Task constraints

Newell (1985, 1986) identified the importance of interacting constraints on the emergent behaviours of learners or performers in sport as they assemble functional states of movement organisation in achieving task goals. Constraints, related to the person, task and environment, were defined as ‘boundaries or features that limit motion of the entity under consideration at any moment in time’ (Newell, 1986, p.347). Personal (or organismic) constraints include factors such as individual anthropometrics (height, weight, and limb lengths), fitness (e.g., strength, speed, aerobic capacity, and flexibility), mental skills (e.g. concentration, confidence, emotional control and motivation), perceptual and decisionmaking skills (e.g., recognising patterns of play, anticipation by reading the movements of opponents) and personality factors (e.g., risk taking or conservative behaviours). Newell (1986, p.350) distinguished between general environmental constraints, such as gravity, ambient temperature, natural light and altitude and task constraints, which are task specific and concerned with the goals of a specific activity. More recently, socio-cultural constraints (e.g., family support, cultural expectations and access to facilities) have also been considered as environmental constraints. Application of the constraints framework to the study of sport performance has led to task constraints being defined to include factors such as rules of games, equipment used, boundary playing areas and markings, nets and goals, the number of...

Use of cadavers and anthropometric test devices (ATDs) for assessing lower limb injury outcome from under‐vehicle explosions

Lower extremities are particularly susceptible to injury in an under‐vehicle explosion. Operational fitness of military vehicles is assessed through anthropometric test devices (ATDs) in full‐scale blast tests. The aim of this study was to compare the response between the Hybrid‐III ATD, the MiL‐Lx ATD and cadavers in our traumatic injury simulator, which is able to replicate the response of the vehicle floor in an under‐vehicle explosion. All specimens were fitted with a combat boot and tested on our traumatic injury simulator in a seated position. The load recorded in the ATDs was above the tolerance levels recommended by NATO in all tests; no injuries were observed in any of the 3 cadaveric specimens. The Hybrid‐III produced higher peak forces than the MiL‐Lx. The time to peak strain in the calcaneus of the cadavers was similar to the time to peak force in the ATDs. Maximum compression of the sole of the combat boot was similar for cadavers and MiL‐Lx, but significantly greater for the Hybrid‐III. These results suggest that the MiL‐Lx has a more biofidelic response to under‐vehicle explosive events compared to the Hybrid‐III. Therefore, it is recommended that mitigation strategies are assessed using the MiL‐Lx surrogate and not the Hybrid‐III.

Exposition

During the course of study in semester 1, the first year BFA Dance (Performance) students were exposed to various dance genres (in terms of technical training) and associated practices. They were required to gain physical fitness and increase technical accomplishment, strength, flexibility and stylistic versatility through their training. The students also experienced dancing as soloists, with partners and in larger group scenarios. Exposition presents these elements experienced, through a pure dance work. Movement vocabulary was formed employing several methods: specifically choreographed for the individual student; through task-based instruction, which the students constructed; and from learning pre-existing material. Thom Willems dramatic and layered musical score informed the construction of new movement vocabulary; the development of pre-existing material; and the structure of the work.

Controlled automated discovery of collections of business process models

Automated process discovery techniques aim at extracting process models from information system logs. Existing techniques in this space are effective when applied to relatively small or regular logs, but generate spaghetti-like and sometimes inaccurate models when confronted to logs with high variability. In previous work, trace clustering has been applied in an attempt to reduce the size and complexity of automatically discovered process models. The idea is to split the log into clusters and to discover one model per cluster. This leads to a collection of process models – each one representing a variant of the business process – as opposed to an all-encompassing model. Still, models produced in this way may exhibit unacceptably high complexity and low fitness. In this setting, this paper presents a two-way divide-and-conquer process discovery technique, wherein the discovered process models are split on the one hand by variants and on the other hand hierarchically using subprocess extraction. Splitting is performed in a controlled manner in order to achieve user-defined complexity or fitness thresholds. Experiments on real-life logs show that the technique produces collections of models substantially smaller than those extracted by applying existing trace clustering techniques, while allowing the user to control the fitness of the resulting models.

Process compliance analysis based on behavioural profiles

Process compliance measurement is getting increasing attention in companies due to stricter legal requirements and market pressure for operational excellence. In order to judge on compliance of the business processing, the degree of behavioural deviation of a case, i.e., an observed execution sequence, is quantified with respect to a process model (referred to as fitness, or recall). Recently, different compliance measures have been proposed. Still, nearly all of them are grounded on state-based techniques and the trace equivalence criterion, in particular. As a consequence, these approaches have to deal with the state explosion problem. In this paper, we argue that a behavioural abstraction may be leveraged to measure the compliance of a process log – a collection of cases. To this end, we utilise causal behavioural profiles that capture the behavioural characteristics of process models and cases, and can be computed efficiently. We propose different compliance measures based on these profiles, discuss the impact of noise in process logs on our measures, and show how diagnostic information on non-compliance is derived. As a validation, we report on findings of applying our approach in a case study with an international service provider.

Evaluating a model of parental influence on youth physical activity

Objective To test a conceptual model linking parental physical activity orientations, parental support for physical activity, and children's self-efficacy perceptions with physical activity participation. Participants and setting The sample consisted of 380 students in grades 7 through 12 (mean age, 14.0±1.6 years) and their parents. Data collection took place during the fall of 1996. Main outcome measures Parents completed a questionnaire assessing their physical activity habits, enjoyment of physical activity, beliefs regarding the importance of physical activity, and supportive behaviors for their child's physical activity. Students completed a 46-item inventory assessing physical activity during the previous 7 days and a 5-item physical activity self-efficacy scale. The model was tested via observed variable path analysis using structural equation modeling techniques (AMOS 4.0). Results An initial model, in which parent physical activity orientations predicted child physical activity via parental support and child self-efficacy, did not provide an acceptable fit to the data. Inclusion of a direct path from parental support to child physical activity and deletion of a nonsignificant path from parental physical activity to child physical activity significantly improved model fit. Standardized path coefficients for the revised model ranged from 0.17 to 0.24, and all were significant at the p<0.0001 level. Conclusions Parental support was an important correlate of youth physical activity, acting directly or indirectly through its influence on self-efficacy. Physical activity interventions targeted at youth should include and evaluate the efficacy of individual-level and community-level strategies to increase parents’ capacity to provide instrumental and motivational support for their children's physical activity.

Physical activity and determinants of physical activity in obese and non-obese children

OBJECTIVE To compare the physical activity (PA) patterns and the hypothesized psychosocial and environmental determinants of PA in an ethnically diverse sample of obese and non-obese middle school children. DESIGN Cross-sectional study. SUBJECTS One-hundred and thirty-three non-obese and 54 obese sixth grade children (mean age of 11.4 +/-0.6). Obesity status determined using the age-, race- and gender-specific 95th percentile for BMI from NHANES-1. MEASUREMENTS Objective measurements were collected of PA over a 7-day period using the CSA 7164 accelerometer: total daily counts; daily moderate (3-5.9 METs) physical activity (MPA); daily vigorous physical activity (greater than or equal to 6 METs; VPA); and weekly number of 5, 10 and 20 min bouts of moderate-to-vigorous physical activity (greater than or equal to 3 METs, MVPA). Self-report measures were collected of PA self-efficacy; social influences regarding PA, beliefs about PA outcomes; perceived PA levels of parents and peers, access to sporting and/or fitness equipment at home, involvement in community-based PA organizations; participation in community sports teams; and hours spent watching television or playing video games. RESULTS Compared to their non-obese counterparts, obese children exhibited significantly lower daily accumulations of total counts, MPA and VPA as well as significantly fewer 5, 10 and 20 min bouts of MVPA. Obese children reported significantly lower levels of PA self-efficacy, were involved in significantly fewer community organizations promoting PA and were significantly less likely to report their father or male guardian as physically active. CONCLUSIONS The results are consistent with the hypothesis that physical inactivity is an important contributing factor in the maintenance of childhood obesity. Interventions to promote PA in obese children should endeavor to boost self-efficacy perceptions regarding exercise, increase awareness of, and access to, community PA outlets, and increase parental modeling of PA.

Clinical use of objective measures of physical activity

With measurement of physical activity becoming more common in clinical practice, it is imperative that healthcare professionals become more knowledgeable about the different methods available to objectively measure physical activity behaviour. Objective measures do not rely on information provided by the patient, but instead measure and record the biomechanical or physiological consequences of performing physical activity, often in real time. As such, objective measures are not subject to the reporting bias or recall problems associated with self-report methods. The purpose of this article was to provide an overview of the different methods used to objectively measure physical activity in clinical practice. The review was delimited to heart rate monitoring, accelerometers and pedometers since their small size, low participant burden and relatively low cost make these objective measures appropriate for use in clinical practice settings. For each measure, strengths and weakness were discussed; and whenever possible, literature-based examples of implementation were provided.

Measuring and influencing physical activity with Smartphone technology : a systematic review

Background Rapid developments in technology have encouraged the use of smartphones in physical activity research, although little is known regarding their effectiveness as measurement and intervention tools. Objective This study systematically reviewed evidence on smartphones and their viability for measuring and influencing physical activity. Data Sources Research articles were identified in September 2013 by literature searches in Web of Knowledge, PubMed, PsycINFO, EBSCO, and ScienceDirect. Study Selection The search was restricted using the terms (physical activity OR exercise OR fitness) AND (smartphone* OR mobile phone* OR cell phone*) AND (measurement OR intervention). Reviewed articles were required to be published in international academic peer-reviewed journals, or in full text from international scientific conferences, and focused on measuring physical activity through smartphone processing data and influencing people to be more active through smartphone applications. Study Appraisal and Synthesis Methods Two reviewers independently performed the selection of articles and examined titles and abstracts to exclude those out of scope. Data on study characteristics, technologies used to objectively measure physical activity, strategies applied to influence activity; and the main study findings were extracted and reported. Results A total of 26 articles (with the first published in 2007) met inclusion criteria. All studies were conducted in highly economically advantaged countries; 12 articles focused on special populations (e.g. obese patients). Studies measured physical activity using native mobile features, and/or an external device linked to an application. Measurement accuracy ranged from 52 to 100 % (n = 10 studies). A total of 17 articles implemented and evaluated an intervention. Smartphone strategies to influence physical activity tended to be ad hoc, rather than theory-based approaches; physical activity profiles, goal setting, real-time feedback, social support networking, and online expert consultation were identified as the most useful strategies to encourage physical activity change. Only five studies assessed physical activity intervention effects; all used step counts as the outcome measure. Four studies (three pre–post and one comparative) reported physical activity increases (12–42 participants, 800–1,104 steps/day, 2 weeks–6 months), and one case-control study reported physical activity maintenance (n = 200 participants; >10,000 steps/day) over 3 months. Limitations Smartphone use is a relatively new field of study in physical activity research, and consequently the evidence base is emerging. Conclusions Few studies identified in this review considered the validity of phone-based assessment of physical activity. Those that did report on measurement properties found average-to-excellent levels of accuracy for different behaviors. The range of novel and engaging intervention strategies used by smartphones, and user perceptions on their usefulness and viability, highlights the potential such technology has for physical activity promotion. However, intervention effects reported in the extant literature are modest at best, and future studies need to utilize randomized controlled trial research designs, larger sample sizes, and longer study periods to better explore the physical activity measurement and intervention capabilities of smartphones.

Mediators of physical activity behavior change among women with young children

Background Women with children are less likely to engage in adequate physical activity (PA) than women without children. This study aimed to evaluate the efficacy of two strategies for promoting increased PA among mothers of preschool-aged children, and to explore the mediators of any resulting change in PA behavior. Design Controlled intervention trial incorporating repeated data collection from 554 women, randomized to one of three experimental conditions. Intervention Group 1 served as a control, while women in Groups 2 and 3 were given print information about overcoming PA barriers. Women in Group 3 were also invited to discuss the development of local strategies for the promotion of PA among mothers of young children. The primary strategies included increasing partner support, social advocacy, and capacity building, and were implemented through collaboration among participants, researchers, and community organizations. Main Outcome Measures Adequate physical activity (PA), self-efficacy (SE) and partner support (PS). Results: Following the intervention, women in Group 3 were significantly more likely to meet guidelines for PA than controls (odds ratio [OR]=1.71, confidence interval [CI]=1.05–2.77)] after controlling for age and PA at baseline. After controlling for baseline PA, residualized change in SE (OR=1.86, CI=1.17–2.94) and PS (OR=2.29, CI=1.46–3.58) significantly predicted meeting guidelines. After controlling for residual change in PS and SE, the significant intervention effect was attenuated (Group 3 OR=1.40, CI=0.76–2.36), indicating that partner support and self-efficacy may be mediators of physical activity behavior change. Conclusions The findings indicate that community participation approaches that facilitate increased self-efficacy and partner support can be effective in increasing PA among mothers of young children.

Correlates of objectively measured physical activity in preadolescent youth

Objective The purpose of this study was to identify the psychosocial and environmental correlates of objectively measured physical activity behavior in a diverse sample of sixth-grade students. Design Cross-sectional. Participants and Setting One hundred ninety-eight sixth-grade students from 4 public middle schools in Columbia, South Carolina. The study group was 52.0% female, 55.1% African-American, with a mean age of 11.4 +/- 0.6 years. Main Outcome Measures Time spent in moderate physical activity (MPA) and vigorous physical activity (VPA) was assessed using a uniaxial accelerometer (CSA WAM 7164) (Computer Science and Applications Inc., Shalimar, FL). Determinant variables included: age, gender, race/ethnicity (demographic); physical activity self-efficacy, social norms related to physical activity, and beliefs regarding physical activity outcomes (psychosocial); and perceived physical activity habits of parents and peers, involvement in community physical activity organizations, involvement in community-based sports programs, access to fitness/sporting equipment at home, and self-reported hours spent watching television or playing video games (environmental). Results For boys, physical activity self-efficacy, social norms related to physical activity, and involvement in community physical activity organizations were salient predictors of MPA and VPA. Among girls, only physical activity self-efficacy emerged as a clear predictor of objectively measured physical activity. Conclusions These findings are consistent with previous studies using self-reported physical activity and suggest that interventions to increase physical. activity in preadolescent youth should endeavor to boost physical activity self-efficacy by offering a wide selection of enjoyable, developmentally-appropriate physical activity options.

Validation of a 24-h physical activity recall in indigenous and non-indigenous Australian adolescents

The purpose of this study was to evaluate the concurrent validity of a modified version of the widely used previous day physical activity recall (PDPAR24) self-report instrument in a diverse sample of Australian adolescents comprising Aboriginal and Torres Strait Islanders (A&TSI) and non-indigenous high school students. A sample of 63 A&TSI and 59 non-indigenous high school students (N = 122) from five public secondary schools participated in the study. Participants completed the PDPAR-24 after wearing a seated electronic pedometer on the previous day. Significant positive correlations were observed between the self-reported physical activity variables (mean MET level, blocks of vigorous activity, and blocks of moderate-to-vigorous physical activity) and 24-h step counts. Validity coefficients (rho) ranged from 0.29 to 0.34 (p<0.05). A significant inverse correlation was observed for self-reported screen time and 24-h step count (rho = -0.19, p<0.05). Correlations for A&TSI students were equal to or greater than those observed for non-indigenous students. The PDPAR-24 instrument is a quick, unobtrusive, and cost-effective assessment tool. that would be useful for evaluating physical activity and sedentary behaviour in population-based studies. (C) 2006 Sports Medicine Australia.

Assessment of driving-related performance in chronic whiplash using an advanced driving simulator

Driving is often nominated as problematic by individuals with chronic whiplash associated disorders (WAD), yet driving-related performance has not been evaluated objectively. The purpose of this study was to test driving-related performance in persons with chronic WAD against healthy controls of similar age, gender and driving experience to determine if driving-related performance in the WAD group was sufficiently impaired to recommend fitness to drive assessment. Driving-related performance was assessed using an advanced driving simulator during three driving scenarios; freeway, residential and a central business district (CBD). Total driving duration was approximately 15 min. Five driving tasks which could cause a collision (critical events) were included in the scenarios. In addition, the effect of divided attention (identify red dots projected onto side or rear view mirrors) was assessed three times in each scenario. Driving performance was measured using the simulator performance index (SPI) which is calculated from 12 measures. z-Scores for all SPI measures were calculated for each WAD subject based on mean values of the control subjects. The z-scores were then averaged for the WAD group. A z-score of ≤−2 indicated a driving failing grade in the simulator. The number of collisions over the five critical events was compared between the WAD and control groups as was reaction time and missed response ratio in identifying the red dots. Seventeen WAD and 26 control subjects commenced the driving assessment. Demographic data were comparable between the groups. All subjects completed the freeway scenario but four withdrew during the residential and eight during the CBD scenario because of motion sickness. All scenarios were completed by 14 WAD and 17 control subjects. Mean z-scores for the SPI over the three scenarios was statistically lower in the WAD group (−0.3 ± 0.3; P < 0.05) but the score was not below the cut-off point for safe driving. There were no differences in the reaction time and missed response ratio in divided attention tasks between the groups (All P > 0.05). Assessment of driving in an advanced driving simulator for approximately 15 min revealed that driving-related performance in chronic WAD was not sufficiently impaired to recommend the need for fitness to drive assessment.

Effects of short-duration and long-duration exercise on lipoprotein(a)

Purpose Most studies that use either a single exercise session, exercise training, or a cross-sectional design have failed to find a relationship between exercise and plasma lipoprotein(a) [Lp(a)] concentrations. However, a few studies investigating the effects of longer and/or more strenuous exercise have shown elevated Lp(a) concentrations, possibly as an acute-phase reactant to muscle damage. Based on the assumption that greater muscle damage would occur with exercise of longer duration, the purpose of the present study was to determine whether exercise of longer duration would increase Lp(a) concentration and creatine kinase. (CK) activity more than exercise of shorter duration. Methods Ten endurance-trained men (mean +/- SD: age, 27 +/- 6 yr; maximal oxygen consumption [(V)over dotO(2max)], 57 +/- 7 mL(.)kg(-1) min(-1)) completed two separate exercise sessions at 70% (V)over dotO(2max). One session required 900 kcal of energy expenditure (60 +/- 6 min), and the other required 1500 kcal (112 +/- 12 min). Fasted blood samples were taken immediately before (0-pre), immediately after (0-post), 1 d after (1-post), and 2 d after (2-post) each exercise session. Results CK activity increased after both exercise sessions (mean +/- SE; 800 kcal: 0-pre 55 +/- 11, 1-post 168 +/- 64 U(.)L(-1.)min(-1); 1500 kcal: 0-pre 51 +/- 5, 1-post 187 +/- 30, 2-post 123 +/- 19 U(.)L(-1.)min(-1); P < 0.05). However, median Lp(a) concentrations were not altered by either exercise session (800 kcal: 0-pre 5.0 mg(.)dL(-1), 0-post 3.2 mg(.)dL(-1), 1-post 4.0 mg(.)dL(-1), 2-post 3.4 mg(.)dL(-1); 1500 kcal: 0-pre 5.8 mg(.)dL(-1), 0-post 4.3 mg(.)dL(-1), 1-post 3.2 mg(.)dL(-1), 2-post 5.3 mg(.)dL(-1)). In addition, no relationship existed between exercise-induced changes in CK activity and Lp(a) concentration (800 kcal: r = -0.26; 1500 kcal: r = -0.02). Conclusion These results suggest that plasma Lp(a) concentration will not increase in response to minor exercise-induced muscle damage in endurance-trained runners.