Evidence map›Paper›PMID 37215825›Full record

ArticleHeliyon2023

Analysis of the prevalence and influencing factors of anxiety and depression in the Chinese population: A cross-sectional survey.

Xinyi Kong, Yibo Wu, Xinpei Wang, Yike Sun, Ke Chen, Qiyu Li, Jie Li

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
2.8field-weighted citation impact, top 8% 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

16 citing papers in PubMed, 28 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors at 6 institutions in 1 country.

Xinyi KongDepartment of Cardiovascular Intervention, The Second Affiliated Hospital of Nanchang University, Nanchang, 330006, China.
Yibo WuSchool of Public Health, Peking University, Beijing, 100191, China.
Xinpei WangMedical Equipment Department, Peking University First Hospital, Beijing, 100043, China.
Yike SunCollege of Integrated Traditional Chinese and Western Medicine, Jining Medical University, Jining, 272111, China.
Ke ChenDepartment of Psychology, Anhui University, Anhui Province, Hefei, China.
Qiyu LiSchool of Humanities and Health Management, Jinzhou Medical University, Jinzhou, 121000, China.
Jie LiDepartment of Internal Medicine, Jiangxi Chest Hospital, Nanchang, 330006, China.
Peking University · CNAnhui University · CNJiangxi Chest Hospital · CNJining Medical University · CNJinzhou Medical University · CNSecond Affiliated Hospital of Nanchang University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To explore the prevalence and influencing factors of anxiety and depression symptoms among Chinese people in 2021. Investigation teams were recruited in 120 cities across the country. Based on the data from "the Seventh National Population Census in 2021″, quota sampling was conducted on the residents of these cities to obtain samples that conformed to population characteristics. Next, baseline information on research objects was collected, and the questionnaire survey was conducted through the online questionnaire Wenjuanxing platform. The Patient Health Questionnaire-9 (PHQ-9) rating scale was used to evaluate the mental state of the subjects. The correlation between baseline information and different PHQ-9 risk intervals was analyzed using the Chi-square test and Logit model. The impact of relevant risk factors on PHQ-9 scores was analyzed using the decision tree. The Chi-square test results revealed that place of residence (

Indexed as

AnxietyChinese populationDepressionInfluencing factorsPrevalence

Identifiers

PMID37215825
PMCPMC10192403
OpenAlexW4367309704

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.