Psychographic clustering of blood donors in Egypt using Kohonen's self-organizing maps

TLDR: Self-organizing maps are used to examine the effect of various psychographic and cognitive factors on blood donation in Egypt and show that major variables affecting blood donation are related to altruistic values, perceived risks of blood donation, blood donation knowledge, attitudes towardBlood donation, and intention to donate blood.

Abstract: Blood donation has historically been marketed as one of the purest examples of altruistic or pro-social behavior. The recruitment of blood donors is, however, a challenge as transfusion centers worldwide strive to attract and retain blood donors. This study uses self-organizing maps (SOM) to examine the effect of various psychographic and cognitive factors on blood donation in Egypt. SOM is a machine learning method that can be used to explore patterns in large and complex datasets for linear and nonlinear patterns. The results show that major variables affecting blood donation are related to altruistic values, perceived risks of blood donation, blood donation knowledge, attitudes toward blood donation, and intention to donate blood. The study also shows that SOM models are capable of improving clustering quality while extracting valuable information from multidimensional data. Copyright © 2009 John Wiley & Sons, Ltd.