Usability and Practicality of a Novel Mobile Attachment for Aural Endoscopy (endoscope-i): Formative Usability Study
Bibliographic record
Abstract
Background Our aims were to determine the usability and practicality of the endoscope-i system, a novel mobile attachment for aural endoscopy. This incorporated assessing the ease of use of the endoscope-i for different professionals, and ultimately improving the system by receiving constructive feedback. Objective Our objectives were to assess the ease of the endoscope-i system in conducting an aural examination and to assess its feasibility for integrating its use into clinical practice. We looked to assess its ease, effectiveness, and efficiency; to compare this to current practices with otoscopes; and to determine whether participants perceived the system to be able to produce an image of sufficient quality to make a clinical assessment. Finally, we wanted to assess the usefulness of the current training given for using the system, and we sought to gain feedback for the product from the differing specialists. Methods A formative usability study of the endoscope-i system was conducted with 5 health care professionals. Each session lasted 40 minutes and involved audio/video consent, a hands-on session, a private semistructured interview, and an option to discuss the device with a company representative. Results All participants found the endoscope-i system easy to use. The image quality was perceived to be greater than that achieved by current otoscopes. The ability to record images and view them retrospectively was also seen as a positive. Conclusions This study has not identified any significant issues relating to the design, functionality, or application of the endoscope-i. Participants perceived the system as superior to current options with a directly positive impact on their clinical practice.
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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 | 0.053 | 0.073 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".