GAP2POP as a complementary hierarchical framework for aligning knowledge gaps, health priorities, evidence generation, and population influence-impact

Background Health research evaluation frameworks rarely integrate the identification of knowledge gaps and health needs, the definition of health priorities, evidence generation, the monitoring of population indicators, and the assessment of knowledge translation and population influence and impact within a single model. This structural absence lets research agendas drift from population needs, evidence be produced without correspondence to measurable health indicators, and the link between scientific knowledge and health outcomes remain unexamined. Methods We conceptually developed GAP2POP, a six-level hierarchical framework, through a narrative synthesis integrating principles from epidemiology, evidence-based medicine, implementation science, meta-research, and responsible research evaluation. The framework was designed to serve as both an evaluative tool, for auditing existing research portfolios, and a normative tool, for guiding future ones. Results GAP2POP organizes the research-to-outcome pathway into six hierarchical, bidirectional levels: identification of knowledge gaps and health needs, definition of health priorities, evidence generation, epidemiological outcome monitoring, knowledge translation and implementation, and assessment of population influence and impact. Each level has distinct conceptual functions, operational indicators, and methodological requirements, preventing the collapse of analytically distinct phenomena into one undifferentiated judgment of research value. The framework’s central contribution is a formal distinction between influence, the epistemic and discursive repercussion of research on scientific communities, clinical practice, or health policy without requiring causal demonstration of outcome modification, and impact, the causally attributable and demonstrable modification of a health outcome in a defined population. GAP2POP also identifies four categories of scientific incoherence, foundational, translational, implementational, and causal, that existing frameworks do not capture. Conclusions GAP2POP offers a complementary framework for aligning health research with population needs and evaluating research value with greater precision. By distinguishing influence from impact and locating where coherence breaks down along the research-to-outcome pathway, it may help investigators, funders, and health systems design and assess research agendas.

Authors

Institutions

Publication Details

Journal
F1000Research
Published
2026-09-22
DOI
https://doi.org/10.12688/f1000research.190215.1
Primary Topic
Health Policy Implementation Science
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
article

GAP2POP as a complementary hierarchical framework for aligning knowledge gaps, health priorities, evidence generation, and population influence-impact

Ivan David Lozada‐Martínez, Fabriccio J. Visconti-Lopez, Andy A. Acosta-Monterrosa, David A. Hernandez-Paez et al.
F1000Research
Health Policy Implementation Science
article

GAP2POP as a complementary hierarchical framework for aligning knowledge gaps, health priorities, evidence generation, and population influence-impact

Ivan David Lozada‐Martínez, Fabriccio J. Visconti-Lopez, Andy A. Acosta-Monterrosa, David A. Hernandez-Paez, Ernesto Mario Barceló-Castellanos, Indiana Luz Rojas-Torres, Ernesto Barceló-Martinez
article en

Abstract

Background Health research evaluation frameworks rarely integrate the identification of knowledge gaps and health needs, the definition of health priorities, evidence generation, the monitoring of population indicators, and the assessment of knowledge translation and population influence and impact within a single model. This structural absence lets research agendas drift from population needs, evidence be produced without correspondence to measurable health indicators, and the link between scientific knowledge and health outcomes remain unexamined. Methods We conceptually developed GAP2POP, a six-level hierarchical framework, through a narrative synthesis integrating principles from epidemiology, evidence-based medicine, implementation science, meta-research, and responsible research evaluation. The framework was designed to serve as both an evaluative tool, for auditing existing research portfolios, and a normative tool, for guiding future ones. Results GAP2POP organizes the research-to-outcome pathway into six hierarchical, bidirectional levels: identification of knowledge gaps and health needs, definition of health priorities, evidence generation, epidemiological outcome monitoring, knowledge translation and implementation, and assessment of population influence and impact. Each level has distinct conceptual functions, operational indicators, and methodological requirements, preventing the collapse of analytically distinct phenomena into one undifferentiated judgment of research value. The framework’s central contribution is a formal distinction between influence, the epistemic and discursive repercussion of research on scientific communities, clinical practice, or health policy without requiring causal demonstration of outcome modification, and impact, the causally attributable and demonstrable modification of a health outcome in a defined population. GAP2POP also identifies four categories of scientific incoherence, foundational, translational, implementational, and causal, that existing frameworks do not capture. Conclusions GAP2POP offers a complementary framework for aligning health research with population needs and evaluating research value with greater precision. By distinguishing influence from impact and locating where coherence breaks down along the research-to-outcome pathway, it may help investigators, funders, and health systems design and assess research agendas.

F1000ResearchVol. 15
Universidad Metropolitana (CO), University of the Coast (CO), Universidad Simón Bolívar (CO), Universidad Continental (PE), Massachusetts Institute of Technology (US)
Openalex Percentile: Top 6%
Health Policy Implementation Science
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.