Competence in fundamental motor skills (FMS) facilitates physical activity participation and is important for children’s holistic development. This study aimed to systematically review the FMS levels of children worldwide, using the Test of Gross Motor Development-2 (TGMD-2). In accordance with PRISMA guidelines, studies were identified from searches across 7 databases. Studies were required to: (i) include typically developing children (3–10 years), (ii) be published in English, (iii) have been published between 2004 and 2019 and, (iv) report ≥1 TGMD-2 outcome scores. Extracted data were evaluated based on importance of determinants, strength of evidence, and methodological quality. Data from 64 articles were included. Weighted mean (and standard deviation) scores were calculated for each FMS outcome score. Analyses revealed FMS competence increases across age during childhood, with greater proficiency in locomotor skills than object control skills. Additionally, boys exhibit higher object control skill proficiency than girls. Compared to TGMD-2 normative data, children demonstrate “below average” to “average” FMS levels. This review highlights the scope for FMS development among children worldwide. These findings reinforce the necessity for FMS interventions in early educational settings, as FMS competence is positively associated with physical activity and other health outcomes.

Fundamental movement skills (FMS) are frequently referred to as the “building blocks” of movement for children and adolescents in their lifelong physical activity journey. It is critical, however, that FMS are developed within Physical Education learning environments and other sport-related settings, specifically as these building blocks of movement require appropriate teaching and practice opportunities. While FMS are well-established as an “important focus” for children and adolescents, to the authors’ knowledge, there appears to be no standardized FMS development guidelines existent within the literature. This paper will examine whether the frequency, intensity, time, and type (FITT) principle could be transferable to interventions focusing on FMS development, and if so, whether sufficient consistency of findings exists to guide practitioners in their session design. Applying the FITT principle in this way may help to facilitate the comparison of FMS-related intervention studies, which may contribute to the future development of practical FMS-related guidelines for children and adolescents.

Background: The Functional Movement Screen™ (FMS™) is an assessment of human movement that may signal potential deficits that could predispose an otherwise healthy person to injury risk. FMS™ scores are well reported in both athletic and adult samples. However, to date, there has been no comprehensive systematic review and meta-analysis of FMS™ data among school-aged children and adolescents. Objective: We aimed to systematically review and analyse functional movement proficiency of children and adolescents, specifically when assessed using the FMS™, and to establish initial normative values for the FMS™ in this population group and to further estimate differences in functional movement proficiency between the sexes, by school level (i.e., between primary and secondary school-level children and adolescents), and based on differences in child and adolescent body mass index (BMI). Methods: In accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, prospective studies were identified from searches across eight databases (MEDLINE, SPORTDiscus, CINAHL, Web of Science, EMBASE, ERIC, PsychINFO and PubMed), without any date restrictions, up to December 2020. The primary meta-analysis estimated the overall FMS™ score for school-aged children and adolescents across published studies. An additional three subgroup meta-analyses estimated comparisons for FMS™ data with school level, sex, and BMI across published studies. FMS™ data were meta-analysed using a number of different meta packages (Schwarzer et al. in Meta-Analysis with R, 1st ed, Springer International Publishing, Berlin, 2015), available in R Studio. Results: A total of 19 articles were included in the systematic review. Meta-analysis revealed a weighted FMS™ mean score of 14.06, with a standardised Tau value of 0.56, signalling a moderate-to-large degree of variability in FMS™ means between studies. The difference in FMS™ means between samples of males (weighted FMS™ mean 13.91) and females (weighted FMS™ mean 14.56) was compatible with a possible small effect size (standardised mean difference − 0.27). The variability in FMS™ means between studies was approximately five times greater in samples of secondary school children (factor difference in Tau values 5.16). The final meta-regression identified a negative association between BMI and FMS™ scores (r = − 0.42), which signalled a moderate-to-large difference in FMS™ scores between healthy weight and overweight children/adolescents. Conclusion: This systematic review and meta-analysis represents a novel and important synthesis of published FMS™ data from groups of children and adolescents. The study signals possible sex- and age-related differences in FMS™ scores, as well as a clear negative relationship between BMI and functional movement proficiency. More longitudinal research is needed to better understand the developmental trajectory and the effects of maturation milestones on FMS™ proficiency. Additional research is also needed to identify the types of interventions that could improve functional movement proficiency among ‘at risk’ groups, who are susceptible to functional movement deficiency, and whether changes in body composition mediate the relationship between these interventions and the improvement of FMS™ scores.

Purpose: This study aimed to investigate the relationship between fundamental movement skills (FMS) and markers of health among a cohort of Irish primary school children. Methods: Participants (N = 296, mean age: 7.99 ± 2.02 years) were senior infant (n = 149, mean age: 6.02 ± 0.39 years) and 4th class (n = 147, mean age: 9.97 ± 0.40 years) students from three primary schools in Cork, Ireland. FMS proficiency (TGMD-2) and markers of health (BMI percentile, waist circumference percentile, blood pressure percentiles, resting heart rate, cardiorespiratory fitness, objectively measured physical activity; PA) measurements were recorded. Correlation and hierarchical stepwise multiple linear regression analyses were conducted to investigate the relationship between FMS and markers of health. Results: A small, positive relationship was found between FMS (Gross Motor Quotient; GMQ) and cardiorespiratory fitness with small negative correlations between GMQ and 550 m time SDS among 6-year-olds (r(129) = −.286, p < .05) and 10-year-olds (r(132) = −.340, p < .05). A moderate, positive correlation was found between GMQ and light PA (r(71) = .400, p < .05). Small positive correlations were revealed between GMQ and moderate PA (r(71) = .259, p < .05) and between GMQ and total PA (r(71) = .355, p < .05). After adjusting for age, sex, the interaction effect of age and sex, and school attended, FMS explained 15.9% and 24.8% of the variance in 550 m time SDS among 6- and 10-year-olds, respectively, and 6% and 6.5% of the variance in light PA and moderate PA, respectively. After adjusting for age and sex, FMS explained 11.6% of the variance in total PA. Conclusion: A wide range of FMS is important for children’s cardiorespiratory fitness and PA.

The use of embedded smartphone sensors offers opportunities to measure physical activity (PA) and human movement. Big data-which includes billions of digital traces-offers scientists a new lens to examine PA in fine-grained detail and allows us to track people's geocoded movement patterns to determine their interaction with the environment. The objective of this study was to examine the validity of the Movn smartphone app (Moving Analytics) for collecting PA and human movement data. The criterion and convergent validity of the Movn smartphone app for estimating energy expenditure (EE) were assessed in both laboratory and free-living settings, compared with indirect calorimetry (criterion reference) and a stand-alone accelerometer that is commonly used in PA research (GT1m, ActiGraph Corp, convergent reference). A supporting cross-validation study assessed the consistency of activity data when collected across different smartphone devices. Global positioning system (GPS) and accelerometer data were integrated with geographical information software to demonstrate the feasibility of geospatial analysis of human movement. A total of 21 participants contributed to linear regression analysis to estimate EE from Movn activity counts (standard error of estimation [SEE]=1.94 kcal/min). The equation was cross-validated in an independent sample (N=42, SEE=1.10 kcal/min). During laboratory-based treadmill exercise, EE from Movn was comparable to calorimetry (bias=0.36 [-0.07 to 0.78] kcal/min, t82=1.66, P=.10) but overestimated as compared with the ActiGraph accelerometer (bias=0.93 [0.58-1.29] kcal/min, t89=5.27, P<.001). The absolute magnitude of criterion biases increased as a function of locomotive speed (F1,4=7.54, P<.001) but was relatively consistent for the convergent comparison (F1,4=1.26, P<.29). Furthermore, 95% limits of agreement were consistent for criterion and convergent biases, and EE from Movn was strongly correlated with both reference measures (criterion r=.91, convergent r=.92, both P<.001). Movn overestimated EE during free-living activities (bias=1.00 [0.98-1.02] kcal/min, t6123=101.49, P<.001), and biases were larger during high-intensity activities (F3,6120=1550.51, P<.001). In addition, 95% limits of agreement for convergent biases were heterogeneous across free-living activity intensity levels, but Movn and ActiGraph measures were strongly correlated (r=.87, P<.001). Integration of GPS and accelerometer data within a geographic information system (GIS) enabled creation of individual temporospatial maps. The Movn smartphone app can provide valid passive measurement of EE and can enrich these data with contextualizing temporospatial information. Although enhanced understanding of geographic and temporal variation in human movement patterns could inform intervention development, it also presents challenges for data processing and analytics.

Given the well-established impact of COVID-19 on university students’ health and lifestyle parameters, the current study sought to investigate these impacts within an Irish university setting. A cross-sectional design was employed, with a 68-item questionnaire instrument disseminated to all Year 2 undergraduate students in the host institution (N = 2752), yielding a 9.7% response rate (n = 266). This questionnaire elicited students’ self-reported changes to health-related behaviours, mental well-being and academic engagement across 4 defined time-points: (T0: prior to COVID-19, T1: initial onset of COVID-19, T2: during COVID-19, and T3: time of data collection). Many items were adapted from previous Irish research and additional validated scales included the Alcohol Use Disorders Identification Test (AUDIT-C) and the World Health Organisation’s Well-being scale (WHO-5). Key findings revealed that at T1, substantially more males reported ‘good/very good’ general health than females (76.3% vs. 70.8%), while physical activity patterns followed a similar trend at both T0 (80% vs. 66.1%) and T1 (66.7% vs. 61%). A total of 78.4% of participants reported a body mass gain from T0 to T3, thus reflecting the reduced physical activity levels and compromised nutritional patterns across this period. Worryingly, AUDIT-C scale data revealed hazardous drinking habits were evident in both males and females, while fruit and vegetable intake, physical activity levels, and mental well-being among this cohort remained notably sub-optimal. Ratings of positive academic engagement also decreased substantially between T0 (90.3%) and T3 (30.4%). These findings substantiate the rationale for tailored health promotion interventions in university settings to support students’ transition back to traditional programme delivery and, of equal importance, to improve general health and well-being post-COVID-19 within this cohort.