Evidence map›Paper›PMID 29097340›Full record

ArticleJournal of clinical epidemiology2018

Self-reported medication use validated through record linkage to national prescribing data.

Jonathan D Hafferty, Archie I Campbell, Lauren B Navrady, Mark J Adams, Donald MacIntyre, Stephen M Lawrie, Kristin Nicodemus, David J Porteous, Andrew M McIntosh

Abstract read
In one paragraph

Article in Journal of clinical epidemiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 63 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
63citing papers in PubMed, 3 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

63 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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  18. UnidentifiedJournal of psychopharmacology (Oxford, England) · 2024
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3 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Jonathan D HaffertyDivision of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh EH10 5HF, UK. Electronic address: jonathan.hafferty@ed.ac.uk.
Archie I CampbellGeneration Scotland, Centre for Genomics and Experimental Medicine, Institute for Genetics and Molecular Medicine, Western General Hospital, University of Edinburgh, Edinburgh EH4 2XU, UK.
Lauren B NavradyDivision of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh EH10 5HF, UK.
Mark J AdamsDivision of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh EH10 5HF, UK.
Donald MacIntyreDivision of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh EH10 5HF, UK.
Stephen M LawrieDivision of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh EH10 5HF, UK.
Kristin NicodemusGeneration Scotland, Centre for Genomics and Experimental Medicine, Institute for Genetics and Molecular Medicine, Western General Hospital, University of Edinburgh, Edinburgh EH4 2XU, UK; Institute for Genetics and Molecular Medicine, Western General Hospital, University of Edinburgh1, Edinburgh EH4 2XU, UK.
David J PorteousGeneration Scotland, Centre for Genomics and Experimental Medicine, Institute for Genetics and Molecular Medicine, Western General Hospital, University of Edinburgh, Edinburgh EH4 2XU, UK; Institute for Genetics and Molecular Medicine, Western General Hospital, University of Edinburgh1, Edinburgh EH4 2XU, UK; Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, 7 George Square, EH8 9JZ, UK.
Andrew M McIntoshDivision of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh EH10 5HF, UK; Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, 7 George Square, EH8 9JZ, UK.

Funding

Medical Research Council MR/J000914/1MRF_ C0396Wellcome Trust
6 · The paper itself

Abstract

objectivesResearchers need to be confident about the reliability of epidemiologic 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

settingParticipants in the Generation Scotland population-based cohort (N = 10,244) recruited 2009-2011 self-reported regular usage of several commonly prescribed medication classes. This was matched against Scottish NHS prescriptions data using 3- and 6-month fixed time windows. Potential predictors of discordant self-report, including general intelligence and psychological distress, were studied via multivariable logistic regression.

resultsAntidepressants self-report showed very good agreement (κ = 0.85, [95% confidence interval (CI) 0.84-0.87]), comparable to antihypertensives (κ = 0.90 [CI 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.

conclusionIn 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 nonpsychiatric medications. Although other patient-level factors influenced self-report for some medications, none predicted greater accuracy across all medications studied.

Indexed as

AdultAgedAged, 80 and overAge DistributionAntidepressive AgentsCohort StudiesDatabases, FactualDrug PrescriptionsFemaleHumansLogistic ModelsMaleMental DisordersMiddle AgedPrescription DrugsReproducibility of ResultsAntidepressive AgentsPrescription DrugsAgreementIndicationLinkageMedicinesPharmacoepidemiologySelf-report

Identifiers

PMID29097340
PMCPMC5808931

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.