文章基本信息

标题：Predicting neighbourhood-level psychiatric admission rates using multi-level regression with post-stratification-derived estimates of ecological cognitive social capital
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作者：Christopher WN Saville
期刊名称：International Journal of Population Data Science
电子版ISSN：2399-4908
出版年度：2019
卷号：4
期号：3
页码：1-1
DOI：10.23889/ijpds.v4i3.1247
出版社：Swansea University
其他摘要：Background with rationaleEcological cognitive social capital, the aggregated beliefs about community and norms of one’s neighbours, is an important protective factor for mental health. However, the techniques currently used in the literature to estimate it are basic. Multi-level regression with post-stratification (MRP) is a technique for making such small area estimates using survey data, and appears a promising alternative to existing methods. Main AimTo test the predictive validity of MRP-derived estimates of sense of belonging and generalised trust on psychiatric admission rates across Wales. MethodsMRP estimates of two questions measuring social capital, trust and belonging, were created for all middle super output areas in Wales using the National Survey for Wales 2016-17. These estimates were then used to predict rates of psychiatric admission in the same areas during 2017. Estimates of the same two variables were also computed using the simple aggregation approach used elsewhere in the literature, and the predictive validity of the two types of estimate were compared ResultsTrust and belonging were both protective factors, with MRP estimates yielding higher risk ratios (.80 and .77 respectively) than simple aggregation equivalents (.91 and .93). ConclusionMRP appears to be a useful technique for computing estimates of ecological social capital and other self-report based measures, outperforming techniques currently used in the literature in terms of predictive validity.