“You Take This Day by Day, Come What May”: A Qualitative Study of the Psychosocial Impacts of Living with Duchenne Muscular Dystrophy
Bibliographic record
Abstract
INTRODUCTION: Studies have reported health-related quality-of-life impacts of Duchenne muscular dystrophy (DMD); however, further research is needed to understand how those with DMD experience their condition and how psychosocial impacts evolve over time in response to disease progression. This qualitative study explores the social and emotional implications of key transitions, challenges and adaptations throughout the disease course from the perspective of patients and family caregivers. METHODS: Semi-structured interviews were conducted with men and boys with DMD, and/or their caregivers, in the USA. Thematic analysis was used to examine patterns in data collected across the interviews. RESULTS: Nineteen participants were included. Three major themes were identified: (1) barriers to participation are multifaceted; (2) an emotional journey shaped by 'inevitable progression;' (3) family provides critical tangible and emotional support. This study illustrates that psychosocial impacts of DMD are shaped by knowledge of the condition's natural history alongside other factors including the extent of social barriers, personal growth and adaptation, and family support. CONCLUSIONS: Findings provide insight into the strength and resilience with which individuals and their families respond to daily challenges and major clinical milestones and highlight the relative importance of loss of upper limb function as a transition in DMD affecting health-related quality-of-life.
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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 | 0.017 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.012 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| 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".