Stigma associated with sexually transmissible infection testing in an online testing environment: examining the perspectives of youth in Vancouver, Canada
Bibliographic record
Abstract
Background Online sexually transmissible infection (STI) testing is increasingly available and has shown promising results across different settings. However, evidence on how stigma associated with STI testing may be experienced by youth in the context of these online services is limited. METHODS: A convenience sample of 71 youth (aged 15-24 years) both male and female was engaged through online and offline recruitment strategies in Vancouver, Canada. Through semistructured and exploratory interviews, participants were asked about their perceptions of stigma associated with STI testing in an online testing environment. Data were analysed using a thematic analysis approach. RESULTS: Youth came from a diverse set of sociodemographic backgrounds and most (n=46, 65%) had previously accessed STI testing in clinic-based settings. Participants' perceptions pointed to the benefits of online testing for reducing the external stigma despite the potential persistence of internalised stigma. Notions of hegemonic masculinity and emphasised femininity were also present in the participants' descriptions of the role of gender in accessing online STI testing. CONCLUSIONS: Online STI testing could potentially ameliorate the experiences of participants in regards to the stigma associated with STI testing; however, participants' internalised feelings of shame and stigma around testing for STI may continue to persist. Our findings underscore the need to revisit and re-evaluate existing STI testing services to provide less anxiety-inducing testing environments for youth.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.015 | 0.004 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".