Pharmaceutical pictograms: User-centred redesign, selection and validation
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
In an earlier study, several tested International Pharmaceutical Federation (FIP) pictograms did not achieve validity among older adults in Singapore. In this study, for 27 unvalidated FIP pictograms, we (1) developed variants of each pictogram, (2) elicited the most-preferred variant, and (3) assessed the validity of the most-preferred variant among older Singaporeans. In phase 1, up to three variants of the 27 pictograms were developed, based on older adults' feedback from a previous study. In phase 2, the most-preferred variant of 26 pictograms, which had two or three variants, was selected by 100 older participants. In phase 3, the 27 most-preferred variants (including the pictogram with only one variant) were assessed for validity – transparency and translucency – among 278 older participants (10 pictograms per participant). To evaluate transparency, participants were first asked: “If you see this picture on a medicine label, what do you think it means?” for each assigned pictogram. If they responded, they were asked, “How do you know?”, and if not, they were told, “Tell me everything you see in this picture”. Then, participants were shown their assigned pictograms again, one by one, and the pictogram's intended meaning was revealed to evaluate translucency. Pictograms were classified as valid (≥66% participants interpreted its intended meaning correctly [transparency criterion] and ≥ 85% participants rated its representativeness as ≥5 [translucency criterion]), partially valid (only transparency criterion fulfilled) or not valid. In phase 1, 77 variants of the 27 pictograms were developed. In phase 2, a majority of the most-preferred variants were selected by >50% participants. In phase 3, 10 (37.0%) of the 27 pictograms tested were considered valid, and five (18.5%) were partially valid. A higher proportion of pictograms portraying dose and route of administration and precautions were valid or partially valid, versus those depicting indications or side effects. Contextual redesigning and selection of pharmaceutical pictograms, which initially failed to achieve validity in a population, contributed to their validation. The redesigned validated pictograms from this study can be incorporated into relevant patient information materials in clinical practice.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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