1,556 research outputs found

    Art Appreciation Instruction and Changes of Classroom Questioning at Senior Secondary School in Visual Culture Context

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    This paper discusses art appreciation instruction and the changes of classroom questioning at senior secondary school in visual culture context so as to improve art appreciation instruction and find out the strategy for the further development of art education at senior secondary school based on that at primary and junior secondary schools. It analyzes existing problems including classroom questioning in traditional appreciation education by the method of case analysis. It also makes in-depth discussion on art appreciation instruction and the changes of classroom questioning at senior secondary school in visual culture context

    Beliefs about medicines and non-adherence in patients with stroke, diabetes mellitus and rheumatoid arthritis: a cross-sectional study in China

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    OBJECTIVES: To investigate beliefs about medicines and their association with medicine adherence in patients with chronic diseases in China. DESIGN: A cross-sectional questionnaire-based study SETTING: Two large urban hospitals in Hefei and Tianjin, China PARTICIPANTS: Hospital inpatients (313 stroke patients) and outpatients (315 diabetic patients and 339 rheumatoid arthritis (RA) patients) were recruited between January 2014 and September 2014. OUTCOME MEASURES: The Beliefs about Medicines Questionnaire (BMQ), assessing patients' beliefs about the specific medicine (Specific-Necessity and Specific-Concerns) prescribed for their conditions (stroke/diabetes/RA) and more general background beliefs about pharmaceuticals as a class of treatment (BMQ-General Benefit, Harm and Overuse); the Perceived Sensitivity to Medicines scale (PSM) assessed patients' beliefs about how sensitive they were to the effects of medicines and the Medication Adherence Report Scale. The association between non-adherence and beliefs about medicines was assessed using a logistic regression model. RESULTS: Patients with diabetes mellitus had a stronger perceived need for treatment (mean (SD) Specific-Necessity score, 3.75 (0.40)) than patients with stroke (3.69 (0.53)) and RA (3.66 (0.44)) (p=0.049). Moderate correlations were observed between Specific-Concerns and General-Overuse, General-Harm and PSM (Pearson correlation coefficients, 0.39, 0.49 and 0.49, respectively, p<0.01). Three hundred and eleven patients were non-adherent to their medicine (159 (51.0%) in the stroke group, 60 (26.7%) in the diabetes mellitus group and 62 (19.8%) in the RA group, p<0.01). Across the whole sample, after adjusting for demographic characteristics, non-adherence was associated with patients who had higher concerns about their medicines (OR, 1.35, 95% CI 1.07 to 1.71) and patients who believed that they were personally sensitive to the effects of medications (OR 1.44, 95% CI 1.16 to 1.85). CONCLUSION: The BMQ is a useful tool to identify patients at risk of non-adherence. In the future, adherence intervention studies may use the BMQ to screen for patients who are at risk of non-adherence and to map interventional support

    Approaches to Modelling Heterogeneity in Longitudinal Studies

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    This thesis is about estimation bias of longitudinal data when there is correlation between the explanatory variable and the individual effect. In our study, we firstly introduce what is longitudinal data, then we introduce the commonly used estimation methods for the general linear model: the least squares method and maximum likelihood method. We apply these estimation methods to three simple general models which are commonly used to analyse longitudinal data. Secondly, we use frequentist and Bayesian analysis to explore the estimation bias theoretically and empirically, with an emphasis on the heterogeneity bias. This bias occurs where random effect estimation is used to analyse data with nonzero correlation between explanatory variables and the individual effect. We then empirically compare the estimated value with the true value. In this way, we demonstrate and verify the theoretical formulation which can be used to determine the size of the bias [Mundlak, 1978]. In order to avoid the estimation bias, the fixed effect estimation should be used to get the better solution under nonzero correlation situation. The Hausman test is used to confirm this. However, the bias not only occurs when we use frequentist analysis, but also exist by using the Bayesian estimation of random effect model. Finally, we follow the Mundlak [1978] idea, then define the special Bayesian model which can be used as Hausman test and as a comparable model. We also prove that it is best fit model among the random effect, fixed effect and pooled model if there is correlation between explanatory variables and individual effect. Throughout this thesis, we illustrate this ideas using examples based on real and simulated data
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