Evidence map›Paper›PMID 42354565›Full record

ArticleHealthcare (Basel, Switzerland)2026

Visually Induced Motion Sickness During Smartphone Use in Moving Metro Carriages: Effects of Posture and Viewing Duration-A Randomized Crossover Study.

Yi-Lang Chen, Chun-Yu Chan, Yun-Pei Fan, Tzu-Ting Wei

Abstract read
In one paragraph

Article in Healthcare (Basel, Switzerland), 2026. 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

4 authors.

Yi-Lang ChenDepartment of Industrial Engineering and Management, Ming Chi University of Technology, New Taipei 243303, Taiwan.ORCID 0000-0002-1292-0758
Chun-Yu ChanDepartment of Industrial Engineering and Management, Ming Chi University of Technology, New Taipei 243303, Taiwan.
Yun-Pei FanDepartment of Industrial Engineering and Management, Ming Chi University of Technology, New Taipei 243303, Taiwan.
Tzu-Ting WeiDepartment of Industrial Engineering and Management, Ming Chi University of Technology, New Taipei 243303, Taiwan.

Funding

National Science and Technology Council 113-2221-E-131-029-MY3
6 · The paper itself

Abstract

BACKGROUND/

objectivesSmartphone use during public transit is widespread, yet the combined effects of posture, viewing duration, and sex on visual fatigue and visually induced motion sickness (VIMS) under real commuting conditions remain insufficiently understood. This study examined these factors during smartphone video viewing aboard Taipei MRT carriages.

methodsForty healthy young adults (20 males, 20 females) completed four randomized conditions crossing two postures (sitting, standing) and two viewing durations (15 min, 30 min). Conditions were administered in a randomized order. Critical flicker fusion frequency (CFF), visual fatigue scale (VFS) scores, viewing distance, and VIMSSQ-short change scores were assessed as primary outcomes and analyzed using three-way mixed ANOVA.

resultsViewing duration produced the largest and most consistent effects across all outcomes (η

conclusionsProlonged viewing duration and standing posture are key contributors to smartphone-related visual and motion discomfort in metro environments. Limiting continuous viewing time and preferring a seated posture when using smartphones during commuting are recommended strategies to reduce both visual fatigue and VIMS among healthy young adults; generalizability to broader commuter populations warrants further investigation.

Indexed as

critical flicker fusion frequency (CFF)MRT carriagessmartphone useviewing distancevisual fatigue scale (VFS)visually induced motion sickness

Identifiers

PMID42354565
PMCPMC13300375

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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.