Evidence map›Paper›PMID 38778168›Full record

ArticleScientific reports2024

How different text display patterns affect cybersickness in augmented reality.

Jianing Zhang, Xiaoping Che, Enyao Chang, Chenxin Qu, Xiaofei Di, Haiming Liu, Jingxin Su

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Trial
  2. Trial
  3. Article
  4. 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

7 authors.

Jianing ZhangSchool of Software Engineering, Beijing Jiaotong University, Beijing, China.
Xiaoping CheSchool of Software Engineering, Beijing Jiaotong University, Beijing, China. xpche@bjtu.edu.cn.
Enyao ChangSchool of Software Engineering, Beijing Jiaotong University, Beijing, China.
Chenxin QuSchool of Software Engineering, Beijing Jiaotong University, Beijing, China.
Xiaofei DiSchool of Software Engineering, Beijing Jiaotong University, Beijing, China.
Haiming LiuSchool of Software Engineering, Beijing Jiaotong University, Beijing, China.
Jingxin SuSchool of Software Engineering, Beijing Jiaotong University, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cybersickness remains a pivotal factor that impacts user experience in Augmented Reality (AR). Research probing into the relationship between AR reading tasks and cybersickness, particularly focusing on text display patterns and user characteristics, has been scant. Moreover, the influence of cybersickness on searching ability and the broader spectrum of user experience has not been rigorously tested. Recent investigations have aimed to pinpoint the variables that contribute to cybersickness during AR reading sessions. In one such study, 40 participants underwent a series of controlled experiments with randomized text display patterns, including variations in text speed and text movement modes. Post-experiment, participants completed a questionnaire that helped quantify their experiences and the degree of cybersickness encountered. The data highlighted that satiety, text speed, and text movement mode are significant contributors to cybersickness. When participants experienced higher levels of cybersickness, font color stood out as a particularly influential factor, whereas gender differences seemed to affect the onset of cybersickness more noticeably at lower levels. This study also drew attention to the impact of cybersickness on search ability within AR environments. It was noted that as cybersickness intensity increased, search ability was markedly compromised. In sum, the research underscores the importance of text display patterns and user characteristics, such as past AR experience, in understanding cybersickness and its detrimental effects on user experience and search ability, particularly under conditions of intense cybersickness.

Indexed as

Augmented RealityAdultFemaleHumansMaleReadingSurveys and QuestionnairesUser-Computer InterfaceYoung AdultAR readingAugmented realityCybersickness

Identifiers

PMID38778168
PMCPMC11111777

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.