Strategies for improving primary care for adolescents and young adults transitioning from pediatric services: perspectives of Canadian primary health care professionals
Bibliographic record
Abstract
BACKGROUND: Family physicians and other members of the primary health care (PHC) team may be ideally positioned to provide transition care to adolescents and young adults (AYAs; aged 12-25 years) exiting pediatric specialty services. Potential solutions to well-known challenges associated with integrating PHC and specialty care need to be explored. OBJECTIVE: To identify strategies to transition care by PHC professionals for AYAs with chronic conditions transitioning from pediatric to adult-oriented care. METHODS: Participants were recruited from six Primary Care Networks in Calgary, Alberta. A total of 18 semi-structured individual interviews were completed, and transcribed verbatim. Data were analyzed using a qualitative description approach, involving thematic analysis. RESULTS: Participants offered a range of strategies for supporting AYAs with chronic conditions. Our analysis resulted in three overarching themes: (i) educating AYAs, families, and providers about the critical role of primary care; (ii) adapting existing primary care supports for AYAs and (iii) designing new tools or primary care practices for transition care. CONCLUSIONS: Ongoing and continuous primary care is important for AYAs involved with specialty pediatric services. Participants highlighted a need to educate AYAs, families and providers about the critical role of PHC. Solutions to improve collaboration between PHC and pediatric specialist providers would benefit from additional perspectives from providers, AYAs and families. These findings will inform the development of a primary care-based intervention to improve transitional care.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.023 | 0.004 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".