Evaluating the model of offering expanded genetic carrier screening to high school students within the Sydney Jewish community
Bibliographic record
Abstract
Programs offering reproductive genetic carrier screening (RGCS) to high school students within the Ashkenazi Jewish community in several countries including Canada and Australia have demonstrated high uptake and retention of educational messages over time. This study was undertaken to evaluate whether testing for an expanded number of conditions in a high school setting would impact the effectiveness of education. In this questionnaire-based study, genetic carrier testing for nine conditions was offered to 322 year 11 students from five high schools, with students attending a compulsory 1-h education session prior to voluntary testing. Comparison of pre- and post-education measures demonstrated a significant increase in knowledge, positive attitudes, and reduced concern immediately after the education session. Retention of knowledge, measures of positive attitude, and low concern over a 12-month period were significantly higher than baseline, although there was some reduction over time. In total, 77% of students exhibited informed choice regarding their intention to test. A significant increase in baseline knowledge scores and positive attitude was also demonstrated between our original 1995 evaluation (with testing for only one condition) and 2014 (testing for nine conditions) suggesting community awareness and attitudes to RGCS have increased. These findings validate the implementation of effective education programs as a key component of RGCS and are relevant as gene panels expand with the introduction of genomic technologies.
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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 | 0.009 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".