Increased hepatitis <scp>C</scp> virus vaccine clinical trial literacy following a brief intervention among people who inject drugs
Bibliographic record
Abstract
INTRODUCTION AND AIMS: While people who inject drugs are at high risk of hepatitis C virus (HCV) infection and will be the target population for future HCV vaccine trials, little is known about clinical trial literacy (CTL) in this group. We assessed the impact of a brief intervention (BI) designed to improve HCV vaccine CTL among people who inject drugs in Sydney, Australia. DESIGN AND METHODS: People who inject drugs enrolled in a community-based prospective observational study between November 2008 and September 2010 (n = 102) completed a CTL assessment followed immediately by the BI. Post-test assessment was conducted at 24 weeks. RESULTS: The median age of the sample was 27 years, 73% were male and 60% had 10 or less years of schooling. The median time since first injection was 5 years and 20% reported daily or more frequent injecting. The mean number of correct responses increased from 5.3 to 6.3/10 (t = -4.2; 101df, P < 0.001) 24 weeks post-intervention. Statistically significant differences were observed for three knowledge items with higher proportions of participants correctly answering questions related to randomisation (P = 0.002), blinding (P = 0.005) and vaccine-induced seropositivity (P = 0.003) post-intervention. DISCUSSION AND CONCLUSIONS: A significant increase in HCV vaccine CTL was observed, suggesting that new and relatively novel concepts can be learned and recalled in this group. These findings support the feasibility of future trials among this population. [Correction added on 21 November 2012, after first online publication: T-score for mean number of correct responses was corrected to '-4.2' in the Results section.]
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".