Jin H. Yan

Developmental differences in children's ballistic aiming movements of the arm.

An experiment was conducted to examine the change in the relation between programming and “on-line” correction as a developmental explanation of childrens arm movement performance. Each of 54 children in three age groups (5. 8, and 10 yr.) completed two types of rapid aiming arm movements in the longitudinal plane on the surface of a digitizer. Percent primary submovements and timing variability were dependent variables. Analysis suggested that the 5-yr.-olds used “on-line” monitoring during the arm movement and did not perform the movement sequence as a functional unit. Compared with 8- and 10-yr.-olds, the 5-yr.-olds planned a smaller portion of movements, executed the arm movements with more variability in time to peak velocity. The 8- and 10-yr.-olds appeared to plan their movements and execute the sequence as a unit. The developmental implications were discussed.

Effects of Aging, Grip Span, and Grip Style on Hand Strength

rm and hand movements such as reaching, grasping, A transporting, and manipulating objects are essential to everyday life. Consistent and efficient hand strength contributes to quality of life in general as well as to many specific daily activities (e.g., cooking, dining, dressing, driving, or openingjars or bottles). Hand strength for daily functional living is especially critical for senior adults who continue to sustain independent lifestyles. Morbidity and longevity studies have indicated that the adult lifespan for both men and women continues to increase, primarily due to advances in medical technology and information dissemination systems (Campion, 1998). However, the developmental aspects of aging continue to precipitate decreases in physiological functions in addition to increases in degenerative conditions requiring medically related intervention among most senior adults (Watts, 1998). As a result, many seniors (age 65 years or older) use assistive devices to compensate for their declining physical and motor capabilities or to achieve independence in daily living (Laplante, Hendershot, & Moss, 1992). These devices include walkers, canes, crutches, reachers, and wheelchairs (Malone, 1980). Use of these orthotic assistive devices requires some degree of handgrip strength. Thus, a better understanding of the grip movement conditions

Developmental Kinematics of Young Girls' Overarm Throwing

S Udies have shown that faster throwing velocity or onger throwing distance is a collective function of childrens practice experience, growth, and maturation (Halverson & Roberton, 1979; Halverson, Roberton, & Langendorfer, 1982; Nelson, Thomas, & Nelson, 1991; Nelson, Thomas, Nelson, & Abraham, 1986). Developmental levels of overarm throwing were initially proposed by Wild (1938) and further studied by Roberton and her colleagues (e.g., Roberton, 1977, 1978; Roberton, Halverson, & Erbaugh, 1981). Researchers typically analyze the action components of overarm throwing such as forearm action (lateralmedial rotation of the humerus), arm swing (humerus oblique, independent, or lags), trunk rotation (block or differentiated), and foot stepping (from no step to contralateral and long step). However, quantitative values concerning the characteristics of throwing-related joint activities (elbow, shoulder, and trunk) for young childrens overarm throwing have yet to be determined. Marques-Bruna and Grimshaw (1997) raised questions concerning the underlying mechanisms for age-related differences in children. The measurement ofjoint kinematics (angles, angular velocities, or the timing ofjoint movements) can quantify the joint activities and offer

Does Data Distribution Change as a Function of Motor Skill Practice

Theories about motor control and learning pose both central control (e.g., motor programming) and dynamical systems views of skilled behavior. Regardless of the theoretical views and differing methodologies used, experimenters in both models collect behavioral data about skill processes to infer about control and learning. Evaluation of learning typically requires many practice trials over substantial periods of time (Abernethy & Sparrow, 1992; Schmidt, 2003). Of primary interest is Micceri’s (1989) hypothesis that the shape of the data distribution may change as a result of practice., particularly from normal distributions at the beginning of practice to “lumpy” distributions later in practice trials. “Lumpy” distributions occur, because subgroups of participants change in similar ways as a result of practice. Micceri showed this was true in many samples from psychological data, leading to the notion that practice data from movement tasks may also change in nonnormal ways as a result of practice. For example, practice has two associated effects on reaction time. As the amount of practice increases, the number of errors decreases and the reaction times within participants become less variable (Sanders, 1998). Another example may be the type or level of the skill; some fundamental skills (e.g., walking, jumping) of childhood that develop in all healthy children may well be expected to show normal distributions, while other skills developed more with practice (e.g., throwing and striking) may have more nonnormal distributions. Of course, this may also depend on the skill characteristics being assessed. In throwing, the outcome (how far was the ball thrown) could be the measure, or some other process characteristic of the throw, such as differentiated rotation between the shoulders and hip, could be collected with high-speed analysis. A review of Volume 74 (2003) of Research Quarterly for Exercise and Sport shows that seven studies involving practice/training were reported. The average sample size of the groups was 12.9, with a range from 8 to 31. None of these studies reported evaluating potential changes in data distribution over practice/training trials. Thus, evaluating the change in the distribution over practice in small sample sizes is logical. The evaluation of data normality is just one of three assumptions for parametric analyses (normality, linearity, and homoscedasticity; e.g., Mertler & Vannatta, 2002). Most modern statistical texts have become increasingly concerned that researchers do “pre-analysis data screening” on the three assumptions as well as issues such as missing data and outliers. In fact, books often devote a separate chapter to that topic (e.g., Mertler & Vannatta, 2002). In the current study, we reanalyzed a published data set (Thomas, Yan, & Stelmach, 2000) to examine changes in the distribution’s shape over a series of practice trials. In this experiment, 60 6-year-olds, 9-year-olds, and college Does Data Distribution Change as a Function of Motor Skill Practice?