DIGITAL HEALTH最新文献

Objective: Digital approaches have the potential to make activity promotion attractive and age-appropriate for children and adolescents. KIJANI is a mobile application aiming to increase physical activity (PA) in youth via gamification and augmented reality. This study investigates the user experience with KIJANI through a multimethod approach.

Approaches: KIJANI is based on the concept that virtual coins can be earned through PA, for example, in the form of collected step counts. With these coins, blocks can be bought, which can be used to create virtual buildings and landscapes and integrate these into the player's real-world environment via augmented reality. To evaluate the user experience, participants played KIJANI in groups of three for 25 min. Afterwards KIJANI was evaluated qualitatively with one-on-one semi-structured interviews as well as quantitatively with standardized questionnaires.

Results: Overall, 22 participants (12.6 ± 1.7 years, 6 girls) were included in the study. The overall game concept and realization were well received by the target group. Study participants did have various and creative ideas for the further development of KIJANI. The majority (n = 16) thought that using KIJANI would increase their PA level. User experience based on the UEQ scale was (mean ± SD): attractiveness (1.78 ± 1.82), perspicuity (2.15 ± 0.680), efficiency (0.67 ± 1.25), dependability, (1.21 ± 0.93), stimulation (1.24 ± 1.78), and novelty (1.27 ± 1.34).

Conclusion: With these insights, a further step has been taken in the participatory development of KIJANI. Apps like KIJANI appear to be suitable for PA promotion in children and adolescents.

Objective: Acute kidney injury (AKI) is easily missed and underdiagnosed in routine clinical care. Timely AKI management is important to decrease morbidity and mortality risks. We recently implemented an AKI e-alert at the University Medical Center Utrecht, comparing plasma creatinine concentrations with historical creatinine baselines, thereby identifying patients with AKI. This alert is limited to data from tertiary care, and primary care data can increase diagnostic accuracy for AKI. We assessed the added value of linking primary care data to tertiary care data, in terms of timely diagnosis or excluding AKI.

Methods: With plasma creatinine tests for 84,984 emergency department (ED) visits, we applied the Kidney Disease Improving Global Outcome guidelines in both tertiary care-only data and linked data and compared AKI cases.

Results: Using linked data, the presence of AKI could be evaluated in an additional 7886 ED visits. Sex- and age-stratified analyses identified the largest added value for women (an increase of 4095 possible diagnoses) and patients ≥60 years (an increase of 5190 possible diagnoses). We observed 398 additional visits where AKI was diagnosed, as well as 185 cases where AKI could be excluded. We observed no overall decrease in time between baseline and AKI diagnosis (28.4 days vs. 28.0 days). For cases where AKI was diagnosed in both data sets, we observed a decrease of 2.8 days after linkage, indicating a timelier diagnosis of AKI.

Conclusions: Combining primary and tertiary care data improves AKI diagnostic accuracy in routine clinical care and enables timelier AKI diagnosis.

Objectives: More and more disasters are occurring and there will be an increasing shortage of physicians in the future. Telemedicine could be a solution here to offer medical care despite the lack of physicians in the area of operation. This study analyzes whether telemedicine for lower-qualified paramedics is comparable to conventional disaster medicine.

Methods: A simulation study was conducted in which one conventional and two telemedicine groups cared for thermal-traumatically injured in a stressful situation. The telemedicine was conducted on tablets with integrated vital sign monitoring or on smartphones. The physician engagement time, the number of physician contacts, the time for relevant measures and the usage behavior of telemedicine were examined between these groups.

Results: One telemedicine group showed significantly fewer patient contacts. This can be attributed to the ongoing consultation in the intervention group with more contacts. There are no significant differences in the relevant measures.

Conclusion: Telemedicine is comparable to conventional disaster medicine in civil protection. Due to potential technical failures, it should primarily be used to compensate for the lack of physicians, and training should focus on an exit-strategy in case of a failure of the telemedicine.

Background: NLP models like ChatGPT promise to revolutionize text-based content delivery, particularly in medicine. Yet, doubts remain about ChatGPT's ability to reliably support evaluations of cognitive performance, warranting further investigation into its accuracy and comprehensiveness in this area.

Method: A cohort of 60 cognitively normal individuals and 30 stroke survivors underwent a comprehensive evaluation, covering memory, numerical processing, verbal fluency, and abstract thinking. Healthcare professionals and NLP models GPT-3.5 and GPT-4 conducted evaluations following established standards. Scores were compared, and efforts were made to refine scoring protocols and interaction methods to enhance ChatGPT's potential in these evaluations.

Result: Within the cohort of healthy participants, the utilization of GPT-3.5 revealed significant disparities in memory evaluation compared to both physician-led assessments and those conducted utilizing GPT-4 (P < 0.001). Furthermore, within the domain of memory evaluation, GPT-3.5 exhibited discrepancies in 8 out of 21 specific measures when compared to assessments conducted by physicians (P < 0.05). Additionally, GPT-3.5 demonstrated statistically significant deviations from physician assessments in speech evaluation (P = 0.009). Among participants with a history of stroke, GPT-3.5 exhibited differences solely in verbal assessment compared to physician-led evaluations (P = 0.002). Notably, through the implementation of optimized scoring methodologies and refinement of interaction protocols, partial mitigation of these disparities was achieved.

Conclusion: ChatGPT can produce evaluation outcomes comparable to traditional methods. Despite differences from physician evaluations, refinement of scoring algorithms and interaction protocols has improved alignment. ChatGPT performs well even in populations with specific conditions like stroke, suggesting its versatility. GPT-4 yields results closer to physician ratings, indicating potential for further enhancement. These findings highlight ChatGPT's importance as a supplementary tool, offering new avenues for information gathering in medical fields and guiding its ongoing development and application.

Objective: Connected health services will change the scope of health professionals' roles. It is unclear how parents of a child with inflammatory bowel disease perceive the role of health professionals in relation to these services and what their experiences and needs are. The purpose of this study is to highlight parents' experiences with this role. Furthermore, it aims to outline the fundamental needs that parents have regarding this role, in order to promote audience-specific access to these services and derive overarching action measures.

Methods: Fourteen parents of children with inflammatory bowel disease from seven different clinics in Switzerland were recruited. Between August 2022 and February 2023, these parents were interviewed in semi-structured interviews. The interviews were analyzed using a structured qualitative content analysis.

Results: Five main categories were identified, with few parents having prior experience with the role of health professionals in this area. Parents saw health professionals in the role of gatekeepers, transferers of knowledge and in a supporting function for these services. From the parents' perspective, health professionals should recognize the limitations of these services and use them as a complement to standard treatment.

Conclusion: The role of health professionals in relation to connected health services needs to be adapted from the parents' perspective. To meet the needs of parents, health professionals must have access to these services. In addition to health professionals' personal engagement with these services, institutional and policy changes, as well as research on role development from the perspective of other stakeholders are needed.

In the post-COVID-19 era, telehealth experience and knowledge must be structured to deliver high-quality care. Type 1 diabetes is a chronic disease that lends itself to being a model for telehealth diffusion, especially in the pediatric setting where the use of cloud-connected technologies is widespread. Here, we present "how to set the tone" and manage a telemedicine session according to our experiences and those reported in the literature, according to the health professional perspective. A practical workflow on how healthcare professionals can structure a virtual diabetes clinic is reported, as well as critical issues related to limits in physical examination, communication registers, relationships, and visit settings. A proactive virtual visit model could be feasible, stratifying patients according to continuous glucose monitoring metrics, and personalized interventions can be provided to each patient. Analysis of benefits and hassles due to telehealth for each patient has to be considered, as well as their personal perspective, expectations, and reported barriers, mainly related to connection issues and digital literacy.

Objective: Diabetes patients can draw on an increasing number of eHealth apps to support them in the self-management of their disease. While studies so far have focused on patients with type 1 diabetes, we explored how patients with type 2 diabetes mellitus (T2DM) integrate eHealth apps into their practices aimed at managing and coping with the disease, which aspects were considered particularly valuable and which challenges users encountered.

Methods: Semi-structured interviews and focus group sessions were conducted to explore how patients cope with T2DM in their daily lives and their attitude towards eHealth. In a further step, four eHealth apps were tested by patients and their expectations and experiences studied by way of qualitative interviews and focus groups.

Results: The analysis showed that the study participants valued in particular the possibility to use eHealth apps to sense and gain a better understanding of their own body, to learn about specific responses of their body to nutrition and physical activity, and to support changes in daily routines and lifestyle. Key challenges encountered related to difficulties in interpreting the data, matching the data to other bodily sensations, getting overly occupied with the disease and difficulties in integrating the apps into personal, family, and care practices.

Conclusion: Under certain conditions, eHealth can play an important role for patients in developing a nuanced, personal understanding of their body and coping with T2DM. A prerequisite is that eHealth needs to be fitted into the specific practices of users, and patients desire a strong role by their care professionals in providing support in interpretation of data.

Objective: Tuberculosis (TB) remains a significant global infectious disease, posing a considerable health threat, particularly in resource-constrained regions. Due to diverse datasets, radiologists face challenges in accurately diagnosing TB using X-ray images. This study aims to propose an innovative approach leveraging image processing techniques to enhance TB diagnostic accuracy within the automatic segmentation and classification (AuSC) framework for healthcare.

Methods: The AuSC of detection of TB (AuSC-DTB) framework comprises several steps: image preprocessing involving resizing and median filtering, segmentation using the random walker algorithm, and feature extraction utilizing local binary pattern and histogram of gradient descriptors. The extracted features are then classified using the support vector machine classifier to distinguish between healthy and infected chest X-ray images. The effectiveness of the proposed technique was evaluated using four distinct datasets, such as Japanese Society of Radiological Technology (JSRT), Montgomery, National Library of Medicine (NLM), and Shenzhen.

Results: Experimental results demonstrate promising outcomes, with accuracy rates of 94%, 95%, 95%, and 93% achieved for JSRT, Montgomery, NLM, and Shenzhen datasets, respectively. Comparative analysis against recent studies indicates superior performance of the proposed hybrid approach.

Conclusions: The presented hybrid approach within the AuSC framework showcases improved diagnostic accuracy for TB detection from diverse X-ray image datasets. Furthermore, this methodology holds promise for generalizing other diseases diagnosed through X-ray imaging. It can be adapted with computed tomography scans and magnetic resonance imaging images, extending its applicability in healthcare diagnostics.

Background: Interactive telemedicine applications have been progressively introduced in the assessment of cognitive and literacy skills. However, there is still a lack of research focusing on the validity of this methodology for the neuropsychological assessment of children with Specific Learning Disorder (SLD).

Methods: Seventy-nine children including 40 typically developing children (18 males, age 11.5 ± 1.06) and 39 children with SLD (24 males, age 12.3 ± 1.28) were recruited. Each participant underwent the same neuropsychological battery assessing reading accuracy, speed, and comprehension, writing, numerical processing, computation, and semantic numerical sense, twice (once during an in-person session (I) and once during a remote (R) home-based videoconference session). Four groups were subsequently defined based on the administration order. Repeated-measure-ANOVAs with assessment type (R vs. I testing) as within-subject factor and diagnosis (SLD vs. TR) and administration order (R-I vs. I-R) as between-subject factors, and between-group t-tests comparing the two assessment types within each time of administration, were run.

Results: No differences emerged between I and R assessments of reading accuracy and speed, numerical processing, and computation; on the contrary, potential biases against R assessment emerged when evaluating skills in writing, reading comprehension, and semantic numerical sense. However, regardless of the assessment type, the scores obtained with I and R assessments within the same administration time point overlapped.

Discussion: These results partially support the validity and reliability of the assessment of children's learning skills via a remote home-based videoconferencing system. Implementing telemedicine as an assessment tool may increase timely access to primary health care and to support research activity.

Background: Musculoskeletal (MSK) disorders, affecting billions of people worldwide, pose significant challenges to the healthcare system and require effective management models. The rapid development of digital healthcare technologies (DHTs) has revolutionized the healthcare industry. DHT-based interventions have shown promising clinical benefits in managing MSK disorders, alleviating pain, and improving functional impairment. There is, however, no bibliometric analysis of the overall trends on this topic.

Methods: We extracted all relevant publications from the Web of Science Core Collection (WoSCC) database until April 30, 2023. We performed bibliometric analysis and visualization using CiteSpace, VOSviewer, and R software. Annual trends of publications, countries/regions distributions, funding agencies, institutions, co-cited journals, author contributions, references, core journals, and keywords and research hotspots were analyzed.

Results: A total of 6810 papers were enrolled in this study. Publications have increased drastically from 16 in 1995 to 1198 in 2022, with 4067 articles published in the last five years. In all, 53 countries contributed with publications to this research area. The United States, the United Kingdom, and China were the most productive countries. Harvard University was the most contributing institution. Regarding keywords, research focuses include artificial intelligence, deep learning, machine learning, telemedicine, rehabilitation, and robotics.

Conclusion: The COVID-19 pandemic has further accelerated the adoption of DHTs, highlighting the need for remote care options. The analysis reveals the positive impact of DHTs on improving physician productivity, enhancing patient care and quality of life, reducing healthcare expenditures, and predicting outcomes. DHTs are a hot topic of research not only in the clinical field but also in the multidisciplinary intersection of rehabilitation, nursing, education, social and economic fields. The analysis identifies four promising hotspots in the integration of DHTs in MSK pain management, biomechanics assessment, MSK diagnosis and prediction, and robotics and tele-rehabilitation in arthroplasty care.