Evidence map›Paper›PMID 30794206›Full record

ArticleJournal of medical Internet research2019

QuikLitE, a Framework for Quick Literacy Evaluation in Medicine: Development and Validation.

Jiaping Zheng, Hong Yu

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

2 authors.

Jiaping ZhengCollege of Information and Computer Sciences, University of Massachusetts Amherst, Amherst, MA, United States.ORCID 0000-0001-7662-810X
Hong YuDepartment of Computer Science, University of Massachusetts Lowell, Lowell, MA, United States.ORCID 0000-0001-9263-5035

Funding

Resource Curation and Evaluation for EHR Note ComprehensionR01LM012817 · NLM · UNIVERSITY OF MASSACHUSETTS LOWELL · PI YU, HONG · 2018 to 2020
$1.0M
NLM NIH HHS R01 LM012817
6 · The paper itself

Abstract

backgroundA plethora of health literacy instruments was developed over the decades. They usually start with experts curating passages of text or word lists, followed by psychometric validation and revision based on test results obtained from a sample population. This process is costly and it is difficult to customize for new usage scenarios.

objectiveThis study aimed to develop and evaluate a framework for dynamically creating test instruments that can provide a focused assessment of patients' health literacy.

methodsA health literacy framework and scoring method were extended from the vocabulary knowledge test to accommodate a wide range of item difficulties and various degrees of uncertainty in the participant's answer. Web-based tests from Amazon Mechanical Turk users were used to assess reliability and validity.

resultsParallel forms of our tests showed high reliability (correlation=.78; 95% CI 0.69-0.85). Validity measured as correlation with an electronic health record comprehension instrument was higher (.47-.61 among 3 groups) than 2 existing tools (Short Assessment of Health Literacy-English, .38-.43; Short Test of Functional Health Literacy in Adults, .34-.46). Our framework is able to distinguish higher literacy levels that are often not measured by other instruments. It is also flexible, allowing customizations to the test the designer's focus on a particular interest in a subject matter or domain. The framework is among the fastest health literacy instrument to administer.

conclusionsWe proposed a valid and highly reliable framework to dynamically create health literacy instruments, alleviating the need to repeat a time-consuming process when a new use scenario arises. This framework can be customized to a specific need on demand and can measure skills beyond the basic level.

Indexed as

AdultFemaleHealth LiteracyHumansMaleMiddle AgedPsychometricsReproducibility of Resultscrowdsourcinghealth literacypsychometrics

Identifiers

PMID30794206
PMCPMC6406229

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LicenceCC BY
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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.