Enhancing Healthcare through Sensor-Enabled Digital Twins in Smart Environments: A Comprehensive Analysis.

This comprehensive review investigates the transformative potential of sensor-driven digital twin technology in enhancing healthcare delivery within smart environments. We explore the integration of smart environments with sensor technologies, digital health capabilities, and location-based services, focusing on their impacts on healthcare objectives and outcomes. This work analyzes the foundational technologies, encompassing the Internet of Things (IoT), Internet of Medical Things (IoMT), machine learning (ML), and artificial intelligence (AI), that underpin the functionalities within smart environments. We also examine the unique characteristics of smart homes and smart hospitals, highlighting their potential to revolutionize healthcare delivery through remote patient monitoring, telemedicine, and real-time data sharing. The review presents a novel solution framework leveraging sensor-driven digital twins to address both healthcare needs and user requirements. This framework incorporates wearable health devices, AI-driven health analytics, and a proof-of-concept digital twin application. Furthermore, we explore the role of location-based services (LBS) in smart environments, emphasizing their potential to enhance personalized healthcare interventions and emergency response capabilities. By analyzing the technical advancements in sensor technologies and digital twin applications, this review contributes valuable insights to the evolving landscape of smart environments for healthcare. We identify the opportunities and challenges associated with this emerging field and highlight the need for further research to fully realize its potential to improve healthcare delivery and patient well-being.

"Take the tablet or don't take the tablet?"-A qualitative study of patients' experiences of self-administering anti-cancer medications related to adherence and managing side effects.

PURPOSE: Medication non-adherence is a well-recognised problem in cancer care, negatively impacting health outcomes and healthcare resources. Patient-related factors influencing medication adherence (MA) are complicated and interrelated. There is a need for qualitative research to better understand their underlying interaction processes and patients' needs to facilitate the development of effective patient-tailored complex interventions. This study aimed to explore experiences, perceptions, and needs relating to MA and side effect management of patients who are self-administering anti-cancer treatment. METHODS: Semi-structured audio-recorded interviews with patients who have haematological cancer were conducted. A comparative, iterative, and predominantly inductive thematic analysis approach was employed. RESULTS: Twenty-five patients from a specialist cancer hospital were interviewed. While self-administering cancer medications at home, patients' motivation to adhere was affected by cancer-related physical reactions, fears, cancer literacy and beliefs, and healthcare professional (HCP) and informal support. Patients desired need for regular follow-ups from respectful, encouraging, informative, responsive, and consistent HCPs as part of routine care. Motivated patients can develop high adherence and side effect self-management over time, especially when being supported by HCPs and informal networks. CONCLUSION: Patients with cancer need varied support to medically adhere to and manage side effects at home. HCPs should adapt their practices to meet the patients' expectations to further support them during treatment. We propose a multi-dimensional and technology- and theory-based intervention, which incorporates regular HCP consultations providing tailored education and support to facilitate and maintain patient MA and side effect self-management.

Lessons for Vietnam on the Use of Digital Technologies to Support Patient-Centered Care in Low- and Middle-Income Countries in the Asia-Pacific Region: Scoping Review.

BACKGROUND: A rapidly aging population, a shifting disease burden and the ongoing threat of infectious disease outbreaks pose major concerns for Vietnam's health care system. Health disparities are evident in many parts of the country, especially in rural areas, and the population faces inequitable access to patient-centered health care. Vietnam must therefore explore and implement advanced solutions to the provision of patient-centered care, with a view to reducing pressures on the health care system simultaneously. The use of digital health technologies (DHTs) may be one of these solutions. OBJECTIVE: This study aimed to identify the application of DHTs to support the provision of patient-centered care in low- and middle-income countries in the Asia-Pacific region (APR) and to draw lessons for Vietnam. METHODS: A scoping review was undertaken. Systematic searches of 7 databases were conducted in January 2022 to identify publications on DHTs and patient-centered care in the APR. Thematic analysis was conducted, and DHTs were classified using the National Institute for Health and Care Excellence evidence standards framework for DHTs (tiers A, B, and C). Reporting was in line with the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. RESULTS: Of the 264 publications identified, 45 (17%) met the inclusion criteria. The majority of the DHTs were classified as tier C (15/33, 45%), followed by tier B (14/33, 42%) and tier A (4/33, 12%). At an individual level, DHTs increased accessibility of health care and health-related information, supported individuals in self-management, and led to improvements in clinical and quality-of-life outcomes. At a systems level, DHTs supported patient-centered outcomes by increasing efficiency, reducing strain on health care resources, and supporting patient-centered clinical practice. The most frequently reported enablers for the use of DHTs for patient-centered care included alignment of DHTs with users' individual needs, ease of use, availability of direct support from health care professionals, provision of technical support as well as user education and training, appropriate governance of privacy and security, and cross-sectorial collaboration. Common barriers included low user literacy and digital literacy, limited user access to DHT infrastructure, and a lack of policies and protocols to guide the implementation and use of DHTs. CONCLUSIONS: The use of DHTs is a viable option to increase equitable access to quality, patient-centered care across Vietnam and simultaneously reduce pressures on the health care system. Vietnam can take advantage of the lessons learned by other low- and middle-income countries in the APR when developing a national road map to digital health transformation. Recommendations that Vietnamese policy makers may consider include emphasizing stakeholder engagement, strengthening digital literacy, supporting the improvement of DHT infrastructure, increasing cross-sectorial collaboration, strengthening governance of cybersecurity, and leading the way in DHT uptake.

Smartphone Technology to Remotely Measure Postural Sway during Double- and Single-Leg Squats in Adults with Femoroacetabular Impingement and Those with No Hip Pain.

BACKGROUND: The COVID-19 pandemic has accelerated the demand for utilising telehealth as a major mode of healthcare delivery, with increasing interest in the use of tele-platforms for remote patient assessment. In this context, the use of smartphone technology to measure squat performance in people with and without femoroacetabular impingement (FAI) syndrome has not been reported yet. We developed a novel smartphone application, the TelePhysio app, which allows the clinician to remotely connect to the patient's device and measure their squat performance in real time using the smartphone inertial sensors. The aim of this study was to investigate the association and test-retest reliability of the TelePhysio app in measuring postural sway performance during a double-leg (DLS) and single-leg (SLS) squat task. In addition, the study investigated the ability of TelePhysio to detect differences in DLS and SLS performance between people with FAI and without hip pain. METHODS: A total of 30 healthy (nfemales = 12) young adults and 10 adults (nfemales = 2) with diagnosed FAI syndrome participated in the study. Healthy participants performed DLS and SLS on force plates in our laboratory, and remotely in their homes using the TelePhysio smartphone application. Sway measurements were compared using the centre of pressure (CoP) and smartphone inertial sensor data. A total of 10 participants with FAI (nfemales = 2) performed the squat assessments remotely. Four sway measurements in each axis (x, y, and z) were computed from the TelePhysio inertial sensors: (1) average acceleration magnitude from the mean (aam), (2) root-mean-square acceleration (rms), (3) range acceleration (r), and (4) approximate entropy (apen), with lower values indicating that the movement is more regular, repetitive, and predictable. Differences in TelePhysio squat sway data were compared between DLS and SLS, and between healthy and FAI adults, using analysis of variance with significance set at 0.05. RESULTS: The TelePhysio aam measurements on the x- and y-axes had significant large correlations with the CoP measurements (r = 0.56 and r = 0.71, respectively). The TelePhysio aam measurements demonstrated moderate to substantial between-session reliability values of 0.73 (95% CI 0.62-0.81), 0.85 (95% CI 0.79-0.91), and 0.73 (95% CI 0.62-0.82) for aamx, aamy, and aamz, respectively. The DLS of the FAI participants showed significantly lower aam and apen values in the medio-lateral direction compared to the healthy DLS, healthy SLS, and FAI SLS groups (aam = 0.13, 0.19, 0.29, and 0.29, respectively; and apen = 0.33, 0.45, 0.52, and 0.48, respectively). In the anterior-posterior direction, healthy DLS showed significantly greater aam values compared to the healthy SLS, FAI DLS, and FAI SLS groups (1.26, 0.61, 0.68, and 0.35, respectively). CONCLUSIONS: The TelePhysio app is a valid and reliable method of measuring postural control during DLS and SLS tasks. The application is capable of distinguishing performance levels between DLS and SLS tasks, and between healthy and FAI young adults. The DLS task is sufficient to distinguish the level of performance between healthy and FAI adults. This study validates the use of smartphone technology as a tele-assessment clinical tool for remote squat assessment.

'It's Too nice': Adapting iSupport Lite for Ethnically Diverse Family Carers of a Person with Dementia.

OBJECTIVES: Resources to support dementia carers from ethnically diverse families are limited. We explored carers' and service providers' views on adapting the World Health Organization's iSupport Lite messages to meet their needs. METHODS: Six online workshops were conducted with ethnically diverse family carers and service providers (n = 21) from nine linguistic groups across Australia. Recruitment was via convenience and snowball sampling from existing networks. Data were analyzed using thematic analysis. RESULTS: Participants reported that iSupport Lite over-emphasized support from family and friends and made help-seeking sound "too easy". They wanted messages to dispel notions of carers as "superheroes", demonstrate that caring and help-seeking is stressful and time-consuming, and that poor decision-making and relationship breakdown does occur. Feedback was incorporated to co-produce a revised suite of resources. CONCLUSIONS: Beyond language translation, cultural adaptation using co-design provided participants the opportunity to develop more culturally relevant care resources that meet their needs. These resources will be evaluated for clinical and cost-effectiveness in future research. CLINICAL IMPLICATIONS: By design, multilingual resources for carers must incorporate cultural needs to communicate support messages. If this intervention is effective, it could help to reduce dementia care disparities in ethnically diverse populations in Australia and globally.

A Nudge-Inspired AI-Driven Health Platform for Self-Management of Diabetes.

Diabetes mellitus is a serious chronic disease that affects the blood sugar levels in individuals, with current predictions estimating that nearly 578 million people will be affected by diabetes by 2030. Patients with type II diabetes usually follow a self-management regime as directed by a clinician to help regulate their blood glucose levels. Today, various technology solutions exist to support self-management; however, these solutions tend to be independently built, with little to no research or clinical grounding, which has resulted in poor uptake. In this paper, we propose, develop, and implement a nudge-inspired artificial intelligence (AI)-driven health platform for self-management of diabetes. The proposed platform has been co-designed with patients and clinicians, using the adapted 4-cycle design science research methodology (A4C-DSRM) model. The platform includes (a) a cross-platform mobile application for patients that incorporates a macronutrient detection algorithm for meal recognition and nudge-inspired meal logger, and (b) a web-based application for the clinician to support the self-management regime of patients. Further, the platform incorporates behavioral intervention techniques stemming from nudge theory that aim to support and encourage a sustained change in patient lifestyle. Application of the platform has been demonstrated through an illustrative case study via two exemplars. Further, a technical evaluation is conducted to understand the performance of the MDA to meet the personalization requirements of patients with type II diabetes.

Smartphone as a Disease Screening Tool: A Systematic Review.

Disease screening identifies a disease in an individual/community early to effectively prevent or treat the condition. COVID-19 has restricted hospital visits for screening and other healthcare services resulting in the disruption of screening for cancer, diabetes, and cardiovascular diseases. Smartphone technologies, coupled with built-in sensors and wireless technologies, enable the smartphone to function as a disease-screening and monitoring device with negligible additional costs and potentially higher quality results. Thus, we sought to evaluate the use of smartphone applications for disease screening and the acceptability of this technology in the medical and healthcare sectors. We followed a systematic review process using four databases, including Medline Complete, Web of Science, Embase, and Proquest. We included articles published in English examining smartphone application utilisation in disease screening. Further, we presented and discussed the primary outcomes of the research articles and their statistically significant value. The initial search yielded 1046 studies for the initial title and abstract screening. Of the 105 articles eligible for full-text screening, we selected nine studies and discussed them in detail under four main categories: an overview of the literature reviewed, participant characteristics, disease screening, and technology acceptance. According to our objective, we further evaluated the disease-screening approaches and classified them as clinically administered screening (33%, n = 3), health-worker-administered screening (33%, n = 3), and home-based screening (33%, n = 3). Finally, we analysed the technology acceptance among the users and healthcare practitioners. We observed a significant statistical relationship between smartphone applications and standard clinical screening. We also reviewed user acceptance of these smartphone applications. Hence, we set out critical considerations to provide equitable healthcare solutions without barriers when designing, developing, and deploying smartphone solutions. The findings may increase research opportunities for the evaluation of smartphone solutions as valid and reliable screening solutions.

Validity and Reliability of a Novel Smartphone Tele-Assessment Solution for Quantifying Hip Range of Motion.

BACKGROUND: Tele-health has become a major mode of delivery in patient care, with increasing interest in the use of tele-platforms for remote patient assessment. The use of smartphone technology to measure hip range of motion has been reported previously, with good to excellent validity and reliability. However, these smartphone applications did not provide real-time tele-assessment functionality. We developed a novel smartphone application, the TelePhysio app, which allows the clinician to remotely connect to the patient's device and measure their hip range of motion in real time. The aim of this study was to investigate the concurrent validity and between-sessions reliability of the TelePhysio app. In addition, the study investigated the concurrent validity, between-sessions, and inter-rater reliability of a second tele-assessment approach using video analysis. METHODS: Fifteen participants (nfemales = 6) were assessed in our laboratory (session 1) and at their home (session 2). We assessed maximum voluntary active hip flexion in supine and hip internal and external rotation, in both prone and sitting positions. TelePhysio and video analysis were validated against the laboratory's 3-dimensional motion capture system in session 1, and evaluated for between-sessions reliability in session 2. Video analysis inter-rater reliability was assessed by comparing the analysis of two raters in session 2. RESULTS: The TelePhysio app demonstrated high concurrent validity against the 3D motion capture system (ICCs 0.63-0.83) for all hip movements in all positions, with the exception of hip internal rotation in prone (ICC = 0.48, p = 0.99). The video analysis demonstrated almost perfect concurrent validity against the 3D motion capture system (ICCs 0.85-0.94) for all hip movements in all positions, with the exception of hip internal rotation in prone (ICC = 0.44, p = 0.01). The TelePhysio and video analysis demonstrated good between-sessions reliability for hip external rotation and hip flexion, ICC 0.64 and 0.62, respectively. The between-sessions reliability of hip internal and external rotation for both TelePhysio and video analysis was fair (ICCs 0.36-0.63). Inter-rater reliability ICCs for the video analysis were 0.59 for hip flexion and 0.87-0.95 for the hip rotation range. CONCLUSIONS: Both tele-assessment approaches, using either a smartphone application or video analysis, demonstrate good to excellent concurrent validity, and moderate to substantial between-sessions reliability in measuring hip rotation and flexion range of motion, but less in internal hip rotation in the prone position. Thus, it is recommended that the seated position be used when assessing hip internal rotation. The use of a smartphone to remotely assess hip range of motion is an appropriate, effective, and low-cost alternative to the face-to-face assessments. This method provides a simple, cost effective, and accessible patient assessment tool with no additional cost. This study validates the use of smartphone technology as a tele-assessment tool for remote hip range of motion assessment.

Crowdsourcing Operational and Design Flaws of Diabetes Mobile Apps.

Unfortunately, many of the diabetes mobile apps have operational and design flaws that are debarring users from maximizing from the self-management paradigm. We, therefore, aim to identify the markers of operational and design flaws of diabetes mobile apps to facilitate a better user-centred design. e crowdsourced negative user review comments (rating score: 1-3) of 47 diabetes mobile apps from the google play store. A total of 781 negative user comments (rating score 1-3) from the apps are coded to identify and categorize the themes relating to the operational and design flaws. The operational and design flaws account for 50.32% of the challenges faced by the unhappy diabetes mobile apps users. Among them, 44.73% have issues with app crashing, 17.3% are concerned about device compatibility that inhibits seamless operations, 9.67% are worried about the problem of data uploading. Poor design is a worry to 19.29% of the users who complain of the crowded user interface, poor data management, poor analytics, difficulty scheduling doctors' appointments, and transferring data. More patients with diabetes can be encouraged to continue using diabetes mobile apps for self-management of diabetes through improved design and a pace-wise software advancement to match the ever-growing enhancements in android operating systems and telecommunication devices. This will help to counter most of the challenges identified in this study.

Are serious games too serious? Diffusion of wearable technologies and the creation of a diffusion of serious games model.

Today globally, more people die from chronic diseases than from war and terrorism. This is not due to aging alone but also because we lead unhealthy lifestyles with little or no exercise and typically consume food with poor nutritional content. This paper proffers the design science research method to create an artefact that can help people study the diffusion of serious games. The ultimate goal of the study is to create a serious game that can help people to improve their balance in physical exercise, nutrition and well-being. To do this, first we conducted 97 interviews to study if wearables can be used for gathering health data. Analysis indicates that designers, manufacturers, and developers of wearables and associated software and apps should make their devices reliable, relevant, and user friendly. To increase the diffusion, adoption, and habitual usage of wearables key issues such as privacy and security need to be addressed as well. Then, we created a paper prototype and conducted a further 32 interviews to validate the first prototype of the game, especially with respect to the diffusion possibilities of the game. Results are positive from a formal technology acceptance point of view showing relevance and usefulness. But informally in the open questions some limitations also became visible. In particular, ease of use is extremely important for acceptance and calling it a game can in fact be an obstruction. Moreover, the artefact should not be patronizing and age differences can also pose problems, hence the title not to make the serious game too serious. Future research plans to address these problems in the next iteration while the future implementation plan seeks for big platforms or companies to diffuse the serious game. A key theoretical contribution of this research is the identification of habit as a potential dependent variable for the intention to use wearables and the development of a diffusion model for serious games. The hedonic perspective is added to the model as well as trust and perceived risks. This model ends the cycle of critical design with an improvement of theory as result contributing to the societal goal of decreasing Obesities and Diabetes.

Intelligent therapeutic decision support for 30 days readmission of diabetic patients with different comorbidities.

The significance of medication therapy in managing comorbid diabetes is vital for maintaining the overall wellness of patients and reducing the cost of healthcare. Thus, using appropriate medication or medication combinations will be necessary for improved person-centred care and reduce complications associated with diagnosis and treatment. This study explains an intelligent decision support framework for managing 30 days unplanned readmission (30_URD) of comorbid diabetes using the Random Forest (RF) algorithm and Bayesian Network (BN) model. After the analysis of the medical records of 101,756 de-identified diabetic patients treated with 21 medications for 28 comorbidity combinations, the optimal medications for minimizing the likelihood of early readmissions were determined. This approach can help for identifying and managing most vulnerable patients thereby giving room to enhance post-discharge monitoring through clinical specialist supports to build critical-self management skills that will minimize the cost of diabetes care.

Exploring nurses' reactions to a novel technology to support acute health care delivery.

AIMS AND OBJECTIVES: To explore nurses' reactions to new novel technology for acute health care. BACKGROUND: Past failures of technology developers to deliver products that meet nurses' needs have led to resistance and reluctance in the technology adoption process. Thus, involving nurses in a collaborative process from early conceptualisation serves to inform design reflective upon current clinical practice, facilitating the cementing of 'vision' and expectations of the technology. DESIGN: An exploratory descriptive design to capture nurses' immediate impressions. METHODS: Four focus groups (52 nurses from medical and surgical wards at two hospitals in Australia; one private and one public). RESULTS: Nursing reactions towards the new technology illustrated a variance in barrier and enabler comments across multiple domains of the Theoretical Domains Framework. Most challenging for nurses were the perceived threat to their clinical skill, and the potential capability of the novel technology to capture their clinical workflow. Enabling reactions included visions that this could help integrate care between departments; help management and support of nursing processes; and coordinating their patients care between clinicians. Nurses' reactions differed across hospital sites, influenced by their experiences of using technology. For example, Site 1 nurses reported wide variability in their distribution of barrier and enabling comments and nurses at Site 2, where technology was prevalent, reported mostly positive responses. CONCLUSION: This early involvement offered nursing input and facilitated understanding of the potential capabilities of novel technology to support nursing work, particularly the characteristics seen as potentially beneficial (enabling technology) and those conflicting (barrier technology) with the delivery of both safe and effective patient care. RELEVANCE TO CLINICAL PRACTICE: Collaborative involvement of nurses from the early conceptualisation of technology development brings benefits that increase the likelihood of successful use of a tool intended to support the delivery of safe and efficient patient care.

Digital Twins for More Precise and Personalized Treatment.

The use of Digital Twins (DTs) or the digital replicas of physical entities has provided benefits to several industry sectors, most notably manufacturing. To date, the application of DTs in the healthcare sector has been minimal, however. But, as pressure increases for more precise and personalized treatments, it behooves us to investigate the potential for DTs in the healthcare context. As a proof-of-concept demonstration prior to working with real patients, we attempt in this paper, to explore the potential for creating and using DTs. We do this in a synthetic environment at this stage, making use of data that is all computer-generated. DTs of synthetic present patients are created making use of data of synthetic past patients. In the real world, the clinical objective for creating such DTs of real patients would be to enable enhanced real-time clinical decision support to enable more precise and personalized care. The objective of the numerical experiment reported in this paper, is to envisage the possibilities and challenges of such an approach. We attempt to better understand the strengths and weaknesses of applying DTs in the healthcare context to support more precise and personalized treatments.

Web-Based Intervention for Multilingual Family Carers of People with Dementia: Insights from the DrawCare Study.

Addressing the needs of ethnically diverse multilingual people can be challenging in environments that are non-native to them. The consequences of this issue become more significant in healthcare contexts. Insights from the DrawCare study-an Australian study that explores the effectiveness of a web-based intervention for multilingual family carers of people with dementia-are presented illustrating the enabling role of digital health.

Non-invasive blood glucose monitoring technology in diabetes management: review.

Diabetes is one of the leading non-communicable diseases globally, adversely impacting an individual's quality of life and adding a considerable burden to the healthcare systems. The necessity for frequent blood glucose (BG) monitoring and the inconveniences associated with self-monitoring of BG, such as pain and discomfort, has motivated the development of non-invasive BG approaches. However, the current research progress is slow, and only a few BG self-monitoring devices have made considerable progress. Hence, we evaluate the available non-invasive glucose monitoring technologies validated against BG recordings to provide future research direction to design, develop, and deploy self-monitoring of BG with integrated emerging technologies. We searched five databases, Embase, MEDLINE, Proquest, Scopus, and Web of Science, to assess the non-invasive technology's scope in the diabetes management paradigm published from 2000 to 2020. A total of three approaches to non-invasive screening, including saliva, skin, and breath, were identified and discussed. We observed a statistical relationship between BG measurements obtained from non-invasive methods and standard clinical measures. Opportunities exist for future research to advance research progress and facilitate early technology adoption for healthcare practice. The results promise clinical validity; however, formulating regulatory guidelines could foresee the deployment of approved non-invasive BG monitoring technologies in healthcare practice. Further, research prospects are there to design, develop, and deploy integrated diabetes management systems with mobile technologies, data analytics, and the internet of things (IoT) to deliver a personalised monitoring system.

Intelligent decision support systems for dementia care: A scoping review.

In the context of dementia care, Artificial Intelligence (AI) powered clinical decision support systems have the potential to enhance diagnosis and management. However, the scope and challenges of applying these technologies remain unclear. This scoping review aims to investigate the current state of AI applications in the development of intelligent decision support systems for dementia care. We conducted a comprehensive scoping review of empirical studies that utilised AI-powered clinical decision support systems in dementia care. The results indicate that AI applications in dementia care primarily focus on diagnosis, with limited attention to other aspects outlined in the World Health Organization (WHO) Global Action Plan on the Public Health Response to Dementia 2017-2025 (GAPD). A trifecta of challenges, encompassing data availability, cost considerations, and AI algorithm performance, emerges as noteworthy barriers in adoption of AI applications in dementia care. To address these challenges and enhance AI reliability, we propose a novel approach: a digital twin-based patient journey model. Future research should address identified gaps in GAPD action areas, navigate data-related obstacles, and explore the implementation of digital twins. Additionally, it is imperative to emphasize that addressing trust and combating the stigma associated with AI in healthcare should be a central focus of future research directions.

Co-Design, Development, and Evaluation of a Mobile Solution to Improve Medication Adherence in Cancer: Design Science Research Approach.

BACKGROUND: Medication nonadherence negatively impacts the health outcomes of people with cancer as well as health care costs. Digital technologies present opportunities to address this health issue. However, there is limited evidence on how to develop digital interventions that meet the needs of people with cancer, are perceived as useful, and are potentially effective in improving medication adherence. OBJECTIVE: The objective of this study was to co-design, develop, and preliminarily evaluate an innovative mobile health solution called Safety and Adherence to Medication and Self-Care Advice in Oncology (SAMSON) to improve medication adherence among people with cancer. METHODS: Using the 4 cycles and 6 processes of design science research methodology, we co-designed and developed a medication adherence solution for people with cancer. First, we conducted a literature review on medication adherence in cancer and a systematic review of current interventions to address this issue. Behavioral science research was used to conceptualize the design features of SAMSON. Second, we conducted 2 design phases: prototype design and final feature design. Last, we conducted a mixed methods study on patients with hematological cancer over 6 weeks to evaluate the mobile solution. RESULTS: The developed mobile solution, consisting of a mobile app, a web portal, and a cloud-based database, includes 5 modules: medication reminder and acknowledgment, symptom assessment and management, reinforcement, patient profile, and reporting. The quantitative study (n=30) showed that SAMSON was easy to use (21/27, 78%). The app was engaging (18/27, 67%), informative, increased user interactions, and well organized (19/27, 70%). Most of the participants (21/27, 78%) commented that SAMSON's activities could help to improve their adherence to cancer treatments, and more than half of them (17/27, 63%) would recommend the app to their peers. The qualitative study (n=25) revealed that SAMSON was perceived as helpful in terms of reminding, supporting, and informing patients. Possible barriers to using SAMSON include the app glitches and users' technical inexperience. Further needs to refine the solution were also identified. Technical improvements and design enhancements will be incorporated into the subsequent iteration. CONCLUSIONS: This study demonstrates the successful application of behavioral science research and design science research methodology to design and develop a mobile solution for patients with cancer to be more adherent. The study also highlights the importance of applying rigorous methodologies in developing effective and patient-centered digital intervention solutions.

Trends in blood pressure changes and hypertension prevalence in Australian adults before and during the COVID-19 pandemic.

Efforts to limit the impact of the coronavirus disease (COVID-19) pandemic led to the implementation of public health measures and reallocation of health resources. To investigate trends in blood pressure (BP), hypertension and BMI in the Australian population during the COVID-19 pandemic, data from publicly accessible health stations were analyzed. Average BP and BMI measured by the SiSU Health Station network in Australia in over 1.6 million health screenings were compared between the years 2018 and 2021. Additionally, paired trajectories for BP and BMI development before and during the COVID-19 pandemic were calculated. Comparisons between pre-COVID years and post-COVID years of 2018 versus 2020, 2019 versus 2020, 2018 versus 2021, and 2019 versus 2021 showed increases in average adjusted systolic BP of 2.0, 1.7, 2.6, and 2.3 mmHg, respectively. Paired analysis of longitudinal data showed an overall increase in the trajectory of systolic BP of 3.2 mmHg between pre- and post-COVID years. The prevalence of hypertension in users of the health stations increased by approximately 25% in the years 2020-2021. Similar trends were seen for BMI. Data from public Australian health stations indicated a strong trend toward higher BP during the COVID-19 pandemic. At the population level, BP increments have been shown to markedly increase cardiovascular disease risk. Anti-pandemic measures need to be carefully evaluated in terms of secondary public health effects and health support systems extended to effectively target cardiovascular risk.

Automatic user sentiments extraction from diabetes mobile apps - An evaluation of reviews with machine learning.

Using diabetes mobile apps for self-management of diabetes is one of the emerging strategies for controlling blood sugar levels and maintaining the wellness of patients with diabetes. This study aims to develop a strategy for thematically extracting user comments from diabetes mobile apps to understand the concern of patients with diabetes. Hence, 2678 user comments obtained from the Google Play Store are thematically analyzed with Non-negative Matrix Factorization (NMF) to identify the themes for describing positive, neutral, and negative sentiments. These themes are used as the ground truth for developing a 10-fold cross-validation ensemble Multilayer Artificial Neural Network (ANN) model following the Bag of Word (BOW) analysis of lemmatized user comments. The result shows that a total of 41.24% of positive sentimental users identified the diabetes mobile apps as Effective for Blood Sugar Monitoring (EBSM), 32.36% with neutral sentiments are mostly impressed by the Information Quality (IQ), whereas 40.81% of unhappy users are worried about the Poor Information Quality (PIQ). The prediction accuracy of the ANN model is 89%-97%, which is 5%-48% better than other predominant algorithms. It can be concluded from this study that diabetes mobile apps with a simple user interface, effective data storage and security, medication adherence, and doctor appointment scheduling are preferred by patients with diabetes.

Sentiments prediction and thematic analysis for diabetes mobile apps using Embedded Deep Neural Networks and Latent Dirichlet Allocation.

The increasing reliance on mobile health for managing disease conditions has opened a new frontier in digital health, thus, the need for understanding what constitutes positive and negative sentiments of the various apps. This paper relies on Embedded Deep Neural Networks (E-DNN), Kmeans, and Latent Dirichlet Allocation (LDA) for predicting the sentiments of diabetes mobile apps users and identifying the themes and sub-themes of positive and negative sentimental users. A total of 38,640 comments from 39 diabetes mobile apps obtained from the google play store are analyzed and accuracy of 87.67 % ± 2.57 % was obtained from a 10-fold leave-one-out cross-validation. This accuracy is 2.95 % - 18.71 % better than other predominant algorithms used for sentiment analysis and 3.47 % - 20.17 % better than the results obtained by previous researchers. The study also identified the challenges of diabetes mobile apps usage to include safety and security issues, outdated information for diabetes management, clumsy user interface, and difficulty controlling operations. The positives of the apps are ease of operation, lifestyle management, effectiveness in communication and control, and data management capabilities.