Authors:
Oscar Castro
1
;
Jacqueline Mair
1
;
2
;
Florian von Wangenheim
1
;
3
and
Tobias Kowatsch
4
;
5
;
1
;
3
Affiliations:
1
Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence and Technological Enterprise (CREATE), Singapore
;
2
Saw Swee Hock School of Public Health, National University of Singapore, Singapore
;
3
Centre for Digital Health Interventions, Department of Management, Technology, and Economics, ETH Zurich, Zurich, Switzerland
;
4
School of Medicine, University of St. Gallen, St. Gallen, Switzerland
;
5
Institute for Implementation Science in Health Care, University of Zurich, Zurich, Switzerland
Keyword(s):
Taxonomy, Classification System, Ontology, Behavioral Medicine, Health Psychology, Evidence Synthesis, Systematic Review, Machine Learning.
Abstract:
Decades of research have created a vast archive of information on human behavior, with relevant new studies being published daily. Despite these advances, knowledge generated by behavioral science – the social and biological sciences concerned with the study of human behavior – is not efficiently translated for those who will apply it to benefit individuals and society. The gap between what is known and the capacity to act on that knowledge continues to widen as current evidence synthesis methods struggle to process a large, ever-growing body of evidence characterized by its complexity and lack of shared terminologies. The purpose of the present position paper is twofold: (i) to highlight the pitfalls of traditional evidence synthesis methods in supporting effective knowledge translation to applied settings, and (ii) to sketch a potential alternative evidence synthesis approach which leverages on the use of ontologies – formal systems for organizing knowledge – to enable a more effec
tive, artificial intelligence-driven accumulation and implementation of knowledge. The paper concludes with future research directions across behavioral, computer, and information sciences to help realize such innovative approach to evidence synthesis, allowing behavioral science to advance at a faster pace.
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