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Self-Reported Medication Use Validated Through Record Linkage to National Prescribing Data

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Abstract

Objective
Researchers need to be confident about the reliability of epidemiological studies that quantify medication use through self-report. Some evidence suggests that psychiatric medications are systemically under-reported. Modern record linkage enables validation of self-report with national prescribing data as gold standard. Here, we investigated the validity of medication self-report for multiple medication types.
Study Design and Setting
Participants in the Generation Scotland population-based cohort (N=10,244) recruited 2009-11 self-reported regular usage of several commonly prescribed medication classes. This was matched against Scottish NHS prescriptions data using three- and six-month fixed time windows. Potential predictors of discordant self-report, including general intelligence and psychological distress, were studied via multivariate logistic regression.
Results
Antidepressants self-report showed very good agreement (κ=0.85, (95% Confidence Interval (CI) 0.84-0.87)), comparable to antihypertensives (κ=0.90, (0.89-0.91)). Self-report of mood stabilizers showed moderate-poor agreement (κ=0.42 CI 0.33-0.50). Relevant past medical history was the strongest predictor of self-report sensitivity, whereas general intelligence was not predictive.
Conclusion
In this large population-based study, we found self-report validity varied among medication classes, with no simple relationship between psychiatric medication and under-reporting. History of indicated illness predicted more accurate self-report, for both psychiatric and non-psychiatric medications. Although other patient-level factors influenced self-report for some medications, none predicted greater accuracy across all medications studied.

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