Literature DB >> 17004354

Misinterpretation of drinking water quality monitoring data with implications for risk management.

Samantha N Rizak1, Steve E Hrudey.   

Abstract

A survey of two groups of environmental professionals was conducted to explore the degree of understanding in the interpretation of monitoring results for informing decision-making and responding to data appropriately to manage environmental health risks. Specifically, the understanding of the predictive value of a monitoring result and the appreciation that false positive results will inevitably predominate when monitoring for rare or infrequent hazards was explored. Results indicate evidence of misinterpretation and overconfidence in the meaning of monitoring results, and the ability of laboratory methods to detect reliably an infrequent hazard in environmental samples. A hypothetical monitoring scenario was presented with characteristics sufficient to estimate what level of confidence was warranted in a positive result. The majority of respondents in both groups (most of whom had more than 10 years experience in their field) reported between very likely to almost certain confidence (80-100% likelihood) in a hypothetical monitoring result which was, in fact, less than 5% likely to be correct. Additionally, there was little influence of the beliefs expressed about the validity of the monitoring result on the actions proposed to be taken in response to finding that monitoring result. The independence of respondents' follow-up action to what they believe of a monitoring result implies a level of detachment between the understanding of the monitoring data and the resulting risk management response.

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Year:  2006        PMID: 17004354     DOI: 10.1021/es0520417

Source DB:  PubMed          Journal:  Environ Sci Technol        ISSN: 0013-936X            Impact factor:   9.028


  2 in total

1.  How do the Chinese perceive ecological risk in freshwater lakes?

Authors:  Lei Huang; Yuting Han; Ying Zhou; Heinz Gutscher; Jun Bi
Journal:  PLoS One       Date:  2013-05-09       Impact factor: 3.240

2.  Can Public Health Risk Assessment Using Risk Matrices Be Misleading?

Authors:  Shabnam Vatanpour; Steve E Hrudey; Irina Dinu
Journal:  Int J Environ Res Public Health       Date:  2015-08-14       Impact factor: 3.390

  2 in total

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