Evidence map›Paper›PMID 36865073›Full record

ArticleFrontiers in psychiatry2023

Predictive potential of somatic symptoms for the identification of subthreshold depression and major depressive disorder in primary care settings.

Xiuwen Li, Huimin Zhang, Xue Han, Lan Guo, Felicia Ceban, Yuhua Liao, Jingman Shi, Wanxin Wang, Yifeng Liu, Weidong Song and 6 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in psychiatry, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
5.1field-weighted citation impact, top 4% 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

18 citing papers in PubMed, 23 citations in OpenAlex.

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  6. Predicting Suicidal Ideation in Community-based Older Adults Using Self-report Questionnaires with Machine Learning.Clinical psychopharmacology and neuroscience : the official scientific journal of the Korean College of Neuropsychopharmacology · 2025
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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

16 authors at 5 institutions in 2 countries.

Xiuwen LiDepartment of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China.
Huimin ZhangDepartment of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China.
Xue HanDepartment of Psychiatry, Shenzhen Nanshan Center for Chronic Disease Control, Shenzhen, China.
Lan GuoDepartment of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China.
Felicia CebanMood Disorders Psychopharmacology Unit, University Health Network, Toronto, ON, Canada.
Yuhua LiaoDepartment of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China.
Jingman ShiDepartment of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China.
Wanxin WangDepartment of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China.
Yifeng LiuDepartment of Psychiatry, Shenzhen Nanshan Center for Chronic Disease Control, Shenzhen, China.
Weidong SongDepartment of Psychiatry, Shenzhen Nanshan Center for Chronic Disease Control, Shenzhen, China.
Dongjian ZhuDepartment of Psychiatry, Shenzhen Nanshan Center for Chronic Disease Control, Shenzhen, China.
Hongqiong WangDepartment of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China.
Lingjiang LiMental Health Institute of the Second Xiangya Hospital, Central South University, Changsha, China.
Beifang FanDepartment of Psychiatry, Shenzhen Nanshan Center for Chronic Disease Control, Shenzhen, China.
Ciyong LuDepartment of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China.
Roger S McIntyreMood Disorders Psychopharmacology Unit, University Health Network, Toronto, ON, Canada.
Sun Yat-sen University · CNShenzhen Nanshan Center for Chronic Disease Control · CNBrain and Cognition Discovery Foundation · CASecond Xiangya Hospital of Central South University · CNUniversity of Toronto · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The presence of heterogenous somatic symptoms frequently obscures the recognition of depression in primary care. We aimed to explore the association between somatic symptoms and subthreshold depression (SD) and Major Depressive Disorder (MDD), as well as to determine the predictive potential of somatic symptoms in identifying SD and MDD in primary care. Methods: Data were derived from the Depression Cohort in China study (ChiCTR registry number: 1900022145). The Patient Health Questionnaire-9 (PHQ-9) was used to assess SD by trained general practitioners (GPs), and the Mini International Neuropsychiatric Interview depression module was used to diagnose MDD by professional psychiatrists. Somatic symptoms were assessed using the 28-item Somatic Symptoms Inventory (SSI). Results: In total of 4,139 participants aged 18-64 years recruited from 34 primary health care settings were included. The prevalence of all 28 somatic symptoms increased in a dose-dependent manner from non-depressed controls to SD, and to MDD ( Conclusions: Somatic symptoms were associated with the presence of SD and MDD. In addition, somatic symptoms, notably those related to energy, showed good predictive potential in identifying SD and MDD in primary care. The clinical implication of the present study is that GPs should consider the closely related somatic symptoms for early recognition for depression in practice.

Indexed as

depressionmajor depressive disorderprimary carescreeningsomatic symptomssubthreshold depression

Identifiers

PMID36865073
PMCPMC9971499
OpenAlexW4320723887

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.