P2-S2.22 Innovations to attract young female sex workers to access STI services in drop in centres (DIC): a case study from Bangalore, South India
Bibliographic record
Abstract
Background Young female sex workers pose a challenge in accessing continuous services in prevention program. Being young, relatively active and new to sex work increases their vulnerability drastically but also attract more clients. As young sex workers they often do not access services provided in the drop in centre due to several factors including self stigma, lack of Peer interaction, and less awareness about services in the DIC. Method Community consultations were done initially to know the barriers to accessing services in the DIC. As physical appearance goes a long way in determining how an individual is perceived by oneself and others around, introducing sessions on beauty and healthcare by a trained beautician, was felt suitable in attracting sex workers to the Drop in Centre. A beautician was hired and oriented towards the program. The primary focus of the sessions was to showcase and teach the sex workers basic skills in dressing well and looking good using quick and cost-effective ways. Apart from this the beautician also provided few beauty services which was accessed by the sex workers. These services were charged nominally so that the amount was used to replenish the cosmetics and makeup materials. Other crucial aspects of health, such as cleanliness, hygiene and prevention of STI, female condom demonstration and distribution were covered during counselling session and one to one interactions. This innovative approach aimed towards increasing uptake and access of services proved cost effective and was received well by the most vulnerable, young sex workers, attracting them to the DIC. Results As a result of introducing these sessions in the DIC 25 young sex workers were accessing services from the drop in centre every week. There was a steady increase in testing for STI in the introductory months itself. A peer network among the young sex workers was initiated and this helped the project to ensure that access to STI services were regular by this community. This innovative approach acted as a catalyst to improve the self-esteem of sex workers and ensured access to services there by reducing their vulnerability. Conclusion It is imperative for prevention programs to evolve and find newer and innovative methods to address the changing needs of vulnerable communities like the female sex workers. This strategy has proved to attract young sex workers there by effectively providing them STI and other services within the program.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".