Serious Games for Cognitive Training in Ambient Assisted Living Environments - A technology acceptance perspective

SERIOUS GAMES FOR
COGNITIVE TRAINING IN AMBIENT
ASSISTED LIVING ENVIRONMENTS
TECHNOLOGY ACCEPTANCE of
Jan Wittland
Philipp Brauner
Martina Ziefle
Human-Computer Interaction Center
RWTH Aachen University, Germany
philipp.brauner@rwth-aachen.de
Full Paper presentation at INTERACT 2015, 14.-18. September 2015, Bamberg, Germany:
J. Wittland, P. Brauner, M. Ziefle, Serious Games for Cognitive Training in Ambient Assisted Living Environments – A
Technology Acceptance Perspective, in: J. Abascal, S. Barbosa, M. Fetter, T. Gross, P. Palanque, M. Winckler (Eds.),
Proceedings of the 15th INTERACT 2015 Conference, LNCS Volume 9296, Springer International Publishing, 2015: pp.
453–471. doi:10.1007/978-3-319-22701-6_34.

Agenda
 Motivation
– Demographic change
– Ambient Assisted Living
 Two Serious Games for AAL
 Technology Acceptance
 Evaluation
– Research Questions
– Design, Sample
– Input Devices
– Performance
– Acceptance
 Discussion and Outlook
2015-09-16
Serious Games for Cognitive Training in AAL - A Technology Acceptance Perspective / Wittland, J., Brauner, P.,
Ziefle M. / Interact 2015, Bamberg, Germany
2

INTRODUCTION
AND MOTIVATION
Chapter 1

Motivation – Demographic change
 Demographic change
– Developed societies are aging
– Dependency ratio will double by 2050
– Number of people 75+ will triple until 2060
 Demographic challenge
– Reduce costs of social systems
 Develop assistive technology
– Support elderly and frail people
– Systems that promote staying
healthy and independent
 Ensure acceptance of these systems
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DESTATIS, 12th coordinated population projection (W1)

Future Care Lab at RWTH Aachen University
 Ambient Assisted Living Lab (originally for heart patients)
– House automation (lights, air conditioning, music, …)
– Multi touch wall and table
– Sensory Floor
– Interactive gesture lamp
– 3d Motion tracking and gesture detection
– Infrared camera
– Weight scale
 Extensive studies on technology acceptance
– Motives and barriers for usage
– Privacy & trust, usability
– Age, Gender, technology expertise,
medical conditions
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teaservideo:
http://vimeo.com/31951636

Future Care Lab Video
2015-09-16
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http://vimeo.com/31951636


Serious Games for Healthcare in
Ambient Assisted Living Environments
 Started with useful apps and service
Now: Add hedonic components
 “FitnessFarm” – Exercise Game
– Kinect-based motion tracking
– Elderly report lower pain levels and fun
strengthens independence and happiness
 “Cook It Right” – cognitive abilities
– Train remembering and planning abilities
– Early diagnosis MCI and dementia?
– Prolong cognitive decline?
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Goal: Understand user and system factors that
influence acceptance and performance in SG4HC.

How can Acceptance be measured?
 Technology Acceptance Models
 Goal: Predict use of technology or services (USE)
– Identify promoting or hindering factors
– Design, trainings, marketing, different products, …
 Predict (USE) in advance?
– Measure usage intention (INTENT)
– High correlation between (INTENTION) and (USE)
USEINTENTF..
F1
2015-09-16
8
Fi
Months…years

Technology Acceptance Research: Unified Theory
of Acceptance and Use of Technology 2 (UTAUT2)
 Intention To Use and Use governed by
– Performance Expectancy (PE)
– Effort Expectancy (EE)
– Facilitating conditions (FC)
– Social Influence (SI)
– Hedonic Motivation (HM)
– Habit (H)
– Price-Value (PV)
 Mediated by
– Age
– Gender
– Experience
2015-09-16
9
Venkatesh,Thong,Xu,ConsumerAcceptanceandUseof
InformationTechnology:ExtendingtheUnifiedTheoryof
AcceptanceandUseofTechnology,MISQuarterly.36(2012)
157–178.

Iterative development process
 User-centered and iterative design
– Personas, storyboards
– Paper prototypes
– Functional prototypes
(graphics from paper prototype)
– Participatory
 Cooking environment
– First: Remember a recipe
– Second: Combine elements to cook meal
 Turn-based
 Touch-based interaction
– Goal: Correctness and Performance
2015-09-16
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EVALUATION:
STUDY DESIGN
Chapter 2

Evaluation
Research Questions
 Preferred Input Device
– Tablet
– Table
– Wall-Sized Display
 Determinants for Performance and Usage
– Influence of Age, Gender, technology experience,
– Domain expertise, gaming frequency
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 see publication

Evaluation: Experimental Setup
 Depended Variables:
– Performance level 1…3
– Intention To Use
– UTAUT2 factors
– Device Rating
 Independent Variables:
– Gender, Age
– Need for Achievement
– Technical expertise
(self-efficacy, PEU, UF)
– Cooking expertise
(self-efficacy, PEU, UF)
Level 1 Level 2Pre Survey Level 3 Post Survey
Increasing complexity
 Sample:
– Young & Elderly
– Males/females
2015-09-16
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Multiple Recipes with varying complexity
 Different recipes as XML trees
– (root ≙ completed meals)
 Increasing complexity
– Simple (12 nodes / 11 transitions)
– Medium (23 nodes / 22 transitions)
– Hard (24 nodes / 23 transitions)
2015-09-16
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(simple – scrambled eggs)
(medium - pancake)
(hard – steak and roast potatoes)

Three interaction surfaces
 Tablet
– 18 × 28 cm2
– Wireless connection
 Table
– 47.5 × 29.9cm2
– Display embedded in table from Swedish furniture
store
 Wall
– 4.8 × 2.4m2
– rear projection, infrared cameras
2015-09-16
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Evaluation: Sample description
 64 participants
– 34 male, 30 female
– 32 younger, 32 older subjects (16-84 years)
 Age
– Lower technology expertise/self-efficacy (ρ=-.399, p<.01)
– Less inclinde towards games (ρ=-.731, p<.01)
– Higher health attitude (ρ=.323, p<.01)
– Same Need for Achievement (ρ=.04, p<.01)
 Gender1
– Influences technology expertise (ρ=-.376, p<.01)
– game frequency (ρ=-.234 p=.063 <.1)
– Same health attitude (ρ=-.079, p=.535)
– Same Need for Achievement (ρ=-.14, p>.1)
– Women higher domain expertise (ρ=.361, p>.1)
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Genderdummycoded1=male,2=female

Results: Performance
 Decreases with level’s difficulty (Wow!)
 Complex slower than Middle
(just one additional element)
 Performance decreases with
– Age (ρ=-.675, p<.01)
– Lower technical self-efficacy (ρ=-.475, p<.01)
– Lower gaming frequency (ρ=-.373, p<.01)
– Low domain expertise (ρ=.388, p<.05)
 Multiple linear regression reveals
– AGE+GAMING FREQ. (r2=.366)
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Results: Determinants for Intention to Use
User factors
 User factors
– Age marginally related to Intention to Use
r=.222 (p < .1)
– Independent of
 Gender
 Gaming frequency (!)
 Self-efficacy in interacting with technology
 Cooking self-efficacy
 Need for Achievement
 Performance!
 Usually:
– Age, gender, technical self-efficacy, and gaming freq.
 Intention To Use
2015-09-16
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Results: Determinants for Intention to Use
UTAUT2 factors
 UTAUT2 factors
– Performance Expectancy (PE)
– Effort Expectancy (EE)
– Facilitating conditions (FC)
– Social Influence (SI)
– Hedonic Motivation (HM)
– Habit (H)
– Price-Value (PV)
 Multiple linear regression reveals
– Hedonic Motivation and Habit strongest predictors for
Intention To Use (r2 = .63)
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BI ρ-Correlation
PE .499, p<.01
EE p>.1
FC p>.1
H .578, p<.01
SO .612, p<.01
PV .413, p<.01
HE .718, p<.01

Discussion and Takeaway
 Performance relates to
– Age, Gaming Experience
 Intention to Use independent of
– (Age)
– Gender, Performance and domain expertise
– Technical self-efficacy, gaming frequency
(contrary to exercise game!)
 Most crucial for adoption
– Hedonic Motivation  make games fun
– Habit  nudge people to use them, provide social or financial
incentives, role models
 Limitation:
– Short term (actual use?) and between-subj. evaluation
– No evaluation of game’s efficacy  generally disputed!
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Summary
Thank you for you attention. Questions?
 Evaluation of a
Cognitive training game in AAL environment
 Performance
– explained by age and gaming frequency
 Usage Intention
– User factors: Independent of Gender, technical
expertise, gaming frequency, cooking expertise, Need
for Achievement
– UTAUT2: Strongest predictors:
Hedonic Motivation and Habit
2015-09-16
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Contact:
Philipp Brauner
brauner@comm.rwth-aachen.de
Human-Computer Interaction Center
RWTH Aachen University
See also:. Brauner, A. Holzinger, M. Ziefle, Ubiquitous Computing at its best: Serious Exercise
Games for Older Adults in Ambient Assisted Living Environments – A Technology Acceptance
Perspective, EAI Endorsed Transactions on Serious Games. 15 (2015) 1–12. doi:10.4108/sg.1.4.e3.

 Three Devices
– Tablet (18×28cm2, wireless connection, capacitive)
– Table (47×30cm2, HDMI, capacitive)
– Wall (4.8×2.4m2, HDMI, IR cameras)
– Between-subjects design
 Results
– Overall high rating
– Unclear findings
 Wall less suitable
 Tablet imprecise (latency)?
– Even no clear preference in
within-subj. study  offer all devices
– Details in paper
Device Ratings
2015-09-16
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Similarities and differences:
Technology and cooking domain
 Domain expertise
– (SE) Self-efficacy
– (EoU) Perceived Ease of Use
– (UF) Usage Frequency
 SE, EoU, UF closely related within domain
 Both domains distinct
2015-09-16
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Cook it Right – Cognitive training in AAL
User factors, performance, and UTAUT2
2015-09-16
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Serious Games for Cognitive Training in Ambient Assisted Living Environments - A technology acceptance perspective

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