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Consistency and precision of cancer reporting in a multiwave national panel survey

Overview of attention for article published in Population Health Metrics, June 2010
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Title
Consistency and precision of cancer reporting in a multiwave national panel survey
Published in
Population Health Metrics, June 2010
DOI 10.1186/1478-7954-8-20
Pubmed ID
Authors

Anna Zajacova, Jennifer Beam Dowd, Robert F Schoeni, Robert B Wallace

Abstract

Many epidemiological studies rely on self-reported information, the accuracy of which is critical for unbiased estimates of population health. Previously, accuracy has been analyzed by comparing self-reports to other sources, such as cancer registries. Cancer is believed to be a well-reported condition. This paper uses novel panel data to test the consistency of cancer reports for respondents with repeated self-reports. Data come from 978 adults who reported having been diagnosed with cancer in at least one of four waves of the Panel Study of Income Dynamics, 1999-2005. Consistency of cancer occurrence reports and precision of timing of onset were studied as a function of individual and cancer-related characteristics using logistic and ordered logistic models. Almost 30% of respondents gave inconsistent cancer reports, meaning they said they never had cancer after having said they did have cancer in a previous interview; 50% reported the year of diagnosis with a discrepancy of two or more years. More recent cancers were reported with a higher consistency and timing precision; cervical cancer was reported more inaccurately than other cancer types. Demographic and socio-economic factors were only weak predictors of reporting quality. Results suggest that retrospective reports of cancer contain significant measurement error. The errors, however, are fairly random across different social groups, meaning that the results based on the data are not systematically biased by socio-economic factors. Even for health events as salient as cancer, researchers should exercise caution about the presumed accuracy of self-reports, especially if the timing of diagnosis is an important covariate.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Belgium 1 7%
Unknown 13 93%

Demographic breakdown

Readers by professional status Count As %
Student > Doctoral Student 3 21%
Student > Master 3 21%
Student > Ph. D. Student 2 14%
Researcher 1 7%
Professor > Associate Professor 1 7%
Other 1 7%
Unknown 3 21%
Readers by discipline Count As %
Medicine and Dentistry 4 29%
Nursing and Health Professions 2 14%
Social Sciences 2 14%
Computer Science 1 7%
Business, Management and Accounting 1 7%
Other 1 7%
Unknown 3 21%