Palliative care in duchenne muscular dystrophy: A study on parents' understanding
Bibliographic record
Abstract
INTRODUCTION: Duchene muscular dystrophy (DMD) is a neuromuscular disease of childhood, which has clear progression. The international standardized care guidelines for DMD suggest that palliative care is essential for the affected children. OBJECTIVE: To explore the parent's understanding of palliative care services available for children with DMD and the challenges faced by them in utilizing the same. METHODS: A cross-sectional qualitative exploratory study was conducted among six families of boys diagnosed with DMD. A semi-structured interview guide with prompts was used to conduct in-depth interviews which lasted for an average of 1 h. Thematic analysis was done to identify the pattern or themes. RESULTS: and challenges." Awareness about palliative care services is the dominant theme identified as influencing rest of the experiences narrated by the parents of children with DMD. DISCUSSION: Integration of palliative care services from an early stage of the illness can help the child to make transition from one stage to another stage of the illness. To ensure the utilization of the available palliative care services, there is a need to create awareness about it among the general public. CONCLUSION: Introducing the concept of palliation of symptoms and ensuring quality of life of the child with DMD by accessing the available services can aid the parents to reach out for help for their child.
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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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| 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".