Recent progress in technology has allowed for the development and validation of computer-based adaptations of existing pencil-and-paper neuropsychological measures and comprehensive cognitive test batteries. These computer-based assessments are frequently implemented in the field of clinical sports psychology to evaluate athletes’ functioning postconcussion. These tests provide practical and psychometric advantages over their pencil-and-paper counterparts in this setting; however, these tests also provide clinicians with unique challenges absent in paper-and-pencil testing. The purpose of this article is to present advantages and disadvantages of computer-based testing, generally, as well as considerations for the use of computer-based assessments for the evaluation of concussion among athletes. Furthermore, the paper provides suggestions for further development of computerized assessment of sports concussion given the limitations of the current technology.
John L. Woodard and Annalise A.M. Rahman
Minakshi Nayak, Karen Wills, Megan Teychenne, and Verity Cleland
Detrimental associations have been identified between sedentary behavior (SB) and health. 1 The SB includes sitting or reclining activities such as television (TV) viewing, computer use, or reading. 2 TV viewing has been consistently associated with adverse health outcomes, including obesity, 3
Akinori Nagano, Senshi Fukashiro, and Taku Komura
Contribution of series elasticity of the human mm. triceps surae in cyclic heel-raise exercise (similar to hopping but the feet do not leave the floor) was examined via computer modeling and simulation. A two-dimensional skeletal model of the human body was constructed. Upright posture was maintained throughout the simulation to prevent the model from falling. A mathematical representation of the mm. triceps surae was implemented in the skeletal model. The muscle was activated by the neural activation input signal with a time resolution of 0.050 sec. Cyclic heel-raise exercises of cycle duration ranging from 0.300 sec to 0.900 sec, corresponding to the motion frequency of 200 to 66.7 cycles/min, were generated using an optimization approach. The goal of the numerical optimization was to generate cyclic motions with as much range of motion as possible. As a result, realistic heel-raise motions were generated with the range of motion between 0.0023 m (cycle duration = 0.300 sec) and 0.0414 m (cycle duration = 0.900 sec). It was found that contribution of the series elasticity in positive mechanical work output of the muscle-tendon complex during the pushoff phase (from the lowest position to the termination of a cycle) increased as motion frequency increased (3% at 66.7 cycles/min to 47% at 200 cycles/min). Relatively higher muscle activation was found during the downward moving phase when the motion frequency was higher. These tendencies are consistent with the findings reported in preceding studies involving experimental animals as well as human participants. It is suggested that series elasticity plays an integral role in the generation of cyclic human motions.
Mallory S. Kobak, Andrew Lepp, Michael J. Rebold, Hannah Faulkner, Shannon Martin, and Jacob E. Barkley
equipment and technology ( 5 , 7 , 12 – 14 , 18 , 23 , 34 , 35 , 37 , 43 ). In recent years, young children have become a growing part of the population who utilize mobile Internet-connected electronic devices (eg, cellular telephones, tablet computers) for purposes such as talking/texting, accessing
This study sought to identify factors associated with computer resistance for employees within subsets of three segments of the sport industry. Seven hypotheses were developed to test the relationship between computer resistance and various independent variables, including assorted demographic factors and an employee’s background. Prior hands-on computer experience was the most important determinant of the extent of computer resistance. Another important determinant was age, with younger employees being less computer resistant than older employees. Other characteristics associated with computer resistance included number of years in present employment and exposure to computer education.
Janet E. Fulton, Xuewen Wang, Michelle M. Yore, Susan A. Carlson, Deborah A. Galuska, and Carl J. Caspersen
To examine the prevalence of television (TV) viewing, computer use, and their combination and associations with demographic characteristics and body mass index (BMI) among U.S. youth.
The 1999 to 2006 National Health and Nutrition Examination Survey (NHANES) was used. Time spent yesterday sitting and watching television or videos (TV viewing) and using the computer or playing computer games (computer use) were assessed by questionnaire.
Prevalence (%) of meeting the U.S. objective for TV viewing (≤2 hours/day) ranged from 65% to 71%. Prevalence of no computer use (0 hours/day) ranged from 23% to 45%. Non-Hispanic Black youth aged 2 to 15 years were less likely than their non-Hispanic White counterparts to meet the objective for TV viewing. Overweight or obese school-age youth were less likely than their normal weight counterparts to meet the objective for TV viewing
Computer use is prevalent among U.S. youth; more than half of youth used a computer on the previous day. The proportion of youth meeting the U.S. objective for TV viewing is less than the target of 75%. Time spent in sedentary behaviors such as viewing TV may contribute to overweight and obesity among U.S. youth.
Gunnar Treff, Kay Winkert, Katja Machus, and Jürgen M. Steinacker
of the computer screen, which was placed in front of the RowErg. The display of the Concept2 ergometer was tilted down and not visible for the rowers during the test. Figure 1 —Schematic view of the screen during the ramp test. The solid diagonal line represents target power output; the broken lines
Jorge Mota, José Ribeiro, Maria Paula Santos, and Helena Gomes
This study aimed to examine the relationship between obesity status (body mass index: BMI) and physical and sedentary activities in adolescents. The sample comprised 230 girls and 220 boys (14.6 years old, SD = 1.6). Physical Activity (PA) was assessed by a questionnaire. Sedentary behaviors, such as TV viewing, computer use, and commuting to and from school were analyzed. Participants were categorized as nonobese or overweight/obese according to age-adapted BMI. No significant differences were found in relation to PA characteristics or in TV watching on weekdays vs. weekends. Nonobese participants spent significantly less time using computers on weekends (p = .04) and weekdays (p = .025) than their overweight/obese counterparts. Logistic regression analysis showed that those who used computers on weekdays more than 4 hrs per day were likely (odds ratio: 5.79; p < .003) to be overweight or obese. This study identified a relationship between computer use, but not physical activity or TV viewing, and weight status among Portuguese adolescents.
Sally A. McLure, John J. Reilly, Sean Crooks, and Carolyn D. Summerbell
A novel computer tool (peas@tees), designed to assess habitual physical activity levels in children aged 9 and 10 years, was evaluated. Study 1 investigated agreement between peas@tees and accelerometry in 157 children. Bland-Altman limits of agreement (LOA) revealed peas@tees underestimated physical activity levels compared with accelerometry (bias −21 min; 95% LOA -146–105). Study 2 investigated stability of peas@tees in a separate sample of 42 children. Intraclass correlation coefficient was 0.75 (95% CI 0.62–0.84). Computer tools are promising as a cheap, feasible, and useful method to monitor children’s habitual levels of physical activity at the group level.
Jeffrey J. Martin, Nate McCaughtry, Pamela Kulinna, Donetta Cothran, and Roberta Faust
The purpose of our study was to examine the impact of mentoring-based professional development on physical education teachers’ efficacy. Experienced mentor teachers were paired (n = 15) with inexperienced protégé teachers (n = 15) at the beginning of a yearlong intervention study. It was hypothesized that teachers would increase their efficacy to use pedometers and computers to enhance instruction, and reduce their computer anxiety. Repeated-measures ANOVAs for mentors and protégés revealed a variety of significant main effects. We found increases in computer and pedometer efficacy. A second set of repeated-measures ANOVAs based on mentors’, protégés’, and control groups’ scores revealed a significant interaction for computer efficacy, indicating that both mentors and protégés significantly increased their computer efficacy compared with the control group. Finally, a significant interaction effect was also found for pedometer efficacy, again indicating that both groups significantly increased their efficacy compared with control teachers.