50,928 research outputs found
Supporting students at risk
No full textThe term 'at risk' is used broadly within the education sector to describe a range of situations and behaviours that may lead to negative educational and social outcomes for students. We need, however, to be clear in our own thinking about the type of risk that various situations present in order to give effective assistance to students.\ud
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In general, there are two distinct discourses of being at risk applied to school students: firstly, at risk of academic failure includes passive disengagement from schooling and dropping out; secondly, at risk of harm, includes abuse, self-harm and suicide. While the discourses may be discrete, however, there is also considerable overlap at times and resolution may require both environmental and behavioural considerations. Indeed, the consequences of academic failure, such as early school drop-out, may be to place the individual at further risk, jeopardising development as a mentally and physically healthy adult. Failure to complete compulsory schooling, unemployment, unsafe health practices and low self-worth are among the risk factors that may lead to inability to fully develop as an adult (Kelly, 2001).\ud
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In this chapter, we will examine both discourses independently, considering the related behaviours, the attribution of responsibility, and ways in which the situations may be addressed. We will also note systemic similarities in addressing the needs of all at risk students and conclude by examining the characteristics of teachers and classrooms that minimise both academic risk and risk of harm
Bland-Altman plot of estimated glomerular filtration rate using serum creatinine and cystatin-C.
No full textBland-Altman plot of estimated glomerular filtration rate using serum creatinine and cystatin-C.</p
Problematics in young people as researchers: Visions and voices
No full textWhile during the past twenty years working with young people has witnessed the rise of a movement involving young people in the planning and conduct of formal and genuine research activities, the methodology is still under-theorised and under-utilised. In a previous publication (Bland & Atweh, 2003), we discussed some theoretical foundations for the involvement of students in meaningful educational research based on critical theory and its later developments in the writings of Habermas. In this paper, we will discuss in detail the question of “voice‿ arising from collaborative projects with young people. We will refect on our experiences from one specific collaborative project with high school students that has been going on at the Queensland University of Technology for the past 12 years. The first section of the paper will provide the vision behind collaborative research projects with young people, concentrating on those conducted in educational settings. This will be followed by a short description of the Student Action Research for University Access (SARUA) project involving staff of the Faculty of Education and numerous high school students and their teachers in metropolitan Brisbane. The third section will problematise the question of “voice‿ as we struggled with this concept in the planning and conduct of this project
A change of habitus: Working-class students and educational success
No full textFor students from socio-economically disadvantaged backgrounds, the cultures of secondary schools can be alienating and the schooling experience can be traumatic in various ways. For such students to complete senior secondary school and enter university can be considered quite a remarkable success. As the coordinator of a university access program targeting low socio-economic students, I wanted to find out from those who had made a successful transition to university how they dealt with their high school environments. This paper summarises some of the research done with a group of students participating in the access program and takes some of their comments to exemplify their common experiences. Through their anecdotes and insights, a pattern or trajectory emerged which has relevance for discussions of the deterministic nature of habitus. This paper is intended to illustrate the possibility that individual habitus can change through conscious effort but that change may come at a high price
Bland-Altman plots comparing calibration methods.
No full textBland-Altman plots comparing calibration methods. The mean differences are shown as solid lines and 95% limits of agreement are shown as dashed lines. A) Bland-Altman plot comparing differences between internal derived muscle density values and hydroxyapatite (HA) bone phantom derived muscle density values (n = 10 muscle samples). B) Bland-Altman plot comparing differences between the sucrose water phantom derived muscle density values and hydroxyapatite (HA) bone phantom derived muscle density values (n = 10 muscle samples). Internal and sucrose water phantom derived muscle density values are represented in g/cm3. HA phantom derived muscle density values are represented in mgHA/cm3. (TIFF)</p
Bland-Altman plots comparing calibration methods.
No full textBland-Altman plots comparing the differences between internal derived muscle density values and reference sucrose water phantom derived muscle density values (n = 10 muscle samples). Different combinations of regions of interest (ROIs) for the internal calibration method are represented in different colours. The mean differences are shown as solid lines and 95% limits of agreement are shown as dashed lines. A) Bland-Altman plot with all tested internal calibration ROI combinations. B) Bland-Altman plot with two internal calibration ROI combinations (air, adipose; air, blood).</p
Bland-Altman agreement of VO<sub>2</sub> peak in the validation of the reference equation.
No full textBland-Altman agreement of VO2 peak in the validation of the reference equation.</p
HIV status, breastfeeding modality at 5 months and postpartum maternal weight changes over 24 months in rural South Africa
No full textObjective:
To determine the effect of infant feeding practices on postpartum weight change among HIV-infected and -uninfected women in South Africa.<p></p>
Methods:
In a non-randomised intervention cohort study of antiretroviral therapy-naïve women in South Africa, infants were classified as exclusive (EBF), mixed (MF) or non-breastfed (NBF) at each visit. We analysed infant feeding cumulatively from birth to 5 months using 24-hour feeding history (collected weekly for each of the preceding 7 days). Using generalised estimating equation mixed models, allowing for repeated measures, we compared postpartum weight change (kg) from the first maternal postpartum weight within the first 6 weeks (baseline weight) to each subsequent visit through 24 months among 2340 HIV-infected and -uninfected women with live births and at least two postpartum weight measurements.<p></p>
Results:
HIV-infected (−0.2 kg CI: −1.7 to 1.3 kg; P = 0.81) and -uninfected women (−0.5 kg; 95% CI: −2.1 to 1.2 kg; P = 0.58) had marginal non-significant weight loss from baseline to 24 months postpartum. Adjusting for HIV status, socio-demographic, pregnancy-related and infant factors, 5-month feeding modality was not significantly associated with postpartum weight change: weight change by 24 months postpartum, compared to the change in the reference EBF group, was 0.03 kg in NBF (95% CI: −2.5 to +2.5 kg; P = 0.90) and 0.1 kg in MF (95% CI: −3.0 to +3.2 kg; P = 0.78).<p></p>
Conclusion:
HIV-infected and -uninfected women experienced similar weight loss over 24 months. Weight change postpartum was not associated with 5-month breastfeeding modality among HIV-infected and -uninfected women
Bland-Altman plot of the difference in creatinine-based estimated glomerular filtration rate (eGFR<sub>cr</sub>) and cystatin C-based estimated glomerular filtration rate (eGFR<sub>cys</sub>) versus the mean of the two estimates.
No full textBland-Altman plot of the difference in creatinine-based estimated glomerular filtration rate (eGFRcr) and cystatin C-based estimated glomerular filtration rate (eGFRcys) versus the mean of the two estimates.</p
Bland-Altman plots for <i>v</i><sub><i>FH</i></sub> between PC MRI and CFD.
No full texta) Bland-Altman plot for the voxel-wise mean and difference in vFH between PC MRI and CFD for subject 1. b) Analogous plot to a) after down-sampling the data in plane by 3x3 voxels.</p
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