Cocreation of Integrated Interventions Addressing Noncommunicable Diseases and Environmental Degradation: Protocol for a Participatory Qualitative Study
Bibliographic record
Abstract
BACKGROUND: Addressing the adverse impacts of climate change on human health requires a global effort across multiple sectors. People living in low- and middle-income countries are particularly vulnerable to the health crises induced by climate change. Therefore, context specific solutions to tackle such challenges are essential to ensure preventive measures are in place for mitigating such risks. OBJECTIVE: This protocol aims to outline an integrated, participatory approach to cocreate multisectoral interventions tailored to specific environmental and health challenges in Bangladesh, India, and Indonesia. This work is done as part of the Global Health Research Centre for Non-Communicable Diseases and Environmental Change, funded by the National Institute for Health and Care Research. The overall aim is to collaboratively design and assess interventions that deliver dual benefits for planetary and human health. METHODS: To address the multisectoral nature of the challenges, this study will adopt a cocreation methodology that blends co-design and coproduction approaches. While the problem areas are specific to each context-tackling air pollution due to plastic burning in Indonesia, improving dietary diversity of public food procurement systems and managing extreme heat in India, and mitigating drinking water salinity in Bangladesh-the underlying cocreation framework is consistent and can be adapted to the needs of each study setting. The workflow consists of 4 key stages guided by an existing cocreation framework: planning, developing, evaluation, and reporting, with the 6 core elements of the Medical Research Council's complex intervention development framework embedded throughout the process. Drawing on the Double Diamond design process, the cocreation stage involves the following phases: codevelopment of a theory of change to explore potential context-specific interventions, short-listing of intervention components through gap analysis and prioritization, co-designing and coproducing selected intervention components, and assessing appropriateness and feasibility of intervention implementation. The cocreation process will be evaluated using the Research Quality Plus for Co‑Production framework to ensure methodological rigor and quality. RESULTS: Cocreation will take place over 6 months. Sampling and recruitment of cocreators (key stakeholders across sectors) have been completed in all 3 countries, with each cocreator group consisting of 20-30 members. We have developed the tools for the cocreation phase, informed by the findings from formative research, and received the necessary ethics approval to conduct these activities. We will generate a series of academic and nonacademic outputs on the cocreation process to disseminate the findings, as well as training materials for implementers to facilitate future adoption in similar settings. CONCLUSIONS: The cocreation of multisectoral interventions to tackle both environmental change and health is a comparatively new domain of implementation research. This protocol addresses the complex, multidimensional, and unique nature of such interventions by developing a structured and scientifically sound approach to be implemented in real-life settings. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/80368.
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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 | 0.153 | 0.104 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.009 | 0.008 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.007 | 0.007 |
| Research integrity | 0.008 | 0.011 |
| Insufficient payload (model declined to judge) | 0.046 | 0.009 |
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".