Search Results (13)

Adolescents living with HIV (ALHIV) face significant challenges in self-managing their chronic condition. Digital health technology (DHT) has become increasingly common and understanding ALHIVs’ preferences is essential for developing interventions tailored to this unique population. This study aimed to explore the preferences of ALHIV regarding the use of DHT for self-management. A qualitative research approach with an exploratory and descriptive design was used. Participants were recruited using a purposive sampling method. Data were gathered through six nominal focus groups with 29 participants at two Community Health Centers in the Western Cape Province, South Africa. The participants were ALHIV aged 15–24 years. Discussions focused on current technology usage and the ranking of desired DHT features. The transcripts were analyzed using thematic analysis. Three main themes emerged: (1) everyday usage of digital technology where participants frequently used digital devices for communication, social media, and finding information; (2) the role of digital technology in self-management; a strong interest in digital technology that provides medication reminders, health education, and peer support; and (3) factors influencing digital technology, including the cost of data, limited connectivity, and issues of privacy related to participants’ HIV status. The ALHIV showed a strong willingness to use digital platforms for health information, reminders, and peer support, although concerns about connectivity, data cost, and privacy remain. These findings underscore the need for flexible, user-centered approaches when designing DHT interventions for self-management in South Africa. Full article

In addition to axial motor complications such as abnormal posture, instability, falls, and gait variability, neurodegenerative diseases like Parkinsonian syndromes include executive dysfunction, Parkinson’s disease dementia, and neuropsychiatric symptoms. These motor disorders significantly affect mobility, quality of life, and well-being. Recently, physical activity of various intensities monitored both remotely and face-to-face via digital health technologies, mobile platforms, or sensory cues has gained relevance in managing idiopathic and atypical Parkinson’s disease (PD and APD). Remote monitoring solutions, including home-based digital health assessments using semi-structured activities, offer unique advantages. Real-world gait parameters like walking speed can now be continuously assessed with body-worn sensors. Developing effective strategies to slow pathological aging and mitigate neurodegenerative progression is essential. This study presents outcomes of using digital health technologies (DHTs) for remote assessment of motor function, physical activity, and daily living tasks, aiming to reduce disease progression in PD and APD. In addition to wearable inertial sensors, clinical rating scales and digital biomarkers enhance the ability to characterize and monitor motor symptoms. By reviewing recent literature, we identified emerging trends in quantifying and intervening in neurodegeneration using tools that evaluate both remote and face-to-face physical activity. Our findings confirm that DHTs offer accurate detection of motor fluctuations and support clinical evaluations. In conclusion, DHTs represent a scalable, effective strategy for improving the clinical management of PD and APD. Their integration into healthcare systems may enhance patient outcomes, support early intervention, and help delay the progression of both motor and cognitive symptoms in aging individuals. Full article

Background/Objectives: Progressive supranuclear palsy (PSP) is an atypical Parkinsonian disorder characterized by Parkinsonism with gait imbalance, vertical gaze palsy, and frontal cognitive dysfunction. Though digital health technologies (DHTs) are widely used both clinically and in research as outcome measures, there is a lack of consistency applied to these devices and their resulting metrics. This scoping review aims to identify efforts taken to validate wearable DHTs for use in PSP, identify gaps in research, and discuss the steps needed to expand their use and acceptance as primary trial endpoints. Methods: In this scoping review, we conducted a search of the MEDLINE database to examine the use of DHTs as outcome measures in Progressive Supranuclear Palsy. Results: A total of 17 publications were identified and reviewed. Included articles evaluated the use of DHT to measure lower extremity function/gait, balance, upper extremity function, and speech. Conclusions: Our scoping review highlights the importance of standardization of DHT metrics by thorough assessment of their content validity, reliability, construct validity, responsiveness, and discriminant validity. Efforts must be taken to ensure DHTs capture clinically relevant, patient-centered outcome measures that are comparable to conventional rating scales, that consistently discriminate disease progression. Incorporation of DHTs as clinical trial endpoints has the potential to encourage clinical research and to advance patient care. Full article

(1) Background: Digital Health Technology (DHT) is an emerging method for stroke rehabilitation that could potentially be very effective in solving different problems in the therapeutic process. This study aims to explore the use of DHT for stroke rehabilitation in Canada, providing insights into how current technologies have been implemented and identifying gaps to inform future decision-making in clinical, research, and policy settings in the Canadian setting. (2) Methods: We followed the Arksey and O’Malley framework for scoping reviews. The original search was created in Medline (Ovid) and translated to PsycINFO (Ovid), Scopus, and CINAHL with Full Text (EBSCOhost). To locate grey literature, we searched Canadian Theses and Google. The search yielded 163 articles, of which we included 14 (8.6%) in the review. (3) Results: Fourteen studies published between 2010 and 2022 in Canada varied in design: 4 qualitative (28.6%), 4 randomized clinical trials (RCTs) (28.6%), 2 mixed methods (14.3%), and other types. The main goals included assessing intervention effectiveness (35.7%), client (28.6%) and clinician (28.6%) perceptions of technology, and feasibility (21.5%). Most studies focused on upper extremity (UE) function (85.71%), with some addressing walking speed (7.1%) and sitting balance (7.1%). Research mainly targeted the chronic phase of stroke (64.3%). Studies were conducted in home (50%) and institutional settings (42.9%). Technologies included sensors (50%), virtual reality (VR) (42.9%), games (28.6%), telerehabilitation (28.6%), and robots (14.3%). (4) Conclusions: This scoping review offers key insights into the use of DHTs for stroke rehabilitation in Canada, highlighting the types of technologies, their effectiveness, and the facilitators and barriers to adoption. These technologies show promise in improving patient outcomes, and their integration into Canadian healthcare systems presents a significant opportunity to enhance stroke rehabilitation. Full article

(1) Background: Digital health technologies (DHTs) are increasingly being utilized to facilitate receiving rehabilitation services remotely, offering innovative solutions to enhance recovery outcomes. This scoping review examines the role of DHT in home-based stroke rehabilitation, focusing on its applications, effectiveness, and limitations. It identifies key advancements and future directions for improving stroke recovery through technological innovations. (2) Methods: Using Arksey and O’Malley’s framework, a systematic search was conducted across multiple databases to identify studies involving DHT for home-based stroke rehabilitation. Eligible studies incorporated technologies for monitoring and evaluation. Data extraction followed PRISMA-ScR guidelines, synthesizing findings across various research designs. (3) Results: Ten studies were reviewed, categorizing technologies into wearable devices, smartphones, and sensor-based solutions. These tools primarily assessed mobility, upper extremity function, cognitive function, daily living activities, and continuous physiological monitoring. High feasibility and usability were reported, though challenges included small sample sizes and user-centered design limitations. (4) Conclusions: Most DHTs used for evaluating and monitoring home-based stroke rehabilitation are wearable and sensor-based, mainly focusing on mobility and upper extremity function. Their application is effective, but limitations remain. Future research should address these gaps to enhance usability and coverage. Full article

This review examines the significant influence of Digital Twins (DTs) and their variant, Digital Human Twins (DHTs), on the healthcare field. DTs represent virtual replicas that encapsulate both medical and physiological characteristics—such as tissues, organs, and biokinetic data—of patients. These virtual models facilitate a deeper understanding of disease progression and enhance the customization and optimization of treatment plans by modeling complex interactions between genetic factors and environmental influences. By establishing dynamic, bidirectional connections between the DTs of physical objects and their digital counterparts, these technologies enable real-time data exchange, thereby transforming electronic health records. Leveraging the increasing availability of extensive historical datasets from clinical trials and real-world sources, AI models can now generate comprehensive predictions of future health outcomes for specific patients in the form of AI-generated DTs. Such models can also offer insights into potential diagnoses, disease progression, and treatment responses. This remarkable progression in healthcare paves the way for precision medicine and personalized health, allowing for high-level individualized medical interventions and therapies. However, the integration of DTs into healthcare faces several challenges, including data security, accessibility, bias, and quality. Addressing these obstacles is crucial to realizing the full potential of DHTs, heralding a new era of personalized, precise, and accurate medicine. Full article

The unprecedented rapid growth of digital health has brought new opportunities to the health field. However, elderly patients with chronic diseases, as an important potential beneficiary group, are affected by the digital divide, leading to unsatisfactory usage of digital health technologies (DHTs). Our study focused on the factors influencing the adoption of DHTs among this vulnerable group. To extend the UTAUT theory, technology anxiety and several demographic predictors were included to address the age characteristics of the respondents. An on-site survey was conducted in general, district, and community hospitals in Shanghai (n = 309). Facilitating conditions negatively influenced technology anxiety. Technology anxiety hindered behavioural intention. Social influence had a significant but negative impact on behavioural intention. Education, whether older adults have had experience with DHTs and previous smartphone usage experiences were significantly associated with technology anxiety. The findings provide valuable information for multiple stakeholders, including family members of elderly users, product designers, and policymakers. Ameliorating facilitating conditions, improving devices’ usage experience, encouraging attempts and focusing on groups with lower educational levels can help to reduce technology anxiety and promote DHT acceptance and use in older age groups. Full article

Nocturnal scratching substantially impairs the quality of life in individuals with skin conditions such as atopic dermatitis (AD). Current clinical measurements of scratch rely on patient-reported outcomes (PROs) on itch over the last 24 h. Such measurements lack objectivity and sensitivity. Digital health technologies (DHTs), such as wearable sensors, have been widely used to capture behaviors in clinical and real-world settings. In this work, we develop and validate a machine learning algorithm using wrist-wearing actigraphy that could objectively quantify nocturnal scratching events, therefore facilitating accurate assessment of disease progression, treatment effectiveness, and overall quality of life in AD patients. A total of seven subjects were enrolled in a study to generate data overnight in an inpatient setting. Several machine learning models were developed, and their performance was compared. Results demonstrated that the best-performing model achieved the F1 score of 0.45 on the test set, accompanied by a precision of 0.44 and a recall of 0.46. Upon satisfactory performance with an expanded subject pool, our automatic scratch detection algorithm holds the potential for objectively assessing sleep quality and disease state in AD patients. This advancement promises to inform and refine therapeutic strategies for individuals with AD. Full article

Digital health technologies (DHTs) at the intersection of health, medical informatics, and business aim to enhance patient care through personalised digital approaches. Ensuring the efficacy and reliability of these innovations demands rigorous clinical validation. A PubMed literature review (January 2006 to July 2023) identified 1250 papers, highlighting growing academic interest. A focused narrative review (January 2018 to July 2023) delved into challenges, highlighting issues such as diverse regulatory landscapes, adoption issues in complex healthcare systems, and a plethora of evaluation frameworks lacking pragmatic guidance. Existing frameworks often omit crucial criteria, neglect empirical evidence, and clinical effectiveness is rarely included as a criterion for DHT quality. The paper underscores the urgency of addressing challenges in accreditation, adoption, business models, and integration to safeguard the quality, efficacy, and safety of DHTs. A pivotal illustration of collaborative efforts to address these challenges is exemplified by the Digital Health Validation Center, dedicated to generating clinical evidence of innovative healthcare technologies and facilitating seamless technology transfer. In conclusion, it is necessary to harmonise evaluation approaches and frameworks, improve regulatory clarity, and commit to collaboration to integrate rigorous clinical validation and empirical evidence throughout the DHT life cycle. Full article

Chronic kidney disease poses a growing global health concern, as an increasing number of patients progress to end-stage kidney disease requiring kidney replacement therapy, presenting various challenges including shortage of care givers and cost-related issues. In this narrative essay, we explore innovative strategies based on in-depth literature analysis that may help healthcare systems face these challenges, with a focus on digital health technologies (DHTs), to enhance removal and ensure better control of broader spectrum of uremic toxins, to optimize resources, improve care and outcomes, and empower patients. Therefore, alternative strategies, such as self-care dialysis, home-based dialysis with the support of teledialysis, need to be developed. Managing ESKD requires an improvement in patient management, emphasizing patient education, caregiver knowledge, and robust digital support systems. The solution involves leveraging DHTs to automate HD, implement automated algorithm-driven controlled HD, remotely monitor patients, provide health education, and enable caregivers with data-driven decision-making. These technologies, including artificial intelligence, aim to enhance care quality, reduce practice variations, and improve treatment outcomes whilst supporting personalized kidney replacement therapy. This narrative essay offers an update on currently available digital health technologies used in the management of HD patients and envisions future technologies that, through digital solutions, potentially empower patients and will more effectively support their HD treatments. Full article

Fatigue is a common symptom in Multiple Sclerosis (MS), and its assessment depends entirely on patient reports. Importantly, managing MS symptoms is increasingly supported by Digital Health Technology (DHT), which includes Mobile Health Technology (mHT). Considering the growing interest, we aimed to synthesise evidence about smartphone applications for the assessment and management of fatigue in MS, as well as to investigate their usability, feasibility, and reliability. We performed a literature search in PubMed, Science Direct, and Embase using a scoping review approach. We included 16 articles and, although many lacked crucial methodological details, DHT was evaluated in all MS clinical subtypes and with disease durations up to more than 20 years. Despite the marked heterogeneity in terms of the employed methods, all documented a high degree of usability, assessed both as feedback from participants and completed tasks. Moreover, the feasibility assessment also showed good results, as apps were able to discriminate between patients with and without fatigue. Importantly, most also showed excellent results in terms of reliability, and some patients reported a reduction in fatigue thanks to mHT. Despite limitations, mHT has been positively evaluated by patients, suggesting a promising role of DHT in the self-management of MS. Full article

Digital health transformation (DHT) has been deployed rapidly worldwide, and many e-health solutions are being invented and improved on an accelerating basis. Healthcare already faces many challenges in terms of reducing costs and allocating resources optimally, while improving provided services. E-solutions in healthcare can be a key enabler for improvements while controlling the budget; however, if the sustainability of those solutions is not assessed, many resources directed towards e-solutions and the cost of adoption/implementation will be wasted. Thus, it is important to assess the sustainability of newly proposed or already in-use e-health solutions. In the literature, there is a paucity of empirically driven comprehensive sustainability models and assessment tools to guide practices in real-world cases. Hence, this study proposes a comprehensive sustainability model for e-health solutions to assess the essential sustainability aspects of e-health solutions and anticipate the likelihood of their sustainability. To build the model, a systematic literature review (SLR) was conducted to extract the e-health sustainability dimensions and elements. In addition, the SLR analyzes the existing definitions of sustainability in healthcare and sustainability assessment methods. The proposed sustainability model has five dimensions, namely; technology, organization, economic, social, and resources. Each dimension has aspects that provide another level of required detail to assess sustainability. In addition, an assessment method was developed for this model to assess the aspects of each dimension, resulting in the overall prediction of the e-health solution’s sustainability level. The sustainability model and the assessment method were validated by three experts in terms of comprehensiveness and applicability to be used in healthcare. Furthermore, a case study was conducted on a Hospital Information System (HIS) of a hospital in Saudi Arabia to evaluate the sustainability model and its assessment method. The sustainability model and assessment method were illustrated to be effective in evaluating the sustainability of e-solutions and more comprehensive and systematic than the evaluation used in the hospital. Full article

Sensor data from digital health technologies (DHTs) used in clinical trials provides a valuable source of information, because of the possibility to combine datasets from different studies, to combine it with other data types, and to reuse it multiple times for various purposes. To date, there exist no standards for capturing or storing DHT biosensor data applicable across modalities and disease areas, and which can also capture the clinical trial and environment-specific aspects, so-called metadata. In this perspectives paper, we propose a metadata framework that divides the DHT metadata into metadata that is independent of the therapeutic area or clinical trial design (concept of interest and context of use), and metadata that is dependent on these factors. We demonstrate how this framework can be applied to data collected with different types of DHTs deployed in the WATCH-PD clinical study of Parkinson’s disease. This framework provides a means to pre-specify and therefore standardize aspects of the use of DHTs, promoting comparability of DHTs across future studies. Full article