Feedback-guided Development for Patient Education Animation: HIV Transmission via Breastfeeding
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This thesis project uses animation to communicate the risk of HIV transmission via breastfeeding to mothers living with HIV in Canada. Current guidelines do not recommend breastfeeding for HIV+ mothers because there is always some level of risk. Knowledge of mother-to-child transmission is poor, and the cultural pressure to breastfeed has complex implications. It was essential that the science of transmission risk be conveyed in a clear and culturally sensitive manner, to allow women to make appropriate, informed decisions about whether or not to breastfeed. To accomplish this, we adopted a user-testing approach. Throughout development, the script, animatic, and character designs were presented for feedback to members of the target audience, healthcare providers, and representatives from Canadian HIV organizations in an iterative design process. At each round of feedback, the script, animatic, and visual assets were revised, and sent for further comment. Ongoing collaboration with the target audience helped us develop an animation with a wide diversity of characters, culturally sensitive metaphors, and nuanced descriptions of risk, in response to feedback that detailed desires about representation and identified how concepts were being misunderstood. User-testing approaches are necessary when creating patient education animations. Population needs, background, and context have a dramatic impact on patient understanding, and cannot be understood properly without user testing and direct feedback. Doing so helps prevent insensitive concepts and easily misinterpreted information, and thus is key to effective patient education animation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it