Disease-modifying therapies for spinal muscular atrophy: Family experience, ethical considerations, and the role of social determinants of health
Bibliographic record
Abstract
OBJECTIVES: Spinal muscular atrophy is a progressive neuromuscular condition associated with a complex chronic disease course. An in-depth understanding of the ethical issues and social determinants of health impacting the experiences of families and children living with this condition is critical to improving care delivery. We identified the ethical tensions faced by families caring for children with spinal muscular atrophy as well as the influence of social determinants of health in relation to their perception of novel disease-modifying therapies. DESIGN: Qualitative study including semi-structured interviews with caregivers of children with spinal muscular atrophy who received disease-modifying therapies. Interviews were audio recorded, transcribed verbatim, and coded. Thematic analysis was utilized to identify ethically salient themes. SETTING: The Hospital for Sick Children (Toronto, Canada)Results:Fifteen family caregivers of children with spinal muscular atrophy type 1 (n = 5), type 2 (n = 5), and type 3 (n = 5) participated. There were three core themes highlighted including (1) best interests of the child, (2) burden of care and associated moral distress, and (3) parent agency. These experiences were impacted by resources and social determinants of health. CONCLUSION: This study provides important insights into the ethical tensions and relevant social determinants of health impacting the caregiver experience. Understanding the experiences of diverse families will allow more appropriate resource distribution, better counselling and supports for families facing unique psychosocial challenges and treatment burdens, and overall improved delivery of patient and family-centered care.
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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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.008 | 0.008 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".