A Companion App to Support Rheumatology Patients Treated with Certolizumab Pegol: Results From a Usability Study
Bibliographic record
Abstract
BACKGROUND: Certolizumab pegol (CZP) is an anti-tumor necrosis factor drug approved for the treatment of multiple moderate to severe chronic inflammatory diseases. In the European Union, CZP is approved for administration by subcutaneous self-injection using a prefilled syringe, prefilled pen, or reusable electromechanical auto-injector (electronic device). CimplyMe is a companion app for use alongside CZP self-injection devices, designed to support CZP-treated patients self-managing their treatment and disease. OBJECTIVE: This study aimed to validate the usability of the companion app by demonstrating that tasks required for use can be performed successfully by intended end users. METHODS: We recruited 15 patients with moderate to severe rheumatoid arthritis, currently prescribed biologic treatment, and using apps on a smart phone. Patients were assessed on their ability to use the companion app in a setting designed to simulate a location where patients regularly administer biologic treatment. To assess the usability of the key features of the app, 8 critical and 3 noncritical tasks were designed. Patients' success on each task was recorded through observations or knowledge-based questions. Successes with difficulty and use errors were also recorded. If a patient made a use error at the first attempt, a second attempt was allowed. Second-attempt use errors were recorded as a task failure. RESULTS: A total of 207 first attempts at the 14 components of the 8 critical tasks were evaluated (3 patients failed to complete one component); 178 (86.0%) critical tasks were successfully completed at the first attempt. The remaining first attempts comprised 16 (7.7%) successes with difficulty and 13 (6.3%) use errors, which had to be repeated. One critical task was not re-attempted by one patient due to time constraints; however, there were no use errors in the 12 completed second attempts. A total of 107 first attempts at the 3 noncritical tasks were made, all of which (107/107, 100.0%) were completed without use errors. CONCLUSIONS: In simulated testing, patients were able to successfully use the companion app without formal training. This study suggests the companion app is easy to use and could help patients prescribed CZP better manage their treatment and disease.
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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 | 0.009 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".