Abstract:
The rapid integration of complex technology into every facet of daily life has fundamentally altered the landscape of human occupation, presenting challenges that traditional occupational therapy models were not designed to address. This paper introduces the Cyb-Occupational Systems Theory (COST), a novel conceptual framework developed to bridge the gap between established occupational science and the realities of human performance within technologically saturated environments. COST integrates foundational principles from systems engineering, cognitive neuroscience, and occupational therapy to propose a new, dynamic understanding of the person-occupation-environment transaction. The theory’s central construct is a taxonomy of ten distinct Cyb-Occupational Archetypes, defined as innate, self-organizing neuro-cognitive profiles that govern an individual’s habitual strategies for interacting with “engineered occupations.” These archetypes—such as The Architect, The Analyst, and The Operator—provide a granular lens through which to analyze performance, moving beyond broad categorizations of ability to a nuanced understanding of cognitive and processing styles. By reframing occupational performance as a function of the congruence between an individual’s dominant archetypes and the demands of a given technological system, COST offers a more precise, systems-based, and neurologically-grounded methodology for assessment and intervention. This paper will articulate the core tenets of COST, detail the ten proposed archetypes, and discuss the theory’s profound implications for enriching existing models like MOHO, PEO, and CMOP-E. Ultimately, COST provides a necessary theoretical evolution, equipping occupational therapy with the language and concepts required to enhance human participation, performance, and well-being in an increasingly engineered world.
Yıldırım, E. (2025). The Cyb-Occupational Systems Theory: A Neuro-Engineering Framework for Human Performance in the 21st Century. Zenodo. https://doi.org/10.5281/zenodo.17058027
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