Barriers in care pathways and unmet mental health needs in LGBTIQ + communities
Bibliographic record
Abstract
Lesbian, gay, bisexual, transgender, intersex, queer people and minority gender identities and sexualities (LGBTIQ+) are often stigmatized and experience discrimination in health care settings, leading to poorer mental health outcomes and unmet needs compared to heterosexual and cisgendered peers. It is thus imperative that mental health providers consider and address structural challenges in order to reduce mental health inequalities of this population. This narrative review assessed the barriers that may prevent access to care and the pathways for care in LGBTIQ + communities. PubMed, PsycInfo, Embase, and Scopus were searched for papers published between December 2021 and February 2022. A total of 107 papers were included with studies reflecting five themes: (1) Unmet mental health needs; (2) Young people; (3) Substance abuse and addiction; (4) Barriers and pathways to care; and (5) Interventions. Findings demonstrate that LGBTIQ + people experience stigmatization and higher rates of substance misuse and mental ill health, which may lead to barriers in accessing health care services, and fewer tailored interventions being provided. These findings have implications for policy, health care screening, and how specialist services are structured. Substantial gaps in the evidence-base exist, and future research should examine how mental health care providers can challenge social issues that maintain discriminatory and stigmatizing practices, and support LGBTIQ + individuals to sustain their resilience.
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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 | 0.005 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".