Healthcare transitions for adolescents with chronic life‐threatening conditions using a Delphi method to identify research priorities for clinicians and academics in Canada
Bibliographic record
Abstract
PURPOSE: Research has only begun to examine the complexity of transition to adulthood under illness conditions. A Delphi method may be utilized to identify pertinent research priorities for academics and clinicians in adolescent healthcare transitions and prioritize a framework for an ongoing programme of research. METHODS: Through a comprehensive recruitment strategy throughout Canada, 114 clinicians and academics were invited to participate in this national study. Three phases were conducted until consensus could be achieved for the five most pressing research priorities. RESULTS: Thirty-eight respondents completed at least one of the three phases of the process. All responses were analysed, and five questions in phase 3 achieving a level of consensus ranging 64-80% were identified as the top five research priorities. These questions included: skills and knowledge adolescents require for the transition process, how to measure success, the factors that influence a successful transition and whether good transitions improve health outcomes. CONCLUSIONS: The results of this study can inform and prioritize a framework for an ongoing programme of research in Canada. The inclusion of clinicians and academics ensures that the research agenda incorporates perspectives from the front-line work of individuals providing care to this population as well as individuals from the academic community with important knowledge and skills related to research approaches and methods.
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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 | 0.038 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.011 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.006 |
| 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".