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The study examined factors influencing career decisions using a sample of high school learners in the Eastern Cape Province of South Africa. A mixed-method approach was utilised. In the quantitative phase of the study, a sample of 536 high school learners in South Africa filled out the Career Interest Inventory (Fisher & Stafford, 1999) in understanding factors that influence career decisions. Phase two sought to understand qualitatively how the identified factors from phase one influence the enactment of career decisions using focus groups with 60 learners drawn from the sample in phase one. Results from phase one showed that learners' career decisions were highly influenced by academic experiences and self-efficacy, parents, teachers, and peers, respectively. Learners perceived ethnic-gender expectations and negative social events as having low levels of influence when making career decisions. Female learners are significantly more highly influenced by parents, teachers, academic experiences, and self-efficacy than their male counterparts. Findings also reveal not only the complexity but also the sense-making that occurs when making career decisions. Implications are made based on these findings.

The estimation of unknown quantities from multiple independent yet non-homogeneous samples has garnered increasing attention in various fields over the past decade. This interest is evidenced by the wide range of applications discussed in recent literature. In this study, we propose a preliminary test estimator for the common mean (μ) with unknown and unequal variances. When there exists prior information regarding the population mean with consideration that μ might be equal to the reference value for the population mean, a hypothesis test can be conducted: H 0 : μ = μ 0 versus H 1 : μ ≠ μ 0 . The initial sample is used to test H 0 , and if H 0 is not rejected, we become more confident in using our prior information (after the test) to estimate μ. However, if H 0 is rejected, the prior information is discarded. Our simulations indicate that the proposed preliminary test estimator significantly decreases the mean squared error (MSE) values compared to unbiased estimators such as the Garybill-Deal (GD) estimator, particularly when μ closely aligns with the hypothesized mean ( μ 0 ). Furthermore, our analysis indicates that the proposed test estimator outperforms the existing method, particularly in cases with minimal sample sizes. We advocate for its adoption to improve the accuracy of common mean estimation. Our findings suggest that through careful application to real meta-analyses, the proposed test estimator shows promising potential. [ABSTRACT FROM AUTHOR]

The challenge of combining two unbiased estimators is a common occurrence in applied statistics, with significant implications across diverse fields such as manufacturing quality control, medical research, and the social sciences. Despite the widespread relevance of estimating the common population mean μ , this task is not without its challenges. A particularly intricate issue arises when the variations within populations are unknown or possibly unequal. Conventional approaches, like the two-sample t-test, fall short in addressing this problem as they assume equal variances among the two populations. When there exists prior information regarding population variances (σ i 2 , i = 1 , 2) , with the consideration that σ 1 2 and σ 2 2 might be equal, a hypothesis test can be conducted: H 0 : σ 1 2 = σ 2 2 versus H 1 : σ 1 2 ≠ σ 2 2 . The initial sample is utilized to test H 0 , and if we fail to reject H 0 , we gain confidence in incorporating our prior knowledge (after testing) to estimate the common mean μ. However, if H 0 is rejected, indicating unequal population variances, the prior knowledge is discarded. In such cases, a second sample is obtained to compensate for the loss of prior knowledge. The estimation of the common mean μ is then carried out using either the Graybill–Deal estimator (GDE) or the maximum likelihood estimator (MLE). A noteworthy discovery is that the proposed preliminary testimators, denoted as μ ^ P T 1 and μ ^ P T 2 , exhibit superior performance compared to the widely used unbiased estimators (GDE and MLE). [ABSTRACT FROM AUTHOR]

A new empirical likelihood ratio test for normality based on moment relations is outlined. The proposed test is developed following the works of Shan et al. (2010). Our proposed test is simple and efficient and it is easy to implement in various statistical packages with the computation of the test statistic not requiring ordering of observations. Monte Carlo simulations revealed that the proposed test proved to be superior under asymmetric alternatives considered as well as symmetric alternatives defined on (0,1). Real data examples are given as well as recommendations of future research areas. [ABSTRACT FROM AUTHOR]

The application of goodness-of-fit (GoF) tests in linear regression modeling is a common practice in applied statistical sciences. For instance, in simple linear regression the assumption of normality of residuals is always necessary to test before making any further inferences. The growing popularity of the use of powerful and efficient empirical likelihood ratio (ELR) based GoF tests in checking for departures from normality in various continuous distributions can be of great use in checking for distributional assumptions of residuals in linear models. Motivated by the attractive properties of the ELR based GoF tests the researchers conducted an extensive Type 1 error rate assessment as well as a Monte Carlo power comparison of selected ELR GoF tests with well-known existing tests against symmetric and asymmetric alternative OLS and BLUS residuals. Under the simulated scenarios, all the studied tests have good control of Type I error rates. The Monte Carlo experiments revealed the superiority of the ELR GoF tests under certain alternatives of both the OLS and BLUS residuals. Our findings also demonstrated the superiority of OLS over BLUS residuals when one is testing for normality in simple linear regression models. A real data study further revealed the applicability of the ELR based GoF tests in testing normality of residuals in linear regression models. [ABSTRACT FROM AUTHOR]

Background: Low levels of physical activity in high- to low-income countries, including South Africa, pose a great risk of cardiovascular-related diseases., Aim: This study aimed to assess and compare the physical fitness profile among children., Setting: The study setting comprised rural and urban primary school learners in the Eastern Cape province, South Africa., Methods: A cross-sectional study was adopted utilising a randomly selected sample of boys and girls aged 9-14 years. Physical fitness measures were assessed using the Euro-fit test battery. Some parametric tests were used for mean comparisons of the various anthropometric measurements and physical fitness characteristics across demographics., Results: The sample consisted of 870 primary school learners. The average weight and height of the sample were 39.29 ± 10.34 kg and 144.06 ± 10.81 cm, respectively, with a mean body mass index (BMI) of 18.80 ± 4.11 kg/m 2 . The results showed that boys reported significantly high levels of physical fitness. Sit-ups ( p ≤ 0.001) and VO2 max ( p ≤ 0.001) significantly increase with age, while all the physical fitness measures were significantly higher among rural-based learners., Conclusion: Rural-based learners and boys generally had better physical fitness performance than their peers. The effect of gender and place of residence should be considered when designing physical fitness interventions., Contribution: This study adds to the existing body of knowledge about the effect of demographic factors on the physical fitness profile of children, where boys and rural-based learners are reported to be more physically fit than their counterparts., Competing Interests: The authors declare that they have no financial or personal relationships that may have inappropriately influenced them in writing this article., (© 2024. The Authors.)

Background: The level, direction or presence of the relationship between perceived physical activity (PA) participation and physical fitness (PF) in children may differ by gender and this will assist in designing gender-specific interventions to promote PA participation, which in turn improves PF levels., Aim: This study aimed to establish the moderating effect of gender on the relationship between perceived PA participation and PF., Method: A cross-sectional study was conducted with a cohort of 870 primary school children aged 9-14 years old. Perceived PA participation was measured using the PAQ-C questionnaire while PF levels were measured using cardiorespiratory endurance (i.e. VO2 max)., Results: The results showed significant gender differences for perceived PA participation levels ( t = -3.40, p ≤ 0.001) and PF ( t = -11.59, p ≤ 0.001), with boys reporting higher levels than the girls. Perceived PA participation had a positive, weak and statistically significant correlation with PF ( r = 0.251; p ≤ 0.001). Gender significantly moderates the relationship between perceived PA participation and PF (β 3 = 3.518; 95% confidence interval [CI]: 0.642 to 6.395; p = 0.017)., Conclusion: The moderating effect of gender on the relationship between perceived PA participation and PF highlights the differences in physiology as well as the societal PA associated roles played by boys and girls., Contribution: The study has established that the relationship between perceived PA participation and PF is more pronounced among boys than girls., Competing Interests: The authors declare that they have no financial or personal relationships that may have inappropriately influenced them in writing this article., (© 2024. The Authors.)

Background:  Waist-related measures are commonly used to classify central adiposity and related comorbidities. This classification may be essential among children, as it may identify the risk of future non-communicable diseases., Methods:  A cross-sectional study was conducted in the Eastern Cape province, South Africa, among 459 primary school learners aged 9-14 years. Height, weight and waist circumference (WC) were measured using standardised techniques recommended by World Health Organization (WHO). The anthropometric measurements, including body mass index (BMI), WC, waist-to-hip ratio (WHR) and waist-to-height ratio (WHtR) were computed and evaluated., Results:  Most participants were girls (57.70%) with an average age of 11.20 ± 1.60 years. The average weight was 38.81 kg ± 10.49 kg with an average height of 144.16 (standard deviation [s.d.] = 10.37) cm. The sample had a BMI of 18.41 kg/m2 (s.d. = 3.19). The results showed, on average, WC of 62.10 cm ± 8.12 cm, WHR of 0.82 ± 0.15 and WHtR of 0.44 ± 0.05. Girls reported significantly higher BMI, WC and WHtR. Based on WHtR, the results showed the acceptable ability to classify children according to abdominal obesity, thus identifying their risk for comorbidities., Conclusion:  Overall body fat indicated by BMI and central obesity shown by waist-related anthropometric measures can play a significant role in classifying children in terms of their risk of comorbidities.Contribution: To prevent the risks of metabolic diseases in childhood, it is necessary to detect abdominal obesity early using WC-based anthropometric measurements, especially WHtR, to identify those at risk.

Background: The working conditions in the South African public service, notably its challenging environment, pose significant threats to the physical health of employees. Calls exist in understanding how this can be addressed., Aim: The study investigated the predictors of physical health, accounting for the role of organisational climate and decent work., Setting: The study was conducted in Bisho in the Eastern Cape province of South Africa., Methods: An instrument was administered through a survey using a sample of 289 respondents. Descriptive and inferential statistics were used to test the hypothesised relationships., Results: No significant direct effect existed to show that the sounder an organisational climate, the better the physical health of employees will be (β = -0.014, t = -0.199, p = 0.843, 95% confidence interval [CI] [-0.153 to 0.125]). However, statistically significant evidence existed to show that the more focus on promoting decent work, the better the physical health of employees will be (β = 0.463, p = < 0.001, 95% CI [0.258 to 0.668]). Finally, decent work has a full mediating effect on the relationship between organisational climate and employee physical health (β = 0.105, 95% CI [0.054 to 0.167])., Conclusion: Public service organisations need to pay attention to the role of its climate and decent working conditions in promoting employee physical health., Contribution: Interventions are needed centered on improving decent work and the organisational climate as identified predictors of employee physical health., Competing Interests: The authors declare that they have no financial or personal relationships that may have inappropriately influenced them in writing this article., (© 2024. The Authors.)