Examining differential success in recruitment using respondent driven sampling (RDS) in a multi-site study of gay, bisexual and other men who have sex with men
Bibliographic record
Abstract
BACKGROUND: The Engage Study is a longitudinal biobehavioral cohort study of gay, bisexual and other men who have sex with men (GBM) in Toronto, Montreal, and Vancouver. Baseline data (2,449 participants) were collected from February 2017 - August 2019 using respondent-driven sampling (RDS). Recruitment in Montreal required fewer seeds, had a much shorter recruitment period, and recruited the largest sample. METHODS: To better understand why RDS recruitment was more successful in Montreal compared to other sites, we conducted an analysis to examine RDS recruitment characteristics for GBM in each of the three study sites, explore demographic characteristics and measures of homophily, that is, the tendency of individuals to recruit other study participants who are like themselves, and compared motivations for study participation. RESULTS: Montreal had the greatest proportion of participants over the age of 45 (29.1% in Montreal, 24.6% in Vancouver, and 21.0% in Toronto) and the highest homophily for this age group, but homophily was high across the three cities. Montreal also reported the lowest percentage of participants with an annual income greater or equal to $60,000 (7.9% in Montreal, 13.1% in Vancouver and 10.6% in Toronto), but homophily was similar across all three cities. The majority of participants indicated interest in sexual health and HIV as the main reason for participating (36.1% in Montreal, 34.7% in Vancouver, and 29.8% in Toronto). Financial interest as the main reason for participation was low (12.7% in Montreal, 10.6% in Vancouver, and 5.7% in Toronto). CONCLUSION: Taken together, although we found some differences in study demographic characteristics and homophily scores, we were unable to fully explain the different recruitment success based on the data available. Our study underlines the fact that success of RDS implementation may vary by unknown factors, and that researchers should be proactive and flexible to account for variability.
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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 | 0.023 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".