Quality of Life in Italian Official Surveys

Quality-of-life studies have a 50-year history and inherited the tradition of the “social indicators” movement, born in the United States during the sixties and involving scholars and researchers, supported by the public administration and interested in gathering and analysing data aimed at studying non-economic components of societal wellbeing. The idea of quantifying “symptoms” (indicators) of living conditions has been launched by Italian statistician and criminologist, Alfredo Niceforo, who has been recognised as the pioneer of social-indicators concept. Moreover, with his book on Les indices numérique de la civilisation et du progrès, he may be considered the originator of an approach of comprehensive welfare and quality of life measurement as it is the concern of modern social indicators and quality of life.     

Validation of the Australian Midwifery Standards Assessment Tool (AMSAT): A tool to assess midwifery competence

Background

There is no current validated clinical assessment tool to measure the attainment of midwifery student competence in the midwifery practice setting. The lack of a valid assessment tool has led to a proliferation of tools and inconsistency in assessment of, and feedback on student learning.

The Social Bases of Rural‐Urban Political Divides: Social Status,Work, and Sociocultural Beliefs

The rural‐urban political divide has sparked media and social science concern. Yet national studies of rural and urban voters have largely failed to draw from the distinct conceptual literatures produced by rural sociologists. We take a new look at individuals’ voting choices, building from two rural sociological literatures, research on spatial inequality and on the rural‐urban continuum, to identify the social bases anteceding Republican voting in presidential elections. We analyze three social bases along which rural‐urban populations vary: social structural statuses, work and employment, and sociocultural values and beliefs. We question the degree to which rural‐urban differences can be accounted for by these factors. Data are from approximately 9,000 respondents to the General Social Surveys for election years 2000–2012. Our findings demonstrate that the literatures produced by rural sociologists provide a strong conceptual foundation for explaining rural‐urban voting differences. Rural and urban residents’ differential social statuses account for the greatest variation in their voting choices. Sociocultural values and beliefs, particularly attitudes toward domestic social issues, are also important. Findings add significant insight into the variety of factors that differentiate rural‐urban individuals’ voting choices as well as illuminate the need for greater emphasis on exurban voters.     

A Sociology of the Periphery Versus a Peripheral Sociology: Rural Sociology and the Dimension of Space1

Abstract Rural sociology is intrinsically concerned with the spatial dimensions of social life. However, this underlying research tradition, particularly the use of space as a research strategy, has been insufficiently addressed and its contributions to general sociology are little recognized. I outline how concern with space, uneven development, and the social relationships of peripheral settings have provided substantive boundary and conceptual meaning to rural sociology, propelled its evolution, and left it with a legacy of strengths, weaknesses, and challenges. A willingness to tackle the dimension of space and the thorny problems it raises often sets rural sociologists apart from other sociologists. This research tradition contrasted with general sociology's concern with developing generalization, aspatial covering laws, and proto-typical relationships of modern or Fordist development settings. Conceptual openings have left sociologists questioning their past agenda. Coupled with the “creative marginality” inherent in the questions and contexts addressed by rural sociologists, this makes the subfield central to contemporary sociology.     

Creating a reference to a complex emergency situation using time series methods: war in Guinea-Bissau 1998-1999

Impacts of complex emergencies or relief interventions have often been evaluated by absolute mortality compared to international standardized mortality rates. A better evaluation would be to compare with local baseline mortality of the affected populations. A projection of population-based survival data into time of emergency or intervention based on information from before the emergency may create a local baseline reference. We find a log-transformed Gaussian time series model where standard errors of the estimated rates are included in the variance to have the best forecasting capacity. However, if time-at-risk during the forecasted period is known then forecasting might be done using a Poisson time series model with overdispersion. Whatever, the standard error of the estimated rates must be included in the variance of the model either in an additive form in a Gaussian model or in a multiplicative form by overdispersion in a Poisson model. Data on which the forecasting is based must be modelled carefully concerning not only calendar-time trends but also periods with excessive frequency of events (epidemics) and seasonal variations to eliminate residual autocorrelation and to make a proper reference for comparison, reflecting changes over time during the emergency. Hence, when modelled properly it is possible to predict a reference to an emergency-affected population based on local conditions. We predicted childhood mortality during the war in Guinea-Bissau 1998-1999. We found an increased mortality in the first half-year of the war and a mortality corresponding to the expected one in the last half-year of the war.     

Effects of Medicaid managed care policies on mental health service use among a national probability sample of children in the child welfare system

Children in the child welfare system are dependent upon Medicaid to finance services for their considerable mental health needs. This study examines the effects of Medicaid policies on mental health service use among a national probability sample of children in the child welfare system. Data for this study came from the National Survey of Child and Adolescent Well-Being, the Caring for Children in Child Welfare study, and the Area Resource File. Weighted multivariate logistic regression analyses were conducted to estimate effects of policy variables on children's use of mental health services, controlling for child-level covariates and county-level health resources. Children in counties with behavioral carve-outs under Medicaid managed care had lower odds of inpatient mental health service use. Medicaid managed care enrollment and variations in type of provider reimbursement did not affect use of mental health services. Older age, greater need for mental health services, and higher levels of caregiver education were associated with increased odds of service use. Restrictions on use of inpatient mental healthcare caused by behavioral carve-outs may disproportionately affect children in the child welfare system who have high rates of such use. Careful adoption of carve-outs is necessary to assure appropriate care for these children.