Evidence map›Paper›PMID 41561600›Full record

ArticleFrontiers in psychology2025

Perceived ease of use, perceived enjoyment, and continuance intention as predictors of medical students' well-being in hybrid learning: an extended TAM approach.

Qiumei Wang, Hui Zhan, Yu Liang, Peilong Li, Lin Ai

Abstract read
In one paragraph

Article in Frontiers in psychology, 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.

  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

5 authors.

Qiumei WangYoujiang Medical University for Nationalities, Baise, China.
Hui ZhanPatton College of Education, Ohio University, Athens, OH, United States.
Yu LiangYoujiang Medical University for Nationalities, Baise, China.
Peilong LiYoujiang Medical University for Nationalities, Baise, China.
Lin AiYoujiang Medical University for Nationalities, Baise, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Although hybrid learning has transformed educational environments by enhancing student engagement and learning outcomes, challenges related to medical students' well-being have emerged, particularly with the application of the technology acceptance model (TAM). Methods: To explore how technology-related factors, such as perceived ease of use, perceived enjoyment, and continuance intention, impact medical students' well-being, a set of questionnaires was distributed to 337 randomly selected undergraduate students from three medical universities in Guangxi, China. Results: The results of the partial least squares structural equation modeling (PLS-SEM) indicated that the ease of use and perceived enjoyment of hybrid learning systems had a significant, direct, and positive impact on students' well-being. This impact was also mediated by students' intentions to continue utilizing the system in the learning process. Discussion: Both perceived ease of use and perceived enjoyment significantly influenced students' continuance intention, which positively affected their well-being. Perceived ease of use significantly affects students' well-being, much more than enjoyment, emphasizing the importance of user-friendly interfaces over purely enjoyable features in hybrid learning platforms for medical students. By positioning well-being as a central outcome, this study extends the explanatory power of the TAM beyond acceptance and satisfaction, offering theoretical insights and practical guidance for designing hybrid learning systems that support both academic achievement and psychological health.

Indexed as

continuance intentionhybrid learningmedical educationperceived ease of useperceived enjoymentstudents’ well-being

Identifiers

PMID41561600
PMCPMC12812907

What OpenQuestion holds

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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.