Advancing nursing education through wearable electronic devices: A scoping review.

AIM: To examine the incorporation of wearable electronic devices in the education of undergraduate nursing students. BACKGROUND: The advancement of technology has influenced nursing education and will continue to do so in the future. Wearable technologies are electronic devices that can be worn as an accessory and expand the possibilities in nursing education with increased engagement in the learning process. DESIGN: A scoping review was conducted following JBI and reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) guidelines. METHODS: The search was performed on August 25th, 2023, in the databases: MEDLINE via PubMed, ISI Web of Science, ERIC, EBSCOhost CINAHL, EBSCOhost Academic Search Premier, EBSCOhost Health Source Nursing, EMBASE, Scopus, BVShost LILACS and ProQuest. Literature that examined the application of wearable electronic devices in the education of undergraduate nursing students was included. RESULTS: This scoping review study included a total of 21 records published between 2014 and 2023. The analysis showed that smart glasses are the most common wearable electronic device used in nursing education, followed by smartwatches. The devices provide an opportunity for competencies development, especially when applied in the simulation environment, such as physical examination and medication administration. Wearable technologies are potentially useful and feasible as learning tools in nursing education, increasing nursing students' motivation, confidence and satisfaction. CONCLUSIONS: In the technological revolution, educators must consider the potential of innovative teaching strategies, such as wearable electronic devices, to advance nursing education. Wearables can contribute to developing competencies required for the professionalism of undergraduate nursing students.

Validity of the estimated angular information obtained using an inertial motion capture system during standing trunk forward and backward bending.

BACKGROUND: Bending the trunk forward and backward while standing are common daily activities and can have various patterns. However, any dysfunction in these movements can considerably affect daily living activities. Consequently, a comprehensive evaluation of spinal motion during these activities and precise identification of any movement abnormalities are important to facilitate an effective rehabilitation. In recent years, with the development of measurement technology, the evaluation of movement patterns using an inertial motion capture system (motion sensor) has become easy. However, the accuracy of estimated angular information obtained via motion sensor measurements can be affected by angular velocity. This study aimed to compare the validity of estimated angular information obtained by assessing standing trunk forward and backward bending at different movement speeds using a motion sensor with a three-dimensional motion analysis system. METHODS: The current study included 12 healthy older men. A three-dimensional motion analysis system and a motion sensor were used for measurement. The participants performed standing trunk forward and backward bending at comfortable and maximum speeds, and five sensors were attached to their spine. Statistical analysis was performed using the paired t-test, intraclass correlation coefficient, mean absolute error, and multiple correlation coefficient. RESULTS: Results showed that the estimated angular information obtained using each motion sensor was not affected by angular velocity and had a high validity. CONCLUSIONS: Therefore, the angular velocity in this study can be applied clinically for an objective evaluation in rehabilitation.

Continuous Assessment of Active-Duty Army Special Operations and Reconnaissance Marines Using Digital Devices and Custom Software: The Digital Comprehensive Operator Readiness Assessment (DcORA) Study.

BACKGROUND: Continuous exposure to extreme and chronic stress from uncontrollable events has been linked to increased psychological and physiological reactivity. Prolonged, frequent deployments may test coping skills over time, ultimately rendering Servicemembers vulnerable to mental health problems and suicide. This study develops a methodology for accurately collecting holistic health measures from Servicemembers using digital tools, including custom-built phone software and body-worn sensors. METHODS: The secure research platform and mobile app continuously collect multiple health measures and, after data analysis, deliver continuously updated summary data back to the Servicemember. This system provides novel insights into the relationships between the measures while helping individuals track their progress toward self-established goals. Participants were given an iPhone (including the study app) and an Apple Watch. Participants tracked their data for more than 6 months and responded to baseline, daily, and weekly questions and assessments. Physiologic, psychologic, and cognitive assessment data across the Preservation of the Force and Family program (POTFF) domains were collected, displayed to the individual, and analyzed in aggregate. RESULTS: When coupled with custom-built software, this hardware can be elevated from a fitness tracker to a user-facing health monitoring, educational, and delivery system. CONCLUSION: This wearable system measured vital factors associated with the health and human performance of Servicemembers. In real-time, it engaged Servicemembers in health and human performance optimization practices to achieve a goal of prevention of physical or mental injury.

Digital Biomarkers for the Assessment of Non-Cognitive Symptoms in Patients with Dementia with Lewy Bodies: A Systematic Review.

Background: Portable digital health technologies (DHTs) could help evaluate non-cognitive symptoms, but evidence to support their use in patients with dementia with Lewy bodies (DLB) is uncertain. Objective: 1) To describe portable or wearable DHTs used to obtain digital biomarkers in patients with DLB, 2) to assess the digital biomarkers' ability to evaluate non-cognitive symptoms, and 3) to assess the feasibility of applying digital biomarkers in patients with DLB. Methods: We systematically searched databases MEDLINE, Embase, and Web of Science from inception through February 28, 2023. Studies assessing digital biomarkers obtained by portable or wearable DHTs and related to non-cognitive symptoms were eligible if including patients with DLB. The quality of studies was assessed using a modified check list based on the NIH Quality assessment tool for Observational Cohort and Cross-sectional Studies. A narrative synthesis of data was carried out. Results: We screened 4,295 records and included 20 studies. Seventeen different DHTs were identified for assessment of most non-cognitive symptoms related to DLB. No thorough validation of digital biomarkers for measurement of non-cognitive symptoms in DLB was reported. Studies did not report on aspects of feasibility in a systematic way. Conclusions: Knowledge about feasibility and validity of individual digital biomarkers remains extremely limited. Study heterogeneity is a barrier for establishing a broad evidence base for application of digital biomarkers in DLB. Researchers should conform to recommended standards for systematic evaluation of digital biomarkers.

"An excellent servant but a terrible master": Understanding the value of wearables for self-management in people with cystic fibrosis and their healthcare providers - A qualitative study.

BACKGROUND: Wearables hold potential to improve chronic disease self-management in conditions like cystic fibrosis (CF) through remote monitoring, early detection of illness and motivation. Little is known about the acceptability and sustainability of integrating wearables into routine care from the perspectives of people with CF (pwCF) and their treating clinicians. METHODS: A cross-sectional qualitative study involving semi-structured interviews with adult pwCF and focus groups comprising members of a CF multidisciplinary team (MDT) were conducted at a specialist CF centre in Australia. A phenomenological orientation underpinned the study. Inductive thematic analysis was performed using the Framework method. The study adhered to the Consolidated Criteria for Reporting Qualitative Research (COREQ) checklist. RESULTS: Nine pwCF and eight members of a CF MDT, representing six clinical disciplines, participated in the study. Eight themes were inductively generated from the data, of which four were identified from each group. PwCF valued wearables for providing real-time data to motivate healthy behaviours and support shared goal-setting with healthcare providers. Wearables did not influence adherence to CF-specific self-management practices and had some hardware limitations. Members of the CF MDT recognised potential benefits of remote monitoring and shared goal-setting, but advised caution regarding data accuracy, generating patient anxiety in certain personality traits, and lack of evidence supporting use in CF self-management. CONCLUSIONS: Perspectives on integrating wearables into CF care were cautiously optimistic, with emerging risks related to patient anxiety and lack of evidence moderating acceptance.

Data Interoperability for Ambulatory Monitoring of Cardiovascular Disease: A Scientific Statement From the American Heart Association.

Wearable devices are increasingly used by a growing portion of the population to track health and illnesses. The data emerging from these devices can potentially transform health care. This requires an interoperability framework that enables the deployment of platforms, sensors, devices, and software applications within diverse health systems, aiming to facilitate innovation in preventing and treating cardiovascular disease. However, the current data ecosystem includes several noninteroperable systems that inhibit such objectives. The design of clinically meaningful systems for accessing and incorporating these data into clinical workflows requires strategies to ensure the quality of data and clinical content and patient and caregiver accessibility. This scientific statement aims to address the best practices, gaps, and challenges pertaining to data interoperability in this area, with considerations for (1) data integration and the scope of measures, (2) application of these data into clinical approaches/strategies, and (3) regulatory/ethical/legal issues.

Prognostic value of electrical bioimpedance measured with a portable and wireless device in acute heart failure. / Valor pronóstico de la bioimpedancia eléctrica medida con el dispositivo IVOL en la insuficiencia cardiaca aguda.

INTRODUCTION AND OBJECTIVES: The current evaluation of acute heart failure (HF) does not allow an adequate prediction of its evolution. The electrical bioimpedance (BI) allows knowing the state of blood volume, until now only with fixed equipment. We have developed and validated a portable and wireless device to measure BI at the ankle (IVOL). The objective of the study is to know the long-term prognostic value of the point measurement of BI with IVOL in patients with acute HF. METHODS: A prospective cohort study of unselected patients admitted for acute HF in a tertiary hospital. The association between BI and different clinical, analytical and echocardiographic variables on admission and clinical evolution were analyzed. RESULTS: 76 patients were included (mean age 66.1 years, 71.1% men, 68.4% hypertensive, 34.2% diabetic, mean NT-ProBNP: 7,103 pg / ml). Of these, 52.6% with non-preserved left ventricular ejection fraction (LVEF) (<50%) and 56.6% with right ventricular (RV) dysfunction. 26.3% died during a mean follow-up of 35.8 months. Survival in patients with BI≤21,8Ω was lower, globally and in the subgroups of patients without preserved LVEF and with RV dysfunction, P<.008). In the multivariate analysis, a BI≥21.8Ω was an independent survival factor (HR: 0.242; 95% CI: 0.86-0.681; P=.007). CONCLUSIONS: BI values measured with IVOL may be an independent predictor of long-term mortality in patients hospitalized for acute HF. This prognostic value is maintained in patients without preserved LVEF function and with RV dysfunction.

Using Artificial Intelligence to Improve the Accuracy of a Wrist-Worn, Noninvasive Glucose Monitor: A Pilot Study.

BACKGROUND: Self-monitoring of glucose is important to the successful management of diabetes; however, existing monitoring methods require a degree of invasive measurement which can be unpleasant for users. This study investigates the accuracy of a noninvasive glucose monitoring system that analyses spectral variations in microwave signals. METHODS: An open-label, pilot design study was conducted with four cohorts (N = 5/cohort). In each session, a dial-resonating sensor (DRS) attached to the wrist automatically collected data every 60 seconds, with a novel artificial intelligence (AI) model converting signal resonance output to a glucose prediction. Plasma glucose was measured in venous blood samples every 5 minutes for Cohorts 1 to 3 and every 10 minutes for Cohort 4. Accuracy was evaluated by calculating the mean absolute relative difference (MARD) between the DRS and plasma glucose values. RESULTS: Accurate plasma glucose predictions were obtained across all four cohorts using a random sampling procedure applied to the full four-cohort data set, with an average MARD of 10.3%. A statistical analysis demonstrates the quality of these predictions, with a surveillance error grid (SEG) plot indicating no data pairs falling into the high-risk zones. CONCLUSIONS: These findings show that MARD values approaching accuracies comparable to current commercial alternatives can be obtained from a multiparticipant pilot study with the application of AI. Microwave biosensors and AI models show promise for improving the accuracy and convenience of glucose monitoring systems for people with diabetes.

Exploring the effects of fitbit incentive on treatment outcomes in veterans undergoing intensive pain rehabilitation program.

OBJECTIVE: This study compares clinical pain outcomes between patients in a pain treatment program that received a Fitbit, to patients that did not. We also explored: (1) cognitive, emotional, and psychological factors that may have impacted the decision to opt in to receiving a Fitbit; and (2) whether the choice to receive a Fitbit impacted changes in cognitive, emotional, and psychological factors following treatment. METHODS: Among 58 patients in a multidisciplinary pain treatment program at a Veterans Affairs Healthcare System hospital, 31 patients opted to receive a Fitbit as adjunct treatment, while 27 did not. This study utilized patient-reported and practitioner-collected data from the pain treatment program. RESULTS: Compared to the non-Fitbit group, the Fitbit group displayed a significant decrease in average pain intensity, however showed no correlation between Fitbit activity and average pain intensity. Additionally, treatment satisfaction was the only predictor of treatment group, when modeling pre- and post-treatment outcomes changes. CONCLUSION: The implementation of a Fitbit may lead to improved pain intensity. Initial evidence suggests that opting to receive a Fitbit during a pain treatment program indicates treatment engagement leading to greater treatment satisfaction. Future work is needed to verify and expand upon this potential mechanism.

Neural Network-Based Prediction of Perceived Sleep Quality Through Wearable Device Data.

BACKGROUND: This study focuses on the development of a neural network model to predict perceived sleep quality using data from wearable devices. We collected various physiological metrics from 18 participants over four weeks, including heart rate, physical activity, and both device-measured and self-reported sleep quality. OBJECTIVES: The primary objective was to correlate wearable device data with subjective sleep quality perceptions. METHODS: Our approach used data processing, feature engineering, and optimizing a Multi-Layer Perceptron classifier. RESULTS: Despite comprehensive data analysis and model experimentation, the predictive accuracy for perceived sleep quality was moderate (59%), highlighting the complexities in accurately quantifying subjective sleep experiences through wearable data. Applying a tolerance of 1 grade (on a scale from 1-5), increased accuracy to 92%. DISCUSSION: More in-depth analysis is required to fully comprehend how wearables and artificial intelligence might assist in understanding sleep behavior.

An mHealth Intervention Promoting Physical Activity and Healthy Eating in a Family Setting (SMARTFAMILY): Randomized Controlled Trial.

BACKGROUND: Numerous smartphone apps are targeting physical activity (PA) and healthy eating (HE), but empirical evidence on their effectiveness for the initialization and maintenance of behavior change, especially in children and adolescents, is still limited. Social settings influence individual behavior; therefore, core settings such as the family need to be considered when designing mobile health (mHealth) apps. OBJECTIVE: The purpose of this study was to evaluate the effectiveness of a theory- and evidence-based mHealth intervention (called SMARTFAMILY [SF]) targeting PA and HE in a collective family-based setting. METHODS: A smartphone app based on behavior change theories and techniques was developed, implemented, and evaluated with a cluster randomized controlled trial in a collective family setting. Baseline (t0) and postintervention (t1) measurements included PA (self-reported and accelerometry) and HE measurements (self-reported fruit and vegetable intake) as primary outcomes. Secondary outcomes (self-reported) were intrinsic motivation, behavior-specific self-efficacy, and the family health climate. Between t0 and t1, families of the intervention group (IG) used the SF app individually and collaboratively for 3 consecutive weeks, whereas families in the control group (CG) received no treatment. Four weeks following t1, a follow-up assessment (t2) was completed by participants, consisting of all questionnaire items to assess the stability of the intervention effects. Multilevel analyses were implemented in R (R Foundation for Statistical Computing) to acknowledge the hierarchical structure of persons (level 1) clustered in families (level 2). RESULTS: Overall, 48 families (CG: n=22, 46%, with 68 participants and IG: n=26, 54%, with 88 participants) were recruited for the study. Two families (CG: n=1, 2%, with 4 participants and IG: n=1, 2%, with 4 participants) chose to drop out of the study owing to personal reasons before t0. Overall, no evidence for meaningful and statistically significant increases in PA and HE levels of the intervention were observed in our physically active study participants (all P>.30). CONCLUSIONS: Despite incorporating behavior change techniques rooted in family life and psychological theories, the SF intervention did not yield significant increases in PA and HE levels among the participants. The results of the study were mainly limited by the physically active participants and the large age range of children and adolescents. Enhancing intervention effectiveness may involve incorporating health literacy, just-in-time adaptive interventions, and more advanced features in future app development. Further research is needed to better understand intervention engagement and tailor mHealth interventions to individuals for enhanced effectiveness in primary prevention efforts. TRIAL REGISTRATION: German Clinical Trials Register DRKS00010415; https://drks.de/search/en/trial/DRKS00010415. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/20534.

[Analysis of the challenges and dilemmas that bioethics of the 21st century will face in the digital health era]. / Análisis de retos y dilemas que deberá afrontar la bioética del siglo xxi, en la era de la salud digital.

The medical history underscores the significance of ethics in each advancement, with bioethics playing a pivotal role in addressing emerging ethical challenges in digital health (DH). This article examines the ethical dilemmas of innovations in DH, focusing on the healthcare system, professionals, and patients. Artificial Intelligence (AI) raises concerns such as confidentiality and algorithmic biases. Mobile applications (Apps) empower but pose challenges of access and digital literacy. Telemedicine (TM) democratizes and reduces healthcare costs but requires addressing the digital divide and interconsultation dilemmas; it necessitates high-quality standards with patient information protection and attention to equity in access. Wearables and the Internet of Things (IoT) transform healthcare but face ethical challenges like privacy and equity. 21st-century bioethics must be adaptable as DH tools demand constant review and consensus, necessitating health science faculties' preparedness for the forthcoming changes.

Advancing Wearable Biosensors for Congenital Heart Disease: Patient and Clinician Perspectives: A Science Advisory From the American Heart Association.

Wearable biosensors (wearables) enable continual, noninvasive physiologic and behavioral monitoring at home for those with pediatric or congenital heart disease. Wearables allow patients to access their personal data and monitor their health. Despite substantial technologic advances in recent years, issues with hardware design, data analysis, and integration into the clinical workflow prevent wearables from reaching their potential in high-risk congenital heart disease populations. This science advisory reviews the use of wearables in patients with congenital heart disease, how to improve these technologies for clinicians and patients, and ethical and regulatory considerations. Challenges related to the use of wearables are common to every clinical setting, but specific topics for consideration in congenital heart disease are highlighted.

Comparison of Novel Telemonitoring System Using the Single-lead Electrocardiogram Patch With Conventional Telemetry System.

BACKGROUND AND OBJECTIVES: Although a single-lead electrocardiogram (ECG) patch may provide advantages for detecting arrhythmias in outpatient settings owing to user convenience, its comparative effectiveness for real-time telemonitoring in inpatient settings remains unclear. We aimed to compare a novel telemonitoring system using a single-lead ECG patch with a conventional telemonitoring system in an inpatient setting. METHODS: This was a single-center, prospective cohort study. Patients admitted to the cardiology unit for arrhythmia treatment who required a wireless ECG telemonitoring system were enrolled. A single-lead ECG patch and conventional telemetry were applied simultaneously in hospitalized patients for over 24 hours for real-time telemonitoring. The basic ECG parameters, arrhythmia episodes, and signal loss or noise were compared between the 2 systems. RESULTS: Eighty participants (mean age 62±10 years, 76.3% male) were enrolled. The three most common indications for ECG telemonitoring were atrial fibrillation (66.3%), sick sinus syndrome (12.5%), and atrioventricular block (10.0%). The intra-class correlation coefficients for detecting the number of total beats, atrial and ventricular premature complexes, maximal, average, and minimal heart rates, and pauses were all over 0.9 with p values for reliability <0.001. Compared to a conventional system, a novel system demonstrated significantly lower signal noise (median 0.3% [0.1-1.6%] vs. 2.4% [1.4-3.7%], p<0.001) and fewer episodes of signal loss (median 22 [2-53] vs. 64 [22-112] episodes, p=0.002). CONCLUSIONS: The novel telemonitoring system using a single-lead ECG patch offers performance comparable to that of a conventional system while significantly reducing signal loss and noise. TRIAL REGISTRATION: Clinical Research Information Service Identifier: KCT0008176.

[Characterization of atrial fibrillation burden using wearables]. / Charakterisierung der Vorhofflimmerlast mittels Wearables.

The characterization of atrial fibrillation (AF) according to current guidelines categorically refers to the differentiation between paroxysmal, persistent, and permanent AF. A more precise characterization of AF, including the evaluation of AF burden, is playing an increasingly significant role in both scientific research and clinical practice. Digital devices, especially those with the capability of passive (semi-)continuous recording, can contribute to a more accurate quantification of AF burden. Particularly in patients with an already established diagnosis of AF, the evaluation of AF burden can be used to monitor the success of antiarrhythmic therapy including antiarrhythmic drugs or pulmonary vein isolation. However, important questions remain unanswered: In addition to a uniform, evidence-based definition of AF burden, clinically relevant cut-offs for AF burden and resulting therapeutic consequences (e.g., subclinical AF) need to be elaborated. Furthermore, the establishment and evaluation of care structures for assessing and integrating AF burden in clinical care, especially by incorporating data from wearable medical devices, should take place.

Digital health interventions for postoperative recovery in children: a systematic review.

BACKGROUND: Digital health interventions offer a promising approach for monitoring during postoperative recovery. However, the effectiveness of these interventions remains poorly understood, particularly in children. The objective of this study was to assess the efficacy of digital health interventions for postoperative recovery in children. METHODS: A systematic review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, with the use of automation tools for searching and screening. We searched five electronic databases for randomised controlled trials or non-randomised studies of interventions that utilised digital health interventions to monitor postoperative recovery in children. The study quality was assessed using Cochrane Collaboration's Risk of Bias tools. The systematic review protocol was prospectively registered with PROSPERO (CRD42022351492). RESULTS: The review included 16 studies involving 2728 participants from six countries. Tonsillectomy was the most common surgery and smartphone apps (WeChat) were the most commonly used digital health interventions. Digital health interventions resulted in significant improvements in parental knowledge about the child's condition and satisfaction regarding perioperative instructions (standard mean difference=2.16, 95% confidence interval 1.45-2.87; z=5.98, P<0.001; I2=88%). However, there was no significant effect on children's pain intensity (standard mean difference=0.09, 95% confidence interval -0.95 to 1.12; z=0.16, P=0.87; I2=98%). CONCLUSIONS: Digital health interventions hold promise for improving parental postoperative knowledge and satisfaction. However, more research is needed for child-centric interventions with validated outcome measures. Future work should focus development and testing of user-friendly digital apps and wearables to ease the healthcare burden and improve outcomes for children. SYSTEMATIC REVIEW PROTOCOL: PROSPERO (CRD42022351492).

Rehabilitation clinicians' use of mainstream wireless technologies in practice: a scoping review.

PURPOSE: This scoping review was conducted to understand the barriers, facilitators, and education and training needs of rehabilitation clinicians in their use of mainstream wireless technologies (MWT) to support people with disabilities and older adults. It was also conducted to understand the functional skills of clients that were targeted with MWT use. MATERIALS AND METHODS: This scoping review was reported using PRISMA-ScR (Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews) and the Population (or Participants)/Concept/Context) framework. We searched PubMed; ProQuest to access APA PsycINFO; Web of Science Core Collection; and EBSCOhost to access Cumulated Index to Nursing and Allied Health Literature (CINAHL), Ovid MEDLINE ALL, and Education Resources Information Center (ERIC). Articles published between 2015-2022 were retrieved. RESULTS: A total of 90 articles were included. Most interventions were apps, smartphones, and tablets; were geared toward adults; and targeted motor, cognitive and speech skills. An infographic on barriers and facilitators was generated as a decision support tool for clinicians when implementing MWT. The topic, format, timing, and source of information clinicians need are also delineated. CONCLUSION: MWT such as apps, smartphones and tablets are being used by rehabilitation clinicians to address motor, cognitive, and speech skills, most commonly in adults. Clinicians voice a need for more education and training. Barriers and facilitators exist at the clinician-, technology-, client-, institution-, and policy levels.Implications For RehabilitationA total of 90 articles from 2015-2022 were included in this scoping reviewMost interventions were apps, smartphones, and tablets; were geared toward adults; and targeted motor, cognitive and speech skills.An infographic was generated as a decision support tool for clinicians when implementing mainstream wireless technologies in clinical practice.Clinicians' education and training needs with regard to mainstream wireless technologies are broad. Materials on a variety of topics, in different formats, from multiple sources are needed.This review also discusses implications of findings on policy, technology development, and future research.

Effects of a mobile health intervention on health-related outcomes in Japanese office workers: a pilot study.

OBJECTIVES: The purpose of the current study was to explore the effects of a mobile health (mHealth) intervention based on the Persuasive System Design (PSD) model on health-related outcomes among office workers. MATERIAL AND METHODS: The authors conducted a trial that consisted of a 4-week baseline and an 8-week intervention period by reference to 23 office workers in a private research company. The mHealth application was developed to improve these workers' daily step count, decrease their sedentary time, and increase their sleep duration in accordance with the PSD model. The app features included at least 1 principal factor from each of the 4 main categories of the PSD model (primary task support, dialogue support, system credibility support, and social support). The objective health-related variables were measured using a smartwatch (Fitbit Luxe) that was synchronized with the application using the Fitbit Web Application Programming Interface. Subjects used the app, which included self-monitoring, personalized messages, education, and a competition system for users, during the intervention period. RESULTS: Sedentary time exhibited a significant decrease (a median reduction of 14 min/day, p < 0.05) during the intervention period. No significant differences in daily step count and sleep duration were observed between the baseline and intervention periods. CONCLUSIONS: This study suggests that the mHealth intervention based on the PSD model was useful for reducing sedentary time among office workers. Given that many previous studies on this topic have not been based on any theories, future studies should investigate the impact of structured selection behavior change theories on health-related outcomes among office workers. Int J Occup Med Environ Health. 2024;37(2):153-64.

Minimum clinical utility standards for wearable seizure detectors: A simulation study.

OBJECTIVE: Epilepsy management employs self-reported seizure diaries, despite evidence of seizure underreporting. Wearable and implantable seizure detection devices are now becoming more widely available. There are no clear guidelines about what levels of accuracy are sufficient. This study aimed to simulate clinical use cases and identify the necessary level of accuracy for each. METHODS: Using a realistic seizure simulator (CHOCOLATES), a ground truth was produced, which was then sampled to generate signals from simulated seizure detectors of various capabilities. Five use cases were evaluated: (1) randomized clinical trials (RCTs), (2) medication adjustment in clinic, (3) injury prevention, (4) sudden unexpected death in epilepsy (SUDEP) prevention, and (5) treatment of seizure clusters. We considered sensitivity (0%-100%), false alarm rate (FAR; 0-2/day), and device type (external wearable vs. implant) in each scenario. RESULTS: The RCT case was efficient for a wide range of wearable parameters, though implantable devices were preferred. Lower accuracy wearables resulted in subtle changes in the distribution of patients enrolled in RCTs, and therefore higher sensitivity and lower FAR values were preferred. In the clinic case, a wide range of sensitivity, FAR, and device type yielded similar results. For injury prevention, SUDEP prevention, and seizure cluster treatment, each scenario required high sensitivity and yet was minimally influenced by FAR. SIGNIFICANCE: The choice of use case is paramount in determining acceptable accuracy levels for a wearable seizure detection device. We offer simulation results for determining and verifying utility for specific use case and specific wearable parameters.