Evidence map›Paper›PMID 27203858›Full record

ArticlePloS one2016

Text Mining of Journal Articles for Sleep Disorder Terminologies.

Calvin Lam, Fu-Chih Lai, Chia-Hui Wang, Mei-Hsin Lai, Nanly Hsu, Min-Huey Chung

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
0.3field-weighted citation impact, top 32% 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

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 19 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. 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

6 authors at 4 institutions in 1 country.

Calvin LamSchool of Nursing, College of Nursing, Taipei Medical University, Taipei, Taiwan.
Fu-Chih LaiSchool of Nursing, College of Nursing, Taipei Medical University, Taipei, Taiwan.
Chia-Hui WangSchool of Nursing, College of Nursing, Taipei Medical University, Taipei, Taiwan.
Mei-Hsin LaiDepartment of Nursing, Hungkuang University, Taichung, Taiwan.
Nanly HsuNursing Department, Yuanpei University, Hsinchu, Taiwan.
Min-Huey ChungSchool of Nursing, College of Nursing, Taipei Medical University, Taipei, Taiwan.
Taipei Medical University · TWHungkuang University · TWNational Yang Ming Chiao Tung University · TWYuanpei University · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveResearch on publication trends in journal articles on sleep disorders (SDs) and the associated methodologies by using text mining has been limited. The present study involved text mining for terms to determine the publication trends in sleep-related journal articles published during 2000-2013 and to identify associations between SD and methodology terms as well as conducting statistical analyses of the text mining findings.

methodsSD and methodology terms were extracted from 3,720 sleep-related journal articles in the PubMed database by using MetaMap. The extracted data set was analyzed using hierarchical cluster analyses and adjusted logistic regression models to investigate publication trends and associations between SD and methodology terms.

resultsMetaMap had a text mining precision, recall, and false positive rate of 0.70, 0.77, and 11.51%, respectively. The most common SD term was breathing-related sleep disorder, whereas narcolepsy was the least common. Cluster analyses showed similar methodology clusters for each SD term, except narcolepsy. The logistic regression models showed an increasing prevalence of insomnia, parasomnia, and other sleep disorders but a decreasing prevalence of breathing-related sleep disorder during 2000-2013. Different SD terms were positively associated with different methodology terms regarding research design terms, measure terms, and analysis terms.

conclusionInsomnia-, parasomnia-, and other sleep disorder-related articles showed an increasing publication trend, whereas those related to breathing-related sleep disorder showed a decreasing trend. Furthermore, experimental studies more commonly focused on hypersomnia and other SDs and less commonly on insomnia, breathing-related sleep disorder, narcolepsy, and parasomnia. Thus, text mining may facilitate the exploration of the publication trends in SDs and the associated methodologies.

Indexed as

Data MiningSleep Wake DisordersCluster AnalysisHumansLogistic ModelsParasomniasPolysomnographySleep Initiation and Maintenance DisordersTerminology as Topic

Identifiers

PMID27203858
PMCPMC4874549
OpenAlexW2398422715

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.