Evidence map›Paper›PMID 37833690›Full record

ArticleBMC psychiatry2023

Prevalence, risk factors and multiple outcomes of treatment delay in Chinese patients with schizophrenia.

Yue-Hui Yu, Quan Lu

Open access · goldAbstract read
In one paragraph

Article in BMC psychiatry, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
2.0field-weighted citation impact, top 14% of its field
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

7 citing papers in PubMed, 9 citations in OpenAlex.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. 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

2 authors at 1 institution in 1 country.

Yue-Hui YuSchool of Public Administration and Policy, Renmin University of China, Beijing, 100872, China.
Quan LuSchool of Labor and Human Resources, Renmin University of China, Beijing, 100872, China. luquanRUC@163.com.
Renmin University of China · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPeople with schizophrenia often delay treatment. This issue is not fully understood, particularly in low-and middle-income countries. This study aimed to elucidate the prevalence, risk factors and multiple outcomes of treatment delay in schizophrenia in a Chinese metropolis.

methodsA two-stage whole cluster sampling survey was conducted in Beijing, China in 2020. A total of 1,619 patients with schizophrenia were included. Heterogeneity between groups and the changing trend of treatment delay were presented. Regression modelling methods were used to examine both the risk factors for treatment delay and related outcomes at individual and family levels.

resultsThe median treatment delay for schizophrenia was 89 days (about 13 weeks). 49.35% surveyed patients delayed treatment for more than three months. Early age of onset, low level of education, living in well developed districts were important risk factors. Treatment delay in schizophrenia was significantly associated with patients' poor medication adherence, comorbidity status and poor social functioning. It also increased the negative impact of the illness on families.

conclusionsThis study accumulated evidence of treatment delay in schizophrenia in China. It occurs even in the metropolis where mental health resources are relatively adequate. Further targeted interventions to raise public awareness should be crucial to reduce treatment delay.

Indexed as

SchizophreniaTime-to-TreatmentChinaEast Asian PeopleHumansPrevalenceRisk FactorsTreatment OutcomeUrban PopulationChinaOutcomesRisk factorsSchizophreniaTreatment delay

Identifiers

PMID37833690
PMCPMC10576347
OpenAlexW4387615536

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.