Review Article

Giving Support, Receiving Support, and Social Contact

Co-authors:

L. Brown

Corresponding author:

L. Brown

Abstract:

These results support the hypothesis that giving support accounts for some of the benefits of social contact. However, our findings are based on the use of different measures to operationalize giving and re- ceiving support. That is, the GISO variable measured support that was actually provided to other people (i.e., enacted support), whereas the RISO variable assessed whether others could be depended upon to provide support (i.e., available support).4 Furthermore, it is not clear whether the adverse effect of RISO was due to received support or to the covariation of received support with dependence. In order to con- trol for the difference between the giving and receiving measures, as well as the potentially adverse effect of dependence, we examined the exchange of emotional support between spouses. This domain of sup- port offered virtually identical giving and receiving measures, and in- cluded measures of dependence.


Keywords: Professional Associations, Research Institutes, Academic Departments, Faculty Members, Postdoctoral Researchers

Description:

Table 1 presents a correlation matrix of the focal social-support measures. Receiving and giving were significantly and strongly corre- lated for measures of emotional support exchanged between spouses (r  .58, p  .001), and weakly correlated for measures of instrumen- tal support exchanged with others (r  .09, p  .01).


References:

We examined our hypotheses using the 846 persons for whom mortality data were available. Because this sample included the re- sponses of both members of a couple, we computed the intraclass cor- relation (ICC) for the couple-level effect on mortality. We first created a variable that grouped individual participants by couple (n  423). We next constructed a two-level hierarchical model (Level 1 estimated variation in mortality at the individual-participant level, Level 2 esti- mated variation at the couple level) using RIGLS (restricted iterative generalized least squares) estimation for binomial models (MLwiN ver. 1.1, Multilevel Models Project, Institute of Education, London, 2000). A significant ICC could be interpreted as indicating that the death of one partner was significantly related to an increase or de- crease in the probability of the other partner dying (within the study period). Results of this procedure indicated that there was no couple- level effect on mortality (ICC  .00, n.s.). Thus, for all analyses, we treated each member of a couple as an independent source of data.

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