Development, Content Validity, and User Review of a Web-based Multidimensional Pain Diary for Adolescent and Young Adults With Sickle Cell Disease
Bibliographic record
Abstract
BACKGROUND: Vaso-occlusive pain, the hallmark of sickle cell disease (SCD), is a major contributor to morbidity, poor health-related quality of life, and health care utilization associated with this disease. There is wide variation in the burden, frequency, and severity of pain experienced by patients with SCD. As compared with health care utilization for pain, a daily pain diary captures the breadth of the pain experience and is a superior measure of pain burden and its impact on patients. Electronic pain diaries based on real-time data capture methods overcome methodological barriers and limitations of paper pain diaries, but their psychometric properties have not been formally established in patients with SCD. OBJECTIVES: To develop and establish the content validity of a web-based multidimensional pain diary for adolescents and young adults with SCD and conduct an end-user review to refine the prototype. MATERIALS AND METHODS: Following identification of items, a conceptual model was developed. Interviews with adolescents and young adults with SCD were conducted. Subsequently, end-user review with use of the electronic pain diary prototype was conducted. RESULTS: Two iterative cycles of in-depth cognitive interviews in adolescents and young adults with SCD informed the design and guided the addition, removal, and modification of items in the multidimensional pain diary. Potential end-users provided positive feedback on the design and prototype of the electronic diary. CONCLUSION: A multidimensional web-based electronic pain diary for adolescents and young adults with SCD has been developed and content validity and initial end-user reviews have been completed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.092 | 0.164 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| 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".