Evidence map›Paper›PMID 39942479›Full record

ArticleHealthcare (Basel, Switzerland)2025

Communication Tapestry: Health Literacy Mediates Public Trust in Physician Health Information in Pakistani Public Hospitals.

Dake Wang, Talib Hussain, Wang Weiying

Abstract read
In one paragraph

Article in Healthcare (Basel, Switzerland), 2025. 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

3 authors.

Dake WangSchool of Media and Communication, Shanghai Jiao Tong University, Shanghai 200240, China.ORCID 0000-0001-6486-8827
Talib HussainDepartment of Business Management, Karakoram International University, Diamer Campus, Gilgit 15100, Pakistan.ORCID 0000-0001-6580-9757
Wang WeiyingChina Research Institute for Science Popularization (CRISP), Beijing 100081, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND/

objectivesThis study explores the multifaceted factors influencing public trust in healthcare services provided by doctors in public hospitals in Pakistan. The objective is to examine the relationships between various determinants such as doctors' reputation and expertise, patient participation in decision-making, communication clarity, health literacy levels, and trust in prescribed medications to provide actionable insights for improving healthcare trust.

methodsA total of 550 patients from public hospitals were surveyed, and data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). This approach enabled the identification of intricate relationships between the key factors influencing trust in healthcare services.

resultsThe findings indicate that patient participation in decision-making and transparent communication significantly enhance trust in prescribed medications. Additionally, health literacy emerged as a crucial factor, with higher levels of understanding leading to greater confidence in healthcare services.

conclusionsThe study highlights the importance of patient-centered care, clear communication strategies, and health literacy initiatives in strengthening public trust in healthcare systems. Practical recommendations are provided for policymakers, healthcare professionals, and researchers to collaboratively improve healthcare service delivery and foster public confidence.

Indexed as

healthcare trusthealth literacyPakistanpatient involvementphysician reputationprescribed medicationspublic hospitalstransparent communication

Identifiers

PMID39942479
PMCPMC11817129

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.