Establishing the Feasibility of a Tablet-Based Consent Process with Older Adults: A Mixed-Methods Study
Bibliographic record
Abstract
Purpose of the Study: This mixed-methods study explored the feasibility and acceptability of using a tablet-based research consent process with adults aged ≥65 years. Design and Methods: In the first phase, focus group participants reported on their perceptions of a tablet-based consent process. In the second phase, older adults were randomized to view either a tablet-based or paper-based consent for a mock clinical trial. Measurements included: time to complete, adverse/unexpected events, user-friendliness, immediate comprehension, and retention at a 1-week delay. Results: Focus group participants (N = 15) expressed interest in the novel format, cautioning that peers would need comprehensive orientation to use the technology. In the randomized pilot (N = 20), retention was 100% and all participants completed the protocol without the occurrence of adverse/unexpected events. Although the participants took longer to complete the tablet-based consent than the paper-based version, user-friendliness, immediate comprehension, and retention of the tablet-based consent were similar to the paper-based consent. Discussion and Implications: The findings suggest that a tablet-based consent process is feasible to implement with older adults and acceptable to this population, but we would underscore that efforts to optimize design of tablet-based consent forms for older adults are warranted.
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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 | 0.195 | 0.183 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".