Community perspectives on ideal bacterial STI testing services for gay, bisexual, and other men who have sex with men in Toronto, Canada: a qualitative study
Bibliographic record
Abstract
BACKGROUND: Innovation is needed to produce sustained improvements in bacterial sexually transmitted infections (STI) testing given suboptimal access and uptake among sexually active gay, bisexual or other men who have sex with men (GBM). Yet, the STI testing processes and technologies that best address local testing barriers among GBM in Toronto is unknown. We aimed to explore men's perspectives regarding STI testing services for GBM to identify and prioritize new STI testing interventions in Toronto, Ontario, Canada. METHODS: We conducted four focus groups with twenty-seven GBM in 2017: two with cisgender men living with HIV, one with cisgender HIV-negative men, and one with transgender men. Twenty-seven men participated in the focus groups with 40% 18-30 years of age, 48% self-identifying as white, and the remainder self-identifying as Middle Eastern, Latino/Hispanic, Asian/Pacific Islander, South Asian, First Nations, African/Caribbean/Black, or mixed race. 59% of participants self-identified as living with HIV. Participants were asked about their STI testing experiences in Toronto, barriers and facilitators to testing, and ideal STI testing process. Focus groups were audio recorded, transcribed verbatim, and analyzed using thematic analysis. RESULTS: Core concepts included how clinical context, bacterial STI testing delivery, and interactions with healthcare providers can create barriers and recommendations for ways to improve. Regarding clinical context, participants desired more clinics with accessible locations/hours; streamlined testing that minimized use of waiting rooms and wait times; and improved clinic ambience. Bacterial STI testing delivery recommendations included standardization to ensure consistency in sexual history intake, tests offered, follow-up and public health reporting between clinics. Men also recommended reducing the multistep process testing by offering components such as lab requisitions and results online. Participants also recommended interactions with healthcare providers be professional and non-judgmental, offer compassionate and competent care with destigmatizing and lesbian, gay, bisexual and trans (LGBT) affirming communication. CONCLUSION: Concrete and practical solutions for improving existing sexual health services and facilitating optimal STI testing include streamlining testing options and providing patient-centred, LGBT-affirming care to enable optimal STI testing.
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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.019 | 0.008 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".