Comparative Measurement of Family Network Systems

Laura Koehly, Christopher Marcum, Jasmine Manalel, Tracy Swan

Contact: koehlyl@mail.nih.gov

The social context of family can have important implications in members’ health and well-being. How we measure that context, however, can change the meaning of those interpersonal processes that impact health. Here, we discuss the varying meaning in different approaches to measuring family systems, particularly in the context of multiple informant designs. While perhaps complicating the analysis, multiple informant designs provide insight into multiple perspectives that comprise family systems and characterize functional and structural features within the family that might be important to members’ health and well-being. We compare network systems derived using three different enumeration processes: the hierarchical mapping technique, an unstructured approach asking participants to enumerate their family, and a structured approach comprising first- and second-degree relatives and ‘other important people’. Our data are drawn from a large corpus of family network systems (N = 733) collected under eight different studies over the last decade. The three study designs result in significantly different average family network sizes (hierarchical ~30, structured, ~38, and unstructured ~18). Our results point to differences by study design with respect to family composition from elicited enumeration (χ2(8) = 8108.0173, p<0.001). Specifically, we find that, as expected, the structured study design, which explicitly instructs participants to enumerate first- and second-degree relatives, yield the highest proportion of biological relatives (73% of composition versus 45% for hierarchical and 68% for unstructured). Study types elicit about equal proportions of non-biological relatives (17% of composition for hierarchical, 22% for structured, and 21% for unstructured). The hierarchical study design elicits the greatest proportion of “other important people” who are not (bio/non-bio) family members (38% of composition), the unstructured design elicits the next largest proportion (12%), while the structured design yields the least (4%). In addition, we consider the value-added in a multiple informant design, identifying potential missed opportunities of a single informant approach and unique structural features that arise using a multiple informant approach.

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