Computer vision syndrome and its relationship with sleep and fatigue in medical students.

Madison Garlock, Miranda Speth, Matthew McEchron

Abstract read

In one paragraph

Article in BMC medical education, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it

0cells of the map it votes in

1citing 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

1 citing paper in PubMed.

Growing challenges in nursing education: prevalence and mediating role of computer vision syndrome in the relationship between visual fatigue and sleep disturbance among nursing students.BMC nursing · 2025
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.

Madison GarlockRocky Vista University, Ivins, UT, 84738, USA. Madison.garlock@ut.rvu.edu.

Miranda SpethRocky Vista University, Ivins, UT, 84738, USA.

Matthew McEchronRocky Vista University, Englewood, CO, 80112, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Previous studies have suggested that medical students may be at considerable risk for Computer Vision Syndrome (CVS), partly because of the increasing amount of online content delivery via computer interface. This study used validated surveys to examine the prevalence of CVS in medical students and its relationship with fatigue and sleep impairments. Survey data showed that 83.1% of medical students exhibited a CVS score of 6 or above, suggesting they suffer from CVS, 57.3% of students scored above five on the Pittsburgh Sleep Quality Index (PSQI), indicating poor sleep quality, and 56.7% scored 36 or higher on the Fatigue Severity Scale (FSS), indicating significant fatigue. Data also showed that the CVS, PSQI, and FSS survey measures were correlated (p < 0.001) with each other. These results suggest that CVS in medical students may be related to poor sleep quality and fatigue.

Indexed as

FatigueSleep Wake DisordersStudents, MedicalAdultFemaleHumansMaleSleep QualitySurveys and QuestionnairesYoung AdultComputer vision syndromeFatigueMedical educationMedical studentsSleep quality

Identifiers

PMID40624501

DOI10.1186/s12909-025-07503-1

PMCPMC12232783

What OpenQuestion holds

Textmetadata

LicenceCC BY-NC-ND

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.