Digital Health

The goal of this observational pre-post study is to evaluate a remote-patient-monitoring-system (RPM-system) integrated within an electronic health record (EHR) system in a real world cohort of approximately 12.000 people with diabetes in an outpatient care setting. The main question it aims to answer is: Whether glycemic outcomes following integration of the RPM system into the EHR over a two-year period are non-inferior compared with outcomes observed prior to an ambulatory care restructuring (including a prototype of the RPM-system) in October 2024. Participants are included in the RPM-system as part of their regular medical care for diabetes.

This research study is testing two self-care approaches that may help prevent or reduce period pain in young females with recurrent painful menstrual cramps. Participants will be placed by chance into 1 of 3 groups: auricular acupressure, Baduanjin qigong, or a self-care education comparison group. The auricular acupressure and Baduanjin groups will receive online training and then practice the treatment on their own for 12 weeks. The main question is whether these two approaches can reduce the severity of menstrual pain. The study will also look at whether they can improve other symptoms that often happen with period pain, such as tiredness, poor sleep, anxiety, low mood, trouble concentrating, and reduced physical function. Researchers will also study stool and blood-related biological markers to better understand whether changes in gut bacteria and body metabolism may be linked to symptom improvement. A total of 145 participants will take part in the study at NTU, and any side effects or other safety concerns will be checked every week.

The overall objective is to evaluate the effectiveness and implementation of the Corrie Lipids Program, a comprehensive digital health initiative designed to address critical gaps in lipid-lowering as a component of ASCVD treatment by delivering an intervention that combines a patient-facing smartphone app, clinician education and coaching, and seamless incorporation into clinical workflows. Researchers plan to assess this multicenter digital health initiative in approximately 1,000 adults with uncontrolled LDL-C and elevated ASCVD risk using the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework. The study will examine whether the program improves LDL-C goal attainment, app engagement, prescribing patterns, and LDL-C monitoring, while also identifying barriers and facilitators to implementation across sites.

The goal of this randomised clinical trial is to utilise a remote monitoring algorithm to gather essential clinical data, aiming to guide the management of post-Transcatheter Aortic Valve Implantation (TAVI) patients and reduce both postprocedural hospital length of stay and readmissions. This strategic integration of technology aims to address gaps identified in previous studies and enhance the effectiveness of post-TAVI patient care. One significant concern after TAVI is the development of heart conduction abnormalities on the ECG and abnormal rhythms, such as heart block, potentially requiring permanent pacemaker insertion. Addressing these rhythm issues is crucial for reducing the overall length of stay. The main question it aims to answer is: Does a remote patient monitoring protocol-driven strategy reduce post-TAVI hospital length of stay and adverse events? Participants post-TAVI procedure and eligible for same-day discharge, as determined by their primary cardiologist, will be randomized upon informed consent into the active arm (remote monitoring) or control group (standard of care). Participants in the active arm will: receive four remote monitoring devices. Receive support from a validated clinical decision-making algorithm for further management. Participants in the control group will: adhere to the best standard of care as per current practice. Researchers will compare the active arm to the control group to see if the remote patient monitoring protocol-driven strategy reduces post-TAVI hospital length of stay and adverse events.

The goal of this observational study is to evaluate the feasibility and accuracy of a self-administered remote neurological examination using the "Iskhaa" mobile application in patients with brain tumors aged above 5 years who are able to follow app-based instructions. The main questions it aims to answer are: 1. Development of a mobile application equipped with symptom assessment and recording videos as patients perform specific neurological tasks. 2. Development and validation of the AI model to detect functional changes and predict subsequent neurological deterioration. Participants will: 1. Use the Iskhaa mobile application to perform guided self-neurological examinations following pre-recorded video instructions. 2. Complete EORTC QLQ-C30 and BN20 questionnaires for quality of life assessment. 3. Record and upload videos (e.g., speech, walking, limb movements) using their mobile camera for analysis. 4. In Phase 1 (onsite), 100 participants will use the app under supervision to ensure usability and accuracy. 5. In Phase 2 (offsite), 500 participants will use the app independently at home for monthly self-assessments, with reminders and follow-up support. 6. Continue routine clinic visits every 3-6 months and imaging every 6-12 months as per standard clinical care. The study will compare app-recorded data with physician assessments to determine agreement and validity of remote neurological monitoring using artificial intelligence analysis.

This study aims to develop and evaluate the longitudinal effectiveness of the Artificial Intelligence Family Involvement Generative Agent (AIFIGA) program in enhancing the health of nursing staff, family, and residents' health through the use of a sequential, mixed methods research design. The development of a real-time, interactive, and informative AIFIGA program that sparks innovation is necessary to achieve effective communication between families and nursing staff. In Phase I, lasting 18 months, we will develop the AIFIGA program based on triangulate research design, observation and in-depth interview understanding the daily communication experiences and expectations from both families and nursing staff perception in Nursing Homes(NHs) after COVID-19, as well as our previous years' research results. The training data for AIFIGA will be derived from the collection of communication dialogues in these qualitative data. Furthermore, the intelligence of AIFIGA will be developed using publicly available large language models (LLMs). In Phase II, spanning the next 18 months, we will evaluate the longitudinal effects of the AIFIGA program on the health of residents, families, and nursing staff, tracking changes over time (baseline, 1 month, 3 months, and 6 months). There will be two groups of participants: (a) an AIFIGA group that receives the AIFIGA program and uses it for 3 months, and (b) a control group that receives only routine care.

This study aims to investigate differences in perception of barriers and facilitators of digitalization and Artificial Intelligence (AI) usage in healthcare across different generational groups (youth, working-age adults, and seniors). The results will help create practical recommendations for public health projects and consultants to support fair and inclusive use of new digital tools in healthcare. A cross-sectional online survey will be conducted among students at HAW, patients and employees in the rehabilitation center in Oldenburg, and seniors participating in the "Digital im Alter"(DIA) project.

The management of diabetes is of great value in reducing the risk of complications and alleviating the socioeconomic burden. Currently, the diabetes management models in China have not effectively integrated the advantages of traditional Chinese medicine (TCM) and Western medicine. They also fail to achieve intelligent and automated management, resulting in high management costs and low efficiency. Therefore, it is extremely urgent to explore a new, efficient, convenient, low - cost, and personalized long - distance, full - course, intelligent management model for diabetes that integrates TCM and Western medicine both online and offline. Based on this, our research group plans to rely on the pre - designed and developed Idata database. We will deeply integrate the diagnostic and treatment advantages of TCM constitution differentiation and Western medical examinations and laboratory tests, construct an automated follow - up path, and build an integrated online diabetes management platform for Internet hospitals, which consists of "intelligent hardware + APP + cloud services + a back - end think - tank of TCM and Western medicine experts + a back - end professional management and care team". This initiative aims to blaze a new trail in the field of long - distance, full - course, and personalized management of diabetes through the synergy of TCM and Western medicine for Chinese diabetes patients. We expect to significantly reduce the incidence of diabetes complications, remarkably improve the overall health status and quality of life of patients, and bring unprecedented positive impacts on the well - being of diabetes patients.

Data collection study to establish a predictive model of infection observed during childhood cancer therapy using data captured by wearable technology.

Cardiovascular diseases continue to be the leading cause of death worldwide. Among them, coronary artery disease has the greatest impact, being characterized as one of the main causes of death in Brazil over the last decade. One of the well-established treatments is coronary artery bypass grafting, which is the most performed among cardiac surgeries and, in our scenario, is primarily funded by the Unified Health System (SUS). The information obtained from the Paulista Registry of Cardiovascular Surgeries (REPLICCAR), in partnership with FAPESP, has been important for implementing improvements in the landscape of cardiac surgeries in the state of São Paulo. Although outcomes in cardiac surgery have improved due to the structuring and organization of quality programs, this is still not a reality at the national level. In a situation where data collection and quality initiatives play a central role in continuous improvement, generating value becomes essential for the sustainability of cardiac surgery programs. In this sense, the concept of Enhanced Recovery After Surgery (ERAS) has gained increasing traction. This concept is based on multidisciplinary protocols and scientific evidence, which help prepare patients for rapid recovery, resulting in reduced complications, shorter hospital stays, and, primarily, lower hospital costs. On the other hand, the increase in surgical waiting lists has also led to a rise in home mortality due to cardiac causes. Thus, among the various challenges imposed by the current scenario, the investigators believe that preparing patients for rapid recovery after coronary artery bypass grafting presents an opportunity for the sustainability of the healthcare system. Therefore, the aim of this project is to evaluate the impact of a technology platform based on ERAS on the postoperative recovery time of patients undergoing coronary artery bypass grafting in reference centers in the state of São Paulo, Timely Project - REPLICCAR III.

This study aims to explore patients' use of digital services for self-management of their health following major surgery at Jessa Hospital. Besides this, the study evaluates patients' ability to process and critically assess health information during recovery, their understanding of health concepts and risk factors, and their perception of data security and control over personal health information. Additionally, the study aims to examine patients' motivation to use digital services, their access to and trust in reliable digital health resources, and how well these services meet their individual needs. Furthermore, the study assesses the acceptability, appropriateness, and feasibility of using digital health tools in a post-operative setting, as well as evaluating the digital readiness of patients after surgery.

This feasibility trial has three main objectives: * To investigate the impact of the transmural care pathway TOTeM on the Length of Stay (LOS) for patients undergoing robotic distal pancreatectomy. * To investigate the feasibility of the implementation of TOTeM for patients undergoing robotic distal pancreatic surgery, we will measure the recruitment rate by tracking the number of eligible patients who are approached for participation, the percentage who consent to join the study over a specified time period, and the adherence rate which describes how well participants follow the study protocol including the prescribed interventions or follow-up assessments. * Assessment of the potential changes in medical costs and outcomes for the purpose of performing a cost-effectiveness analysis from a hospital and patient perspective.

The aim of this clinical trial is to evaluate whether nurse-led telehealth support helps individuals with gout better manage their condition and adhere to urate-lowering medication after discharge from a rheumatology clinic. Eligible patients will be recruited from five rheumatology departments in the Central Denmark Region after achieving two consecutive target serum urate levels-below 0.36 mmol/L, or below 0.30 mmol/L for patients with tophi. Participants will be adults with gout who meet specific medical criteria, are taking medications such as allopurinol or Adenuric, and are able to read and write Danish. Participants will be randomly assigned to one of two groups: * Intervention group: nurse-led telehealth support. * Control group: usual care with follow-up by their general practitioner. The primary goal is to support patients in maintaining healthy uric acid levels after 52 weeks. Participants in the nurse-led group have the option to choose from four support options: I1: App-Based Support - an app provides information and reminders. I2: Letter Reminders - messages are sent via digital or postal mail. I3: Text Reminders - SMS messages are sent every three months. I4: Phone Support - nurses call three times a year to check in.

The study focuses on patients who require outpatient infusion of therapy ("Infusions, Intravenous"\[Mesh\]) "Administration, Intravenous"\[Mesh\] ("Home Infusion Therapy"\[Mesh\]) "Parenteral Nutrition, Home"\[Mesh\] via a peripherally inserted central catheter (PICC) ("Central Venous Catheters"\[MeSH\] "Catheterization, Central Venous"\[MeSH\] "Catheterization, Peripheral" \[MeSH\] "Vascular Access Devices"\[Mesh\] )

Inadequate medication adherence (MA) in chronic conditions, including cardiovascular prevention, represents an important risk factor. The use of new IT technologies in this setting is supposed to be useful to improve patients' adherence, but currently available solutions have significant limitations, including lack of personalization and reliance on expensive ad hoc systems. This interdisciplinary project aims to verify the hypothesis that in patients on chronic antihypertensive treatment MA can be improved through the implementation of a novel digital health solution for MA monitoring and support, based on inexpensive and user-friendly, commercially available technology (voice assistant), connected with web interface for the physician. The intervention will be personalized based on the creation of Personas, intended as multidisciplinary-based representations of different user types. This approach will be tested in a randomized clinical trial.

This study aims to evaluate the effectiveness of pain education and clinical hypnosis delivered via a mobile app compared to a guideline-informed factsheet for reducing pain and disability in people experiencing chronic low back pain attending general practice.

The goal of the HealthyW8 study (an intervention study) is: To assess the usefulness and effects of a digital-based healthy lifestyle recommender system (HRLS) on the prevention of obesity in the following propulations: schoolchildren (5-10 y) and their parents, young adults (18-25 y) and elders (\>65 y). The main questions it aims to answer are: Outcome 1: To select and validate a tool-assisted 3-mo intervention (mostly digital) by iteratively testing the HLRS on reducing risk of overweight/obesity among the described age groups. Outcome 2: To assess the effect of 1-y interventions (mostly digital) with the HLRS described and further iteratively improved previously (outcome 1) on reducing risk of overweight/obesity at described ages. Researchers will compare the intervention group before the intervention (baseline) and after it (3-mo intervention trial), or control group (standard care) vs. Intervention group (1-y intervention) to see changes on changes in overweight/obesity, and related parameters (body composition and biomarkers). Participants will follow the HLRS recommendations (meal plans, physical activity and sleep pattern measures and recommendations, assessment of behavioural/psychological aspects, and motivational features through digital devices), which will be assessed by means of measurement of body weight, body composition, and biomarkers.

This study aims to evaluate whether patients recognize a need for a remote monitoring care pathway during the post-operative period following major surgery at Jessa Hospital by means of a semi- structured interview. Besides this, the study explores patient perceptions and willingness to participate in digital monitoring care pathways, identifies potential barriers to adoption, and addressing concerns related to safety, data security, and privacy. Additionally, the study aims to assess patient needs regarding parameter collection, technology usage, and the overall functionality of digital monitoring systems, while evaluating the perceived usefulness of such a pathway in post-operative care.

This qualitative feasibility study investigates a digital health app designed for patients who are frequently admitted to the psychiatric acute ward, to facilitate crisis support outside of office hours to avoid unnecessary readmissions, as well as self-harm. As this is a novel app to be implemented in an already existing service, key uncertainties regarding the intervention content and its delivery needs to be addressed before potentially conducting a full-scale trial, or, alternatively, to inform further intervention refinement. Such uncertainties are appropriate to explore in a feasibility study according to the Medical Research Council (MRC) framework for the development and evaluation of complex interventions. There is a need to investigate whether the app is acceptable and useful to the patients using it, and to the healthcare providers who respond to it. There is also a need to know whether the healthcare providers responding to the app find the task manageable. The context in which the staff are to deliver the intervention, i.e. the in-bed ward, may be subject to different barriers, such as a staff shortage due to sick leave and heavy workload in the ward. Such barriers are essential to identify ahead of possible future trials in other contexts.

Smart technologies, such as wearable devices, mobile technologies, and artificial intelligence, are being investigated for use in health management. These technologies have the potential to be applied in disease pre-warning, decision-making support, health education, and healthcare maintenance. They are expected to address the challenges in managing thrombosis, improve access to high-quality medical resources in various regions, and enhance the development of a network for thrombosis rescue and treatment prevention. The objective of this study is to evaluate the impact of mobile venous thromboembolism application (mVTEA) based patient-centered management of pulmonary thromboembolism (PTE) on the long-term outcome of PTE patients, in order to enhance clinical practice and establish a foundation of evidence for managing patients with PTE.

Sedentary behaviour among medical inpatients is strongly associated with hospital-associated functional decline and poses a severe threat to patients' functional capacity and independency. High human and socioeconomic costs underline the urgency to find solutions to this world-wide problem. Objective: This multicentre study, including a total of 400 patients from Copenhagen, Aalborg, Tórshavn, and Nuuk, will assess the effect of a digital intervention that aims to reduce sedentary behaviour and increase physical activity in medical inpatients. Intervention: Digital feedback and nudging regarding the patients' physical activity levels to patients and healthcare staff Design: Stepped-wedge cluster randomised multicentre trial Primary outcome: Daily average time of patients' physical activity (minutes).

The goal of this observational study is to learn about the effects of sleep disorders on health and ageing in older people over the age of 65. The main question it aims to answer is: How do sleep disorders impact the motoric and cognitive ageing trajectories of older individuals? Participants will undergo a set of instrumental, laboratory and clinical diagnostic examinations to comprehensively assess the impact of sleep disorders on health.

NFTs are blockchain-based digital and physical assets traded on digital marketplaces. Current and exploratory NFT use cases include art, collectibles, in-game items, real estate, ticketing, events, fintech, licenses, IDs, and healthcare. NFT marketplaces, online games, virtual worlds, and open-source coding platforms use NFTs to incentivize participation. In trials, where the effectiveness of financial remuneration to increase trial participation is unclear, NFTs could encourage involvement. Considering the increasing opportunities for blockchain technology and NFT use in both the economy and society, we present a pilot study protocol to gauge the interest and feasibility of using NFTs as payment for trial participants, the first of its kind to our knowledge. Additionally, as the global population ages and chronic diseases become more prevalent, innovative solutions to sustain engagement in longevity-focused interventions are needed. Harnessing CURATE.AI, an indication-agnostic artificial intelligence (AI) platform that modulates the intensity of interventions to generate truly personalized profiles - or digital avatars, we will develop N-of-1 learning trajectory profiles for fifteen healthy volunteers trained on the CURATE.DTx, a digital therapeutic (DTx) platform. The profiles will be artistically modified and minted for the participants in the Ethereum blockchain, whereafter the recipient can choose to keep, display, or trade their NFT. Through interviews, we will evaluate the interest and acceptability of NFTs as an incentive for trial participation. This pioneering exploration connects AI-driven personalized medicine with inventive blockchain solutions. Our research aims to advance the field of digital therapeutics and pave the way for novel approaches to patient-centered care and incentivization strategies in clinical trials.

The Digital Detox study is designed as a randomized controlled trial (two unblinded parallel groups) to examine the effects of reducing smartphone screentime on mental health. After giving informed consent, participants will be screened for eligibility. Inclusion criteria are adult subjects (greater-equal 18 years) using their smartphone daily for 3 hours or more, with sufficient German skills and no ongoing psychotherapy, psychological or psychopharmacological treatment. For eligibility screening, participants have to upload a screenshot of their smartphone screen time of the last week, have to state about mental health disorders (self-report) and their sociodemographic variables (age, gender, country of residence, education and professional status, urban/rural nature of place of residence), and have to fill out the following questionnaires: depressive symptoms (PHQ-9), well-being (WHO-5), sleep quality (ISI), stress (PSQ-20), loneliness (three-item loneliness scale), physical activity, and smartphone usage behavior. If the inclusion criteria are met, participants will be randomized to the intervention or control group. The intervention consists of a three-week screen time reduction to a maximum of 2 hours per day for 3 consecutive weeks. The control group continues to use their smartphones as usual during this time. At the beginning of the study (=baseline T0), all participants will complete the following primary outcome measures (depressive symptoms (PHQ-9), well-being (WHO-5), sleep quality (ISI), stress (PSQ-20)) and secondary outcome measures (loneliness (three-item loneliness scale), craving (CEQ-F), physical activity). Both groups will also complete items on loneliness and physical activity twice during the intervention (after the first and second week of the intervention) to monitor changes in these variables during the intervention. After the three weeks of intervention (post-intervention T1), both groups will again fill out the the same outcome measures as for T0. After the 3-week intervention, there are no further restrictions regarding the participants' smartphone screen time. Follow-up (T2) will be after 3 more weeks and the same outcome measures as for T0 and T1 will be collected. The weekly smartphone screen time is assessed via self-reporting and screenshot upload. Information is also provided on the weekly activations of the smartphone and a screenshot is uploaded of the most frequently used apps. All data is collected weekly for the previous week. The study will be performed entirely via a smartphone app (ESMIra), which is designed especially to run longitudinal studies. Primary hypotheses: * H1: Reducing smartphone use to a maximum of 2 hours/day over 3 weeks leads to a difference in the depressive symptoms of the intervention participants before and after participating in the intervention. * H2: Reducing smartphone use to a maximum of 2 hours/day over 3 weeks leads to a difference in the the sleep quality of the intervention participants before and after participating in the intervention. * H3: Reducing smartphone use to a maximum of 2 hours/day over 3 weeks leads to a difference in perceived stress of the intervention participants before and after participating in the intervention. * H4: Reducing smartphone use to a maximum of 2 hours/day over 3 weeks leads to a difference in the well-being of the intervention participants before and after participating in the intervention. * H5: The reduction in smartphone use to a maximum of 2 hours/day over 3 weeks led to a difference in depressive symptoms between the control and intervention groups at the post-intervention time point. * H6: The reduction in smartphone use to a maximum of 2 hours/day over 3 weeks led to a difference in sleep quality between the control and intervention groups at the post-intervention time point. * H7: The reduction in smartphone use to a maximum of 2 hours/day over 3 weeks led to a difference in perceived stress between the control and intervention groups at the post-intervention time point. * H8: The reduction in smartphone use to a maximum of 2 hours/day over 3 weeks led to a difference in well-being between the control and intervention groups at the post-intervention time point.

This study aims to develop and evaluate an AI-driven Personalized Exercise Feedback Program (AI-PEF) to enhance exercise adherence and health outcomes in mTBI patients. Methods: AI-PEF integrates the transtheoretical model and self-determination theory with machine learning algorithms to provide real-time, personalized feedback. A phased randomized controlled trial will be conducted: Phase I evaluates feasibility and acceptability through Delphi methods with expert consensus and patient feedback; Phase II validates preliminary outcomes with 30 participants in a 2-arm randomized trial; and Phase III assesses the program's impact on adherence, sleep quality, depressive symptoms, and quality of life with 90 participants in a 3-arm randomized trial.