Evidence map›Paper›PMID 27043754›Full record

ReviewJournal of health communication2016

Effects on Text Simplification: Evaluation of Splitting Up Noun Phrases.

Gondy Leroy, David Kauchak, Alan Hogue

Abstract readEvaluation StudyReview
In one paragraph

Review in Journal of health communication, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. A survey of automated methods for biomedical text simplification.Journal of the American Medical Informatics Association : JAMIA · 2022
    Article
  2. 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

3 authors.

Gondy Leroya Management Information Systems Department , University of Arizona , Tucson , Arizona , USA.
David Kauchakb Computer Science Department , Pomona College , Claremont , California , USA.
Alan Hoguec Department of Linguistics , University of Arizona , Tucson , Arizona , USA.

Funding

Evidence-based Strategy and Tool to Simplify Text for Patients and ConsumersR01LM011975 · NLM · UNIVERSITY OF ARIZONA · PI LEROY, GONDY · 2015 to 2024
$2.9M
Large-scale evaluation of text features affecting perceived and actual text diffiR03LM010902 · NLM · UNIVERSITY OF ARIZONA · PI LEROY, GONDY · 2011 to 2012
$131k
NLM NIH HHS R01 LM011975NLM NIH HHS R01LM011975NLM NIH HHS R03 LM010902NLM NIH HHS R03LM010902
6 · The paper itself

Abstract

To help increase health literacy, we are developing a text simplification tool that creates more accessible patient education materials. Tool development is guided by a data-driven feature analysis comparing simple and difficult text. In the present study, we focus on the common advice to split long noun phrases. Our previous corpus analysis showed that easier texts contained shorter noun phrases. Subsequently, we conducted a user study to measure the difficulty of sentences containing noun phrases of different lengths (2-gram, 3-gram, and 4-gram); noun phrases of different conditions (split or not); and, to simulate unknown terms, pseudowords (present or not). We gathered 35 evaluations for 30 sentences in each condition (3 × 2 × 2 conditions) on Amazon's Mechanical Turk (N = 12,600). We conducted a 3-way analysis of variance for perceived and actual difficulty. Splitting noun phrases had a positive effect on perceived difficulty but a negative effect on actual difficulty. The presence of pseudowords increased perceived and actual difficulty. Without pseudowords, longer noun phrases led to increased perceived and actual difficulty. A follow-up study using the phrases (N = 1,350) showed that measuring awkwardness may indicate when to split noun phrases. We conclude that splitting noun phrases benefits perceived difficulty but hurts actual difficulty when the phrasing becomes less natural.

Indexed as

LanguageHealth LiteracyHumansPatient Education as Topic

Identifiers

PMID27043754
PMCPMC4864954

What OpenQuestion holds

Textmetadata
LicenceTDM
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.