• U.S. adults reduced physical activity during the early pandemic period. • Reductions in walking and steps were larger for low-income and Hispanic adults. • More vigorous physical activity was reported by those who were active at home. • More steps were recorded by those who were active in their neighborhoods.

Background: Ecological momentary assessment (EMA) uses mobile technology to enable in situ self-report data collection on behaviors and states. In a typical EMA study, participants are prompted several times a day to answer sets of multiple-choice questions. Although the repeated nature of EMA reduces recall bias, it may induce participation burden. There is a need to explore complementary approaches to collecting in situ self-report data that are less burdensome yet provide comprehensive information on an individual’s behaviors and states. A new approach, microinteraction EMA (μEMA), restricts EMA items to single, cognitively simple questions answered on a smartwatch with single-tap assessments using a quick, glanceable microinteraction. However, the viability of using μEMA to capture behaviors and states in a large-scale longitudinal study has not yet been demonstrated. Objective: This paper describes the μEMA protocol currently used in the Temporal Influences on Movement & Exercise (TIME) Study conducted with young adults, the interface of the μEMA app used to gather self-report responses on a smartwatch, qualitative feedback from participants after a pilot study of the μEMA app, changes made to the main TIME Study μEMA protocol and app based on the pilot feedback, and preliminary μEMA results from a subset of active participants in the TIME Study. Methods: The TIME Study involves data collection on behaviors and states from 246 individuals; measurements include passive sensing from a smartwatch and smartphone and intensive smartphone-based hourly EMA, with 4-day EMA bursts every 2 weeks. Every day, participants also answer a nightly EMA survey. On non–EMA burst days, participants answer μEMA questions on the smartwatch, assessing momentary states such as physical activity, sedentary behavior, and affect. At the end of the study, participants describe their experience with EMA and μEMA in a semistructured interview. A pilot study was used to test and refine the μEMA protocol before the main study. Results: Changes made to the μEMA study protocol based on pilot feedback included adjusting the single-question selection method and smartwatch vibrotactile prompting. We also added sensor-triggered questions for physical activity and sedentary behavior. As of June 2021, a total of 81 participants had completed at least 6 months of data collection in the main study. For 662,397 μEMA questions delivered, the compliance rate was 67.6% (SD 24.4%) and the completion rate was 79% (SD 22.2%). Conclusions: The TIME Study provides opportunities to explore a novel approach for collecting temporally dense intensive longitudinal self-report data in a sustainable manner. Data suggest that μEMA may be valuable for understanding behaviors and states at the individual level, thus possibly supporting future longitudinal interventions that require within-day, temporally dense self-report data as people go about their lives.

Background: Young adulthood (ages 18-29 years) is marked by substantial weight gain, leading to increased lifetime risks of chronic diseases. Engaging in sufficient levels of physical activity and sleep, and limiting sedentary time are important contributors to the prevention of weight gain. Dual-process models of decision-making and behavior that delineate reflective (ie, deliberative, slow) and reactive (ie, automatic, fast) processes shed light on different mechanisms underlying the adoption versus maintenance of these energy-balance behaviors. However, reflective and reactive processes may unfold at different time scales and vary across people. Objective: This paper describes the study design, recruitment, and data collection procedures for the Temporal Influences on Movement and Exercise (TIME) study, a 12-month intensive longitudinal data collection study to examine real-time microtemporal influences underlying the adoption and maintenance of physical activity, sedentary behavior, and sleep. Methods: Intermittent ecological momentary assessment (eg, intentions, self-control) and continuous, sensor-based passive monitoring (eg, location, phone/app use, activity levels) occur using smartwatches and smartphones. Data analyses will combine idiographic (person-specific, data-driven) and nomothetic (generalizable, theory-driven) approaches to build models that may predict within-subject variation in the likelihood of behavior “episodes” (eg, ≥10 minutes of physical activity, ≥120 minutes of sedentary time, ≥7 hours sleep) and “lapses” (ie, not attaining recommended levels for ≥7 days) as a function of reflective and reactive factors. Results: The study recruited young adults across the United States (N=246). Rolling recruitment began in March 2020 and ended August 2021. Data collection will continue until August 2022. Conclusions: Results from the TIME study will be used to build more predictive health behavior theories, and inform personalized behavior interventions to reduce obesity and improve public health. International Registered Report Identifier (IRRID): DERR1-10.2196/36666

Background: Adolescence through emerging adulthood represents a critical period associated with changes in lifestyle behaviors. Understanding the dynamic relationships between cognitive, social, and environmental contexts is informative for the development of interventions aiming to help youth sustain physical activity and limit sedentary time during this life stage. Ecological momentary assessment (EMA) is an innovative method involving real-time assessment of individuals’ experiences and behaviors in their naturalistic or everyday environments; however, EMA compliance can be problematic due to high participant burdens. Objective: This systematic review synthesized existing evidence pertaining to compliance in EMA studies that investigated wake-time movement behaviors among adolescent and emerging adult populations. Differences in EMA delivery scheme or protocol, EMA platforms, prompting schedules, and compensation methods—all of which can affect participant compliance and overall study quality—were examined. Methods: An electronic literature search was conducted in PubMed, PsycINFO, and Web of Science databases to select relevant papers that assessed movement behaviors among the population using EMA and reported compliance information for inclusion (n=52) in October 2022. Study quality was assessed using a modified version of the Checklist for Reporting of EMA Studies (CREMAS). Results: Synthesizing the existing evidence revealed several factors that influence compliance. The platform used for EMA studies could affect compliance and data quality in that studies using smartphones or apps might lessen additional burdens associated with delivering EMAs, yet most studies used web-based formats (n=18, 35%). Study length was not found to affect EMA compliance rates, but the timing and frequency of prompts may be critical factors associated with missingness. For example, studies that only prompted participants once per day had higher compliance (91% vs 77%), but more frequent prompts provided more comprehensive data for researchers at the expense of increased participant burden. Similarly, studies with frequent prompting within the day may provide more representative data but may also be perceived as more burdensome and result in lower compliance. Compensation type did not significantly affect compliance, but additional motivational strategies could be applied to encourage participant response. Conclusions: Ultimately, researchers should consider the best strategies to limit burdens, balanced against requirements to answer the research question or phenomena being studied. Findings also highlight the need for greater consistency in reporting and more specificity when explaining procedures to understand how EMA compliance could be optimized in studies examining physical activity and sedentary time among youth. Trial Registration: PROSPERO CRD42021282093; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=282093