Professional Role Attitudes and Decision-making in Medication Administration

This is a case study of nurses\u27 attitudes toward professional nurse role factors affecting decision-making in medication administration. This chapter includes an introduction to the problem, a statement of the problem, objectives of the study, the significance of the problem, definitions of terms pertinent to this study, variables and their operational definitions, and a summary statement. The objectives of this study are to examine five selected role attitudes of nurses that may affect the specific decisions involved in floor stock system medication administration procedures. These selected role attitudes are frequency, complexity, importance, discretion, and search intensity. The theoretical and methodological frameworks utilized in this study, as well as the role attitude variables, are based on a previous study done by Hinshaw

Changes in the physical fitness of elite women's rugby union players over a competition season

OBJECTIVE: To investigate changes in the physical fitness characteristics of elite women’s rugby union players over a competitive season. METHODS: Thirty-two elite women’s rugby union players, all members of the South African Rugby Union High Performance Squad, were sub-divided into 2 positional categories of 17 forwards and 15 backs, respectively, and assessed pre-, mid- and post-competition season. Players underwent anthropometric (stature, body mass and sum of 7 skinfolds) and physical performance measurements (vertical jump, 10 m and 40 m sprint, 1 repetition maximum (1RM) bench press and multi-stage shuttle-run test). Analysis. A 2-factor analysis of variance was used to evaluate differences in physical fitness variables between and within playing positions over the competition season (p<0.01). RESULTS: In both groups, no significant changes were detected in the sum of skinfolds, vertical jump height, 1RM bench press and multi-stage shuttle-run test scores throughout the season. However, sprint times (10 m and 40 m) significantly increased and then decreased for both groups between the early (pre- to mid-season) and later phases of the season (mid- to post-season), respectively. CONCLUSION: The results suggest that, for improvement in physical fitness, players need to train at higher loads, especially in the preparatory phase. Thereafter, they must take measures to actively maintain these gains throughout the competitive season. Direct supervision of their conditioning should be encouraged.Department of HE and Training approved lis

COVARIATE-ADJUSTED NONPARAMETRIC ANALYSIS OF MAGNETIC RESONANCE IMAGES USING MARKOV CHAIN MONTE CARLO

Permutation tests are useful for drawing inferences from imaging data because of their flexibility and ability to capture features of the brain that are difficult to capture parametrically. However, most implementations of permutation tests ignore important confounding covariates. To employ covariate control in a nonparametric setting we have developed a Markov chain Monte Carlo (MCMC) algorithm for conditional permutation testing using propensity scores. We present the first use of this methodology for imaging data. Our MCMC algorithm is an extension of algorithms developed to approximate exact conditional probabilities in contingency tables, logit, and log-linear models. An application of our non-parametric method to remove potential bias due to the observed covariates is presented

Results From South Africa’s 2016 Report Card on Physical Activity for Children and Youth

South Africa’s 2016 Report Card on Physical Activity for Children and YouthWe present results of the 2016 Healthy Active Kids South Africa (HAKSA) Report Card on the current status of physical activity (PA) and nutrition in South African youth. The context in which we interpret the findings is that participation in PA is a fundamental human right, along with the right to “attainment of the highest standard of health.” Methods: The HAKSA 2016 Writing Group was comprised of 33 authorities in physical education, exercise science, nutrition, public health, and journalism. The search strategy was based on peer-reviewed manuscripts, dissertations, and ‘gray’ literature. The core PA indicators are Overall Physical Activity Level; Organized Sport Participation; Active and Outdoor Play; Active Transportation; Sedentary Behaviors; Family and Peer Influences; School; Community and the Built Environment; and National Government Policy, Strategies, and Investment. In addition, we reported on Physical Fitness and Motor Proficiency separately. We also reported on nutrition indicators including Overweight and Under-nutrition along with certain key behaviors such as Fruit and Vegetable Intake, and policies and programs including School Nutrition Programs and Tuck Shops. Data were extracted and grades assigned after consensus was reached. Grades were assigned to each indicator ranging from an A, succeeding with a large majority of children and youth (81% to 100%); B, succeeding with well over half of children and youth (61% to 80%); C, succeeding with about half of children and youth (41% to 60%); D, succeeding with less than half but some children and youth (21% to 40%); and F, succeeding with very few children and youth (0% to 20%); INC is inconclusive. Results: Overall PA levels received a C grade, as we are succeeding with more than 50% of children meeting recommendations. Organized Sports Participation also received a C, and Government Policies remain promising, receiving a B. Screen time and sedentary behavior were a major concern. Under- and over-weight were highlighted and, as overweight is on the rise, received a D grade. Conclusion: In particular, issues of food security, obesogenic environments, and access to activity-supportive environments should guide social mobilization downstream and policy upstream. There is an urgent need for practice-based evidence based on evaluation of existing, scaled up interventions.Discovery Health, Johannesburg, South Africa, and the National Research Foundation of South Africa

A BAYESIAN HIERARCHICAL FRAMEWORK FOR SPATIAL MODELING OF fMRI DATA

Functional neuroimaging techniques enable investigations into the neural basis of human cognition, emotions, and behaviors. In practice, applications of functional magnetic resonance imaging (fMRI) have provided novel insights into the neuropathophysiology of major psychiatric,neurological, and substance abuse disorders, as well as into the neural responses to their treatments. Modern activation studies often compare localized task-induced changes in brain activity between experimental groups. One may also extend voxel-level analyses by simultaneously considering the ensemble of voxels constituting an anatomically defined region of interest (ROI) or by considering means or quantiles of the ROI. In this work we present a Bayesian extension of voxel-level analyses that offers several notable benefits. First, it combines whole-brain voxel-by-voxel modeling and ROI analyses within a unified framework. Secondly, an unstructured variance/covariance for regional mean parameters allows for the study of inter-regional functional connectivity, provided enough subjects are available to allow for accurate estimation. Finally, an exchangeable correlation structure within regions allows for the consideration of intra-regional functional connectivity. We perform estimation for our model using Markov Chain Monte Carlo (MCMC) techniques implemented via Gibbs sampling which, despite the high throughput nature of the data, can be executed quickly (less than 30 minutes). We apply our Bayesian hierarchical model to two novel fMRI data sets: one considering inhibitory control in cocaine-dependent men and the second considering verbal memory in subjects at high risk for Alzheimer’s disease. The unifying hierarchical model presented in this manuscript is shown to enhance the interpretation content of these data sets

Profile of coronary heart disease risk factors in first-year university students

There is substantial evidence that coronary heart disease risk factors are present in people of all ages. The extent to which the problem exists in university students in South Africa has not been confirmed in the literature and needs further investigation. The aim of the study was to profile the coronary heart disease risk factors in first year university students who are at moderate risk for coronary heart disease. A quantitative, cross-sectional study design was used wherein 173 first year students aged 18 – 44 years were identified as being at moderate risk for coronary heart disease according to ACSM guidelines. Descriptive statistics were used in the analysis of the data. Among first year students screened for coronary heart disease risk factors, 28.4% of the subjects were found to be at moderate risk. A sedentary lifestyle constituted the most prevalent coronary heart disease risk factor at 31.19%, with smoking (17.97%), obesity (14.24%), family history and dyslipidemia (13.56%), hypertension (9.15%), and impaired fasting glucose (0.34%) also present. The prevalence of multiple coronary heart disease risk factors showed two risk factors to be the most prevalent among the subjects at 45.66%, with three, four, five and six risk factors prevalent at 30.06%, 16.18%, 7.51% and 0.58%, respectively. The majority of first year university students presented with multiple risk factors that place them at moderate risk for coronary heart disease, with physical inactivity constituting the most prevalent risk factor.Department of HE and Training approved lis

Factors influencing participation in physical activity among 11-13 year-old school children in the Western Cape, South Africa

South African adolescents, in general, are physically inactive, and obesity amongst the youth at schools has become an alarming trend. This study aimed to identify the predisposing, reinforcing and enabling factors of physical activity and to determine the strongest predictors of physical activity participation among adolescents in the Western Cape. A cross-sectional, descriptive research design was used based on quantitative research methods. A sample of 348 learners, both male and female aged 11 to 13 years, from grades 4 to 7, were conveniently selected from two primary schools in the Metropole South Education District of the Western Cape. Data collection was conducted using the Children’s Physical Activity Correlates Questionnaire. Descriptive and inferential statistics were used to analyse the data. Pearson correlation and regression analysis were performed to determine the relationship between the variables and to determine the strongest predictors of physical activity, respectively. The results showed that parental influence (r = 0.236, p < 0.01), peer influence (r = 0.012, p < 0.05), perceived physical activity self- efficacy (r = 0.212, p < 0.05) and perceived physical activity competence (r = 0.192, p < 0.05) were all significantly strong predictors of physical activity, with parental influence being the strongest predictor overall. This suggests that adolescents are more likely to participate in physical activity if they receive support from their parents. Parental support includes parents participating with adolescents, attending physical activity team games, buying physical activity equipment, giving permission for after school activities and providing transport to physical activity venues. Parental encouragement for adolescents includes positive reinforcement and continuous encouragement while adolescents are physically active.DHE

POPULATION FUNCTIONAL DATA ANALYSIS OF GROUP ICA-BASED CONNECTIVITY MEASURES FROM fMRI

In this manuscript, we use a two-stage decomposition for the analysis of func- tional magnetic resonance imaging (fMRI). In the first stage, spatial independent component analysis is applied to the group fMRI data to obtain common brain networks (spatial maps) and subject-specific mixing matrices (time courses). In the second stage, functional principal component analysis is utilized to decompose the mixing matrices into population- level eigenvectors and subject-specific loadings. Inference is performed using permutation-based exact conditional logistic regression for matched pairs data. Simulation studies suggest the ability of the decomposition methods to recover population brain networks and the major direction of variation in the mixing matrices. The method is applied to a novel fMRI study of Alzheimer\u27s disease risk under a verbal paired associates task. We found empirical evidence of alternative ICA-based metrics of connectivity in clinically asymptomatic at risk subjects when compared to controls

The "ART" of Linkage: Pre-Treatment Loss to Care after HIV Diagnosis at Two PEPFAR Sites in Durban, South Africa

BACKGROUND. Although loss to follow-up after antiretroviral therapy (ART) initiation is increasingly recognized, little is known about pre-treatment losses to care (PTLC) after an initial positive HIV test. Our objective was to determine PTLC in newly identified HIV-infected individuals in South Africa. METHODOLOGY/PRINCIPAL FINDINGS. We assembled the South African Test, Identify and Link (STIAL) Cohort of persons presenting for HIV testing at two sites offering HIV and CD4 count testing and HIV care in Durban, South Africa. We defined PTLC as failure to have a CD4 count within 8 weeks of HIV diagnosis. We performed multivariate analysis to identify factors associated with PTLC. From November 2006 to May 2007, of 712 persons who underwent HIV testing and received their test result, 454 (64%) were HIV-positive. Of those, 206 (45%) had PTLC. Infected patients were significantly more likely to have PTLC if they lived =10 kilometers from the testing center (RR=1.37; 95% CI: 1.11-1.71), had a history of tuberculosis treatment (RR=1.26; 95% CI: 1.00-1.58), or were referred for testing by a health care provider rather than self-referred (RR=1.61; 95% CI: 1.22-2.13). Patients with one, two or three of these risks for PTLC were 1.88, 2.50 and 3.84 times more likely to have PTLC compared to those with no risk factors. CONCLUSIONS/SIGNIFICANCE. Nearly half of HIV-infected persons at two high prevalence sites in Durban, South Africa, failed to have CD4 counts following HIV diagnosis. These high rates of pre-treatment loss to care highlight the urgent need to improve rates of linkage to HIV care after an initial positive HIV test.US National Institute of Allergy and Infectious Diseases (R01 AI058736, K24 AI062476, K23 AI068458); the Harvard University Center for AIDS Research (P30 AI42851); National Institutes of Health (K24 AR 02123); the Doris Duke Charitable Foundation (Clinical Scientist Development Award); the Harvard University Program on AID