Frontiers in digital health最新文献

{"title":"Innovative mobile app solution for facial nerve rehabilitation: a usability analysis.","authors":"Kathrin Machetanz, Mario Lins, Constantin Roder, Georgios Naros, Marcos Tatagiba, Helene Hurth","doi":"10.3389/fdgth.2024.1471426","DOIUrl":"10.3389/fdgth.2024.1471426","url":null,"abstract":"<p><strong>Background: </strong>Facial palsy after vestibular schwannoma surgery is temporary in many cases but can significantly affect patients' quality of life. Physical training-initially guided and subsequently performed by the patient-is of paramount importance for recovery of facial nerve function. The introduction of medical application software (apps) might improve therapy by maintaining motivation for daily home-based training and surveilling patients' rehabilitation progress.</p><p><strong>Methods: </strong>We developed a mobile app, \"FACEsemper\", for home-based facial nerve rehabilitation. This app guides patients through a daily training program comprising six variable exercises, each performed in three repetitions. The app allows the user to customize the exercise intensity for different facial areas and includes a reminder function for daily training. Additional features include photo documentation, a calendar function, training report generation, and the possibility of direct communication with the attending physician. The app's usability was prospectively investigated with 27 subjects, including 8 physicians, 9 patients with facial palsy and 10 healthy subjects, over a two-week period. Usability was assessed using various self-rating questionnaires (i.e., mHealth App Usability Questionnaire, MAUQ; System Usability Scale, SUS; Visual Aesthetics of Apps Inventory, VisAAI) and scores were compared across the groups.</p><p><strong>Results: </strong>The participants reported an average smartphone use of 12.19 years and completed a mean number of 290 ± 163 facial exercises during the study period. Patients used the app significantly more frequently than the other two groups (<i>p</i> = 0.017). The average total scores of the questionnaires were: MAUQ 5.67/7, SUS 89.6/100, VisAAI 5.88/7 and specific rating 6.13/7. In particular, the simplicity of use and craftsmanship of the app were rated very highly. Usability scores did not significantly differ between groups. A primary limitation identified was malfunction of the daily reminder feature in some Android versions.</p><p><strong>Conclusion: </strong>This usability study demonstrated a positive user experience and excellent usability of the FACEsemper app. However, some limitations and areas for improvement were identified. As a next step, the app should be evaluated in a large patient cohort with facial palsy to determine its potential medical benefits for facial rehabilitation compared to traditional training methods.</p>","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11532141/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142577394","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Statistical refinement of patient-centered case vignettes for digital health research.","authors":"Marvin Kopka, Markus A Feufel","doi":"10.3389/fdgth.2024.1411924","DOIUrl":"10.3389/fdgth.2024.1411924","url":null,"abstract":"<p><p>Digital health research often relies on case vignettes (descriptions of fictitious or real patients) to navigate ethical and practical challenges. Despite their utility, the quality and lack of standardization of these vignettes has often been criticized, especially in studies on symptom-assessment applications (SAAs) and self-triage decision-making. To address this, our paper introduces a method to refine an existing set of vignettes, drawing on principles from classical test theory. First, we removed any vignette with an item difficulty of zero and an item-total correlation below zero. Second, we stratified the remaining vignettes to reflect the natural base rates of symptoms that SAAs are typically approached with, selecting those vignettes with the highest item-total correlation in each quota. Although this two-step procedure reduced the size of the original vignette set by 40%, comparing self-triage performance on the reduced and the original vignette sets, we found a strong correlation (<i>r</i> = 0.747 to <i>r</i> = 0.997, <i>p</i> < .001). This indicates that using our refinement method helps identifying vignettes with high predictive power of an agent's self-triage performance while simultaneously increasing cost-efficiency of vignette-based evaluation studies. This might ultimately lead to higher research quality and more reliable results.</p>","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11532084/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142577396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unleashing the potential of eHealth in outpatient cancer care for patients undergoing immunotherapy-a quantitative study considering patients' needs and current healthcare challenges.","authors":"Tobias A W Holderried, Isabel Stasik, Marie-Therese Schmitz, Friederike Schmitz, Tizian K Meyer, Leonie Stauß, Martin Kirschner, Dirk Skowasch, Jennifer Landsberg, Matthias Schmid, Peter Brossart, Martin Holderried","doi":"10.3389/fdgth.2024.1414442","DOIUrl":"10.3389/fdgth.2024.1414442","url":null,"abstract":"<p><strong>Background: </strong>The use of online information and communication is globally increasing in the healthcare sector. In addition to known benefits in other medical fields, possible specific potentials of eHealth lie in the monitoring of oncological patients undergoing outpatient therapy. Specifically, the treatment with immune checkpoint inhibitors (ICI) requires intensive monitoring due to various possible negative side effects. The present study explores cancer patients' perspectives on eHealth and demonstrates how eHealth applications, from the patients' point of view, can contribute to further improving outpatient immunotherapy.</p><p><strong>Methods and findings: </strong>Our multicenter study was executed at the university hospitals in Bonn and Aachen. A structured questionnaire was distributed to patients receiving outpatient immunotherapy. Contents addressed were (1) the patients' attitude towards eHealth applications, (2) the use of modern information and communications technologies (ICT) in (2a) everyday life and (2b) health-related information search including eHealth literacy, (3) the use of internet-enabled devices as well as (4) socio-demographic data. 164 patients were included in the study, of whom 39.0% were female and 61.0% male and the average age was 62.8 years. Overall, there was a high distribution of internet-enabled devices for everyday use and a great interest in integrating eHealth applications into outpatient immunotherapy. The assessment of eHealth potentials significantly depended on age. The younger participants demonstrated a broader use of modern ICT and a higher affinity for its use in outpatient immunotherapy. In some aspects, level of education and gender were also relevant factors influencing the patients' view on eHealth.</p><p><strong>Conclusion: </strong>This study demonstrates the potential for further integration of eHealth applications into outpatient immunotherapy from the patients' perspective. It indicates a dependency on age and educational level for the further integration of eHealth into patient care in oncology. Due to particular patient needs regarding age, level of education, gender and other subgroups, specific education and training as well as target-group specific digital health interventions are necessary to fully utilize the potentials of eHealth for outpatient immunotherapy. Future studies are required to specifically address target-group specific usability of eHealth applications and eHealth literacy, as well as to address information security and data protection.</p>","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11532137/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142577399","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Biofuser: a multi-source data fusion platform for fusing the data of fermentation process devices.","authors":"Dequan Zhang, Wei Jiang, Jincheng Lou, Xuanzhou Han, Jianye Xia","doi":"10.3389/fdgth.2024.1390622","DOIUrl":"10.3389/fdgth.2024.1390622","url":null,"abstract":"<p><p>In the past decade, the progress of traditional bioprocess optimization technique has lagged far behind the rapid development of synthetic biology, which has hindered the industrialization process of synthetic biology achievements. Recently, more and more advanced equipment and sensors have been applied for bioprocess online inspection to improve the understanding and optimization efficiency of the process. This has resulted in large amounts of process data from various sources with different communication protocols and data formats, requiring the development of techniques for integration and fusion of these heterogeneous data. Here we describe a multi-source fusion platform (Biofuser) that is designed to collect and process multi-source heterogeneous data. Biofuser integrates various data to a unique format that facilitates data visualization, further analysis, model construction, and automatic process control. Moreover, Biofuser also provides additional APIs that support machine learning or deep learning using the integrated data. We illustrate the application of Biofuser with a case study on riboflavin fermentation process development, demonstrating its ability in device faulty identification, critical process factor identification, and bioprocess prediction. Biofuser has the potential to significantly enhance the development of fermentation optimization techniques and is expected to become an important infrastructure for artificial intelligent integration into bioprocess optimization, thereby promoting the development of intelligent biomanufacturing.</p>","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11532143/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142577387","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Accessing medical care in the era of the digital revolution: arguing the case for the \"<i>digitally marginalised</i>\".","authors":"Anoop C Choolayil, Sadhishkumar Paranthaman, Vijesh Sreedhar Kuttiatt","doi":"10.3389/fdgth.2024.1468633","DOIUrl":"10.3389/fdgth.2024.1468633","url":null,"abstract":"<p><p>This article explores the intersection of healthcare accessibility and digitalisation from a rights perspective. Drawing from two illustrative cases presented to a filariasis management clinic in Puducherry, where the authors are affiliated, the article argues that despite the multiple benefits that digital health poses, there are individuals and sections of society that experience marginalisation in healthcare owing to digitalisation. Collating the data generated through the observations of the authors and the narratives of the patients, the article illustrates that such marginalisation can originate even from a relatively simple ICT adaptation like text message-based appointments, inducing health inequities. The impact of such digital marginalisation disproportionately affects vulnerable sections like older adults and the rural population in an intersectional pattern where disadvantages compound to produce larger health inequities for the affected. The study advocates for bridging the digital divide through efforts including digital literacy-when possible-and alternative solutions like dedicated helpdesks, training healthcare staff and involving NGOs and voluntary organisations to ensure health equity for the digitally marginalised.</p>","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11532061/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142577385","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cost-effectiveness of digital interventions for mental health: current evidence, common misconceptions, and future directions.","authors":"Claudia Buntrock","doi":"10.3389/fdgth.2024.1486728","DOIUrl":"10.3389/fdgth.2024.1486728","url":null,"abstract":"","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11532097/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142577390","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AI-enabled workflow for automated classification and analysis of feto-placental Doppler images.","authors":"Ainhoa M Aguado, Guillermo Jimenez-Perez, Devyani Chowdhury, Josa Prats-Valero, Sergio Sánchez-Martínez, Zahra Hoodbhoy, Shazia Mohsin, Roberta Castellani, Lea Testa, Fàtima Crispi, Bart Bijnens, Babar Hasan, Gabriel Bernardino","doi":"10.3389/fdgth.2024.1455767","DOIUrl":"10.3389/fdgth.2024.1455767","url":null,"abstract":"<p><strong>Introduction: </strong>Extraction of Doppler-based measurements from feto-placental Doppler images is crucial in identifying vulnerable new-borns prenatally. However, this process is time-consuming, operator dependent, and prone to errors.</p><p><strong>Methods: </strong>To address this, our study introduces an artificial intelligence (AI) enabled workflow for automating feto-placental Doppler measurements from four sites (i.e., Umbilical Artery (UA), Middle Cerebral Artery (MCA), Aortic Isthmus (AoI) and Left Ventricular Inflow and Outflow (LVIO)), involving classification and waveform delineation tasks. Derived from data from a low- and middle-income country, our approach's versatility was tested and validated using a dataset from a high-income country, showcasing its potential for standardized and accurate analysis across varied healthcare settings.</p><p><strong>Results: </strong>The classification of Doppler views was approached through three distinct blocks: (i) a Doppler velocity amplitude-based model with an accuracy of 94%, (ii) two Convolutional Neural Networks (CNN) with accuracies of 89.2% and 67.3%, and (iii) Doppler view- and dataset-dependent confidence models to detect misclassifications with an accuracy higher than 85%. The extraction of Doppler indices utilized Doppler-view dependent CNNs coupled with post-processing techniques. Results yielded a mean absolute percentage error of 6.1 ± 4.9% (<i>n</i> = 682), 1.8 ± 1.5% (<i>n</i> = 1,480), 4.7 ± 4.0% (<i>n</i> = 717), 3.5 ± 3.1% (<i>n</i> = 1,318) for the magnitude location of the systolic peak in LVIO, UA, AoI and MCA views, respectively.</p><p><strong>Conclusions: </strong>The developed models proved to be highly accurate in classifying Doppler views and extracting essential measurements from Doppler images. The integration of this AI-enabled workflow holds significant promise in reducing the manual workload and enhancing the efficiency of feto-placental Doppler image analysis, even for non-trained readers.</p>","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11521966/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142549254","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing health technology implementation during academic research and early-stage development: support tools for awareness and guidance: a review.","authors":"Meyke Roosink, Lisette van Gemert-Pijnen, Ruud Verdaasdonk, Saskia M Kelders","doi":"10.3389/fdgth.2024.1386998","DOIUrl":"10.3389/fdgth.2024.1386998","url":null,"abstract":"<p><p>For successful health technology innovation and implementation it is key to, in an early phase, understand the problem and whether a proposed innovation is the best way to solve the problem. This review performed an initial exploration of published tools that support innovators in academic research and early stage development with awareness and guidance along the end-to-end process of development, evaluation and implementation of health technology innovations. Tools were identified from scientific literature as well as in grey literature by non-systematic searches in public research databases and search engines, and based on expert referral. A total number of 14 tools were included. Tools were classified as either readiness level tool (<i>n</i> = 6), questionnaire/checklist tool (<i>n</i> = 5) or guidance tool (<i>n</i> = 3). A qualitative analysis of the tools identified 5 key domains, 5 innovation phases and 3 implementation principles. All tools were mapped for (partially) addressing the identified domains, phases, and principles. The present review provides awareness of available tools and of important aspects of health technology innovation and implementation (vs. non-technological or non-health related technological innovations). Considerations for tool selection include for example the purpose of use (awareness or guidance) and the type of health technology innovation. Considerations for novel tool development include the specific challenges in academic and early stage development settings, the translation of implementation to early innovation phases, and the importance of multi-disciplinary strategic decision-making. A remaining attention point for future studies is the validation and effectiveness of (self-assessment) tools, especially in the context of support preferences and available support alternatives.</p>","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11513387/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142523773","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impacts on study design when implementing digital measures in Parkinson's disease-modifying therapy trials.","authors":"Jennie S Lavine, Anthony D Scotina, Seth Haney, Jessie P Bakker, Elena S Izmailova, Larsson Omberg","doi":"10.3389/fdgth.2024.1430994","DOIUrl":"https://doi.org/10.3389/fdgth.2024.1430994","url":null,"abstract":"<p><strong>Introduction: </strong>Parkinson's Disease affects over 8.5 million people and there are currently no medications approved to treat underlying disease. Clinical trials for disease modifying therapies (DMT) are hampered by a lack of sufficiently sensitive measures to detect treatment effect. Reliable digital assessments of motor function allow for frequent at-home measurements that may be able to sensitively detect disease progression.</p><p><strong>Methods: </strong>Here, we estimate the test-retest reliability of a suite of at-home motor measures derived from raw triaxial accelerometry data collected from 44 participants (21 with confirmed PD) and use the estimates to simulate digital measures in DMT trials. We consider three schedules of assessments and fit linear mixed models to the simulated data to determine whether a treatment effect can be detected.</p><p><strong>Results: </strong>We find at-home measures vary in reliability; many have ICCs as high as or higher than MDS-UPDRS part III total score. Compared with quarterly in-clinic assessments, frequent at-home measures reduce the sample size needed to detect a 30% reduction in disease progression from over 300 per study arm to 150 or less than 100 for bursts and evenly spaced at-home assessments, respectively. The results regarding superiority of at-home assessments for detecting change over time are robust to relaxing assumptions regarding the responsiveness to disease progression and variability in progression rates.</p><p><strong>Discussion: </strong>Overall, at-home measures have a favorable reliability profile for sensitive detection of treatment effects in DMT trials. Future work is needed to better understand the causes of variability in PD progression and identify the most appropriate statistical methods for effect detection.</p>","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11496294/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142514121","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Digital assessments for children and adolescents with ADHD: a scoping review.","authors":"Franceli L Cibrian, Elissa M Monteiro, Kimbelery D Lakes","doi":"10.3389/fdgth.2024.1440701","DOIUrl":"https://doi.org/10.3389/fdgth.2024.1440701","url":null,"abstract":"<p><strong>Introduction: </strong>In spite of rapid advances in evidence-based treatments for attention deficit hyperactivity disorder (ADHD), community access to rigorous gold-standard diagnostic assessments has lagged far behind due to barriers such as the costs and limited availability of comprehensive diagnostic evaluations. Digital assessment of attention and behavior has the potential to lead to scalable approaches that could be used to screen large numbers of children and/or increase access to high-quality, scalable diagnostic evaluations, especially if designed using user-centered participatory and ability-based frameworks. Current research on assessment has begun to take a user-centered approach by actively involving participants to ensure the development of assessments that meet the needs of users (e.g., clinicians, teachers, patients).</p><p><strong>Methods: </strong>The objective of this mapping review was to identify and categorize digital mental health assessments designed to aid in the initial diagnosis of ADHD as well as ongoing monitoring of symptoms following diagnosis.</p><p><strong>Results: </strong>Results suggested that the assessment tools currently described in the literature target both cognition and motor behaviors. These assessments were conducted using a variety of technological platforms, including telemedicine, wearables/sensors, the web, virtual reality, serious games, robots, and computer applications/software.</p><p><strong>Discussion: </strong>Although it is evident that there is growing interest in the design of digital assessment tools, research involving tools with the potential for widespread deployment is still in the early stages of development. As these and other tools are developed and evaluated, it is critical that researchers engage patients and key stakeholders early in the design process.</p>","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11493775/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142514120","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}