Exploring the Perceived Self-management Needs of Young Adults With Osteogenesis Imperfecta
Bibliographic record
Abstract
PURPOSE: To explore the perceived self-management needs of young adults with osteogenesis imperfecta (OI) with the goal of optimizing the self-management and transitional care services. METHODS: A qualitative descriptive study was performed with young adults diagnosed with OI. Two semistructured interviews were conducted before and after their first appointment with a nurse practitioner in the adult healthcare settings (a new partnership initiated by the pediatric hospital). Data were transcribed and descriptively analyzed. RESULTS: Seven participants with OI types I, III, and IV were interviewed. Ages ranged from 23 to 34 years, and years since discharge from the pediatric hospital ranged from 3 to 10. Four themes emerged including (1) dropped in the jungle, with no one to call; (2) they do not know how to treat me; (3) I feel like I'm going to get back in the loop; and (4) self-managing what I know, how I know. CONCLUSIONS: Similar to other childhood-onset conditions, adolescents and young adults with OI require education and mentorship, and clinicians in the adult healthcare system need to be prepared and supported to receive them. Collective efforts are needed to improve the self-management and transitional care needs for young adults with OI.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".