Transitions to Postsecondary Education in Young Adults with Hemoglobinopathies: Perceptions of Patients and Staff
Bibliographic record
Abstract
The transition from high school to postsecondary education can be challenging for adolescents and young adults (AYAs) with chronic health conditions. AYAs with hemoglobinopathies, including sickle cell disease, are a particularly vulnerable group whose academic performance is impacted by unpredictable disease symptoms. AYA with hemoglobinopathies may require academic accommodations to promote postsecondary success; however, accessing appropriate supports can be complicated. METHODS: Given these complexities, a multidisciplinary team in a pediatric outpatient clinic designed and implemented a standardized intervention to support AYA with hemoglobinopathies in navigating the transition to postsecondary education. A quality improvement (QI) project was initiated to support the referral of all eligible patients with hemoglobinopathies to postsecondary accessibility offices. This article will describe the development of the intervention and present key findings from qualitative interviews with patients (ages 18-19) and postsecondary accessibility office staff about the implemented resources as an initial step of an ongoing QI project. We used thematic analysis to identify themes across interviews with both groups of stakeholders. RESULTS: Key themes across both groups of interviews highlighted the benefits of the intervention, including (1) knowledge of available services, (2) registering early with appropriate documentation, and (3) self-advocacy. CONCLUSIONS: The preliminary qualitative findings validate the importance of embedding discussions about the transition to postsecondary education into routine clinic appointments for AYA with chronic health conditions. Clinical implications of this ongoing QI project for health care providers working with AYA with chronic health conditions will be shared.
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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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".