Opportunities and barriers to STI testing in community health centres in China: a nationwide survey
Bibliographic record
Abstract
BACKGROUND: China has strengthened its primary care workforce and implemented a wide network of community health centres (CHCs). However, STI testing and management are not currently included in the 'Essential Package of Primary Health Care in China'. Legislation change to encourage STI service delivery would be important, but it is also critical to determine if there are also provider-related opportunities and barriers for implementing effective STI programmes through CHCs if future legislation were to change. METHODS: A national representative survey was conducted between September and December 2015 in a stratified random sample of 180 CHCs based in 20 cities in China. Primary care practitioners (PCPs) provided information on current experiences of STI testing as well as the barriers and facilitators for STI testing in CHCs. Multivariate logistic regression was conducted to determine factors associated with PCPs performing STI testing. RESULTS: 3580 out of 4146 (86%) invited PCPs from 158 CHCs completed the survey. The majority (85%, 95% CI 84% to 87%) of doctors stated that STI testing was an important part of healthcare. However, less than a third (29%, 95% CI 27% to 31%) would perform an STI test if the patients asked. Barriers for performing STI testing included lack of training, concerns about reimbursement, concerns about damage to clinics' reputations and the stigma against key populations. Respondents who reported that they would perform an STI test were likely to be younger, received a bachelor degree or higher, received specific training in STIs, believed that STI test was an important part of healthcare or had resources to perform STI testing. CONCLUSIONS: There is potential for improving STI management in China through upskilling the primary care workforce in CHCs. Specific training in STIs is needed, and other structural, logistical and attitudinal barriers are needed to be addressed.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".