Community resources and community sentiment: youth in rural Brandenburg, Germany

Abstract

Dramatic social change in East Germany has warranted the need for communities to assist youth in managing new opportunities and risks. Using data from Youth in Rural Brandenburg '96, the relationship between youth ages 15 to 21 and their communities was examined through a model of community sentiment. Incorporated were sociodemographic, life interest, social network and support, community, and community resource variables in explaining community attachment and satisfaction. Of interest were resources of special relevance for youth: employment, housing, leisure, and social support. Descriptive analyses indicated negative evaluations of employment and leisure resources, more positive views of housing and social support, above-average levels of attachment, and ambivalent feelings of satisfaction. Males expressed more favorable attitudes toward employment, leisure, and community satisfaction than did females; no differences were noted by age or income. Structural equation modeling results emphasized the importance of social support and leisure resources in explaining community sentiment. Gender, length of residence, family interest, and social support resources directly influenced community attachment. Gender, organizational memberships, population, social support resources, and leisure resources directly influenced community satisfaction. Leisure and social support resources also allowed for the indirect effects of various social network variables on attachment and satisfaction. In addition, social support resources mediated the negative effects of female gender on attachment and satisfaction, and social support and leisure resources mediated the negative effects of community organizational memberships on satisfaction. The final, best-fitting parsimonious model explained almost half the variance in attachment and three-quarters of the variance in satisfaction. Age, income, family socioeconomic status, regional economic status, employment, and housing resources were not significant predictors in the model.