Validating the green Brain Capital Model - Abdelraheem, Omnia Mahmoud (AUC Knowledge Fountain, 2025)
Background: Brain health is increasingly recognized as a critical asset for human and societal well-being, yet planetary crises threaten neurological integrity. The Green Brain Capital (GBC) model emerges as a novel framework linking cognitive capacity with ecological resilience. Objective: To define Green Brain Capital and identify its core attributes through a rigorous, multi-phase literature synthesis and expert consensus process. Methods: This study employed Schwartz-Barcott and Kim’s hybrid concept analysis model, which integrates theoretical inquiry with empirical validation. The theoretical phase included a scoping review to explore conceptualizations of Brain Capital and related constructs, followed by targeted systematic and rapid literature reviews to assess and refine the model’s core attributes. The empirical phase used a two-round Delphi consensus study with interdisciplinary experts to evaluate and validate proposed attributes. Searches were conducted in Scopus, PubMed, and ProQuest, with no restrictions on publication type, language, or date. Data were extracted using a standardized form, and expert consensus was achieved iteratively. Findings: The analysis yielded a structured definition of green brain capital including four core attributes: ecological intelligence, green skills, digital literacy, and environment and brain health. Delphi consensus (N = 31, retention = 93.9%) confirmed most components, with strong agreement on environmental determinants and ecological intelligence. Indicators were preliminary identified for operationalizing each attribute using high-quality, publicly available datasets. Interpretation: This study provides the first comprehensive conceptual framework for green brain capital. It offers a foundation for a potential index to guide strategy and benchmarking. While eco-emotions and digital literacy components merit further empirical exploration, the validated model offers a robust foundation for future research and multi-sectoral implementation. Funding: Supported by the AUC Climate Change Grant under Agreement Number: CCI-Cycle 2-SSE-IGHHE-M.S.03.