How acute affect dynamics impact longitudinal changes in physical activity among children.

Research examined how acute affect dynamics, including stability and context-dependency, contribute to changes in children's physical activity levels as they transition from late-childhood to early-adolescence. Children (N = 151) (ages 8-12 years at baseline) participated in an ecological momentary assessment and accelerometry study with six semi-annual bursts (7 days each) across three years. A two-stage mixed-effects multiple location-scale model tested random intercept, variance, and slope estimates for positive affect as predictors of moderate-to-vigorous physical activity (MVPA). Multi-year declines in MVPA were greater for children who had greater subject-level variance in positive affect. Children who experienced more positive affect when alone did not experience steeper declines in physical activity. Interventions aiming for long-term modifications in children's physical activity may focus on buffering the effects of within-day fluctuations in affect or tailoring programs to fit the needs of "acute dynamic process phenotypes."

Real-Time Data Collection to Examine Relations Between Physical Activity and Affect in Adults With Mental Illness.

Adults with serious mental illness engage in limited physical activity, which contributes to significant health disparities. This study explored the use of both ecological momentary assessments (EMAs) and activity trackers in adults with serious mental illness to examine the bidirectional relationship between activity and affect with multilevel modeling. Affective states were assessed up to seven times per day using EMA across 4 days. The participants (n = 20) were equipped with a waist-worn accelerometer to measure moderate to vigorous physical activity. The participants had a mean EMA compliance rate of 88.3%, and over 90% of completed EMAs were matched with 30-min windows of accelerometer wear. The participants who reported more positive affect than others had a higher probability of engaging in moderate to vigorous physical activity. Engaging in more moderate to vigorous physical activity than one's usual was associated with more negative affect. This study begins to address the effect of momentary mood on physical activity in a population of adults that is typically difficult to reach.

MixWILD: A program for examining the effects of variance and slope of time-varying variables in intensive longitudinal data.

The use of intensive sampling methods, such as ecological momentary assessment (EMA), is increasingly prominent in medical research. However, inferences from such data are often limited to the subject-specific mean of the outcome and between-subject variance (i.e., random intercept), despite the capability to examine within-subject variance (i.e., random scale) and associations between covariates and subject-specific mean (i.e., random slope). MixWILD (Mixed model analysis With Intensive Longitudinal Data) is statistical software that tests the effects of subject-level parameters (variance and slope) of time-varying variables, specifically in the context of studies using intensive sampling methods, such as ecological momentary assessment. MixWILD combines estimation of a stage 1 mixed-effects location-scale (MELS) model, including estimation of the subject-specific random effects, with a subsequent stage 2 linear or binary/ordinal logistic regression in which values sampled from each subject's random effect distributions can be used as regressors (and then the results are aggregated across replications). Computations within MixWILD were written in FORTRAN and use maximum likelihood estimation, utilizing both the expectation-maximization (EM) algorithm and a Newton-Raphson solution. The mean and variance of each individual's random effects used in the sampling are estimated using empirical Bayes equations. This manuscript details the underlying procedures and provides examples illustrating standalone usage and features of MixWILD and its GUI. MixWILD is generalizable to a variety of data collection strategies (i.e., EMA, sensors) as a robust and reproducible method to test predictors of variability in level 1 outcomes and the associations between subject-level parameters (variances and slopes) and level 2 outcomes.

Validity of proximity sensor-based wear-time detection using the ActiGraph GT9X.

Our study investigated the performance of proximity sensor-based wear-time detection using the GT9X under laboratory and free-living settings. Fifty-two volunteers (23.2 ± 3.8 y; 23.2 ± 3.7 kg/m2) participated in either a laboratory or free-living protocol. Lab participants wore and removed a wrist-worn GT9X on 3-5 occasions during a 3-hour directly observed activity protocol. The 2-day free-living protocol used an independent temperature sensor and self-report as the reference to determine if wrist and hip-worn GT9X accurately determined wear (i.e., sensitivity) and non-wear (i.e., specificity). Free-living estimates of wear/non-wear were also compared to Troiano 2007 and Choi 2012 wear/non-wear algorithms. In lab, sensitivity and specificity of the wrist-worn GT9X in detecting total minutes of wear-on and off was 93% and 49%, respectively. The GT9X detected wear-off more often than wear-on, but with a greater margin of error (4.8 ± 11.6 vs. 1.4 ± 1.4 min). In the free-living protocol, wrist and hip-worn GT9X's yielded sensitivity and specificity of 72 and 90% and 84 and 92%, respectively. GT9X estimations had inferior sensitivity but superior specificity to Troiano 2007 and Choi 2012 algorithms. Due to inaccuracies, it may not be advisable to singularly use the proximity-sensor-based wear-time detection method to detect wear-time.

REAL-TIME SUBJECTIVE ASSESSMENT OF PSYCHOLOGICAL STRESS: ASSOCIATIONS WITH OBJECTIVELY-MEASURED PHYSICAL ACTIVITY LEVELS.

Psychosocial stress may be a factor in the link between physical activity and obesity. This study examines how the daily experience of psychosocial stress influences physical activity levels and weight status in adults. This study reports temporally ordered relationships between sedentary, light, and moderate-to-vigorous physical activity levels and real-time reports of subjective psychosocial stress levels. Adults (n=105) wore an accelerometer and participated in an ecological momentary assessment (EMA) of stress by answering prompts on a mobile phone several times per day over 4 days. Subjective stress was negatively related to sedentary activity in the minutes immediately preceding and immediately following an EMA prompt. Light activity was positively associated with a subsequent EMA report of higher stress, but there were no observed associations between stress and moderate-to-vigorous activity. Real-time stress reports and accelerometer readings for the same 4-day period showed no association. Nor were there associations between real-time stress reports and weight status.

Estimation of Energy Expenditure for Wheelchair Users Using a Physical Activity Monitoring System.

OBJECTIVE: To develop and evaluate energy expenditure (EE) estimation models for a physical activity monitoring system (PAMS) in manual wheelchair users with spinal cord injury (SCI). DESIGN: Cross-sectional study. SETTING: University-based laboratory environment, a semistructured environment at the National Veterans Wheelchair Games, and the participants' home environments. PARTICIPANTS: Volunteer sample of manual wheelchair users with SCI (N=45). INTERVENTION: Participants were asked to perform 10 physical activities (PAs) of various intensities from a list. The PAMS consists of a gyroscope-based wheel rotation monitor (G-WRM) and an accelerometer device worn on the upper arm or on the wrist. Criterion EE using a portable metabolic cart and raw sensor data from PAMS were collected during each of these activities. MAIN OUTCOME MEASURES: Estimated EE using custom models for manual wheelchair users based on either the G-WRM and arm accelerometer (PAMS-Arm) or the G-WRM and wrist accelerometer (PAMS-Wrist). RESULTS: EE estimation performance for the PAMS-Arm (average error ± SD: -9.82%±37.03%) and PAMS-Wrist (-5.65%±32.61%) on the validation dataset indicated that both PAMS-Arm and PAMS-Wrist were able to estimate EE for a range of PAs with <10% error. Moderate to high intraclass correlation coefficients (ICCs) indicated that the EE estimated by PAMS-Arm (ICC3,1=.82, P<.05) and PAMS-Wrist (ICC3,1=.89, P<.05) are consistent with the criterion EE. CONCLUSIONS: Availability of PA monitors can assist wheelchair users to track PA levels, leading toward a healthier lifestyle. The new models we developed can estimate PA levels in manual wheelchair users with SCI in laboratory and community settings.

Feasibility and Performance Test of a Real-Time Sensor-Informed Context-Sensitive Ecological Momentary Assessment to Capture Physical Activity.

BACKGROUND: Objective physical activity monitors (eg, accelerometers) have high rates of nonwear and do not provide contextual information about behavior. OBJECTIVE: This study tested performance and value of a mobile phone app that combined objective and real-time self-report methods to measure physical activity using sensor-informed context-sensitive ecological momentary assessment (CS-EMA). METHODS: The app was programmed to prompt CS-EMA surveys immediately after 3 types of events detected by the mobile phone's built-in motion sensor: (1) Activity (ie, mobile phone movement), (2) No-Activity (ie, mobile phone nonmovement), and (3) No-Data (ie, mobile phone or app powered off). In addition, the app triggered random (ie, signal-contingent) ecological momentary assessment (R-EMA) prompts (up to 7 per day). A sample of 39 ethnically diverse high school students in the United States (aged 14-18, 54% female) tested the app over 14 continuous days during nonschool time. Both CS-EMA and R-EMA prompts assessed activity type (eg, reading or doing homework, eating or drinking, sports or exercising) and contextual characteristics of the activity (eg, location, social company, purpose). Activity was also measured with a waist-worn Actigraph accelerometer. RESULTS: The average CS-EMA + R-EMA prompt compliance and survey completion rates were 80.5% and 98.5%, respectively. More moderate-to-vigorous intensity physical activity was recorded by the waist-worn accelerometer in the 30 minutes before CS-EMA activity prompts (M=5.84 minutes) than CS-EMA No-Activity (M=1.11 minutes) and CS-EMA No-Data (M=0.76 minute) prompts (P's<.001). Participants were almost 5 times as likely to report going somewhere (ie, active or motorized transit) in the 30 minutes before CS-EMA Activity than R-EMA prompts (odds ratio=4.91, 95% confidence interval=2.16-11.12). CONCLUSIONS: Mobile phone apps using motion sensor-informed CS-EMA are acceptable among high school students and may be used to augment objective physical activity data collected from traditional waist-worn accelerometers.

Within-Day Time-Varying Associations Between Behavioral Cognitions and Physical Activity in Adults.

This study used time-varying effect modeling to examine time-of-day differences in how behavioral cognitions predict subsequent physical activity (PA). Adults (N = 116) participated in three 4-day "bursts" of ecological momentary assessment (EMA). Participants were prompted with eight EMA questionnaires per day assessing behavioral cognitions (i.e., intentions, self-efficacy, outcome expectations) and wore an accelerometer during waking hours. Subsequent PA was operationalized as accelerometer-derived minutes of moderate- or vigorousintensity PA in the 2 hr following the EMA prompt. On weekdays, intentions positively predicted subsequent PA in the morning (9:25 a.m.-11:45 a.m.) and in the evening (8:15 p.m.-10:00 p.m.). Self-efficacy positively predicted subsequent PA on weekday evenings (7:35 p.m.-10:00 p.m.). Outcome expectations were unrelated to subsequent PA on weekdays. On weekend days, behavior cognitions and subsequent PA were unrelated regardless of time of day. This study identifies windows of opportunity and vulnerability for motivation-based PA interventions aiming to deliver intervention content within the context of adults' daily lives.

Adaptive intervention design in mobile health: Intervention design and development in the Cell Phone Intervention for You trial.

BACKGROUND/AIMS: The obesity epidemic has spread to young adults, and obesity is a significant risk factor for cardiovascular disease. The prominence and increasing functionality of mobile phones may provide an opportunity to deliver longitudinal and scalable weight management interventions in young adults. The aim of this article is to describe the design and development of the intervention tested in the Cell Phone Intervention for You study and to highlight the importance of adaptive intervention design that made it possible. The Cell Phone Intervention for You study was a National Heart, Lung, and Blood Institute-sponsored, controlled, 24-month randomized clinical trial comparing two active interventions to a usual-care control group. Participants were 365 overweight or obese (body mass index≥25 kg/m2) young adults. METHODS: Both active interventions were designed based on social cognitive theory and incorporated techniques for behavioral self-management and motivational enhancement. Initial intervention development occurred during a 1-year formative phase utilizing focus groups and iterative, participatory design. During the intervention testing, adaptive intervention design, where an intervention is updated or extended throughout a trial while assuring the delivery of exactly the same intervention to each cohort, was employed. The adaptive intervention design strategy distributed technical work and allowed introduction of novel components in phases intended to help promote and sustain participant engagement. Adaptive intervention design was made possible by exploiting the mobile phone's remote data capabilities so that adoption of particular application components could be continuously monitored and components subsequently added or updated remotely. RESULTS: The cell phone intervention was delivered almost entirely via cell phone and was always-present, proactive, and interactive-providing passive and active reminders, frequent opportunities for knowledge dissemination, and multiple tools for self-tracking and receiving tailored feedback. The intervention changed over 2 years to promote and sustain engagement. The personal coaching intervention, alternatively, was primarily personal coaching with trained coaches based on a proven intervention, enhanced with a mobile application, but where all interactions with the technology were participant-initiated. CONCLUSION: The complexity and length of the technology-based randomized clinical trial created challenges in engagement and technology adaptation, which were generally discovered using novel remote monitoring technology and addressed using the adaptive intervention design. Investigators should plan to develop tools and procedures that explicitly support continuous remote monitoring of interventions to support adaptive intervention design in long-term, technology-based studies, as well as developing the interventions themselves.

Using ecological momentary assessment to understand where and with whom adults' physical and sedentary activity occur.

PURPOSE: This study used Ecological Momentary Assessment (EMA), a real-time self-report strategy, to describe the physical and social contexts of adults' physical activity and sedentary activity during their everyday lives and to determine whether these patterns and relationships differ for men and women. METHODS: Data from 114 adults were collected through mobile phones across 4 days. Eight electronic EMA surveys were randomly prompted each day asking about current activities (e.g., physical or sedentary activity), physical and social contexts, and perceived outdoor environmental features (e.g., greenness/vegetation, safety, and traffic). All participants also wore accelerometers during this period to objectively measure moderate-to-vigorous physical activity (MVPA) and sedentary activity. RESULTS: Home was the most common physical context for EMA-reported physical and sedentary activity. Most of these activities occurred when participants were alone. When alone, the most commonly EMA-reported physical activity and sedentary activity was walking and reading/using computer, respectively. When in outdoor home locations (e.g., yard and driveway) women demonstrated higher levels of MVPA, whereas men demonstrated higher levels of MVPA when in outdoor park settings (ps < .05). Men but not women demonstrated higher levels of MVPA in settings with a greater degree of perceived greenness and vegetation (p < .05). CONCLUSIONS: The current study shows how EMA via mobile phones and accelerometers can be combined to offer an innovative approach to assess the contexts of adults' daily physical and sedentary activity. Future studies could consider utilizing this method in more representative samples to gather context-specific information to inform the development of physical activity interventions.

Accelerometry-based Recognition of the Placement Sites of a Wearable Sensor.

This work describes an automatic method to recognize the position of an accelerometer worn on five different parts of the body: ankle, thigh, hip, arm and wrist from raw accelerometer data. Automatic detection of body position of a wearable sensor would enable systems that allow users to wear sensors flexibly on different body parts or permit systems that need to automatically verify sensor placement. The two-stage location detection algorithm works by first detecting time periods during which candidates are walking (regardless of where the sensor is positioned). Then, assuming that the data refer to walking, the algorithm detects the position of the sensor. Algorithms were validated on a dataset that is substantially larger than in prior work, using a leave-one-subject-out cross-validation approach. Correct walking and placement recognition were obtained for 97.4% and 91.2% of classified data windows, respectively.

Burden and Inattentive Responding in a 12-Month Intensive Longitudinal Study: Interview Study Among Young Adults.

BACKGROUND: Intensive longitudinal data (ILD) collection methods have gained popularity in social and behavioral research as a tool to better understand behavior and experiences over time with reduced recall bias. Engaging participants in these studies over multiple months and ensuring high data quality are crucial but challenging due to the potential burden of repeated measurements. It is suspected that participants may engage in inattentive responding (IR) behavior to combat burden, but the processes underlying this behavior are unclear as previous studies have focused on the barriers to compliance rather than the barriers to providing high-quality data. OBJECTIVE: This study aims to broaden researchers' knowledge about IR during ILD studies using qualitative analysis and uncover the underlying IR processes to aid future hypothesis generation. METHODS: We explored the process of IR by conducting semistructured qualitative exit interviews with 31 young adult participants (aged 18-29 years) who completed a 12-month ILD health behavior study with daily evening smartphone-based ecological momentary assessment (EMA) surveys and 4-day waves of hourly EMA surveys. The interviews assessed participants' motivations, the impact of time-varying contexts, changes in motivation and response patterns over time, and perceptions of attention check questions (ACQs) to understand participants' response patterns and potential factors leading to IR. RESULTS: Thematic analysis revealed 5 overarching themes on factors that influence participant engagement: (1) friends and family also had to tolerate the frequent surveys, (2) participants tried to respond to surveys quickly, (3) the repetitive nature of surveys led to neutral responses, (4) ACQs within the surveys helped to combat overly consistent response patterns, and (5) different motivations for answering the surveys may have led to different levels of data quality. CONCLUSIONS: This study aimed to examine participants' perceptions of the quality of data provided in an ILD study to contribute to the field's understanding of engagement. These findings provide insights into the complex process of IR and participant engagement in ILD studies with EMA. The study identified 5 factors influencing IR that could guide future research to improve EMA survey design. The identified themes offer practical implications for researchers and study designers, including the importance of considering social context, the consideration of dynamic motivations, and the potential benefit of including ACQs as a technique to reduce IR and leveraging the intrinsic motivators of participants. By incorporating these insights, researchers might maximize the scientific value of their multimonth ILD studies through better data collection protocols. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/36666.

Investigating the day-level associations between affective variability and physical activity using ecological momentary assessment.

BACKGROUND: Understanding affect as a determinant of physical activity has gained increased attention in health behavior research. Fluctuations in affect intensity from moment-to-moment (i.e., affective variability) may interfere with cognitive and regulatory processes, making it difficult to engage in goal-directed behaviors such as physical activity. Preliminary evidence indicates that those with greater trait-level affective variability engage in lower levels of habitual physical activity. However, the extent to which daily fluctuations in affect variability are associated with same-day physical activity levels is unknown. This study used ecological momentary assessment (EMA) to investigate day-level associations between affective variability (i.e., within-subject variance) and physical activity. METHODS: Young adults (N = 231, M = 23.58 ± 3.02 years) provided three months of smartphone-based EMA and smartwatch-based activity data. Every two weeks, participants completed a 4-day EMA measurement burst (M = 5.17 ± 1.28 bursts per participant). Bursts consisted of hourly randomly-prompted EMA surveys assessing momentary positive-activated (happy, energetic), positive-deactivated (relaxed), negative-activated (tense, stressed), and negative-deactivated (sad, fatigued) affect. Participants continuously wore a smartwatch to measure physical activity across the three months. Mixed-effects location scale modeling examined the day-level associations of affective variability (i.e., positive-activated, positive-deactivated, negative-activated, and negative-deactivated) and physical activity, controlling for covariates such as mean levels of affect, between-subject effects of physical activity, time of day, day of week, day in study, and smartwatch wear time. RESULTS: There were 41,546 completed EMA surveys (M = 182.22 ± 69.82 per participant) included in the analyses. Above and beyond mean levels of affect, greater day-level variability in positive-activated affect was associated with greater physical activity on that same day compared to other days (τ = 0.01, p < .001), whereas greater day-level variability in negative-deactivated affect was associated with less physical activity on that same day compared to other days (τ = -0.01, p < .001). Day-level variability in positive-deactivated affect or negative-activated affect were not associated with day-level physical activity (ps > .05) CONCLUSIONS: Individuals were less active on days with greater variability in feeling sad and fatigued but more active on days with greater variability in feeling happy and energetic. Understanding the dynamic relationships of affective variability with day-level physical activity can strengthen physical activity interventions by considering how these processes differ within individuals and unfold within the context of daily life. Future research should examine causal pathways between affective variability and physical activity across the day.

mHealth-Based Just-in-Time Adaptive Intervention to Improve the Physical Activity Levels of Individuals With Spinal Cord Injury: Protocol for a Randomized Controlled Trial.

BACKGROUND: The lack of regular physical activity (PA) in individuals with spinal cord injury (SCI) in the United States is an ongoing health crisis. Regular PA and exercise-based interventions have been linked with improved outcomes and healthier lifestyles among those with SCI. Providing people with an accurate estimate of their everyday PA level can promote PA. Furthermore, PA tracking can be combined with mobile health technology such as smartphones and smartwatches to provide a just-in-time adaptive intervention (JITAI) for individuals with SCI as they go about everyday life. A JITAI can prompt an individual to set a PA goal or provide feedback about their PA levels. OBJECTIVE: The primary aim of this study is to investigate whether minutes of moderate-intensity PA among individuals with SCI can be increased by integrating a JITAI with a web-based PA intervention (WI) program. The WI program is a 14-week web-based PA program widely recommended for individuals with disabilities. A secondary aim is to investigate the benefit of a JITAI on proximal PA, defined as minutes of moderate-intensity PA within 120 minutes of a PA feedback prompt. METHODS: Individuals with SCI (N=196) will be randomized to a WI arm or a WI+JITAI arm. Within the WI+JITAI arm, a microrandomized trial will be used to randomize participants several times a day to different tailored feedback and PA recommendations. Participants will take part in the 24-week study from their home environment in the community. The study has three phases: (1) baseline, (2) WI program with or without JITAI, and (3) PA sustainability. Participants will provide survey-based information at the initial meeting and at the end of weeks 2, 8, 16, and 24. Participants will be asked to wear a smartwatch every day for ≥12 hours for the duration of the study. RESULTS: Recruitment and enrollment began in May 2023. Data analysis is expected to be completed within 6 months of finishing participant data collection. CONCLUSIONS: The JITAI has the potential to achieve long-term PA performance by delivering tailored, just-in-time feedback based on the person's actual PA behavior rather than a generic PA recommendation. New insights from this study may guide intervention designers to develop engaging PA interventions for individuals with disability. TRIAL REGISTRATION: ClinicalTrials.gov NCT05317832; https://clinicaltrials.gov/study/NCT05317832. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/57699.

A feasibility study on the use of audio-based ecological momentary assessment with persons with aphasia.

We describe a smartphone/smartwatch system to evaluate anomia in individuals with aphasia by using audio-recording-based ecological momentary assessments. The system delivers object-naming assessments to a participant's smartwatch, whereby a prompt signals the availability of images of these objects on the watch screen. Participants attempt to speak the names of the images that appear on the watch display out loud and into the watch as they go about their lives. We conducted a three-week feasibility study with six participants with mild to moderate aphasia. Participants were assigned to either a nine-item (four prompts per day with nine images) or single-item (36 prompts per day with one image each) ecological momentary assessment protocol. Compliance in recording an audio response to a prompt was approximately 80% for both protocols. Qualitative analysis of the participants' interviews suggests that the participants felt capable of completing the protocol, but opinions about using a smartwatch were mixed. We review participant feedback and highlight the importance of considering a population's specific cognitive or motor impairments when designing technology and training protocols.

Potential of social engagement for overcoming barriers to physical activity in individuals with spinal cord injury.

Introduction: Many barriers to physical activity (PA) exist for individuals with spinal cord injury (SCI). Social engagement may improve motivation to perform PA, which in turn may increase PA levels. This pilot study investigates how social engagement facilitated by mobile technology may reduce lack of motivation as a barrier to PA in individuals with SCI and demonstrates design implications for future technologies. Methods: A user-needs survey was conducted with participants in the community. We recruited 26 participants (16 individuals with SCI and 10 family members or peers). A participatory design process using semi-structured interviews was used to identify themes relating to PA barriers. Results: One theme related to PA barriers was lack of PA-focused forums to connect with peers. Participants with SCI considered connecting with other individuals with SCI more motivating than connecting with their family members. Another key finding was that participants with SCI did not perceive that personal fitness trackers were targeted towards wheelchair-based activities. Conclusions: Engagement and communication with peers who have similar functional mobility levels and life experiences can potentially improve motivation for PA; however, PA-motivational platforms are not tailored towards wheelchair-users. Our preliminary findings show that some individuals with SCI are not satisfied with current mobile-technologies for wheelchair-based PA.

The ILHBN: challenges, opportunities, and solutions from harmonizing data under heterogeneous study designs, target populations, and measurement protocols.

The ILHBN is funded by the National Institutes of Health to collaboratively study the interactive dynamics of behavior, health, and the environment using Intensive Longitudinal Data (ILD) to (a) understand and intervene on behavior and health and (b) develop new analytic methods to innovate behavioral theories and interventions. The heterogenous study designs, populations, and measurement protocols adopted by the seven studies within the ILHBN created practical challenges, but also unprecedented opportunities to capitalize on data harmonization to provide comparable views of data from different studies, enhance the quality and utility of expensive and hard-won ILD, and amplify scientific yield. The purpose of this article is to provide a brief report of the challenges, opportunities, and solutions from some of the ILHBN's cross-study data harmonization efforts. We review the process through which harmonization challenges and opportunities motivated the development of tools and collection of metadata within the ILHBN. A variety of strategies have been adopted within the ILHBN to facilitate harmonization of ecological momentary assessment, location, accelerometer, and participant engagement data while preserving theory-driven heterogeneity and data privacy considerations. Several tools have been developed by the ILHBN to resolve challenges in integrating ILD across multiple data streams and time scales both within and across studies. Harmonization of distinct longitudinal measures, measurement tools, and sampling rates across studies is challenging, but also opens up new opportunities to address cross-cutting scientific themes of interest.

Health behavior changes, such as prevention of suicidal thoughts and behaviors, smoking, drug use, and alcohol use; and the promotion of mental health, sleep, and physical activities, and decreases in sedentary behavior, are difficult to sustain. The ILHBN is a cooperative agreement network funded jointly by seven participating units within the National Institutes of Health to collaboratively study how factors that occur in individuals' everyday life and in their natural environment influence the success of positive health behavior changes. This article discusses how information collected using smartphones, wearables, and other devices can provide helpful active and passive reflections of the participants' extent of risk and resources at the moment for an extended period of time. However, successful engagement and retention of participants also require tailored adaptations of study designs, measurement tools, measurement intervals, study span, and device choices that create hurdles in integrating (harmonizing) data from multiple studies. We describe some of the challenges, opportunities, and solutions that emerged from harmonizing intensive longitudinal data under heterogeneous study and participant characteristics within the ILHBN, and share some tools and recommendations to facilitate future data harmonization efforts.

Children's perceptions of physical activity environments captured through ecological momentary assessment: a validation study.

OBJECTIVE: This study used ecological momentary assessment (EMA) to investigate whether children's perceptions of physical activity (PA) settings correspond with (1) parents' perceptions of neighborhood characteristics (convergent construct validity) and (2) children's level of PA in those settings (concurrent criterion validity). METHODS: Low-to-middle income, ethnically-diverse children (N=108) (ages 9-13) living in Southern California participated in 8 days of EMA during non-school time. EMA measured current activity type (e.g., sports/exercise, TV watching) and perceptions of the current setting (i.e., vegetation, traffic, safety). The Neighborhood Environment Walkability Survey (NEWS) assessed parents' perceptions of neighborhood characteristics. EMA responses were time-matched to moderate-to-vigorous physical activity (MVPA) (measured by accelerometer) in the 30 min before and after each EMA survey. Data were collected in 2009-2010. RESULTS: Children's perceptions of vegetation and traffic in PA settings corresponded with parents' perceptions of the aesthetics (OR=2.21, 95% CI=1.04-4.73) and traffic (OR=2.64, 95% CI=1.31-5.30) in neighborhood environment, respectively. MVPA minutes were higher in settings perceived by children to have less traffic (ß=3.47, p<.05). CONCLUSIONS: This work provides initial support for the construct and criterion validity of EMA-based measures of children's perceptions of their PA environments.

Detecting Sleep and Nonwear in 24-h Wrist Accelerometer Data from the National Health and Nutrition Examination Survey.

INTRODUCTION: Estimating physical activity, sedentary behavior, and sleep from wrist-worn accelerometer data requires reliable detection of sensor nonwear and sensor wear during both sleep and wake. PURPOSE: This study aimed to develop an algorithm that simultaneously identifies sensor wake-wear, sleep-wear, and nonwear in 24-h wrist accelerometer data collected with or without filtering. METHODS: Using sensor data labeled with polysomnography ( n = 21) and directly observed wake-wear data ( n = 31) from healthy adults, and nonwear data from sensors left at various locations in a home ( n = 20), we developed an algorithm to detect nonwear, sleep-wear, and wake-wear for "idle sleep mode" (ISM) filtered data collected in the 2011-2014 National Health and Nutrition Examination Survey. The algorithm was then extended to process original raw data collected from devices without ISM filtering. Both algorithms were further validated using a polysomnography-based sleep and wake-wear data set ( n = 22) and diary-based wake-wear and nonwear labels from healthy adults ( n = 23). Classification performance (F1 scores) was compared with four alternative approaches. RESULTS: The F1 score of the ISM-based algorithm on the training data set using leave-one-subject-out cross-validation was 0.95 ± 0.13. Validation on the two independent data sets yielded F1 scores of 0.84 ± 0.60 for the data set with sleep-wear and wake-wear and 0.94 ± 0.04 for the data set with wake-wear and nonwear. The F1 score when using original, raw data was 0.96 ± 0.08 for the training data sets and 0.86 ± 0.18 and 0.97 ± 0.04 for the two independent validation data sets. The algorithm performed comparably or better than the alternative approaches on the data sets. CONCLUSIONS: A novel machine-learning algorithm was designed to recognize wake-wear, sleep-wear, and nonwear in 24-h wrist-worn accelerometer data that are applicable for ISM-filtered data or original raw data.

Examining Whether Physical Activity Location Choices Were Associated With Weekly Physical Activity Maintenance Across 13 Months of the COVID-19 Pandemic in Emerging Adults.

BACKGROUND: Recent studies have shown potentially detrimental effects of the COVID-19 pandemic on physical activity (PA) in emerging adults (ages 18-29 y). However, studies that examined the effects of COVID-19 on PA location choices and maintenance for this age group remain limited. The current study investigated changes in PA location choices across 13 months during the pandemic and their associations with PA maintenance in this population. METHODS: Emerging adults (N = 197) living in the United States completed weekly survey on personal smartphones (May 2020-June 2021) regarding PA location choices and maintenance. Mixed-effects models examined the main effects of PA location choice and its interaction with weeks into the pandemic on participants' PA maintenance. RESULTS: On a given week, participants performing PA on roads/sidewalks or at parks/open spaces were 1½ and 2 times as likely to maintain PA levels, respectively. Moreover, after September 2021, weeks when individuals performed PA on roads/sidewalks had a protective effect on PA maintenance. CONCLUSIONS: Performing PA on roads/sidewalks and at parks/open spaces was associated with PA maintenance during the COVID-19 pandemic. PA promotion and intervention efforts for emerging adults during large-scale disruptions to daily life should focus on providing programmed activities in open spaces to maintain their PA levels.