Gamification of cognitive training: a crowdsourcing inspired approach for older adultsAlberto Mora, Carina González, Joan Arnedo, Alexis ÁlvarezUniversitat Oberta de CatalunyaXVII International Conference on Human Computer Interaction, Interacción’16.Salamanca, 15th September, 2016

Index

• Introduction

• Gamification: healthcare and wellness

• Gamification: crowdsourcing approaches

• Commercial solutions: analysis

• Preventive Neuro Health

• Design / Architecture

• Conclusion / Work in progress

Introduction

• Dementia, a serious concern for the most advanced word societies in the

world (Prince et al., 2013)

• Progressive syndrome

• Cognitive functions deteriorate beyond normal ageing expectations

• Primary problems:

• Memory, thinking, behaviour and the ability to perform everyday activities

• Secondary problems:

• Emotional, social behaviour and motivation

• Affectation of quality of life and independence

Introduction

• World Health Organization: 7.7 million of new cases every year

• Remoteness from drug therapies (Kueider, Krystal, & Rebok, 2014)

• Dynamic interventions: promoting training tools for stimulation

• Tasks in a monotonous way

• Possibility of gradual improvements

• Demotivation (prevention vs treatment)

• Gamification: powerful technique to engage people and lead to the

therapeutic objectives: adherence to the interventions

Gamification: healthcare and wellness

• Traditional predominance of physical activities

• An increasing relevance by academia in cognitive training and gamification

(48.76%, from 2014 to 2015. Source: Google Scholar)

• European projects:

• DOREMI: aims to design of a gamified cognitive training solution for older people by

using a User-Centered design process

• PERSSILAA: attempts to develop and validate a new service model to screen for

and prevent frailty of older adults, supporting cognitive functioning and by the use of

gamification

• Great difficulty in designing a gamified experience, particularly in healthcare

(Pereira et al., 2014)

Gamification: healthcare and wellness

• Personalization: therapeutic and motivation• Engaging to every participant through gamification is not a silver bullet for all

motivations problems of every older adult (Tondello, Wehbe, & Nacke, 2015)

• Personalization offers system-tailored contents and services to its users, tailoring

content and functionality to a particular user’s need based on a user’s

characteristics (Orji, Vassileva, y Mandryk, 2014)

• The entire gamification system should be designed to come to an end for an

individual player (Nicholson, 2015)

• In practice: “Generic” and ad-hoc designs with a PBL predominance

Crowdsourcing

• Cooperation vs competition

• Definition

• A type of participative online activity in which is proposed to a group of individuals of

varying knowledge, heterogeneity, and number, via a flexible open call, the voluntary

undertaking of a task (Estellés Arolas y González Ladrón-de-Guevara, 2012)

• Older adults, gamification and crowdsourcing:

• A gamified crowdsourcing design promote the engagement of older people (Choi,

Choi, So, Lee, & You, 2014)

• Positive outcomes in the motivation of participants by integrating gamification (Itoko,

Arita, Kobayashi, & Takagi, 2014)

• 140.000 people (Gamer motivation, Quantic Foundry)

Crowdsourcing

Analysis

• Research outcomes and commercial solutions

• Literature review -> unrecommendable issues

• Competitive environments (1)

• Direct comparisons (2)

• Absence of peer reinforcement (3)

• Silver-bullet for all motivational issues (4)

• Generic reinforcements (5)

• Ignorance of rewards (6)

• Enabling distracting elements (7)

• Missing of an involving metaphor (8)

Analysis

Preventive Neuro Health

• ICA-UOC (Gencat Industrial Doctorate Programme)

• A gamified tool which aims to prevent cognitive decline in healthy older adults

or in early stages of dementia, which does not require clinical supervision.

• 42 exercises (alpha version)

• Exercises designed by neuropsychologists (experience in cognitive

rehabilitation with GNPT tool > 3500 patients)

• Covering six cognitive function (and sub-functions)

Preventive Neuro Health

Diseño (capa de gamificación)

• Modelo

Design (gamification layer)

• Design framework (Mora, Zaharias, González, & Arnedo-Moreno, 2015)

• BDD + Lean UX

• Metaphor

• A cooperative system based on a crowdsourcing model

• Users provide individual actions of cognitive training

• +Training -> +Features

• Objectives (non-therapeutic)

• Encouraging a regular performance (create a habit)

• Promoting the best performances (put right interest in it)

• Foregrounding the social-collaborative achievements (an influencer community)

Design (gamification layer)

• User stories: expected behaviours from the user perspective (DCU) from BDD

• SDT (Ryan & Deci, 2000): Autonomy + Competence + Relatedness

• SPARC: assessing intrinsic motivations (+2)

• Autonomy: the exercises must be selectable by older adults

• Relatedness: each exercise performed has some positive impact on the

community

• Competence: ensure that older adults are able to master it effectively

• Sense: exercises make sense to older adults and are coherent with their

cognitive healthcare and well-being

• Purpose: exercises have clear objective from a neuropsychologist perspective

Design (gamification layer)

• Measurement

• Acceptance tests: objectives’ achievement:

• Objective 1 (encouraging a regular interaction): daily active users, daily challenges

passed, weekly sessions completed, training schedule updates and time of use

• Objective 2 (promoting best performances): optional exercises conducted, status

updates, rewards and records

• Objective 3 (promote relationships and cooperation): daily social interactions,

feedback, ratings, reviews and support

Design (gamification layer)

• Game-design elements, user preferences (HEXAD user type) and phases

Design (gamification layer)

• Habit forming products (Eyar, 2014):

Design (user interface)

• Mobile and multi-touch

• Simplicity: light background, dark font, relevant content featured, information

tailored to each functionality,…

• Legibility and hierarchy: bigger fonts, buttons with a largest touchable area,…

• Pattern recognition: actions presented in buttons for intuitive and quickly

identification, use of standard colour of hyperlinks,…

• Help and documentation: previous instructions to identify each block and

functionality, visual description of exercises,…

• Functional flow: interaction flows are very well-defined, reduce the elements of

choice. All the content is presented on the screen (scroll is never used)

Design (user interface)

Design (architecture)

• Technology• Django framework 1.9.4• Python3• HTML5/CSS3• ImpactJS

• Modules• Automatic scheduler• Gamification engine • Analizador de interacción• Gestor de información• Generador de ejercicios

Diseño (arquitectura)

• Automatic scheduler

• Exercise schedule: cognitive states, previous user choices and rating

• Difficulty: tutorial and historical

• Gamification engine

• Game-design elements and engagement cycle management.

• Static data (demographic data and preferences), dynamic (user interaction)

• User Interaction Tracker

• Usability and performance

• Data Manager

• Report generator

• Exercise generator

• Setting values and multimedia contents

Diseño (arquitectura)

Conclusions

• Motivational problems and background

• Gamification: healthcare and wellness

• Cooperative approaches and older adults

• Personalization: therapeutic and motivation (1st approach)

• A literature review and analysis of commercial tools (weaknesses)

• A proposal of a gamified tool which aims to prevent cognitive decline in

healthy older adults or in early stages of dementia

• A design based on a framework from DCU and Agile Methodologies

• Architecture

References

• Prince, M., Bryce, R., Albanese, E., Wimo, A., Ribeiro, W., & Ferri, C. P. (2013). The global

prevalence of dementia: A systematic review and metaanalysis. Alzheimer’s & Dementia, 9(1), 63–

75. http://doi.org/10.1016/j.jalz.2012.11.007

• Kueider, A., Krystal, B., & Rebok, G. (2014). Cognitive Training for Older Adults: What Is It and

Does It Work. Center on Aging at American Institutes for Research, 1–8

• Pereira, P., Duarte, E., Rebelo, F., & Noriega, P. (2014). A review of gamification for health-related

contexts. In Design, User Experience, and Usability (pp. 742–753). Springer International.

http://doi.org/10.1007/978-3-319-07626-3_70

• Tondello, G., Wehbe, R., & Nacke, L. (2015). Towards a Personalized Playful Digital Wellness

Assistant. In Workshop on Personalization in Serious and Persuasive Games and Gamified

Interactions. In proccedings of CHI PLAY 2015

• Orji, R., Vassileva, J., & Mandryk, R. L. (2014). Modeling the efficacy of persuasive strategies for

different gamer types in serious games for health. User Modeling and User- Adapted Interaction,

24(5), 453–498. http://doi.org/10.1007/s11257-014-9149-8

References

• Estelles Arolas, E., & González Ladrón-de-Guevara, F. (2012). Towards an integrated

crowdsourcing definition. Journal of Information Science, 38(2), 189–200.

http://doi.org/10.1177/0165551512437638

• Itoko, T., Arita, S., Kobayashi, M., & Takagi, H. (2014). Involving senior workers in crowdsourced

proofreading. In Universal Access in Human-Computer Interaction. Aging and Assistive

Environments (pp. 106–117). Springer International. http://doi.org/10.1007/978-3-319-07446-7_11

• Game generation, Quantic Foundry. http://quanticfoundry.com/2016/02/10/gamer-generation/

• Mora, A., Zaharias, P., González, C., & Arnedo-Moreno, J. (2015). FRAGGLE: a FRamework for

AGile Gamification of Learning Experiences. In Games and Learning Alliance conference (GALA

2015). To appear

• Ryan, R., & Deci, E. (2000). Self-determination theory and the facilitation of intrinsic motivation,

social development, and well-being. American Psychologist, 55, 68–78.

• Eyar, N. (2014). Hooked: How to Build Habit-Forming Products. (R. Hoover, Ed.)

amoraca@uoc.edu / @amoracarreno