Assessing the Usability of a Novel Toolkit for Creating Visual Key Information Pages for Informed Consent for Research: Mixed Methods Usability Study
Bibliographic record
Abstract
Background: Key information pages for informed consent require a concise summary of information to improve participant understanding but have not widely incorporated health literacy best practices. Objective: We previously developed a visual key information template to improve informed consent. In this study, we conducted usability testing of this customizable one-page key information template. Methods: We used the Designing for Accelerated Translation framework to plan for actionable, efficient usability testing. Participants (N=15) were asked to spend about 20 minutes using the visual key information template and engaging in a think-aloud protocol. They then responded to qualitative debrief questions about the template and validated measures of acceptability, appropriateness, and feasibility. Interviews were recorded, transcribed, and analyzed with a usability-focused codebook and thematic analysis. Results: The toolkit was positively received. Common usability challenges included interpreting instructions, condensing consent content, replacing and resizing icons, and fitting information into template boxes. Participants had positive experiences with toolkit elements, particularly with the icon library, and generally felt the toolkit was easy to use and encouraged simplification of information. Some participants noted not fully reviewing instructions before the study and discussed specific technical abilities as potential limitations of widespread use. We documented suggestions and made changes to the toolkit in response to feedback received. Conclusions: Overall, participants considered the toolkit to be appropriate, acceptable, and feasible. Additional implementation outcomes are being collected in a multisite stepped-wedge randomized trial. Further research may investigate changes to format and software that balances functionality with ease of use.
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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 | 0.244 | 0.231 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".