• Frances P Morrison, Rita Kukafka, and Stephen B Johnson.
• Columbia University, Department of Biomedical Informatics, USA.
• AMIA Annu Symp Proc. 2005 Jan 1: 540-4.

BackgroundHealth messages are crucial to the field of public health in effecting behavior change, but little research is available to assist writers in composing the overall structure of a message. In order to develop software to assist non-expert message writers in constructing effective messages, the structure of existing health messages must be understood, and an appropriate method for analyzing health message structure developed.Methods72 messages from expert sources were used for development of the method, which was then tested for reproducibility using ten randomly selected health messages. Four raters analyzed the messages and inter-coder agreement was calculated.ResultsA method for analyzing the structure of the messages was developed using sublanguage analysis and discourse analysis. Overall kappa between four coders was 0.69, demonstrating "substantial agreement."ConclusionA novel framework for characterizing health message structure and a method for analyzing messages appears to be reproducible.

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