A qualitative exploration of children's lives with rare diseases
Bibliographic record
Abstract
BACKGROUND: Rare diseases encompass a diverse group of debilitating and sometimes life-threatening conditions that affect a small percentage of the population, posing a significant public health challenge. Despite their rarity, around 70% of these diseases afflict children, yet limited research has focused on their experiences. This study aimed to gain insights into the day-to-day challenges children living with rare diseases face. METHODS: We conducted semistructured one-to-one interviews with 11 children and young people (7-16 years) diagnosed with a range of rare diseases, purposively sampled from a tertiary pediatric healthcare setting in Ireland. We analyzed the interview transcripts, and themes were devised inductively. RESULTS: Two themes were identified: "Knowledge and Understanding of Rare Diseases" and "Fitting in Versus Feeling Different." These themes emerged across various settings-the home, hospital, school, and social environments-to illustrate the impact of rare diseases on the participants' daily lives. A conceptual framework was developed to illustrate how the children's knowledge, experiences, and emotions shape their identity in a rare disease context. CONCLUSIONS: Our analysis revealed a complex interplay between the participants' sense of belonging and their awareness of being different, influenced by the manifestations and demands of their rare conditions or illnesses. This duality in their identity was most pronounced in social settings, where the participants felt the most significant impact of their rare diseases. Understanding this interplay sheds light on the unique social challenges children with rare medical conditions face. Raising awareness about these conditions could mitigate these children's social challenges, fostering a more inclusive society for those with rare diseases.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".