User Experiences of the McMaster Optimal Aging Portal’s Evidence Summaries and Blog Posts: Usability Study
Bibliographic record
Abstract
BACKGROUND: Evidence summaries and blogs can support evidence-informed healthy aging, by presenting high-quality health research evidence in plain language for a nonprofessional (citizen) audience. OBJECTIVE: Our objective was to explore citizens' perceptions about the usability of evidence summaries and blog posts on the Web-based McMaster Optimal Aging Portal. METHODS: Twenty-two citizens (aged 50 years and older) and informal caregivers participated in a qualitative study using a think-aloud method and semistructured interviews. Eleven interviews were conducted in person, 7 over the telephone, and 4 by Skype. RESULTS: We identified themes that fell under 4 user-experience categories: (1) desirability: personal relevance, (2) understandability: language comprehension, grasping the message, dealing with uncertainty, (3) usability: volume of information, use of numbers, and (4) usefulness: intention to use, facility for sharing. CONCLUSIONS: Participants recognized that high-quality evidence on aging was valuable. Their intended use of the information was influenced by how much it applied to their own health circumstances or those of a loved one. Some specific formatting features that were preferred included consistent layout, content organized by subheadings, catchy titles, numerical information summarized in a table, and inclusion of a glossary.
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How this classification was reachedexpand
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".