Evidence map›Paper›PMID 40898221›Full record

ArticleBMC research notes2025

Practical guidance on publishing plain-language summaries for scientific manuscripts with an Asia-Pacific audience.

Blair Hesp, Bert Yu-Hung Chen, Shobana Ganesan, Joyce Hiu Yan Lee, Sharon Wei Ling Lee, Anna Onuma, Shu Wang, Alvin Wei, Julie Yuan, Tim Stentiford

Abstract readLetter
In one paragraph

Article in BMC research notes, 2025. 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
–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

0 citing papers in PubMed.

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.

Blair HespFirst In Human, Kainic Medical Communications Ltd, Dunedin, New Zealand. blairh@kainicmedical.com.
Bert Yu-Hung ChenVercentrys Taiwan, Taipei, Taiwan.
Shobana GanesanCactus Life Sciences Pvt Ltd (part of Cactus Communications), Mumbai, India.
Joyce Hiu Yan LeeNucleus Global, an Inizio Company, Sydney, Australia.
Sharon Wei Ling LeeCostello Medical Singapore Pte Ltd, Singapore, Singapore.
Anna OnumaFirst In Human, Kainic Medical Communications Ltd, Dunedin, New Zealand.
Shu WangLilly Suzhou Pharmaceutical Co. Ltd, Shanghai, China.
Alvin WeiL'Oréal Research and Innovation, Shanghai, China.
Julie YuanJohn Wiley & Sons Singapore Pte Ltd, Singapore, Singapore.
Tim StentifordNucleus Global, an Inizio Company, Sydney, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Plain language summaries (PLSs) of scientific publications are intended to distill full-length scientific publications into a short, inclusive, accessible format that can be rapidly comprehended by all potential readers, but often retain cultural and linguistic barriers to accessibility, particularly for audiences in the Asia-Pacific region (APAC). Various publications have attempted to provide guidance on how to prepare PLSs, but there have been limited attempts to standardize structure or content and there is no universal guidance for PLSs. Furthermore, PLSs pertaining to research in patient populations in APAC, or relating to conditions that are prevalent in APAC, should be developed using language and imagery appropriate for the intended audience. This commentary aims to outline key considerations for preparing a PLS for an APAC audience, including language, imagery, and font selection. Developing culturally-sensitive PLSs for potential readers in APAC may increase the audience for the scientific literature and assist effective engagement in the region.

Indexed as

Guidelines as TopicPlain Language SummariesPublishingAsiaAccessibilityAsia-PacificCommunicationPlain language summary

Identifiers

PMID40898221
PMCPMC12406417

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.