Evidence map›Paper›PMID 40269743›Full record

ArticleBMC ophthalmology2025

Students' association of poor eye-use behavior with myopia: focus on study phase.

Tingting Li, Feng Yang, Xiaoling Liu, Caiyun Cao, Peng Ding, Shaojun Xu, Shuman Tao, Xiaoyan Wu, Fangbiao Tao

Abstract readMulticenter Study
In one paragraph

Article in BMC ophthalmology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. The application of artificial intelligence in myopia prediction for children and adolescents: a review.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2026
    Review
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

9 authors.

Tingting LiDepartment of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, No 81 Meishan Road, Hefei, 230032, Anhui, China.
Feng YangDepartment of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, No 81 Meishan Road, Hefei, 230032, Anhui, China.
Xiaoling LiuDepartment of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, No 81 Meishan Road, Hefei, 230032, Anhui, China.
Caiyun CaoDepartment of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, No 81 Meishan Road, Hefei, 230032, Anhui, China.
Peng DingMOE Key Laboratory of Population Health Across Life Cycle, No 81 Meishan Road, Hefei, 230032, Anhui, China.
Shaojun XuDepartment of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, No 81 Meishan Road, Hefei, 230032, Anhui, China.
Shuman TaoMOE Key Laboratory of Population Health Across Life Cycle, No 81 Meishan Road, Hefei, 230032, Anhui, China.
Xiaoyan WuDepartment of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, No 81 Meishan Road, Hefei, 230032, Anhui, China.
Fangbiao TaoDepartment of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, No 81 Meishan Road, Hefei, 230032, Anhui, China. taofangbiao@126.com.

Funding

National Key Research and Development Program of China 2021YFC2702100, 2021YFC2702105National Natural Science Foundation of China 82273653
6 · The paper itself

Abstract

backgroundTo investigate the prevalence of poor eye-use behavior and myopia in Chinese students, and examine the associations of poor eye-use behavior with myopia, as well as its study phase differences.

methodsFrom March to July 2023, a total of 67 910 students were selected from 56 schools in 14 cities of China by stratified cluster sampling. The Eye-use Behavior Evaluation Scale for Students (EBESS) was adopted to investigate the eye-use behavior of students. Students underwent an uncorrected visual acuity examination and a non-cycloplegic autorefraction examination. The chi-square test was used to compare the prevalence of myopia between different groups. The binary logistic regression model was conducted to analyze the association of poor eye-use behavior with myopia.

resultsThe prevalence of poor eye-use behavior and myopia of students were 27.6% and 53.0%, respectively. The poorer the eye-use behavior of students, the higher the prevalence of myopia (P < 0.001). After adjusting for age, gender, sibling, parental myopia, parental education level, self-reported learning burden, mode of travel to school, physical education lesson, city, usage distance of mobile phone / iPad / game console, reading and writing distance, weekdays outdoor time, and weekends outdoor time, binary logistic regression model analysis results showed that the poor eye-use behavior was positively correlated with myopia (OR = 1.10, 95% CI: 1.03 ~ 1.19). According to the study phase and further stratified analysis, in primary school (OR = 1.35, 95% CI: 1.20 ~ 1.50) and senior high school students (OR = 1.28, 95% CI: 1.08 ~ 1.51), poor eye-use behavior was positively correlated with myopia. However, in kindergarten and junior high school students, there was no statistically significant difference (P > 0.05).

conclusionPoor eye-use behavior was a potential risk factor for myopia in students, and this effect was significantly different between study phases. This suggests that future research should establish interventions to protect students from the effects of poor eye-use behavior.

Indexed as

MyopiaRefraction, OcularStudentsAdolescentChildChinaCross-Sectional StudiesFemaleHumansMalePrevalenceRisk FactorsVisual AcuityEye-use behaviorMyopiaStudy phase

Identifiers

PMID40269743
PMCPMC12016136

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.