Understanding caregiver experiences with disease-modifying therapies for spinal muscular atrophy: a qualitative study
Bibliographic record
Abstract
OBJECTIVE: Spinal muscular atrophy (SMA) is a neuromuscular disorder that manifests with motor deterioration and respiratory complications. The paradigm of care is shifting as disease-modifying therapies including nusinersen, onasemnogene abeparvovec and risdiplam alter the disease trajectory of SMA. The objective of this study was to explore caregivers' experiences with disease-modifying therapies for SMA. DESIGN: Qualitative study including semistructured interviews with caregivers of children with SMA who received disease-modifying therapies. Interviews were audio recorded, transcribed verbatim, coded and analysed using content analysis. SETTING: The Hospital for Sick Children (Toronto, Canada). RESULTS: Fifteen family caregivers of children with SMA type 1 (n=5), type 2 (n=5) and type 3 (n=5) participated. There were two emerging themes and several subthemes (in parentheses): (1) inequities in access to disease-modifying therapies (variable regulatory approvals, prohibitively expensive therapies and insufficient infrastructure) and (2) patient and family experience with disease-modifying therapies (decision making, hope, fear and uncertainty). CONCLUSION: The caregiver experience with SMA has been transformed by the advent of disease-modifying therapies. Consistent and predictable access to disease-modifying therapies is a major concern for caregivers of children with SMA but is influenced by regulatory approvals, funding and eligibility criteria that are heterogenous across jurisdictions. Many caregivers described going to great lengths to access therapies, highlighting issues related to justice, such as equity and access. This diverse population reflects contemporary patients and families with SMA; their broad experiences may inform the healthcare delivery of other emerging orphan drugs.
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 | 0.012 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.007 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".