Qualitative study to support the content validity of the immune thrombocytopenia (ITP) Life Quality Index (ILQI)
Bibliographic record
Abstract
Immune thrombocytopenia (ITP) is an acquired immune-mediated disorder. Bleeding is the primary symptom that presents in varying severities. ITP has a negative impact on health-related quality of life (HRQoL). The ITP Life Quality Index (ILQI) was developed as a 10-item patient-reported outcome measure to assess impact on HRQoL in ITP. The objective of the present study was to confirm the content validity of the ILQI with a qualitative interview study in the UK involving 15 adult participants with ITP. Combined concept elicitation (CE) and cognitive debriefing (CD) interviews were conducted to explore the symptoms and impacts associated with ITP and confirm content validity of the draft ILQI. The CE phase elicited 14 ITP symptom concepts, including: bruising (all 15 patients, 100%), fatigue (14, 93·3%) and bleeding gums/blood blisters (13, 86·7%). Impacts included decreased ability to participate in sport (all 15 patients, 100%) and anxiety (12, 80%). The CD phase resulted in an adjustment to the ILQI recall period from 1 week to 'the past month'. Updates were made to improve relevance and response options. The qualitative interviews support the content validity of the ILQI and confirm that the concepts assessed are relevant and consistently understood and interpreted by adult patients with ITP.
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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 | 0.028 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".