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Intervention strategies for user interaction

SenseI (Sensor based Engagement for Improved Health)

Description/Objectives


WP2 concerns a) the development of intervention strategies based on the physical, mental and social state assessment (WP1) and a user’s health profile, and b) the communication and display of health-related exercise advices that are relevant for the user in the specific real-time context of exercising. User-specific intervention programs will be designed based on the user’s amount and type of exercise and the user’s mental and social state.

Community health profiling

The community health profiling provides a snap shot of the health status of the population involved, focusing on the life style aspects targeted in the project. A framework for this health profile will be produced based on the RIVM model of health. Health data will be systematically gathered through The Amsterdam Health Monitor in cooperation with the RIVM and CBS.

Subgroup health profiling

For profiling the subgroups, we follow the asset-based approach (Morgan & Ziglio, 2007). Assets are any resource, skill or knowledge that enhances the ability of individuals, families and neighborhoods to get and sustain an active and healthy lifestyle. Specifically, we will use the Motivational Interviewing and Structured Interview Matrix (SIM; O'Sullivan et al, 2012), which includes contextual evaluation, identification of effective motivational strategies, inventory of the needs, wishes, habits, knowledge, expectations and app-experience of our set of target (sub)groups.

Evaluation and design of overall interaction paradigm and motivational agent behaviour

We will evaluate and design the human-agent interaction by identifying the user requirements for interaction through context analysis of the target users’ lifestyle, exercise routines, rituals and habits around exercising and smart-phone usage patterns. A limited set of main interaction paradigms are evaluated and compared to identify one or two effective system roles (for instance should the system act as a buddy, information provider, game, or coach). Based on the intervention programs developed by VU-FHMS, UT will evaluate and design persuasive system behaviours to optimise user compliance and habit-formation as well as satisfaction in using the system.

Physical, mental/emotional and social feedback

The output of the algorithms developed in this work package to detect physical (i.e., quantity and quality of exercise), mental (i.e., emotion-related user states such as stress and fatigue) and social aspects of exercising will be used to determine the intervention strategies. Based on the quantity of exercise in relation to the individual user’s aims and objectives, we will develop intervention programs aimed at improving the health status of the individual in question. Based on the quality of exercise in relation to the individual user’s aims and objectives, we will develop intervention programs aimed at improving the quality of movement (e.g., cadence, economy, fluency etc. of walking and running). In addition, based on the explicit verbal report data and the implicit voice data (UT and HvA-DCMI), guidelines for specific individualized interventions with regard to attention, mood/emotion and subjective fatigue, will be implemented.

WP Leader: