Guidelines for Creating Senior-Friendly Product Instructions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Although older adults feel generally positive about technologies, many face difficulties when using them and need support during the process. One common form of support is the product instructions that come with devices. Unfortunately, when using them, older adults often feel confused, overwhelmed, or frustrated. In this work, we sought to address the issues that affect older adults’ ability to successfully complete tasks using product instructions. By observing how older adults used the product instructions of various devices and how they made modifications to simplify the use of the instructions, we identified 11 guidelines for creating senior-friendly product instructions. We validated the usability and effectiveness of the guidelines by evaluating how older adults used instruction manuals that were modified to adhere to these guidelines against the originals and those that were modified by interaction design researchers. Results show that, overall, participants had the highest task success rate and lowest task completion time when using guideline-modified user instructions. Participants also perceived these instructions to be the most helpful, the easiest to follow, the most complete, and the most concise among the three. We also compared the guidelines derived from this research to existing documentation guidelines and discussed potential challenges of applying them.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it