A Crowdsourced Physician Finder Prototype Platform for Men Who Have Sex with Men in China: Qualitative Study of Acceptability and Feasibility
Bibliographic record
Abstract
BACKGROUND: Men who have sex with men (MSM), including both gay and bisexual men, have a high prevalence of HIV and sexually transmitted infections (STIs) in China. However, healthcare seeking behaviors and engagement in clinical services among MSM are often suboptimal. Global evidence shows that embedding online HIV or sexual health services into gay social networking applications holds promise for facilitating higher rates of healthcare utilization among MSM. We developed a prototype of a gay-friendly health services platform, designed for integration within a popular gay social networking app (Blued) in China. OBJECTIVE: The purpose of this study was to evaluate the acceptability of the platform and ask for user feedback through focus group interviews with young MSM in Guangzhou and Shenzhen, cities in Southern China. METHODS: The prototype was developed through an open, national crowdsourcing contest. Open crowdsourcing contests solicit community input on a topic in order to identify potential improvements and implement creative solutions. The prototype included a local, gay-friendly, STI physician finder tool and online psychological consulting services. Semistructured focus group discussions were conducted with MSM to ask for their feedback on the platform, and a short survey was administered following discussions. Thematic analysis was used to analyze the data in NVivo, and we developed a codebook based on the first interview. Double coding was conducted, and discrepancies were discussed with a third individual until consensus was reached. We then carried out descriptive analysis of the survey data. RESULTS: A total of 34 participants attended four focus group discussions. The mean age was 27.3 years old (SD 4.6). A total of 32 (94%) participants obtained at least university education, and 29 (85%) men had seen a doctor at least once before. Our survey results showed that 24 (71%) participants had interest in using the online health services platform and 25 (74%) thought that the system was easy to use. Qualitative data also revealed that there was a high demand for gay-friendly healthcare services which could help with care seeking. Men felt that the platform could bridge gaps in the existing HIV or STI service delivery system, specifically by identifying local gay-friendly physicians and counselors, providing access to online physician consultation and psychological counseling services, creating space for peer support, and distributing pre-exposure prophylaxis and sexual health education. CONCLUSIONS: Crowdsourcing can help develop a community-centered online platform linking MSM to local gay-friendly HIV or STI services. Further research on developing social media-based platforms for MSM and evaluating the effectiveness of such platforms may be useful for improving sexual health outcomes.
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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 | 0.014 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".