Objectives: This paper extends further the systematic nature of social and behavioral risk factor surveillance by showing how it becomes a learning system. The authors argue that such a systematic approach will lead to a better informed public health practice and a better understand of key public health concerns such as obesity. Methods: This paper is based on methods developed over some 25 years of experience in designing and operating behavioral risk factor surveillance systems. Measurement issues still remain a key concern and special attention is paid to the role of time as a critical variable in developing a surveillance system. Results: The paper lays out five critical areas for attention if a system is to be considered a learning system. Examples are given from ongoing surveillance systems that have developed a base for a learning system and notes how these are institutionalized. Conclusion: In the ideal case a learning system based on sociobehavioral surveillance is dependent on data being collected continuously with careful attention paid to the analytical challenges of such complex data. This is an ideal systematic approach that has not been realized in most surveillance systems now available.

Institutionalization of social and behavioral risk factor surveillance as a learning system

CAMPOSTRINI, Stefano;
2005

Abstract

Objectives: This paper extends further the systematic nature of social and behavioral risk factor surveillance by showing how it becomes a learning system. The authors argue that such a systematic approach will lead to a better informed public health practice and a better understand of key public health concerns such as obesity. Methods: This paper is based on methods developed over some 25 years of experience in designing and operating behavioral risk factor surveillance systems. Measurement issues still remain a key concern and special attention is paid to the role of time as a critical variable in developing a surveillance system. Results: The paper lays out five critical areas for attention if a system is to be considered a learning system. Examples are given from ongoing surveillance systems that have developed a base for a learning system and notes how these are institutionalized. Conclusion: In the ideal case a learning system based on sociobehavioral surveillance is dependent on data being collected continuously with careful attention paid to the analytical challenges of such complex data. This is an ideal systematic approach that has not been realized in most surveillance systems now available.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/10278/29619
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