SynthesisFrontiers in psychology2022
Hierarchical Structure of Depression Knowledge Network and Co-word Analysis of Focus Areas.
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.
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.
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.
Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Knowledge development visualization and mapping path of the psychological capital research.Frontiers in psychology · 2022Pooled it
- Research Progress, Challenges, and Future Trends of Modified Atmosphere Packaging (MAP) Technology for Food and Agricultural Products: A Bibliometric Analysis (2016-2025).Foods (Basel, Switzerland) · 2026Review
- Knowledge graph and its application in the study of neurological and mental disorders.Frontiers in psychiatry · 2025Review
- The Depressive Tendency Questionnaire for Chinese Middle School Students: Development and Initial Validation.Psychology research and behavior management · 2024Article
- Research Trends and Hotspots on Asthma and Depression: A Bibliometric Analysis.Journal of asthma and allergy · 2024Review
- Characteristics and trends in acceptance and commitment therapy research: A bibliometric analysis.Frontiers in psychology · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
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
Identifiers
What OpenQuestion holds
Registered trials
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.