Digital medicine in neurological research-Between hype and evidence

To paraphrase a classic, evaluating digital technologies in health is a bit like eating spinach - no one is against it in principle because it is good for you. However, no one would do it unless being asked to. In recent years, the sheer number of digital health technologies that potentially fulfil public health purposes has increased tremendously. The basis for evaluating such tools for public health purposes however has not met this pace, and in particular frameworks for the systematic development and evaluation of digital technologies in public health are rare. Existing frameworks for digital technologies focus on clinical aspects of digital health applications (e.g., NICE Evidence standards framework for digital health technologies), thus lacking both a population and prevention focus. Generic frameworks such as the Health Technology Assessment (HTA) methodology do not contain items specific to digital technologies and public health purposes. Here, we describe the process of developing a framework specific for the development and evaluation of digital public health technologies based on the core HTA model. We conduct a scoping review of frameworks for the development and the evaluation of technologies in public health and digital health, following PRISMA-SCR guidelines. The identified frameworks are then mapped onto the core HTA model to develop additional items specific for the development and the evaluation of digital technologies in public health. These additional items can be used to integrate the development and evaluation of digital technologies for public health purposes within the wider HTA context, making this process both transferable and scalable.

Designing digital health applications for climate change mitigation and adaptation.

There are dynamic interactions between (digital) technologies and society. Digital technologies have a(re-)structuring effect on social relationships and social innovations in avariety of ways. Because of these characteristics, technological innovations affect our individual lifestyles and living environments. In particular, the development and implementation of interventions with digital (health) technologies is attracting increasing national and international attention (e.g. telematics GP consultations and app-supported patient education programs).Digital health technologies enable new forms of interaction and knowledge-based reproduction in the field of health. The integration of potential users in the development process of digital health technologies and interventions requires the discussion of new research approaches. The interests, needs, and requirements of users may influence the nonuse of digital health technologies. It is above all the successful implementation, involving potential users, that can have an influence on acceptance and integrative use in the later course of care. The discourse on the participatory development and implementation of interventions with digital health technologies in the field of digital public health presents itself as acomplex process characterized by various theoretical approaches and methodological procedures and requiring representation, evaluation, and classification.

Digital health technologies and health-care privatisation

Being a 21st-century health care provider is extremely demanding. The growing number of chronic diseases, lack of medical workforce, increasing amounts of administrative tasks, the cost of medical treatment, and rising life expectancy result in an immense challenge for medical professionals. This transformation has been triggered by the growing presence of digital health. Digital health does not only refer to technological transformation; it also fundamentally reshapes the physician-patient relationship and treatment circumstances. We argue that patient empowerment, the spread of digital health, the biopsychosocial-digital approach, and the disappearance of the ivory tower of medicine lead to a new role for physicians. Digital health allows the job of being a medical professional to become more rewarding and creative. The characteristics of a physician-as-idol could shift from self-confident to curious, from rule follower to creative, and from lone hero to team worker. Empowered physicians (e-physicians) can be described as “electronic,” where they use digital technologies in their practice with ease; “enabled,” where they are enabled by regulations and guidelines; and “empowered,” where they are empowered by technologies that support their job and their empowered patients (e-patients). They can be described as “experts” in the use of technologies in their practice or in knowing the best, most reliable, and trustworthy digital health sources and technologies. They can also be described as “engaged,” when understanding the feelings and points of view of their patients, giving relevant feedback, and involving them throughout the whole healing process. The skills and approaches that characterize this era of e-physicians, such as face-to-face communication skills, digital literacy, interdisciplinarity, knowing where to find information, translating large amounts of data into insights for patients, among others, should always have been at the core of practicing medicine. However, the economical, technological, and administrative burden of the profession has not made it possible for most physicians to enjoy the benefits of their training, individual capabilities, and creativity. By understanding how digital health technologies can support or augment their capabilities, physicians would have the chance to practice the art of medicine like never before.

Digital health technologies can potentially increase the efficiency and quality of pediatric palliative care (PPC), yet their use in home-based PPC remains limited. Limited digital health care literacy and inadequate training can reduce confidence and foster negative attitudes, whereas positive experiences and basic digital health care literacy may encourage adoption. This study aims to explore the use of digital health technologies by Norwegian health care personnel in home-based PPC and examine the association between their digital health care literacy and their attitudes toward digital health. A cross-sectional study was conducted from September 2023 to May 2024, with an online survey targeting health care personnel involved in home-based PPC through primary or specialist health care services. Data were collected using selected items from the Norwegian Healthcare Personnel Survey on eHealth 2022, the Digital Health Care Literacy Scale (DHLS), and the Information Technology Attitude Scales for Health (ITASH), alongside demographic characteristics. Higher DHLS scores indicate greater digital health care literacy, while higher ITASH scores reflect more positive attitudes toward digital health technologies. Pearson correlation, ANOVA, and multiple linear regression analyses were conducted to comprehensively explore the relationships and associations among the variables. Health care personnel (n=148) from diverse health care services responded to the survey. Half of the respondents (72/144, 50%) had experience with real-time video consultation, while phone calls were the primary communication method (138/145, 95.2%). Additionally, 55.6% (79/142) of the respondents had limited or minimal access to electronic health records from other health care services. Health care personnel perceived digital health technologies for remote PPC as a supplement (126/135, 93.3%) rather than a replacement for in-person care. Mean digital health care literacy was 18.29 (SD 3.8) on a scale from 0 to 23. On a scale from 1 to 4, the highest recorded scores pertained to attitudes toward digital health technologies in supporting care (mean 3.17, SD 0.39) and the perceived need for training (mean 3.16, SD 0.43). A statistically significant association was found between the respondents' level of digital health care literacy and their attitudes toward digital health technologies in supporting care (β=0.030, 95% CI 0.014-0.047; P<.001). This study examined the use of digital health technologies by Norwegian health care personnel in home-based PPC, their digital health care literacy, and attitudes toward digital health. Despite positive attitudes and high digital health care literacy, use of digital health technologies was limited, suggesting that inadequate digital health solutions may hinder effective implementation. Addressing these barriers is crucial to enhancing the implementation of digital health in home-based PPC. Future research should focus on integrating digital health technologies into existing infrastructure and workflows while exploring their impact on personalized care to ensure high-quality home-based PPC.

To improve long-term outcomes of therapies for chronic diseases, health promotion and lifestyle modifications are the most promising and sustainable strategies. In addition, advances in digital technologies provide new opportunities to address limitations of drug-based treatments, such as medication non-adherence, adverse effects, toxicity, drug resistance, drug shortages, affordability, and accessibility. Pharmaceutical drugs and biologics can be combined with digital health technologies, including mobile medical apps (digital therapeutics), which offer additional clinical benefits and cost-effectiveness. Promises of drug+digital combination therapies are recognized by pharmaceutical and digital health companies, opening opportunities for integrating pharmacotherapies with non-pharmacological interventions (metapharmacology). Herein we present unique features of digital health technologies which can deliver personalized self-care modalities such as breathing exercises, mindfulness meditation, yoga, physical activity, adequate sleep, listening to preferred music, forgiveness and gratitude. Clinical studies reveal how aforementioned complimentary practices may support treatments of epilepsy, chronic pain, depression, cancer, and other chronic diseases. This article also describes how digital therapies delivering “medicinal” self-care and other non-pharmacological interventions can also be personalized by accounting for: 1) genetic risks for comorbidities, 2) adverse childhood experiences, 3) increased risks for viral infections such as seasonal influenza, or COVID-19, and 4) just-in-time stressful and traumatic circumstances. Development and implementation of personalized pharmacological-behavioral combination therapies (precision metapharmacology) require aligning priorities of key stakeholders including patients, research communities, healthcare industry, regulatory and funding agencies. In conclusion, digital technologies enable integration of pharmacotherapies with self-care, lifestyle interventions and patient empowerment, while concurrently advancing patient-centered care, integrative medicine and digital health ecosystems.

BackgroundChronic urticaria (CU) is a complex and unpredictable skin condition that significantly affects patients’ quality of life. As the healthcare landscape increasingly integrates digital health technologies, understanding their perceived usefulness in CU management from both patient and physician perspectives is crucial.ObjectiveThis study investigates the acceptance, perceived usefulness, and potential barriers to using digital health services, such as medical apps and video consultations, among patients with CU and their healthcare providers.MethodsA quantitative survey was conducted across multiple specialized centers, specialist clinics, and general practices, involving both patients and physicians. The study utilized standardized questionnaires to assess digital health literacy, technology readiness, and attitudes toward adopting digital health services in CU management. Descriptive and inferential statistics, including Fisher’s exact test, were employed to analyze the data.ResultsA substantial proportion of the 121 surveyed patients and 101 physicians perceived digital health technologies as beneficial in managing CU, with 59.5% of patients and 75.3% of physicians agreeing on their advantages. However, 21.5% of patients and 14.9% of physicians remained neutral, while 8.3% of patients and 4.0% of physicians found these technologies unhelpful. Key barriers to adoption were identified, including concerns over data privacy, limitations in technical infrastructure, and a lack of awareness of available digital health solutions.ConclusionWhile many patients and physicians recognize the potential of digital health technology to improve urticaria management, some remain uncertain or skeptical. Addressing concerns and improving digital understanding is critical to the future implementation and integration of these technologies into care. Due to the cross-sectional design of the study and the self-reported data, further research may be needed to confirm these results.

Digital health education and an understanding of effective technology application are essential for shaping the clinical environments of the future. This requires an understanding of nursing students’ attitudes and behaviours in health education. The objective of this study was to investigate nursing students’ perceptions of and attitudes towards digital health technologies. The study employed a qualitative research method focusing on the independent work of the students enrolled in the 2023/2024 Digital Technologies in Health course. Qualitative data were collected through Moodle, the common e-learning platform at Tallinn Health University of Applied Sciences. The document analysis database consisted of 185 student self-reflections and self-assessments. Trust in technology and the use of software emerged as key factors in the learning process. Students recognised the importance of quality health data and demonstrated trust in utilising electronic records, even when lacking previous experience. Despite their positive attitudes towards digital technologies, significant challenges remain in the application of fundamental digital skills. The most pressing concerns are related to digital literacy and innovation. Students perceive the use of digital tools as potentially distancing healthcare professionals from patients, which raises ethical concerns, particularly in relation to their future professional roles. Nursing educators should prioritise fostering a strong professional nursing identity, with particular emphasis on the positive impact of digital health technologies in clinical practice.

Digital health technologies can potentially reduce health disparities in cancer care. However, the benefits of digital health technology depend partly on users' digital health literacy, that is, "capabilities and resources required for individuals to use and benefit from digital health resources," which combines health and digital literacy. We examined issues for digital health technology implementation in cancer care regarding digital health literacy, via stakeholder consultation. Consumers, health care professionals, researchers, developers, nongovernment and government/policy stakeholders (N=51) participated in focus groups/interviews discussing barriers, enablers, needs and opportunities for digital health implementation in cancer care. Researchers applied framework analysis to identify themes of digital health literacy in the context of disparity and inclusion. Limited digital and traditional health literacy were identified as barriers to digital technology engagement, with a range of difficulties identified for older, younger and socio-economically or geographically disadvantaged groups. Digital health technology was a potential enabler of health care access and literacy, affording opportunities to increase reach and engagement. Education combined with targeted design and implementation were identified means of addressing health and digital literacy to effectively implement digital health in cancer care. Implementing digital health in cancer care must address the variability of digital health literacy in recipients, including groups living with disadvantage and older and younger people, in order to be effective. SO WHAT?: If cancer outcome disparity is to be reduced via digital health technologies, they must be implemented strategically to address digital health literacy needs. Health policy should reflect this approach.

BackgroundThe potential benefits of incorporating digital technologies into health care are well documented. For example, they can improve access for patients living in remote or underresourced locations. However, despite often having the greatest health needs, people who are older or living in more socially deprived areas may be less likely to have access to these technologies and often lack the skills to use them. This puts them at risk of experiencing further health inequities. In addition, we know that digital health inequities associated with older age may be compounded by lower socioeconomic status. Yet, there is limited research on the intersectional barriers and facilitators for engagement with digital health technology by older people who are particularly marginalized.ObjectiveThis study aimed to explore factors influencing engagement with digital health technologies among people at the intersection of being older and socially deprived.MethodsWe conducted semistructured interviews with people who were 70 years or older, living in a socially deprived area, or both. Chronic kidney disease was our clinical context. We thematically analyzed interview transcripts using the Unified Theory of Acceptance and Use of Technology as a theoretical framework.ResultsWe interviewed 26 people. The majority were White British (n=20) and had moderate health and digital literacy levels (n=10 and n=11, respectively). A total of 13 participants were 70 years of age or older and living in a socially deprived area. Across participants, we identified 2 main themes from the interview data. The first showed that some individuals did not use digital health technologies due to a lack of engagement with digital technology in general. The second theme indicated that people felt that digital health technologies were “not for them.” We identified the following key engagement factors, with the first 2 particularly impacting participants who were both older and socially deprived: lack of opportunities in the workplace to become digitally proficient; lack of appropriate support from family and friends; negative perceptions of age-related social norms about technology use; and reduced intrinsic motivation to engage with digital health technology because of a perceived lack of relevant benefits. Participants on the intersection of older age and social deprivation also felt significant anxiety around using digital technology and reported a sense of distrust toward digital health care.ConclusionsWe identified factors that may have a more pronounced negative impact on the health equity of older people living in socially deprived areas compared with their counterparts who only have one of these characteristics. Successful implementation of digital health interventions therefore warrants dedicated strategies for managing the digital health equity impact on this group. Future studies should further develop these strategies and investigate their effectiveness, as well as explore the influence of related characteristics, such as educational attainment and ethnicity.

Digital health technology provides opportunities to leverage artificial intelligence and other digital applications to promote cardiovascular health. Digital health technologies include artificial intelligence (such as machine learning [ML], neural networks),1 analytic systems, mobile apps, wearables, email, text messaging, and telemedicine.2 In this article, we review the role of digital technology in cardiovascular health and a selection of recent studies to evaluate the evidence of its effectiveness. Artificial intelligence is broadly defined as the capability of computer systems to perform tasks similar to humans.3 Examples include vision, speech, pattern recognition, and decision making. Machine learning is the ability of the computer program to learn from experience. This typically occurs from analysis of large sets of data processed through human-derived algorithms to enhance, predict, and explain outcomes.4 An example of the use of ML in clinical care is cardiovascular disease (CVD) prediction and electrocardiographic interpretation. Neural networks, named after the human nervous system, are nonlinear statistic models that control where signals are sent. Neural networks can be used for decision making such as cardiovascular diagnosis confirmation. Digital Technology Use in Cardiovascular Risk Assessment Several studies have demonstrated improved CVD risk factor identification using ML compared with traditional risk assessment tools. Researchers developed an ML risk calculator and compared it with the American College of Cardiology/American Heart Association CVD risk calculator in 6459 participants from the Multi-Ethnic Study of Atherosclerosis.5 Study participants were free of CVD at baseline and followed for 13 years. Results revealed that the American College of Cardiology/American Heart Association risk calculator was less precise: statin therapy was recommended to 46% of the sample, with 23.8% of CVD events occurring in those not recommended a statin. In comparison, the ML risk calculator recommended a statin to 11% of the sample, with 14.4% of CVD events occurring in those not recommended a statin.5 Similarly in 3 cohorts from Australia, 4 ML models were developed and compared with the 2008 Framingham model. The ML models provided 2.7% to 5.2% better predictions across all 3 cohorts.6 Taken together, the authors of these studies suggest ML provides promise in providing more precise estimates of CVD risk. Digital Health Interventions for Cardiovascular Disease Prevention Digital health interventions have the potential to provide a personalized approach to promote cardiovascular health. Behavior change theory is a key component of digital interventions and includes theoretical frameworks such as supportive accountability,7 self-efficacy theory,8 social cognitive theory, and the health belief model.9 Precision healthcare has been promoted for decades. Many of the challenges in operationalizing precision healthcare are healthcare accessibility, scheduling, care continuity, and inadequate knowledge exchange between provides and patients.10 Thus, promotion of healthy lifestyles and lifestyle risk factor reduction remain inadequately addressed in patients with CVD.11 To achieve sustainable change, individual-level personalized strategies may be leveraged through digital health interventions. Evidence of the effectiveness of digital health interventions has varied but is promising overall. Text messaging has been successfully used to provide information regarding healthy diet and physical activity recommendations, monitoring, and individual feedback. Text messaging has resulted in improvements in diet and activity in many (TextMe,12 Mobile MyPlate,13 MyQuest,14 Text-To-Move15), but not all studies.16 Smartphone/mobile apps have been designed to improve dietary and physical activity behavior. Examples include apps that track dietary patterns and activity through user input of text or visual images.17,18 Users can set their own goals and receive feedback on progress toward goals. Reviews of smartphone apps have had variable results with many demonstrating short-term improvement. Villinger et al19 conducted a systematic review and meta-analysis of the effectiveness of mobile app interventions on nutrition behaviors (41 studies, 27 randomized controlled trials [RCTs]). Findings revealed significantly improved nutrition behaviors and nutrition-related outcomes (P = .004 and P = .043, respectively). A second systematic review of 27, primarily RCTs, found significant between-group improvements in 19 of the 27 studies.20 A meta-analysis of 6 RCTs in adults using a smartphone app as the primary component of the intervention revealed a trend for more steps per day in the intervention compared with the control groups, with programs lasting less than 3 months more effective than longer programs.21 Taken together, text messaging and smartphone/mobile apps have the potential to improve lifestyle behaviors associated with cardiovascular health. The addition of strategies to increase sustainability of the effects needs to be assessed. Digital Health Interventions: Primary and Secondary Prevention Widmer et al2 conducted a meta-analysis of 51 RCTs and cohort studies using digital health interventions for the prevention of CVD events and risk factor modification. Subgroup analyses of primary prevention studies (2 studies) did not provide evidence of a statistically significant reduction in CVD outcomes. However, evaluation of individual risk factors in primary prevention studies found a significant reduction in weight (11 studies; −3.35 lb), systolic blood pressure (23 studies; mean difference, −2.12 mm Hg), total cholesterol (13 studies; mean difference, −5.19 mg/dL), low-density lipoprotein cholesterol (8 studies; mean difference, −4.96 mg/dL), and glucose (6 studies; mean difference, −1.38 mg/dL).2 A subgroup analysis of secondary prevention studies demonstrated a significant impact of digital interventions on CVD outcomes (relative risk, 0.60; a 40% relative risk reduction), improvement in body mass index (6 studies; mean difference, −0.31 kg/m2) but no improvement in weight, systolic blood pressure, total cholesterol, low-density lipoprotein cholesterol, and glucose. Taken together, this meta-analysis suggested that digital interventions were beneficial not only in lowering CVD events in higher-risk patients but also in lowering risk factors in primary prevention approaches.2 In a second meta-analysis conducted by Akinosun et al,11 researchers analyzed 25 RCTs in patients with traditional CVD risk factors who received a digital intervention versus usual care.11 Findings revealed benefits in total cholesterol (mean difference, −0.29), high-density lipoprotein cholesterol (mean difference, −0.09), low-density lipoprotein (mean difference, 0.18), physical activity (mean difference 0.23), physical inactivity (relative risk, 0.54), and diet (relative risk, 0.79). There was no significant improvement in body mass index, systolic and diastolic blood pressure, hemoglobin A1C, alcohol intake, smoking, and medication adherence. Authors concluded that digital interventions were more effective at improving healthy behaviors than reducing unhealthy behaviors. In patients who experienced a myocardial infarction, a digital health intervention providing medication reminders, vital sign and activity tracking, education, and outpatient care coordination resulted in a 52% lower 30-day readmission rate compared with usual care.22 Sociodemographic characteristics (age, sex, and race) did not influence use of the digital intervention, highlighting a potential role for digital interventions in the promotion of equity in social determinants of health.23 Digital Health Interventions in Cardiac Rehabilitation Cardiac rehabilitation is an essential component of secondary prevention of CVD.24 Some patients face barriers in participation in cardiac rehabilitation due to physical accessibility, time, and travel.25 Digital health interventions have the potential to bridge these barriers and increase participation. Digital delivery of cardiac rehabilitation therapy with real-time personalized support has several advantages.26 In a systematic review of 31 studies in which authors examined digital health interventions for cardiac rehabilitation, the results revealed that cardiac rehabilitation program adherence was greater in patients using digital interventions than traditional methods alone. Secondary benefits were found in self-efficacy, weight management, diet, and quality of life. Taken together, digital cardiac rehabilitation was feasible and effective whether used alone or in combination with traditional cardiac rehabilitation.26 Conclusion Digital health technology is an evolving field with tremendous potential to improve cardiovascular health. Cardiovascular disease remains the major cause of death in the United States. The age-adjusted mortality rate has increased in the last decade. More people died from CVD causes in 2020 (nearly 900 000 deaths) than any year since 2003.27 Opportunities to reduce CVD and CVD risk have not been fully leveraged, and digital technology interventions have the potential to meet this need. Digital health technology also has the potential to provide equitable and personalized care. Device data, electronic medical record data, and social determinants of health data provide an opportunity to combine and identify longitudinal trends and risk factors before CVD begins. In the future, large data sets can be created that can be analyzed using ML to identify patterns and structures within and among the data to provide a more robust risk assessment to promote CVD prevention.

Background:Digital Health Technologies (DHTs) are increasingly expanding conventional rheumatology care, offering new modalities for patient engagement and treatment management. Understanding the factors influencing their adoption and usage among patients in...

The Council for Cardiology Practice of the European Society of Cardiology (ESC), in collaboration with the Digital Health Committee (DHC), undertook an electronic survey with 15 question multiple-choice questionnaire sent to 32 461 members of the ESC with the aim to assess the knowledge and usage of digital health (DH) technologies (DHTs) by office-based cardiologists. Of 559 respondents, 57% graded their knowledge about DH as ‘fair’ and three quarters identified the correct definition of DH. Clinical information systems, mHealth Apps, and telemedicine were the most frequently used DHTs, but 41% of respondents had concerns about their ethical and data transparency. Lack of legal clarity, low patient motivation, limited DH literacy, and poor access to DH were perceived as the main barriers to the adoption of DH. Seventy percent of the respondents were aware of the DH pages on the ESC website and 76% of the educational sessions in the DH area during the ESC Congress 2019. Only 16% had not read articles on DH. Eight-eight percent of responders declared that they would ‘probably’ or definitely attend future educational initiatives on DHT.

U.S. seniors' digital health and everyday technology use when their health declines are unknown. Longitudinal cohort using the National Health and Aging Trends Study, a nationally representative, annually administered sample of community-dwelling Medicare beneficiaries (n = 4,037). We used difference-in-differences to assess the adjusted difference (AD) in technology use from 2011 to 2014 between those with and without health declines. Health decline measures included new-onset dementia; new-onset depression; decreases in activities of daily living (ADLs), short physical performance battery (SPPB), grip strength, and self-reported health; relocation to nursing facility; increased hospitalizations; and new-onset comorbidity. Digital health included use of the Internet to research health conditions, contact clinicians, fill prescriptions, and address insurance matters. Between 2011 and 2014, seniors experiencing health decline used various digital health technologies at low absolute rates (range: 1%-20%). Between 2011 and 2014, use of everyday technology decreased significantly among seniors with new-onset dementia (from 73% to 51%; AD, -26%), decreased ADLs (from 76% to 67%; AD, -10%), decreased SPPB (from 88% to 86%; AD, -3%), and relocation to a nursing facility (from 49% to 22%; AD, -31%) compared to seniors without comparable decline (all p < .05). Use of digital health decreased significantly among seniors with new-onset probable dementia (from 9% to 4%; AD, -6%) and decreased SPPB (from 24% to 25%; AD, -4%; all p < .05). The type of health decline a senior experiences predicts technology use, which may allow better targeting of digital health to specific seniors. Seniors with new dementia, relocation to a nursing home, and declining physical performance seem especially poor candidates for technology interventions.