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As more behavioral health interventions move from traditional to digital platforms, the application of evidence-based theories and techniques may be doubly advantageous. First, it can expedite digital health intervention development, improving efficacy, and increasing reach. Second, moving behavioral health interventions to digital platforms presents researchers with novel (potentially paradigm shifting) opportunities for advancing theories and techniques. In particular, the potential for technology to revolutionize theory refinement is made possible by leveraging the proliferation of 'real-time' objective measurement and 'big data' commonly generated and stored by digital platforms. Much more could be done to realize this potential. This paper offers proposals for better leveraging the potential advantages of digital health platforms, and reviews three of the cutting edge methods for doing so: optimization designs, dynamic systems modeling, and social network analysis., Author(s): Arlen C. Moller [sup.1] [sup.2] , Gina Merchant [sup.3] , David E. Conroy [sup.4] , Robert West [sup.5] , Eric Hekler [sup.6] , Kari C. Kugler [sup.4] , Susan [...]

A central goal of behavioral medicine is the creation of evidence-based interventions for promoting behavior change. Scientific knowledge about behavior change could be more effectively accumulated using 'ontologies.' In information science, an ontology is a systematic method for articulating a 'controlled vocabulary' of agreed-upon terms and their inter-relationships. It involves three core elements: (1) a controlled vocabulary specifying and defining existing classes; (2) specification of the inter-relationships between classes; and (3) codification in a computer-readable format to enable knowledge generation, organization, reuse, integration, and analysis. This paper introduces ontologies, provides a review of current efforts to create ontologies related to behavior change interventions and suggests future work. This paper was written by behavioral medicine and information science experts and was developed in partnership between the Society of Behavioral Medicine's Technology Special Interest Group (SIG) and the Theories and Techniques of Behavior Change Interventions SIG. In recent years significant progress has been made in the foundational work needed to develop ontologies of behavior change. Ontologies of behavior change could facilitate a transformation of behavioral science from a field in which data from different experiments are siloed into one in which data across experiments could be compared and/or integrated. This could facilitate new approaches to hypothesis generation and knowledge discovery in behavioral science., Author(s): Kai R. Larsen [sup.1] , Susan Michie [sup.2] , Eric B. Hekler [sup.3] , Bryan Gibson [sup.4] , Donna Spruijt-Metz [sup.5] , David Ahern [sup.6] , Heather Cole-Lewis [sup.7] [...]

This paper presents the Futurium platform used by Digital Futures, a foresight project launched by the European Commission's Directorate General for Communications Networks, Content and Technology (DG CONNECT). Futurium was initially developed with the primary purpose of hosting and curating visions and policy ideas generated by Digital Futures (Digital Futures was launched in July 2011 by DG CONNECT's Director General Robert Madelin following a prior DG CONNECT exercise called Digital Science.). However, it has turned into a platform on which to experiment with new policymaking models based on scientific evidence and stakeholder participation, referred to in this paper as 'Policy Making 3.0'. The platform hosts an online foresight toolkit to facilitate the joint creation of ideas to help design future policies. It leverages the potential of social networks, open data, semantic and knowledge mining technologies as well as participatory brainstorming techniques to engage stakeholders and harness their views and creativity to better inform policies that matter to them. The Futurium distinguishes between different variables, reflecting the emotional vs. rational mindsets of the participants, and offers the possibility to frame the engagement and co-creation process into multiple phases of a workflow. Futurium was developed to support Digital Futures, but its open architecture makes it easily adaptable to any policymaking/decision-making context where thinking ahead, participation, scientific evidence and agility are needed. Futurium is an early prototype implementation of the Policy Making 3.0 model, which is a long-term vision requiring further investigation and experimentation. The Futurium production website can be seen here: ec.europa.eu/digital-agenda/futurium. Keywords Policy making 3.0 * Foresight. Futures * Participatory policymaking * Crowdsourcing * Collective emotional intelligence * Collective rational intelligence . Evidence-based policy making * Data mining * Socialmedia * Complex systems * Digital futures * Futurium, 1 Rationale Nowadays, public policies need to be continuously reviewed and adapted to deal with unforeseen issues or to react to emergency situations such as coping with the consequences of [...]