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PubMed2026

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 ≥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 + 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 cm across Standard Care, Platform, and Platform + Devices groups respectively, and systolic blood pressure declined by -4.84 to -7.15 mmHg across groups. The Platform + 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 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↗

PubMed2026

User Engagement and Feature Preferences in an AI-Powered mHealth Intervention for Diabetes Prevention: Secondary Analysis of a Randomized Controlled Trial.

BACKGROUND: Prediabetes is highly prevalent and increasing globally, yet lifestyle interventions remain underused. AI-driven mobile health (mHealth) tools can help scale diabetes prevention efforts, but the key factors driving their success are not well understood. OBJECTIVE: This post hoc secondary analysis of a randomized controlled trial (RCT) aimed to characterize the most valued features and the role of user engagement in outcomes of a fully automated mHealth intervention for diabetes prevention. METHODS: Data from 151 participants with prediabetes and overweight or obesity who were assigned to an AI-based diabetes prevention program (Sweetch) in a parent RCT (NCT05056376) were analyzed. Engagement (defined as the total number of days the app was used) was categorized into tertiles (low, medium, and high). Baseline characteristics were compared across engagement groups using ANOVA, Kruskal-Wallis, and chi-square tests, and regression models assessed the association between engagement and achievement of diabetes risk reduction outcomes (≥5% weight loss, ≥4% weight loss with ≥150 min/week of physical activity, or ≥0.2 percentage point reduction in hemoglobin A1c [HbA1c] at 12 months). Perceived usefulness of intervention features was surveyed at 12 months. RESULTS: Median engagement was 98 (IQR 34-232) days. Older age (P<.001) and lower baseline BMI (P=.04) were significantly associated with higher engagement. Compared with low engagement, high engagement was associated with greater odds of achieving the composite diabetes risk reduction outcome (odds ratio [OR] 2.59, 95% CI 1.11-6.01; P=.03), ≥5% weight loss (OR 3.31, 95% CI 1.16-9.42; P=.03), and ≥0.2 percentage point reduction in HbA1c (OR 3.57, 95% CI 1.19-10.75; P=.02). Participants most frequently rated weight tracking, physical activity tracking, and the digital body weight scale as the features that were most helpful for achieving their health goals. CONCLUSIONS: Higher engagement with an AI-driven intervention requiring no human intervention was associated with improved diabetes risk reduction. Contrary to concerns about lower digital literacy, older adults engaged with the intervention more than younger adults. Features related to weight and physical activity tracking were most valued by patients in the program. TRIAL REGISTRATION: ClinicalTrials.gov NCT05056376; https://clinicaltrials.gov/study/NCT05056376.

Humans↗

PubMed2026

Unanticipated Effects of Parental Social Media Use: Guidance for Clinicians.

"Sharenting," the practice of parents posting photographs, videos, and information about their children on social media, has an ever-growing presence in modern society. However, researchers and the public are now recognizing the potential consequences of sharing, including creation of permanent digital footprints, strained familial relationships, and threats to children's safety. Despite this emerging evidence, no U.S. clinical or legal guidelines exist for parents on safe sharing. Visits with behavioral health providers and family physicians can serve as key points for intervention. This column aims to provide clinicians with a better understanding of sharenting and its potential effects on patients and families, guidance on discussing safe online sharing, and a tool for parents and other caregivers to use when deciding whether to post.

Humans↗

PubMed2026

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↗

PubMed2026

Nurse-Led Home-Based Mobile Health Cardiac Rehabilitation Program for Patients With Chronic Heart Failure: A Randomized Controlled Trial.

This 12-week randomized controlled trial evaluated a nurse-led mHealth intervention for patients with chronic heart failure, conceptually informed by Riegel's middle-range theory of self-care of chronic illness. The program integrated wearable activity tracking with weekly nurse-led behavioral coaching, reflecting the core self-care processes of monitoring, maintenance, and management. Compared with usual care, the intervention significantly improved daily step count, 6-minute walk distance, metabolic equivalents, and left ventricular ejection fraction. Findings highlight the effectiveness of theory-informed, nurse-delivered mHealth strategies in enhancing physical activity and cardiopulmonary function, while underscoring the critical role of advanced practice nurses in home-based chronic disease management.

Aged↗

PubMed2026

Cost-Effectiveness of Electronic Patient-Reported Outcome Measure Interventions in Cancer: Systematic Review and Parameter Extraction for Economic Modeling.

BACKGROUND: Complex digital interventions that integrate electronic patient-reported outcome measures (ePROM) into clinical practice in cancer have the potential to improve quality of life, increase survival, and reduce health resource use and costs. Such systems can help patients with cancer self-manage chemotherapy symptoms, reduce clinicians' workloads through automated decision support, and resolve problems earlier. However, more research on the cost-effectiveness of ePROM monitoring is needed. OBJECTIVE: This paper comprises two complementary components: (1) a systematic literature review summarizing and evaluating the quantitative and qualitative evidence related to the cost-effectiveness of ePROM monitoring and (2) a health economic model parameter extraction. We also conducted supplementary targeted searches and scoping to provide context to our findings. METHODS: We searched Ovid (including MEDLINE and Embase), Scopus, and the International Health Technology Assessment Database for original English-language papers published on or before March 2025 using search strings that combined terms related to ePROMs, health economics, and cancer/oncology. We included papers reporting health economic-related outcomes for ePROM interventions designed for adult cancer populations and excluded screening tools and conference abstracts. RESULTS: We included 34 publications from 27 unique studies and identified and analyzed 26 ePROM-integrated interventions within these. Most (23/26) of the included interventions explicitly described some form of alert handling and automated decision support based on remote ePROM monitoring. Of the 34 publications, 5 presented full cost-effectiveness analysis results, of which 3 were highly uncertain and lacked clear differences in costs and health outcomes between ePROMs and standard care; conversely, 2 presented strong evidence of cost-effectiveness due to quality-of-life improvements, reduced hospitalizations, and potentially more autonomy in health-related travel (eg, ePROM-monitored patients can drive or walk to the hospital instead of using taxis or ambulances). A further 5 publications reported partial health economic results (eg, cost-consequence and budget impact), of which 1 detected no difference in strategies; in contrast, 4 reported lower health resource use and costs of ePROMs, mainly due to hospitalization reductions. Overall, 12 of the 27 studies included a qualitative component but mostly focused on user experience and design-related themes; only 2 of these addressed economic-specific themes (eg, changes in workflow and resource use due to ePROM implementation and integration), indicating some potential for time saving due to ePROM monitoring. CONCLUSIONS: Some ePROM-integrated interventions demonstrated cost-effectiveness in cancer care, but the evidence base remains limited. Where evidence does exist, cost-effectiveness appears driven by reduced hospitalization and improved quality of life. Qualitative research within the included studies rarely addressed economic questions. We provide a detailed parameter extraction for use in future economic modeling and recommend research priorities, including quantitative mapping of ePROM symptom data onto health resource use patterns, and qualitative work exploring how ePROM implementation affects clinical workloads and patient-perspective costs.

Humans↗

PubMed2026

Facilitating Thought Progression via a Gamified Mobile Application for Depression: Possible Mediators of Outcomes.

Mobile health interventions represent a scalable and accessible alternative to traditional therapy, which often is out of reach due to high costs and societal stigma. Rumination is considered a key mechanism of emotional disorders and represents a potential treatment target for digital health interventions. The current study investigated the role of rumination as a mediator of the reduction in depression and anxiety reported after the use of a gamified mobile app based on the Facilitating Thought Progression (FTP) framework. One hundred-one adults with mild to moderate depression were randomized to the FTP intervention or a waitlist control group and completed weekly assessments of depression, anxiety, and rumination over 8 weeks. Multilevel structural equation modeling revealed that reduction in rumination significantly mediated decreases in depression and anxiety in the intervention group but not in the waitlist condition. These findings suggest that the FTP app targeted rumination and further highlights its role as a critical target for interventions for depression and anxiety.

Adult↗

PubMed2026

Post-intervention effectiveness of a computerized personalized cognitive stimulation program adapted according to cognitive reserve in older adults without cognitive impairment in Primary Care: A randomized clinical trial.

BACKGROUND: Cognitive reserve may influence responsiveness to cognitive interventions, yet it is rarely used to tailor computerized stimulation. OBJECTIVE: To evaluate the effectiveness of a computerized cognitive stimulation program personalized according to cognitive reserve on cognition, reserve-related activities, and digital competence in community-dwelling older adults without cognitive impairment in Primary Care. METHODS: In this randomized clinical trial, 102 adults aged ≥65 years with normal cognitive performance were recruited from three primary care centers in Zaragoza, Spain, and stratified by cognitive reserve level before random allocation to intervention or control. The intervention comprised digital literacy sessions followed by 8 weeks of home-based computerized cognitive stimulation tailored to participants' cognitive reserve profiles and life history. Controls received a single group-based health education session focused on maintaining everyday cognitive activity. Outcomes were assessed at baseline and post-intervention using global cognition (MEC-35), the Cognitive Reserve Questionnaire, the Mobile Device Proficiency Questionnaire-16, and domain-specific neuropsychological tests. A total of 100 participants completed the final evaluation and were included in complete-case analyses. RESULTS: Compared with controls, the intervention group showed greater adjusted post-intervention improvements in global cognition (MEC-35 between-group difference: 1.8 points) and several cognitive measures, including temporal orientation, calculation, attention, praxis, verbal fluency, processing speed, executive functions, and verbal learning. CRQ scores and digital competence also improved, with small-to-large effect sizes. CONCLUSIONS: A computerized cognitive stimulation program adapted according to cognitive reserve appears feasible in Primary Care and may improve cognition, engagement in reserve-related activities, and digital competence in older adults without cognitive impairment.

Humans↗

PubMed2026

Self-selected goals outperform assigned goals in reducing mobile phone usage: Evidence from a randomized controlled trial.

Excessive smartphone use is increasingly recognized as a public-health concern, yet scalable approaches to help individuals regulate daily use remain limited. We examine whether allowing individuals to self-select reduction goals improves behavioral and psychological outcomes when incentives and average goal levels are held constant across conditions. In a twelve-week randomized controlled trial, (N = 149; over 9000 person-day observations), participants were assigned to (i) a self-selected condition (choosing a 10%, 20%, or 30% reduction in daily phone use), (ii) an assigned condition (assigned a 14% reduction goal), or (iii) a no-goal control condition. Participants who selected their own goals reduced phone use by 26 min more per day (73% larger reduction) and achieved their goals 11 percentage points more often than those assigned goals, despite identical incentives and average goal levels. Reductions in phone use and higher goal achievement were associated with improvements in perceived addiction, depressive, and anxiety symptoms. These psychological outcomes were secondary endpoints. Although the between-group estimates generally followed the same directional pattern as the behavioral outcomes, the sample size for these analyses was limited and the between-group differences were not statistically significant. These findings should therefore be interpreted with caution. Overall, the results provide causal field evidence that self-selection under this goal-setting design can improve behavioral outcomes. Allowing individuals to choose their own goals may strengthen engagement and support healthier digital behavior. Incorporating opportunities for goal-selection may represent a simple addition to digital-health and public-health interventions aimed at helping individuals moderate smartphone use and improve well-being.

Humans↗

PubMed2026

Effectiveness of Embedded Social Media Content on E-cigarette Attitudes and Behaviors: Results from a Randomized Control Trial.

BACKGROUND: This longitudinal randomized controlled trial examined the effects of anti-vaping social media content on e-cigarette attitudes and intentions among U.S. young adults (ages 18-24; n=3,400). METHODS: Targeted content was embedded directly into participants' social media feeds, with varying levels of impressions. RESULTS: Results indicate that increased exposure to anti-vaping messages significantly elevated perceived risk of harm (β=0.11, 95% CI: 0.03-0.20, p < .01) and social unacceptability of e-cigarette use (β=0.10, 95% CI: 0.03-0.18, p < .01), while decreasing intentions to vape (RRR = 0.59, 95% CI: 0.36-0.97, p < .05). Notably, these attitudinal shifts occurred even with relatively low ad exposure and over an extended intervention period, while controlling for the e-cigarette use status (never, former, or current) of participants. Discussion These findings support the effectiveness of digital media campaigns in influencing health-related behaviors and attitudes among young adults. Specifically, embedding anti e-cigarette content directly in the feed of young adults is shown to be effective in shifting attitudes in a space where these young adults are already engaged. Limitations include limited ad impressions and minimal change in ad awareness recall, suggesting future research should explore longer interventions and broader nicotine product messaging.

Humans↗

PubMed2026

Mobile health apps improve Health-Related Quality of Life in Type 2 Diabetes Mellitus by enhancing medication adherence: A multicentre randomised controlled trial with mediation analysis.

AIMS: This study evaluated whether a gamified mHealth application (CareAide®) improves Health-Related Quality of Life (HRQoL) in Type 2 Diabetes Mellitus (T2DM) and whether this effect is mediated by medication adherence. METHODS: Prespecified secondary analysis of the T2DM cohort from a 6-month multicentre RCT (NCT06068309; N = 663; three Malaysian hospitals). Participants were randomised 1:1 to standard care or CareAide®. Adherence (MMAS-8), EQ-5D-5L utility (Malaysian value set), and AQoL-6D were assessed at baseline and 6 months. Simple mediation analysis (PROCESS Model 4; 5000 bootstraps) adjusted for baseline HRQoL. RESULTS: CareAide® significantly predicted higher MMAS-8 scores (mean difference +1.756; d = 1.638; p < 0.001). Higher MMAS-8 scores significantly predicted improved AQoL-6D utility (b = 0.024; p < 0.001). The direct effect on AQoL-6D was non-significant (p = 0.248). Bootstrapped indirect effect confirmed full mediation via AQoL-6D (0.042; 95% CI [0.024, 0.060]). A sensitivity analysis adjusting for baseline HbA1c confirmed full mediation (indirect = 0.034; 95% CI [0.015, 0.052]; n = 563). EQ-5D-5L utility showed a significant direct between-group difference at 6 months (p = 0.012) but did not operate as a mediation outcome. CONCLUSIONS: Medication adherence fully mediates the AQoL-6D HRQoL benefit of a gamified mHealth intervention in T2DM, as confirmed by both the primary and HbA1c-adjusted sensitivity analyses. These findings support integration of behaviourally informed digital adjuncts into routine primary diabetes care.

Humans↗

PubMed2026

A pragmatic randomized controlled trial of self-directed online writing interventions for posttraumatic stress symptoms in a real-world digital setting.

Background: Public health and other large-scale crises, such as the COVID-19 pandemic, have intensified the global mental health burden, creating unprecedented demand for accessible interventions for posttraumatic stress symptoms (PTSS).Objective: We evaluated the feasibility and effectiveness of two self-directed online writing interventions embedded within China's WeChat ecosystem during the COVID-19 pandemic through a pragmatic randomised controlled trial.Methods: Between December 2021 and August 2022, 1,526 adults were screened for PTSS via a Tencent Medinfo Mini-Program. Eligible participants (n = 211) were randomised to Guided Narrative Technique-Writing (GNT-W, n = 100) or Expressive Writing (EW, n = 111). Both interventions comprised three self-directed daily writing sessions delivered entirely online without human support. Primary outcome was PTSD symptom severity (PTSD Checklist-Short), assessed at baseline, post-intervention, 2-week, and 1-month follow-ups.Results: While initial engagement followed typical digital health patterns (64.5% overall attrition), participants who initiated treatment showed strong adherence (77% completion). Both interventions were associated with significant within-group reductions in PTSS severity (GNT-W: b = -0.43, p = .023, d = -0.43; EW: b = -0.60, p = .001, d = -0.58), with no significant between-group difference (group × time: b = 0.18, p = .48). GNT-W did not confer additional benefit over EW protocol on PTSS severity.Conclusions: Both self-directed writing interventions were associated with within-group reductions in PTSS; without an inactive control condition, however, these changes cannot be firmly attributed to the interventions. GNT-W showed no advantage over the simpler EW protocol. These findings offer preliminary support for embedding scalable, low-barrier writing interventions in widely used digital platforms.Chinese Clinical Trial Registry: ChiCTR2000034836.

Humans↗

PubMed2026

Privacy, security, and reliability risks of artificial intelligence in healthcare: a systematic review of empirical evidence.

BACKGROUND: Artificial intelligence (AI) is increasingly integrated into healthcare information systems, supporting clinical decision-making, imaging analysis, and predictive modeling. While these applications offer operational and clinical benefits, they also introduce emerging risks to patient privacy, data security, and system reliability. OBJECTIVE: To systematically review empirical evidence on privacy breaches, security vulnerabilities, and misuse associated with AI applications in healthcare settings. METHODS: PubMed, Embase, Web of Science, Scopus, IEEE Xplore, and ACM Digital Library were searched for empirical studies published between January 2015 and November 2025 that evaluated AI use or misuse in clinical diagnosis, treatment, or decision-making. Two reviewers independently screened studies and extracted data using a standardized form. Findings were synthesized narratively due to heterogeneity in study designs, AI methods, and reported outcomes. RESULTS: Of 7,285 records identified through database searches and 205 through citation screening, 22 empirical studies met the inclusion criteria, spanning multiple clinical domains and data modalities, predominantly medical imaging applications. Five recurring threat categories were identified: patient re-identification, membership inference, unauthorized access and adversarial exploitation, input manipulation, and misuse or overinterpretation of AI outputs. Across studies, AI models were shown to encode latent biometric signals across diverse data types, limiting the effectiveness of traditional anonymization and synthetic data approaches. Adversarial attacks and input manipulation were also shown to compromise diagnostic performance and system integrity. CONCLUSION: This systematic review provides empirical evidence suggesting that contemporary AI systems in healthcare introduce privacy and security risks that may challenge traditional assumptions about data protection. These findings underscore the need for privacy- and security-by-design approaches and governance frameworks that address risks across the AI lifecycle.

Humans↗

PubMed2026

Financial incentives and health coaching to improve glycemic outcomes among young adults with type 1 diabetes: A factorial randomized trial (SweetGoals).

AIM: This study aimed to improve glycemic control among young adults with type 1 diabetes (T1D), an at-risk and understudied population. METHOD: N = 300 young adults with T1D recruited nationally were randomized to the factorial combination of (1) financial incentives targeting glucose checking and mealtime behaviors and (2) web health coaching focused on increasing motivation and goal setting for self-management behaviors. All received a smartphone app that accessed device data and provided weekly goal feedback. The intervention lasted 6 months. HbA1c (A1c) was assessed at baseline, +6 months, and +12 months. The mean number of glucose checking and mealtime goals met per week during the intervention were tested as mediators of intervention effects on A1c at 12 months. RESULTS: A1c was significantly reduced from baseline to +12 months across all participants. Indirect effects of both incentives and coaching on A1c reductions were significant and partially mediated by mealtime but not glucose checking goal achievement. There was no synergistic (interaction) effect of incentives and coaching. CONCLUSION: Incentives and coaching both improved critical mealtime behavior but through different strategies. These results suggest that either intervention would be suitable for future testing and dissemination, and that lower cost of incentives may favor their prioritization.

Adolescent↗

PubMed2026

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↗

PubMed2026

Enhancing Self Care Among Oral Cancer Survivors Using a Digital Approach: The Empowered Survivor Trial.

BACKGROUND: Oral and oropharyngeal cancer survivors experience debilitating physical and psychosocial challenges. Little knowledge exists on the efficacy of interventions to enhance self-efficacy in managing these challenges, increase survivorship preparedness, and improve health-related quality of life (HRQoL). METHODS: Individuals (n = 643) diagnosed with oral or oropharyngeal cancer diagnosed within past 3 years were randomized to a digital intervention, Empowered Survivor (ES) or a Generic Online Intervention (GO). Primary (self-efficacy, preparedness, HRQoL) and secondary outcomes (self-care activities) were measured at Baseline, 2-months, and 6-months. RESULTS: Participants assigned to ES reported greater self-efficacy and increased self-care activities of oral self-exams, swallowing, and mobility exercises than those assigned to GO (self-efficacy: 2 months, p = 0.003, 6-months, p < 0.001; self-care activities). CONCLUSIONS: The ES enhanced self-efficacy and increased self-care activities. Further examinations of survivorship preparedness and HRQoL in oral and oropharyngeal cancer are warranted. TRIAL REGISTRATION: Registered on clinicaltrials. gov as NCT04713449.

Humans↗

PubMed2026

Assessing perinatal depression identifying abilities among maternal and child health workers in rural China using smartphone-based virtual patients: a multi-center cross-sectional study.

OBJECTIVE: To assess rural maternal and child health (MCH) workers' virtual patients (VPs)-assessed performance in identifying perinatal depression (PND) using smartphone-based VPs, and to identify factors associated with this performance in rural Hunan, China. METHODS: A multicentre cross-sectional study was conducted in Hunan Province, China. A standardized questionnaire collected demographic and work-related characteristics of rural MCH workers. Smartphone-based VPs were used to assess PND identification performance in a simulated clinical scenario. An overall score ≥60 was used as a prespecified operational benchmark across consultation, ancillary assessment, diagnosis, management, and health education domains. Data were analyzed using SPSS 26.0. RESULTS: A total of 375 rural MCH workers participated, yielding an effective response rate of 90.4%. Only 25.9% met the prespecified operational benchmark for VP-assessed PND identification performance. The mean accuracy scores for consultation, ancillary assessment, diagnosis, management, and health education were 94%, 48%, 64%, 58%, and 74%, respectively. Complete consultation accuracy was higher among MCH workers from township health centers than among those from county-level MCH hospitals. MCH workers aged 18-39 years showed higher odds of complete diagnostic accuracy for PND than those aged ≥40 years. CONCLUSIONS: Smartphone-based VP assessment was feasible in rural MCH settings and revealed suboptimal PND identification performance. Mobile VPs may help identify frontline performance gaps and inform targeted training, but further validation against real-world clinical performance, or standardized patient encounters is needed before large-scale implementation. These findings may support targeted capacity-building for rural MCH workers and more equitable perinatal mental health care.

Humans↗

PubMed2026

The application of artificial intelligence in healthcare practice: A mapping review of systematic reviews.

Artificial intelligence (AI) is rapidly transforming healthcare practice, with growing evidence supporting its use in diagnosis, prognosis, treatment planning, and operational decision-making. The proliferation of systematic reviews in recent years underscores the need for an updated synthesis of the literature to inform research, policy, and practice. We searched PubMed, Web of Science, Scopus, IEEE Xplore, and CINAHL for systematic reviews and meta-analyses published between 2019 and February 2026. Eligible reviews focused on AI applications in healthcare practice, were peer-reviewed, and written in English. A total of 368 reviews met the inclusion criteria. Publication volume increased steadily, peaking in 2025. AI research was concentrated in high-density domains, such as radiology, oncology, and critical care. Across reviews, diagnostic imaging, electronic health record (EHR) data, and biomarkers/laboratory results accounted for 68% of training data sources, though newer data types, such as wearable device and sensor data, emerged from 2022 onward. Diagnosis, prognosis, and treatment comprised over 80% of AI applications, with novel uses emerging in recent years, such as AI-assisted clinical documentation (e.g., ambient documentation tools) and patient education. Ethical concerns were reported in 78.5% of reviews, with privacy, model accuracy, data and algorithmic bias, and explainability as recurrent themes. The proportion of reviews reporting ethical concerns increased from 2021 to 2025. AI applications in healthcare are expanding in scope, diversifying in data sources, and evolving toward novel clinical and operational uses. The human-centered AI or augmented intelligence paradigm, integrating computational precision with clinical expertise, holds significant promise but will require parallel advances in governance, regulatory frameworks, and ethical oversight to ensure safe adoption.

Artificial Intelligence↗