Frontiers in digital health最新文献

This paper will discuss the European funded iToBoS project, tasked by the European Commission to develop an AI diagnostic platform for the early detection of skin melanoma. The paper will outline the project, provide an overview of the data being processed, describe the impact assessment processes, and explain the AI privacy risk mitigation methods being deployed. Following this, the paper will offer a brief discussion of some of the more complex aspects: (1) the relatively low population clinical trial study cohort, which poses risks associated with data distinguishability and the masking ability of the applied anonymisation tools, (2) the project's ability to obtain informed consent from the study cohort given the complexity of the technologies, (3) the project's commitment to an open research data strategy and the additional privacy risk mitigations required to protect the multi-modal study data, and (4) the ability of the project to adequately explain the outputs of the algorithmic components to a broad range of stakeholders. The paper will discuss how the complexities have caused tension which are reflective of wider tensions in the health domain. A project level solution includes collaboration with a melanoma patient network, as an avenue for fair and representative qualification of risks and benefits with the patient stakeholder group. However, it is unclear how scalable this process is given the relentless pursuit of innovation within the health domain, accentuated by the continued proliferation of artificial intelligence, open data strategies, and the integration of multi-modal data sets inclusive of genomics.

Background: Amyotrophic Lateral Sclerosis (ALS) significantly impacts the lives of people with the diagnosis and their families. A supportive social environment is important for people with ALS to adopt effective coping strategies and health behaviours, and reduce depressive symptoms. Peer support can provide a supportive social environment and can happen in-person and online. Advantages of online peer support are that people can engage from their own home, at their own time and pace, and that it offers a variety of different platforms and modes of communication.

Objectives: To (1) explore the benefits and challenges of online peer support for people with ALS, and (2) identify successful elements of online peer support for people with ALS.

Methods: The method selected for this systematic review was a narrative synthesis. Six databases were systematically searched in April 2020 for articles published between 1989 and 2020. The search was updated in June 2022. The quality of the included studies was assessed with the Critical Appraisal Skills Programme qualitative research checklist.

Results: 10,987 unique articles were identified through the systematic database search. Of those, 9 were included in this review. One of the main benefits of online peer support was that people could communicate using text rather than needing verbal communication, which can be challenging for some with ALS. Successful elements included using profile pages and graphics to identify others with similar or relevant experiences. Challenges included ALS symptoms which could make it difficult to use technological devices.

Conclusions: Peer support can provide a non-judgmental and supportive environment for people with ALS, in which they can exchange experiences and emotional support, which can help people in developing adaptive coping strategies. However, ALS symptoms may make it more difficult for people to use technological devices and engage in online peer support. More research is needed to identify what kind of specific barriers people with ALS experience, and how these could be overcome.

Background: Mobile e-health technologies have proven to provide tailored assessment, intervention, and coaching capabilities for various usage scenarios. Thanks to their spread and adoption, smartphones are one of the most important carriers for such applications.

Problem: However, the process of design, realization, evaluation, and implementation of these e-health solutions is wicked and challenging, requiring multiple stakeholders and expertise.

Method: Here, we present a tailorable intervention and interaction e-health solution that allows rapid prototyping, development, and evaluation of e-health interventions at scale. This platform allows researchers and clinicians to develop ecological momentary assessment, just-in-time adaptive interventions, ecological momentary intervention, cohort studies, and e-coaching and personalized interventions quickly, with no-code, and in a scalable way.

Result: The Twente Intervention and Interaction Instrument (TIIM) has been used by over 320 researchers in the last decade. We present the ecosystem and synthesize the main scientific output from clinical and research studies in different fields.

Discussion: The importance of mobile e-coaching for prediction, management, and prevention of adverse health outcomes is increasing. A profound e-health development strategyand strategic, technical, and operational investments are needed to prototype, develop, implement, and evaluate e-health solutions. TIIM ecosystem has proven to support these processes. This paper ends with the main research opportunities in mobile coaching, including intervention mechanisms, fine-grained monitoring, and inclusion of objective biomarker data.

Background: With the continuous advancement of digital technologies, electronic Personal Health Records (ePHR) offer end-users greater control and convenience over their health data. Although ePHR are perceived as innovative tools in medical services that provide patient-centered care and disease prevention, many system interfaces are inclined toward younger users, overlooking investigations pertinent to elderly users. Our objective is to uncover the preferences of the elderly for an ideal ePHR system interface.

Materials and methods: Relying on a literature review, we identified six interface attributes. Utilizing conjoint analysis, we constructed 16 representative design scenarios based on orthogonal design by combining different attribute levels. We invited 187 elderly participants to evaluate these scenarios. Data analysis was performed using SPSS 26.0. The results indicate that among the ePHR interface design attributes, the elderly prioritize color attributes, followed by the notification method. Designs with contrasting color schemes, skeuomorphic design approaches, and icon-centric menu navigation with segmented layouts, and voice notifications when a message is received, are the most preferred interface design choices.

Discussion: This research elucidates the ideal interface design elements for ePHR as perceived by the elderly, offering valuable references for age-friendly design considerations in ePHR systems.

Results: Implementing these insights can aid in promoting mobile health services among the elderly demographic, enhancing their user experience in health management interfaces. This, in turn, fosters the widespread adoption of mobile health service technologies, further advancing the development of a healthy aging society.

Digital Therapeutics (DTx) are experiencing rapid advancements within mobile and mental healthcare sectors, with their ubiquity and enhanced accessibility setting them apart as uniquely effective solutions. In this evolving context, our research focuses on deep breathing, a vital technique in mental health management, aiming to optimize its application in DTx mobile platforms. Based on well-founded theories, we introduced a gamified and affordance-driven design, facilitating intuitive breath control. To enhance user engagement, we deployed the Mel Frequency Cepstral Coefficient (MFCC)-driven personalized machine learning method for accurate biofeedback visualization. To assess our design, we enlisted 70 participants, segregating them into a control and an intervention group. We evaluated Heart Rate Variability (HRV) metrics and collated user experience feedback. A key finding of our research is the stabilization of the Standard Deviation of the NN Interval (SDNN) within Heart Rate Variability (HRV), which is critical for stress reduction and overall health improvement. Our intervention group observed a pronounced stabilization in SDNN, indicating significant stress alleviation compared to the control group. This finding underscores the practical impact of our DTx solution in managing stress and promoting mental health. Furthermore, in the assessment of our intervention cohort, we observed a significant increase in perceived enjoyment, with a notable 22% higher score and 10.69% increase in positive attitudes toward the application compared to the control group. These metrics underscore our DTx solution's effectiveness in improving user engagement and fostering a positive disposition toward digital therapeutic efficacy. Although current technology poses challenges in seamlessly incorporating machine learning into mobile platforms, our model demonstrated superior effectiveness and user experience compared to existing solutions. We believe this result demonstrates the potential of our user-centric machine learning techniques, such as gamified and affordance-based approaches with MFCC, which could contribute significantly to the field of mobile mental healthcare.

Introduction: Population health data integration remains a critical challenge in low- and middle-income countries (LMIC), hindering the generation of actionable insights to inform policy and decision-making. This paper proposes a pan-African, Findable, Accessible, Interoperable, and Reusable (FAIR) research architecture and infrastructure named the INSPIRE datahub. This cloud-based Platform-as-a-Service (PaaS) and on-premises setup aims to enhance the discovery, integration, and analysis of clinical, population-based surveys, and other health data sources.

Methods: The INSPIRE datahub, part of the Implementation Network for Sharing Population Information from Research Entities (INSPIRE), employs the Observational Health Data Sciences and Informatics (OHDSI) open-source stack of tools and the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) to harmonise data from African longitudinal population studies. Operating on Microsoft Azure and Amazon Web Services cloud platforms, and on on-premises servers, the architecture offers adaptability and scalability for other cloud providers and technology infrastructure. The OHDSI-based tools enable a comprehensive suite of services for data pipeline development, profiling, mapping, extraction, transformation, loading, documentation, anonymization, and analysis.

Results: The INSPIRE datahub's "On-ramp" services facilitate the integration of data and metadata from diverse sources into the OMOP CDM. The datahub supports the implementation of OMOP CDM across data producers, harmonizing source data semantically with standard vocabularies and structurally conforming to OMOP table structures. Leveraging OHDSI tools, the datahub performs quality assessment and analysis of the transformed data. It ensures FAIR data by establishing metadata flows, capturing provenance throughout the ETL processes, and providing accessible metadata for potential users. The ETL provenance is documented in a machine- and human-readable Implementation Guide (IG), enhancing transparency and usability.

Conclusion: The pan-African INSPIRE datahub presents a scalable and systematic solution for integrating health data in LMICs. By adhering to FAIR principles and leveraging established standards like OMOP CDM, this architecture addresses the current gap in generating evidence to support policy and decision-making for improving the well-being of LMIC populations. The federated research network provisions allow data producers to maintain control over their data, fostering collaboration while respecting data privacy and security concerns. A use-case demonstrated the pipeline using OHDSI and other open-source tools.

Introduction: Digital tools, such as mobile apps and the Internet, are being increasingly used to promote healthy eating habits. However, there has been inconsistent reporting on the effectiveness of smartphones and web-based apps in influencing dietary behaviors. Moreover, previous reviews have been limited in scope, either by focusing on a specific population group or by being outdated. Therefore, the purpose of this review is to investigate the impacts of smartphone- and web-based dietary interventions on promoting healthy eating behaviors worldwide.

Methods: A systematic literature search of randomized controlled trials was conducted using databases such as Google Scholar, PubMed, Global Health, Informit, Web of Science, and CINAHL (EBSCO). The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed to prepare the entire document. EndNote (version 20) was used for reference management. The risk of bias in the articles was assessed using the "Revised Cochrane Risk of Bias tool for randomized trials (RoB 2.0)" by the Cochrane Collaboration. Narrative synthesis, using text and tables, was used to present the results. The study was registered in PROSPERO under protocol number CRD42023464315.

Results: This review analyzed a total of 39 articles, which consisted of 25 smartphone-based apps and 14 web-based apps. The studies involved a total of 14,966 participants. Out of the 25 studies, 13 (52%) showed that offline-capable smartphone apps are successful in promoting healthier eating habits. The impact of smartphone apps on healthy adults has been inconsistently reported. However, studies have shown their effectiveness in chronically ill patients. Likewise, internet-based mobile apps, such as social media or nutrition-specific apps, have been found to effectively promote healthy eating behaviors. These findings were consistent across 14 studies, which included healthy adults, overweight or obese adults, chronically ill patients, and pregnant mothers.

Conclusion: Overall, the findings suggest that smartphone apps contribute to improving healthy eating behaviors. Both nutrition-specific and social media-based mobile apps consistently prove effective in promoting long-term healthy eating habits. Therefore, policymakers in the food system should consider harnessing the potential of internet-based mobile apps and social media platforms to foster sustainable healthy eating behaviors.