Health Care Professionals' and Parents' Perspectives on the Use of AI for Pain Monitoring in the Neonatal Intensive Care Unit: Multisite Qualitative Study.

BACKGROUND: The use of artificial intelligence (AI) for pain assessment has the potential to address historical challenges in infant pain assessment. There is a dearth of information on the perceived benefits and barriers to the implementation of AI for neonatal pain monitoring in the neonatal intensive care unit (NICU) from the perspective of health care professionals (HCPs) and parents. This qualitative analysis provides novel data obtained from 2 large tertiary care hospitals in Canada and the United Kingdom. OBJECTIVE: The aim of the study is to explore the perspectives of HCPs and parents regarding the use of AI for pain assessment in the NICU. METHODS: In total, 20 HCPs and 20 parents of preterm infants were recruited and consented to participate from February 2020 to October 2022 in interviews asking about AI use for pain assessment in the NICU, potential benefits of the technology, and potential barriers to use. RESULTS: The 40 participants included 20 HCPs (17 women and 3 men) with an average of 19.4 (SD 10.69) years of experience in the NICU and 20 parents (mean age 34.4, SD 5.42 years) of preterm infants who were on average 43 (SD 30.34) days old. Six themes from the perspective of HCPs were identified: regular use of technology in the NICU, concerns with regard to AI integration, the potential to improve patient care, requirements for implementation, AI as a tool for pain assessment, and ethical considerations. Seven parent themes included the potential for improved care, increased parental distress, support for parents regarding AI, the impact on parent engagement, the importance of human care, requirements for integration, and the desire for choice in its use. A consistent theme was the importance of AI as a tool to inform clinical decision-making and not replace it. CONCLUSIONS: HCPs and parents expressed generally positive sentiments about the potential use of AI for pain assessment in the NICU, with HCPs highlighting important ethical considerations. This study identifies critical methodological and ethical perspectives from key stakeholders that should be noted by any team considering the creation and implementation of AI for pain monitoring in the NICU.

Clinical Validation of Digital Healthcare Solutions: State of the Art, Challenges and Opportunities.

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.

Adoption of Diabetes Technology in Denmark: Continuous Glucose Monitor as Time-Machine.

Health technologies to monitor glucose values are an important part of daily diabetes self-care. Based on 12 months of fieldwork in Denmark with 14 people with type 2 diabetes, I explore people's experience of living with Continuous Glucose Monitoring. This new technology automatically measures glucose levels throughout the day but is not yet common in type 2 diabetes treatment in Denmark. In this article, I capture the social shaping of Continuous Glucose Monitoring, employing the concept of time. I show how adoption of the technology is embedded in a form of biographical time. This refers to people's use of the technology linked to their stories about themselves. Drawing on a notion of habitus, people's embodied past experiences and future prospects come to shape its use, I propose. My main claim is that while people with diabetes implement the technology into their lives in unique ways, adapting it to their circumstances and social conditions, practice of Continuous Glucose Monitoring reproduce social structures. This is evinced, I argue, in people's tinkering with the technology and the frames of reference used to inform it. I introduce the term "tinkering in time", highlighting the introduction of new health technology within the frame of lived human time.

Who uses connected health technologies after a cancer diagnosis? evidence from the US Health Information National Trends Survey.

PURPOSE: As the number of people living with and beyond cancer increases, connected health technologies offer promise to enhance access to care and support, while reducing costs. However, uptake of connected health technologies may vary depending on sociodemographic and health-related variables. This study aimed to investigate demographic and health predictors of connected health technology use among people living with and beyond cancer. METHODS: Cross-sectional data from the US Health Information National Trends Survey Version 5 Cycle 4 (H5c4) was used. Regression analysis was used to examine associations between sociodemographic factors and the use of connected health technologies. The sample was restricted to individuals who self-reported a cancer diagnosis or history of cancer. RESULTS: In this cycle, 626 respondents self-reported a cancer diagnosis, with 41.1% using connected health technologies (health and wellness apps and/or wearable devices). Most were female (58.9%) and white (82.5%); 43.4% had graduated college or higher education. One third (33.6%) had a household income of $75,000 or more. Respondents who were younger, have higher education, were living as married, had higher incomes, had higher self-rated health and had higher health-related self-efficacy were significantly more likely to use connected health technologies. There were no significant associations between gender, race, stratum, time since diagnosis, history of anxiety or depression, and use of connected health technologies among people living with and beyond cancer. CONCLUSIONS: Connected health technology use among people living with and beyond cancer is associated with sociodemographic factors. Future research should examine these demographic disparities as the use of connected health technologies in healthcare continues to gather momentum. IMPLICATIONS FOR CANCER SURVIVORS: The study underscores a disparity in connected heath technology usage among people living with and beyond cancer. There is a pressing need for research into adoption barriers and interventions to ensure equitable digital healthcare integration among this population, especially with the heightened adoption of technology post COVID-19 pandemic.

Evaluating the Energy Efficiency of Popular US Smartphone Health Care Apps: Comparative Analysis Study Toward Sustainable Health and Nutrition Apps Practices.

BACKGROUND: The emergence of smartphones has sparked a transformation across multiple fields, with health care being one of the most notable due to the advent of mobile health (mHealth) apps. As mHealth apps have gained popularity, there is a need to understand their energy consumption patterns as an integral part of the evolving landscape of health care technologies. OBJECTIVE: This study aims to identify the key contributors to elevated energy consumption in mHealth apps and suggest methods for their optimization, addressing a significant void in our comprehension of the energy dynamics at play within mHealth apps. METHODS: Through quantitative comparative analysis of 10 prominent mHealth apps available on Android platforms within the United States, this study examined factors contributing to high energy consumption. The analysis included descriptive statistics, comparative analysis using ANOVA, and regression analysis to examine how certain factors impact energy use and consumption. RESULTS: Observed energy use variances in mHealth apps stemmed from user interactions, features, and underlying technology. Descriptive analysis revealed variability in app energy consumption (150-310 milliwatt-hours), highlighting the influence of user interaction and app complexity. ANOVA verified these findings, indicating the critical role of engagement and functionality. Regression modeling (energy consumption = ß0 + ß1 × notification frequency + ß2 × GPS use + ß3 × app complexity + ε), with statistically significant P values (notification frequency with a P value of .01, GPS use with a P value of .05, and app complexity with a P value of .03), further quantified these bases' effects on energy use. CONCLUSIONS: The observed differences in the energy consumption of dietary apps reaffirm the need for a multidisciplinary approach to bring together app developers, end users, and health care experts to foster improved energy conservation practice while achieving a balance between sustainable practice and user experience. More research is needed to better understand how to scale-up consumer engagement to achieve sustainable development goal 12 on responsible consumption and production.

HCI-modelling for improving the clinical usability of digital health technologies.

INTRODUCTION: Digital Health Technologies (DHTs) have been shown to have variable usability as measured by efficiency, effectiveness and user satisfaction despite large-scale government projects to regulate and standardise user interface (UI) design. We hypothesised that Human-Computer Interaction (HCI) modelling could improve the methodology for DHT design and regulation, and support the creation of future evidence-based UI standards and guidelines for DHTs. METHODOLOGY: Using a Design Science Research (DSR) framework, we developed novel UI components that adhered to existing standards and guidelines (combining the NHS Common User Interface (CUI) standard and the NHS Design System). We firstly evaluated the Patient Banner UI component for compliance with the two guidelines and then used HCI-modelling to evaluate the "Add New Patient" workflow to measure time to task completion and cognitive load. RESULTS: Combining the two guidelines to produce new UI elements is technically feasible for the Patient Banner and the Patient Name Input components. There are some inconsistencies between the NHS Design System and the NHS CUI when implementing the Patient Banner. HCI-modelling successfully quantified challenges adhering to the NHS CUI and the NHS Design system for the "Add New Patient" workflow. DISCUSSION: We successfully developed new design artefacts combing two major design guidelines for DHTs. By quantifying usability issues using HCI-modelling, we have demonstrated the feasibility of a methodology that combines HCI-modelling into a human-centred design (HCD) process could enable the development of standardised UI elements for DHTs that is more scientifically robust than HCD alone. CONCLUSION: Combining HCI-modelling and Human-Centred Design could improve scientific progress towards developing safer and more user-friendly DHTs.

Filling the gaps in the evaluation and selection of mobile health technologies in respiratory medicine.

INTRODUCTION: Mobile health (mHealth) technology in respiratory medicine is a fast-growing and promising digital technology that is popular among patients and healthcare providers (HCPs). They provide reminders and step-by-step instructions for the correct inhalation technique, monitor patients' adherence to treatment, and facilitate communication between patients and HCPs. AREAS COVERED: While numerous mHealth apps have been developed over the years, most applications do not have supporting evidence. Selecting the best mHealth app in respiratory medicine is challenging due to limited studies carrying out mHealth app selection. Although mHealth technologies play an important part in the future of respiratory medicine, there is no single guide on the evaluation and selection of mHealth technologies for patients with pulmonary diseases. This paper aims to provide an overview of mHealth technologies, particularly emphasizing digital inhalers and standalone applications used in asthma. Additionally, it offers insights into the evaluation, selection, and pertinent considerations surrounding mHealth applications in respiratory medicine. EXPERT OPINION: Evaluating mHealth apps will take time, resources, and collaboration between stakeholders such as governmental regulatory bodies, subject-matter experts, and industry representatives. Filling the gaps in the evaluation and selection of the mHealth app will improve clinical decision-making, personalized treatments, self-management and disease monitoring in respiratory medicine.

User-Centered Framework for Implementation of Technology (UFIT): Development of an Integrated Framework for Designing Clinical Decision Support Tools Packaged With Tailored Implementation Strategies.

BACKGROUND: Electronic health record-based clinical decision support (CDS) tools can facilitate the adoption of evidence into practice. Yet, the impact of CDS beyond single-site implementation is often limited by dissemination and implementation barriers related to site- and user-specific variation in workflows and behaviors. The translation of evidence-based CDS from initial development to implementation in heterogeneous environments requires a framework that assures careful balancing of fidelity to core functional elements with adaptations to ensure compatibility with new contexts. OBJECTIVE: This study aims to develop and apply a framework to guide tailoring and implementing CDS across diverse clinical settings. METHODS: In preparation for a multisite trial implementing CDS for pediatric overweight or obesity in primary care, we developed the User-Centered Framework for Implementation of Technology (UFIT), a framework that integrates principles from user-centered design (UCD), human factors/ergonomics theories, and implementation science to guide both CDS adaptation and tailoring of related implementation strategies. Our transdisciplinary study team conducted semistructured interviews with pediatric primary care clinicians and a diverse group of stakeholders from 3 health systems in the northeastern, midwestern, and southeastern United States to inform and apply the framework for our formative evaluation. RESULTS: We conducted 41 qualitative interviews with primary care clinicians (n=21) and other stakeholders (n=20). Our workflow analysis found 3 primary ways in which clinicians interact with the electronic health record during primary care well-child visits identifying opportunities for decision support. Additionally, we identified differences in practice patterns across contexts necessitating a multiprong design approach to support a variety of workflows, user needs, preferences, and implementation strategies. CONCLUSIONS: UFIT integrates theories and guidance from UCD, human factors/ergonomics, and implementation science to promote fit with local contexts for optimal outcomes. The components of UFIT were used to guide the development of Improving Pediatric Obesity Practice Using Prompts, an integrated package comprising CDS for obesity or overweight treatment with tailored implementation strategies. TRIAL REGISTRATION: ClinicalTrials.gov NCT05627011; https://clinicaltrials.gov/study/NCT05627011.

Community-Dwelling Older Adults' Readiness for Adopting Digital Health Technologies: Cross-Sectional Survey Study.

BACKGROUND: Digital health technologies offer the potential to improve the daily lives of older adults, maintain their health efficiently, and allow aging in place. Despite increasing evidence of benefits and advantages, readiness for adopting digital interventions among older people remains underexplored. OBJECTIVE: This study aims to explore the relationships between sociodemographic-, health-, and lifestyle-related factors and technology use in everyday life and community-dwelling older adults' readiness to adopt telemedicine, smartphones with texting apps, wearables, and robotics. METHODS: This was a cross-sectional, population-based survey study with a stratified probabilistic sample of adults aged 75 years or older living in South Tyrol (autonomous province of Bolzano/Bozen, Italy). A random sample of 3600 community-dwelling older adults living at home was invited to complete a questionnaire including single items (older adults' readiness to use health technology) and scales (PRISMA-7; Program of Research on Integration of Services for the Maintenance of Autonomy). Descriptive and logistic regression analyses were performed to analyze the data. RESULTS: In total, 1695 community-dwelling older adults completed the survey (for a response rate of 47%). In terms of potential digital health technology adoption, wearable devices were favored by 33.7% (n=571), telemedicine by 30.1% (n=510), smartphones and texting apps by 24.5% (n=416), and assistant robots by 13.7% (n=232). Sociodemographic-, health- and lifestyle-related factors, as well as the use of technology in everyday life, played a significant role in explaining readiness to adopt digital health technologies. For telemedicine, age ≥85 years (odds ratio [OR] 0.74, 95% CI 0.56-0.96), financial constraints (OR 0.68, 95% CI 0.49-0.95), and less than 2 hours of physical activity per week (OR 0.75, 95% CI 0.58-0.98) were associated with nonreadiness, while Italian-speaking participants (OR 1.54, 95% CI 1.16-2.05) and those regularly using computers (OR 1.74, 95% CI 1.16-2.60), smartphones (OR 1.69, 95% CI 1.22-2.35), and the internet (OR 2.26, 95% CI 1.47-3.49) reported readiness for adoption. CONCLUSIONS: Community-dwelling older adults display varied readiness toward the adoption of digital health technologies, influenced by age, mother tongue, living situation, financial resources, physical activity, and current use of technology. The findings underscore the need for tailored interventions and educational programs to boost digital health technology adoption among community-dwelling older adults.

Available rehabilitation technology with the potential to be incorporated into the clinical practice of physiotherapists: A systematic review.

Background: The development of prototypes capable of intervening in the area of rehabilitation in physical therapy clinical practice activities that were previously carried out in a traditional way, that is, manually, demonstrates how technology is having an impact on professional careers such as physiotherapy. Objective: The purpose of this study is to present a comprehensive examination of various technologies employed in the facilitation of patient rehabilitation, with a focus on their potential integration within the clinical practice of physical therapists. Methods: We conducted a systematic search in four electronic databases (CINAHL, Embase, PEDro, and PubMed) for research on rehabilitation technologies. The eligible studies should demonstrate a clear utilization of technology in various aspects of the clinical approach to the rehabilitation process and have been published between 2000 and 2021 in either Portuguese or English. Results: A total of 18 articles that satisfied the selection criteria were included in the study. The studies were classified into four distinct categories of rehabilitation technologies, which were determined by the specific characteristics of the technology employed and its integration with the therapeutic approach to rehabilitation. These categories include digital technologies, artificial intelligence and/or robotics, virtual technologies, and hybrid technologies. Implications on Physiotherapy Practice: Rehabilitation technologies possess the capacity to effectively facilitate clinical activities performed by physical therapy professionals, including injury prevention, movement monitoring, and coordination of rehabilitation programs, with minimal or negligible intervention from the physical therapist. Further research is required to ascertain the precise capabilities of various technologies in collaborating with physiotherapists to deliver comprehensive care for patients' physical well-being, encompassing both therapeutic and preventive approaches. Trial Registration: PROSPERO registration number CRD42020222288.

The Effect of Using a Remote Patient Management Platform in Optimizing Guideline-Directed Medical Therapy in Heart Failure Patients: A Randomized Controlled Trial.

BACKGROUND: Guideline-directed medical therapy (GDMT) remains underutilized in patients with heart failure with reduced ejection fraction, leading to morbidity and mortality. OBJECTIVES: The Medly Titrate (Use of Telemonitoring to Facilitate Heart Failure Mediation Titration) study was an open-label, randomized controlled trial to determine whether remote medication titration for patients with heart failure with reduced ejection fraction was more effective than usual care (UC). METHODS: In this study, 108 patients were randomized to remote GDMT titration through the Medly heart failure program (n = 56) vs UC (n = 52). The primary outcome was the proportion of patients completing GDMT titration at 6 months. Secondary outcomes included the number of clinic visits and time required to achieve titration, patient health outcomes, and health care utilization, including urgent clinic/emergency department visits and hospitalization. RESULTS: At 6 months, GDMT titration was completed in 82.1% (95% CI: 71.2%-90.8%) of patients in the intervention arm vs 53.8% in UC (95% CI: 41.1%-67.7%; P = 0.001). Remote titration required fewer in-person (1.62 ± 1.09 vs 2.42 ± 1.65; P = 0.004) and virtual clinic visits (0.50 ± 1.08 vs 1.29 ± 1.86; P = 0.009) to complete titration. Median time to optimization was shorter with remote titration (3.42 months [Q1-Q3: 2.99-4.04 months] vs 5.47 months [Q1-Q3: 4.14-7.33 months]; P < 0.001). The number of urgent clinic/emergency department visits (incidence rate ratio of remote vs control groups: 0.90 [95% CI: 0.53-1.56]; P = 0.70) were similar between groups, with a reduction in all-cause hospitalization with remote titration (incidence rate ratio: 0.55 [95% CI: 0.31-0.97]; P = 0.042). CONCLUSIONS: Remote titration of GDMT in heart failure with reduced ejection fraction was effective, safe, feasible, and increased the proportion of patients achieving target doses, in a shorter period of time with no excess adverse events compared with UC. (Use of Telemonitoring to Facilitate Heart Failure Mediation Titration [Medly Titrate]; NCT04205513).

Development of a Value Assessment Framework for Pediatric Health Technologies Using Multicriteria Decision Analysis: Expanding the Value Lens for Funding Decision Making.

OBJECTIVES: A health technology assessment (HTA) does not systematically account for the circumstances and needs of children and youth. To supplement HTA processes, we aimed to develop a child-tailored value assessment framework using a multicriteria decision analysis approach. METHODS: We constructed a multicriteria-decision-analysis-based model in multiple phases to create the Comprehensive Assessment of Technologies for Child Health (CATCH) framework. Using a modified Delphi process with stakeholders having broad disciplinary and geographic variation (N = 23), we refined previously generated criteria and developed rank-based weights. We established a criterion-pertinent scoring rubric for assessing incremental benefits of new drugs. Three clinicians independently assessed comprehension by pilotscoring 9 drugs. We then validated CATCH for 2 childhood cancer therapies through structured deliberation with an expert panel (N = 10), obtaining individual scores, consensus scores, and verbal feedback. Analyses included descriptive statistics, thematic analysis, exploratory disagreement indices, and sensitivity analysis. RESULTS: The modified Delphi process yielded 10 criteria, based on absolute importance/relevance and agreed importance (median disagreement indices = 0.34): Effectiveness, Child-specific Health-related Quality of Life, Disease Severity, Unmet Need, Therapeutic Safety, Equity, Family Impacts, Life-course Development, Rarity, and Fair Share of Life. Pilot scoring resulted in adjusted criteria definitions and more precise score-scaling guidelines. Validation panelists endorsed the framework's key modifiers of value. Modes of their individual prescores aligned closely with deliberative consensus scores. CONCLUSIONS: We iteratively developed a value assessment framework that captures dimensions of child-specific health and nonhealth gains. CATCH could improve the richness and relevance of HTA decision making for children in Canada and comparable health systems.

Stepping Forward: A Scoping Systematic Literature Review on the Health Outcomes of Smart Sensor Technologies for Diabetic Foot Ulcers.

Diabetic foot ulcers (DFUs) pose a significant challenge in diabetes care, demanding advanced approaches for effective prevention and management. Smart insoles using sensor technology have emerged as promising tools to address the challenges associated with DFU and neuropathy. By recognizing the pivotal role of smart insoles in successful prevention and healthcare management, this scoping review aims to present a comprehensive overview of the existing evidence regarding DFU studies related to smart insoles, offloading sensors, and actuator technologies. This systematic review identified and critically evaluated 11 key studies exploring both sensor technologies and offloading devices in the context of DFU care through searches in CINAHL, MEDLINE, and ScienceDirect databases. Predominantly, smart insoles, mobile applications, and wearable technologies were frequently utilized for interventions and patient monitoring in diabetic foot care. Patients emphasized the importance of these technologies in facilitating care management. The pivotal role of offloading devices is underscored by the majority of the studies exhibiting increased efficient monitoring, prevention, prognosis, healing rate, and patient adherence. The findings indicate that, overall, smart insoles and digital technologies are perceived as acceptable, feasible, and beneficial in meeting the specific needs of DFU patients. By acknowledging the promising outcomes, the present scoping review suggests smart technologies can potentially redefine DFU management by emphasizing accessibility, efficacy, and patient centricity.

Decentralized Clinical Trials in the Development of Drugs and Biological Products.

Decentralized clinical trials (DCTs) are trials where some or all of the trial-related activities occur at locations other than traditional clinical trial sites. FDA supports decentralization to improve participation in clinical trials. While there are benefits of DCTs, including convenience for participants, sponsors and investigators should be aware of potential challenges such as coordination of trial activities at locations other than traditional trial sites and supervision of delegated trial-activities performed remotely. Appropriate training, oversight, and up-front risk assessment and management will be key to implementing a DCT successfully.

Barriers and facilitators to the implementation of digital technologies in mental health systems: a qualitative systematic review to inform a policy framework.

BACKGROUND: Despite the potential for improved population mental health and wellbeing, the integration of mental health digital interventions has been difficult to achieve. In this qualitative systematic review, we aimed to identify barriers and facilitators to the implementation of digital technologies in mental healthcare systems, and map these to an implementation framework to inform policy development. METHODS: We searched Medline, Embase, Scopus, PsycInfo, Web of Science, and Google Scholar for primary research articles published between January 2010 and 2022. Studies were considered eligible if they reported barriers and/or facilitators to the integration of any digital mental healthcare technologies. Data were extracted using EPPI-Reviewer Web and analysed thematically via inductive and deductive cycles. RESULTS: Of 12,525 references identified initially, 81 studies were included in the final analysis. Barriers and facilitators were grouped within an implementation (evidence-practice gap) framework across six domains, organised by four levels of mental healthcare systems. Broadly, implementation was hindered by the perception of digital technologies as impersonal tools that add additional burden of care onto both providers and patients, and change relational power asymmetries; an absence of resources; and regulatory complexities that impede access to universal coverage. Facilitators included person-cantered approaches that consider patients' intersectional features e.g., gender, class, disability, illness severity; evidence-based training for providers; collaboration among colleagues; appropriate investment in human and financial resources; and policy reforms that tackle universal access to digital health. CONCLUSION: It is important to consider the complex and interrelated nature of barriers across different domains and levels of the mental health system. To facilitate the equitable, sustainable, and long-term digital transition of mental health systems, policymakers should consider a systemic approach to collaboration between public and private sectors to inform evidence-based planning and strengthen mental health systems. PROTOCOL REGISTRATION: The protocol is registered on PROSPERO, CRD42021276838.

Benefits and barriers associated with the use of smart home health technologies in the care of older persons: a systematic review.

BACKGROUND: Smart home health technologies (SHHTs) have been discussed in the frame of caregiving to enable aging-in-place and independence. A systematic review was conducted in accordance with the PRISMA guidelines to gather the up-to-date knowledge on the benefits and barriers of using SHHTs in the care of older persons from the perspective of older persons and their caregivers. METHODS: Ten electronic databases were reviewed for empirical peer-reviewed literature published from 01.01.2000 to 31.12.2021 in English, German, and French reporting on experimental, qualitative, quantitative, and other empirical study designs were included. Included studies contained user-feedback from older persons over 65 years of age or their caregivers (formal and informal). We used an extraction document to collect relevant data from all included studies and applied narrative synthesis to analyze data related to benefits and barriers of SHHTs. RESULTS: 163 empirical peer-reviewed articles were included, the majority of those published between 2014 and 2021. Five first-order categories of benefits and five of barriers were found with individual sub-themes. SHHTs could be useful in the care context where continuous monitoring is needed. They improve self-management and independent living of older persons. Barriers currently exist with respect to ease of usability, social acceptance, and cost. CONCLUSIONS: SHHTs could be useful in the care context but are not without concerns. Researchers and policy makers can use the information as a starting point to better understand how the roles and outcomes of SHHTs could be improved for the care of older persons, while caregivers of older adults could use our findings to comprehend the scope of SHHTs and to decide when and where such technology could best address their individual family needs. Limitations lie in the possible exclusion of relevant articles published outside the inclusion criteria as well as the fact that due to digital divide, our review represents opinions of those who could and wanted to participate in the included 163 studies. TRIAL REGISTRATION: This review has been registered as PROSPERO CRD42021248543. A protocol was completed in March 2021 with the PRISMA-P guidance. We have extended the review period from 2000 to 2020 since the registration of the protocol to 2000-2021.

Walk a mile in my shoes: perspectives towards sharing of health and experience data among individuals living with sickle cell disorder.

Background: Advancements in digital health technologies (DHTs) mean people are increasingly recording and managing personal health data. As observed during the COVID-19 pandemic, sharing of such data may provide unrivalled opportunities in advancing our understanding of conditions otherwise poorly understood, including rare conditions. Methods: A semi-structured focus group (n=25) explored perspectives and experiences of sharing health data among those with a group of rare haematological conditions, sickle cell disorder (SCD). The focus group explored (I) what 'feeling well' looks like; (II) how this could be monitored using DHTs; (III) which data healthcare professionals (HCPs) should pay greater attention to and; (IV) types of data willing to be shared, with whom, and under which conditions. Key themes were further assessed via an online survey (n=50). Results: Patient-relevant measures of condition-management focused on "everything else that comes with" SCD, suggesting HCPs did not pay sufficient attention to day-to-day symptom variability. This was juxtaposed against the "fixed and one-off" electronic health record (EHR), collecting pre-specified data at pre-determined snapshots of time, not considered reflective of outcomes associated with "feeling well" day-to-day. Forty-four-point-seven percent of respondents had previously shared health data. Most were willing to share data concerning symptoms and health service utilisation, but were less willing to share genomic and EHR data. Sixty-one-point-seven percent believed HCPs did not pay enough attention to daily fluctuations in mental and physical health. Financial benefits (74.5%), trust in organisations seeking data (72.3%), and knowing how data will be used (61.7%) were key facilitators of data sharing. Seventy-one percent, 70% and 65.2% had not previously shared health data with the pharmaceutical industry, charitable organisations and digital health interventions respectively, but were open to doing so in the future. Conclusions: Those living with the rare condition SCD were supportive of collecting and sharing data to foster research and improve understanding and outcomes. However, specific requirements were identified to respect privacy and informational needs regarding future use of data. DHTs can be a valuable tool in improving understanding of the day-to-day impact of health conditions, but understanding patient needs is critical in ensuring involvement in the process, as not all data types are considered of equal value, benefit, or risk.

Development of a culturally targeted chatbot to inform living kidney donor candidates of African ancestry about APOL1 genetic testing: a mixed methods study.

Clinical chatbots are increasingly used to help integrate genetic testing into clinical contexts, but no chatbot exists for Apolipoprotein L1 (APOL1) genetic testing of living kidney donor (LKD) candidates of African ancestry. Our study aimed to culturally adapt and assess perceptions of the Gia® chatbot to help integrate APOL1 testing into LKD evaluation. Ten focus groups and post-focus group surveys were conducted with 54 LKDs, community members, and kidney transplant recipients of African ancestry. Data were analyzed through thematic analysis and descriptive statistics. Key themes about making Gia culturally targeted included ensuring: (1) transparency by providing Black LKDs' testimonials, explaining patient privacy and confidentiality protections, and explaining how genetic testing can help LKD evaluation; (2) content is informative by educating Black LKDs about APOL1 testing instead of aiming to convince them to undergo testing, presenting statistics, and describing how genetic discrimination is legally prevented; and (3) content avoids stigma about living donation in the Black community. Most agreed Gia was neutral and unbiased (82%), trustworthy (82%), and words, phrases, and expressions were familiar to the intended audience (85%). Our culturally adapted APOL1 Gia chatbot was well regarded. Future research should assess how this chatbot could supplement provider discussion prior to genetic testing to scale APOL1 counseling and testing for LKD candidate clinical evaluation.

Social and Ethical Implications of Digital Crisis Technologies: Case Study of Pandemic Simulation Models During the COVID-19 Pandemic.

BACKGROUND: Responses to public health crises are increasingly technological in nature, as the prominence of COVID-19-related statistics and simulations amply demonstrates. However, the use of technologies is preconditional and has various implications. These implications can not only affect acceptance but also challenge the acceptability of these technologies with regard to the ethical and normative dimension. OBJECTIVE: This study focuses on pandemic simulation models as algorithmic governance tools that played a central role in political decision-making during the COVID-19 pandemic. To assess the social implications of pandemic simulation models, the premises of data collection, sorting, and evaluation must be disclosed and reflected upon. Consequently, the social construction principles of digital health technologies must be revealed and examined for their effects with regard to social, ethical, and ultimately political issues. METHODS: This case study starts with a systematization of different simulation approaches to create a typology of pandemic simulation models. On the basis of this, various properties, functions, and challenges of these simulation models are revealed and discussed in detail from a socioscientific point of view. RESULTS: The typology of pandemic simulation methods reveals the diversity of model-driven handling of pandemic threats. However, it is reasonable to assume that the use of simulation models could increasingly shift toward agent-based or artificial intelligence models in the future, thus promoting the logic of algorithmic decision-making in response to public health crises. As algorithmic decision-making focuses more on predicting future dynamics than statistical practices of assessing pandemic events, this study discusses this development in detail, resulting in an operationalized overview of the key social and ethical issues related to pandemic crisis technologies. CONCLUSIONS: This study identifies 3 major recommendations for the future of pandemic crisis technologies.