Frontiers in digital health最新文献

Background: Current methods of measuring disease progression of neurodegenerative disorders, including Parkinson's disease (PD), largely rely on composite clinical rating scales, which are prone to subjective biases and lack the sensitivity to detect progression signals in a timely manner. Digital health technology (DHT)-derived measures offer potential solutions to provide objective, precise, and sensitive measures that address these limitations. However, the complexity of DHT datasets and the potential to derive numerous digital features that were not previously possible to measure pose challenges, including in selection of the most important digital features and construction of composite digital biomarkers.

Methods: We present a comprehensive machine learning based framework to construct composite digital biomarkers for progression tracking. This framework consists of a marginal (univariate) digital feature screening, a univariate association test, digital feature selection, and subsequent construction of composite (multivariate) digital disease progression biomarkers using Penalized Generalized Estimating Equations (PGEE). As an illustrative example, we applied this framework to data collected from a PD longitudinal observational study. The data consisted of Opal™ sensor-based movement measurements and MDS-UPDRS Part III scores collected at 3-month intervals for 2 years in 30 PD and 10 healthy control participants.

Results: In our illustrative example, 77 out of 235 digital features from the study passed univariate feature screening, with 11 features selected by PGEE to include in construction of the composite digital measure. Compared to MDS-UPDRS Part III, the composite digital measure exhibited a smoother and more significant increasing trend over time in PD groups with less variability, indicating improved ability for tracking disease progression. This composite digital measure also demonstrated the ability to classify between de novo PD and healthy control groups.

Conclusion: Measures from DHTs show promise in tracking neurodegenerative disease progression with increased sensitivity and reduced variability as compared to traditional clinical scores. Herein, we present a novel framework and methodology to construct composite digital measure of disease progression from high-dimensional DHT datasets, which may have utility in accelerating the development and application of composite digital biomarkers in drug development.

Smartphones and wearable sensors offer an unprecedented ability to collect peripheral psychophysiological signals across diverse timescales, settings, populations, and modalities. However, open-source software development has yet to keep pace with rapid advancements in hardware technology and availability, creating an analytical barrier that limits the scientific usefulness of acquired data. We propose a community-driven, open-source peripheral psychophysiological signal pre-processing and analysis software framework that could advance biobehavioral health by enabling more robust, transparent, and reproducible inferences involving autonomic nervous system data.

Introduction: Limb massive hemorrhage is the first cause of potentially preventable death in trauma. Its prompt and proper management is crucial to increase the survival rate. To handle a massive hemorrhage, it is important to train people without medical background, who might be the first responders in an emergency. Among the possible ways to train lay rescuers, healthcare simulation allows to practice in a safe and controlled environment. In particular, immersive technologies such as Virtual Reality (VR) and Augmented Reality (AR) give the possibility to provide real time feedback and present a realistic and engaging scenario, even though they often lack personalization.

Methods: This work aims to overcome the above-mentioned limitation, by presenting the design, development and usability test of an AR application to train non-experienced users on the use of antihemorrhagic devices. The application combines a Microsoft Hololens2 headset, with an AR application developed in Unity Game Engine. It includes a training scenario with a multimodal interactive system made of visual and audio cues, that would adapt to user's learning pace and feedback preference.

Results: Usability tests on 20 subjects demonstrated that the system is well tolerated in terms of discomfort and workload. Also, the system has been high rated for usability, user experience, immersion and sense of presence.

Discussion: These preliminary results suggest that the combination of AR with multimodal cues can be a promising tool to improve hemorrhage management training, particularly for unexperienced users. In the future, the proposed application might increase the number of people who know how to use an anti-hemorrhagic device.

Introduction: The aim of this study is to compare the injury patterns of female water polo players before and after the implementation of the Male-Assisted Female Training (MAFT) program. The study seeks to identify key factors influencing these changes and propose corresponding injury prevention measures.

Methods: We utilized pattern analysis and classification techniques to explore the injury data. A Hypergraph Neural Network (HGNN) was employed for pattern extraction, where each athlete was represented as a node in a hypergraph, with node dimensions capturing high-order relational embedding information. We applied the graph Laplacian operator to aggregate neighborhood features and visualize structural and feature differences in hypergraphs based on different influencing factors. Additionally, we introduced graph structure regularization to improve classification accuracy and prevent overfitting in the relatively small dataset, enhancing our ability to identify critical factors affecting injury types.

Results: The analysis revealed significant differences in injury patterns before and after the MAFT program, with specific influencing factors being identified through both pattern recognition and classification techniques. The classification models, supported by graph structure regularization, achieved improved accuracy in distinguishing key features that contributed to changes in injury types.

Discussion: These findings provide insights into the critical factors influencing injury patterns in female water polo players and highlight the effectiveness of the MAFT program in mitigating certain injury risks. Based on the identified features, we propose targeted preventive measures to reduce injury incidence, particularly in relation to changes brought about by the MAFT training mode. Further research is needed to refine these measures and explore their long-term effectiveness.

Introduction: The ubiquity of Bring Your Own Device (BYOD) personal smartphones, Instant Messaging (IM), and third-party apps, has made these technologies compelling for efficient communications between clinicians regarding patient care. However, the sensitivity of patient-related information necessitates secure, GDPR compliant modalities that prevent unauthorised access and ensure confidentiality. This scoping review explores existing guidelines, policies, and regulations that advise clinicians in the UK and Ireland on the secure use of these digital communication tools.

Methods: Following the Joanna Briggs Institute (JBI) updated Framework for Scoping Reviews and the PRISMA ScR guidelines, this review examines the literature to identify relevant guidelines, policies, and regulations informing current clinical practice on the use of this technology. Academic databases including OneSearch, Embase, EBSCO, PubMed, Medline, and CINAHL were searched, in addition to hand searches of professional entities' websites, including trade unions, regulators, two national health systems, and several employers. Direct inquiries were made to 69 professional entities via telephone, email, websites, and X (formerly known as Twitter).

Results: The review identified 18 papers that broadly recognise the importance of secure communication however, a lack of information on the appropriate selection or configuration of these popular technologies was evident. Most guidelines emphasise general security and data protection standards rather than providing clear actionable recommendations for technology use, thereby leaving a significant gap in technical guidance for clinicians.

Discussion: There is a distinct lack of detailed, specific, consistent technical guidance available to clinicians. This review evidences an urgent requirement for enhanced guidelines that specify the most secure platforms, appropriate features, and configuration to maximise the security and confidentiality of clinical communications. Further research is recommended to develop comprehensive, actionable advice for clinicians.

Background: The worldwide scarcity of nurses is a pressing concern, with the World Health Organization predicting a deficit of 5.9 million nurses globally by 2025. Notably, 89% of this shortage is expected to impact low- and middle-income countries. To address the growing demand for nursing professionals, the concept of telenursing care is being considered. However, there is limited evidence regarding nurses' attitudes towards telenursing care in Ethiopia. This study aims to understand how nurses feel about telenursing care and the factors related to it at a specialized teaching referral hospital in northwest Ethiopia.

Method: We conducted a cross-sectional study at a specialized teaching referral hospital, employing a simple random sampling technique to gather information from 423 nurses. The study took place from July 28 to December 19, 2022/23. Descriptive statistics, including tables and bar graphs, were utilized. Additionally, a binary logistic regression analysis was conducted with 95% confidence intervals and a significance level of P < 0.05 to identify factors influencing nurses' attitudes toward telenursing.

Result: Out of the total 416 nurses who responded, representing a response rate of 98.35%, 39.7% exhibited favorable attitudes towards telenursing care. Factors associated with nurses' attitudes included awareness, source of information, social media use, knowledge, computer access, digital training, internet access, and computer training.

Conclusions: The findings indicate a low level of positive attitudes towards telenursing care among nurses. To enhance future acceptance, use, and implementation, policymakers, higher education institutions, and other stakeholders should collaborate to improve nurses' attitudes toward telenursing care, taking into consideration various factors and user preferences.

Introduction: Knee osteoarthritis (OA) significantly impacts the quality of life of those afflicted, with many patients eventually requiring surgical intervention. While Total Knee Arthroplasty (TKA) is common, it may not be suitable for younger patients with unicompartmental OA, who might benefit more from High Tibial Osteotomy (HTO). Effective patient education is crucial for informed decision-making, yet most online health information has been found to be too complex for the average patient to understand. AI tools like ChatGPT may offer a solution, but their outputs often exceed the public's literacy level. This study assessed whether a customised ChatGPT could be utilized to improve readability and source accuracy in patient education on Knee OA and tibial osteotomy.

Methods: Commonly asked questions about HTO were gathered using Google's "People Also Asked" feature and formatted to an 8th-grade reading level. Two ChatGPT-4 models were compared: a native version and a fine-tuned model ("The Knee Guide") optimized for readability and source citation through Instruction-Based Fine-Tuning (IBFT) and Reinforcement Learning from Human Feedback (RLHF). The responses were evaluated for quality using the DISCERN criteria and readability using the Flesch Reading Ease Score (FRES) and Flesch-Kincaid Grade Level (FKGL).

Results: The native ChatGPT-4 model scored a mean DISCERN score of 38.41 (range 25-46), indicating poor quality, while "The Knee Guide" scored 45.9 (range 33-66), indicating moderate quality. Cronbach's Alpha was 0.86, indicating good interrater reliability. "The Knee Guide" achieved better readability with a mean FKGL of 8.2 (range 5-10.7, ±1.42) and a mean FRES of 60 (range 47-76, ±7.83), compared to the native model's FKGL of 13.9 (range 11-16, ±1.39) and FRES of 32 (range 14-47, ±8.3). These differences were statistically significant (p < 0.001).

Conclusions: Fine-tuning ChatGPT significantly improved the readability and quality of HTO-related information. "The Knee Guide" demonstrated the potential of customized AI tools in enhancing patient education by making complex medical information more accessible and understandable.

Background: Digital Healthcare Solutions (DHS) are transforming healthcare by improving patients' experiences, safety and quality of care. However, despite all the proposed and observed advantages of DHS, a growing body of research suggests that these DHS are not equally accessible to all. This research aimed to assess whether equity frameworks for digital health solutions can be used to guide the development of digital health solutions to increase access to care for dementia patients in the UK and, thereafter, develop practical guidelines to guide the design of equitable DHS products to address this growing issue.

Methods: A scoping review across four databases and grey literature was done to identify equity frameworks and design principles for DHS. The equity frameworks and design principles were analyzed to make recommendations on increasing equity in the product.

Results: 34 publications and reports met the inclusion criteria. Four equity frameworks were analyzed and one was selected. Equitable product development guidelines were created based on patient-centered design principles.

Conclusion: Although DHS can increase inequity in healthcare, concrete methods and practical guidelines can minimize this if DHS developers design for maximum equity and closely collaborate with healthcare providers and end-users in product development. Future research could use these guidelines to test usability for developers and investigate other equitable approaches like institutional barriers to adoption.