Evidence map›Paper›PMID 38830649›Full record

ArticleSaudi medical journal2024

Do digital health information searches of individuals with chronic diseases affect health literacy and patient empowerment? A path analysis.

Şenay Şener, Seda Göger

Abstract read
In one paragraph

Article in Saudi medical journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Şenay ŞenerFrom the Department of Health Care Services (Şener), Safranbolu State Hospital, Ministry of Health, Karabük, and from the Department of Health Care Services (Göger), Vocational School of Health Services, Sakarya University, Sakarya, Turkey.
Seda GögerFrom the Department of Health Care Services (Şener), Safranbolu State Hospital, Ministry of Health, Karabük, and from the Department of Health Care Services (Göger), Vocational School of Health Services, Sakarya University, Sakarya, Turkey.ORCID https://orcid.org/0000-0003-2066-7147

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo analyze the relationship between chronically ill patients' behaviors in acquiring and verifying health information from a digital environment with health literacy and patient empowerment using a structural equation modeling approach.

methodsThis study was carried out in a public hospital in Turkey between February and May 2023. The study consisted of 365 participants and used descriptive and correlation-based designs for statistical analyses. It also executed computations for descriptive statistics and correlations to carry out a path analysis to assess model fitness and to identify direct and indirect effects.

resultsThis study identified that Web 1.0 and health information acquisition and digital verification variables statistically and significantly affected access to information, understanding information, appraisal (valuing)/evaluation, and application/use variables. The study also found that access to information variables was statistically significant on identity/identicalness, self-control, decision-making, and recognition and comprehension. The tested model fit the data well and adequately explained the direct effects of the variables.

conclusionThe study concluded by suggestively improving the chronically ill patients' media or digital literacy levels through special training to stimulate their internet use effectively.

Indexed as

Health LiteracyAdultAgedChronic DiseaseConsumer Health InformationDigital HealthEmpowermentFemaleHumansInformation Seeking BehaviorInternetMaleMiddle AgedTurkeyYoung Adultdigital environmenthealth literacypath analysispatient empowerment

Identifiers

PMID38830649
PMCPMC11147591

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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.