The impact of severe osteogenesis imperfecta on the lives of young patients and their parents – a qualitative analysis
Bibliographic record
Abstract
BACKGROUND: Osteogenesis imperfecta (OI) is a rare genetic disorder that causes increased bone fragility. Living with, caring for, and parenting a child with OI are all highly demanding and challenging. This study is a temporal analysis of the impact of severe OI on the lives of young patients and their parents. METHODS: This study was carried out at the Shriners Hospital for Children, a pediatric orthopedic hospital located in Montreal, Canada. Using qualitative interpretative description, we conducted semi-structured interviews with 24 subjects - 12 young patients diagnosed with severe OI and 12 of their parents. The interview data were subject to a predominantly inductive open thematic analysis and a temporal comparative analysis. We did a retrospective chart review to complement our data collection. RESULTS: We found that the impact of severe OI on the young patients and their parents was characterized by four themes: 1) Starting at the time of diagnosis, a series of stages shaped life and the return to every day "normal", 2) Living with OI was full of "ups and downs" throughout life, 3) Every day "normal" life with OI consisted of significant changes for parents and challenges for the whole family, and 4) Living with OI generated some positive experiences. CONCLUSION: This study contributes to a better theoretical understanding of the impact of severe OI on families. It also has some practical implications for the development of effective support systems for patients with severe OI and their families.
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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 | 0.009 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.008 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| 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".