducted in person at the hospitals. The primary outcomes were perceived stress and depressive symptoms, whereas the secondary outcomes included posttraumatic stress, insomnia severity, cognitive stress response, occupational stress, and burnout. Physiological outcomes were assessed using heart rate variability and electroencephalography. Measurements were collected at baseline, immediately after the intervention, and at 4-week follow-up. Data were analyzed using a multivariate linear model to evaluate the main effects of time, group, and time&#xd7;group interactions. RESULTS: Of the 75 randomized participants (exercise: n=24, 32%; yoga: n=25, 33.3%; and control: n=26, 34.7%), 71 (94.7%) who completed at least 9 of the 12 sessions (&#x2265;40 min each) were included in the outcome analysis (exercise: n=21, 29.5%; yoga: n=24, 33.8%; and control: n=26, 36.6%). For the coprimary outcomes, the group&#xd7;time interaction for depressive symptoms (Patient Health Questionnaire-9) approached but did not reach the Bonferroni-corrected threshold (F4,136=2.71; P=.03; adjusted &#x3b1;=.025); however, planned pairwise comparisons revealed significantly greater improvement in the yoga group compared to the control group at 4-week follow-up (&#x3b2;=-3.67; adjusted P<.001). For the Perceived Stress Scale, the interaction was not significant (P=.29), although a significant main effect of time (P<.001) indicated overall stress reduction across all groups. For secondary outcomes, a significant group&#xd7;time interaction was found for the Cognitive Stress Responses Scale (P=.003), indicating differential trajectories of improvement. The yoga group showed a consistent linear decrease, whereas the exercise group showed immediate but less sustained gains. CONCLUSIONS: Digitally delivered adaptive yoga programs demonstrated superior and sustained improvements in depressive symptoms and Cognitive Stress Responses Scale scores compared with the active cognitive behavioral therapy-based self-care control group. However, the exercise program showed more modest and less sustained effects, warranting further investigation using larger samples.

Adult

Smartphone Apps for Preventing Adolescent Health Problems Among Health Care Professionals: Systematic Search and Quality Assessment.

BACKGROUND: Health care professionals must consider multiple dimensions of prevention when consulting with adolescents. Identifying risky behaviors early in adolescence is crucial for reducing both morbidity and mortality. General practitioners are increasingly eager to incorporate digital tools for prevention into their consultations with adolescents; however, the relevance and clinical validity of these digital tools are not always established or well-known. Consequently, primary care professionals require guidance and support in selecting relevant mobile health (mHealth) tools. OBJECTIVE: The aim of this study is to identify relevant and useful digital apps to help primary care professionals detect at-risk adolescents across all recommended areas of prevention: orthopedics, mental health, substance abuse, risk behaviors, sexual health, vaccinations, social relationships, and nutrition. METHODS: A systematic review of smartphone apps, with an analysis of content quality, was carried out by 4 researchers using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) checklist. The App Store and Google Play Store platforms were surveyed. The inclusion criteria were as follows: free of charge, date of last update, availability in French or English, relevance of the preventive approach to adolescents, and scientific validation. Four health care professionals assessed the apps: 2 selected the apps relevant to health care professionals, then 3 analyzed these apps using the French version of the Mobile App Rating Scale (MARS-F). Intraclass correlation coefficient, model (2,1) (2-way random effects, absolute agreement, single measures); standard error of measurement; and mean absolute error were also calculated. RESULTS: A total of 976 apps were identified, 49 of which had disappeared from the platforms prior to analysis. Nine apps were retained. Seven (0.72%) were included after evaluation using the MARS-F: 2 on mental health and 5 on sexual health (including 3 on contraception only). The mean MARS-F interrater score ranged from 2.5/5 to 3.8/5. The global MARS-F score demonstrated a pooled SD of 0.60 and an intraclass correlation coefficient (2,1) of 0.0003, resulting in a calculated standard error of measurement of 0.60. The average discrepancy between raters was a mean absolute error of 0.53. CONCLUSIONS: No similar studies have been identified in the literature that specifically focus on mobile apps designed to support health care professionals in delivering preventive care to adolescents. Of the 8 areas of prevention identified as relevant for adolescents, only 3 are addressed by the apps validated through our methodology (5 focus on sexual health). Consequently, current apps are insufficient to support health care professionals in their overall preventive work with adolescents. Such a review should be conducted systematically prior to the development of any new tool to prevent duplication and channel creative efforts toward truly innovative digital solutions. Furthermore, a thorough analysis of relevant, recommended websites is essential, as these resources complement the use of mobile apps designed for health care professionals.

Humans

AI-Driven Precision Medicine in Alzheimer's Disease: Drug Repurposing, Digital Therapeutics and Clinical Decision Support.

Alzheimer's Disease (AD) is a neurodegenerative disease that causes significant clinical, social, and economic burden worldwide. Despite improvements in understanding its multifaceted pathogenesis, current treatments are mostly symptomatic and ineffective across varied patient populations. To overcome these constraints, AI-driven precision medicine allows tailored risk assessment, treatment selection, and disease monitoring. This review covers AI's role in AD precision medicine, focusing on drug repurposing, digital therapies and clinical decision support systems. Machine and deep learning models are used to predict medication response, integrate heterogeneous data sources such as genomics, transcriptomics, neuroimaging and electronic health records, and uncover pharmacogenomic treatment success factors. The paper covers AIenabled precision pharmacology, including tailored dosing algorithms, adaptive therapeutic monitoring, and adverse drug reaction prediction. Bioinformatics-based target identification, network pharmacology, graphbased AI models, virtual screening, and real-world and clinical data validation are emphasized in AI-driven medication repurposing. AI-powered digital treatments like personalized cognitive training platforms, wearable- derived digital biomarkers, virtual and mixed reality interventions, adherence monitoring, and digital twins for therapy optimization have been discussed. AI-based clinical decision support systems are also thoroughly assessed for clinical value, accuracy, and explainability in disease subtyping, trajectory prediction, and risk stratification in preclinical and prodromal AD. Despite these promises, data heterogeneity, algorithmic bias, legal barriers, and privacy concerns exist. Federated learning enables safe multi-center collaboration and hybrid AI-human approaches, and it represents the future. AI's ability to alter AD care opens the door to precision medicine paradigms that use repurposed medications, digital tools and intelligent decision-making to improve patient outcomes.

Alzheimer&#x2019;s disease

Attomolar Detection of HIV-1 With Label-Free RCA-rCRISPR on Smartphone.

HIV remains a major global public health challenge, causing 42.3 million deaths since its discovery in the early 1980s. Despite progress in prevention and treatment, around 60% of people with HIV (PWH) remain undiagnosed in resource-limited regions due to the lack of inexpensive and equipment-free detection methods. Here, we developed a low-cost, robust, and label-free CRISPR-based diagnostic platform for detecting HIV viral load with minimal instrumentation. Our strategy combines rolling circle amplification (RCA) with plasmid reporter-based ratiometric CRISPR (rCRISPR) that enables the detection of HIV RNA down to single-digit aM sensitivity from PWH-derived HIV samples ex vivo. Unlike conventional RCA, which requires fragmentations of long RNA target sequences, our design harnesses the triple functions of the phi29 DNA polymerase (namely exonuclease activity, polymerization, and strand displacement), enabling the detection of the long HIV genome without pre-fragmentation. Cas12a reaction then detected RCA products by converting supercoiled &#x3a6;X174 plasmid reporters to relaxed forms. The target concentration was quantified based on the supercoil-to-relaxed plasmid ratio. Further, we constructed an all-in-one smartphone-based minigel electrophoresis device to demonstrate equipment-free HIV viral load testing. Finally, the assay has demonstrated for BRAF point mutation detection, showcasing the robustness of our strategy for broad disease diagnostic applications.

CRISPR

USleep: efficacy of app-based audio interventions to improve sleep disturbance in working adults, a multi-arm randomized controlled trial.

STUDY OBJECTIVES: To evaluate the efficacy of three categories of standalone, audio-based sleep interventions (Bedtime Stories, Sleep Sounds, Sleep Skills) delivered via mental health application (MHapp) in improving sleep among working adults with sleep disturbance. METHODS: A multi-arm, parallel randomized controlled trial was conducted. Adults with self-reported sleep disturbances were recruited online and randomly allocated to Bedtime Stories, Sleep Sounds, Sleep Skills, or digital control. Participants completed self-report questionnaires on sleep disturbance and other related outcomes at baseline (t0) and after the 4-week intervention (t1). The primary analysis followed an intention-to-treat approach using mixed-effects models. RESULTS: A total of 495 working adults (mean age&#x2009;=&#x2009;32.7&#xa0;years; 55.8% female) were randomized. For sleep disturbance (primary outcome), the between-group Hedges' g effect sizes were very small and not statistically significant (Bedtimes stories vs. control: g&#x2009;=&#x2009;0.12, 95% CI -0.13 to 0.37, Sleep Sounds vs. control: g&#x2009;=&#x2009;0.14, 95% CI -0.11 to 0.39, Sleep Skills 0.07, 95% CI -0.07 to 0.29), with slightly greater reductions in sleep disturbance for the intervention groups than control. The same pattern was observed for sleep-related impairment, mental health, well-being, and pre-sleep arousal. CONCLUSION: Audio-based sleep interventions delivered via a MHapp did not demonstrate superior efficacy over a digital control condition in reducing self-reported sleep disturbance among working adults. Although safe and well-tolerated, their use as standalone treatments for sleep disturbance is not supported by these findings. Future research should explore effectiveness in real-world settings, including user content choice across categories, and use objective sleep measures. CLINICAL TRIAL REGISTRATION: Registered at https://www.isrctn.com/ under "Evaluating the efficacy of audio-based digital tools to improve sleep on the Unmind workplace well-being platform"; https://www.isrctn.com/ISRCTN13426045; registration number: 13426045.

Humans

Use of wearable technologies for physical activity promotion in older adults: A systematic review.

This systematic review, conducted according to PRISMA guidelines and registered in PROSPERO (CRD420251055299), examined the use of wearable technologies for promoting physical activity (PA) in adults aged 60 years and older. Searches across five databases (PubMed, Scopus, Web of Science, CINAHL, Cochrane) identified 2438 records, of which only six randomized controlled trials published between 2021 and 2025 met inclusion criteria, with sample sizes ranging from 36 to 551 participants and mean ages between 65 and 79 years. Given the small number of included studies, findings should be interpreted as preliminary. The studies ranged from the standalone use of commercial trackers (Fitbit, Polar, ActiGraph) to multicomponent interventions combining wearables with physiotherapist feedback, telephone counseling, web-based platforms, or interactive cognitive-motor training. Wearables used alone, as in the REACT trial, produced small or non-significant PA effects. In contrast, interventions integrating devices with personalized feedback, professional support, or digital platforms, such as PROMOTE and TASMANIA, were associated with more consistent improvements in PA, physical function, and cognitive outcomes. Multicomponent programs, such as PEER and ICMT, reported broader benefits, including cognition, balance, and reductions in sedentary behavior, though these findings derive from individual trials and require replication. Risk of bias, assessed with the Cochrane Risk of Bias tool version 2 (RoB 2.0), was rated as "some concerns" for five studies and low for only one, mainly due to gaps in randomization reporting, missing data, and lack of preregistration. Tentatively, and based on a very limited evidence base, wearables may have greater impact when embedded within broader behavioral systems, incorporating feedback, coaching, or interactive components, rather than when used in isolation as passive monitoring tools. Adherence and psychosocial outcomes appeared related to comfort and perceived usefulness among older adults, though larger and more robust trials are needed to confirm these patterns.

Humans

Attomolar Detection of HIV-1 with Label-Free RCA-rCRISPR on Smartphone.

Human Immunodeficiency Virus-1 (HIV) remains a major global public health challenge, having led to over 42.3 million deaths since its discovery in the early 1980s. Despite progress in prevention and treatment, around 60% of people with HIV (PWH) remain undiagnosed in resource-limited regions, disproportionately affecting vulnerable populations and underserved communities across the world. This illustrates the critical need for accessible, accurate, and equipment-free diagnostic tools to enhance detection and thus provide opportunities to curb its spread. Here, we developed a low-cost, robust, and label-free rolling circle amplification (RCA)-rCRISPR diagnostic platform for detecting HIV viral load with minimal instrumentation. Our strategy, combining the integration of RNA-detecting RCA reaction with plasmid reporter-based ratiometric CRISPR (rCRISPR), enables sensitive detection of unprocessed RNA targets without the need for intensive sample pre-treatment. This label-free RCA-rCRISPR diagnostic platform detected HIV RNA down to single-digit aM sensitivity (~3000 copies/mL) from PWH-derived HIV samples ex vivo. Unlike typical RCA, which requires sample fragmentations to break long RNA target sequences, our design harnesses the triple functions of the phi29 DNA polymerase (namely exonuclease activity, polymerization, and strand displacement), enabling the detection of the entire HIV genome without pre-fragmentation. For point-of-care (POC) applications, we constructed an all-in-one smartphone-based minigel electrophoresis device to facilitate equipment-free HIV viral load testing, making it accessible to resource-limited communities. Additionally, the assay has demonstrated the ability for point mutation detection (BRAF mutation in canine urothelial carcinoma), showcasing the robustness of our strategy for broad disease diagnostic applications.

HIV

The 2026 Bundibugyo Ebola Outbreak: A Warning for Global Preparedness for Future Epidemics.

Dear Editor, The 2026 Bundibugyo Ebolavirus (BDBV) outbreak has once again demonstrated that the threat of emerging diseases remains a major global health challenge. The outbreak, first detected in the Democratic Republic of Congo (DRC) and spread to Uganda, is not only a regional crisis but also a test of the world's preparedness for pathogens with epidemic potential. Unlike Zaire Ebolavirus (EBOV), which has benefited from effective vaccines and treatments in recent years, BDBV still lacks a licensed vaccine or specific treatment[1]. As of June 6, a total of 515 laboratory-confirmed cases and 91 deaths have been reported in DRC, while Uganda has reported 19 laboratory-confirmed cases and two deaths. The occurrence of unexplained deaths among both the community and healthcare workers, along with prior reports of an unidentified hemorrhagic fever, suggest that the outbreak has been likely originated in March 2026 or even earlier. Accordingly, the virus is believed to have spread unnoticed for several weeks before being identified through genomic sequencing in mid-May 2026[2]. The resurgence of Ebola in Africa results from a complex interaction of environmental, social, and political factors. Deforestation, the development of mining activities, the expansion of agriculture, and increased human contact with wildlife have elevated the likelihood of spillovers from wildlife reservoirs, particularly fruit bats, which are considered the most likely natural hosts of ebolaviruses. Moreover, weak disease surveillance systems and limited access to health services have delayed the identification of early cases. The similarity of the initial symptoms of Ebola to other endemic diseases in the region, such as malaria, makes early diagnosis difficult and provides ample opportunity for transmission to spread. Insecurity, misinformation, attacks on healthcare facilities, and armed conflict in the region have also posed serious challenges to the implementation of contact tracing programs and rapid response to the epidemic[3,4]. One of the most critical challenges highlighted by this outbreak is the weakness of diagnostic capacities in the affected areas. The initial 2007 outbreak of BDBV proved that delayed lab confirmation paralyzes public health responses[5]. Now, dealing with a much larger outbreak in 2026, the persistence of this challenge highlights a dangerous failure to invest in diagnostic infrastructure over the last 19 years. Many health facilities do not have access to molecular laboratories, rapid sample transport systems, and biosafety infrastructure[6]. These limitations delay the diagnosis and isolation of patients, thus perpetuating disease transmission. Investment in the development of mobile laboratories, rapid point-of-care diagnostic tests, and digital reporting systems can dramatically reduce the time to diagnosis and response to an outbreak. The BDBV outbreak shows that laboratory preparedness must be considered an essential part of global health security. Furthermore, the early detection of emerging pathogens depends not only on diagnostic technologies but also on the expertise of local scientists who are able to recognize unusual epidemiological and laboratory patterns. During the current outbreak, suspected Ebola cases initially tested negative using common diagnostic tests (designed for Zaire Ebola Virus), which delayed the identification of the BDBV. Specifically, field-based diagnostics in Bunia were calibrated exclusively to detect the EBOV responsible for recent Congolese outbreaks. Consequently, patient samples collected throughout late April and early May yielded negative results, requiring cross-country transport to Kinshasa for genomic confirmation[2]. This experience revealed a major vulnerability in outbreak preparedness: diagnostic tools designed for known threats may be ineffective in detecting less common or unexpected pathogens. Therefore, strengthening local scientific capacities, developing genomic surveillance, and expanding access to flexible and adaptable diagnostic platforms should be considered as a top priority for global health security. The lack of a licensed vaccine for BDBV was one of the most significant challenges of this epidemic. While the rVSV-ZEBOV vaccine has played a significant role in controlling Zaire ebolavirus, there is no licensed vaccine for BDBV. In response to this outbreak, efforts to develop mRNA-based vaccines, adenoviral vectors, rVSV-based vaccines, and multipotent vaccines have been accelerated[7]. However, the experience of this epidemic has shown that the development of medical products for rare diseases continues to face financial and investment constraints. This challenge highlights the need for sustained support from governments and international institutions for research and development of pathogens with epidemic potential. The 2026 Bundibugyo outbreak provides several key lessons for the global community. First, early detection and rapid diagnosis are the most important factors in containing the epidemic. The 19-year interval between the 2007 BDBV outbreak and the 2026 outbreak underscores persistent shortcomings in investment toward decentralized, pan-ebolavirus diagnostic infrastructure, with diagnostic delays hindering timely outbreak identification in both instances. Second, the trust and active participation of local communities are as important as medical interventions. Additionally, the rapid cross-border transmission dynamics between the DRC and Uganda demonstrate that blanket travel restrictions and border closures are impractical. As communities in the Great Lakes region routinely cross national borders for trade and healthcare, coordinated regional surveillance and timely information sharing are likely to be more effective than broad border closures in mitigating disease transmission[8]. Third, the protection of health workers must be a priority in preparedness plans. Fourth, a "One Health" approach is essential for simultaneous monitoring of humans, animals, and the environment. Although BDBV is not a new pathogen, the lack of licensed medical interventions and limited investment in research reflect many of the vulnerabilities associated with the concept of "Disease X."[9]. Unlike Zaire Ebola Virus, for which licensed vaccines and monoclonal antibody therapies are available, BDBV forces public health responses to rely almost entirely on non-pharmaceutical interventions such as isolation and infection control[10]. This gap reflects the structural inequity in global health research and development funding, with pathogens affecting resource-limited regions receiving insufficient attention until they spark an international emergency[2]. The BDBV outbreak proves that global epidemic preparedness cannot be pathogen-selective; it requires proactive investment in broad-spectrum countermeasures and resilient frontline health systems[8]. In conclusion, the 2026 BDBV outbreak is a serious wake-up call for the global health system. The epidemic revealed that gaps in surveillance systems, diagnostic capacities, vaccine development, and preparedness for emerging diseases persist. Investing in health infrastructure, developing Pan-Ebolavirus vaccines, strengthening laboratories, expanding the One-Health approach, and supporting research on emerging zoonotic pathogens must be at the top of global health security priorities. Otherwise, the BDBV outbreak may be just a prelude to larger crises to come.

Ebolavirus

The effect of dietetic counseling combined with digital tools intervention on hemodynamic markers in Greek adults: The GATEKEEPER Study.

BACKGROUND AND AIM: Hypertension is a leading cardiovascular risk factor with substantial global impact on morbidity, mortality, and healthcare costs. While lifestyle interventions remain central to management, mHealth technologies offer promising adjunctive support, though their clinical effectiveness remains uncertain. This study evaluated whether combining dietetic counseling with digital tools improves hemodynamic markers in adults aged &#x2265;55 years with increased cardiometabolic risk. METHODS AND RESULTS: This 3-month RCT (NCT05031299) included 954 adults with at least one metabolic syndrome risk factor, allocated 1:1:1 to Standard Care (dietetic counseling), Platform (counseling plus web-based platform), or Platform&#xa0;+&#xa0;Devices (counseling plus platform plus wearables). Outcomes included anthropometrics, lifestyle characteristics, blood pressure, pulse pressure, and estimated pulse wave velocity, analyzed using linear mixed-effects models adjusted for age and sex. All groups improved over 3 months. Waist circumference decreased by -6.29, -4.92, and -4.69&#xa0;cm across Standard Care, Platform, and Platform&#xa0;+&#xa0;Devices groups respectively, and systolic blood pressure declined by -4.84 to -7.15&#xa0;mmHg across groups. The Platform&#xa0;+&#xa0;Devices group showed greater increases in physical activity (94.62 MET-min/week; 95% CI 66.49 to 122.76) and greater reductions in pulse pressure (-3.90&#xa0;mmHg; -6.58 to -1.22) versus Standard Care. Weight loss was associated with lower odds of hypertension (OR 0.4; 95% CI 0.2-0.7), greater likelihood of hypertension reversal (OR 3.6; 1.2-10.3), and higher probability of achieving normal pulse pressure (OR 1.8; 1.1-3.1). CONCLUSIONS: Dietary lifestyle intervention improved cardiometabolic outcomes, with limited added benefit from digital tools. Weight loss was the primary driver of hemodynamic improvement.

Aged

Multidisciplinary mHealth Rehabilitation for Patients With Abdominal Cancer Who Are Receiving Chemoradiotherapy: Randomized Phase II Trial.

BACKGROUND: Concurrent chemoradiotherapy (CCRT) for abdominal cancer frequently induces muscle loss, weight loss, and malnutrition. OBJECTIVE: This exploratory randomized phase II trial evaluated whether a multidisciplinary, mobile health (mHealth)-based multimodal rehabilitation program could preserve handgrip strength and muscle mass in patients with abdominal cancer undergoing CCRT. METHODS: In this prospective, multicenter, randomized, open-label phase II trial (NCT05325554), 111 eligible patients with abdominal malignancies scheduled for CCRT were randomly assigned (1:1) to receive either multidisciplinary mHealth rehabilitation care (MRC; n=57) or standard care (SC; n=54). The MRC program was delivered by a dedicated multidisciplinary team using the AiNST mHealth platform and wearable heart rate monitors. The primary end point was handgrip strength at the end of CCRT (analyzed with analysis of covariance adjusting for baseline). Secondary end points were exploratory and analyzed without multiplicity adjustment; sensitivity analysis using false discovery rate (FDR) correction was performed. RESULTS: Between February 2022 and April 2023, 111 patients were enrolled. Adherence was high (n=93, 83.9% achieved exercise targets). After adjusting for baseline handgrip strength, the MRC group had significantly higher handgrip strength at the end of CCRT than the SC group (adjusted mean difference 4.87 kg, 95% CI 3.36-6.38; P<.001). Exploratory analyses of secondary end points (without multiplicity adjustment) showed that the MRC group also had better preservation of body weight (P=.005), skeletal muscle mass (P<.001), serum albumin (P=.009), prealbumin (P=.02), and lower rates of hematological toxicity (P<.05), as well as improved psychological status (distress thermometer [DT] and Hospital Anxiety and Depression Scale [HADS]) and nutritional scores (Nutritional Risk Screening 2002 [NRS-2002] and Patient-Generated Subjective Global Assessment [PG-SGA]) at the end of CCRT (all P<.05). All nominally significant secondary end points remained significant after FDR correction (q<.05). These findings are preliminary and should be interpreted with caution due to the open-label design, population heterogeneity, and exploratory secondary analyses. CONCLUSIONS: In this exploratory phase II trial, a multidisciplinary, mHealth-based multimodal rehabilitation program was associated with better preservation of handgrip strength, muscle mass, and nutritional status, as well as lower rates of certain treatment toxicities, compared with SC. However, definitive conclusions are limited by the open-label design, heterogeneity of tumor types, and short follow-up. Larger, blinded phase III trials are needed to confirm these findings.

Humans

The effects of fitspiration TikTok content on body image and mood among young adult women in the U.S.

Fitspiration is an appearance-based form of media that promotes physical fitness and dieting. While not true of all fitspiration media, some forms promote these ideals through visuals of toned, athletic bodies that have become increasingly prevalent on the short-form video platform, TikTok. Although often framed as health-promoting, fitspiration exposure has been associated with upward appearance comparison (i.e., comparison with people perceived as more attractive) and negative effects on body image and mood. The present study investigated the effects of short-form video-based fitspiration on social comparison, appearance importance, appearance anxiety, body dissatisfaction, and negative affect. Using an experimental design, 150 undergraduate women (Mage = 19.28) in the United States were randomly assigned to view a five-minute TikTok compilation of either animal (n&#x202f;=&#x202f;75) or fitspiration videos (n&#x202f;=&#x202f;75). Participants completed baseline measures prior to viewing and state-level measures after completing their video set. Results indicated that, relative to control, viewing fitspiration content led to greater social comparison, appearance concerns, feelings of being fat, and sadness. Baseline appearance concerns and depressive symptoms significantly moderated group differences in responses, such that negative fitspiration effects on state-level appearance concerns were found among individuals high but not low in baseline appearance concerns and among individuals low but not high in baseline depressive symptoms. These findings contribute to the growing literature on fitspiration by demonstrating the immediate psychological effects of this content in short-form videos and highlighting the importance of considering individual differences in vulnerability.

Humans

Precision targeting of teacher burnout using network-informed ecological momentary interventions.

Teacher well-being affects classroom functioning and workforce stability, yet generic digital programs rarely use person-specific affect dynamics to select support. This cluster-randomised trial evaluated whether micro-interventions selected from high expected influence (EI) nodes in teachers' contemporaneous affect networks produced larger changes in burnout-related EI and everyday happiness than content-matched random allocation. The objectives were to estimate allocation effects on changes in estimated network summaries and happiness, evaluate network change as a statistical mediator, examine personality moderation, and benchmark simpler allocation rules. A two-arm cluster randomised platform trial was conducted in 84 public schools across four urban districts in H Province. After a 14&#xa0;day baseline of ecological momentary assessment (EMA), person specific partial correlation networks were estimated for happiness, exhaustion, detachment, efficacy and rumination. An optimisation engine prioritised three brief micro-intervention types per teacher according to baseline EI, while the active control received the same library without network information. EMA continued for 8&#xa0;weeks; Bayesian multilevel models, permutation-based mediation, and benchmarking analyses were applied. EI-based targeting produced larger reductions in the composite EI-change index than active control (mean difference 0.11, 95% credible interval 0.08 to 0.14) and higher week 7 EMA happiness (4.4 points on a 0 to 100 scale, 95% credible interval 2.7 to 6.0), with a positive arm by week slope difference of 0.62 points per week (95% credible interval 0.39 to 0.85). Model-based mediation estimates were consistent with approximately one half of the happiness difference being statistically associated with change in the composite EI-change index (average conditional mediation estimate 3.5 points, 95% credible interval 2.0 to 5.2). Benchmarking showed smaller gains under severity, threshold, or group-level centrality rules. Effects were stronger among teachers higher in conscientiousness. The findings indicate that integrating EMA, network modelling, and EI-driven optimisation yields measurable gains beyond content-matched exposure, providing a proof of concept for district-scale precision mental health that requires prospective implementation testing. Replication in additional regions, expanded node sets, and longer follow up are warranted to assess durability and generalisability.

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