ArticleJournal of medical systems2012
Engagement in E-learning opportunities: an empirical study on patient education using expectation confirmation theory.
Article in Journal of medical systems, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Theories Informing eHealth Implementation: Systematic Review and Typology Classification.Journal of medical Internet research · 2021Pooled it
- Telerehabilitation of patients with stroke: Initial program theories for successful implementation.PM & R : the journal of injury, function, and rehabilitation · 2025Article
- Predictors of users' adherence to a fully automated digital intervention to manage insomnia complaints.Journal of the American Medical Informatics Association : JAMIA · 2023Article
- Online KidClot education for patients and families initiating warfarin therapy: The eKITE study.Thrombosis research · 2022Article
- Patient Expectations: Searching Websites on How to Apply to Access Medical Records.International journal of environmental research and public health · 2022Article
- Students' satisfaction and continued intention toward e-learning: a theory-based study.Medical education online · 2021Article
- Introducing E-learning in Epidemiology Course for Undergraduate Medical Students at the Faculty of Medicine, University of Belgrade: A Pilot Study.Journal of medical systems · 2015Article
- Assessing the relationship between technology readiness and continuance intention in an E-appointment system: relationship quality as a mediator.Journal of medical systems · 2014Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Medical e-learning technology is widely employed to create an online platform for patients and healthcare providers alike. However, there are few studies that have investigated the reasons why some users reject e-learning technology usage after their initial experience. This study was conducted with the aim to better understand the factors leading to patients' continued usage of e-learning technologies. The theoretical foundation was based on the expectation-confirmation theory (ECT). The questionnaire survey was conducted during a two-month period and covered a total sample of 281 outpatients in a regional-teaching hospital. We found that the intention to continue e-learning usage was significantly related to patients' education level, expectation, perceived performance, confirmation and satisfaction. The use of this ECT model may provide administrators in the healthcare industry insights into the implementation of e-learning technologies. This research also opens up a new direction and enhances the completeness of related researches in the fields of medical informatics and health education.
Indexed as
Identifiers
21104303What OpenQuestion holds
Registered trials
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.