Evidence map›Paper›PMID 40855410›Full record

ArticleBMC medical research methodology2025

Survey of practices of handling exposure measurement errors in modern epidemiology: are the best practices in statistics being adopted by epidemiologists?

Anthony James Russell, Montana Kekaimalu Hunter, George Maldonado, Igor Burstyn

Abstract read
In one paragraph

Article in BMC medical research methodology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–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

3 citing papers in PubMed.

  1. Review
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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

4 authors.

Anthony James RussellIntegral Consulting, San Francisco, CA, USA.
Montana Kekaimalu HunterFrank H. Netter MD School of Medicine, Quinnipiac University, North Haven, CT, USA.ORCID 0000-0003-1123-5940
George MaldonadoEnvironmental Health Sciences, School of Public Health, University of Minnesota, Minneapolis, MN, USA.
Igor BurstynEnvironmental and Occupational Health, Dornsife School of Public Health, Drexel University, Philadelphia, PA, USA. ib68@drexel.edu.ORCID 0000-0002-7153-4478

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMeasurement errors in epidemiological studies can impact the validity and reliability of findings. Without proper context, inferences (causal or otherwise) based on these findings may be compromised. The consequences of measurement error are well known, but in practice commonly ignored when interpreting findings in epidemiological research.

methodsWe examined papers published in 2022 in three leading epidemiology journals (International Journal of Epidemiology, Epidemiology, and American Journal of Epidemiology) to assess the occurrence and handling of exposure measurement error (EME). We randomly sampled 64 papers that assessed exposure-outcome relationships. Two authors independently reviewed the selected papers and searched for (a) explicit definition of the exposure in question and how it was measured, (b) an acknowledgment of the possibility of exposure measurement error and (c) statistical investigation of the expected impact or adjustment for EME.

resultsOur review of recent epidemiological studies reveals encouraging progress on the interpretation and adjustment of EME; however, room of improvement still exists. Among our sample of 64 articles, 2 (3.1%) articles reported exposures for which measurement error did not exist, 3 (4.7%) articles lacked a well-defined research question which precluded proper classification, 8 (12.5%) articles ignored EME, 24 (37.5%) reported on EME or discussed EME as a limitation but treated it as "negligible" without investigating further, 14 (21.9%) articles conducted sensitivity analyses to describe the potential effect EME may have on the studies and 8 (12.5%) articles attempted to quantitatively estimate the impact of EME on the reported risk estimate. Further, 8 (12.5%) articles erroneously claimed that EME would bias risk estimates towards the null (2 of which were also included above).

conclusionsModern epidemiological research shows improved handling and interpretation of EME, while some concerns persist. For instance, the epidemiological literature indicates that it is still resistant to adoption of state-of-the-art methods for managing measurement errors. We recommend that the practice of qualitatively discussing the impact of measurement error in exposure in epidemiology be replaced with modern developments in statistics and comprehensively accounted for.

Indexed as

Epidemiologic StudiesEpidemiologistsEpidemiologyBiasData Interpretation, StatisticalEpidemiologic MethodsHumansReproducibility of ResultsSurveys and QuestionnairesBiasEpidemiologic methodsExposureMeasurement error

Identifiers

PMID40855410
PMCPMC12376469

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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.