Evidence map›Paper›PMID 35664156›Full record

SynthesisFrontiers in psychology2022

Hierarchical Structure of Depression Knowledge Network and Co-word Analysis of Focus Areas.

Qingyue Yu, Zihao Wang, Zeyu Li, Xuejun Liu, Fredrick Oteng Agyeman, Xinxing Wang

Abstract readSystematic Review
In one paragraph

Synthesis in Frontiers in psychology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–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

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Review
  4. Article
  5. Review
  6. 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

6 authors.

Qingyue YuCollege of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China.
Zihao WangCollege of Medicine, Jiangsu University, Zhenjiang, China.
Zeyu LiJingjiang College of Jiangsu University, Zhenjiang, China.
Xuejun LiuCollege of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China.
Fredrick Oteng AgyemanSchool of Management, Jiangsu University, Zhenjiang, China.
Xinxing WangSchool of Management, Jiangsu University, Zhenjiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Contemporarily, depression has become a common psychiatric disorder that influences people's life quality and mental state. This study presents a systematic review analysis of depression based on a hierarchical structure approach. This research provides a rich theoretical foundation for understanding the hot spots, evolutionary trends, and future related research directions and offers further guidance for practice. This investigation contributes to knowledge by combining robust methodological software for analysis, including Citespace, Ucinet, and Pajek. This paper employed the bibliometric methodology to analyze 5,000 research articles concerning depression. This current research also employed the BibExcel software to bibliometrically measure the keywords of the selected articles and further conducted a co-word matrix analysis. Additionally, Pajek software was used to conduct a co-word network analysis to obtain a co-word network diagram of depression. Further, Ucinet software was utilized to calculate K-core values, degree centrality, and mediated centrality to better present the research hotspots, sort out the current status and reveal the research characteristics in the field of depression with valuable information and support for subsequent research. This research indicates that major depressive disorder, anxiety, and mental health had a high occurrence among adolescents and the aged. This present study provides policy recommendations for the government, non-governmental organizations and other philanthropic agencies to help furnish resources for treating and controlling depression orders.

Indexed as

depressionhierarchical structureknowledge networkvisualization networkword frequency statistical analysis

Identifiers

PMID35664156
PMCPMC9160970

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.