3 research outputs found
Impact of demographic characteristics on architecture students' creativity
No full textArchitecture is a multidisciplinary, multiskilled, multidimensional, and multimedia practice. Designers need to know about many crafts, technologies, and theories and to have the ability to communicate with specialists in many fields. This is also true in the education process for the discipline. Architectural education is not simply vocational education achieved by training. The multifaceted structure of the architectural field leads to the development of a wide spectrum of courses in the architectural curriculum. The distribution and classification of architectural courses in the curriculum, states that the courses in the curriculum of contemporary architectural education institutions can be classified into four categories. In the first category, some courses develop an architectural orientation; second, some courses provide the scientific foundation of architecture; the third category consists of the courses that strengthen the base of architectural design, and expression; and finally, there are the design studio courses that synthesize the concepts of the previous three categories. The design studio is the core of all architecture courses and the most dominant in architectural education. Every design is a problem at the beginning of the design process. Creativity is a fundamental aspect in design problem-solving since the development of new design solutions demands to put into practice creative skills. Creative thinking enables the frame of a problem from unconventional viewpoints. It allows gifted designers to go beyond predictable solutions, and explore innovative ideas. This study focuses on the demographic characteristics of architecture students that impact their creativity. Therefore, the main aim of this research is to determine the effects of differences of demographic variables on creativity and offering solutions. To reach this aim a questionnaire was constituted by researchers and sent to architecture students at Hasan Kalyoncu University during 2020-2021 fall semester via e-mail. The Kaufman Domains of Creativity Scale (K-DOCS) was employed in the current study to measure participants' creativity. Obtained data were analysed statistically using SPSS 22.0 software. © 2022 Author(s)
Social cognitive examination of people diagnosed with multiple sclerosis and healthy subjects
No full textCOVID-19 and mental health in 8 low- and middle-income countries: A prospective cohort study
No full textBackground The Coronavirus Disease 2019 (COVID-19) pandemic and associated mitigation policies created a global economic and health crisis of unprecedented depth and scale, raising the estimated prevalence of depression by more than a quarter in high-income countries. Low- and middle-income countries (LMICs) suffered the negative effects on living standards the most severely. However, the consequences of the pandemic for mental health in LMICs have received less attention. Therefore, this study assesses the association between the COVID-19 crisis and mental health in 8 LMICs. Methods and findings We conducted a prospective cohort study to examine the correlation between the COVID-19 pandemic and mental health in 10 populations from 8 LMICs in Asia, Africa, and South America. The analysis included 21,162 individuals (mean age 38.01 years, 64% female) who were interviewed at least once pre- as well as post-pandemic. The total number of survey waves ranged from 2 to 17 (mean 7.1). Our individual-level primary outcome measure was based on validated screening tools for depression and a weighted index of depression questions, dependent on the sample. Sample-specific estimates and 95% confidence intervals (CIs) for the association between COVID-19 periods and mental health were estimated using linear regressions with individual fixed effects, controlling for independent time trends and seasonal variation in mental health where possible. In addition, a regression discontinuity design was used for the samples with multiple surveys conducted just before and after the onset of the pandemic. We aggregated sample-specific coefficients using a random-effects model, distinguishing between estimates for the short (0 to 4 months) and longer term (4+ months). The random-effects aggregation showed that depression symptoms are associated with a increase by 0.29 standard deviations (SDs) (95% CI [−.47, −.11], p-value = 0.002) in the 4 months following the onset of the pandemic. This change was equivalent to moving from the 50th to the 63rd percentile in our median sample. Although aggregate depression is correlated with a decline to 0.21 SD (95% CI [−0.07, −.34], p-value = 0.003) in the period thereafter, the average recovery of 0.07 SD (95% CI [−0.09, .22], p-value = 0.41) was not statistically significant. The observed trends were consistent across countries and robust to alternative specifications. Two limitations of our study are that not all samples are representative of the national population, and the mental health measures differ across samples. Conclusions Controlling for seasonality, we documented a large, significant, negative association of the pandemic on mental health, especially during the early months of lockdown. The magnitude is comparable (but opposite) to the effects of cash transfers and multifaceted antipoverty programs on mental health in LMICs. Absent policy interventions, the pandemic could be associated with a lasting legacy of depression, particularly in settings with limited mental health support services, such as in many LMICs. We also demonstrated that mental health fluctuates with agricultural crop cycles, deteriorating during “lean”, pre-harvest periods and recovering thereafter. Ignoring such seasonal variations in mental health may lead to unreliable inferences about the association between the pandemic and mental health. Nursena Aksunger and colleagues investigate the association between the COVID-19 pandemic and mental health in eight low- and middle-income countries. Author summary Why was this study done? The worldwide economic and health crises triggered by the Coronavirus Disease 2019 (COVID-19) pandemic have had a significant influence on mental health, with the estimated prevalence of depression having increased by more than 25% in high-income countries. Although the adverse consequences of the pandemic on living standards have been most severe in low- and middle-income countries (LMICs), the consequences of the pandemic for mental health in LMICs have received less attention. What did the researchers do and find? The purpose of this research is to investigate the association between the COVID-19 pandemic and mental health in 8 LMICs in Asia, Africa, and South America. Before and during the pandemic, the mental health of 21,162 individuals (mean age 38.01 years, 64.0% female) was measured using survey data. Our individual-level primary outcome measure was based on validated depression screening instruments and a sample-specific weighted index of depression questions. We found that depression symptoms were associated with a significant increase in the 4 months following the onset of the pandemic (0.29 standard deviations (SDs), 95% confidence interval (CI) [−.47, −.11], p-value = 0.002) and that the average recovery of 0.07 SD was not statistically significant in the subsequent period (95% CI [−0.09, .22], p-value = 0.41). What do these findings mean? We showed a substantial negative correlation between the COVID-19 pandemic and mental health after adjusting for seasonality, suggesting that the pandemic might induce long-term depression, especially in LMICs with poor mental health support facilities. We also provided evidence for seasonal changes in mental health depending on agricultural crop cycle. This seasonality should be considered when examining changes in mental health over time in order to prevent drawing inaccurate conclusions. The observed trends were consistent across countries and robust to alternative analyses, although the study was limited by the fact that not all samples were representative of the national population and the mental health indicators differed among samples
