Working Out the Kinks: Testing the Feasibility of an Electronic Pain Diary for Adolescents with Arthritis
Bibliographic record
Abstract
BACKGROUND: Current approaches to evaluating pain in children with chronic arthritis suffer from methodological problems. A real-time data capture approach using electronic diaries has been proposed as a new standard for pain measurement. However, there is limited information available regarding the development and feasibility of this approach in children. OBJECTIVES: The aim of the present study was to pilot test the e-Ouch electronic pain diary in terms of compliance and acceptability in adolescents with arthritis to further refine the prototype. METHODS: A descriptive study design -- with two iterative phases of testing, modifying the prototype and retesting -- was used. A purposive sample of 13 adolescents with mild to severe pain and disability was drawn from a large rheumatology clinic in a university-affiliated pediatric tertiary care centre in Canada over a four-week period in December 2004. Participants were signalled with an alarm to use the diary three times per day for a two-week period. Adolescents completed an electronic diary acceptability questionnaire. RESULTS: Overall mean compliance rates for phases 1 and 2 were 72.9% and 70.5%, respectively. Compliance was affected by the timing of data collection and technical difficulties. Children rated the diary as highly acceptable and easy to use. Phase 1 testing revealed aspects of the software program that affected compliance, which were subsequently altered and tested in phase 2. No further technical difficulties arose in phase 2 testing. CONCLUSIONS: Feasibility testing is a crucial first step in the development of electronic pain measures before use in clinical and research 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 | 0.022 | 0.049 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 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".