Design and implementation of a sexual health intervention for migrant construction workers situated in Shanghai, China
Bibliographic record
Abstract
BACKGROUND: China's growing population of internal migrants has exceeded 236 million. Driven by rapid development and urbanization, this extreme population mobility creates opportunities for transmission of HIV and sexually-transmitted infections (STI). Large numbers of rural migrants flock to megacities such as Shanghai in search of employment. Although migrants constitute a key population at heightened risk of acquiring HIV or an STI, there is a lack of easily accessible sexual health services available for them. In response, we designed a short, inexpensive sexual health intervention that sought to improve HIV and STI knowledge, while reducing stigma, risky sexual behaviour, and sexual transmission of HIV and STI among migrant construction workers (MCW) situated in Shanghai, China. RESULTS: We implemented a three-armed, community-randomized trial spread across three administrative districts of Shanghai. The low-intensity intervention included educational pamphlets. The medium-intensity intervention included pamphlets, posters, and videos. The high-intensity intervention added group and individual counselling sessions. Across 18 construction sites, 1871 MCW were allocated at baseline to receive one intervention condition. Among baseline participants, 1304 workers were retained at 3-months, and 1013 workers were retained at 6-months, representing a total of 579 person-years of follow-up. All workers, regardless of participation, had access to informational materials even if they did not participate in the evaluation. Overall outputs included: 2284 pamphlets distributed, 720 posters displayed, 672 h of video shown, 376 participants accessed group counselling, and 61 participants attended individual counselling sessions. A multivariable analysis of participation found that men (aOR = 2.2; 95 % CI 1.1, 4.1; p = 0.036), workers situated in Huangpu district (aOR = 5.0; 95 % CI 2.6, 9.5; p < 0.001), and those with a middle school education (aOR = 1.9; 95 % CI 1.2, 3.0; p = 0.01) were more likely to have participated in intervention activities. CONCLUSION: A brief educational intervention that prioritized ease of delivery to a highly mobile workforce was feasible and easily accessed by participants. Routine implementation of sexual health interventions in workplaces that employ migrant labour have the potential to make important contributions toward improving HIV and STI outcomes among migrant workers in China's largest cities.
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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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".