InterAction Lab, University of Trento 4/26/2018 Understanding Motivations of Older People to Engage in Socio-Technical Interventions for Active Ageing Mlađan Jovanović InterAction Lab, University of Trento mladjan.jovanovic@unitn.it

Context Problem Goals Means 4/26/2018 Context Problem Increase the number of older adults who engage in regular and sustained physical and social activities Goals Reduction of falls and traumatic events Improvement od physical, mental and emotional being Means Socio-technical intervention that builds on physical activity and social interaction Robotic friend that supports execution of everyday activities (FriWalk) Intelligent system that produces activities recommendation (FriTab)

4/26/2018 Problem Understanding and formulating motivations of older adults to engage in the intervention Prior to actual design Socio-technical context of engagement Personal level – why engaging in an activity Social level – why engaging in social networking Technological level – why using the technology Active Ageing Physically, mentally and socially active lifestyle as we age

Active Ageing determinants Health - a state of complete physical, mental, and social well-being (not merely the absence of frailty or infirmity) Participation - the ability to engage in socio-economic and cultural activities (e.g. attending cultural activities, volunteering, being part of local communities, or interacting with family and friends) Security - having adequate protection and care when assistance is required while maintaining as much autonomy and independence as possible

4/26/2018 Proposed solution Using existing motivational framework to analyse, identify and formulate motivations Analyse: the initial study to understand motivations Identify: follow-up study to identify concrete motivations for a set of behaviours Formulate: scenario-based requirements specification with the motivations included Instantiate the motivational framework for the set of predefined behaviours/scenarios

IBM motivational framework Methodology Revised 4/26/2018 IBM motivational framework Domain grounding Designing scenarios Evaluating scenarios

Conceptual Foundation 4/26/2018 Conceptual Foundation The Integrated Behaviour Model (IBM) Intention_to_engage = F(attitudes, norms, agency) attitudes = experience ∧ beliefs_about_outcomes norms = injunctive_norms ∧ descriptive_norms agency = perceived_control ∧ self-efficacy

IBM Feelings about behavior Behavioral beliefs Experiential attitude 4/26/2018 IBM Feelings about behavior Behavioral beliefs Experiential attitude Instrumental Attitude Others’ expectations Others’ behaviour Injunctive norm Descriptive Perceived Norm Control beliefs Efficacy beliefs Perceived control Self-efficacy Personal Agency Knowledge and skills Salience of the behaviour Intention or decision to perform the behaviour Environmental constraints Habits The Behaviour

Understanding Motivations 1/2 4/26/2018 Understanding Motivations 1/2 Semi-structured interviews 18 participants 10 from Italy (6 females, 4 males; mean age 75; 5 from rural areas, 5 from urban areas) 8 from UK (4 females, 4 males; mean age 70; 8 from urban areas) Thematic analysis of the transcripts Extrapolating all the statements relevant to IBM’s codes that describe behavioural intention (activity, attitude, norms, agency)

Understanding Motivations 2/2 4/26/2018 Understanding Motivations 2/2 Insights Attitudes Physical activites as source of serenity (mental well-being) and a way to stay fit (physical well-doing) Social experience while doing the activities Norms Family members influence the selection of an acitivity Relationships with age peers regulate the activities in practice Agency Perceive ageing as a natural process Determined, resilient and proactive (high internal locus of control) Independent active persons involved in different kinds of activities in both social and private contexts

Identifying Motivations – initial scenarios Section Description Demographics to describe the type of user Location to identify whether the user is rural or urban Lifestyle to indicate current levels of activity Gap for activity to highlight where the system could be used within the user’s life Arrival of system to explain how the system arrives with the user Recommendation the type of recommendation provided by the recommender system Basis for recommendation how the system knows what to recommend Decision how the user responds to the recommendation Implementation how the system assists in performing the recommendation Using system features how the system contributes to the experience Result what happens after the recommendation has been followed

Identifying Motivations – storyboards 1/2 4/26/2018 Hello, I am Isabella

Identifying Motivations – storyboards 2/2 Hello, I am Michael

Identifying Motivations – extensions Section Description Desire for activity to highlight potential desire for the system functionality while doing the activity Desire for social interaction to highlight potential desire for social interaction through the system Experience feelings to describe emotional responses associated with the behaviour Attitude benefits to describe beliefs about the outcomes associated with the behaviour Influential others to indicate what other people think the person should do Perception of peers to highlight person’s perception about what others (age peers) are doing Perceived control to indicate the perception of the degree to which various environmental factors influence the behaviour Self-efficacy to indicate level of confidence in the ability to perform the behaviour Facilitators to indicate facilitators to perform the behaviour Barriers to indicate barriers to perform the behaviour

4/26/2018 Conclusion Analysing, identifying and formulating motivational factors in designing for active ageing Design the experience before designing the system Future work on the frontend of the recommendation system (FriTab) Identification of users’ needs – understanding and drawing requirements Basic functionalities and design – sketching High-fidelity prototypes – refining Motivational/Usability/UX studies – assessing

InterAction Lab, University of Trento 4/26/2018 Understanding Motivations of Older People to Engage in Socio-Technical Interventions for Active Ageing Mlađan Jovanović InterAction Lab, University of Trento mladjan.jovanovic@unitn.it