Background: Tai Chi Chuan (TCC) is considered a mind and body practice of Chinese origin, considered as an intangible cultural heritage of humanity by UNESCO, and recommended by the World Health Organization as a therapeutic approach to prevent falls. Objective: To assess the effects of TCC on older adult’s balance. Methods: A systematic review of randomized clinical trials was conducted by two independent reviewers using the ROB2 tool to assess the risk of bias under the following databases: PubMed, SCOPUS, Web of Science, PEDro, Embase, Cochrane, CINAHL, and LILACS. A meta-analysis of the selected articles for the dynamic and static balance criteria was conducted in a population of older adults (over 65 years) with publications from 2010 to 2024. Results: Eighteen randomized clinical trials fulfilled the criteria. TCC improves dynamic balance in the timed up and go and gait speeds tests, and static balance in the single-leg test and functional reach test when compared with the control group in the meta-analysis. Adverse events were found in only one study, and the training parameters were heterogeneous. Conclusion: TCC improves older adults with both dynamic and static balance. The results of the parameters indicate a direction in which TCC is prescribed for clinical practice with minimal or no risk of adverse effects.
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Effects of Tai Chi Chuan on Older Adults’ Balance: A Systematic Review With Meta-Analysis
Rafael Bertolini, Rafael Vercelino, Luis Fernando Ferreira, and Luis Henrique Telles da Rosa
Gaze Behaviors, Estimated Quiet Eye Characteristics, and Decision Making of Nonexpert Assistant Referees Judging Offside Events in Soccer
Carlos Albaladejo-García, Vicente Luis-del Campo, Jesús Morenas, and Francisco J. Moreno
The study analyzed the gaze behavior and decision-making performance of 20 soccer assistant referees while judging offside events. Specifically, gaze behaviors, gaze entropy, and estimated quiet eye (eQE; defined as the last fixation prior to the attacker’s ball pass) characteristics (i.e., location, onset, offset, and duration) were analyzed in relation to decision-making accuracy. Although a significant number of fixations were observed on the offside line, the highest viewing time corresponded to the ball carrier. The gaze behavior indicated a high distribution of fixations, as evidenced by high stationary gaze entropy (>90%). The assistant referees also distinguished offside from onside positions above chance. However, they displayed nonprolonged eQE on the offside line. As a result, no significant relationships were found between the eQE characteristics and decision-making accuracy. The study concludes that the absence of more functional gaze behaviors, specifically with longer eQE focused on the offside line, impaired the decision-making accuracy of nonexpert assistant referees in soccer.
Predicting Basketball Shot Outcome From Visuomotor Control Data Using Explainable Machine Learning
Nikki Aitcheson-Huehn, Ryan MacPherson, Derek Panchuk, and Adam W. Kiefer
Quiet eye (QE), the visual fixation on a target before initiation of a critical action, is associated with improved performance. While QE is trainable, it is unclear whether QE can directly predict performance, which has implications for training interventions. This study predicted basketball shot outcome (make or miss) from visuomotor control variables using a decision tree classification approach. Twelve basketball athletes completed 200 shots from six on-court locations while wearing mobile eye-tracking glasses. Training and testing data sets were used for modeling eight predictors (shot location, arm extension time, and absolute and relative QE onset, offset, and duration) via standard and conditional inference decision trees and random forests. On average, the trees predicted over 66% of makes and over 50% of misses. The main predictor, relative QE duration, indicated success for durations over 18.4% (range: 14.5%–22.0%). Training to prolong QE duration beyond 18% may enhance shot success.
Device-Based Measurement of Office-Based Physical Activity and Sedentary Time: A Systematic Review
Noah Bongers, Genevieve N. Healy, George Thomas, and Bronwyn K. Clark
Background: The aim of this study was to systematically review the findings for validity, reliability, and acceptability of device-based measures of office-based physical activity and/or sedentary time in an office context to evaluate workplace interventions. Methods: The review was conducted according to the Preferred Reporting Items for Systematic Reviews and Analysis guidelines. Five electronic databases (PubMed, EMBASE, CINAHL, Cochrane, and Web of Science) were searched (inception to December 2023). Keywords included population (e.g., workers), type of measure (e.g., device-based), measurement constructs (e.g., validity), context (e.g., office), and behavior (e.g., sitting). Two authors screened titles, abstracts, and full texts independently with disagreements resolved by a third author. Findings were reported using narrative synthesis, and COnsensus-based standards for the Selection of health status Measurement INstruments was used for quality assessment. Results: In total, 2,299 articles were identified, with 16 articles retained. These reported 21 measurement protocols (nine in free-living settings) assessing eight worn, four remote, and one combined method. Sixteen protocols assessed office sitting, with standing (n = 8), moving (n = 11), postural transitions (n = 7), and location (n = 2) also assessed. Participant sample sizes ranged from one to 42 (median = 13). Criterion validity was assessed in all 21 protocols, with lower limb–worn measures of sitting, and worn and remote measures of location reporting the highest validity/accuracy compared with the ground truth (good to excellent). Only two articles reported acceptability (good acceptability), with none reporting reliability. Conclusions: There is evidence of valid device-based measures of office behavior (particularly sitting and location of workers), but this has largely been obtained in laboratory settings and/or with small samples. Larger studies in more varied free-living settings, potentially using multiples sources of data and assessing acceptability, are required.
Effect of Accelerometer Cut-Points on Preschoolers’ Physical Activity and Sedentary Time: A Systematic Review and Meta-Analysis
Sophie M. Phillips, Kimberly A. Clevenger, Brianne A. Bruijns, Patricia Tucker, Leigh M. Vanderloo, Aidan Loh, Manahil Naveed, and Matthew Bourke
This systematic review and meta-analysis aimed to compare estimated levels of physical activity (PA) and sedentary time (ST) of preschool-aged children (3–5 years old) based on different published accelerometer cut-points used in this age group. Four electronic databases were searched to identify studies estimating levels of PA or ST (ST, light PA [LPA], and moderate to vigorous PA [MVPA]) using multiple accelerometer cut-points, in a sample of preschool-aged children. Data were extracted and risk of bias assessed for all included studies. Random-effects meta-analysis was used to estimate pooled effects for unique combinations of accelerometer cut-points for each outcome. Twenty-four studies, reporting on 18 unique samples, were included. Results demonstrated substantial variability in estimates of PA and ST across different cut-points, with significant differences in estimates of the behaviors between most cut-points. Few cut-points showed similarity; Evenson and Pate were some of the most similar for the assessment of PA and ST of young children. However, when calculating the differences in ST, LPA, and MVPA between the cut-points, the Evenson cut-point estimates approximately 60 min more LPA per day and the Pate 148CPM cut-points estimates 23 and 37 min more ST and MVPA each day, respectively. Given that these were the most similar estimates, this highlights the magnitude of differences between the accelerometer cut-points when estimating preschool-aged children’s movement behavior. This review provides an illustration on the limitations of accelerometer cut-points used to determine PA and ST of preschool-aged children; in that they often produce substantially different estimates. This review provides a compelling rationale as to why further research moving toward alternative data processing methodologies is required, including to identify an optimal approach to estimating movement behavior outcomes in young children that considers congruence with past and future research.
Methodology for Assessing Infant (0–2 Years) Movement Using Accelerometers: A Scoping Review
Danae Dinkel, John P. Rech, Priyanka Chaudhary, Rama Krishna Thelagothoti, Jon Youn, Hesham Ali, Michaela Schenkelberg, and Brian Knarr
Measuring infants’ (0–2 years) physical activity is a growing area of research globally. Accelerometers have been widely used to measure older children’s and adults’ physical activity. An increasing number of studies have used accelerometers as a way to measure infant physical activity, which has resulted in the application of a variety of methods. The purpose of this scoping review is to synthesize the published literature on accelerometer methodology to measure daytime physical activity among infants (0–2 years). A systematic search of five online databases using carefully selected key terms was conducted to compile relevant literature. The results of the online database searches were screened for inclusion in the scoping review. In total, 105 articles met the inclusion criteria of using accelerometers to measure infants’ physical activity. The methodologies used in the included studies were categorized by age groups: <1 month, 1–6 months, >6–12 months, >12–18 months, >18–24 months, and longitudinal (i.e., multiple measurements taken across the previously mentioned age groups). Accelerometry methodologies (e.g., wear location, number of devices, device initialization) and study design qualities (e.g., outcome of interest and location of data collection) varied widely between and within the various age groups. Accelerometer brand or type of device demonstrated greatest variation across included studies. However, ActiGraph devices to measure physical activity within free-living environments were the most common. This review provides evidence of the need for researchers to ensure the methodology used is reported in detail in order to help develop methodology that can accurately assess infant daytime movement.
Shaking Up Activity Counts: Assessing the Comparability of Accelerometers and Activity Count Computation
Hannah J. Coyle-Asbil, Bernadette Murphy, and Lori Ann Vallis
Accelerometers have been at the forefront of free-living activity capture for decades, and accordingly ActiGraph the largest distributor. Historically, limitations in data storage and battery power led to the use of summary metrics, which have been termed activity counts. Recently, ActiGraph publicly released their count-based algorithm, marking a notable development in the field. This study aimed to assess and compare activity counts generated through different processing techniques (ActiLife and open-source), filters that are available through ActiGraph count generation (normal- and low-frequency extension), and data from various ActiGraph models and GENEActiv devices. We evaluated ActiGraph GT3X+ (n = 8), ActiGraph wGT3X-BT (n = 10), ActiGraph GT9X (n = 8; primary and secondary sensors), OPAL (n = 6), and GENEActiv (n = 5), subjected to oscillations across their full dynamic range (0.005–8 G) using a multiaxis shaker table. Results indicated that the low-frequency extension produced significantly higher counts compared to the normal frequency across the devices and processing techniques. Notably, open-source counts (R and Python) were statistically equivalent to ActiLife-generated counts (p < .05) for the GT9X, wGT3X-BT, and the GT3X+. Overall, many of the counts generated by different ActiGraph models were statistically equivalent or had mean differences <5.03 counts. Conversely, the GENEActiv, OPAL, and GT9X secondary monitor exhibited significantly higher responses than the other ActiGraph models at higher frequencies with mean differences ranging from 55.50 to 104.91 counts. This study provides insights into accelerometer data processing methods and highlights the comparability of counts across different devices and techniques.
A Walkthrough of ActiGraph Counts
Ali Neishabouri, Joe Nguyen, Matthew R. Patterson, Rakesh Pilkar, and Christine C. Guo
Activity counts have been used for over two decades with over 22,000 published scientific papers in public health and clinical research. ActiGraph recently released the algorithm for computing counts from raw accelerometer data as an open-source Python library, which is now ported by researchers to other languages, notably R. The current commentary presents historical overview of ActiGraph counts, and its development and evolution as a measure of physical activity. Further, we provide general recommendations on extracting counts from raw accelerometer data and discuss specific considerations with respect to device types, resampling, nonwear, axes orientations, and epoch length that may influence counts. Last, we provide a tutorial on how to use ActiGraph’s open-source Python library, agcounts, for consistent, accurate, and reproducible count. We expect this commentary will provide familiarity and transparency needed to adopt and produce activity counts in a consistent manner, allowing researchers to conduct statistical comparisons across multiple data sets and studies.
Achieving Advocacy Success—The International Society for Physical Activity and Health’s Long-Term Strategy to Advance Physical Activity as a Priority in Global Health Policy
Trevor Shilton and Karen Milton
Background: In 2011, physical inactivity was described as the Cinderella risk factor for noncommunicable diseases. This metaphor was used to highlight the disjunct between the advancing evidence on physical inactivity as a risk factor for ill health, its high prevalence, and the paucity of global policy response or priority afforded to physical activity. This paper describes the strategic actions of the International Society for Physical Activity and Health (ISPAH) to raise the profile of physical activity as a global public health priority. Methods: From 2008, ISPAH coordinated a long-term advocacy strategy to advance the status of physical activity and promote its presence as a priority within global health policy. The society employed an advocacy mix that reflected contemporary advocacy theory and models. Results: Through 6 advocacy deliverables, aligned to the global calendar of United Nations and World Health Organization policy developments, ISPAH seized the opportunity to advance physical activity policy and strategies to inform global noncommunicable disease action planning and align with the Sustainable Development Goals. ISPAH’s successful execution of global advocacy for physical activity highlights the importance of leadership, clear objectives, progressive action, timeliness, partnerships, and persistence. Conclusion: As a result of strategic global advocacy since 2008, the field in 2024 is better positioned in relation to global professional mobilization, policy, and technical support for physical activity. However, despite impressive progress across more than 12 years, and the innovation of the Global Action Plan on Physical Activity, the work of global advocacy for physical activity is far from complete.
The Current Status of Leisure Constraints, Leisure Sports Behaviors, and Active Aging Among Chinese Older Adults
Yajun Qiu, Yi Shang, Haibo Tian, and Dongjun Yang
Background: Against the backdrop of China’s active response to population aging, an increasing number of older adults are participating in leisure sports activities to enrich later life and experience active aging. However, when participating in these activities, older adults encounter constraints that affect their leisure sports behaviors. Methods: To understand the current state of leisure constraints, leisure sports behaviors, and active aging among Chinese seniors, we collected 1,581 surveys from older adults in Zhejiang Province, China. A stepwise regression model was used to explore the relationships between leisure constraints and leisure sports behavior as well as between leisure sports behavior and active aging. Results: The respondents’ leisure sports were characterized by light-intensity, moderate duration, high-frequency, and long-term participation with various leisure constraints, such as a lack of organized leisure sports activities. However, the respondents reported that their aging status was positive. Leisure constraints were negatively associated with leisure sports behavior, and self-constraint had a significant impact on leisure sports behavior. Leisure sports behavior positively affected the active aging of older participants and was positively associated with the four subdimensions of active aging: health, participation, security, and lifelong learning. Conclusion: High-frequency and long-term participation in leisure sports is an effective strategy for Chinese seniors to promote active aging. However, there are still many constraints that limit the leisure sports behaviors of older adults. Implications: The findings may inspire Chinese older adults to achieve active aging through leisure sports and provide support for the literature.