Taking Care of the Caregivers: A Quality‐of‐Life Measure for the Parents of Children With Transfusion‐Dependent Thalassemia
Bibliographic record
Abstract
BACKGROUND: Children with transfusion-dependent thalassemia (TDT), also known as thalassemia major, require monthly blood transfusions and regular iron chelation therapy for long-term survival. While the burden of caring for these children is recognized, little has been done to address the parents' experience. PROCEDURE: A 38-item parent self-report was included in the previously designed disease-specific tool, the transfusion-dependent quality-of-life questionnaire (TranQol), to identify the issues they may be facing. We wanted to ensure that the self-report was reliable and valid. Questionnaires were given to parents during their children's routine clinic visits as part of a multi-center North American study of the TranQol. Construct validity was assessed using Pearson's correlation with the Pediatric Quality of Life (PedsQL) Family Impact Module (FIM) (hypothesis: correlation of 0.4-0.6). RESULTS: Sixty-seven parents completed both the TranQol and PedsQL Family Impact Module questionnaires at baseline. There was substantial correlation (r = 0.76) between TranQol parent self-report scores (median 63, interquartile range [IQR]: 53-76) and PedsQL Family Impact Module scores (median 77, IQR: 59-89). CONCLUSIONS: The median PedsQL FIM score was similar to previously reported scores for parents of children with sickle cell disease. The TranQol parental burden tool demonstrated construct validity was internally reliable (Cronbach's α = 0.94) and had acceptable test-retest reliability (intraclass correlation coefficient [ICC] = 0.81), for future research into TDT. In addition, this tool could also be used to help clinicians assess the impact of the disease on parents to potentially target appropriate support and care that is required.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".