Although mobile health-tracking technologies have burgeoned, offering objective health information to consumers on an unprecedented scale, opportunities to directly test effects of such monitoring have been limited. Low-cost mobile breathalyzers are one tool commonly employed for blood alcohol concentration (BAC) assessment. The authors explored outcomes linked with BAC-tracking technologies, examining effects on alcohol use and self-estimation of BAC levels in a large U.S. sample. Participants (N=32,179) were individuals who voluntarily purchased a mobile breathalyzer and provided at least three ad-lib readings between 2016 and 2022. A paired smartphone application prompted users to enter a BAC self-estimate (a guess) before the measured BAC level was displayed. Analyses included observations collected during active consumption (BAC >0.00%) from breathalyzer users who opted to share anonymized data. Breathalyzer users who displayed inattentive patterns of guessing were excluded from self-estimation analyses. The final dataset comprised 787,393 BAC readings and 387,643 self-estimates. The accuracy of BAC guesses increased by 2.38% over the course of breathalyzer use. Associations between breathalyzer use and BAC levels varied significantly according to participants' initial drinking levels (b=-0.0062, 95% CI=-0.0065, -0.0059). Among heavy-drinking participants, BAC levels decreased on average from 0.106% to 0.096%, whereas the reverse trend was observed for lighter-drinking participants, whose levels increased from 0.058% to 0.067%. A similar interaction emerged for BAC underestimation (b=-0.0058, 95% CI=-0.0066, -0.0049), with odds of underestimation decreasing among heavy-drinking and increasing among light-drinking participants. The results indicate promise for mobile BAC-tracking technologies as a low-impact intervention with the potential to decrease drinking among individuals who drink heavily-a population particularly susceptible to alcohol-related problems. In contrast, inverted trends emerged for light-drinking individuals, highlighting the need for empirical research in the fast-moving landscape of digital health.

While artificial intelligence (AI) holds significant promise for health care, excessive trust in these tools may unintentionally delay patients from seeking professional care, particularly among patients with chronic illnesses. However, the behavioral dynamics underlying this phenomenon remain poorly understood. This study aims to quantify the influence of AI trust on health care delays through integrated survey-based mediation analysis and real-world research, and to simulate intervention efficacy using agent-based modeling (ABM). A cross-sectional online survey was conducted in China from December 2024 to May 2025. Participants were recruited via convenience sampling on social media (WeChat and QQ) and hospital portals. The survey included a 21-item questionnaire measuring AI trust (5-point Likert scale), AI usage frequency (6-point scale), chronic disease status (physician-diagnosed, binary), and self-reported health care delay (binary). Responses with completion time <90 seconds, logical inconsistencies, missing values, or duplicates were excluded. Analyses included descriptive statistics, multivariable logistic regression (α=.05), mediation analysis with nonparametric bootstrapping (500 iterations), and moderation testing. Subsequently, an ABM simulated 2460 agents within a small-world network over 14 days to model behavioral feedback and test 3 interventions: broadcast messaging, behavioral reward, and network rewiring. The final sample included 2460 adults (mean age 34.46, SD 11.62 years; n=1345, 54.7% female). Higher AI trust was associated with increased odds of delays (odds ratio [OR] 1.09, 95% CI 1.00-1.18; P=.04), with usage frequency partially mediating this relationship (indirect OR 1.24, 95% CI 1.20-1.29; P<.001). Chronic disease status amplified the delay odds (OR 1.42, 95% CI 1.09-1.86; P=.01). The ABM demonstrated a bidirectional trust erosion loop, with population delay rates declining from 10.6% to 9.5% as mean AI trust decreased from 1.91 to 1.52. Interventions simulation found broadcast messaging most effective in reducing delay odds (OR 0.94, 95% CI 0.94-0.95; P<.001), whereas network rewiring increased odds (OR 1.04, 95% CI 1.04-1.05; P<.001), suggesting a "trust polarization" effect. This study reveals a nuanced relationship between AI trust and delayed health care-seeking. While trust in AI enhances engagement, it can also lead to delayed care, particularly among patients with chronic conditions or frequent AI users. Integrating survey data with ABM highlights how AI trust and delay behaviors can strengthen one another over time. Our findings indicate that AI health tools should prioritize calibrated decision support rather than full automation to balance autonomy, odds, and decision quality in digital health. Unlike previous studies that focus solely on static associations, this research emphasizes the dynamic interactions between AI trust and delay behaviors.

Ensuring participant safety in research studies evaluating digital mental health interventions delivered remotely - insights from the PIPA trial of an online parenting intervention to prevent affective disorders in high-risk adolescents.

Digital health interventions (DHIs), delivered via digital platforms such as internet-based programs, mobile applications or short messages, may improve patient-reported outcomes (PROs), but comparative effectiveness is unclear. We conducted a network meta-analysis of randomized controlled trials in adults undergoing elective surgery under general anesthesia, identified in PubMed, Embase, CENTRAL, and Web of Science to March 1, 2025. Standardized mean differences (SMDs), mean differences (MDs) with minimal important differences (MIDs), and 95% CIs were estimated. Risk of bias was assessed with RoB 2 and certainty of evidence with GRADE. Fifty-six trials (6,154 patients) were included. Extended reality (XR) most effectively reduced perioperative anxiety (SMD 0.60; 95% CI 0.37-0.84; MD 8.05; MID 6.71; moderate-certainty). For postoperative pain, mobile applications (SMD 0.64; 95% CI 0.32-0.95; MD 1.36; MID 1.0; moderate-certainty) and XR (SMD 0.51; 95% CI 0.26-0.76; MD 1.09; MID 1.0; moderate-certainty) were probably effective. For quality of life, 2D video yielded the greatest gain (SMD 0.99; 95% CI 0.11-1.88; MD 0.11; MID 0.05; high-certainty). XR also improved satisfaction (SMD 1.27; 95% CI 0.63-1.91; MD 1.91; MID 0.75; moderate-certainty). These findings suggest that DHIs may improve perioperative PROs.

Introduction Type 2 diabetes mellitus (T2DM) represents a global public health problem. In Ecuador, it is the second leading cause of death among women and the third among men. Digital health technologies, including mobile applications, messaging platforms, and web-based tools, have emerged as promising interventions for managing this condition, although a gap remains between their theoretical potential and their effective implementation in clinical practice. Objective To explore and synthesize the available evidence on the experiences, perceptions, barriers, and facilitators reported by adult users with type 2 diabetes mellitus regarding the use of digital health technologies for managing their disease in community or outpatient settings. Methodology An integrative systematic review of literature published between 2015 and 2025 was conducted in PubMed, Scopus, and Google Scholar. Qualitative, quantitative, and mixed-methods studies in English and Spanish involving adults using mobile applications for T2DM were included. Methodological quality was assessed using the Johns Hopkins Evidence-Based Practice model. Results A total of 66 studies were analyzed, with qualitative designs predominating (n=28), followed by randomized clinical trials (n=13) and experimental studies (n=14). Most studies were rated as high (n=35) or good quality (n=28). Experiences were grouped into three categories: positive (usefulness, satisfaction, empowerment, educational support), conditioning factors (individual, contextual, and design-related), and barriers (technological, usability, personal). Perceptions focused on usefulness, usability, and impact on self-care. Facilitators included simple design, personalization, professional support, cultural adequacy, and motivation. Conclusions Digital health technologies promote self-management and glycemic control, although barriers persist that limit their sustained adoption. Systematic Review Registration https://www.crd.york.ac.uk/prospero/ , identifier CRD420251241989.

BackgroundOstomy creation for cancer treatment negatively impacts the quality of life of both patients and caregivers. Hispanic patients with cancer and caregivers often face additional challenges, including limited access to supportive care programs.ObjectiveThis study aimed to examine the experiences and preferences of Hispanic patients with cancer living with ostomies and their caregivers to inform the cultural adaptation of an existing intervention program and the design of Ostomy Self-Care Program (Programa de AutoCuidado de Estoma [PACE]).MethodsIn this 2-stage study, conducted between March and August 2023 in San Antonio, Texas, we used a qualitatively driven mixed methods design, starting with an initial survey followed by qualitative interviews to explore the experiences, needs, and intervention preferences of Hispanic patients and caregivers managing ostomy care. We used Braun and Clarke’s 6-phase thematic analysis approach to analyze the qualitative data and performed descriptive analysis for the quantitative data. Subsequently, we applied affinity diagramming and persuasive systems design principles to guide the design of PACE.ResultsIn total, 14 Hispanic participants managing an ostomy (9 patients with cancer and 5 caregivers) completed a survey and participated in interviews, continuing until data saturation was reached. Participants had a mean age of 58.9 (SD 13.01, range 37‐79) years, and most (n=12) reported a high school diploma or General Educational Development as their highest education level. Around 5 (36%) participants scored below 26 on the eHealth Literacy Scale (eHEALS), indicating low digital health literacy, and the average Charlson Comorbidity Index (CCI) was 3.21 (SD 1.86, range 0‐6). Overall, 3 major themes emerged from the qualitative data analysis, namely perceptions of living with an ostomy, seeking support, and postsurgery challenges. Additionally, two primary themes emerged from participant interviews: (1) importance of preferred language and multimedia delivery and (2) patients and caregivers desire early introduction, multimodal delivery of materials, and inclusion of peer and family support. These themes informed the design and development of a culturally appropriate, web-based, bilingual PACE intervention that integrates content visualization, cultural adaptations, and persuasive technologies—strategies designed to encourage user engagement.ConclusionsOur findings emphasize the importance of understanding the ostomy care experiences, supportive care needs, and intervention preferences of Hispanic patients and caregivers. Informed by stakeholders’ insights, we culturally adapted the original intervention program using persuasive systems design principles to design and develop the PACE intervention, aiming to enhance engagement among Hispanic patients with cancer and caregivers, support effective self-management of ostomy care, and improve health outcomes.

Traumatic brain injury (TBI) in the U.S. military can result in lasting health issues, with insomnia being a common symptom that worsens recovery, cognitive function, and performance, especially when combined with common co-occurring conditions like chronic pain, post-traumatic stress disorder (PTSD), and depression. Insomnia may be an important intervention target for managing post-concussive symptoms and overall functioning in service members who have sustained a TBI. However, the standard of care for the treatment of insomnia, Cognitive Behavioral Therapy for Insomnia (CBTI), is not widely available in military health care settings. The aim of this paper is to describe the design and analysis plan of the clinical trial to evaluate and compare two methods for delivering CBTI including in-person CBTI or CBTI delivered remotely via a clinician-supervised digital platform in a sample of active-duty service members presenting for care in a military TBI specialty clinic. This is a phase II, randomized clinical trial designed to evaluate and compare the effects of CBTI (in-person or via a digital health platform) on sleep, behavioral health, and cognitive functions relative to treatment as usual among a sample of service members with a history of TBI. The effectiveness of in-person CBTI and CBTI delivered via a digital health platform, relative to treatment as usual, will be compared at baseline, after the six-week intervention, and again three months later on symptoms of insomnia, sleep quality, post-concussive symptoms, neurocognitive functioning, and psychological health. TBI is common in military personnel, often leading to insomnia that affects health and performance. While CBTI is the first-line recommended treatment for insomnia, CBTI is rarely implemented as the standard of care in military TBI specialty clinics, highlighting the need to assess its role in treating post-concussion symptoms and related issues. Clinical trials evaluating insomnia treatment in U.S. military service members with a history of TBI are essential to inform clinical practice for military TBI patients affected by insomnia and to potentially improve recovery, duty readiness, and cognitive function in this population. ClinicalTrials.gov: NCT06867666. Registered on 2/26/2025.

Sustainable value generation from digital health investments: lessons from EU-funded projects preceding the European health data space.

Lived experiences of health professionals using digital health in Australian aged care: A scoping review.

Digital health literacy of ICU survivors: A prospective cohort study.

Handling Editor: Monica AndersenA global perspective of parent engagement with digital sleep health interventions for young children: A scoping review.

In the present era, environmental attitudes and awareness, along with digital behavior among the youth, play a crucial role in ensuring the sustainability of natural resources and societal well-being. This study examined the digital behavior, mental health, and environmental attitudes among the undergraduate students at Krishnagar Government College, West Bengal, India. A structured questionnaire-based survey was conducted using a ‘Google Form’ to collect the responses anonymously. A total of 398 responses were received from the surveyed students, which is approximately 16 to 18% of the enrolled college student population. Key findings suggest that excessive screen time was associated with poorer sleep, increased academic stress, and concentration difficulties. Students who seldom sought support were significantly more likely to report severe stress, while eco-conscious behaviors, such as using reusable drinking water bottles, were associated with more positive overall well‑being. Clustering of the responses revealed distinct student profiles based on usage and stress metrics, suggesting targeted interventions. This study provided a comprehensive statistical overview of college students’ well‑being in the digital age and offered evidence-based recommendations for college campus policies and support programs.

Digital health integration in chronic kidney disease.

The infodemic-pandemic nexus: Cross-national analysis of online misinformation's impact on population health.

Social media offers numerous advantages, yet the dark side of it haunts youth. One of the several potential detrimental aspects appears as social media addiction (SmA), which poses risks to the psychological well-being (PW) of youth. Among university students, excessive social media use can lead to SmA and a subsequent decrease in PW. This study scrutinizes the mediating effects of techno-invasion (TI) and techno-overload (TO), instigated by SmA, on students' psychological well-being, a relationship that previous research has not conclusively explored. Our research constructs a model to examine the moderating effects of social capital, specifically through the lenses of social bonding and social bridging, on the nexus between social media-induced challenges and psychological well-being. This investigation examines the associations between SmA, TO and TI through self-esteem among students. Data collected through a three-wave time-lagged design from 991 university students in Abu Dhabi, UAE, were analyzed with the PROCESS macro. The findings reveal that SmA is significantly negatively related to students' self-esteem, which in turn is associated with increased levels of TI and TO, ultimately reducing psychological well-being. Moreover, the study verifies the moderating roles of social bonding and social bridging in the TI-PW and TO-PW relationships. The paper concludes by addressing the broader implications of these findings and suggesting avenues for future research in this domain. This study demonstrates how SmA reduces self-esteem, which in turn increases TO and TI, ultimately leading to a decline in PW. The findings suggest that improving self-esteem and enhancing social capital through stronger connections with family and friends can help alleviate the negative consequences of SmA on students' well-being, offering valuable contributions to the literature on digital stress and mental health.

Sleep and mental health problems are common across the working adult population. This process evaluation provides insight into the experiences of employees who took part in a digital intervention trial: Supporting Employees with Insomnia and Emotional Regulation Problems (SLEEP). The programme combined digital CBT for insomnia with emotion regulation. Digital content was supported by remote therapy. The objectives of this process evaluation were to explore participants' experiences of the intervention, and identify how the intervention achieved change. Twenty-one semi-structured interviews were conducted using videoconferencing. A stratified sample of participants from within each of five cohorts of the SLEEP trial was interviewed. Thematic analysis utilized a collaborative codebook and framework approach. To conceptualize mechanisms of change, behaviour change techniques were retrospectively coded onto participant interview data. An overarching theme: 'Better sleep, better wellbeing' was generated, with three interlinking themes conceptualizing the process by which positive changes to sleep and wellbeing were achieved. These were: 'Procedure: The value of therapy sessions versus digital-only', 'Context: Working on mental health from home during COVID-19', and 'Mechanisms: Practice, feedback and problem solving.' Participants' experiences of SLEEP were predominantly positive and suggested a spillover effect of improved sleep on overall wellbeing. Triangulation of quantitative outcomes showed congruent improvements. Maintaining therapist contact to facilitate behaviour change throughout the programme was important. Furthermore, providing a private space for therapist calls was essential to facilitate the intervention in the workplace; an important insight for the development of digital mental health interventions intended for the workplace.

Multi-Platform analytics integration for clinical trial Recruitment: A digital health informatics implementation framework.

Digital health services and rural healthcare access: Evidence from China

A prognosis-centric evaluation model for wearable sensor inputs in digital health intelligence

Alcohol-related liver disease (ArLD) is a public health concern that requires multidisciplinary interventions. Digital health tools may improve retention in alcohol use disorder (AUD) treatment and enhance health outcomes. This study explores a blended intervention (brief intervention plus a serious game (SG) based on motivational interviewing and cognitive-behavioural therapy) on AUD in patients with ArLD. Randomised, single-blinded controlled trial on patients with recent-onset ArLD and AUD. Brief intervention plus the SG was compared to standard addiction therapy. Primary outcomes were AUD treatment retention and adherence at 6 months. Secondary outcomes included liver disease progression, alcohol use patterns, quality of life, functionality, motivational changes and usability. Seventy-nine patients (mean age 56, MELD-Na 14) were included. Participants in the intervention arm were three times more likely to remain in treatment at month six than those in the control arm (adjusted odds ratio (aOR) 3.24; 82.9% vs. 47.4% of engagement respectively) and attended 50% more appointments. Effect sizes (Cohen's D) were moderate for adherence at months three and six (0.51-0.64). At 6 months, Model for End-Stage Liver Disease Sodium (MELD-Na) scores were lower in the experimental group (12 vs. 16, p < 0.001). Among baseline drinkers, alcohol consumption decreased more in the intervention group at month one (11 vs. 6 Standard Drink Units (SDU)/day, p = 0.031). The blended intervention increases engagement with AUD treatment, reduces the amount of consumed alcohol and improves MELD-Na scores. These results support the use of digital tailored interventions for AUD in these patients.