The purpose of this research was to determine whether adolescents who participate in sport perform better academically in comparison to their non–participating counterparts. An availability sample of 210 learners between 14 and 24 years from a secondary school in the Dr Kenneth Kaunda District took part in this research. The participants were assessed by a Biographical Questionnaire adapted from Mpshe (1996); an adapted version of The Physical Activity Index of Sharkey (1979); the General Scholastic and Aptitude Test (GSAT)(Claassen, De Beer, Hugo & Meyer,1998); The revised two–factor Study Process Questionnaire: R–SPQ–2F of Biggs (1987a, 1987b); The Rosenberg Self–Esteem Scale (RSES), Rosenberg (1965); an adapted version of The Self–concept and Motivation Questionnaire of Bester (2003), and The Psychological Wellbeing (PWB) Scales of Ryff (1989). To obtain an overview of the participants’ academic performance, averages obtained in the June 2010 examinations in the four compulsory learning areas, i.e. Setswana First Language, English First Additional Language, Life Orientation and either Mathematics or Mathematical Literacy, were calculated. A significant relationship between sport participation and academic performance was yielded by a cross–tabulation with a practical significance of 0.09. Univariate regression models with academic performance as dependent variable and the following variables as independent variables were calculated as separate models, namely: IQ, Deep approach and Surface Approach as dimensions of the R–SPQ–2F, Motivation, Self–esteem and Psychological well–being. Only self–esteem was found to significantly predict academic performance. A further analysis using an interaction between sport participation and self–esteem did not yield a significant finding. It was concluded that it is important that Educational planners should take cognisance of the literature and research findings of this study. In future studies bigger samples can be used and the interaction between cognitive, non–cognitive and sociodemographic variables in the prediction of academic performance can be studied. / Thesis (M.A. (Research Psychology))--North-West University, Potchefstroom Campus, 2011.

The purpose of this research was to determine whether adolescents who participate in sport perform better academically in comparison to their non–participating counterparts. An availability sample of 210 learners between 14 and 24 years from a secondary school in the Dr Kenneth Kaunda District took part in this research. The participants were assessed by a Biographical Questionnaire adapted from Mpshe (1996); an adapted version of The Physical Activity Index of Sharkey (1979); the General Scholastic and Aptitude Test (GSAT)(Claassen, De Beer, Hugo & Meyer,1998); The revised two–factor Study Process Questionnaire: R–SPQ–2F of Biggs (1987a, 1987b); The Rosenberg Self–Esteem Scale (RSES), Rosenberg (1965); an adapted version of The Self–concept and Motivation Questionnaire of Bester (2003), and The Psychological Wellbeing (PWB) Scales of Ryff (1989). To obtain an overview of the participants’ academic performance, averages obtained in the June 2010 examinations in the four compulsory learning areas, i.e. Setswana First Language, English First Additional Language, Life Orientation and either Mathematics or Mathematical Literacy, were calculated. A significant relationship between sport participation and academic performance was yielded by a cross–tabulation with a practical significance of 0.09. Univariate regression models with academic performance as dependent variable and the following variables as independent variables were calculated as separate models, namely: IQ, Deep approach and Surface Approach as dimensions of the R–SPQ–2F, Motivation, Self–esteem and Psychological well–being. Only self–esteem was found to significantly predict academic performance. A further analysis using an interaction between sport participation and self–esteem did not yield a significant finding. It was concluded that it is important that Educational planners should take cognisance of the literature and research findings of this study. In future studies bigger samples can be used and the interaction between cognitive, non–cognitive and sociodemographic variables in the prediction of academic performance can be studied. / Thesis (M.A. (Research Psychology))--North-West University, Potchefstroom Campus, 2011.

Physical activity has several advantages for health. The first objective of this research was to determine the relationship between physical activity and selected physical and psychological health components. The physical components include: diabetes risk, obesity, cholesterol and cardiovascular disease. The psychological health components include stress and depression. Secondly, this research aimed to determine the relationship between physical activity and medical costs. Medical costs were divided into pharmaceutical, general practitioners and hospital claims. A total of 9 860 employees of the same financial institution in South Africa, between the ages 18 and 64 (x̄ = 35.3 ± 18.6 years), participated in the study and participation was voluntary. No differentiation was made between race groups. The assessment of selected health risk factors and physical activity was done by using the Health Risk Assessment (HRA) methodology developed by the company, Monitored Health Risk (MHM). Assessment included a physical activity, diabetes risk and cardiovascular risk questionnaire, BMI and random blood glucose measurements, as well as stress and depression scores. The amount of days absent from work in the past six months was also determined by the questionnaire. Participants was categorised in three groups – low, moderate and high physical activity participation. Medical expenditure data was obtained from Monitored Health Risk Management Pty (Ltd). Hospital, pharmaceutical and general practitioners (GP) claims included all costs occurring during a six month period. The majority of the study group showed low physical activity participation (78.27%). The results also showed that both men and women showed an increased risk for diabetes, and high physical activity levels have a practically and statistically significant effect on the reduction of diabetes risk. In this study all the physical activity groups of both males and females showed an increased average body mass index (BMI) and therefore are considered to be an increased risk according to the classification as stipulated by the study perimeters. The average means for cholesterol in all groups are categorised as low risk. No significant differences are seen between the female groups as well as between the different male groups. The men in the study group showed higher cardiovascular risk than women. There are no statistically significant differences between the women’s groups. However, regarding the male groups, the low physically active male group showed significant differences to the high physical active male group. Thus, in this study it appears that the men participating in high levels of physical activity show the lowest risk for cardiovascular disease and therefore appear to be influenced by physical activity. The majority of the study group is shown to be in the high stress category (55.48%). It seems that work issues (82%), financial problems (74%) and family problems (69%) contribute most to the population’s high stress levels and depression experience. The Physical activity index (PAI) in relation to stress only shows practical significance in moderate and high physical women. The PAI and stress-related index reports statistically (p≤0.05; 0.001) significant and practice significant difference within the population. There was also a statistically significant (p≤0.05) relation between stress and physical activity in relation to days absent. Although high levels of stress and low levels of physical activity are present in the population, the relation become statistically significant in relation with depression. The study group was divided into two groups when the medical cost was examined. One group consisted of those individuals who do not use chronic medication and the other group, those individuals that use chronic medication. The majority of the study group (chronic and nonchronic medication use), show low physical activity participation (average of 78.80%). The results show statistically and practically significant differences between the groups that do not use chronic medication and the groups that use chronic medication. The women that use chronic medication show an increase in pharmaceutical costs with an increase in physical activity. However, when investigating the GP cost of women who use chronic medication, there is only a small difference in GP cost in the different physical activity participation categories. The data shows that men have higher pharmaceutical costs than women in all the physical activity categories. The results also indicate that men who use chronic medication, participating in low levels of physical activity do show higher pharmacy and GP costs. Medical cost associated with hospitalisation of those men whose chronic medications show an average higher medical cost (R231.72 versus R672.71). The women who are on chronic medication show about two and a half times higher hospitalisation cost (R253.97 versus R650.82) and the men an almost four times higher cost (R189.34 versus R721.71). No practically significant difference was found between the groups. The women show an increased incidence of low physical activity participation (82.38%), whereas 68.80% of the men show low physical activity participation. Women who use chronic medication and participate in moderate physical activity show lower hospital costs. The women in this study group that use chronic medication and participate in high levels of physical activity show the highest hospital cost. The men’s profile indicates that medical cost due to hospital claims rise with the higher levels of physical activity. / Thesis (PhD (Human Movement Sciences))--North-West University, Potchefstroom Campus, 2013.

Physical activity has several advantages for health. The first objective of this research was to determine the relationship between physical activity and selected physical and psychological health components. The physical components include: diabetes risk, obesity, cholesterol and cardiovascular disease. The psychological health components include stress and depression. Secondly, this research aimed to determine the relationship between physical activity and medical costs. Medical costs were divided into pharmaceutical, general practitioners and hospital claims. A total of 9 860 employees of the same financial institution in South Africa, between the ages 18 and 64 (x̄ = 35.3 ± 18.6 years), participated in the study and participation was voluntary. No differentiation was made between race groups. The assessment of selected health risk factors and physical activity was done by using the Health Risk Assessment (HRA) methodology developed by the company, Monitored Health Risk (MHM). Assessment included a physical activity, diabetes risk and cardiovascular risk questionnaire, BMI and random blood glucose measurements, as well as stress and depression scores. The amount of days absent from work in the past six months was also determined by the questionnaire. Participants was categorised in three groups – low, moderate and high physical activity participation. Medical expenditure data was obtained from Monitored Health Risk Management Pty (Ltd). Hospital, pharmaceutical and general practitioners (GP) claims included all costs occurring during a six month period. The majority of the study group showed low physical activity participation (78.27%). The results also showed that both men and women showed an increased risk for diabetes, and high physical activity levels have a practically and statistically significant effect on the reduction of diabetes risk. In this study all the physical activity groups of both males and females showed an increased average body mass index (BMI) and therefore are considered to be an increased risk according to the classification as stipulated by the study perimeters. The average means for cholesterol in all groups are categorised as low risk. No significant differences are seen between the female groups as well as between the different male groups. The men in the study group showed higher cardiovascular risk than women. There are no statistically significant differences between the women’s groups. However, regarding the male groups, the low physically active male group showed significant differences to the high physical active male group. Thus, in this study it appears that the men participating in high levels of physical activity show the lowest risk for cardiovascular disease and therefore appear to be influenced by physical activity. The majority of the study group is shown to be in the high stress category (55.48%). It seems that work issues (82%), financial problems (74%) and family problems (69%) contribute most to the population’s high stress levels and depression experience. The Physical activity index (PAI) in relation to stress only shows practical significance in moderate and high physical women. The PAI and stress-related index reports statistically (p≤0.05; 0.001) significant and practice significant difference within the population. There was also a statistically significant (p≤0.05) relation between stress and physical activity in relation to days absent. Although high levels of stress and low levels of physical activity are present in the population, the relation become statistically significant in relation with depression. The study group was divided into two groups when the medical cost was examined. One group consisted of those individuals who do not use chronic medication and the other group, those individuals that use chronic medication. The majority of the study group (chronic and nonchronic medication use), show low physical activity participation (average of 78.80%). The results show statistically and practically significant differences between the groups that do not use chronic medication and the groups that use chronic medication. The women that use chronic medication show an increase in pharmaceutical costs with an increase in physical activity. However, when investigating the GP cost of women who use chronic medication, there is only a small difference in GP cost in the different physical activity participation categories. The data shows that men have higher pharmaceutical costs than women in all the physical activity categories. The results also indicate that men who use chronic medication, participating in low levels of physical activity do show higher pharmacy and GP costs. Medical cost associated with hospitalisation of those men whose chronic medications show an average higher medical cost (R231.72 versus R672.71). The women who are on chronic medication show about two and a half times higher hospitalisation cost (R253.97 versus R650.82) and the men an almost four times higher cost (R189.34 versus R721.71). No practically significant difference was found between the groups. The women show an increased incidence of low physical activity participation (82.38%), whereas 68.80% of the men show low physical activity participation. Women who use chronic medication and participate in moderate physical activity show lower hospital costs. The women in this study group that use chronic medication and participate in high levels of physical activity show the highest hospital cost. The men’s profile indicates that medical cost due to hospital claims rise with the higher levels of physical activity. / Thesis (PhD (Human Movement Sciences))--North-West University, Potchefstroom Campus, 2013.