Assessing social support networks in cross-national comparative surveys: Measurement issues

Assessing social support networks in cross-national comparative surveys: Measurement issues In recent years many cross-national comparative surveys, such as Gender and Generation Programme, International Social Survey Programme, European Quality of Life Survey, or General Social Survey, have included assessment of social support networks. Generally, two approaches were used; the name generator approach and the role relation approach. As more cross-country surveys are conducted every year, it may seem reasonable to use such data sets, since they provide high quality comparisons across countries. However, one should pay close attention to the measurement instruments, as these may cause unintentional but systematic variability in the observed data. While the data from each survey can be of high quality “per se”, we claim that results from these surveys are not comparable, owing to their different measurement approaches and survey instruments. In this paper we present data from several experiments which show that scientific findings from these surveys depend significantly on questionnaire design. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Quality & Quantity Springer Journals

Assessing social support networks in cross-national comparative surveys: Measurement issues

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Publisher
Springer Netherlands
Copyright
Copyright © 2011 by Springer Science+Business Media B.V.
Subject
Social Sciences; Methodology of the Social Sciences; Social Sciences, general
ISSN
0033-5177
eISSN
1573-7845
D.O.I.
10.1007/s11135-011-9456-7
Publisher site
See Article on Publisher Site

Abstract

In recent years many cross-national comparative surveys, such as Gender and Generation Programme, International Social Survey Programme, European Quality of Life Survey, or General Social Survey, have included assessment of social support networks. Generally, two approaches were used; the name generator approach and the role relation approach. As more cross-country surveys are conducted every year, it may seem reasonable to use such data sets, since they provide high quality comparisons across countries. However, one should pay close attention to the measurement instruments, as these may cause unintentional but systematic variability in the observed data. While the data from each survey can be of high quality “per se”, we claim that results from these surveys are not comparable, owing to their different measurement approaches and survey instruments. In this paper we present data from several experiments which show that scientific findings from these surveys depend significantly on questionnaire design.

Journal

Quality & QuantitySpringer Journals

Published: Mar 6, 2011

References

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