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Transcript of Persuasive systems design for health - Philips Notes in Computer Science, Persuasive, Vol. 6137, pp....
11/22/15
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!OULU ADVANCED RESEARCH ON SOFTWARE AND INFORMATION SYSTEMS
Persuasive systems design for health
Harri Oinas-Kukkonen University of Oulu, Finland
@profhok
HLS-15 Conference, Eindhoven November 16, 2015
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Outline • The PSD Model • What’s up, Doc? • Lessons learned • Wrap up
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THE PSD MODEL Persuasive Systems Design Model
Oinas-Kukkonen H. & Harjumaa M. (2009) Persuasive Systems Design: Key Issues, Process Model, and System Features. Communications of the Association for Information Systems, Vol. 24, Article 28, March 2009, pp. 485-500.
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Forms of influence
Forms of influence
Persuasion Inducements
Exchanges of money, goods, or
services for actions by the person being
influenced
Coercion
Force and possibly economic sanctions
Deception
A pop-up window or a hyperlink may be
purposefully deceitful (example)
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The PSD Model
• Persuasion Postulates • Persuasion Context
– To discern opportune and/or inopportune moments for delivering the message(s)
• Persuasive Features – To implement actual SW features
Oinas-Kukkonen H. & Harjumaa M. (2009) Persuasive Systems Design: Key Issues, Process Model, and System Features. Communications of the Association for Information Systems, Vol. 24, Article 28, March 2009, pp. 485-500.
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The intent The event The strategy
Primary task support Computer-human dialogue support
Perceived system credibility
Social influence
Persuasive software features
Persuasion context
Intended outcome/change
Use, user, and technology contexts
Message, route
Persuasion postulates
Consistency (P2)
Incrementality (P3)
Usefulness and ease of use (P5)
Unobtrusiveness (P6)
Routes (P4)
Transparency (P7)
IT is never neutral (P1)
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PERSUASION POSTULATES
Oinas-Kukkonen H. & Harjumaa M. (2009) Persuasive Systems Design: Key Issues, Process Model, and System Features. Communications of the Association for Information Systems, Vol. 24, Article 28, March 2009, pp. 485-500.
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Step 1: Applies to all PS ① Information technology is never neutral ② People like their views about the world to be organized as
consistent ③ Persuasion is often incremental ④ Direct and indirect routes are key persuasion strategies ⑤ Persuasive systems should be both useful and easy to use ⑥ Persuasion through persuasive systems must always be
unobtrusive to a user’s primary tasks ⑦ Persuasion through persuasive systems should always be
transparent
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PERSUASIVE DESIGN CATEGORIES AND FEATURES
Primary task support
Dialogue support
Perceived credibility
Social influence
The intent
Intended Outcome/
Change
The event
Use, user and technology contexts
The strategy
Persuader, message,
route, bias
After understanding the postulates
PERSUASION CONTEXT
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PERSUASION CONTEXT
Oinas-Kukkonen H. & Harjumaa M. (2009) Persuasive Systems Design: Key Issues, Process Model, and System Features. Communications of the Association for Information Systems, Vol. 24, Article 28, March 2009, pp. 485-500.
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Persuasion context: The intent
• The intended Outcome/Change – O/C Design Matrix
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Persuasion context: The intent
O/C DESIGN MATRIX
C-Change B-Change A-Change
F-Outcome Forming an act of complying (F/C)
Forming a behavior (F/B)
Forming an attitude (F/A)
A-Outcome Altering an act of complying (A/C)
Altering a behavior (A/B)
Altering an attitude (A/A)
R-Outcome Reinforcing an act of complying (R/C)
Reinforcing a behavior (R/B)
Reinforcing an attitude (R/A)
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Persuasion context: The event
• Use context – Problem domain dependent features – User(s) in situ
• User context – User dependent features – User’s life situation
• Technology context – Technology dependent features
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Persuasion context: The strategy
• Persuader – Endogenous, exogenous, autogenous
• Message – One or multiple arguments and what kinds of
arguments • Route
– Direct vs. indirect route (or perhaps both) • Designer bias
– Often the empirical and/or experimental research does not reveal much about the motives behind the system under study
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PERSUASIVE FEATURES
Oinas-Kukkonen H. & Harjumaa M. (2009) Persuasive Systems Design: Key Issues, Process Model, and System Features. Communications of the Association for Information Systems, Vol. 24, Article 28, March 2009, pp. 485-500.
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Persuasive SW features
Persuasive systems design
Primary task support
Tailoring, tunneling, reduction, self-monitoring,
rehearsal, simulation, personalization
Dialogue support
Praise, rewards, reminders, suggestion, liking, similarity,
social role
Perceived credibility
Surface credibility, authority, trustworthiness, expertise, real-world feel, 3rd party
endorsements, verifiability
Social influence
Social learning, social comparison, social
facilitation, normative influence, recognition,
competition, cooperation
Mos
t of t
he fe
atur
es a
dopt
ed fr
om F
ogg
(200
3)
The goal is not to implement all features
à Choosing the right
features
Categories Features
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The applicability of the PSD model
• Design, development and evaluation of apps – Note: Even SW specifications
• Comparative evaluations of applications – From research prototypes to full-fledged commercial
apps • Research model
– Field studies, experiments, surveys – Case studies
• Systematic (and other types of) literature reviews
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WHAT’S UP, DOC? Health BC
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What’s up, Doc?
100%
90%
80%
70%
60% Behavioral patterns
50% Healthcare
40% Environmental exposure
30% Social circumstances
20% Genetic predisposition
10% (Schroeder 2007)
0%
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Tech support for BC
• Behavior Change Support Systems – Oinas-Kukkonen H. (2013) A Foundation for the Study of Behavior Change
Support Systems. Personal and ubiquitous computing, Vol. 17, No. 6, August 2013, pp. 1223-1235
– Oinas-Kukkonen H. (2010) Behavior Change Support Systems: A Research Model and Agenda. Lecture Notes in Computer Science, Persuasive, Vol. 6137, pp. 4-14, 2010, Springer-Verlag
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Need for persuasive design
• Design issues deserve more attention, as they have real implications.
• If the systems are not designed properly, the persuasive potential is not fulfilled.
• Previous research – persuasive system design has a significant impact on adherence – in boosting effective user engagement, and – keeping the users motivated in their endeavors.
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CONDUCTED RESEARCH My, my team’s, with my research collabs
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Adopting a healthier lifestyle
• Physical activity • Eating behavior • Sleep patterns • Mental health • Stress level • Link with clinical applications • Sensors and SW architectures • Ethical and societal aspects
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Physical activity • Enwald Heidi, Niemelä Raimo, Keinänen-Kiukaanniemi Sirkka, Leppäluoto Juhani, Jämsä
Timo, Herzig Karl-Heinz, Oinas-Kukkonen Harri, Huotari Maija-Leena (2012) Human information behaviour and physiological measurements as a basis to tailor health information. An explorative study in a physical activity intervention among prediabetic individuals in Northern Finland. Health Information and Libraries Journal, 29(2), 131-140
• Segerståhl Katarina & Oinas-Kukkonen Harri (2011) Designing for personal exercise monitoring employing multiple modes of delivery: Implications from a qualitative study on heart rate monitoring. International Journal of Medical Informatics, Vol. 80, Issue 12, pp. e203-e213, December 2011
• Wäljas Minna, Segerståhl Katarina, Väänänen-Vainio-Mattila Kaisa & Oinas-Kukkonen Harri (2010) Cross-Platform Service User Experience: A Field Study and an Initial Framework. In: Proceedings of the Twelfth International Conference on Human-Computer Interaction with Mobile Devices and Services (MobileHCI ’2010), Lisboa, Portugal, September 7-10, 2010, pp 219-228.
• Harjumaa Marja, Segerståhl Katarina & Oinas-Kukkonen Harri (2009) Understanding Persuasive System Functionality in Practice: a Field Trial of Polar FT60. ACM International Conference Proceeding Series, Vol. 350, Proceedings of the Fourth International Conference on Persuasive Technology.
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Eating behavior (incl. drinking, smoking) • Lehto T. & Oinas-Kukkonen H. (2015). Explaining and Predicting Perceived Effectiveness and Use Continuance
Intention of a Behavior Change Support System. Behaviour and Information Technology, Vol. 34, No. 2, pp. 176-189 • Lehto T. & Oinas-Kukkonen H. (2015) Examining the Persuasive Potential of Health Behavior Change Support
Systems. AIS Transactions on Human-Computer Interaction. Vol. 7, No. 3, September, pp. 126-140 • Lehto, T, Oinas-Kukkonen, H, Pätiälä, T & Saarelma, O (2013). Virtual Health Coaching for Consumers: A Persuasive
Systems Design Perspective. International Journal of Networking and Virtual Organisations, Vol. 13, No. 1, pp. 24-41 • Enwald H., Kortelainen T., Leppäluoto J., Keinänen-Kiukaanniemi S., Jämsä Timo, Oinas-Kukkonen Harri, Herzig
Karl-Heinz, Huotari Maija-Leena (2013) Perceptions of fear appeal and preferences for feedback in tailored health communication. An explorative study among prediabetic individuals. Information Research: an international electronic journal, Vol 18, No. 3, paper 584, September 2013
• Lehto T., Oinas-Kukkonen H. & Drozd F. (2012) Factors Affecting Perceived Persuasiveness of a Behavior Change Support System. International Conference on Information Systems (ICIS 2012), Orlando, Florida, December 16-19
• Lehto T. , Oinas-Kukkonen H., Pätiälä T. & Saarelma O. (2012) Consumers’ Perceptions of a Virtual Health Check: An Empirical Investigation. In: 20th European Conference on Information Systems, ECIS 2012 Proceedings, Paper 154.
• Drozd F., Lehto T. & Oinas-Kukkonen H. (2012) Exploring Perceived Persuasiveness of a Behavior Change Support System: A Structural Model. LNCS, 2012, Volume 7284, Persuasive Technology, pp. 157-168R
• Lehto T. & Oinas-Kukkonen H. (2011) Persuasive Features in Web-Based Alcohol and Smoking Interventions: A Systematic Review of the Literature. Journal of Medical Internet Research, 13(3), e46
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Sleep patterns • Langrial Sitwat, Oinas-Kukkonen Harri, Lappalainen Päivi & Lappalainen Raimo
(2014) Influence of persuasive reminders and virtual rehearsal on information systems for sleep deprivation. Proceedings of the Pacific Asia Conference on Information Systems, PACIS 2014 Proceedings, Paper 228, http://aisel.aisnet.org/pacis2014/228.
• Langrial Sitwat, Oinas-Kukkonen Harri & Wang Shiyuan (2012) Design of a Web-based Information System for Sleep Deprivation - A Trial Study. Communications in Computer and Information Science, 2012, Volume 313, pp. 41-51.
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Mental health • Lappalainen Päivi, Langrial Sitwat, Oinas-Kukkonen Harri, Tolvanen Asko &
Lappalainen Raimo (2015) Web-based Acceptance and Commitment Therapy for Depressive Symptoms with Minimal Support: Treatment Efficacy and Participants’ Experiences: A Randomized Controlled Trial. Behavior Modification.
• Kuonanoja Liisa, Langrial Sitwat, Lappalainen Päivi, Lappalainen Raimo & Oinas-Kukkonen Harri (2015) Treating Depression through a Behavior Change Support System without Face-to-Face Therapy. AIS Transactions on Human-Computer Interaction. Vol. 7, No. 3, September, pp. 192-210
• Langrial Sitwat, Oinas-Kukkonen Harri, Lappalainen Päivi & Lappalainen Raimo (2014) Managing Depression through a Behavior Change Support System without Face-to-Face Therapy. In: PERSUASIVE 2014, LNCS 8462, pp. 155-166.
• Langrial Sitwat, Lehto Tuomas, Oinas-Kukkonen Harri, Harjumaa Marja & Karppinen Pasi (2012) Native Mobile Applications for Personal Well-Being: A Persuasive Systems Design Evaluation. In: 16th Pacific Asia Conference on Information Systems, PACIS 2012 Proceedings. Paper 93.
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Stress level • Mian Salman, Oinas-Kukkonen Harri, Riekki Jukka (2015) Leveraging the usage of
sensors and the social web: Towards systems for socially challenging situations. Sixth Scandinavian Conference on Information Systems, August 9-12, 2015. In: SCIS 2015, LNBIP 223, pp. 44-60.
• Harjumaa Marja, Halttu Kirsi, Koistinen Kati & Oinas-Kukkonen Harri (2015) User experience of mobile coaching for stress-management to tackle prevalent complaints. Sixth Scandinavian Conference on Information Systems, August 9-12, 2015. In: SCIS 2015, LNBIP 223, pp. 152-164.
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Link with clinical systems • Enwald Heidi, Kortelainen Terttu, Leppäluoto Juhani, Keinänen-Kiukaanniemi Sirkka,
Jämsä Timo, Oinas-Kukkonen Harri, Herzig Karl-Heinz, Huotari Maija-Leena (2013) Perceptions of fear appeal and preferences for feedback in tailored health communication. An explorative study among prediabetic individuals. Information Research: an international electronic journal, Vol 18, No. 3, paper 584, September 2013
• Karppinen Pasi Lehto Tuomas, Oinas-Kukkonen Harri, Pätiälä Timo & Saarelma Osmo (2014) Using hermeneutics to uncover anomalies for non-adoption of behavior change support systems. Proceedings of the 18th Pacific Asia Conference on Information Systems, PACIS 2014 Proceedings, Paper 110.
• Karppinen P., Alahäivälä T., Jokelainen T., Keränen A.-M., Salonurmi T., & Oinas-Kukkonen H. (2014) Flow or No Flow? A Qualitative Study of Health Behavior Change Support System. Proceedings of the 47th Annual Hawaii International Conference on Systems Sciences (HICSS 2014), Waikoloa, Big Island, Hawaii, January 4-7, 2014, IEEE Computer Society Press, 3044-3053.
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Sensors and SW architectures • Kinnunen Matti, Mian Salman, Oinas-Kukkonen Harri, Riekki Jukka, Jutila Mirjami,
Ervasti Mari, Ahokangas Petri & Alasaarela Esko (2016) Wearable and mobile sensors connected to social media in human well-being applications. Telematics and Informatics. Vol. 33, Issue 1, pp. 92-101.
• Oduor Michael, Alahäivälä Tuomas & Oinas-Kukkonen Harri (2014) Persuasive software design patterns for social influence. Personal and ubiquitous computing, Vol. 18, No. 7, October 2014, pp. 1689-1704.
• Alahäivälä Tuomas, Oinas-Kukkonen Harri & Jokelainen Terhi (2013) Software Architecture Design for Health BCSS: Case Onnikka. Lecture Notes in Computer Science, 2013, Volume 7822, Persuasive Technology, pp. 3-14.
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Ethical and societal aspects • Oinas-Kukkonen Harri & Oinas-Kukkonen Henry (2013) Humanizing the Web:
Change and Social Innovation. Palgrave Macmillan, Basingstoke, UK, 248 pages • Karppinen Pasi & Oinas-Kukkonen Harri (2013) Three Approaches to Ethical
Considerations in the Design of Behavior Change Support Systems. Lecture Notes in Computer Science, 2013, Volume 7822, Persuasive Technology, pp. 87-98.
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LESSONS LEARNED Reviews, experiments, studies, surveys
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Mobile apps for wellbeing: SOCI • Mostly to share information through Facebook, Twitter, blogs,
discussion forums • Note: Social support found minimal (sic) ANG AWA HEA LIV MIM MOK MO
M MOR MYB MYC SEE T2M
Social compar.
Co-operation
Social facilitation
Normative infl.
Competition
Social learning
Recognition
Langrial et al. (2012) Native Mobile Applications for Personal Well-Being: A Persuasive Systems Design Evaluation. In: PACIS 2012 Proceedings. http://aisel.aisnet.org/pacis2012/93
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Mobile apps for wellbeing: CRED • Credibility support low (even if some features found) • Note: Weak implementations
ANG AWA HEA LIV MIM MOK MO
M MOR MYB MYC SEE T2M
Trustworthiness
Real-world feel
Expertise
Verifiability
Authority
3rd party endorsements
Surface credibility Not evaluated Langrial et al. (2012) Native Mobile Applications for Personal Well-Being: A Persuasive Systems Design Evaluation. In: PACIS 2012 Proceedings. http://aisel.aisnet.org/pacis2012/93
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Mobile apps for wellbeing: DIAL • Reminders the most common feature • Note: Dialogue support surprisingly little utilized
ANG AWA HEA LIV MIM MOK MOM
MOR MYB MYC SEE T2M
Reminders
Praise
Suggestion
Rewards
Similarity
Social role
Liking Not evaluated Langrial et al. (2012) Native Mobile Applications for Personal Well-Being: A Persuasive Systems Design Evaluation. In: PACIS 2012 Proceedings. http://aisel.aisnet.org/pacis2012/93
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Mobile apps for wellbeing: PRIM • Self-monitoring, reduction, personalization most commonly utilized • Note: Tailoring wasn’t used in any of the evaluated applications (sic)
ANG AWA HEA LIV MIM MOK MOM
MOR MYB MYC SEE T2M
Self-monitoring
Reduction
Personalization
Rehearsal
Tunneling
Simulation
Tailoring
Langrial et al. (2012) Native Mobile Applications for Personal Well-Being: A Persuasive Systems Design Evaluation. In: PACIS 2012 Proceedings. http://aisel.aisnet.org/pacis2012/93
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Persuasive feature categories (weight loss)
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Drozd et al. (2012) Exploring Perceived Persuasiveness of a Behavior Change Support System: A Structural Model. Lecture Notes in Computer Science, 2012, Volume 7284, Persuasive Technology.
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• Objective – Consumer perceptions of Virtual Health Check and
Coaching – Non-clinical web-based system for personal lifestyle and
health management • Limitation
– No measurement whether actual behavior change took place though the virtual health coaching
• Data – N=130 virtual check; N=91 adopted coaching
Adoption and use continuance of health coaching Lehto et al. (2012) Consumers’ Perceptions of a Virtual Health
Check: An Empirical Investigation. In: ECIS 2012 Proceedings, http://aisel.aisnet.org/ecis2012/154
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Adoption and use continuance of health coaching • PRIM: Negative feedback for the general and non-tailored
health-related advice – Multiple non-interoperable applications in use – Inputting the same data into several locations diminishes
primary task support • System has to fit into the regular daily lives of the users
– Cf. Unobtrusiveness Postulate • Unpredictable events
– Illness of the user – Also adapting to more mundane events such as a holiday
season or a long work trip
Lehto et al. (2012) Consumers’ Perceptions of a Virtual Health Check: An Empirical Investigation. In: ECIS 2012 Proceedings, http://aisel.aisnet.org/ecis2012/154
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• DIAL: request for reminders to keep motivated – May be strengthened, e.g. virtual rewards
• CRED: Credibility assessments rather positive – Institution-based trust
[SOCI: No social support in this app.]
Adoption and use continuance of health coaching Lehto et al. (2012) Consumers’ Perceptions of a Virtual Health
Check: An Empirical Investigation. In: ECIS 2012 Proceedings, http://aisel.aisnet.org/ecis2012/154
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• Perceived usefulness (value-for-user) important – Some respondents did not see the point of continuing
using the virtual coaching system • Tech is not the solution for everything
– Technostress, fatigue, and social overload – Enjoyment, fun – Technology-related addictions
Adoption and use continuance of health coaching Lehto et al. (2012) Consumers’ Perceptions of a Virtual Health
Check: An Empirical Investigation. In: ECIS 2012 Proceedings, http://aisel.aisnet.org/ecis2012/154
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PRIMARY TASK SUPPORT
58%
DIALOGUE SUPPORT
PERCEIVED CREDIBILITY
41%
PERCEIVED PERSUASIVENESS
71%
INTENTION TO ADOPT VIRTUAL
HEALTH COACHING 31%
GENDER !=0.76 (P<0.001)
!=0.31 (P<0.01)
!=0.64 (P<0.001)
!=0.46 (P<0.001)
!=0.52 (P<0.001)
!=-0.16 (P=0.01)
!=-0.08 (P=0.04)
!=0.19 (P=0.02)
Adoption and use continuance of health coaching Lehto, et al. (2013). Virtual Health Coaching for Consumers: A
Persuasive Systems Design Perspective. International Journal of Networking and Virtual Organisations, Vol. 13, No. 1.
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Use continuance intention and perceived effectiveness
• Theory-driven effort to empirically explain and predict users’ continuance intention towards a BCSS for weight loss
• N = 314 • Structural Equation Modelling
Lehto T. & Oinas-Kukkonen H. (2015). Explaining and Predicting Perceived Effectiveness and Use Continuance Intention of a Behavior Change Support System. Behaviour and Information Technology, Vol. 34, No. 2.
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Feature categories…
PRIMR2=0.414
DIAL
CREDR2=0.194
SOCSR2=0.483
SOID
EFFOR2=0.189
EFFER2=0.523
CONTR2=0.4600.378
0.1560.643 0.407
0.202
0.140
0.1240.346
0.178
0.426
0.4340.441
0.254
Note. All paths p<0.01; DIAL=Dialogue support; SOID=Social identification; SOCS=Social support; PRIM=Primary task support; CRED=Perceived credibility; EFFO=Perceived effort;
EFFE=Perceived effectiveness; CONT=Continuance intention
Lehto T. & Oinas-Kukkonen H. (2015). Explaining and Predicting Perceived Effectiveness and Use Continuance Intention of a Behavior Change Support System. Behaviour and Information Technology, Vol. 34, No. 2.
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… and perceived effectiveness
Note. ***p<0.01 n.s. non-significantNumbers displayed in parentheses represent
the effect sizes for total effects.
SOCS
CRED
DIAL
PRIM
EFFER2=0.534
.382***(.254)
.161***(.094)
.091 n.s.
.196***(.106)
Use frequency
.134***(.048)
Lehto T. & Oinas-Kukkonen H. (2015). Explaining and Predicting Perceived Effectiveness and Use Continuance Intention of a Behavior Change Support System. Behaviour and Information Technology, Vol. 34, No. 2.
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… and use continuance intention
Note. ***p<0.01 n.s. non-significantNumbers displayed in parentheses represent
the effect sizes for total effects.
SOCS
CRED
DIAL
PRIM
CONTR2=0.402
.209***(.104)
.038 n.s.
.218***(.088)
.206***(.093)
Use frequency
.259***(.102)
Lehto T. & Oinas-Kukkonen H. (2015). Explaining and Predicting Perceived Effectiveness and Use Continuance Intention of a Behavior Change Support System. Behaviour and Information Technology, Vol. 34, No. 2.
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Treating Depression Through a BCSS Without Face-to-Face Therapy
• People suffering from depressive symptoms • Web-based acceptance and commitment therapy (ACT) • No face-to-face contact • Participants (N = 39) • Randomly assigned to an HBCSS or a waiting list control
condition • The program comprised home assignments, online feedback
given by master’s-level students of psychology over a 7-week intervention period, and automated email-based reminders
Lappalainen et al. (2015) Web-based Acceptance and Commitment Therapy for Depressive Symptoms with Minimal Support: Treatment Efficacy and Participants’ Experiences: A RCT. Behavior Modification. Kuonanoja et al. (2015) Treating Depression through a Behavior Change Support System without Face-to-Face Therapy. AIS Transactions on Human-Computer Interaction.
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Study setting
• Standardized self-reporting measures – Beck Depression Inventory [BDI-II], – Symptom Checklist–90 [SCL-90], – Acceptance and Action Questionnaire [AAQ-2], – Five Facet Mindfulness Questionnaire [FFMQ], – Automatic Thoughts Questionnaire [ATQ], and – White Bear Suppression Inventory [WBSI]
• Pre- and post-measurement • Long-term effects examined via12-month follow-up
Lappalainen et al. (2015) Web-based Acceptance and Commitment Therapy for Depressive Symptoms with Minimal Support: Treatment Efficacy and Participants’ Experiences: A RCT. Behavior Modification. Kuonanoja et al. (2015) Treating Depression through a Behavior Change Support System without Face-to-Face Therapy. AIS Transactions on Human-Computer Interaction.
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Results
• Significant effects in favor of the HBCSS group on depression symptomatology
• The treatment effects in the HBCSS group were maintained over the 12-month follow-up period
• The HBCSS participants stated that they would be happy to recommend the same intervention to others with depressive symptoms
Lappalainen et al. (2015) Web-based Acceptance and Commitment Therapy for Depressive Symptoms with Minimal Support: Treatment Efficacy and Participants’ Experiences: A RCT. Behavior Modification. Kuonanoja et al. (2015) Treating Depression through a Behavior Change Support System without Face-to-Face Therapy. AIS Transactions on Human-Computer Interaction.
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Reminders and rehearsal
• Two groups; Both rehearsed target behavior virtually; However, only one group received e-mail reminders
• Mixed-method approach was used for analysis • Data collection was performed with semi-structured self-
reported questionnaires and post-study interviews • Results
– The severity of depression was noticeably decreased and participants’ self-confidence to manage depressive thoughts was generally increased through R&R
– The effect of reminders for task completion was less than anticipated (when the participants felt that virtual rehearsal was an effective technique for learning new behaviors)
Lappalainen et al. (2015) Web-based Acceptance and Commitment Therapy for Depressive Symptoms with Minimal Support: Treatment Efficacy and Participants’ Experiences: A RCT. Behavior Modification. Kuonanoja et al. (2015) Treating Depression through a Behavior Change Support System without Face-to-Face Therapy. AIS Transactions on Human-Computer Interaction.
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WRAP UP Future of persuasive systems design
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Humanized tech
Being part of our everyday lives opens up tremendous opportunities for influencing people’s behaviors The role of persuasive systems design will only keep growing