Development of a core outcome set for multimorbidity trials in low- and middle-income countries (COSMOS): Study Protocol
Bibliographic record
Abstract
Abstract Introduction ‘Multimorbidity’ describes the presence of two or more long-term conditions, which can include communicable and non-communicable diseases, and mental disorders. The rising global burden from multimorbidity is well-documented, but trial evidence for effective interventions in low- and middle-income countries (LMICs) is limited. Selection of appropriate outcomes is fundamental to trial design to ensure cross-study comparability, but there is currently no agreement on a core outcome set (COS) to include in trials investigating multimorbidity specifically in LMIC. Our aim is to develop international consensus on two COS for trials of interventions to prevent and treat multimorbidity in LMIC settings. Methods and Analysis Following methods recommended by the Core Outcome Measures in Effectiveness Trials (COMET initiative), the development of these two COS will occur in three stages: (1) generation of a long list of potential outcomes for inclusion; (2) two-round online Delphi surveys; and (3) consensus meetings. First, to generate an initial list of outcomes, we will conduct a systematic review of multimorbidity intervention and prevention trials and interviews with people living with multimorbidity and their caregivers in LMICs. Outcomes will be classified using an outcome taxonomy. Two-round Delphi surveys will be used to elicit importance scores for these outcomes from people living with multimorbidity, caregivers, healthcare professionals, policy makers, and researchers in LMICs. Finally, consensus meetings will be held to discuss the Delphi survey results and agree outcomes for inclusion in the two COS. Ethics and dissemination The study has been approved by the Research Governance Committee of the Department of Health Sciences, University of York, UK [HSRGC/2020/409/D:COSMOS]. Each participating country/research group will obtain local ethics board approval. Informed consent will be obtained from all participants. We will disseminate findings through peer-reviewed open access publications, and presentations at global conferences selected to reach a wide range of LMIC stakeholders. Trial registration PROSPERO ID CRD42020197293 COMET https://www.comet-initiative.org/Studies/Details/1580 Strengths and limitations of this study The development process follows guidelines and best practice recommendations for developing core outcome sets and integrates four sources of information. Interviews with people living with multimorbidity and caregivers are conducted in several LMICs (in South Asia, Africa and Latin America), by local teams, and in local languages to identify outcomes relevant to them. The Delphi survey and consensus meetings are conducted in English which limits the breadth of participation in these stages of the process. Despite involvement of a wide range of LMIC stakeholders in the process, there may be some limitations to the generalisability of the final core outcome sets due to the heterogeneity of target conditions and the diversity of countries, cultures and experiences.
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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 | 0.162 | 0.145 |
| Meta-epidemiology (narrow) | 0.005 | 0.005 |
| Meta-epidemiology (broad) | 0.009 | 0.009 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.076 | 0.021 |
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".