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PANACEA: INTELLIGENT GAMIFICATION
TECHNIQUES TO REDUCE DROP OUT
Robin De Croon
Vero Vanden Abeele & Katrien Verbert
Human-Computer Interaction (augment & eMedia)2
Pain center UZA
Human-Computer Interaction (augment & eMedia)3
Appi@Home (BeWell Innovations)
• Pain patients are asked to use Appi@Home for 10 weeks
• blood pressure
• oxygen saturation
• sleep tracker
• activity tracker
• (weight scale)
• questionnaires
 Patients only adhere in the beginning
Human-Computer Interaction (augment & eMedia)4
Context
The objective is to investigate whether the combination of motivational
design techniques and context-aware recommender system techniques can
increase the motivation of chronic patients to adhere to telemonitoring (as part
of their therapy), and hence, whether these ‘intelligent’ gamification techniques
can reduce drop out.
Human-Computer Interaction (augment & eMedia)5
General goal
The objective is to investigate whether the combination of motivational
design techniques and context-aware recommender system techniques
can increase the motivation of chronic patients to adhere to telemonitoring
(as part of their therapy), and hence, whether these ‘intelligent’ gamification
techniques can reduce drop out.
Human-Computer Interaction (augment & eMedia)6
General goal
• Set of motivational design techniques
• Analytics shell that can track gamification metrics
• Context-aware recommender system that selects gamification strategies
• Scientific model of and baseline for current drop-out rates
Human-Computer Interaction (augment & eMedia)7
Desired outcomes
 implement in existing Well@Home platform
• Fitness and health apps do not share knowledge
(De Mesmaeker et al., 2012; Lister, West, Cannon, Sax, & Brodegard, 2014; Oinas-Kukkonen & Harjumaa, 2009)
• Less known how gamification can be used within a sensitive setting
• Different user groups and personality types necessitate different techniques
(Bateman, Lowenhaupt, & Nacke, 2011; Busch et al., 2015; L. E. Nacke, Bateman, & Mandryk, 2011;
Orji, Mandryk, Vassileva, & Gerling, 2013)
• Contexts less inclined or simply unable to follow up on techniques
Human-Computer Interaction (augment & eMedia)8
Domain
Diary study
N = 18 – 24 participants
Focus group
N = 8 – 12 participants
6 – 8 patients
2 – 4 careproviders
Co-creation
session
N = 8 – 12 participants
Formative
evaluation
N = 5 – 8 participants
Summative
evaluation
N = 16 – 22 participants
Analysis phase Design phase Evaluation phase
Human-Computer Interaction (augment & eMedia)9
Methodology
Diary study
N = 18 – 24 participants
Focus group
N = 8 – 12 participants
6 – 8 patients
2 – 4 careproviders
Co-creation
session
N = 8 – 12 participants
Formative
evaluation
N = 5 – 8 participants
Summative
evaluation
N = 16 – 22 participants
Analysis phase Design phase Evaluation phase
Human-Computer Interaction (augment & eMedia)10
Methodology
• Digital diary  integrate in Appi@Home
• Patients already use platform
• Experiment with voice recording
• Four steps
• introduction
• diary study
• verification
• contextual inquiry after 2 weeks
• SMEC file submitted today 
Human-Computer Interaction (augment & eMedia)11
Diary study
Matthews, Mark, and Gavin Doherty. 2011. “In the Mood: Engaging Teenagers in Psychotherapy Using Mobile Phones.” In
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 2947–56. CHI ’11. New York, NY, USA: ACM.
Beyer, Hugh, and Karen Holtzblatt. 1997. Contextual Design: Defining Customer-Centered Systems. Elsevier.
Diary study
N = 18 – 24 participants
Focus group
N = 8 – 12 participants
6 – 8 patients
2 – 4 careproviders
Co-creation
session
N = 8 – 12 participants
Formative
evaluation
N = 5 – 8 participants
Summative
evaluation
N = 16 – 22 participants
Analysis phase Design phase Evaluation phase
Human-Computer Interaction (augment & eMedia)12
Methodology
• Anthropomorphism approach
• Introduce supercoaches
• Easier to talk about motivational design techniques
• Six steps
• introduction
• potential issues
• supercoaches
• switch roles
• gamification mechanics
• dot voting
Human-Computer Interaction (augment & eMedia)13
Focus group
Bert Vandenberghe and Karin Slegers. 2016. Anthropomorphism as a Strategy to Engage End-Users in Health Data Ideation. In
Proceedings of the 9th Nordic Conference on Human-Computer Interaction, 18.
Gamification mechanics
14 Human-Computer Interaction (augment & eMedia)
Andrzej Christopher Marczewski. 2017b. Gamification Mechanics Elements.
https://www.gamified.uk/ user-types/gamification-mechanics-elements. (2017). Accessed:
2017-8-4.
Human-Computer Interaction (augment & eMedia) 15
Focus group - Supercoaches
16 Human-Computer Interaction (augment & eMedia)
De Croon R., Verbert K., Vanden Abeele V. (2017). Anthropomorphism-based focus group protocol to select gamification mechanics.
Postive gaming workshop on gamification and games for wellbeing at CHI PLAY 2017.
Human-Computer Interaction (augment & eMedia)17
Workshop @ CHIPlay 2017
Human-Computer Interaction (augment & eMedia)18
Parallel study: motivate badminton players
Human-Computer Interaction (augment & eMedia)19
Initial plan
As planned
• Perform study as planned
• But with lower number of participants
Extra
• Implement motivational design
techniques in parallel application
• User tracking
Human-Computer Interaction (augment & eMedia)20
Backup plan
21 Human-Computer Interaction (augment & eMedia)
https://www.figma.com/file/VCbS6lmSJxSqxToS2dnGTM3n/first-sketches
Progress
• Research
• Gamification, contextual inquiry, fear avoidance, …
• Focus group + diary study
• Protocol
• Gamification mechanics
• Position paper
• User study
• Presentation @ UZA
• Observed 4 consultations @ UZA
• List with tele-monitoring actions
• Prototype
• Figma sketches
22 Human-Computer Interaction (augment & eMedia)
Planning
• October
• Contact first participants
• Submit SMEC diary study
• Update Figma sketches and implement 5 in JavaScript
• ITEA report on gamification
• November
• First focus group?
• Enable user to use Panacea@Home
• In collaboration with BeWell
23 Human-Computer Interaction (augment & eMedia)
Planning
• October
• Contact first participants
• Submit SMEC diary study
• Update Figma sketches and implement 5 in JavaScript
• ITEA report on gamification
• November
• First focus group?
• Enable user to use Panacea@Home
• In collaboration with BeWell
24 Human-Computer Interaction (augment & eMedia)
• Protocols & ethical clearance needed when working with hospital
• Pain patients are not mobile
Human-Computer Interaction (augment & eMedia)25
Lessons learned
• How to motivate (younger) people over the phone for focus group?
• How to deal with medical data access?
• Resources/papers I should know?
Human-Computer Interaction (augment & eMedia)26
My questions
27
Feedback? 
Human-Computer Interaction (augment & eMedia)
robin.decroon@cs.kuleuven.be

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Seminar Groep T - Panacea project

  • 1. PANACEA: INTELLIGENT GAMIFICATION TECHNIQUES TO REDUCE DROP OUT Robin De Croon Vero Vanden Abeele & Katrien Verbert
  • 2. Human-Computer Interaction (augment & eMedia)2 Pain center UZA
  • 3. Human-Computer Interaction (augment & eMedia)3 Appi@Home (BeWell Innovations)
  • 4. • Pain patients are asked to use Appi@Home for 10 weeks • blood pressure • oxygen saturation • sleep tracker • activity tracker • (weight scale) • questionnaires  Patients only adhere in the beginning Human-Computer Interaction (augment & eMedia)4 Context
  • 5. The objective is to investigate whether the combination of motivational design techniques and context-aware recommender system techniques can increase the motivation of chronic patients to adhere to telemonitoring (as part of their therapy), and hence, whether these ‘intelligent’ gamification techniques can reduce drop out. Human-Computer Interaction (augment & eMedia)5 General goal
  • 6. The objective is to investigate whether the combination of motivational design techniques and context-aware recommender system techniques can increase the motivation of chronic patients to adhere to telemonitoring (as part of their therapy), and hence, whether these ‘intelligent’ gamification techniques can reduce drop out. Human-Computer Interaction (augment & eMedia)6 General goal
  • 7. • Set of motivational design techniques • Analytics shell that can track gamification metrics • Context-aware recommender system that selects gamification strategies • Scientific model of and baseline for current drop-out rates Human-Computer Interaction (augment & eMedia)7 Desired outcomes  implement in existing Well@Home platform
  • 8. • Fitness and health apps do not share knowledge (De Mesmaeker et al., 2012; Lister, West, Cannon, Sax, & Brodegard, 2014; Oinas-Kukkonen & Harjumaa, 2009) • Less known how gamification can be used within a sensitive setting • Different user groups and personality types necessitate different techniques (Bateman, Lowenhaupt, & Nacke, 2011; Busch et al., 2015; L. E. Nacke, Bateman, & Mandryk, 2011; Orji, Mandryk, Vassileva, & Gerling, 2013) • Contexts less inclined or simply unable to follow up on techniques Human-Computer Interaction (augment & eMedia)8 Domain
  • 9. Diary study N = 18 – 24 participants Focus group N = 8 – 12 participants 6 – 8 patients 2 – 4 careproviders Co-creation session N = 8 – 12 participants Formative evaluation N = 5 – 8 participants Summative evaluation N = 16 – 22 participants Analysis phase Design phase Evaluation phase Human-Computer Interaction (augment & eMedia)9 Methodology
  • 10. Diary study N = 18 – 24 participants Focus group N = 8 – 12 participants 6 – 8 patients 2 – 4 careproviders Co-creation session N = 8 – 12 participants Formative evaluation N = 5 – 8 participants Summative evaluation N = 16 – 22 participants Analysis phase Design phase Evaluation phase Human-Computer Interaction (augment & eMedia)10 Methodology
  • 11. • Digital diary  integrate in Appi@Home • Patients already use platform • Experiment with voice recording • Four steps • introduction • diary study • verification • contextual inquiry after 2 weeks • SMEC file submitted today  Human-Computer Interaction (augment & eMedia)11 Diary study Matthews, Mark, and Gavin Doherty. 2011. “In the Mood: Engaging Teenagers in Psychotherapy Using Mobile Phones.” In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 2947–56. CHI ’11. New York, NY, USA: ACM. Beyer, Hugh, and Karen Holtzblatt. 1997. Contextual Design: Defining Customer-Centered Systems. Elsevier.
  • 12. Diary study N = 18 – 24 participants Focus group N = 8 – 12 participants 6 – 8 patients 2 – 4 careproviders Co-creation session N = 8 – 12 participants Formative evaluation N = 5 – 8 participants Summative evaluation N = 16 – 22 participants Analysis phase Design phase Evaluation phase Human-Computer Interaction (augment & eMedia)12 Methodology
  • 13. • Anthropomorphism approach • Introduce supercoaches • Easier to talk about motivational design techniques • Six steps • introduction • potential issues • supercoaches • switch roles • gamification mechanics • dot voting Human-Computer Interaction (augment & eMedia)13 Focus group Bert Vandenberghe and Karin Slegers. 2016. Anthropomorphism as a Strategy to Engage End-Users in Health Data Ideation. In Proceedings of the 9th Nordic Conference on Human-Computer Interaction, 18.
  • 14. Gamification mechanics 14 Human-Computer Interaction (augment & eMedia) Andrzej Christopher Marczewski. 2017b. Gamification Mechanics Elements. https://www.gamified.uk/ user-types/gamification-mechanics-elements. (2017). Accessed: 2017-8-4.
  • 16. Focus group - Supercoaches 16 Human-Computer Interaction (augment & eMedia)
  • 17. De Croon R., Verbert K., Vanden Abeele V. (2017). Anthropomorphism-based focus group protocol to select gamification mechanics. Postive gaming workshop on gamification and games for wellbeing at CHI PLAY 2017. Human-Computer Interaction (augment & eMedia)17 Workshop @ CHIPlay 2017
  • 18. Human-Computer Interaction (augment & eMedia)18 Parallel study: motivate badminton players
  • 19. Human-Computer Interaction (augment & eMedia)19 Initial plan
  • 20. As planned • Perform study as planned • But with lower number of participants Extra • Implement motivational design techniques in parallel application • User tracking Human-Computer Interaction (augment & eMedia)20 Backup plan
  • 21. 21 Human-Computer Interaction (augment & eMedia) https://www.figma.com/file/VCbS6lmSJxSqxToS2dnGTM3n/first-sketches
  • 22. Progress • Research • Gamification, contextual inquiry, fear avoidance, … • Focus group + diary study • Protocol • Gamification mechanics • Position paper • User study • Presentation @ UZA • Observed 4 consultations @ UZA • List with tele-monitoring actions • Prototype • Figma sketches 22 Human-Computer Interaction (augment & eMedia)
  • 23. Planning • October • Contact first participants • Submit SMEC diary study • Update Figma sketches and implement 5 in JavaScript • ITEA report on gamification • November • First focus group? • Enable user to use Panacea@Home • In collaboration with BeWell 23 Human-Computer Interaction (augment & eMedia)
  • 24. Planning • October • Contact first participants • Submit SMEC diary study • Update Figma sketches and implement 5 in JavaScript • ITEA report on gamification • November • First focus group? • Enable user to use Panacea@Home • In collaboration with BeWell 24 Human-Computer Interaction (augment & eMedia)
  • 25. • Protocols & ethical clearance needed when working with hospital • Pain patients are not mobile Human-Computer Interaction (augment & eMedia)25 Lessons learned
  • 26. • How to motivate (younger) people over the phone for focus group? • How to deal with medical data access? • Resources/papers I should know? Human-Computer Interaction (augment & eMedia)26 My questions
  • 27. 27 Feedback?  Human-Computer Interaction (augment & eMedia) robin.decroon@cs.kuleuven.be

Editor's Notes

  1. Explain pectus – severe pain First week, OK, afterwards
  2. (i.e. interactions of patients with the telemonitoring platform and game-elements such as leaderboards, experience points, performance graphs) as well as adherence metrics, (i.e. those user actions that can be indicative of adherence such as retention versus churn, daily active usage, session length, etc.).
  3. Contexts: e.g., boarding school sleep tracker
  4. - Heeft u moeilijkheden ervaren bij uw telemonitoringshandelingen? Zo ja, welke? - Waarom heeft u vandaag wel/niet al uw telemonitoringsensoren/toestellen kunnen gebruiken? - Wat zou uw ervaring van vandaag beter kunnen maken met betrekking tot het Appi@Home platform? - Verhinderde de pijn vandaag het gebruik van Appi@Home? - Heeft iemand u vandaag belet om uw telemonitoringshandelingen te stellen? - Is er een andere reden waarom u niet alle sensors kon gebruiken? - Welke medicatie heeft u vandaag ingenomen? - Iets anders dat u nog kwijt wilt over het gebruik van het Appi@Home platform?