Jeanne S. Hurlbert

Network Range and Health

The inclusion of network concepts in the stress-distress model of health represents a major theoretical advance. Most researchers use the dyadic approach of social network analysis to construct network measures of social support. Working from the argument that network structure and social support are conceptually and empirically distinct, we extend the stress-distress model to include measures of network structure (network range) as predictors of exposure to stress, access to social support, and distress. We find that the density, diversity, and size dimensions of network range affect exposure to stress, access to social support, and distress differentially and that, in each case, their effects are gender-specific.

Exploring the determinants of support provision: provider characteristics, personal networks, community contexts, and support following life events.

To explore the determinants of support provision in the natural disaster context, we followed House (1981) and developed a model that specifies how characteristics of the providers, their personal networks, and the community contexts in which they live facilitate or impede their ability to provide support. All three sets of factors affected support provision during Hurricane Andrew, but the pattern of effects differs for the preparation and short-term recovery phases of the hurricane. Age, income, network density, and local economic conditions had significant effects on support provision in the preparation phase. Income did not have a significant effect on short-term recovery support, but religion, house damage, the size and diversity dimensions of network structure, and the local bonds and sentiments dimensions of community attachment did. After comparing the explanatory power of our model in the two phases, we conclude by investigating the implications of this test for understanding the determinants of support provision more generally.

Social Networks, Social Circles, and Job Satisfaction.

This paper tests the proposition that social networks serve as a social resource which affects job satisfaction through the provision of social support. Drawing from the literature on job satisfaction and social support, the author argues that three types of networks are likely to affect job satisfaction: dense networks, social circles composed of co-workers, and kin-centered networks. Data from the 1985 General Social Survey, indicates that co-worker social circles and kin-centered networks positively affect job satisfaction and that certain of these network effects vary by contextual factors.

Occupational Stress, Social Support, and the Buffer Hypothesis

The relationship between occupational stress, social support, and strain was investigated in a series of influential studies in the late 1970s and early 1980s. This continues to provide the most consistent support for the buffer hypothesis in the stress-strain literature. The authors argue that this support is more tenuous than it appears because these studies have theoretical and methodological limitations. When they are corrected, there is, at best, weak support for the buffer hypothesis in this as in other role domains. However, promising developments in the stress-strain model in other role domains can be incorporated into the occupational context.

THE SOCIAL CONTEXT OF MEN'S AND WOMEN'S JOB SEARCH TIES: MEMBERSHIP IN VOLUNTARY ORGANIZATIONS, SOCIAL RESOURCES, AND JOB SEARCH OUTCOMES

We address a neglected issue in the literature on social resources by asking how one aspect of the context of searcher-contact ties, shared membership in voluntary organizations, affects social resources and, through them, job search outcomes. We also ask whether these effects differ by gender. Our results show that using a contact with whom a job searcher shared membership in a fraternal/service organization decreased the probability that the searcher-contact tie was weak, but membership in these organizations and in church and recreational organizations increased the probability that the tie was gender homophilous. Both church and business voluntary organizational contexts had a positive effect on the use of a contact who was significantly older. Finally, for women, we find a negative effect of shared membership in school organizations on the probability that the searcher-contact tie was weak and, for men, a positive effect of business organizational context on the probability that the tie was gender homophilous. We also find that voluntary organizational contexts exert indirect effects on search outcomes through these tie and contact characteristics, but these effects depend not only upon the type of voluntary organizational context and the gender of the searcher, but also upon the type of social resources through which the effects are exerted. We suggest that the structure of voluntary organizations may underlie these effects. In our conclusions, we examine the implications of these analyses for studying this and other tie contexts, for understanding resource-building, and for studying the role of social networks in individual action.

Neighborhood disadvantage, network social capital, and depressive symptoms.

Research on why neighborhood disadvantage matters for health focuses on the capacity of neighborhoods to regulate residents’ behavior through informal social control. The authors extend this research by conducting a multilevel analysis of data from a 1995 telephone survey of 497 residents of 32 neighborhoods in a U.S. city. The authors find that network social capital mediates the contextual effect of neighborhood disadvantage on depressive symptoms and that health effects of network social capital persist when perceived neighborhood disorder, a standard indicator of low informal social control, is controlled for. The findings demonstrate the value of a conceptualization and measurement of network social capital that (1) considers ties that transcend neighborhood boundaries, (2) investigates health benefits of network social capital in the forms of closure and embedded support resources and range and embedded instrumental resources, and (3) uses network data on specific network members with strong and weak ties to respondents.

Social networks, marital status, and well-being

Recent research demonstrates both the role social networks play in well-being through the provision of social support and the connection between marital status and well-being. Research has also demonstrated that networks serve as resources through the provision of instrumental aid. In this paper, we build upon these literatures by asking whether the form and composition of social networks affect well-being and whether these effects vary contextually by marital status. Using multiple indicators of life satisfaction and anomia, we find that social networks do affect both aspects of well-being, and that the effects of network structure on life satisfaction differ across marital status. The pattern of these effects suggests that different structural positions (e.g. marital statuses) produce a need for different types of resources. We find no contextual effects on the relationship between network structure and anomia, however.

Exploring the structural contexts of the support process: social networks, social statuses, social support, and psychological distress

Despite the long-standing interest of sociologists in the impact of social structure on the psychological well-being of individuals, the structural contexts of the support process remain understudied. To begin to fill this gap, some support researchers have used social statuses to tap location in the social structure. Others have analyzed the interpersonal environments in which individuals are embedded by using quasi-network data that describe categories of alters or, less commonly, network data linked to specific alters. We use network data to test models that examine: (1) direct effects of network structure on perceived adequacy of social support; and (2) their direct and indirect effects (through social support) on psychological distress — net of social status effects. Our results suggest that the social network context is more important in the support process than researchers using quasi-network data have concluded.

Social Network Analysis: A Structural Perspective for Family Studies

We review research on egocentric networks to show how network analysis provides both a distinctive perspective and a methodology for studying the family. In this perspective, individuals are influenced by social networks but are also active agents in their creation. We describe such key concepts as density, range, size, homogeneity and homophily. We also consider network stability, affect structure, segmentation and overlap. We discuss a number of methodological issues along with work in selected substantive areas. Finally, we discuss the data resources of network analysis and suggest an agenda for family applications of network concepts and methodology.

Small networks and selectivity bias in the analysis of survey network data

Abstract Selectivity bias is a danger whenever observations are systematically excluded from a data set on the basis of a dependent variable, whether this exclusion is explicit or implicit. If present, the problem has severe consequences for the validity of statistical estimates of effects. The problem is of importance to the analysis of survey network data, since many network measures (such as density) are available only for persons having networks of size two or larger, while others (such as percent kin) are defined only for those having networks of size one or more. Analysts can adjust for selectivity bias by estimating the risk of exclusion (in this case, of having a network of size 0 or 1), and including the modeled risk as a control in substantive equations. Such estimates are presented for the 1985 General Social Survey network data; in the course of this results of Fischer and Phillips on social isolation are replicated. Other ways of guarding against selection bias are also discussed; at a minimum, network size should be included among the set of regressors in analyses of survey network data, as a methodological control if not as a substantive variable.