Evidence map›Paper›PMID 35846467›Full record

ArticleHeliyon2022

Assessing author willingness to enter study information into structured data templates as part of the manuscript submission process: A pilot study.

A Amina Wilkins, Paul Whaley, Amanda S Persad, Ingrid L Druwe, Janice S Lee, Michele M Taylor, Andrew J Shapiro, Natalie Blanton Southard, Courtney Lemeris, Kristina A Thayer

Open access · goldAbstract read
In one paragraph

Article in Heliyon, 2022. 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
1.4field-weighted citation impact, top 18% of its field
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, 5 citations in OpenAlex.

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

10 authors at 3 institutions in 2 countries.

A Amina WilkinsU.S. Environmental Protection Agency (EPA), Center for Public Health and Environmental Assessment (CPHEA), Washington, DC, USA.
Paul WhaleyLancaster Environment Centre, Lancaster University, Lancaster, UK.
Amanda S PersadU.S. Environmental Protection Agency (EPA), Center for Public Health and Environmental Assessment (CPHEA), Washington, DC, USA.
Ingrid L DruweU.S. Environmental Protection Agency (EPA), Center for Public Health and Environmental Assessment (CPHEA), Washington, DC, USA.
Janice S LeeU.S. Environmental Protection Agency (EPA), Center for Public Health and Environmental Assessment (CPHEA), Washington, DC, USA.
Michele M TaylorU.S. Environmental Protection Agency (EPA), Center for Public Health and Environmental Assessment (CPHEA), Washington, DC, USA.
Andrew J ShapiroU.S. Environmental Protection Agency (EPA), Center for Public Health and Environmental Assessment (CPHEA), Washington, DC, USA.
Natalie Blanton SouthardICF International, Fairfax, VA, USA.
Courtney LemerisICF International, Fairfax, VA, USA.
Kristina A ThayerU.S. Environmental Protection Agency (EPA), Center for Public Health and Environmental Assessment (CPHEA), Washington, DC, USA.
Environmental Protection Agency · USICF International (United States) · USJohns Hopkins University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Environmental health and other researchers can benefit from automated or semi-automated summaries of data within published studies as summarizing study methods and results is time and resource intensive. Automated summaries can be designed to identify and extract details of interest pertaining to the study design, population, testing agent/intervention, or outcome (etc.). Much of the data reported across existing publications lack unified structure, standardization and machine-readable formats or may be presented in complex tables which serve as barriers that impede the development of automated data extraction methodologies.As full automation of data extraction seems unlikely soon, encouraging investigators to submit structured summaries of methods and results in standardized formats with meta-data tagging of content may be of value during the publication process. This would produce machine-readable content to facilitate automated data extraction, establish sharable data repositories, help make research data FAIR, and could improve reporting quality. Objectives: A pilot study was conducted to assess the feasibility of asking participants to summarize study methods and results using a structured, web-based data extraction model as a potential workflow that could be implemented during the manuscript submission process. Methods: Eight participants entered study details and data into the Health Assessment Workplace Collaborative (HAWC). Participants were surveyed after the extraction exercise to ascertain 1) whether this extraction exercise will impact their conducting and reporting of future research, 2) the ease of data extraction, including which fields were easiest and relatively more problematic to extract and 3) the amount of time taken to perform data extractions and other related tasks. Investigators then presented participants the potential benefits of providing structured data in the format they were extracting. After this, participants were surveyed about 1) their willingness to provide structured data during the publication process and 2) whether they felt the potential application of structured data entry approaches and their implementation during the journal submission process should continue to be further explored. Conclusions: Routine provision of structured data that summarizes key information from research studies could reduce the amount of effort required for reusing that data in the future, such as in systematic reviews or agency scientific assessments. Our pilot study suggests that directly asking authors to provide that data, via structured templates, may be a viable approach to achieving this: participants were willing to do so, and the overall process was not prohibitively arduous. We also found some support for the hypothesis that use of study templates may have halo benefits in improving the conduct and completeness of reporting of future research. While limitations in the generalizability of our findings mean that the conditions of success of templates cannot be assumed, further research into how such templates might be designed and implemented does seem to have enough chance of success that it ought to be undertaken.

Indexed as

Author feedbackAuthor journal submission requirementsAuthor opinionAuthor willingnessAutomated data extractionData extractionData sharingData summaryData templatesManuscript submissionNatural language Processing (NLP)Science translationStandardized dataStructured dataStudy evaluation templateSystematic review

Identifiers

PMID35846467
PMCPMC9280381
OpenAlexW4220860813

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.