Journal of Physical Activity and Health
In recent years, it has become increasingly evident that higher education in the United States is experiencing somewhat of a paradigm shift. We are being challenged to reform our institutions in order to respond to changing societal needs resulting from the fast-paced, digital transformation of industries, societal systems, and our daily lives. The member institutions of the American Academy of Kinesiology will need to think long and hard about how they will respond to these challenges. America’s universities have a responsibility to be a catalyst for the human-centric, technology-driven transformation of sectors such as transportation, agriculture, medicine, public health, clean energy, and manufacturing, among others, and to provide the vision, leadership, and innovation that such workforce transformation demands. Within the academy, we rightly take great pride in our long-standing contributions to the development and deployment of breakthrough discoveries and innovations that have contributed to the transformation of society. However, we have begun to realize that our institutions will need to bring this same commitment to innovation to our teaching, curricula, and instructional programs. Addressing these new areas of need and opportunity will require institutional innovation and reform, for us and for the postsecondary education sector generally. I believe that American Kinesiology Association member departments can play a significant role in the transformation of higher education at our institutions. I am delighted that the American Kinesiology Association has begun to think through how these changes will impact the future of our discipline. I am both optimistic and excited about the many ways that American Kinesiology Association member institutions will continue to play a leading role in the new higher education reality.
Journal of Physical Activity & Health
Kara K. Palmer, Adam Pennell, Bryan Terlizzi, Michael A. Nunu, David F. Stodden, and Leah E. Robinson
This study (a) examined the associations among different performance metrics derived from different strategies (i.e., maximum and average scores) and trials from product-oriented measures of motor skills, and (b) explored how different performance metrics from product-oriented assessments of motor skills change in young children with typical development. Children (N = 279; 156 girls; M age = 4.44 years) completed a battery of product-oriented assessments for throwing (in meters per second, five trials); kicking (in meters per second, five trials); jumping (in centimeters, five trials); running (in meters per second, two trials); and hopping (in meters per second, four trials—two preferred foot, two nonpreferred foot). A total of 36 performance metrics were derived—throw (n = 7), kick (n = 7), jump (n = 7), run (n = 4), and hop (n = 11). Intraclass correlations examined reliability among performance metrics for each skill; linear mixed models examined whether variations changed across early childhood. There was excellent reliability among all performance metrics for each skill (all ICC > .90). Linear mixed models revealed that children’s motor performance improved for two metrics of the throw, five variations of the jump, and three metrics of the hop (all p < .05). Researchers should be aware that some performance metrics from product-oriented assessments (e.g., maximum and average of three or five trials) are highly related and change, whereas others do not.
Sugalya Amatachaya, Pakwipa Chokphukiao, Puttipong Poncumhak, Roongnapa Intaruk, Thiwabhorn Thaweewannakij, and Pipatana Amatachaya
Adequate body composition is essential for health, function, and independence in older adults. However, standard body composition assessments require complex and costly modalities, limiting their use for early detection of body composition changes and periodic follow-up. This study explored the ability of three practical measures—handgrip strength, five times sit-to-stand test, and upper limb loading during seated push-up test (ULL-SPUT)—to determine body composition in 109 older adults with and without sarcopenia. Participants (average age 76 years) were cross-sectionally measured for outcomes of the study. The ULL-SPUT and handgrip strength, but not the five times sit-to-stand test, significantly correlated with body composition (rs , r = .297–.827, p < .01). The ULL-SPUT, in combination with demographic data, could determine body composition up to 82%. Therefore, the ULL-SPUT may be a practical preliminary measure to identify older adults for whom standard body composition assessments and follow-up would prove timely and beneficial.
Maria Kasanen, Arto Laukkanen, Donna Niemistö, Jimi Kotkajuuri, Nanne-Mari Luukkainen, and Arja Sääkslahti
This study was conducted to determine how total fundamental movement skill (FMS) score and, separately, locomotor skill (LMS), and object control skill scores in children 3–8 years old predicted their specific-intensity physical activity 3 years later. Overall, 441 Finnish children (51.7% female, baseline mean age of 5.6 years) participated in the study. Total FMS, LMS, and object control skill scores were assessed using the Test of Gross Motor Development, third edition. The time spent engaged in physical activity of different intensities (light, moderate, vigorous, moderate-to-vigorous, light-to-vigorous, and sedentary behavior) was determined using accelerometers. A two-level regression model was used in the analysis, considering potential covariates and interactions. The results showed that moderate physical activity, vigorous physical activity, and moderate-to-vigorous physical activity were predicted by the total FMS score (β = 0.177 to 0.203, p = .001–.003) and the LMS score (β = 0.140 to 0.164, p = .004–.014), but not the object control skill score. Moreover, the LMS score inversely predicted sedentary behavior (β = −0.116, p = .042). In conclusion, higher FMS and, specifically, LMS scores seem to predict more engagement in moderate-to-vigorous physical activity and less sedentary behavior over time. However, most of the variance in physical activity remains unexplained.