The influence of burden of care and perceived stigma on expressed emotions of relatives of stable persons with schizophrenia in Nigerian semi-urban/urban settings

RESUMO: Schizophrenia’s burden defines experience of family members and is associated with high level of distress. Courtesy stigma, a distress concept, worsens caregivers’ burden of care and impacts on schizophrenia. Expressed emotion (EE), another family variable, impacts on schizophrenia. However, relationship between EE, burden of care and stigma has been little explored in western literature but not in sub-Saharan Africa particularly Nigeria. This study explored the impact of burden of care and courtesy stigma on EE among caregivers of persons with schizophrenia in urban and semi-urban settings in Nigeria. Fifty caregivers each from semi-urban and urban areas completed a socio-demographic schedule, family questionnaire, burden interview schedule and perceived devaluation and discrimination scale. The caregivers had a mean age of 42 (± 15.6) years. Majority were females (57%), married (49%), from Yoruba ethnic group (68%), monogamous family (73%) and Christians (82%). A higher proportion of the whole sample (53%) had tertiary education. Three out of ten were sole caregivers. Seventy three (73%) lived with the person they cared for. The average number of hours spent per week by a caregiver with a person with schizophrenia was 35 hours. The urban sample had significantly higher proportion of carers with high global expressed emotion (72.7%) than the semi-urban sample (27.3%). The odds of a caregiver in an urban setting exhibiting high expressed emotion are 4.202 times higher than the odds of caregiver in a semi-urban setting. Additionally, there was significance difference between the urban and semi-urban caregivers in discrimination dimension. High levels of subjective and objective burden were associated with high levels of critical comments. In conclusion, this study is the first demonstration of urban-semi-urban difference in expressed emotion in an African country and its findings provide further support to hypothesized relationship between components of EE and burden of care.

Analysis of panoramio photo tags in order to extract land use information

In the recent past, hardly anyone could predict this course of GIS development. GIS is moving from desktop to cloud. Web 2.0 enabled people to input data into web. These data are becoming increasingly geolocated. Big amounts of data formed something that is called "Big Data". Scientists still don't know how to deal with it completely. Different Data Mining tools are used for trying to extract some useful information from this Big Data. In our study, we also deal with one part of these data - User Generated Geographic Content (UGGC). The Panoramio initiative allows people to upload photos and describe them with tags. These photos are geolocated, which means that they have exact location on the Earth's surface according to a certain spatial reference system. By using Data Mining tools, we are trying to answer if it is possible to extract land use information from Panoramio photo tags. Also, we tried to answer to what extent this information could be accurate. At the end, we compared different Data Mining methods in order to distinguish which one has the most suited performances for this kind of data, which is text. Our answers are quite encouraging. With more than 70% of accuracy, we proved that extracting land use information is possible to some extent. Also, we found Memory Based Reasoning (MBR) method the most suitable method for this kind of data in all cases.