Typeface legibility of patient information leaflets intended for community-dwelling seniors
Bibliographic record
Abstract
BACKGROUND: there are guidelines available from a number of countries and organisations regarding the design of written information, as appropriate design is essential for effective communication. The design of leaflets should be evaluated, as written information that does not adhere to guidelines may not be effective for seniors. OBJECTIVE: to use current typeface guidelines to describe the design of health information leaflets. DESIGN: this was a cross-sectional study of leaflets from pharmacies and seniors' clinics. SETTING: community pharmacies, seniors' clinics in Edmonton, Canada. METHODS: health information leaflets and hydrochlorthiazide information sheets were collected. The body of each was evaluated, based on guidelines (from Canada, UK and USA). Adherence to recommendations was assessed descriptively. RESULTS: a total of 388 unique leaflets and 10 hydrochlorthiazide sheets were collected from 21 pharmacies and 3 clinics. Most leaflets were produced by pharmaceutical companies (42.8%) and contained disease information (43.8%). Only one-third of all leaflets used the minimum recommended point size (12 point), 18.6% followed American guidelines for line spacing (1.5 lines), but 77.1% had appropriate contrast. CONCLUSIONS: although guidelines are available, most leaflets did not meet recommendations. Improvements in the leaflet design should be considered to aid seniors in the uptake of information.
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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 | 0.008 | 0.062 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".