Test–retest reliability of a mobile application of the patient reported outcomes burdens and experiences (PROBE) study
Bibliographic record
Abstract
INTRODUCTION: The Patient Reported Outcomes, Burdens, and Experiences (PROBE) questionnaire is a patient-reported outcome tool that assesses quality of life and disease burden in people with haemophilia (PWH). AIM: To assesses the test-retest reliability of PROBE when completed using the mobile phone application. METHODS: We recruited PWH, including carriers, and individuals with no bleeding disorders who attended haemophilia-related workshops or via social media. Participants completed PROBE three times (twice on the app: T1 and T2, and once on the web, T3). Test-retest reliability was analysed for T1 versus T2 (app to app, time period one) and T2 versus T3 (app to web, time period two). RESULTS: We enrolled 48 participants (median age = 56 [range 27-78] years). Eighteen participants (37.5%) were PWH and seven (14.6%) were carriers. On general health domain questions, we found almost perfect agreement, except for a question on the frequency of use of pain medication in the last 12 months [Kappa coefficient (κ) .72 and .37 for time period one and two, respectively] and any use of pain medications (κ .75) for time period two. For haemophilia-related questions, we found substantial to perfect agreement, except for the questions on the number of joint bleeds in the previous 6 months for time period one (κ .49) and the number of bleeds in the previous two weeks for time period two (κ .34). CONCLUSIONS: The results demonstrate the reliability of the PROBE app. The app can be used interchangeably with the paper and web platforms for PROBE administration.
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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 | 0.021 | 0.042 |
| 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 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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; 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".