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You Fu, Zan Gao, James C. Hannon, Ryan D. Burns and Timothy A. Brusseau Jr.


This study aimed to examine the effect of a 9-week SPARK program on physical activity (PA), cardiorespiratory endurance (Progressive Aerobic Cardiovascular Endurance Run; PACER), and motivation in middle-school students.


174 students attended baseline and posttests and change scores computed for each outcome. A MANOVA was employed to examine change score differences using follow-up ANOVA and Bonferroni post hoc tests.


MANOVA yielded a significant interaction for Grade × Gender × Group (Wilks’s Λ = 0.89, P < .001). ANOVA for PA revealed significant differences between SPARK grades 6 and 7 (Mean Δ = 8.11, P < .01) and Traditional grades 6 and 8 (Mean Δ = –6.96, P < .01). ANOVA also revealed greater PACER change for Traditional boys in grade 8 (P < .01) and SPARK girls in grade 8 (P < .01). There were significant interactions with perceived competence differences between SPARK grades 6 and 8 (Mean Δ = 0.38, P < .05), Enjoyment differences between SPARK grades 6 and 7 (Mean Δ = 0.67, P < .001), and SPARK grades 6 and 8 (Mean Δ = 0.81, P < .001).


Following the intervention, SPARK displayed greater increases on PA and motivation measures in younger students compared with the Traditional program.

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Zachary C. Pope, Nan Zeng, Xianxiong Li, Wenfeng Liu and Zan Gao

Background: This study examined the accuracy of Microsoft Band (MB), Fitbit Surge HR (FS), TomTom Cardio Watch (TT), and Apple Watch (AW) for energy expenditure (EE) estimation at rest and at different physical activity (PA) intensities. Method: During summer 2016, 25 college students (13 females; M age = 23.52 ± 1.04 years) completed four separate 10-minute exercise sessions: rest (i.e., seated quietly), light PA (LPA; 3.0-mph walking), moderate PA (MPA; 5.0-mph jogging), and vigorous PA (VPA; 7.0-mph running) on a treadmill. Indirect calorimetry served as the criterion EE measure. The AW and TT were placed on the right wrist and the FS and MB on the left—serving as comparison devices. Data were analyzed in late 2017. Results: Pearson correlation coefficients revealed only three significant relationships (r = 0.43–0.57) between smartwatches’ EE estimates and indirect calorimetry: rest-TT; LPA-MB; and MPA-AW. Mean absolute percentage error (MAPE) values indicated the MB (35.4%) and AW (42.3%) possessed the lowest error across all sessions, with MAPE across all smartwatches lowest during the LPA (33.7%) and VPA (24.6%) sessions. During equivalence testing, no smartwatch’s 90% CI fell within the equivalence region designated by indirect calorimetry. However, the greatest overlap between smartwatches’ 90% CIs and indirect calorimetry’s equivalency region was observed during the LPA and VPA sessions. Finally, EE estimate variation attributable to the use of different manufacturer’s devices was greatest at rest (53.7 ± 12.6%), but incrementally decreased as PA intensity increased. Conclusions: MB and AW appear most accurate for EE estimation. However, smartwatch manufacturers may consider concentrating most on improving EE estimate accuracy during MPA.

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David F. Stodden, Zan Gao, Jacqueline D. Goodway and Stephen J. Langendorfer

This cross-sectional study examined associations among motor skill competence (MSC) and health-related fitness (HRF) in youth. A convenient sample of 253 boys and 203 girls (aged 4–13 years) participated in the study. Associations among measures of MSC (throwing and kicking speed and standing long jump distance) and a composite measure of HRF (push-ups, curl-ups, grip strength and PACER test) across five age groups (4–5, 6–7, 8–9, 10–11 and 12–13 yrs.) were assessed using hierarchical regression modeling. When including all children, throwing and jumping were significantly associated with the composite HRF factor for both boys and girls (throw, t = 5.33; jump, t = 4.49) beyond the significant age effect (t = 4.98) with kicking approaching significance (t = 1.73, p = .08). Associations between throwing and kicking speed and HRF appeared to increase from early to middle to late childhood age ranges. Associations between jumping and HRF were variable across age groups. These results support the notion that the relationship between MSC and HRF performance are dynamic and may change across childhood. These data suggest that the development of object control skills in childhood may be important for the development and maintenance of HRF across childhood and into adolescence.

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Weidong Li, Zan Gao, Zhihua Yin, Ping Xiang, Bo Shen and Qingtao Kong


This study examined the impact of published national physical activity (PA) and health guidelines, documents, and initiatives on the evolution of research on teaching K-12 physical education (PE) in U.S.A. from 1996 to October 2013.


A total of 262 peer-reviewed, data-based journal articles meeting our inclusion and exclusion criteria were identified through a comprehensive search. These articles were coded and the resulting data were analyzed.

Results and Discussions:

The findings showed that 41% (108 out of 262) of articles had cited these identified guidelines, documents and Centers for Disease Controls and Prevention (CDC) reports. In particular, the most frequently cited documents were Healthy People documents, the 1996 Report of Surgeon General, and CDC reports and studies. The citation of these guidelines, documents and CDC reports fluctuated over the years. Our findings also showed that among the research studies citing these national documents and reports, 56% of them focused on students’ PA/fitness, while only a few studies focused on students’ psycho-motor skills and game performance. The majority of the studies reviewed were nonexperimental quantitative studies while 10% using randomized control trials or randomized group control trials design.


The results revealed a substantial proportion of articles cited national guidelines, initiatives and CDC study reports. These guidelines and documents have had some impact on the evolution of research on teaching K-12 PE.