Reducing overestimation in reported mobile phone use associated with epidemiological studies.
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Date
2008-09-11
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Abstract
Case control studies of mobile phones are commonly based on retrospective self reported exposure information which are often characterized as involving substantial uncertainty concerning data validity We assessed the validity of self reported mobile phone use and developed a statistical model to account for the over reporting of exposure We collected information on mobile phone use from 70 volunteers using two sources of data self report in an interview and network operator records We used regression models to obtain bias corrected estimates of exposure A correlation coefficient of 0 71 was obtained between the self reported and the network operators data on average calling time log transformed minutes per month A simple linear regression model where the duration of calls acquired from network operators is explained with the self reported duration fitted the data reasonably well adjusted R 2 0 51 The constant term was 2 71 and the regression coefficient 0 49 logarithmic scale No significant improvement in the model fit was achieved by including potential predictors of accuracy in self reported exposure estimates such as the pattern of mobile phone use the modality of response to the questionnaire or demographic characteristics Overestimation in self reported intensity of mobile phone use can be accounted for by the use of regression calibration The estimates obtained in our study may not be applicable in other contexts but similar methods could be used to reduce bias in other studies