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Implementation science is increasingly recognized as essential for achieving the health-related sustainable development goals (SDGs), particularly in low- and middle-income countries (LMICs), where health systems often face resource constraints, fragmented priorities, and persistent inequities, which make it more difficult to generate real and positive impacts on society. While the field has advanced in high-income countries, the frameworks and tools developed there do not always apply to LMIC contexts, so the following question remains, how can LMICs ensure that research not only grows in volume but also contributes to measurable improvements in population health? We propose a conceptual framework combining meta-science, scientometrics, evidence-based research and medicine, and population health metrics to inform research and implementation decisions in LMICs. Meta-science supports methodological appraisal, scientometrics identifies potential mismatches in research attention, and evidence-based research and medicine inform research justification and local applicability. Population health metrics guide prioritization and monitoring without independently establishing causal impact. These elements create a pathway that moves beyond measuring productivity to assessing real-world impact. A proposed research relevance dashboard specifies indicators and responsibilities, with application adapted to institutional capacity. This framework could support alignment with SDG 3 (Good Health and Wellbeing) and SDG 10 (Reduced Inequalities), but its feasibility and incremental value require empirical evaluation.
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Lozada-Martinez et al. (2026) studied this question.
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