Global research on cognitive function for Schizophrenia from 2014 to 2024: a bibliometric and visual analysis
Bibliographic record
Abstract
Aims Schizophrenia (SCZ) is a complex and multifactorial severe mental disorder, one of whose characteristics is cognitive impairment. We used bibliometric methods to identify the current research hotspots and emerging trends in this field.Methods We thoroughly searched SCZ cognitive function publications in the WoSCC database (2014-2024). We used CiteSpace and VOSviewer for a systematic analysis of countries, institutions, authors, journals, keywords, and more to evaluate the current research landscape, trends, and areas of interest.Results We identified 11121 articles. The majority of these publications come from the United States, the United Kingdom, China, Germany, and Canada. ‘Schizophrenia Research’ is the most active journal. ‘Bipolar disorder’, ‘meta-analysis’, ‘deficit’, ‘negative symptoms’, and ‘performance’ are the most common research topics. Michael F. Green is a highly influential author, and the University of London is a highly influential institution. Additionally, cluster analysis reveals that research primarily focuses on schizophrenia spectrum disorders, bipolar disorder, and genetic architecture.Conclusions Our research reveals that the identification of key network characteristics and cognitive heterogeneity, the interaction between polygenic risk and environmental factors, the safety of pharmacological interventions, and the cognitive development of youth are likely to be areas that should be prioritized in current and future research.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.024 | 0.063 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".