Community based Primary Care for Adolescents and Young Adults Transitioning From Pediatric Specialty Care: Results from a Scoping Review
Bibliographic record
Abstract
Background:Ongoing primary care during adolescence is recommended by best practice guidelines for adolescents and young adults (AYAs; ages 12-25) with chronic conditions. A synthesis of the evidence on the roles of Primary Care Physicians (PCPs) and benefits of primary care is needed to support existing guidelines.Methods:We used Arksey and O’Malley’s scoping review framework, and searched databases (MEDLINE, EMBASE, PsychINFO, CINAHL) for studies that (i) were published in English between 2004 and 2019, (ii) focused on AYAs with a chronic condition(s) who had received specialist pediatric services, and (iii) included relevant findings about PCPs. An extraction tool was developed to organize data items across studies (eg, study design, participant demographics, outcomes).Results:Findings from 58 studies were synthesized; 29 (50%) studies focused exclusively on AYAs with chronic health conditions (eg, diabetes, cancer), while 19 (33%) focused exclusively on AYAs with mental health conditions. Roles of PCPs included managing medications, “non-complex” mental health conditions, referrals, and care coordination, etc. Frequency of PCP involvement varied by AYAs; however, female, non-Black, and older AYAs, and those with severe/complex conditions appeared more likely to visit a PCP. Positive outcomes were reported for shared-care models targeting various conditions (eg, cancer, concussion, mental health).Conclusion:Our findings drew attention to the importance of effective collaboration among multi-disciplinary specialists, PCPs, and AYAs for overcoming multiple barriers to optimal transitional care. Highlighting the need for further study of the implementation of shared care models to design strategies for care delivery during transitions to adult 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 | 0.030 | 0.111 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.008 |
| Bibliometrics | 0.025 | 0.027 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".