Evidence map›Paper›PMID 40837811›Full record

ReviewWorld journal of psychiatry2025

Medication literacy and treatment adherence in people living with human immunodeficiency virus: Mediating effects of psychosocial factors.

Cheng-Hua Xu, Di Hu, Hui-Jiao Lin, Yi-De Yang, Meng-Nan Li, Le-Wen Shao

Abstract readReview
In one paragraph

Review in World journal of psychiatry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

6 authors.

Cheng-Hua XuDepartment of Nursing, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310006, Zhejiang Province, China.
Di HuDepartment of Hospital Infection Management Section, Taizhou Municipal Hospital, Taizhou 318000, Zhejiang Province, China.
Hui-Jiao LinDepartment of Emergency Medicine, Taizhou Municipal Hospital, Taizhou 318000, Zhejiang Province, China.
Yi-De YangDepartment of Infectious Diseases, Taizhou Municipal Hospital, Taizhou 318000, Zhejiang Province, China.
Meng-Nan LiDepartment of Nursing, Taizhou Municipal Hospital, Taizhou 318000, Zhejiang Province, China.
Le-Wen ShaoDepartment of Nursing, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310006, Zhejiang Province, China. 951109@zju.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Treatment adherence among people living with human immunodeficiency virus (PLWH) is a critical determinant of viral suppression and improved quality of life. Medication literacy, as a key factor influencing adherence, is itself shaped by various psychosocial variables. Existing studies suggest that human immunodeficiency virus (HIV)-related stigma, self-efficacy, and trust in healthcare providers serve as significant mediators in the relationship between health literacy and treatment adherence. This review systematically explores how medication literacy affects treatment adherence in PLWH through intermediary psychosocial mechanisms such as depression, anxiety, and social support. By synthesizing current evidence, we aim to inform the development of targeted psychosocial interventions to enhance treatment outcomes and quality of life for this population. Our findings provide an evidence-based foundation for nursing practice and support innovative strategies in comprehensive HIV care.

Indexed as

AnxietyDepressionDigital healthHuman immunodeficiency virusMedication literacyPsychosocial factorsSelf-efficacySocial supportStigmas

Identifiers

PMID40837811
PMCPMC12362642

What OpenQuestion holds

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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.