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Electronics are set to merge with our bodies to extend our perceptions. Smartphones and watches will give way to the bodyNET1: a network of sensors, screens and smart devices woven into our clothing, worn on our skin and implanted in our bodies (see 'Superhuman powers').

The widespread use of digital technologies that can be worn on our bodies—wearables—is presented as a turning point for various areas of biomedical research and healthcare, such as stress. The ability to constantly measure these parameters, the perceived quality of measurement, and their individual and personal level frame wearable technology as a possibly crucial step in the direction of a more accurate and objective definition and measurement of stress for clinical, research, and personal purposes. In this paper, we discuss the hypothesis that the use of wearables for stress is also beneficial from an ethical viewpoint. We start by situating wearables in the context of existing methods and limitations of stress research. On this basis, we discuss the ethics of wearables for stress by applying ethical principles from bioethics (beneficence, non-maleficence, autonomy, justice), which allows us to identify ethical benefits as well as challenges in this context. As a result, we develop a more balanced view of the ethics of wearables for stress, which we use to present recommendations and indications with a focus on certification, accessibility, and inclusion. This article is, thus, a contribution towards ethically grounded wearable and digital health technology for stress.

Health Wearable Devices enhance the quality of life, promote positive lifestyle changes and save time and money in medical appointments. However, Wearable Devices store large amounts of personal information that is accessed by third parties without user consent. This creates ethical issues regarding privacy, security and informed consent. This paper aims to demonstrate users’ ethical perceptions of the use of Wearable Devices in the health sector. The impact of ethics is determined by an online survey which was conducted from patients and users with random female and male division. Results from this survey demonstrate that Wearable Device users are highly concerned regarding privacy issues and consider informed consent as “very important” when sharing information with third parties. However, users do not appear to relate privacy issues with informed consent. Additionally, users expressed the need for having shorter privacy policies that are easier to read, a more understandable informed consent form that involves regulatory authorities and there should be legal consequences the violation or misuse of health information provided to Wearable Devices. The survey results present an ethical framework that will enhance the ethical development of Wearable Technology.

In response to a burgeoning pediatric mental health epidemic, recent guidelines have instructed pediatricians to regularly screen their patients for mental health disorders with consistency and standardization. Yet, gold-standard screening surveys to evaluate mental health problems in children typically rely solely on reports given by caregivers, who tend to unintentionally under-report, and in some cases over-report, child symptomology. Digital phenotype screening tools (DPSTs), currently being developed in research settings, may help overcome reporting bias by providing objective measures of physiology and behavior to supplement child mental health screening. Prior to their implementation in pediatric practice, however, the ethical dimensions of DPSTs should be explored. Herein, we consider some promises and challenges of DPSTs under three broad categories: accuracy and bias, privacy, and accessibility and implementation. We find that DPSTs have demonstrated accuracy, may eliminate concerns regarding under- and over-reporting, and may be more accessible than gold-standard surveys. However, we also find that if DPSTs are not responsibly developed and deployed, they may be biased, raise privacy concerns, and be cost-prohibitive. To counteract these potential shortcomings, we identify ways to support the responsible and ethical development of DPSTs for clinical practice to improve mental health screening in children.

AgeTech refers to a growing sector that is advancing the use of technologies, such as information and communication technologies (ICTs), mobile technologies, robotics, wearables and smart home systems to enhance the lives of older adults. Although AgeTech can be seen as an opportunity for empowering older people and enhance their overall quality of life, crucial ethical issues have to be addressed. The articles in this topical collection focus on these and other ethical questions, particularly in respect to key emerging technologies of AI and robotics. The overall aim is to explore the multifaceted ethical landscape of emerging AgeTech and to provide frameworks and strategies for ethically-appropriate technologies that support the health, well-being, and quality of life of older adults.

As wearable devices, which allow individuals to track and self-manage their health, become more ubiquitous, the opportunities are growing for researchers to use these sensors within interventions and for data collection. They offer access to data that are captured continuously, passively, and pragmatically with minimal user burden, providing huge advantages for health research. However, the growth in their use must be coupled with consideration of their potential limitations, in particular, digital inclusion, data availability, privacy, ethics of third-party involvement, data quality, and potential for adverse consequences. In this paper, we discuss these issues and strategies used to prevent or mitigate them and recommendations for researchers using wearables as part of interventions or for data collection.

In many regions globally, including low-resource settings, there is a growing trend towards using mHealth technology, such as wearable sensors, to enhance health behaviors and outcomes. However, adoption of such devices in research conducted in low-resource settings lags behind use in high-resource areas. Moreover, there is a scarcity of research that specifically examines the user experience, readiness for and challenges of integrating wearable sensors into health research and community interventions in low-resource settings specifically. This study summarizes the reactions and experiences of young women (N = 57), ages 18 to 24 years, living in poverty in Kampala, Uganda, who wore Garmin vívoactive 3 smartwatches for five days for a research project. Data collected from the Garmins included participant location, sleep, and heart rate. Through six focus group discussions, we gathered insights about the participants’ experiences and perceptions of the wearable devices. Overall, the wearable devices were met with great interest and enthusiasm by participants. The findings were organized across 10 domains to highlight reactions and experiences pertaining to device settings, challenges encountered with the device, reports of discomfort/comfort, satisfaction, changes in daily activities, changes to sleep, speculative device usage, community reactions, community dynamics and curiosity, and general device comfort. The study sheds light on the introduction of new technology in a low-resource setting and also on the complex interplay between technology and culture in Kampala’s slums. We also learned some insights into how wearable devices and perceptions may influence behaviors and social dynamics. These practical insights are shared to benefit future research and applications by health practitioners and clinicians to advance and enhance the implementation and effectiveness of wearable devices in similar contexts and populations. These insights and user experiences, if incorporated, may enhance device acceptance and data quality for those conducting research in similar settings or seeking to address population-specific needs and health issues.

Enhanced recovery after surgery (ERAS) guidelines recommend early postoperative mobilization to reduce complications, but adherence is often suboptimal, highlighting the need for effective tools to monitor and encourage movement. The Mindray enhanced patient monitoring (ePM)/electrophysiology (ep) pod, capable of tracking activity, vital signs, sleep, and pain, offers high-precision postoperative monitoring and is well-suited for research on activity feedback. The study aims to assess whether wearable device-based (ePM/ep pod) activity feedback could reduce postoperative complications within 30 days of colorectal cancer (CRC) surgery. We conducted an open-label, evaluator-blind, randomized controlled trial involving patients aged ≥18 years scheduled for CRC surgery. Patients were randomized to a feedback group or a control group. Both groups were set the same target activity time postoperatively based on ERAS guidelines. The feedback group received real-time visual feedback of movement time daily through the ePM/ep pod device, while the control group did not receive feedback. The primary outcome was the comprehensive complication index (CCI) within postoperative 30 days. Secondary outcomes included daily activity time, pain Numeric Rating Scale scores for rest and movement during the first 3 postoperative days, length of stay, percentage of reaching the scheduled mobilization target, 30-day postoperative mortality rate, and the times of first exhaust and defecation. Two hundred thirty-nine patients were recruited between February 2023 and September 2023, with 216 randomized (n=108 for each group). There was no significant difference in CCI within 30 postoperative days between the control group (median CCI 0, range 0-20.90) and the activity feedback group (median CCI 0, range 0-12.20). The estimated mean difference was -0.59 (95% CI -3.56 to 2.38; P=.66). Sensitivity analysis excluding patients with low device compliance did not alter these findings. No significant differences between groups were found in daily activity time, length of hospital stay, or pain scores. Post hoc analysis revealed significant negative correlations between 30-day CCI and activity on the second day after operation (r=-0.166) and the third day after operation (POD3) (r=-0.264; P<.05 for both). Linear regression indicated that POD3 activity significantly reduced CCI (β=-.025; 95% CI -0.045 to -0.006; P=.01), with peak CCI reduction at 215 minutes of activity. In the context of ERAS, this study found no evidence that activity stimulation based on feedback from the wearable device (ePM/ep pod) could reduce 30-day postoperative CCI in patients undergoing CRC surgery. However, the ePM/ep pod could accurately record daily activity duration, which may be negatively correlated with CCI on POD3.

Wearable Digital Health Technology SeriesWearable DHT has reached an inflection point between fanciful descriptions and practical applications. The editors announce a series of articles focusing on the clinical applications of wearable DHT.

Assessment of sleep quality is essential to address poor sleep quality and understand changes. Owing to the advances in the Internet of Things and wearable technologies, sleep monitoring under free-living conditions has become feasible and practicable. Smart rings and smartwatches can be employed to perform mid- or long-term home-based sleep monitoring. However, the validity of such wearables should be investigated in terms of sleep parameters. Sleep validation studies are mostly limited to short-term laboratory tests; there is a need for a study to assess the sleep attributes of wearables in everyday settings, where users engage in their daily routines. This study aims to evaluate the sleep parameters of the Oura ring along with the Samsung Gear Sport watch in comparison with a medically approved actigraphy device in a midterm everyday setting, where users engage in their daily routines. We conducted home-based sleep monitoring in which the sleep parameters of 45 healthy individuals (23 women and 22 men) were tracked for 7 days. Total sleep time (TST), sleep efficiency (SE), and wake after sleep onset (WASO) of the ring and watch were assessed using paired t tests, Bland-Altman plots, and Pearson correlation. The parameters were also investigated considering the gender of the participants as a dependent variable. We found significant correlations between the ring's and actigraphy's TST (r=0.86; P<.001), WASO (r=0.41; P<.001), and SE (r=0.47; P<.001). Comparing the watch with actigraphy showed a significant correlation in TST (r=0.59; P<.001). The mean differences in TST, WASO, and SE of the ring and actigraphy were within satisfactory ranges, although there were significant differences between the parameters (P<.001); TST and SE mean differences were also within satisfactory ranges for the watch, and the WASO was slightly higher than the range (31.27, SD 35.15). However, the mean differences of the parameters between the watch and actigraphy were considerably higher than those of the ring. The watch also showed a significant difference in TST (P<.001) between female and male groups. In a sample population of healthy adults, the sleep parameters of both the Oura ring and Samsung watch have acceptable mean differences and indicate significant correlations with actigraphy, but the ring outperforms the watch in terms of the nonstaging sleep parameters.