Practices Used in Health and Social Services for the Management of Mistreatment Situations towards Adults in a Context of Gender and Sexual Diversity: A Scoping Review
Bibliographic record
Abstract
Research indicates that adults in the context of gender and sexual diversity (GSD) experienced more violence and discrimination than the rest of the population. GSD refers to all the diversities of sexual characteristics, sexual orientations and gender identity of a person or a group. To encourage the use of evidence-based interventions in health and social services, it is important to extrapolate from the scientific literature how mistreatment situations are managed in this context. A scoping review was conducted using the approach of the Johanna Briggs Institute and the Preferred Reporting Items for Systematic Reviews and Meta-analysis Protocols Extension for Scoping Reviews guidelines. In total, 8 databases were searched for relevant studies published in English and in French. Screening according to inclusion criteria (titles, abstracts, and full texts) and data extraction were performed independently by two team members. Twelve studies were included in this scoping review and covered only three types of mistreatments: intimate partner violence, discrimination, and sexual assaults. Findings suggest a need for tools to better identify mistreatment situations in the context of GSD and additional studies to highlight effective interventions using adequate methodology. None of the studies reported data specifically about older adults or regarding key care events related to the management of mistreatment situations (reporting, needs assessment or investigation). Implications include addressing gaps in research and better educating care providers in health and social services in matters related to GSD, to ensure that they have a better understanding of the needs and realities of 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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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; a candidate call from one teacher head, 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".