Dr. Pratibha Shah - United States of America
Abstract of the presentation
Ancient Life Philosophies – An Overlooked and Untapped Source for Deeper Wellness
Co-authors: None
Branch: Ayurveda
In today's fast-paced and hyper-digital world, wellness is often reduced to a checklist of habits or commercial trends, alienated from its deeper roots in meaning, connection, and balance. This presentation will explore how traditional worldviews—such as those found in Ayurveda, Indigenous knowledge systems, and Eastern philosophies—offer timeless, holistic frameworks for living well. These systems view health not just as the absence of disease but as a state of harmony within oneself, with others, and with nature.
A central theme of this talk is the importance of embracing a “two-eyed seeing” approach—originally articulated by Mi’kmaq Elder Albert Marshall—where we view the world through the strengths of both Indigenous and Western perspectives. Applied to health and wellness, this dual lens invites us to value empirical science alongside intuitive wisdom, and to integrate traditional healing practices with modern healthcare in respectful, synergistic ways.
Drawing on examples from Ayurveda and other ancient global systems, the presentation highlights how these philosophies cultivate inner awareness, seasonal living, purposeful action (dharma), and a reverent relationship with the environment—all essential components of sustainable well-being. By reframing wellness as a way of being rather than a set of outcomes, these traditions remind us that true health is cultivated from within and in alignment with the rhythms of life.
Ultimately, this presentation invites a reconnection with ancestral wisdom not as nostalgic revival, but as a vital resource for addressing today’s mental, emotional, and ecological crises. Through a two-eyed view, we can build a more inclusive and profound model of wellness—one that honors both ancient teachings and contemporary insights in the shared journey toward wholeness.
Please note that some of the texts also include machine-generated translations.
