Evidence map›Paper›PMID 41511922›Full record

ArticlePloS one2026

Community management: An effective model to reduce medication discontinuation rate in patients with schizophrenia.

Hua Ren, Qin Yang, Changjiu He, Jian Jiao, Zaiquan Dong

Abstract read
In one paragraph

Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Hua RenThe Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, P.R. China.ORCID 0009-0002-2575-8064
Qin YangThe Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, P.R. China.
Changjiu HeThe Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, P.R. China.
Jian JiaoSleep Medicine Center, Mental Health Center, Translational Neuroscience Center, West China Hospital, Sichuan University, Chengdu, P.R. China.
Zaiquan DongMental Health Center, National Center for Mental Disorders, West China Hospital, Sichuan University, Chengdu, P.R. China.ORCID 0009-0008-9668-5767

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMedication discontinuation is highly prevalent among patients with schizophrenia and is associated with poor clinical outcomes. Although community-based management models have been implemented in China to support patients, recent evidence of their effectiveness in reducing medication discontinuation rates remains limited.

methodsIn this cross-sectional study, we surveyed 1,531 patients with schizophrenia under community management in Chengdu, China, using a multi-stage sampling approach. Data on treatment discontinuation (defined as cessation of all antipsychotics for >15 days without medical advice), socio-demographics, clinical characteristics, and service utilization were collected via face-to-face interviews. Univariate and multivariable logistic regression analyses were used to identify the factors associated with medication discontinuation.

resultsThe overall rate of medication discontinuation was 4.1%. Multivariable analysis identified several independent risk factors for discontinuation: weak stable disease state (adjusted odds ratio [aOR] = 2.70, 95% confidence interval [CI]: 1.34-5.24), lack of insight (aOR for partial vs. no insight = 0.25, 95% CI: 0.08-0.80; aOR for full vs. no insight = 0.18, 95% CI: 0.05-0.65), presence of noticeable side effects (aOR = 1.98, 95% CI: 1.05-3.64), and absence of regular follow-up (aOR for intermittent vs. no follow-up = 0.38, 95% CI: 0.20-0.72; aOR for regular vs. no follow-up = 0.22, 95% CI: 0.10-0.44).

conclusionCommunity management was associated with a low rate of medication discontinuation in patients with schizophrenia. Key modifiable factors, including disease stability, insight, medication side effects, and follow-up adherence should be prioritized in community-based interventions to further improve treatment continuity.

Indexed as

Antipsychotic AgentsSchizophreniaAdherence InterventionsAdultChinaCross-Sectional StudiesFemaleHumansMaleMedication AdherenceMiddle AgedRisk FactorsTreatment InterruptionAntipsychotic Agents

Identifiers

PMID41511922
PMCPMC12788679

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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.