Evidence map›Paper›PMID 33685432›Full record

ArticleBMC psychiatry2021

Barriers to medication adherence for rural patients with mental disorders in eastern China: a qualitative study.

Xiaoyun Chai, Ying Liu, Zhuxin Mao, Shunping Li

Abstract read
In one paragraph

Article in BMC psychiatry, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
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  3. Review
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  5. Article
  6. Medication non-adherence in re-admitted patients at a psychiatry hospital: A qualitative study.The South African journal of psychiatry : SAJP : the journal of the Society of Psychiatrists of South Africa · 2025
    Article
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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Xiaoyun ChaiCentre for Health Management and Policy Research, School of Public Health, Cheeloo College of Medicine, Shandong University, Wenhua Xi Rd 44, Jinan, 250012, China.
Ying LiuAsset Management and Operation Department, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, 250021, China.
Zhuxin MaoSchool of Insurance, Southwestern University of Finance and Economics, Chengdu, 611130, China. zhuxin.mao@hotmail.com.ORCID 0000-0002-7444-1584
Shunping LiCentre for Health Management and Policy Research, School of Public Health, Cheeloo College of Medicine, Shandong University, Wenhua Xi Rd 44, Jinan, 250012, China. lishunping@sdu.edu.cn.ORCID 0000-0001-8144-6220

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMental disorders are destructive and usually require long-term medication, but non-adherence of medication is highly prevalent in patients with mental disorders. Previous studies relating to medication non-adherence were mainly quantitative. Meanwhile, there have been even fewer studies conducted in rural areas in China that focused on patients' medication non-adherence. This study aims to explore the barriers to medication adherence for rural patients with mental disorders in China from the perspectives of patients, patients' family members and healthcare providers.

methodsA qualitative study was carried out in the rural areas of four towns within Shandong Province in eastern China. The study adheres to COREQ guidelines. Semi-structured in-depth interviews were conducted with 11 patients, 21 family members and 8 primary mental health service providers.

resultsThematic analysis generated five major themes: (1) lack of self-insight, (2) inadequate family support, (3) long treatment duration and side effects of drugs, (4) poor economic conditions, and (5) the perceived stigma of illness.

conclusionThese findings may be useful for policymakers and planners to improve medication adherence and decrease the recurrence rate of mental disorders in China.

Indexed as

Medication AdherenceMental DisordersChinaHumansQualitative ResearchRural PopulationChinaMedication adherenceMental disordersQualitative research

Identifiers

PMID33685432
PMCPMC7941940

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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.