Evidence map›Paper›PMID 42005029›Full record

ArticleFrontiers in psychology2026

How does artificial intelligence improve ophthalmology education outcomes?-The mediating role of learning motivation and self-efficacy.

Xia Wang, Siyan Jin, Ping Hu, Hai Jiang

Abstract read
In one paragraph

Article in Frontiers in psychology, 2026. 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.

  1. 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

4 authors.

Xia WangOphthalmologic Center of the Second Hospital, Jilin University, Changchun, China.
Siyan JinOphthalmologic Center of the Second Hospital, Jilin University, Changchun, China.
Ping HuOphthalmologic Center of the Second Hospital, Jilin University, Changchun, China.
Hai JiangOphthalmologic Center of the Second Hospital, Jilin University, Changchun, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Artificial intelligence (AI) is increasingly being applied in medical education, yet evidence on how it translates into achievement it is most effective remains limited in ophthalmology. Methods: This cross-sectional study examined undergraduate ophthalmology students at a university in Jilin Province, China. A total of 416 students were randomly selected at two time points-November 2024 and March 2025-corresponding to the autumn 2024 and spring 2025 course cohorts, respectively. Survey measures captured AI usage, learning motivation, self-efficacy, final examination scores, and AI literacy. A moderated parallel mediation model was tested using structural equation modeling. Results: AI usage was positively associated with academic performance ( Conclusion: AI usage is associated with higher ophthalmology academic performance partly through increased learning motivation and self-efficacy, and AI literacy strengthened the AI usage in the learning motivation path. Given the cross-sectional design, longitudinal validation is warranted.

Indexed as

artificial intelligenceartificial intelligence literacylearning motivationophthalmology studentself-efficacy

Identifiers

PMID42005029
PMCPMC13082947

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.