Monitoring Activity and Gait in Children (MAGIC) using digital health technologies.

Background: Digital health technologies (DHTs) can collect gait and physical activity in adults, but limited studies have validated these in children. This study compared gait and physical activity metrics collected using DHTs to those collected by reference comparators during in-clinic sessions, to collect a normative accelerometry dataset, and to evaluate participants' comfort and their compliance in wearing the DHTs at-home.

Methods: The MAGIC (Monitoring Activity and Gait in Children) study was an analytical validation study which enrolled 40, generally healthy participants aged 3-17 years.

Evaluating a novel 24-hour rest/activity rhythm marker of preclinical β-amyloid deposition.

Study Objectives: To compare sleep and 24-hour rest/activity rhythms (RARs) between cognitively normal older adults who are β-amyloid-positive (Aβ+) or Aβ- and replicate a novel time-of-day-specific difference between these groups identified in a previous exploratory study.

Methods: We studied 82 cognitively normal participants from the Baltimore Longitudinal Study of Aging (aged 75.7 ± 8.

The roles, challenges, and merits of the p value.

Since the 18th century, the p value has been an important part of hypothesis-based scientific investigation. As statistical and data science engines accelerate, questions emerge: to what extent are scientific discoveries based on p values reliable and reproducible? Should one adjust the significance level or find alternatives for the p value? Inspired by these questions and everlasting attempts to address them, here, we provide a systematic examination of the p value from its roles and merits to its misuses and misinterpretations. For the latter, we summarize modest recommendations to handle them.

SciKit digital health package for accelerometry-measured physical activity: comparisons to existing solutions and investigations of age effects in healthy adults.

Introduction: Accelerometry has become increasingly prevalent to monitor physical activity due to its low participant burden, quantitative metrics, and ease of deployment. Physical activity metrics are ideal for extracting intuitive, continuous measures of participants' health from multiple days or weeks of high frequency data due to their fairly straightforward computation. Previously, we released an open-source digital health python processing package, SciKit Digital Health (SKDH), with the goal of providing a unifying device-agnostic framework for multiple digital health algorithms, such as activity, gait, and sleep.

Can Gait Characteristics Be Represented by Physical Activity Measured with Wrist-Worn Accelerometers?

Wearable accelerometers allow for continuous monitoring of function and behaviors in the participant's naturalistic environment. Devices are typically worn in different body locations depending on the concept of interest and endpoint under investigation. The lumbar and wrist are commonly used locations: devices placed at the lumbar region enable the derivation of spatio-temporal characteristics of gait, while wrist-worn devices provide measurements of overall physical activity (PA).

Decentralized clinical trials and rare diseases: a Drug Information Association Innovative Design Scientific Working Group (DIA-IDSWG) perspective.

Background: Traditional clinical trials require tests and procedures that are administered in centralized clinical research sites, which are beyond the standard of care that patients receive for their rare and chronic diseases. The limited number of rare disease patients scattered around the world makes it particularly challenging to recruit participants and conduct these traditional clinical trials.

Main Body: Participating in clinical research can be burdensome, especially for children, the elderly, physically and cognitively impaired individuals who require transportation and caregiver assistance, or patients who live in remote locations or cannot afford transportation.

Wrist-Worn Accelerometry, Aging, and Gait Speed in the Baltimore Longitudinal Study of Aging.

Wrist-worn accelerometry metrics are not well defined in older adults. Accelerometry data from 720 participants (mean age 70 years, 55% women) were summarized into (a) total activity counts per day, (b) active minutes per day, (c) active bouts per day, and (d) activity fragmentation (the reciprocal of the mean active bout length). Linear regression and mixed-effects models were utilized to estimate associations between age and gait speed with wrist accelerometry.

Comparing three wearable accelerometers to measure early activity after cardiac surgery.

Objective: Wearable activity monitors can provide detailed data on activity after cardiac surgery and discriminate a patient's risk for hospital-based outcomes. However, comparative data for different monitoring approaches, as well as predictive ability over clinical characteristics, are lacking. In addition, data on specific thresholds of activity are needed.

Rest-Activity Rhythm Is Associated With Obesity Phenotypes: A Cross-Sectional Analysis.

Background: The prevalence of obesity continues to increase in spite of substantial efforts towards its prevention, posing a major threat to health globally. Circadian disruption has been associated with a wide range of preclinical and clinical disorders, including obesity. However, whether rest-activity rhythm (RAR), an expression of the endogenous circadian rhythm, is associated with excess adiposity is poorly understood.

Considerations to address missing data when deriving clinical trial endpoints from digital health technologies.

Digital health technologies (DHTs) enable us to measure human physiology and behavior remotely, objectively and continuously. With the accelerated adoption of DHTs in clinical trials, there is an unmet need to identify statistical approaches to address missing data to ensure that the derived endpoints are valid, accurate, and reliable. It is not obvious how commonly used statistical methods to handle missing data in clinical trials can be directly applied to the complex data collected by DHTs.

Brain amyloid burden, sleep, and 24-hour rest/activity rhythms: screening findings from the Anti-Amyloid Treatment in Asymptomatic Alzheimer's and Longitudinal Evaluation of Amyloid Risk and Neurodegeneration Studies.

Study Objectives: To examine in a subsample at the screening phase of a clinical trial of a β-amyloid (Aβ) antibody whether disturbed sleep and altered 24-hour rest/activity rhythms (RARs) may serve as markers of preclinical Alzheimer's disease (AD).

Methods: Overall, 26 Aβ-positive (Aβ+) and 33 Aβ-negative (Aβ-) cognitively unimpaired participants (mean age = 71.3 ± 4.

Demographic characteristics associated with circadian rest-activity rhythm patterns: a cross-sectional study.

Background: Rest-activity rhythm (RAR), a manifestation of circadian rhythms, has been associated with morbidity and mortality risk. However, RAR patterns in the general population and specifically the role of demographic characteristics in RAR pattern have not been comprehensively assessed. Therefore, we aimed to describe RAR patterns among non-institutionalized US adults and age, sex, and race/ethnicity variation using accelerometry data from a nationally representative population.

Analysis of Hearing Loss and Physical Activity Among US Adults Aged 60-69 Years.

Importance: Hearing loss may be a modifiable factor associated with decreased physical activity in older adults.

Objective: To examine the association of hearing loss with objectively measured physical activity, including moderate-to-vigorous physical activity, light-intensity physical activity, sedentary behavior, and pattern of physical activity (physical activity fragmentation).

Design, Setting, And Participants: This population-based cross-sectional study used National Health and Nutrition Examination Survey (NHANES) data collected in the 2003 to 2004 cycle and analyzed in 2017 to 2020.

Development of digital measures for nighttime scratch and sleep using wrist-worn wearable devices.

Patients with atopic dermatitis experience increased nocturnal pruritus which leads to scratching and sleep disturbances that significantly contribute to poor quality of life. Objective measurements of nighttime scratching and sleep quantity can help assess the efficacy of an intervention. Wearable sensors can provide novel, objective measures of nighttime scratching and sleep; however, many current approaches were not designed for passive, unsupervised monitoring during daily life.

Identifying neural signatures mediating behavioral symptoms and psychosis onset: High-dimensional whole brain functional mediation analysis.

Along the pathway from behavioral symptoms to the development of psychotic disorders sits the multivariate mediating brain. The functional organization and structural topography of large-scale multivariate neural mediators among patients with brain disorders, however, are not well understood. Here, we design a high-dimensional brain-wide functional mediation framework to investigate brain regions that intermediate between baseline behavioral symptoms and future conversion to full psychosis among individuals at clinical high risk (CHR).

Joint and Individual Representation of Domains of Physical Activity, Sleep, and Circadian Rhythmicity.

Developments in wearable technology have enabled researchers to continuously and objectively monitor various aspects and physiological domains of real-life including levels of physical activity, quality of sleep, and strength of circadian rhythm in many epidemiological and clinical studies. Current analytical practice is to summarize each of these three domains individually via a standard inventory of interpretable features, and explore individual associations between the features and clinical variables. However, the features often exhibit significant interaction and correlation both within and between domains.

Perfusion Pressure Lacks Diagnostic Specificity for the Diagnosis of Acute Compartment Syndrome.

Objective: To evaluate the diagnostic performance of perfusion pressure (PP) thresholds for fasciotomy.

Design: Prospective observational study.

Setting: Seven Level-1 trauma centers.

Organizing and analyzing the activity data in NHANES.

The NHANES study contains objectively measured physical activity data collected using hip-worn accelerometers from multiple cohorts. However, using the accelerometry data has proven daunting because: 1) currently, there are no agreed upon standard protocols for data storage and analysis; 2) data exhibit heterogeneous patterns of missingness due to varying degrees of adherence to wear-time protocols; 3) sampling weights need to be carefully adjusted and accounted for in individual analyses; 4) there is a lack of reproducible software that transforms the data from its published format into analytic form; and 5) the high dimensional nature of accelerometry data complicates analyses. Here, we provide a framework for processing, storing, and analyzing the NHANES accelerometry data for the 2003-2004 and 2005-2006 surveys.

Association of Total Daily Physical Activity and Fragmented Physical Activity With Mortality in Older Adults.

Importance: Fragmented daily physical activity may be a sign of physiological decline that provides more powerful insight into impending mortality than total daily activity.

Objective: To compare and contrast the association between total daily activity and activity fragmentation, which encompasses activity bouts and duration, and mortality risk.

Design, Setting, And Participants: In this cohort study, accelerometer data from 2007 through 2015 and mortality data from 2007 through 2017 were collected from 548 adults aged 65 years and older participating in the Baltimore Longitudinal Study of Aging.

Fragmentation as a novel measure of stability in normalized trajectories of mood and attention measured by ecological momentary assessment.

Electronic diary data, such as that acquired through Ecological Momentary Assessments (EMA), has historically provided novel insights into diverse psychological processes. Analyses of these data typically focus on modeling participant-specific means, variability, and stability. We propose a novel statistical framework to determine participant stability by quantifying fragmentation of standardized trajectories using the following 2-step approach: (1) participant-level EMA scores are normalized, and (2) normalized scores are dichotomized into 2 states, inside and outside a range of 1 standard deviation.

Active-to-Sedentary Behavior Transitions, Fatigability, and Physical Functioning in Older Adults.

Background: With aging, daily physical activity (PA) becomes less frequent and more fragmented. Accumulation patterns of daily PA-including transitions from active-to-sedentary behaviors-may provide important insights into functional status in older, less active populations.

Methods: Participants of the Baltimore Longitudinal Study of Aging (n = 680, 50% male, aged 27-94 years) completed a clinical assessment and wore an Actiheart accelerometer.

Continuous Near-Infrared Spectroscopy Demonstrates Limitations in Monitoring the Development of Acute Compartment Syndrome in Patients with Leg Injuries.

Background: We recorded measurements of muscle perfusion using near-infrared spectroscopy (NIRS) and intramuscular pressure (IMP) in a study designed to develop a decision rule for predicting acute compartment syndrome (ACS). The purpose of this study was to report our experience measuring NIRS data in the context of this broader investigation and to explore factors related to variations in data capture.

Methods: One hundred and eighty-five patients with lower-leg injuries had data consisting of continuous NIRS measurement of the O2 saturation in the anterior compartment of the injured limb and the contralateral (control) limb, and continuous IMP recording in the anterior and deep posterior compartments of the injured leg as part of their participation in an institutional review board-approved multicenter trial.

Novel metrics for growth model selection.

Background: Literature surrounding the statistical modeling of childhood growth data involves a diverse set of potential models from which investigators can choose. However, the lack of a comprehensive framework for comparing non-nested models leads to difficulty in assessing model performance. This paper proposes a framework for comparing non-nested growth models using novel metrics of predictive accuracy based on modifications of the mean squared error criteria.

Epidemiology of objectively measured bedtime and chronotype in US adolescents and adults: NHANES 2003-2006.

Background: We propose a method for estimating the timing of in-bed intervals using objective data in a large representative US sample, and quantify the association between these intervals and age, sex, and day of the week.

Methods: The study included 11,951 participants 6 years and older from the National Health and Nutrition Examination Survey (NHANES) 2003-2006, who wore accelerometers to measure physical activity for seven consecutive days. Participants were instructed to remove the device just before the nighttime sleep period and put it back on immediately after.