Readability of advance directive documentation in Canada: a cross-sectional study
Bibliographic record
Abstract
BACKGROUND: In the Canadian context, health literacy has been shown to depend on place of birth, education level, socioeconomic status, language spoken and geographic location. This study seeks to determine whether currently available advance directive documentation in Canada is written in accordance with the average reading level of the population and to assess whether recommendations for health literacy are currently being met. METHODS: A cross-sectional study design was used. Patient-oriented English-language advance directive documents (brochures and/or forms) were obtained from the health agency websites of all Canadian provinces and territories and analyzed for readability using the Flesch-Kincaid Grade Level and Flesch Readability Ease scales. RESULTS: Advance directives in Canada are distinct from one another and surpass the recommended reading level by 4.5 ± 1.4 grade levels on average (95% confidence interval 8.7-10.3) with the hardest-to-read documents existing in Ontario, Quebec and Alberta. INTERPRETATION: These results demonstrate that the provincial and territorial governments issuing advance directive documentation have fallen short of their fiduciary responsibility to provide documents that facilitate health literacy. Addressing this shortcoming can result in increased patient engagement in advance directive completion while promoting patient autonomy.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".