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Assessing the depression risk in the U.S. adults using nomogram

Bibliographic Data

ID15354526
AuthorsYafeng Zhang (0000-0002-0876-0499, Harbin Medical University, corresponding author), Wei Tian (0000-0003-4125-4704, Harbin Medical University), Xinhao Han (Harbin Medical University), Guangcan Yan (0000-0002-9354-6461, Harbin Medical University), Yuanshuo Ma (0000-0002-6279-0314, Harbin Medical University), Shan Huo (0000-0003-3579-5774, Kelun Group (China)), Yu Shi (0000-0002-8585-9484, Harbin Medical University), Shanshan Dai (0000-0001-9067-2748), Xin Ni (0000-0002-3549-3795, Beijing Children’s Hospital), Zhe Li (0000-0002-2003-0827, Capital Medical University), Lihua Fan (0000-0002-3007-9341, Harbin Medical University), Qiuju Zhang (0000-0003-3407-2136, Harbin Medical University)
Year2022
Volume22
Issue1
Pages416-416
Publication date2022-03-02
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueBMC Public Health (JOURNAL)
Journal identifiersISSN: 1471-2458 • E-ISSN: 1471-2458
PublisherBioMed Central (PUBLISHER • GB)
DOI10.1186/s12889-022-12798-6
PMID35232400
OpenAlexW4214820981
LanguageEN
Citations received1
References cited33

This study presents two prediction models of depression, which can effectively and accurately predict the probability of depression as well as helping the U.S. civilian non-institutionalized population to make optimal treatment decisions

Anxiety · Biostatistics · Cohort · Depression (economics · Depressive symptoms · Environmental health · Logistic regression · Marital status · Nomogram · Patient Health Questionnaire · Population · Psychiatry · Cardiac Health and Mental Health · Demography · Medicine · Mental Health Research Topics · Sleep and related disorders · Epidemiology · Internal Medicine

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Unique citing works1
Citations per year1
Citation span2026 - 2026 (1)
Citation velocitycurrent
Highly citedNo
Citation typesNeutral: 1
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