Background: Teacher-led strategies targeting verbal prompting and demonstrated modeling can increase preschoolers’ physical activity levels; however, it is unknown which strategy promotes higher levels. The purpose of this study was to explore whether teacher verbal prompting or demonstrated modeling elicits higher levels of physical activity among preschoolers. Methods: Participants included 117 (56 females and 61 males; mean = 3.77 y) preschoolers who were observed for 3 days during regular preschool instructions. The System for Observing Student Movement in Academic Routines and Transitions observation system assessed verbal prompting and demonstrated modeling of the teachers, and preschoolers wore an ActiGraph accelerometer to measure physical activity. Results: The multivariate analysis of variance results showed a significant difference for verbal prompting (P < .001), demonstrated modeling (P = .032), light physical activity (P < .001), and moderate to vigorous physical activity (MVPA; P < .001) between segments of the preschool day. A stepwise linear regression showed that preschooler’s MVPA (P = .005) and light physical activity and MVPA (P = .036) were significantly related to demonstrated modeling, but not verbal prompting. During indoor time, light physical activity and MVPA were highest during large group, work time, and morning group, where teacher demonstrated modeling occurred the most. Conclusions: Teacher demonstrated modeling had a significant relationship to preschoolers’ MVPA and light physical activity levels, while teacher verbal prompting did not.
Alexandra V. Carroll, Katherine E. Spring, Darby Winkler, Kameron Suire, and Danielle D. Wadsworth
Shamoon S. Shahzada, Toby C.T. Mak, and Thomson W.L. Wong
The theory of reinvestment in experimental psychology suggested that automated performance could be degraded if attention was internally diverted to the process of skill execution. This study examined the role of attentional focus instructions on real-time conscious motor processing (i.e., reinvestment) during tandem walking. Thirty-six young adults (mean age = 20.94, SD = 1.43 years) participated; their electroencephalography T3–Fz coherence (i.e., real-time reinvestment) was measured during three walking conditions with different attentional focus instructions: external focus, internal focus, and control conditions. The results suggested that attentional focus instructions did not significantly affect real-time conscious motor processing during tandem walking in young adults, possibly due to the low level of motor task complexity of walking by young adults. The Movement-Specific Reinvestment Scale appears to be not sensitive enough to reflect the real-time reinvestment during gait-related movements in young adults.
Wei Guo, Andrew Leroux, Haochang Shou, Lihong Cui, Sun Jung Kang, Marie-Pierre Françoise Strippoli, Martin Preisig, Vadim Zipunnikov, and Kathleen Ries Merikangas
The Mobile Motor Activity Research Consortium for Health (mMARCH) is a collaborative network of clinical and community studies that employ common digital mobile protocols and collect common clinical and biological measures across participating studies. At a high level, a key scientific goal which spans mMARCH studies is to develop a better understanding of the interrelationships between physical activity (PA), sleep (SL), and circadian rhythmicity (CR) and mental and physical health in children, adolescents, and adults. mMARCH studies employ wrist-worn accelerometry to obtain objective measures of PA/SL/CR. However, there is currently no consensus on a standard data processing pipeline for raw accelerometry data and few open-source tools which facilitate their development. The R package GGIR is the most prominent open-source software package for processing raw accelerometry data, offering great functionality and substantial user flexibility. However, even with GGIR, processing done in a harmonized and reproducible fashion across multiple analytical centers requires a nontrivial amount of expertise combined with a careful implementation. In addition, there are many statistical methods useful for analyzing PA/SL/CR patterns using accelerometry data which are implemented in non-GGIR R packages, including methods from multivariate statistics, functional data analysis, distributional data analysis, and time series analyses. To address the issues of multisite harmonization and additional feature creation, mMARCH developed a streamlined harmonized and reproducible pipeline for loading and cleaning raw accelerometry data via GGIR, merging GGIR, and non-GGIR features of PA/SL/CR together, implementing several additional data and feature quality checks, and performing multiple analyses including Joint and Individual Variation Explained, an unsupervised machine learning dimension reduction technique that identifies latent factors capturing joint across and individual to each of three domains of PA/SL/CR. The pipeline is easily modified to calculate additional features of interest, and allows for studies not affiliated with mMARCH to apply a pipeline which facilitates direct comparisons of scientific results in published work by mMARCH studies. This manuscript describes the pipeline and illustrates the use of combined GGIR and non-GGIR features by applying Joint and Individual Variation Explained to the accelerometry component of CoLaus|PsyCoLaus, one of mMARCH sites. The pipeline is publicly available via open-source R package mMARCH.AC.
Cindy Y. Lin, Trever J. Ball, Nicole L. Gentile, Valerie F. McDonald, and Andrew T. Humbert
Background: Physical inactivity is a risk factor for many chronic conditions. This retrospective cohort study examined associations between physical activity (PA) with health care utilization (HU). Methods: A PA vital sign was recorded in clinics from January 2018 to December 2020. Patients were categorized as inactive, insufficiently active, or sufficiently active by US PA aerobic guidelines. Associations between PA vital sign and visits (inpatient admissions, emergency department, urgent care, and primary care) were estimated using population average regression by visit type. Results: 23,721 patients had at least one PA vital sign recorded, with a mean age of 47.3 years and mean body mass index (BMI) of 28; 52% were female and 63% were White. Sufficiently active patients were younger, male, White, and had lower BMI than insufficiently active patients. Achieving 150 minutes per week of moderate to vigorous PA per 1000 patient years was associated with 34 fewer emergency department visits (P < .001), 19 fewer inpatient admissions (P < .001), and 38 fewer primary care visits (P < .001) compared with inactive patients. Stronger associations between lower PA and higher HU were present among those who were older or had a higher comorbidity. BMI, sex, ethnicity, and race did not modify the association between PA and HU. Conclusions: Meeting aerobic guidelines was associated with reduced HU for inpatient, primary care, and emergency department visits.
Fabián Arroyo-Rojas, A. Chloe Simpson, Paige Laxton, Marie Leake, Jamie Linker, and Justin A. Haegele
In this expository paper, we reflect upon our understanding of how disabled people are discussed and treated in kinesiology and adapted physical activity in higher education and explore potential areas of unintentional harm that may be present in our everyday practice. There are three particular aspects of kinesiology in higher education that we discuss: access, language, and assessment. We discuss the challenges of access of disabled people in positions in higher education, language in higher education which serves as centers for knowledge creation, and the problematic nature of assessments based on societal norms, and for us, it is important to shine a spotlight on the many systemic limitations and barriers that disabled persons experience, in hope to amplify the importance of these issues.
Joey Murphy, Karen Milton, Matthew Mclaughlin, Trevor Shilton, Gabriella M. McLoughlin, Lindsey J. Reece, Jacqueline L. Mair, Artur Direito, Katharina E. Kariippanon, Kelly J. Mackenzie, Myrto F. Mavilidi, Erin M. Shellington, Masamitsu Kamada, Leonie Heron, Edtna Jauregui, Chalchisa Abdeta, Ilaria Pina, Ryan Pinto, and Rachel Sutherland
Background: There is limited understanding of the challenges experienced and supports required to aid effective advocacy of the Global Action Plan on Physical Activity (GAPPA). The purpose of this study was to assess the challenges experienced and supports needed to advocate for the GAPPA across countries of different income levels. Methods: Stakeholders working in an area related to the promotion of physical activity were invited to complete an online survey. The survey assessed current awareness and engagement with the GAPPA, factors related to advocacy, and the perceived challenges and supports related to advocacy for implementation of the GAPPA. Closed questions were analyzed in SPSS, with a Pearson’s chi-square test used to assess differences between country income level. Open questions were analyzed using inductive thematic analysis. Results: Participants (n = 518) from 81 countries completed the survey. Significant differences were observed between country income level for awareness of the GAPPA and perceived country engagement with the GAPPA. Challenges related to advocacy included a lack of support and engagement, resources, priority, awareness, advocacy education and training, accessibility, and local application. Supports needed for future advocacy included guidance and support, cooperation and alliance, advocacy education and training, and advocacy resources. Conclusions: Although stakeholders from different country income levels experience similar advocacy challenges and required supports, how countries experience these can be distinct. This research has highlighted some specific ways in which those involved in the promotion of physical activity can be supported to scale up advocacy for the GAPPA. When implementing such supports, consideration of regional, geographic, and cultural barriers and opportunities is important to ensure they are effective and equitable.
Natália Mendes Guardieiro, Gabriel Barreto, Felipe Miguel Marticorena, Tamires Nunes Oliveira, Luana Farias de Oliveira, Ana Lucia de Sá Pinto, Danilo Marcelo Leite do Prado, Bryan Saunders, and Bruno Gualano
Purpose: Investigate whether a cloth facemask could affect physiological and perceptual responses to exercise at distinct exercise intensities in untrained individuals. Methods: Healthy participants (n = 35; 17 men, age 30  y, and 18 women, age 28  y) underwent a progressive square wave test at 4 intensities: (1) 80% of ventilatory anaerobic threshold; (2) ventilatory anaerobic threshold; (3) respiratory compensation point; and (4) exercise peak (Peak) to exhaustion, 5-minute stages, with or without a triple-layered cloth facemask (Mask or No-Mask). Several physiological and perceptual measures were analyzed. Results: Mask reduced inspiratory capacity at all exercise intensities (P < .0001). Mask reduced respiratory frequency (P = .001) at Peak (−8.3 breaths·min−1; 95% confidence interval [CI], −5.8 to −10.8), respiratory compensation point (−6.9 breaths·min−1; 95% CI, −4.6 to −9.2), and ventilatory anaerobic threshold (−6.5 breaths·min−1; 95% CI, −4.1 to −8.8), but not at Baseline or 80% of ventilatory anaerobic threshold. Mask reduced tidal volume (P < .0001) only at respiratory compensation point (−0.5 L; 95% CI, −0.3 to −0.6) and Peak (−0.8 L; 95% CI, −0.6 to −0.9). Shallow breathing index was increased with Mask only at Peak (11.3; 95% CI, 7.5 to 15.1). Mask did not change HR, lactate, ratings of perceived exertion, blood pressure, or oxygen saturation. Conclusions: A cloth facemask reduced time to exhaustion but had no major impact on cardiorespiratory parameters and had a slight but clinically meaningless impact on respiratory variables at higher intensities. Moderate to heavy activity is safe and tolerable for healthy individuals while wearing a cloth facemask. ClinicalTrials.gov: NCT04887714.
Eivind Aadland, Einar Ylvisåker, Kjersti Johannessen, and Ada Kristine Ofrim Nilsen
Background: Limited evidence exists regarding prospective associations for physical activity (PA) and sedentary time (SED) with body mass index (BMI) and muscle strength in young children. We aimed to determine prospective associations for PA and SED with change in BMI and standing long jump over 2 and 4 years in children aged 3–5 years at baseline. Methods: A sample of 262 Norwegian children (50% girls) was followed from 2015 to 2017 and/or 2019. PA and SED (hip-worn ActiGraph GT3X+) were measured at baseline and BMI and standing long jump at baseline and at follow-ups. Multivariate pattern analysis was used to determine prospective associations between the triaxial PA intensity spectrum (0–99 to ≥15,000 counts per minute) and the change in outcomes. Results: We found significant prospective associations between the PA intensity spectrum and standing long jump at 2- (explained variance = 5.8%–7.7%) and 4-year (explained variance = 4.8%–5.6%) follow-ups. Associations were negative for SED and positive for all PA intensities. We found no associations between PA/SED and BMI. Conclusions: Our findings suggest that PA and SED can predict future lower body muscle strength but not BMI in early childhood.
John J. Davis IV, Blaise E. Oeding, and Allison H. Gruber
Background: Running is a popular form of exercise, and its physiological effects are strongly modulated by speed. Accelerometry-based activity monitors are commonly used to measure physical activity in research, but no method exists to estimate running speed from only accelerometer data. Methods: Using three cohorts totaling 72 subjects performing treadmill and outdoor running, we developed linear, ridge, and gradient-boosted tree regression models to estimate running speed from raw accelerometer data from waist- or wrist-worn devices. To assess model performance in a real-world scenario, we deployed the best-performing model to data from 16 additional runners completing a 13-week training program while equipped with waist-worn accelerometers and commercially available foot pods. Results: Linear, ridge, and boosted tree models estimated speed with 12.0%, 11.6%, and 11.2% mean absolute percentage error, respectively, using waist-worn accelerometer data. Errors were greater using wrist-worn data, with linear, ridge, and boosted tree models achieving 13.8%, 14.0%, and 12.8% error. Across 663 free-living runs, speed was significantly associated with run duration (p = .009) and perceived run intensity (p = .008). Speed was nonsignificantly associated with fatigue (p = .07). Estimated speeds differed from foot pod measurements by 7.25%; associations and statistical significance were similar when speed was assessed via accelerometry versus via foot pod. Conclusion: Raw accelerometry data can be used to estimate running speed in free-living data with sufficient accuracy to detect associations with important measures of health and performance. Our approach is most useful in studies where research grade accelerometry is preferable to traditional global positioning system or foot pod-based measurements, such as in large-scale observational studies on physical activity.
Bruno Rodrigues, Jorge Encantado, Eliana Carraça, João Martins, Adilson Marques, Luís Lopes, Eduarda Sousa-Sá, Dylan Cliff, Romeu Mendes, and Rute Santos
Background: We aim to systematically review the literature on measurement properties of self- and proxy-reported questionnaires measuring 24-hour movement behaviors in children and adolescents. Methods: PubMed, PsycINFO, SPORTDiscus, and EMBASE were searched until June 2021. Studies were included if the sample size for validity studies had 50 participants (minimum) and included, at least, both validity and test–retest reliability results of questionnaires. The review followed an adaptation of the Consensus-based Standards for the selection of health Measurement INstruments guidelines, to evaluate the quality of measurements properties of the questionnaires (content, convergent and criterion validity, reliability, measurement error, and responsiveness), as well as the risk of bias of each measurement property. Results: This review included 29 studies, describing 37 questionnaires. Sixty-eight percent showed “adequate” content validity. None of the questionnaires showed overall “adequate” criterion validity, and the risk of bias was “very low” for 92%. One questionnaire showed “adequate” convergent validity, and 73% of the studies were classified with a “high risk of bias.” Seven questionnaires showed “adequate” reliability, and 27.3% of the studies were rated with a “very low risk of bias.” None of the questionnaires showed “adequate” criterion validity and reliability, simultaneously. Conclusions: Existing questionnaires have insufficient measurement properties, and none considered the 24-hour movement behavior paradigm. These results highlight the need for better questionnaires of movement behavior combinations, to improve the monitoring and surveillance systems of 24-hour movement behaviors in this population.