Screen-based and non-screen-based sedentary behaviors are differentially associated with affective states in older adults.

Excessive sedentary behavior (SB) contributes to poor affective and physical feeling states, which is particularly concerning for older adults who are the most sedentary sector of the population. Specific types of SB have been shown to differentially impact health in cross-sectional and longitudinal studies, with screen-based SB more negatively impacting aspects of mental health. This study used Ecological Momentary Assessment (EMA), a real-time, intensive longitudinal data capture methodology, to examine the differential impact of screen-based behaviors on momentary affective responses during SB in naturalistic settings. A diverse sample of older adults (pooled across 2 studies) completed an EMA protocol for 8-10 days with six randomly delivered, smartphone assessments per day. At each EMA prompt, participants reported their current activity, whether they were sitting while doing that activity, and affective states. Multilevel models assessed whether screen-based (vs. non-screen-based) behavior moderated affective response during SB. At the within-person level, older adults experienced less positive affect during SB when engaged in a screen-based behavior compared to a non-screen-based SB (B = -0.10, p < 0.01). At the between-person level, positive associations between SB and negative affect (B = 0.79, p = 0.03) were stronger if participants reported engaging in screen-based behaviors for a greater proportion of prompts. Among older adults, screen-based SB may lead to poorer affective states compared to non-screen-based SB. Interventions aiming to reduce SB in this population should consider targeting reductions in screen-based SB as means to improve affective states.

Studying Movement-Related Behavioral Maintenance and Adoption in Real Time: Protocol for an Intensive Ecological Momentary Assessment Study Among Older Adults.

BACKGROUND: Older adults struggle to maintain newly initiated levels of physical activity (PA) or sedentary behavior (SB) and often regress to baseline levels over time. This is partly because health behavior theories that inform interventions rarely address how the changing contexts of daily life influence the processes regulating PA and SB or how those processes differ across the behavior change continuum. Few studies have focused on motivational processes that regulate the dynamic nature of PA and SB adoption and maintenance on microtimescales (ie, across minutes, hours, or days). OBJECTIVE: The overarching goal of Project Studying Maintenance and Adoption in Real Time (SMART) is to determine the motivational processes that regulate behavioral adoption versus maintenance over microtimescales, using a dual process framework combined with ecological momentary assessment and sensor-based monitoring of behavior. This paper describes the recruitment, enrollment, data collection, and analytics protocols for Project SMART. METHODS: In Project SMART, older adults engaging in at least 30 minutes of moderate-to-vigorous intensity PA per week complete 3 data collection periods over 1 year, with each data collection period lasting 14 days. Across each data collection period, participants wear an ActiGraph GT3X accelerometer (ActiGraph, LLC) on their nondominant waist and an ActivPAL micro4 accelerometer (PAL Technologies, Ltd) on their anterior thigh to measure PA and SB, respectively. Ecological momentary assessment questionnaires are randomly delivered via smartphone 10 times per day on 4 selected days in each data collection period and assess reflective processes (eg, evaluating one's efficacy and exerting self-control) and reactive processes (eg, contextual cues) within the dual process framework. At the beginning and end of each data collection period, participants complete a computer-based questionnaire to learn more about their typical motivation for PA and SB, physical and mental health, and life events over the course of the study. RESULTS: Recruitment and enrollment began in January 2021; enrollment in the first data collection period was completed by February 2022; and all participants completed their second and third data collection by July 2022 and December 2022, respectively. Data were collected from 202 older adults during the first data collection period, with approximate retention rates of 90.1% (n=182) during the second data collection period and 88.1% (n=178) during the third data collection period. Multilevel models and mixed-effects location scale modeling will be used to evaluate the study aims. CONCLUSIONS: Project SMART seeks to predict and model the adoption and maintenance of optimal levels of PA and SB among older adults. In turn, this will inform the future delivery of personalized intervention content under conditions where the content will be most effective to promote sustained behavior change among older adults. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/47320.

Associations Between Social Cognitive Determinants and Movement-Related Behaviors in Studies Using Ecological Momentary Assessment Methods: Systematic Review.

BACKGROUND: The social cognitive framework is a long-standing framework within physical activity promotion literature to explain and predict movement-related behaviors. However, applications of the social cognitive framework to explain and predict movement-related behaviors have typically examined the relationships between determinants and behavior across macrotimescales (eg, weeks and months). There is more recent evidence suggesting that movement-related behaviors and their social cognitive determinants (eg, self-efficacy and intentions) change across microtimescales (eg, hours and days). Therefore, efforts have been devoted to examining the relationship between social cognitive determinants and movement-related behaviors across microtimescales. Ecological momentary assessment (EMA) is a growing methodology that can capture movement-related behaviors and social cognitive determinants as they change across microtimescales. OBJECTIVE: The objective of this systematic review was to summarize evidence from EMA studies examining associations between social cognitive determinants and movement-related behaviors (ie, physical activity and sedentary behavior). METHODS: Studies were included if they quantitatively tested such an association at the momentary or day level and excluded if they were an active intervention. Using keyword searches, articles were identified across the PubMed, SPORTDiscus, and PsycINFO databases. Articles were first assessed through abstract and title screening followed by full-text review. Each article was screened independently by 2 reviewers. For eligible articles, data regarding study design, associations between social cognitive determinants and movement-related behaviors, and study quality (ie, Methodological Quality Questionnaire and Checklist for Reporting Ecological Momentary Assessment Studies) were extracted. At least 4 articles were required to draw a conclusion regarding the overall associations between a social cognitive determinant and movement-related behavior. For the social cognitive determinants in which a conclusion regarding an overall association could be drawn, 60% of the articles needed to document a similar association (ie, positive, negative, or null) to conclude that the association existed in a particular direction. RESULTS: A total of 24 articles including 1891 participants were eligible for the review. At the day level, intentions and self-efficacy were positively associated with physical activity. No other associations could be determined because of conflicting findings or the small number of studies investigating associations. CONCLUSIONS: Future research would benefit from validating EMA assessments of social cognitive determinants and systematically investigating associations across different operationalizations of key constructs. Despite the only recent emergence of EMA to understand social cognitive determinants of movement-related behaviors, the findings indicate that daily intentions and self-efficacy play an important role in regulating physical activity in everyday life. TRIAL REGISTRATION: PROSPERO CRD42022328500; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=328500.

The impact of the COVID-19 pandemic on physical activity habits at a residential university.

OBJECTIVE: To assess changes in physical activity (PA) after a COVID-19 shutdown on a primarily residential university campus. METHODS: Eighty students, faculty, and staff (FS) of a university (age: 32.2 ± 13.6 yr) who wore a consumer wearable technology (CWT) device completed an anonymous survey by inputting data for 30 days prior to- and 30 days following an academic break in 2020, in which the university transitioned to remote learning. RESULTS: Steps decreased after spring break in all subjects (p < .001), but steps were impacted to a greater extent in students. 30-day, weekday, and weekend step averages all decreased in students (p < .001). FS were able to maintain their weekend step averages. CONCLUSIONS: PA decreased in a university community after the COVID-19 shutdown. Students, no longer active transport for campus life, saw a greater impact on their PA. These changes could have an impact on health status.

Accuracy Assessment of a GPS Device for Maximum Sprint Speed.

Global positioning system (GPS) technology can capture maximum sprint speed (MSS) using fewer resources than electronic timing gates (ETG). Yet, errors with GPS technology are typically 1.01 km·hr-1 for instantaneous velocity, potentially limiting GPS accuracy. The purpose of this study was to compare MSS values obtained from GPS technology to those obtained from ETG. The MSS of 24 female athletes was determined using two tests that both began with a 20-m fly-in followed by: 1) 80-m maximal sprint with ETG placed at the start line, 30 m, 60 m, and 80 m, and 2) 30-m maximal sprint with ETG placed every 10 m. Sprint speed was calculated from each timing segment, and the fastest segment for each test was used for the calculated MSS. MSS was also obtained using a GPS unit measuring at 10 Hz. Mean bias and mean absolute percent error (MAPE) of the GPS was lower for the 80-m test (0.09 ± 1.24 km·hr-1, 3.5 ± 3.1%) than the 30-m test (1.58 ± 0.80 km·hr-1, 5.5 ± 2.6%). Lin's concordance agreement was found to be poor for both tests. The equivalence test indicated that the GPS was equivalent for both short and long distances, p < .05, meaning the two results were within a 5% equivalence interval. The GPS devices were within the acceptable range of accuracy at short (10-m) and long (30-m) distances. These results can guide coaching staff regarding how to test their athlete's metrics and the reliability of those results.