Over the last 15 years, wearable health devices have become increasingly commonplace, with ownership ranging from 30-50% of adults globally. Using advanced technologies, wearable devices today support both consumer wellness and medical-grade applications for a range of chronic conditions including sleep disorders such as obstructive sleep apnea and insomnia. Despite the growing interest in wearable devices, few studies have explored global consumer adoption and perspectives, and how health and lifestyle decisions are impacted by available insights. This study aimed to examine wearable device adoption, usage patterns, motivations, confidence in wearable-generated data, and health-related behavior changes among adults, with a particular focus on differences by gender and geographic region. We conducted a cross-sectional, global electronic survey of 9980 employees from a multinational health technology company between July and August 2024 to better understand wearable device usage, perceptions, and beliefs among employees. Participants were invited to participate via digital flyers and emails, as well as via printed materials placed in the workplace. Of the total employees invited to the survey, 1589 (16%) employees were eligible, consented, and completed the survey. Descriptive statistics summarized survey responses, and chi-square tests and proportion tests were used to evaluate differences in drivers of wearable use, confidence, and beliefs by gender, region, and sleep-tracking status. Respondents had a mean (SD) age of 42 (10) years, and 737 (47%) were women, with regional representation from North America (579/1570, 37%), Western Europe (395/1570, 25%), Australasia (395/1570, 25%), and Asia (201/1570, 13%). Most participants (n=1023, 64%) were current wearable device users and 50% of them (n=513) tracked used a wearable device to track sleep. Wrist-worn devices were the most common form factor (1000/1023, 98%) followed by rings (99/1023, 10%). Participants primarily used devices for wellness tracking, and while most (616/1023, 60%) felt confident in the accuracy of the data, only 15% (n=153) regularly shared data with their healthcare provider (HCP). Among those respondents with obstructive sleep apnea (312/1589, 20%), about 21% (108/513) used a wearable device to track their sleep, with similar rates of data sharing. Usage patterns differed by age, geography and gender, as did sharing of data with HCPs. Wearable devices are widely used to support health and wellness behaviors and are associated with self-reported changes in exercise, goal-setting, and sleep habits. Significant differences in engagement and health-related behaviors across gender and geographic regions suggest that demographic and contextual factors influence how wearable technologies are used. These findings may inform the development of more personalized and equitable digital health interventions and support greater integration of consumer-generated health data into healthcare settings.

INTRODUCTION:Academic medical centers are undergoing significant growth which may influence surgeons' perceptions of their roles and value within these institutions. This study aimed to explore academic surgeons' perspectives on their roles and sense of value within an expanding academic medical center. MATERIALS AND METHODS:We conducted semi-structured interviews with 39 surgeons at a single academic medical center. Using a qualitative descriptive approach, we analyzed data through iterative coding and theme development. RESULTS:We identified three main themes: (1) Increased administrative responsibilities with inadequate support, (2) Perceived limited influence in organizational decision-making, and (3) Importance of support from health system administration and colleagues. Surgeons interpreted administrative workload and their level of involvement in institutional decisions as key indicators of their value to the organization. Collegial support played a vital role in countering feelings of disengagement and fostering a sense of belonging. CONCLUSIONS:The organizational structure of academic medical centers impacts surgeons' perceptions of their value. Addressing administrative burdens, enhancing surgeon participation in governance, and fostering supportive professional networks are potential strategies to improve morale and job satisfaction during organizational growth. Future research should focus on developing interventions to address these areas.

Chronic conditions such as cardiovascular disease, diabetes, and chronic obstructive pulmonary disease are associated with obstructive sleep apnea (OSA). These conditions are more prevalent in older adults, who may be at heightened risk for OSA. Studies on OSA prevalence have primarily focused on individuals aged up to 70 years, leaving a significant gap in data regarding the population >70 years. Therefore, it is crucial to assess the prevalence of OSA in this group. We aimed to estimate the prevalence of OSA among older adults across the United States through 2050. A dynamic open-cohort Markov model was constructed to simulate changes in population structure from 2020 to 2050. Parameters for population growth, the progression of OSA, body mass index (BMI) trajectories, all-cause mortality, and mortality linked to OSA and BMI were based on estimates from existing literature and were modeled across various subgroups categorized by age, sex, and BMI trends, updated every five years. OSA prevalence was adjusted according to age, sex, and BMI subgroups. The projection of OSA prevalence (defined as AHI >5) was focused on individuals aged 70-85 years. From 2020 to 2050, the prevalence of OSA in older adults is projected to increase substantially. The overall prevalence of OSA with AHI ≥ 5 is expected to rise by 136%, from 11.9 (33%) million cases in 2020 to 28.2 (53.7%) million cases in 2050. For older females, the prevalence of OSA (AHI ≥ 5) will see an increase of 159%, from 4.7 million (23% of females 70-85 years) cases in 2020 to 12.1 million (45.0%) cases in 2050. For older males, the increase will be more moderate than for females, with a rise of 121%, from 7.3 million (45.7%) cases in 2020 to 16.1 million (63.4%) cases in 2050. The prevalence of OSA in older adults is expected to rise significantly through 2050, with the most pronounced increase among older females. The potential clinical implications of these findings highlight the need for targeted healthcare strategies in the United States to address the anticipated growth in OSA burden in the aging population. ResMed

Introduction In obstructive sleep apnea (OSA), romantic partners can play an important role in adopting PAP (positive airway pressure) therapy, which has been shown to improve sleep and daytime functioning in both PAP users and their partners. However, understanding the drivers of partner involvement in real-world PAP therapy adoption remains a topic of exploration. Methods PAP therapy users with OSA (ResMed, San Diego) were invited to complete a one-time e-survey regarding their PAP therapy experience, including partner involvement in therapy management. Survey responses were retrospectively paired with device-captured therapy data to explore how partner involvement may change based on baseline PAP usage. Logistic regressions explored the association between gender (male/female) and average baseline PAP use (defined as < 4 hours/night, 4 to < 6 hours/night, and 6+ hours/night during the first 30 days of PAP initiation), with the odds of partnership involvement (partner monitor PAP usage (yes/no)). The model adjusted for self-reported age, baseline apnea hypopnea index (AHI), time on platform, and device mode. Results 8,893 PAP users were assessed. Median age was 59 years, and 40.1% were female. Median (IQR) baseline AHI was 15 (4.7, 33.4) and median (IQR) baseline PAP usage was 6.7 (5.4, 7.7) hours/night. Compared to users with ≥ 6 hours/night of PAP use, users who used their PAP device for 4 to <6 hours/night had a 58% greater likelihood of having a partner monitor their PAP usage (1.58 (1.43, 1.75); p < 0.001). Users who used their PAP device for <4 hours/night were almost twice as likely to have a partner monitor their PAP usage (1.96 (1.70, 2.27); p < 0.001). Compared to female users, male users were 45% more likely to have their partner monitor their PAP usage (1.45 (1.32, 1.58); p < 0.001). Conclusion Lower baseline PAP use was associated with increased odds of having a partner involved in therapy management, with males more likely to have their partner monitor usage compared to females. Tailoring social support interventions intended to promote PAP therapy might consider the role of baseline usage and gender. Future studies might further explore relationship dynamics such as trust and intimacy to further contextualize the findings observed.

Rationale: Positive airway pressure (PAP) therapy is the first-line treatment for obstructive sleep apnea (OSA). Understanding the user's therapy experience is essential in promoting PAP usage and achieving treatment goals. Artificial intelligence/machine learning (AI/ML) techniques like traditional natural language processing (NLP) techniques and large language models (LLMs) have become popular approaches for understanding real-world patient experience using large qualitative datasets. However, selecting an appropriate AI/ML model to examine themes and sentiment from real-world patient feedback datasets can be challenging. Methods: We compare the strengths and weaknesses of three AI/ML approaches for examining a large dataset of qualitative survey response data: NLP (BERTopic), LLM-based RAG (Retrieval-Augmented Generation using Mistral, LLama3) and hybrid NLP+LLM-based RAG. Models were assessed for model input and output, prompt engineering, result interpretability, hallucination and reproducibility of results. Qualitative survey response data regarding PAP therapy experience was previously collected from adult PAP therapy users (ResMed, San Diego CA) with OSA. Response data was examined only from users responding in the English language and residing in the United States. The three AI/ML models were used to identify key topic themes and assess sentiment related to PAP therapy experience. All analyses were run locally. Results: Qualitative responses from 5,633 PAP users were assessed. Compared to traditional NLP models, which give keyword-based themes, and standard LLMs, which give broad themes and sentiments, the hybrid RAG framework appeared to provide more accurate sub-themes and sentiments for each user. Furthermore, hallucination was limited as the hybrid model was grounded in real-world evidence and worked well with existing computational resources (Table). Conclusion: As PAP therapy technology continues to evolve, understanding the user experience will remain a central part of effective care management. A hybrid RAG framework for theme identification and sentiment analysis presents a promising solution for gaining valuable real-world user experience insights while efficiently handling large-scale qualitative datasets. However, human oversight is still required for model refinement and future work is needed to explore how a hybrid framework may perform across diverse datasets.

While obstructive sleep apnea (OSA) is widely recognized as a condition that predominantly impacts men, the burden on women is significant, yet often under-appreciated. Given increased attention on understanding gender differences in chronic diseases, especially related to menopausal changes (e.g., body weight and hormones), it is critical to better understand how the burden of OSA develops over time in women. Therefore, we sought to estimate the prevalence of OSA by gender across the United States (US) through the year 2050. A dynamic open cohort population Markov model was developed to simulate population dynamics from 2020 to 2050. Population growth, OSA development, BMI trajectories, all-cause mortality, and OSA and BMI-related mortality were derived from literature estimates and modeled across subgroups of age, sex, and BMI trends in 5-year increments. OSA prevalence was calibrated for subgroups by age, sex and BMI, and distributions of OSA severity grades were modeled based on sex, apnea hypopnea index (AHI) and BMI. OSA prevalence (AHI >5) was projected among those aged 30-69 years. The burden of OSA across the US is expected to rise significantly by 2050, with total cases projected to increase by 34.7%, from 56.9 million in 2020 to 76.6 million by 2050. The prevalence of OSA is estimated to increase for both males and females, but the rise is notably more pronounced among women, with the number of female OSA cases projected to grow by 64.4%, from 18.9 million in 2020 to 30.4 million in 2050, while male cases are expected to increase by 19.0%, from 38.0 million to 46.2 million. Our modeling study projects a significant increase in OSA prevalence across the US through 2050, with a disproportionate rise in the burden among women. This data serves as a call to action to increase awareness in primary healthcare settings, particularly regarding peri-menopausal and post-menopausal women who face weight gain and hormonal changes that increase OSA risk. The findings highlight the need for efficient and accurate diagnostic tools which are appropriate for characteristics of female OSA, along with optimal treatment pathways for female patients. ResMed

Supplemental Table 1: Demographics and clinical data for donor Gife of Life Samples Supplemental Table 2: Putative Ligand-Receptor pairs comparing all cell types from single cell sequencing of tumor samples compared to healthy samples. Supplemental Table 3: Differential gene expression using linear mixed model analysis of cell types from spatial transcriptomic ROIs. Supplemental Table 4: Kras mutational profiling on select donor samples Supplemental Table 5: Antibodies used for multiplex immunofluoresence. Supplemental Table 6: Antibodies and RNAScope probe used for co-IF/ISH.

Supplementary Figures 11-14 and associated legends.

Positive airway pressure (PAP) therapy can provide immediate and lasting clinical benefits in obstructive sleep apnea (OSA). Nevertheless, therapy adherence can be challenging for some users. Identifying benefits related to quality of life and symptom relief may further motivate users to persist with therapy. Users of a smartphone app to track PAP therapy usage (myAir, ResMed) completed a one-time survey about their therapy experience and behaviors. Questions on perceived changes in quality of life (energy level, relationships, general activity, and clear-headedness) and OSA-related symptoms following therapy initiation were assessed using a 5-point scale reflecting worsening, no change, or improvement in the outcome of interest. Descriptive statistics and ordinal logistic regressions were used to assess the relationship between perceived improvement in outcomes and age, gender, and time on therapy. These regressions controlled for demographic and baseline clinical confounders. Data from 10,906 PAP users were included in the analysis (median age: 59 years, 44.8% female, median PAP usage during the first 7 days: 6.5 hrs/day). On average, 91% of users perceived an improvement in at least one of the eleven symptom measures, and 76% perceived an improvement in at least one of the four quality of life (QOL) measures. Users primarily reported perceived improvements in snoring (87%), fatigue (75%), energy level (72%), insomnia (68%), activity level (66%), clear-headedness (59%), and relationships (42%). While users reported perceived improvement in symptoms and QOL measures within the first 90 days, the odds of improvement increased progressively with extended therapy use for QOL measures, accidents, insomnia, moodiness, and snoring (12 (vs. 3) months, all p< 0.05). Differences in symptoms and QOL by age and gender were also observed (p< 0.05). PAP therapy is associated with perceived improvements in QOL outcomes and symptoms, with significant improvements observed within 90 days. Continued PAP usage may further enhance outcomes through one year. Differences in perceived improvements by age and gender suggest an opportunity to better personalize messaging and strategies for PAP therapy initiation and long-term adherence. ResMed

Supplementary Figures 1-10 and associated legends

Consumer wearables provide personalized insights into health behaviors that can be used to enhance care management for many chronic conditions including sleep health. However, sharing these unique data insights with healthcare providers (HCPs) varies widely. This study investigates predictors of data-sharing among wearable device users. Employees of a multinational corporation participated in an e-survey on wearable device usage and behavior between July and August 2024. A weighted logistic regression model assessed the likelihood of a user sharing wearable data with their HCP. Predictors included: sociodemographic factors (age, gender, global region, race, ethnicity, perceived financial security, and self-reported OSA status), data confidence, and sleep tracking motivation. Odds ratios (OR [95% confidence interval]) are reported. Responses from 1,589 people were assessed (mean (SD) age: 42 (10) years, 46% female), with most respondents reporting current use of a wearable device (64%) and having high confidence in device data accuracy (85%). Users with high data confidence (vs. low confidence) were 2.4 times more likely to share data with their HCPs (2.44 [1.54, 3.96]; p < 0.001), and those motivated by sleep tracking (vs. not) were twice as likely to share their data with HCPs (2.01 [1.61, 2.51]; p < 0.001). Compared to North American users, users from Europe (0.25 [0.18, 0.34]; p < 0.001), Australia & New Zealand (0.54 [0.40, 0.71]; p < 0.001), and Asia (0.40 [0.24, 0.65]; p < 0.001) were significantly less likely to share their data with HCPs. Hispanic (vs. non-Hispanic) users were 50% less likely to share their data with HCPs (0.51 [0.26, 0.98]; p < 0.05). Finally, users who indicated some financial security (vs. no financial security) were significantly less likely to share their data (slightly secure: 0.41, [0.17, 0.97], p < 0.05; mostly secure: 0.43, [0.19, 0.94], p < 0.05). Greater data confidence, being motivated by sleep tracking, residing in North America, identifying as non-Hispanic, and lower perceived financial security were important predictors of data sharing with HCPs. Tailoring interventions on sociodemographic factors and user behaviors may help promote data sharing with HCPs, which may further support chronic disease management.

The increasing operations of port craft and railway locomotives pose significant environmental and health challenges to vulnerable communities in California, where disadvantaged populations often bear a disproportionate burden of pollution exposure. This study employs digital inhaler sensors to monitor individual respiratory health and quantify the impacts of air pollution from port craft and railway activities on rescue medication use. Combining spatially resolved emissions data with meteorological inputs, we utilized advanced dispersion modeling to estimate pollution levels, focusing on fine particulate matter with an aerodynamic diameter equal to or less than 2.5 µm (PM2.5) and nitrogen dioxide (NO2). Our analysis revealed that a 10-µg m-3 increase in PM2.5 concentrations is associated with a 3.42% rise in daily rescue medication use when accounting for NO2 and PM2.5 jointly. The impacts are particularly pronounced in deprivation-high communities, where the effect of PM2.5 on rescue medication use is 3.8 times greater than in less disadvantaged areas. These findings highlight stark disparities in health outcomes, with marginalized populations facing heightened risks due to their proximity to emission sources and lack of adequate environmental safeguards. While substantial research has addressed air pollution impacts from roadway traffic and industrial activities, studies focusing specifically on port craft and railway emissions remain limited. Our study demonstrates the unique health burdens associated with these underexplored sources of pollution. Furthermore, the use of digital health technologies allows for unprecedented spatiotemporal resolution in tracking exposure and respiratory outcomes, providing a more nuanced understanding of the complex interplay between environmental and health dynamics. These results underscore the urgent need for targeted interventions, including cleaner technologies, stricter emission regulations, and policies aimed at mitigating exposure in vulnerable populations. Addressing these disparities is essential to advancing environmental justice and protecting public health.