P219 Policy and program recommendations for STBBI incentive-based testing in high-income countries: A systematic review
Bibliographic record
Abstract
Background Despite increasing access to treatment and testing, rates of sexually transmitted and blood-borne infections (STBBI) continue to rise. At the same time, screening uptake remains suboptimal. Incentives (e.g. cash, gift cards, prize draws) have been proposed as a way to increase the immediate rewards of STBBI testing and facilitate a greater uptake of screening. This systematic review was conducted to determine if patient incentives increase STBBI screening uptake in high-income countries. Methods Our review was performed according to the recommendations of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement and the Cochrane Handbook for Systematic Reviews of Interventions. MEDLINE, EMBASE, PsycINFO, CINAHL, Scopus, and Cochrane Library were searched from 2013 to 2020. Inclusion criteria were: English language, high-income countries, primary research studies, and age >13 years. Study quality was assessed using Joanna Briggs Institute quality assessment tools. Results The search yielded 6217 abstracts.13 studies met the inclusion criteria. Of these studies, five were located in the United States, three in the United Kingdom, and five in Australia. Seven studies took place in the community, five studies took place in clinical settings, and one study utilized a combination of community and clinical settings. Study design and intervention heterogeneity precluded meta-analysis or data pooling. Populations screened included: post-secondary students, parolees or probationers, youth, and inner-city emergency department patients. Incentivized STBBI tested were HIV (n=5), chlamydia (n=7), and multiple infections (n=1). Incentives offered were monetary (cash/gift cards/not specified) (n=8), non-monetary (n=2), and mixed (n=3). Conclusion Both monetary and non-monetary incentives enhance STBBI screening in high-income countries. Incentivized testing programs are most effective when developed specific to context and target population. Further research is needed to analyze incentivized screening across similar study designs and to evaluate long-term effectiveness.
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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 | 0.050 | 0.144 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.011 |
| Bibliometrics | 0.014 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 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".