DIGITAL HEALTH最新文献

Background: Obesity is strongly associated with impaired physical function and increased health risks. Functional performance tests such as the Timed Up and Go (TUG), Five Times Sit-to-Stand (5xSTS), and 4-Meter Walk Test (4MWT) are essential for evaluating mobility, strength, and gait speed. Although widely used in clinical practice, the reliability of remote tele-assessment of these tests in adults with obesity remains unclear.

Objective: This study aimed to determine the inter- and intra-rater reliability of tele-assessment compared with face-to-face assessment for commonly used functional performance tests in adults with obesity.

Methods: A repeated-measures observational study was conducted with 82 adults with obesity. Participants performed TUG, 5xSTS, and 4MWT tests both in a clinical setting and remotely at home using video-based tele-assessment.

Results: Inter-rater reliability was good for TUG (ICC = 0.826) and 5xSTS (ICC = 0.880), and moderate for 4MWT (ICC = 0.743). Intra-rater reliability across two tele-assessments was excellent for TUG (ICC = 0.910) and 5xSTS (ICC = 0.902), and good for 4MWT (ICC = 0.858).

Conclusion: Tele-assessment provides a reliable alternative to face-to-face assessment of functional performance tests in adults with obesity. These findings support the integration of remote functional testing into digital health practice, expanding access to mobility and strength evaluations for populations with limited access to in-person care.

Clinical trial registration: Not applicable.

Background: Cervical cancer remains a leading cause of cancer morbidity and mortality among women worldwide, with an estimated 661,021 new cases and 348,189 deaths in 2022. In China's health-resource-limited areas, a substantial share of the population remains hard to reach, and the effectiveness of data-driven identification and digital outreach for this hard-to-reach population is uncertain.

Objective: This study aims to (a) use ID-card-based record linkage to identify women who have never undergone cervical cancer screening and (b) evaluate whether the integrated digital intervention reduces redundant repeat screening while improving women's knowledge, attitudes and practices (KAP) in health-resource-limited areas.

Methods: We will conduct a quasi-experimental controlled trial including an external historical control cohort and two individually randomised digital intervention arms in 11 sites. Women will be identified by matching unique ID-card numbers across the national screening registry and local household records. Newly screened eligible women will be randomly allocated to one of two intervention arms: (a) tailored digital interventions and (b) generic digital interventions, while an external historical cohort (January 2022-December 2023) from the same sites, before implementation of the digital platform, will serve as the control arm.

Results: Recruitment began on 15 April 2025. The trial plans to recruit 142,417 participants (122,817 in the historical control cohort and 9800 in each intervention arm). Baseline surveys commenced on 15 April 2025 and will continue until December 2026.

Conclusions: If effective, this study will be among the first to evaluate a full-process digital health intervention that combines algorithm-based identification with a web-plus-WeChat platform for cervical-cancer screening in resource-limited areas of China. The findings could inform programme development and benefit hard-to-reach populations.

Background: Regular monitoring of blood pressure (BP) provides early detection of hypertension. Automated cuff-based oscillometric devices are commonly used for simplicity and reduced observer subjectivity. However, these devices can be uncomfortable, prompting the development of non-invasive, cuffless BP monitoring in smartwatches. Current validation standards, including ISO 81060-2:2018 and IEEE 1708TM-2019, specify accuracy criteria, yet most studies focus on short-term performance and do not address their long-term stability across the calibration period.

Objective: This prospective single-arm study aimed to assess the long-term accuracy and stability of BP measurements obtained from a smartwatch throughout its recommended calibration interval.

Methods: Thirty-seven participants completed a 28-day protocol, consisting of an initial calibration on day 0 followed by 27 consecutive days of paired measurements of systolic BP (SBP) and diastolic BP (DBP). BP was simultaneously measured using a Samsung Galaxy Watch 5 and a validated reference sphygmomanometer Omron M4. Accuracy was assessed against ISO and IEEE standards, and the recalibration test consistent with European Society of Hypertension (ESH) guidelines was performed using the last three measurements before scheduled recalibration.

Results: The smartwatch met the accuracy criteria based on ISO and IEEE standards in all but one measure, with mean absolute differences, mean differences (MD), and standard deviations for SBP and DBP within acceptable limits. Bland-Altman analysis revealed negligible MD for SBP (-0.34 mmHg) and DBP (0.62 mmHg), with minimal drift over the calibration period (-0.19 mmHg for SBP and 1.02 mmHg for DBP). However, when reference BP was 10 mmHg away from the calibration point, MD was 3.4 mmHg for SBP and 5.1 mmHg for DBP.

Conclusions: The smartwatch demonstrated acceptable long-term stability and accuracy for BP monitoring and trend tracking. However, accuracy declined as values diverged from the calibration point. Cuff-based confirmation is advised when BP fluctuates substantially or when diagnostic or therapeutic decisions are planned.

Trial registration: ClinicalTrials.gov NCT06098092.

Objective: To evaluate the performance of machine learning (ML)-based survival models for 10-year cardiovascular disease (CVD) risk prediction using large-scale electronic health records (EHRs). The study benchmarks these models against the QRISK3 score and conventional Cox proportional hazards (CoxPH) models currently used in UK primary prevention, with the aim of assessing their potential to capture complex risk patterns beyond traditional approaches.

Methods: This study utilized individual-level data from the CPRD Aurum, covering 40 million UK primary care records from 2011 to 2021. A total of 469,496 patients aged 40-85 was analysed. Predictor variables were selected based on QRISK3 definitions, with additional phenotyping for comorbidities and pre-stratified risk scores. ML models, including deep neural networks (e.g., DeepSurv and DeepHit) and ensemble survival models (e.g., random survival forest [RSF] and gradient boosting), were developed for CVD risk prediction. Model performance was assessed using calibration and discrimination metrics, with 'spatial external validation' conducted using a London-held dataset.

Results: A total of 849,651 records were analysed, including 117,421 for 'spatial validation' and 732,230 for development. QRISK3 scores effectively differentiated CVD patients, particularly among females, showing stronger predictive performance. Ensemble methods and neural networks outperformed CoxPH models, with RSF achieving the best discrimination and calibration: AUROC values of 0.738 (95% CI: 0.723-0.752) for males and 0.778 (95% CI: 0.762-0.793) for females, with Brier scores of 0.088 and 0.055.

Conclusion: ML models enhance CVD risk prediction, outperforming conventional approaches in calibration and discrimination. Integrating pre-stratified risk scores further improves performance, highlighting the value of augmenting tools like QRISK.

Objective: Over the past decade, the German tele-emergency medical system (tele-EMS) has undergone continuous expansion. This growth has introduced a range of innovations that have transformed the daily work of tele-EMS physicians. At the same time, it has also brought new challenges, including parallel rescue operations, supra-regional deployments, and an increasing number of patient cases. To address these issues, the utilisation of an artificial intelligence (AI) system developed specifically for tele-EMS physicians was investigated.

Methods: As part of a qualitative study, 11 tele-EMS physicians were interviewed to understand their perspective on the implementation of AI in the field of tele-emergency medicine. The interview questionnaire covers a range of topics, including requirements and concerns of tele-EMS physicians regarding the use of the specific AI system, as well as their willingness to work with this system in future.

Results: The results of the study reveal that, despite certain concerns and fears, tele-EMS physicians are generally positive about the implementation of AI technology in prehospital tele-emergency medicine. When designed effectively, the system is considered potentially suitable for reducing the workload of tele-EMS physicians and improving the quality of patient care.

Conclusions: This study addresses a significant gap in the field of telemedicine research by examining perceptions of tele-EMS physicians regarding the implementation of AI in prehospital tele-emergency medicine, while also outlining critical ethical considerations related to AI integration in tele-emergency care. Furthermore, it provides a set of items for a qualitative interview study that can be easily adapted for use with other medical technologies.

The aim of this review is to explore how the (dis)affordances of digital technologies-such as robots, game consoles, tablet computers, and virtual environments-shape the quality of the social relationships between care workers and residents in dementia care. Using a narrative review methodology, we analyzed 15 peer-reviewed articles published between 2012 and 2023 through thematic analysis. The findings are organized around three contrasting emotional dimensions: comfort-discomfort, joy-anger, and safety-vulnerability. Comfort and discomfort were primarily linked to everyday conversations, joy and anger to experiences of play and entertainment, and safety and vulnerability to how effectively care workers safeguarded residents' sense of security. These results demonstrate that emotional expressions are not only outcomes of interpersonal interaction but are also mediated by technological affordances. Supporting care workers in recognizing and responding to these emotional dynamics is therefore crucial for ensuring that digital technologies enhance residents' well-being and help sustain secure social bonds in dementia care.

Background: Auditory verbal hallucinations (voices) are common in schizophrenia spectrum disorders (SSD), and cause significant distress, making them a critical target in psychotherapeutic interventions. AVATAR therapy, conducted on a two-dimensional computer screen and its adaptation virtual reality-assisted therapy (VRT), using three-dimensional virtual reality (VR), have shown promise. Despite the potential of VRT, research exploring how specific VR characteristics can simulate voices experiences and affect therapy outcome remains scarce. Addressing this gap is key to refining VRT for persistent voices.

Objective: This qualitative substudy of the CHALLENGE trial explored patient perspectives on modified VRT versions (VRT-Emotions, VRT-Environment, and VRT-Whiteboard) and their therapeutic impact, with the aim to inform intervention refinement and development.

Methods: Semistructured interviews were conducted with 15 participants with SSD and persistent voices after undergoing the modified therapies. Data were analyzed within a pragmatist-critical realism orientation, with a hybrid deductive-inductive approach to thematic analysis. Reflexive team dialogues supported analytical rigor.

Results: One overarching theme: A challenging yet transformative therapy, and three subthemes, corresponding to the specific modifications, were generated: Emotional connection with voice, Recognizability builds resistance, and The power of the written word. The modifications were generally perceived to enhance therapeutic experience and effectiveness, albeit participants' perspectives varied and sometimes contrasted.

Conclusions: Findings suggest that refining VRT for persistent voices may involve improving avatar's facial expressions, tailoring therapy to voice experiences, and using recognizable VR environments with gradual exposure and selective visual tools. While controlled studies are needed to establish efficacy, these insights offer practical guidance for VRT refinement and development.  .

Background: Mental health conditions commonly co-occur with chronic diseases, yet few evidence-based interventions are designed for rural populations or scalable within primary care. This study evaluated the mental health impact, clinical significance, and usability of a digitally delivered Personal Empowerment Program (PEP).

Methods: This single-arm prospective interventional trial (October 2023-August 2025) enrolled 182 community-dwelling adults with ≥1 physician-diagnosed chronic condition in Pictou County, Nova Scotia. The six-month PEP program delivered daily digital modules via email and YouTube covering physical fitness, nutrition, mindfulness, sleep, and social connection, with weekly self-monitoring and monthly videoconferencing, optimized for low-bandwidth mobile access. The primary outcome was psychological distress (Kessler Psychological Distress Scale (K10); secondary outcomes included anxiety (GAD-7) and depression (CES-D). Generalized estimated equations assessed changes (baseline, 6, and 12 months).

Results: A total of 115 participants (63.2%) completed 6- and 12-month K10 follow-up assessments. K10 scores declined by 3.00 points (95% CI:-4.05,-1.95) at 6 months and 3.60 (95% CI:-4.84,-2.36) at 12 months (both P < 0.001). GAD-7 scores declined by 1.36 points (95% CI:-2.28,-0.45) at 6 months and 2.11 points (95% CI:-3.03,-1.20) at 12 months, while CES-D scores declined by 2.43 points (95% CI:-4.65,-0.21) at 6 months and 4.31 points (95% CI:-6.84,-1.78) at 12 months. Clinically meaningful improvement at 12 months was observed in 23% (K10), 23% (GAD-7), and 38% (CES-D) of participants. Usability ratings were high.

Conclusions: PEP demonstrates sustained mental health benefits and high usability within a scalable, low-bandwidth digital model, supporting equitable mental health care for rural adults with chronic conditions.

Background: The incidence and mortality of renal cell carcinoma (RCC) have risen significantly in recent years, attracting considerable public attention. Short-video platforms such as TikTok and Bilibili have become important sources of health information, yet the quality and reliability of RCC-related content on these platforms remain unclear.

Methods: On August 31, 2025, we systematically retrieved the top 110 videos related to RCC from both TikTok and Bilibili using the keyword "RCC." Basic video characteristics were extracted, and two validated instruments-the Global Quality Scale (GQS) and the modified DISCERN (mDISCERN)-were employed to evaluate video quality and reliability, respectively. Spearman correlation analysis was used to examine relationships between engagement metrics and quality scores.

Results: Of 196 videos included, TikTok content was predominantly from medical professionals (86.0%), while Bilibili had more non-professional uploads (53.13%). TikTok videos demonstrated significantly higher median scores than Bilibili in both GQS (3 [IQR: 2, 4] vs. 2 [IQR: 2, 3], P < .001) and mDISCERN (2 [IQR: 2, 3] vs. 2 [IQR: 1, 2], P < .001). Nevertheless, the median GQS score of 3 indicates only moderate quality, and the median mDISCERN score of 2 reflects a relatively low level of reliability. Videos from healthcare professionals, especially RCC specialists, scored higher in quality (GQS: 3 [IQR: 3, 4]) and reliability (mDISCERN: 3 [IQR: 2, 3]) than non-professional sources (P < .001). Disease knowledge videos scored highest, while advertisements scored lowest. Engagement metrics showed weak negative or non-significant correlations with quality scores.

Conclusion: The overall quality and reliability of RCC-related short videos on TikTok and Bilibili are suboptimal. Content from medical professionals is more trustworthy, highlighting their essential role in public health education. These findings underscore the need for enhanced content oversight on platforms and critical discernment among viewers when accessing health information online.