Assessing Health Numeracy Among Community-Dwelling Older Adults
Bibliographic record
Abstract
Quantitative information occupies a central role within health care decision making. Despite this, numeracy has attracted little research attention. Therefore, the purpose of this study was to (1) describe the health numeracy skill of a nonclinical, Canadian community-based senior population and (2) determine the relationship between health numeracy skill and prose health literacy, education, and math anxiety in this population. A convenience sample of 140 men and women, 50 + years, completed a questionnaire assessing demographic details, math anxiety, functional health literacy (Shortened Test of Functional Health Literacy for Adults STOFHLA), general context numeracy, and health context numeracy skills. Most participants had adequate functional health literacy (prose and numeracy) as measured by the STOFHLA, poorer general context numeracy skill, higher health context numeracy skill, and moderate math anxiety. Approximately 36% of the variation in general context numeracy scores and 26% of the variation in health context numeracy scores were explained by prose health literacy skill (STOFHLA), math anxiety, and attained education. This research offers an initial assessment of health numeracy skills as measured by three existing numeracy scales among a group of independently functioning older Canadian adults. This work highlights the need for clarification of the numeracy concept and refinement of health numeracy assessment instruments. Moreover, identifying patients' numeracy strengths and weaknesses will enable the development of focused numeracy interventions and may contribute to moving individuals further along the continuum of health literacy proficiency.
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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 | 0.006 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".