Evidence map›Paper›PMID 40442687›Full record

ArticleBMC health services research2025

Determining the relationship between e-health literacy and personal health system and patient satisfaction using structural equation model: an example of a training and research hospital.

Mehmet Koca, Feyza İnceoğlu, Serdar Deniz

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Article in BMC health services research, 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

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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.

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4 · The record

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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.

Mehmet KocaFaculty of Health Sciences, Malatya Turgut Özal University, Malatya, Türkiye. mehmet.koca@ozal.edu.tr.ORCID http://orcid.org/0000-0002-9505-6677
Feyza İnceoğluFaculty of Medicine, Malatya Turgut Özal University, Malatya, Türkiye.ORCID http://orcid.org/0000-0003-1453-0937
Serdar DenizFaculty of Medicine, Malatya Turgut Özal University, Malatya, Türkiye.ORCID http://orcid.org/0000-0002-6941-4813

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn the current technology landscape, several individuals electronically stores their health information. The personal health system offers significant conveniences to users, hence enhancing patient satisfaction. Assessing the impact of e-health literacy, personal health system, and patient happiness on enhancing patient satisfaction an essential outcome of health services is crucial for system improvement and clarity. This study sought to assess the impact of patients’ e-health literacy levels, evaluated at a training and research hospital, on personal health systems and patient satisfaction.

methodsThe research was carried out in a teaching and research hospital associated with the Ministry of Health in Malatya province from March 15, 2024, until April 25, 2024. The research was executed with data from 275 people. The data collection form consists of 4 sections.

resultsIn the present study, 275 people participated, and 57.8% of them were women. 3.69 were the mean score for the personal health system utilization perception, 92.64 was the mean score for the outpatient satisfaction scale, and 3.63 were the mean score for the e-health literacy scale. E-health literacy explained 2% (R2 = 0.02) of outpatient satisfaction and e-health literacy and outpatient satisfaction explained 30% (R2 = 0.30) of the perception of personal health system use.

conclusionOutpatient satisfaction influences individuals’ perceptions of their health system, e-health literacy affects outpatient satisfaction, and outpatient satisfaction serves as a mediator between e-health literacy and personal health system perspectives.

Indexed as

Health LiteracyPatient SatisfactionAdultAgedDigital HealthFemaleHumansMaleMiddle AgedSurveys and QuestionnairesYoung AdultE-health literacyPatient satisfactionPersonal health system

Identifiers

PMID40442687
PMCPMC12124073

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LicenceCC BY-NC-ND
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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.