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What's in a name generator? Choosing the right name generators for social network surveys in healthcare quality and safety research
  1. Ronald S Burt1,
  2. David O Meltzer2,
  3. Michael Seid3,
  4. Amy Borgert3,
  5. Jeanette W Chung2,
  6. Richard B Colletti4,
  7. George Dellal3,
  8. Stacy A Kahn5,
  9. Heather C Kaplan6,
  10. Laura E Peterson7,
  11. Peter Margolis3
  1. 1Booth Graduate School of Business, The University of Chicago, Chicago, Illinois, USA
  2. 2Section of Hospital Medicine, University of Chicago, Chicago, Illinois, USA
  3. 3James M. Anderson Center for Health Systems Excellence, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
  4. 4Department of Pediatrics, The University of Vermont College of Medicine, Burlington, Vermont, USA
  5. 5Section of Pediatric Gastroenterology, Department of Pediatrics and the MacLean Center for Clinical Medical Ethics, University of Chicago, Chicago, Illinois, USA
  6. 6Perinatal Institute and Division of Neonatology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
  7. 7Health Care Consultant, Boston, Massachusetts, USA
  1. Correspondence to Dr David O Meltzer, Section of Hospital Medicine, University of Chicago, 5841 South Maryland Avenue, MC 5000, Chicago, IL 60637, USA; dmeltzer{at}medicine.bsd.uchicago.edu

Abstract

Background Interest in the use of social network analysis (SNA) in healthcare research has increased, but there has been little methodological research on how to choose the name generators that are often used to collect primary data on the social connection between individuals for SNA.

Objective We sought to determine a minimum set of name generators sufficient to distinguish the social networks of a target population of physicians active in quality improvement (QI).

Methods We conducted a pilot survey including 8 name generators in a convenience sample of 25 physicians active in QI to characterize their social networks. We used multidimensional scaling to determine what subset of these name generators was needed to distinguish these social networks.

Results We found that some physicians maintain a social network organized around a specific colleague who performed multiple roles while others maintained highly differentiated networks. We found that a set of 5 of the 8 name generators we used was needed to distinguish the networks of these physicians.

Conclusions Beyond methodology for selecting name generators, our findings suggest that QI networks may require 5 or more generators to elicit valid sets of relevant actors and relations in this target population.

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