Abstract 5: Impact of Community Education Program for Retinoblastoma in Tanzania,
Bibliographic record
Abstract
Abstract Purpose: Over 85% of the 400,000 new pediatric cancer diagnoses annually occur in low- and middle- income countries (LMICs), where limited awareness and inadequate health system capacity contribute to poor outcomes. Retinoblastoma (RB), the most common pediatric eye cancer, is curable if diagnosed early. However, in Tanzania, 70% of RB patients present with vision loss, and survival rates are <30%. This study aimed to pilot a multi-component education intervention to improve community awareness of RB. Methods: Culturally adapted media (posters, retinoblastoma education song, and in person community based education and screening event) were developed to address community knowledge gaps and retinoblastoma misconceptions. Messaging was iteratively refined using a learner verification process with input from a community advisory board. A pre-post study design surveyed 200 participants (50 case and 50 control before and after intervention) to assess community knowledge, attitudes, and screening uptake. Impact of media exposure was correlated with intervention outcomes. Results: The intervention group demonstrated a significant 60% increase (p<0.001) in knowledge scores after the intervention, while no change was observed in the control group. Favorable attitudes toward RB screening increased significantly from 32% to 100% (p<0.001) in the intervention group but remained unchanged in the control group. Screening uptake improved from 0% to 22% among participants in the intervention group, whereas no participants in the control group brought their children for screening. Among media formats, the radio program was the most impactful, with 76% of participants exposed, followed by 64% attending awareness events and 8% viewing community posters. Conclusion: A multi-component intervention combining radio-based education, community events, and provider training significantly improved RB awareness, attitudes, and early screening uptake in an LMIC setting. These findings underscore the importance of tailored educational strategies and healthcare capacity building in reducing childhood cancer disparities in resource-limited settings. Citation Format: Richard Mhone, Mastidia Maximillian, Erica Sanga, Ashish Khanchandani, Perpetua Hhary, Heronima Joas, Kristin Schroeder. Impact of Community Education Program for Retinoblastoma in Tanzania [abstract]. In: Proceedings of the 13th Annual Symposium on Global Cancer Research; 2025 Sep 16. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2025;34(12_Suppl):Abstract nr 5.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".