Abstract

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.

School

School of Sciences and Engineering

Department

Institute of Global Health & Human Ecology

Degree Name

PhD in Applied Sciences

Graduation Date

Fall 2-15-2025

Submission Date

1-26-2026

First Advisor

Mohamed Salama

Second Advisor

Sungsoo Chun

Committee Member 1

Ahmed Mandil

Committee Member 2

Wagida Anwar

Committee Member 3

Anwar Abd El Naser

Extent

109p.

Document Type

Doctoral Dissertation

Institutional Review Board (IRB) Approval

Approval has been obtained for this item

Disclosure of AI Use

Thesis editing and/or reviewing

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Available for download on Wednesday, January 26, 2028

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