Measuring multimorbidity in research: Delphi consensus study
Why is this work in the frame?
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.
Full frame distilled prediction
Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
- Candidate categories
- Insufficient payload (model declined to judge)
- Consensus categories
- none
- Domain
- Candidate signal: noneConsensus signal: none
- Study design
- Candidate signal: ObservationalConsensus signal: Observational
- Genre
- Candidate signal: EmpiricalConsensus signal: Empirical
- Teacher disagreement score
- 0.363
- Threshold uncertainty score
- 0.998
- Validation status
machine_predicted_unvalidated·codex-gemma-dda1882f352a
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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.
- Teacher spread
- 0.152 · how far apart the two teachers sit on this one work
- Validation status
score_only:v0-immature-baseline· verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it
Abstract
Objective: To develop international consensus on the definition and measurement of multimorbidity in research. Design: Delphi consensus study. Setting: International consensus; data collected in three online rounds from participants between 30 November 2020 and 18 May 2021. Participants: Professionals interested in multimorbidity and people with long term conditions were recruited to professional and public panels. Results: 150 professional and 25 public participants completed the first survey round. Response rates for rounds 2/3 were 83%/92% for professionals and 88%/93% in the public panel, respectively. Across both panels, the consensus was that multimorbidity should be defined as two or more long term conditions. Complex multimorbidity was perceived to be a useful concept, but the panels were unable to agree on how to define it. Both panels agreed that conditions should be included in a multimorbidity measure if they were one or more of the following: currently active; permanent in their effects; requiring current treatment, care, or therapy; requiring surveillance; or relapsing-remitting conditions requiring ongoing care. Consensus was reached for 24 conditions to always include in multimorbidity measures, and 35 conditions to usually include unless a good reason not to existed. Simple counts were preferred for estimating prevalence and examining clustering or trajectories, and weighted measures were preferred for risk adjustment and outcome prediction. Conclusions: Previous multimorbidity research is limited by inconsistent definitions and approaches to measuring multimorbidity. This Delphi study identifies professional and public panel consensus guidance to facilitate consistency of definition and measurement, and to improve study comparability and reproducibility.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
The record
- Venue
- BMJ Medicine
- Topic
- Chronic Disease Management Strategies
- Field
- Medicine
- Canadian institutions
- not available
- Funders
- National Institute for Health Research Applied Research Collaboration WestNIHR Leicester Biomedical Research CentreNanyang Technological UniversityNational University of SingaporePeking UniversityNational Institute for Health Research Health Protection Research UnitNational Institute for Health and Care ResearchHealth Data Research UKJohns Hopkins UniversityUniversité de SherbrookeUniversity of Otago
- Keywords
- ComparabilityDelphi methodMedicineConsistency (knowledge bases)DelphiFamily medicineStatisticsComputer science
- Has abstract in OpenAlex
- yes