期刊
TRANSLATIONAL BEHAVIORAL MEDICINE
卷 6, 期 2, 页码 317-328出版社
OXFORD UNIV PRESS
DOI: 10.1007/s13142-016-0395-7
关键词
Behavior change; Implementation science; Research methods
资金
- Robert Wood Johnson Foundation [71995]
- National Science Foundation [IIS-1449751]
- National Heart Lung and Blood Institute [R01HL125440]
- Div Of Information & Intelligent Systems
- Direct For Computer & Info Scie & Enginr [1449751] Funding Source: National Science Foundation
Evidence-based practice is important for behavioral interventions but there is debate on how best to support real-world behavior change. The purpose of this paper is to define products and a preliminary process for efficiently and adaptively creating and curating a knowledge base for behavior change for real-world implementation. We look to evidence-based practice suggestions and draw parallels to software development. We argue to target three products: (1) the smallest, meaningful, self-contained, and repurposable behavior change modules of an intervention; (2) computational models that define the interaction between modules, individuals, and context; and (3) personalization algorithms, which are decision rules for intervention adaptation. The agile science process includes a generation phase whereby contender operational definitions and constructs of the three products are created and assessed for feasibility and an evaluation phase, whereby effect size estimates/casual inferences are created. The process emphasizes early-and-often sharing. If correct, agile science could enable a more robust knowledge base for behavior change.
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