Wearable devices collect time-varying biobehavioral data, offering opportunities to investigate how behaviors influence health outcomes. However, these data often contain measurement error and excess zeros (due to nonwear, sedentary behavior, or connectivity issues), each characterized by subject-specific distributions. Current statistical methods fail to address these issues simultaneously. We introduce a novel modeling framework for zero-inflated and error-prone functional data by incorporating a subject-specific time-varying validity indicator that explicitly distinguishes structural zeros from intrinsic values. We iteratively estimate the latent functional covariates and zero-inflation probabilities via maximum likelihood, using basis expansions and linear mixed models to adjust for measurement error. To assess the effects of the recovered latent covariates, we apply joint quantile regression across multiple quantile levels. Through extensive simulations, we demonstrate that our approach significantly improves estimation accuracy over methods that only address measurement error, and joint estimation yields substantial improvements compared with fitting separate quantile regressions. Applied to a childhood obesity study, our approach effectively corrects for zero inflation and measurement error in step counts, yielding results that closely align with energy expenditure and supporting their use as a proxy for physical activity.

This scoping literature review addresses the research question of measuring stress: What methodologies and associated metrics are employed for the in-situ assessment of stress among knowledge workers? Lab and field studies of any qualitative, quantitative, or mixed design reported in English from 2000 to 15 October 2024 were retrieved from Compendex, PubMed, and Web of Science. The 17 included studies covered office workers in several countries; all included qualitative elements while a minority (6) included quantitative methods. Future research would benefit from the development of unobtrusive data collection methods and analysis of different types of stressors on office workers. The review also informs which methodologies and metrics might be applied to hybrid office workers, a subset of knowledge/office workers, in future studies on stress.

Introduction: While much is known about the complexities of fall-related risks among older adults, less is known about the risk for falls among men, and especially older non-Hispanic Black and Hispanic men with chronic conditions. To address this crucial gap in safety research, this study examined factors associated with incident falls (1 fall) and recurrent falling (2+ falls) among non-Hispanic Black and Hispanic men ages ≥60 years with ≥1 chronic condition. Method: Collected with a cross-sectional, web-delivered questionnaire, data were analyzed from a national sample of 779 non-Hispanic Black (58.8%) and Hispanic (41.2%) men. To assess incident and recurrent falls, the number of self-reported falls in the past year was trichotomized (0 falls vs. 1 fall vs. 2+ falls) and used as the dependent variable. A multinomial logistic regression was fitted to assess factors associated with incident and recurrent falls. The model adjusted for sociodemographics, disease characteristics, health status, and social support. Results: On average, participants were aged 66.8 (±5.4) years and reported 3.8 (±2.7) chronic conditions. Seventy-three percent of men reported 0 falls, 12.6% reported 1 fall, and 14.4% reported 2+ falls in the past year. Relative to men reporting 0 falls, Hispanic men (P < 0.05), men with worse general health status (P < 0.05), and those with clinical depression (P < 0.05) were more likely to report incident and recurrent falls, respectively. Men with more comorbidities (P < 0.05) and those with less help/support to manage health problems (P < 0.05) were more likely to report recurrent falls. Conclusions: Findings highlight the importance of multi-component interventions to prevent falls by strengthening disease self-management, addressing mental health, and introducing social support. Practical applications: This study contributes to the understanding of fall-related risks among older non-Hispanic Black and Hispanic men with chronic conditions and highlights the need for interdisciplinary collaboration in fall prevention efforts.

Assistive technologies can help persons with disabilities (PWD) gain independence and improve their quality of life. However, for these technologies to be helpful, interface design is important to ensure devices can be seamlessly added to everyday life. This study investigates a novel approach to assess the usability of assistive technologies called SUMA - The Single Usability Metric that Accounts for Accessibility. The model includes 13 common measures used to capture website and app usability with special consideration to measure accessibility. To simplify the model, user testing was conducted with PWD, and principal component analysis of the results revealed a subset of dimensions. The finalized SUMA model includes four usability metrics: satisfaction, efficiency, learnability, and accessibility. The model is coded into an Excel workbook enabling other researchers to easily use SUMA to assess the usability of their technologies for PWD. Findings highlighted the importance of capturing accessibility to ensure inclusive design.

BackgroundObesity has become an important threat to children’s health, with physical and psychological impacts that extend into adulthood. Limited physical activity and sedentary behavior are associated with increased obesity risk. Because children spend approximately 6 h each day in school, researchers increasingly study how obesity is influenced by school-day physical activity and energy expenditure (EE) patterns among school-aged children by using wearable devices that collect data at frequent intervals and generate complex, high-dimensional data. Although clinicians typically define obesity in children as having an age-and sex-adjusted body mass index (BMI) value in the high percentiles, the relationships between school-based physical activity interventions and BMI are analyzed using traditional linear regression models, which are designed to assess the effects of interventions among children with average BMI, limiting insight regarding the effects of interventions among children categorized as overweight or obese.MethodsWe investigate the association between wearable device–based EE measures and age-and sex-adjusted BMI values in data from a cluster-randomized, school-based study. We express and analyze EE levels as both a scalar-valued variable and as a continuous, high-dimensional, functional predictor variable. We investigate the relationship between school-day EE (SDEE) and BMI using four models: a linear mixed-effects model (LMEM), a quantile mixed-effects model (QMEM), a functional mixed-effects model (FMEM), and a functional quantile mixed-effects model (FQMEM). The LMEM and QMEM include SDEE as a summary measure, whereas the FMEM and FQMEM allow for the modeling of SDEE as a high-dimensional covariate. The FMEM and FQMEM allow the influence of the time of day at which physical activity is performed to be assessed, which is not possible using the LMEM or the QMEM. The FMEM assesses how frequently collected SDEE data influences mean BMI, whereas the FQMEM assesses the effects on quantile levels of BMI.ResultsThe LMEM and QMEM detected a statistically significant effect of overall mean SDEE on log (BMI) (the natural logarithm of BMI) after adjusting for intervention, age, race, and sex. The FMEM and FQMEM provided evidence for statistically significant associations between SDEE and log (BMI) for only a short time interval. Being a boy or being assigned a stand-biased desk is associated with a lower log (BMI) than being a girl or being assigned a traditional desk. Across our models, age was not a statistically significant covariate, and white students had significantly lower log (BMI) than non-white students in quantile models, but this significant effect was observed for only the 10th and 50th quantile levels of BMI. The functional regression models allow for additional interpretations of the influence of EE patterns on age-and sex-adjusted BMI, whereas the quantile regression models enable the influence of EE patterns to be assessed across the entire BMI distribution.ConclusionThe FQMEM is recommended when interest lies in assessing how device-monitored SDEE patterns affect children of all body types, as this model is robust and able to assess intervention effects across the full BMI distribution. However, the sample size must be sufficiently large to adequately power determinations of covariate effects across the entire BMI distribution, including the tails.

Limb amputation can lead to significant functional challenges in daily activities, prompting amputees to use prosthetic devices (PDs). However, the cognitive demands of PDs and usability issues have resulted in user rejections. This study aimed to create a Human Performance Model for Upper-Limb Prosthetic Devices (HPM-UP). The model used formulations of learnability, error rate, memory load, efficiency, and satisfaction to assess usability. The model was validated in an experiment with 30 healthy participants using a bypass prosthetic device. Findings indicated that the HPM-UP successfully predicted the usability of prosthetic devices, aligning with human subject data. This research proposes a quantitative approach to predict upper limb prosthetic device usability by quantifying each dimension and computationally connecting them. The model, available on Github and executable with Rstudio, could enable clinicians to assess and analyze the human performance of various commercial prostheses, aiding in recommending optimal devices for patients.

Objective:Standing desks present a novel approach to reduce sedentary time in the classroom and address cardiovascular risk factors at an early age. In the context of designing a standing desk study, parents and children were surveyed regarding their perceptions and current use of standing desks and other flexible seating. Methods:Survey administered from January 31st to February 26th, 2024 to a convenience cohort of 50 parent-child pairs presenting for well or acute care at a pediatrics clinic affiliated with an academic institution (Hershey, Pennsylvania, United States). Logistic regression examined parent support of and child willingness to use a standing desk in the classroom. Results:Parents were primarily non-Hispanic, white females above 40 years of age. Child participants mean age and grade level were 10.5 years and 5th grade respectively. Among parents, 85 % (39/46) were supportive of their child's use of a standing desk in the classroom, with 4 declining to answer. For children, almost half, 48 % (24/50), were willing to use a standing desk. Acceptability decreased for child body mass index (BMI) ≥85th percentile versus BMI <85th percentile (parent acceptability OR = 0.07 [95 % CI: 0.01-0.63; p = 0.018]; child acceptability: OR = 0.13 [95 % CI 0.03-0.51, p = 0.003]). Conclusions:Most parents and children are amenable to use of a standing desk in the classroom. Additional information for children with elevated BMI and their parents may be required to address reservations about standing. This study was limited by its small sample size, which may not generalize to other populations.

We examined factors associated with incident (one) and recurrent (2+) falls among 7207 non-Hispanic White (NHW) (89.7%), non-Hispanic Black (NHB) (5.0%), and Hispanic (5.3%) men ages ≥60 years with ≥1 chronic conditions, enrolled in an evidence-based fall program. Multinomial and binary regression analyses were used to assess factors associated with incident and recurrent falls. Relative to zero falls, NHB and Hispanic men were less likely to report incident (OR = 0.55, p < .001 and OR = 0.70, p = .015, respectively) and recurrent (OR = 0.41, p < .001 and OR = 0.58, p < .001, respectively) falls. Men who reported fear of falling and restricting activities were more likely to report incident (OR = 1.16, p < .001 and OR = 1.32, p < .001, respectively) recurrent and (OR = 1.46, p < .001 and OR = 1.71, p < .001, respectively) falls. Men with more comorbidities were more likely to report recurrent falls (OR = 1.10, p < .001). Compared to those who experienced one fall, men who reported fear of falling (OR = 1.28, p < .001) and restricting activities (OR = 1.31, p < .001) were more likely to report recurrent falls. Findings highlight the importance of multi-component interventions to prevent falls.

Unintentional falls cause significant morbidity and are major contributors to mortality among older adults, but less is known about fall-related risk for older men. This study identified modifiable and nonmodifiable risk factors for incident and recurrent falls among older males ages ≥60 years. We searched Medline (OVID), CINAHL, Ultimate, Cochrane, and Embase, for observational studies showing risk factor association with falls among community-based older adult populations. Two hundred studies were identified and 38 met the inclusion criteria. Sixty risk factors, ranging from behavior to environmental, were reviewed. The main risk factors associated with incident and recurrent falls include pain, age, depression, fear of falling, activity/mobility limitations, sleep disorder/chronic hypoxemia, and multimorbidity. Some risk factors, such as pain and multimorbidity, demonstrated dose-response relationships with recurrent falls. Primary studies are needed to investigate the effects of these risk factors on falling among older adult males, with considerations for racial/ethnicity differences.

In this study, we found that workers who use stand-biased desks stood more and sat less during their workday compared to workers who use traditional desks. Stand-biased users also experienced significantly less lower back discomfort compared to both traditional and sit-stand workstation users. Based on these findings, we recommend that the use of stand-biased workstations be considered when designing or renovating work office workspaces. The health risks of sedentary behavior are inherent in most office work, but these risks can be alleviated with intentional equipment choices. Using stand-biased desks can encourage workers to move more throughout the workday without their productivity or comfort being disturbed. Background: Sedentary activity, especially occupational sitting, is a leading cause of musculoskeletal discomfort among office workers. The amount of time employees spend seated is associated with the type of workstation that they utilize.Purpose: We investigated differences in computer utilization, physical activity, and discomfort among office workers who used three workstation types (stand-biased, sit-stand, or traditional).Methods: Among a sample of office workers (n = 61), we used data-logging software to measure computer utilization over 10 days, activity sensors to measure daily general activity levels (i.e., sitting, standing, running, etc.) during the 8am-5pm workday and the 24-h day, and the Nordic Musculoskeletal Questionnaire (NMQ) to evaluate discomfort.Results: There was no significant difference in the number of keyclicks between the three groups; however, the stand-biased group had a significantly higher word count and more errors than the traditional group. The 24-h activity data revealed that the stand-biased group had significantly more standing time, less sitting time, and fewer transitions per hour compared to their traditional counterparts.Conclusions: Stand-biased workstations can be a viable workstation alternative to reduce sitting time without decreasing activity or creating additional discomfort.

Clustering analysis of functional data, which comprises observations that evolve continuously over time or space, has gained increasing attention across various scientific disciplines. Practical applications often involve functional data that are contaminated with measurement errors arising from imprecise instruments, sampling errors, or other sources. These errors can significantly distort the inherent data structure, resulting in erroneous clustering outcomes. In this paper, we propose a simulation-based approach designed to mitigate the impact of measurement errors. Our proposed method estimates the distribution of functional measurement errors through repeated measurements. Subsequently, the clustering algorithm is applied to simulated data generated from the conditional distribution of the unobserved true functional data given the observed contaminated functional data, accounting for the adjustments made to rectify measurement errors. We illustrate through simulations show that the proposed method has improved numerical performance than the naive methods that neglect such errors. Our proposed method was applied to a childhood obesity study, giving more reliable clustering results

BACKGROUND:Although the association of chronic pain (CP) with a poor work-life balance has been well studied, the interaction effect of multiple pain sites on work-life balance is unknown.OBJECTIVE:To evaluate the most prevalent CP site among healthcare workers, the demographic characteristics of the individuals with the predominant pain type, and to assess the interaction of multiple pain sites on work-life balance.METHODS:Using data from the National Health Interview Survey, 2,458 healthcare works were identified for this study. The independent variables were chronic low back and hip pain. The dependent variables were (1) if pain affected their family or significant other, (2) if pain limited their life or work activities, and (3) Usually working >35 hours/week. Multiple logistic regression and an interaction analysis were used to analyze the impact of different pain sites on work-life balance.RESULTS:Among healthcare workers, chronic low back pain was more prevalent than chronic hip pain (69.4% vs 61.4%, p-value<0.001). Respondents with chronic low back pain were mostly 40 - 64 years of age (49.6%), females (71.2%), white (77.6%), married (55.5%), had no college degree (85.4%), earn greater than $75,000 (50.0%). In the interaction analysis, in the presence of chronic hip pain, those with chronic low back pain had an AOR of 2.20 (1.05 - 4.64), p-value 0.038 of chronic low back pain affecting their family and significant others, and an AOR of 2.18 (1.17- 4.05), p-value 0.014 of chronic low back pain affecting their life or work.CONCLUSION:Chronic low back pain was more prevalent than chronic hip pain among healthcare workers. Together both pain sites had a significant impact on the work-life balance of this population. Further studies should assess other dimensions of work-life balance and chronic pain.

Alternative work arrangements have emerged as potential solutions to enhance productivity and work-life balance. However, accurate and objective measurement of work patterns is essential to make decisions about adjusting work arrangements. This study aimed at evaluating objective computer usage metrics as a proxy for productivity using RSIGuard, an ergonomics monitoring software. Data were collected from 789 office-based employees over a two-year period between January 1, 2017 and December 31, 2018 at a large energy company in Texas. A generalized mixed-effects model was utilized to compare computer usage patterns across different days of the week and times of the day. Our findings demonstrate that computer output metrics significantly decrease on Fridays compared to other weekdays, even after controlling for total active hours. Additionally, we found that workers' output varied depending on the time of day, with reduced computer usage observed in the afternoons and a significant decrease on Friday afternoons. The decrease in the number of typos was much less than that in the number of words typed, indicating reduced work efficiency on Friday afternoons. These objective indicators provide a novel approach to evaluating the productivity during the workweek and can help optimize work arrangements to promote sustainability for the benefit of employers, employees, and the environment.

The population of older Americans with cognitive impairments, especially memory loss, is growing. Autonomous vehicles (AVs) have the potential to improve the mobility of older adults with cognitive impairment; however, there are still concerns regarding AVs' usability and accessibility in this population. Study objectives were to (1) better understand the needs and requirements of older adults with mild and moderate cognitive impairments regarding AVs, and (2) create a prototype for a holistic, user-friendly interface for AV interactions. An initial (Generation 1) prototype was designed based on the literature and usability principles. Based on the findings of phone interviews and focus group meetings with older adults and caregivers (n = 23), an enhanced interface (Generation 2) was developed. This generation 2 prototype has the potential to reduce the mental workload and anxiety of older adults in their interactions with AVs and can inform the design of future in-vehicle information systems for older adults.

Abstract Objective: Few studies have examined factors affecting the high frequency of hospitalization for pediatric asthma. This study identifies individual and environmental characteristics of children with asthma from a low-income community with a high number of hospitalizations. Methods: The study population included 902 children admitted at least once to a children’s hospital in South Texas because of asthma from 2010 to 2016. The population was divided into three groups by utilization frequency (high: ≥4 times, medium: 2–3 times, or low: 1 time). Individual-level factors at index admission and environmental factors were included for the analysis. Unadjusted and adjusted multivariate ordered logistic regression models were applied to identify significant characteristics of high hospital utilizers. Results: The high utilization group comprised 2.4% of total patients and accounted for substantial hospital resource utilization: 10.8% of all admissions and 13.5% of days stayed in the hospital. Patients in the high utilization group showed longer length of stay (LOS) and shorter time between admissions on average than the other two groups. The multivariate ordered logistic regression models revealed that age of 5–11 years (OR = 0.57, 95%CI = 0.35–0.93), longer LOS (2 days: OR = 1.80, 95%CI = 1.15–2.84; ≥3 days: OR = 3.38, 95%CI = 2.10–5.46), warm season at index admission (OR = 1.49, 95%CI = 1.01–2.20), and higher average ozone level in children’s residential neighborhoods (OR = 1.78, 95%CI = 1.01–3.14) were significantly associated with a higher number of asthma hospitalizations. Conclusions: The findings suggest the importance of monitoring high hospital utilizers and establishing strategies for such patients based on their characteristics to reduce repeated hospitalizations and to increase optimal use of hospital resources.

Baby boomers, born between 1946 and 1964, comprise a significant portion of the United States’ older adult population. Retirement is also a hallmark of their current life stage. While a body of literature points to the benefits of leisure activities in later life, the roles and relevance of leisure during the retirement transition among first-generation immigrant baby boomers are not well understood. The purpose of this study was to explore leisure throughout the lifespan among first-generation Korean immigrant men (N = 19) and how their cultural values and leisure involvement played out during the retirement transition. Guided by continuity theory of normal aging (Atchley, 1989) and leisure innovation theory (Nimrod, 2008), findings from interview data through interpretive phenomenological analysis (Smith et al., 1995) indicated that (1) perceptions and definition of leisure is shaped by their cultural backgrounds; (2) leisure in the working years mostly involved family leisure activities with an emphasis on providing their children with educational values; (3) leisure activities such as golf and fishing were a particular interest for this demographic, but meanings changed over time; (3) leisure provided continuity during the retirement; and (4) retirement was viewed as an opportunity for new leisure activities, but limited availability of sport and recreation programs was perceived as a barrier. These findings yield meaningful implications in that (a) leisure engagement can provide continuity in maintaining their social roles over the lifespan; and (b) more community-based sport and recreation programs targeting older adults would help them successfully transition to retirement.

With a rapidly aging workforce and the rising prevalence of chronic conditions, efforts are needed to better understand the needs of older adult workers and how to create supportive working environments for them. This study examines factors associated with job satisfaction among full-time employed adults ages 60+ years with 1+ chronic conditions. Data were collected with an internet-delivered survey in January 2022. Analyses included 337 older adult workers with chronic conditions. An ordinal regression model was fitted to assess factors associated with higher levels of job satisfaction. The model adjusted for sociodemographics, disease characteristics, social engagement, work logistics, and perceptions about the workplace. On average, participants were age 65.14(±4.56) years and self-reported 3.05(±2.09) chronic conditions. Twenty-eight percent reported being very satisfied with their current job and 48.4% worked remotely 1+ days per work week. Higher job satisfaction levels were positively associated with being Hispanic (β=0.68, P=0.030), exhibiting stronger organizational citizenship behavior (β=0.16, P< 0.001), and working more days remotely (β=0.12, P=0.026). Higher job satisfaction levels were negatively associated with job-related stress (β=-0.26, P< 0.001), feelings of social disconnectedness (β=-0.12, P=0.010), and greater intentions of leaving current jobs within the next three months (β=-0.70, P< 0.001). Findings suggest that job satisfaction among older adult workers is rooted in their compatibility with their organizations’ work environment, management of job-related stressors, and opportunity to engage in meaningful and fulfilling interactions with others. Strategies such as remote working are encouraged to give older adults flexibility to promote work-life balance and self-manage their chronic conditions.

BACKGROUND: Remote working may enhance company resiliency during natural disasters and other events causing workplace displacement. OBJECTIVE: We conducted an interrupted time series analysis to investigate the impact of Hurricane Harvey on employee computer use during and after a seven-month displacement period from the physical workplace. METHODS: Ergonomic software was used to collect information on employees’ computer usage. RESULTS: Although there was no change in total computer use in response to the hurricane (β 0.25), active computer use significantly declined (β –0.90). All measured computer use behaviors returned to baseline prior to the complete return to the physical workspace. CONCLUSION: Despite a transient period of reduced activity during closure of the workplace building, productivity returned to normal prior to the employees’ return to a commercial workspace. The ability to work remotely may improve resiliency of employees to perform workplace tasks during events causing workplace displacement.

This data set includes 3 groups of participants categorized by their workstation: traditional (seated), Sit-stand, and Stand-biased. All participants conduct primarily administrative duties at work. Collected pre COVIDDataset includes activity measures from activPAL3 and activPAL micro accelerometers, computer utilization from CorityEnviance, demographic data from an IRB approved questionnaire and musculoskeletal data via the Nordic Musculoskeletal Questionnaire. The first tab includes the coded guide for the database. All participants were included as long as they provided at least one of the collected measures.

Objective: The aim of this study is to explore the current characteristics of people with chronic lower back (CLB) pain, and the sociodemographic and work-related predictors of this pain. Study design: The study design used in the study is a cross-sectional study. Method: The 2018 National Health Interview Survey data were used. Chi-squared analysis was used to assess the sociodemographic characteristics, and logistic regression was used to analyze the risk factors after multiple imputation. Results: Of the 72,831 respondents, 25,397 had provided data on CLB pain and were eligible for this study. People with CLB pain were more likely to be obese, white, female, older than 40 years, and did not have a college degree. They were more likely to carry out less than 150 min of moderate aerobic exercise per week. Age was the sociodemographic predictor of CLB pain (P-value <0.001). After imputation and adjusting for covariates, construction and extraction and military-specific occupational groups were associated with an increased risk of CLB pain [odds ratios (OR): 1.32, confidence interval (CI): 1.10-1.59, P-value = 0.004; OR: 2.20, CI: 1.36-3.55, P-value = 0.001]. Working between 41 and 60 h/week significantly also had an increased risk of developing CLB pain (OR: 1.13, CI: 1.01-1.27, P-value 0.043; OR: 1.23, CI: 1.10-1.37, P-value <0.001). Conclusion: Low socio-economic status, poor physical fitness, work-life imbalance, and the type of occupation contribute to the development of CLB pain. An improvement in preventive measures is needed to address this morbidity. More studies should be carried out to analyze the type of workplace movements that increase the risk of developing CLB. (C) 2021 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.