Evidence map›Paper›PMID 34824135›Full record

ArticleFamily medicine and community health2021

Developing and testing an automated qualitative assistant (AQUA) to support qualitative analysis.

Robert P Lennon, Robbie Fraleigh, Lauren J Van Scoy, Aparna Keshaviah, Xindi C Hu, Bethany L Snyder, Erin L Miller, William A Calo, Aleksandra E Zgierska, Christopher Griffin

Abstract read
In one paragraph

Article in Family medicine and community health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

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  7. Potential of artificial intelligence in injury prevention research and practice.Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention · 2024
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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

10 authors.

Robert P LennonFamily and Community Medicine, Penn State Health Milton S. Hershey Medical Center, Hershey, Pennsylvania, USA rlennon@pennstatehealth.psu.edu.ORCID 0000-0003-0973-5890
Robbie FraleighApplied Research Laboratory, Pennsylvania State University, University Park, Pennsylvania, USA.
Lauren J Van ScoyInternal Medicine, Penn State Health Milton S. Hershey Medical Center, Hershey, Pennsylvania, USA.
Aparna KeshaviahMathematica Policy Research Inc, Princeton, New Jersey, USA.
Xindi C HuMathematica Policy Research Inc, Princeton, New Jersey, USA.
Bethany L SnyderCenter for Community Health Integration, Case Western Reserve University, Cleveland, Ohio, USA.
Erin L MillerFamily and Community Medicine, Penn State Health Milton S. Hershey Medical Center, Hershey, Pennsylvania, USA.
William A CaloPublic Health Services, Penn State Health Milton S. Hershey Medical Center, Hershey, Pennsylvania, USA.
Aleksandra E ZgierskaFamily and Community Medicine, Penn State Health Milton S. Hershey Medical Center, Hershey, Pennsylvania, USA.
Christopher GriffinApplied Research Laboratory, Pennsylvania State University, University Park, Pennsylvania, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Qualitative research remains underused, in part due to the time and cost of annotating qualitative data (coding). Artificial intelligence (AI) has been suggested as a means to reduce those burdens, and has been used in exploratory studies to reduce the burden of coding. However, methods to date use AI analytical techniques that lack transparency, potentially limiting acceptance of results. We developed an automated

Indexed as

Artificial IntelligenceMachine LearningCluster AnalysisHumansQualitative ResearchReproducibility of Resultsqualitative research

Identifiers

PMID34824135
PMCPMC8627418

What OpenQuestion holds

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LicenceCC BY-NC
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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.