Research Publications on the Mental Health of Transgender People: A Bibliometric Analysis Using Scopus Database (1992–2021)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose: Assessing research activity is important for planning future research agendas and corresponding policies. The purpose of the current study was to analyze research publications on the mental health of transgender people. Methods: A bibliometric method using the SciVerse Scopus database was conducted. The study period was from 1992 to 2021. Keywords related to transgender and mental health were used to generate bibliometric data. Results: The search strategy found 1862 documents authored by 7820 researchers and disseminated through 641 journals. Research on the mental health of transgender people experienced a steep growth after 2013. Authors and institutions in the United States were the most active in the field. Except for research collaboration between the United States and Canada, no significant cross-country collaboration was noted in the field. The most active journal was the Journal of Gay and Lesbian Mental Health ( n =54, 2.9%), followed by the LGBT Health journal ( n =52, 2.8%). However, documents published in the American Journal of Public Health journal ( n =147.9) received the highest number of citations per document. Articles on suicide, violence, mental stress, and stigma were the most impactful in terms of the number of citations. Major research themes in the field included substance/alcohol use, violence, and the prevalence of depression/anxiety/suicide among transgender youth. Conclusions: Research on the mental health of transgender people is on the rise. International research collaboration in the field is important to help researchers in low- and middle-income countries and increase the visibility of problems about transgender people in these countries.
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.
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 | 0.010 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.055 | 0.193 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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 it