Oral Health and Hygiene Status of Global Transgender Population: A Living Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Due to several interpersonal, social, and organizational challenges, dental health has been occasionally compromised in the transgender population. There is a lack of awareness among transgender persons to access affordable trans-competent oral health care. More information is required to identify and assess the oral health condition of this population in order to encourage better access to oral healthcare and effectively influence public health policy and practice. This systematic review aims to provide evidence about the status of oral health and hygiene of the transgender population across the globe. A systematic literature search using keywords and MESH search terms was conducted using PubMed, Medline, Google Scholar, and EBSCO online databases. The references of included journal articles were manually searched and appropriate studies were included, which were then critically appraised using the Joanna Briggs Institute (JBI) tool and the Newcastle-Ottawa protocol for the risk of bias assessment of prevalence studies, with each study assessed by two independent reviewers. Based on the search procedures, a total of 2026 articles were initially screened and, after evaluation, 20 were included in the systematic review. Transgender persons often face stigma and discrimination in dental healthcare settings, which affects their oral health status. A greater prevalence of substance abuse stemming from anxiety, lack of adequate education, and poor socioeconomic status leads to an increased prevalence of oral health diseases in this marginalized population. There is a need for policies and reforms to appraise their oral health and hygiene status and improve access to oral health services in this population.
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 | 0.010 | 0.029 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.023 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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; 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".