P2.12 Differences in uptake, characteristics, and testing history of clients of getcheckedonline during scale-up to urban, surburban and rural communities in british columbia, canada
Bibliographic record
Abstract
Introduction In Sept 2014, the BC Centre for Disease Control (BCCDC) launched GetCheckedOnline (GCO), an online testing service for STI/HIV which is integrated with clinical and public health services and developed to reduce testing barriers. Based on a successful pilot in urban Vancouver (BC’s largest city) and alignment with regional health authority testing priorities, GCO was expanded to five other urban, suburban and rural communities across BC in Feb 2016. Here we examine differences in GCO uptake between Vancouver and expansion sites from the first year of scale-up in British Columbia (BC). Methods We used routinely collected GCO program data in combination with BC Public Health Laboratory testing data to describe differences between GCO clients in Vancouver and expansion sites. We compared demographic characteristics and testing history as well as key program measures including service uptake (percent creating a GCO account who submitted specimens) and positivity rates (percent positive of specimens submitted). Results Between Feb-Dec 2016, of 2397 clients creating accounts, 1297 (54%) submitted specimens; uptake was slightly lower in expansion sites (577 specimens, 51%) vs. Vancouver (720, 57%; p=0.001), with comparable positivity rates (6% vs. 5%; p=0.77). Compared to Vancouver, GCO clients in expansion sites were more likely to be younger (20–24 years of age) (20% vs. 13%) and symptomatic (20% vs. 14%), and less likely to be men who have sex with men (22% vs. 42%; p≤0.001 for all). GCO clients in expansion sites were more likely to be testing for the first time for both HIV (22% vs. 9%) and STI (16% vs. 9%; p<0.001). Conclusion Scale-up of GCO to five smaller urban, suburban and rural communities across BC demonstrated differences in uptake and populations reached, including greater engagement of individuals not previously tested. Our study highlights the importance of differing regional contexts on the impact of online testing services and the need for their evaluation during scale-up.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".