Evidence map›Paper›PMID 34603092›Full record

ArticleFrontiers in psychiatry2021

The Sichuan Mental Health Survey: Methodology.

Rong-Cheng Su, Li-Hong Huang, Jia Li, Bo Zhou, Jia-Jun Zhao, Hui Li

Abstract read
In one paragraph

Article in Frontiers in psychiatry, 2021. 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

6 authors.

Rong-Cheng SuKey Laboratory of Psychosomatic Medicine, Chinese Academy of Medical Sciences, Chengdu, China.
Li-Hong HuangKey Laboratory of Psychosomatic Medicine, Chinese Academy of Medical Sciences, Chengdu, China.
Jia LiKey Laboratory of Psychosomatic Medicine, Chinese Academy of Medical Sciences, Chengdu, China.
Bo ZhouKey Laboratory of Psychosomatic Medicine, Chinese Academy of Medical Sciences, Chengdu, China.
Jia-Jun ZhaoKey Laboratory of Psychosomatic Medicine, Chinese Academy of Medical Sciences, Chengdu, China.
Hui LiKey Laboratory of Psychosomatic Medicine, Chinese Academy of Medical Sciences, Chengdu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Sichuan Mental Health Survey (SMHS) is a provincially representative survey with a coherent methodology to obtain the prevalence of multiple mental disorders and data of services used and to analyze the psychological and social risk factors or correlates in Sichuan, China. Mental disorders include anxiety disorders, mood disorders, schizophrenia, and other psychotic disorders, drug use and alcohol use disorders, impulse control disorder, and eating disorders. A cross-sectional design is employed to sample adults from 200 communities/villages in all 21 prefectural-level municipalities of Sichuan Province in a five-stage provincially representative disproportionate stratified sampling design. The participants need to be interviewed face to face by trained interviewers from local primary healthcare institutions and by psychiatrists. The quality control staff implement data quality control by checking records and statistics in the interview system, and then re-interviewing checks are done by the psychiatrists. Data is weighted to adjust the sample distribution to match the whole population. The outcomes of the SMHS would not only demonstrate the serious challenges posed by the high burdens of mental disorders but also offer baseline data for policymakers and healthcare professionals to study and resolve the factors that influence mental health in Sichuan, China.

Indexed as

epidemiologic research designfieldworksample weightssurvey modesurvey sampling

Identifiers

PMID34603092
PMCPMC8484526

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Registered trials

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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.