Testing an Electronic Patient-Reported Outcome Platform in the Context of Traumatic Brain Injury: PRiORiTy Usability Study
Bibliographic record
Abstract
Background: Traumatic brain injury (TBI) is a significant public health issue and a leading cause of death and disability globally. Advances in clinical care have improved survival rates, leading to a growing population living with long-term effects of TBI, which can impact physical, cognitive, and emotional health. These effects often require continuous management and individualized care. Traditional paper-based assessments can be cumbersome, potentially impeding regular monitoring of patient-reported outcomes (PROs). Electronic PROs (ePROs) offer a promising alternative by enabling real-time symptom tracking, which can facilitate early identification of issues, support shared decision-making, and improve outcomes for patients with TBI. Objective: This study evaluates the usability of an ePRO platform-Atom5-for individuals with TBI. By analyzing how patients use the system to report their symptoms, the study aims to identify usability issues, assess user satisfaction, and determine the potential of Atom5 to support ongoing patient-centered care. Methods: Atom5 was customized to enable individuals with TBI to report their symptoms. Usability testing was conducted through one-on-one sessions with participants recruited from Headway UK-an organization supporting brain injury survivors. Each participant took part in cognitive interviews using with the "Think Aloud" method, encouraging them to verbalize their thoughts and experiences while using the platform. This approach provided qualitative insights into areas of difficulty, usability strengths, and accessibility barriers. User satisfaction was quantitatively assessed with a brief 4-item questionnaire based on the System Usability Scale. Usability outcomes were analyzed for critical and noncritical errors, focusing on user experience and overall satisfaction. Results: In total, 9 participants completed a single usability testing session using Atom5, including 4 men, 4 women, and 1 nonbinary individual; 4 participants were under 55 years old, and 6 had their TBI <10 years ago. Finally, 8 participants used an Android device. The platform included measures for anxiety (Generalized Anxiety Disorder-2 item), depression (Patient Health Questionnaire-2), posttraumatic stress disorder (Posttraumatic Stress Disorder checklist 2), and TBI-specific quality of life (Traumatic Brain Injury - Quality of Life Short form) and a total of 26 questions. Overall, all participants were satisfied with the system, noting that it was easy to navigate and accessible despite difficulties in understanding some questions. Further, 6 participants encountered no errors, while 1 participant reported one critical error and 2 others reported one noncritical error each. The participants rated their overall satisfaction with the platform at an average score of 3.9 (SD 0.49) out of 5. Conclusions: This usability study suggests that individuals living with TBI can effectively report symptoms using the Atom5 ePRO platform, with generally high satisfaction and few usability issues, thereby enabling continuous monitoring and proactive symptom management. Future ePRO development should focus on inclusivity and adaptability to address the diverse needs of patients with TBI, ensuring these tools can effectively support a wide range of users.
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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 | 0.022 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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".