AI-enabled Playful Enhancement of Resilience and Self-Efficacy with Psychological Learning Theory
Improve resilience and self-efficacy
The outbreak of COVID-19 is a global public health emergency with multifaceted severe consequences for people’s lives and their mental health. The horizons of our daily lives, our ability to travel and interact freely have suddenly been limited. Distress and anxiety are normal responses to such extreme circumstances. One of the most reproducible findings in stress and resilience research is that the higher the controllability of a stress situation, the better individuals cope with this situation. One of the most reproducible findings in stress and resilience research is that the higher the controllability of a stress situation, the better individuals cope with this situation.
In order to support national organisations for psychosocial risk reduction, the contribution from technology innovation is required to propose assistive technologies to help people in responding appropriately in the crisis. AI-Refit will contribute to close a currently existing gap by strengthening resilience in a sustainable highly personalised way by engaging the individual person, reinforcing his or her self-efficacy in a totally innovative, highly adaptive, intelligent way. This technology aims at supporting a broad mass of people today suffering from the COVID-19 crisis but will also be suited to assist persons in individual crisis as well as in any globally affecting crisis in the future.
AI-Refit develops a radically innovative prototype of a digital care centre for (i) a playful AI- and sensor-enabled assessment of mental health and (ii) adaptively engaging into activities to prevent from depressive symptoms, severe anxiety and stress levels, to reinforce resilience and to promote self-efficacy of the individual, based on scientific psychological learning theory.
Firstly, AI-Refit will apply state-of-the-art AI methodology for smart assessment of mental health from a suite of serious games. AI-Refit is based on the digitAAL Life app that estimates neuropsychological assessment. AI-Refit will be extended by mental health based assessment. Secondly, psychological learning theory will provide an overall framework for AI-enabled behaviour change. Adaptive learning of self-regulatory processes will be applied to increase self-efficacy and self-control of the users based upon sensor-based feature vectors from playing games (see above) and feedback from recommended or self-initiated actions. Thirdly, the application of several wearables in the context of mental health will be evaluated for their efficiency and optional integration into the AI-enabled mental health analysis. The assessment of mental parameters, such as, executive functions, stress, emotion and activity will be applied by AI-enabled decision support to define a global resilience and depression sensitised risk factor estimation for early alert and professional consulting. A tele-assistance module will enable fully remote care assistance via professional or informal caregivers which is particularly suited for pandemic risk of social isolation.
JOANNEUM RESEARCH Forschungsgesellschaft mbH, Institute DIGITAL
University of Graz
Medical University of Graz
digitAAL Life GmbH
Project funded under the program ICT of the future