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Cluster Analysis Identifies Subpopulations for Health Promotion Campaign Design
Author(s) -
Mackert Michael,
Walker Lorraine O.
Publication year - 2011
Publication title -
public health nursing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.471
H-Index - 55
eISSN - 1525-1446
pISSN - 0737-1209
DOI - 10.1111/j.1525-1446.2011.00948.x
Subject(s) - cluster (spacecraft) , psychological intervention , formative assessment , health communication , health promotion , variety (cybernetics) , behavior change communication , process (computing) , promotion (chess) , public health , psychology , medicine , environmental health , computer science , nursing , political science , research methodology , artificial intelligence , population , communication , pedagogy , operating system , politics , law , programming language
While health communication campaigns have been effective in addressing a variety of health concerns, even broadly successful campaigns can miss particular subpopulations. The statistical technique of cluster analysis, which makes it possible to group individuals based on sets of identifying variables, is a statistical method that could prove useful in the design of more effective communication campaigns. This paper illustrates the use of cluster analysis to group women based on their (1) prepregnancy weight, (2) weight gain during pregnancy, and (3) weight retention after giving birth as it relates to the process of targeting subpopulations and developing more effective health communication campaigns and interventions. The implications of cluster analysis, from guiding additional formative research to development of health communication strategies, are discussed.