A core outcomes set for clinical trials of interventions for young adults with type 1 diabetes: an international, multi-perspective Delphi consensus study
Bibliographic record
Abstract
BACKGROUND: Achieving consensus from a range of relevant stakeholders about an agreed set of core outcomes to be measured and reported as a minimum in clinical trials has the potential to enhance evidence synthesis and make findings more relevant and applicable. Intervention research to improve outcomes for young adults with type 1 diabetes (T1DM) is hampered by inconsistent use of outcome measures. This population frequently struggles to manage their condition and reports suboptimal clinical outcomes. Our aim was to conduct an international, e-Delphi consensus study to identify a core outcome set (COS) that key stakeholders (young adults with T1DM, diabetes health professionals, diabetes researchers and diabetes policy makers) consider as essential outcomes for future intervention research. METHODS: Using a list of 87 outcomes generated from a published systematic review, we administered two online surveys to a sample of international key stakeholders. Participants in the first survey (survey 1; n = 132) and the second survey (survey 2; n = 81) rated the importance of the outcomes. Survey 2 participants received information on total mean rating for each outcome and a reminder of their personal outcome ratings from Survey 1. Survey 2 results were discussed at a consensus meeting and participants (n = 12: three young adults with T1DM, four diabetes health professionals, four diabetes researchers and one diabetes policy maker) voted on outcomes. Final core outcomes were included provided that 70% of consensus group participants voted for their inclusion. RESULTS: ); level of clinic engagement; and perceived level of control over diabetes. CONCLUSIONS: This study is the first to identify a COS for inclusion in future intervention trials to improve outcomes for young adults with T1DM. Use of this COS will improve the quality of future research and increase opportunities for evidence synthesis. Future research is necessary to identify the most robust outcome measure instruments.
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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 | 0.577 | 0.479 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.010 | 0.007 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.004 | 0.017 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".