The intersection of mpox outbreak and mental health: a bibliometric analysis of current research trends
Bibliographic record
Abstract
Background and Objectives The ongoing mpox outbreaks have garnered significant attention due to their public health implications, particularly the potential mental health impacts. Despite the growing concern, there has been limited exploration of the intersection between mpox and mental health within the research literature. This study aims to conduct a comprehensive bibliometric analysis to examine global research trends, regional distribution, and thematic focus areas related to mpox's psychological and psychiatric implications. Methods We conducted a bibliometric analysis using Scopus and the Web of Science database. The analysis was carried out using the R-bibliometrics package and involved identifying literature on mpox and mental health, focusing on global research trends, regional distribution, and thematic areas of study. The analysis included 416 documents obtained from 295 sources from January 1, 2014 to August 27, 2024. Results Our analysis revealed a growing but unevenly distributed literature on mpox and mental health. Most studies concentrated on the relationship between mpox and conditions such as depression and anxiety, while other psychiatric outcomes remain underexplored. The geographic distribution of research was also uneven, with regions like Europe and the Americas receiving more focus than others. Conclusions The study highlights the need for more targeted research on the mental health sequelae of mpox, particularly for vulnerable populations and regions that are currently underrepresented in the literature. Future research should include longitudinal studies to assess the long-term effects of mpox on mental health and the development of robust methodologies to establish causality. Integrating mental health considerations into public health responses to mpox outbreaks is crucial, with significant implications for research, policy, and clinical practice.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.019 | 0.095 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.226 | 0.295 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".