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Rural schools are a distinctive feature in the autonomous community of Aragon, as state-run rural schools are the main cultural institution in small towns. This research was conducted in four grouped rural schools (hereafter referred to by their Spanish acronym, CRAs) in the province of Teruel in 2017. Our objectives included analising the views of management team members and teachers on educational leadership with a special emphasis on the rural school's differentiating elements. Four CRAs were chosen in the province of Teruel. Three teachers and six members of management teams participated and the study data were collected using a qualitative interview. The content analysis of the interview was conducted using the NVivo program and was organised into two fundamental areas: views of educational leadership and the skills this leadership includes. The general perception of management teams and teachers is positive; they value the effort put into performing the work and understand that both management and CRAs are complex. They also appreciate the management teams' organisation of training and its contents. This analysis suggests a set of conditions that provides a qualitative insight into management possibilities and limitations in the CRA model.

Aim: To analyze the geographical pattern of diabetes mellitus (DM) mortality and its association with socioeconomic factors in 26 Spanish cities.Methods: We conducted an ecological study of DM mortality trends with two cross-sectional cuts (1996-2001; 2002-2007) using census tract (CT) as the unit of analysis. Smoothed standardized mortality rates (sSMR) were calculated using Bayesian models, and a socioeconomic deprivation score was calculated for each CT.Results: In total, 27,757 deaths by DM were recorded, with higher mortality rates observed in men and in the period 1996-2001. For men, a significant association between CT deprivation score and DM mortality was observed in 6 cities in the first study period and in 7 cities in the second period. The highest relative risk was observed in Pamplona (RR, 5.13; 95% credible interval (95%CI), 1.32-15.16). For women, a significant association between CT deprivation score and DM mortality was observed in 13 cities in the first period and 8 in the second. The strongest association was observed in San Sebastián (RR, 3.44; 95%CI, 1.25-7.36). DM mortality remained stable in the majority of cities, although a marked decrease was observed in some cities, including Madrid (RR, 0.67 and 0.64 for men and women, respectively).Conclusions: Our findings demonstrate clear inequalities in DM mortality in Spain. These inequalities remained constant over time are were more marked in women. Detection of high-risk areas is crucial for the implementation of specific interventions. [ABSTRACT FROM AUTHOR]

Background: Procedures for calculating deprivation indices in epidemiologic studies often show some common problems because the spatial dependence between units of analysis and uncertainty of the estimates is not usually accounted for. This work highlights these problems and illustrates how spatial factor Bayesian modeling could alleviate them.Methods: This study applies a cross-sectional ecological design to analyze the census tracts of 3 Spanish cities. To calculate the deprivation index, we used 5 socioeconomic indicators that comprise the deprivation index calculated in the MEDEA project. The deprivation index was estimated by a Bayesian factor analysis using hierarchical models, which takes the spatial dependence of the study units into account. We studied the relationship between this index and the one obtained using principal component analysis. Various analyses were carried out to assess the uncertainty obtained in the index.Results: A high correlation was observed between the index obtained and the non-Bayesian index, but this relationship is not linear and there is disagreement between the methods when the areas are grouped according to quantiles. When the deprivation index is calculated using summary statistics based on the posterior distributions, the uncertainty of the index in each census tract is not taken into account. Failure to take this uncertainty into account may result in misclassification bias in the census tracts when these are grouped according to quantiles of the deprivation index.Conclusions: Not taking uncertainty into account may result in misclassification bias in the census tracts. This bias could interfere in subsequent analyses that include the deprivation index. Our proposal provides another tool for identifying groups with greater deprivation and for improving decision-making for public policy planning. [ABSTRACT FROM AUTHOR]

• Monitoring green infrastructure planning with Foursquare's user-generated content. • Linking green infrastructure elements and Foursquare data for policy design. • Foursquare insights on user perceptions over green infrastructure elements. • Planning green infrastructure considering social preferences and perceptions. • Identifying socially meaningful spaces for improving planning strategies. The design of efficient Green Infrastructure —GI— systems is a key issue to achieve sustainable development city planning goals in the twenty-first century. This study's main contribution is the identification of potential GI elements to better align the environmental, social and economic perspectives in the GI design by including information about the use, activities, preferences and presence of people. To achieve this, user generated content from Location Based Social Network —LBSN— Foursquare is used as a complementary data source. This involved the construction of an interdisciplinary correlation framework, between the Landscape Ecology principles and the GI elements, that included the classification of Foursquare data into grouping types. The classification considered the potential role of Foursquare venues in the GI network. Valencia City in Spain served as an illustrative case study to test the validity of the proposed method. The results suggest that Foursquare can provide a valuable insight on user perceptions of potential GI elements. Moreover, the findings indicate that user generated content from LBSNs like Foursquare can serve as a complementary tool for analysing the dynamics of urban outdoor spaces to assess GI network, thereby facilitating more effective urban planning and contributing to the social sustainability of the city. [ABSTRACT FROM AUTHOR]