Evidence map›Paper›PMID 30866000›Full record

ArticleApplied clinical informatics2019

Common Laboratory Results Frequently Misunderstood by a Sample of Mechanical Turk Users.

Nabeel Qureshi, Ateev Mehrotra, Robert S Rudin, Shira H Fischer

Abstract read
In one paragraph

Article in Applied clinical informatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Nabeel QureshiRAND Corporation, Santa Monica, California, United States.
Ateev MehrotraRAND Corporation, Boston, Massachusetts, United States.
Robert S RudinRAND Corporation, Boston, Massachusetts, United States.
Shira H FischerRAND Corporation, Boston, Massachusetts, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesMore patients are receiving their test results via patient portals. Given test results are written using medical jargon, there has been concern that patients may misinterpret these results. Using sample colonoscopy and Pap smear results, our objective was to assess how frequently people can identify the correct diagnosis and when a patient should follow up with a provider.

methodsWe used Mechanical Turk-a crowdsourcing tool run by Amazon that enables easy and fast gathering of users to perform tasks like answering questions or identifying objects-to survey individuals who were shown six sample test results (three colonoscopy, three Pap smear) ranging in complexity. For each case, respondents answered multiple choice questions on the correct diagnosis and recommended return time.

resultsAmong the three colonoscopy cases (

conclusionPeople frequently misinterpret colonoscopy and Pap smear test results. Greater emphasis needs to be placed on assisting patients in interpretation.

Indexed as

Clinical Laboratory TechniquesCrowdsourcingAdolescentAdultColonoscopyDiagnostic Tests, RoutineFemaleHumansMalePapanicolaou TestYoung Adult

Identifiers

PMID30866000
PMCPMC6415984

What OpenQuestion holds

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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.